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This commit is contained in:
iven
2026-03-01 16:24:24 +08:00
commit 92e5def702
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.git
.github
.claude
.vscode
.idea
target
docs
sdk
scripts
*.md
!crates/**/*.md
LICENSE-*
CLAUDE.md
BUILD_LOG.md
.env
.env.*
*.db
*.sqlite
*.pem
*.key
Thumbs.db
.DS_Store

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# OpenFang Environment Variables
# Copy this file to .env and fill in your values.
# Only set the providers you plan to use.
# ─── LLM Provider API Keys ───────────────────────────────────────────
# Anthropic (Claude models)
# ANTHROPIC_API_KEY=sk-ant-...
# Google Gemini
# GEMINI_API_KEY=AIza...
# GOOGLE_API_KEY=AIza... # Alternative to GEMINI_API_KEY
# OpenAI
# OPENAI_API_KEY=sk-...
# Groq (fast inference)
# GROQ_API_KEY=gsk_...
# DeepSeek
# DEEPSEEK_API_KEY=sk-...
# OpenRouter (multi-provider gateway)
# OPENROUTER_API_KEY=sk-or-...
# Together AI
# TOGETHER_API_KEY=...
# Mistral AI
# MISTRAL_API_KEY=...
# Fireworks AI
# FIREWORKS_API_KEY=...
# ─── Local LLM Providers (no API key needed) ─────────────────────────
# Ollama (default: http://localhost:11434)
# OLLAMA_BASE_URL=http://localhost:11434
# vLLM (default: http://localhost:8000)
# VLLM_BASE_URL=http://localhost:8000
# LM Studio (default: http://localhost:1234)
# LMSTUDIO_BASE_URL=http://localhost:1234
# ─── Channel Tokens ──────────────────────────────────────────────────
# Telegram
# TELEGRAM_BOT_TOKEN=123456:ABC-...
# Discord
# DISCORD_BOT_TOKEN=...
# Slack
# SLACK_BOT_TOKEN=xoxb-...
# SLACK_APP_TOKEN=xapp-...
# WhatsApp (via Cloud API)
# WHATSAPP_TOKEN=...
# WHATSAPP_PHONE_ID=...
# Signal
# SIGNAL_CLI_PATH=/usr/local/bin/signal-cli
# SIGNAL_PHONE_NUMBER=+1...
# Matrix
# MATRIX_HOMESERVER=https://matrix.org
# MATRIX_ACCESS_TOKEN=...
# Email (IMAP/SMTP)
# EMAIL_IMAP_HOST=imap.gmail.com
# EMAIL_SMTP_HOST=smtp.gmail.com
# EMAIL_USERNAME=...
# EMAIL_PASSWORD=...
# ─── OpenFang Configuration ──────────────────────────────────────────
# API server bind address (default: 127.0.0.1:3000)
# OPENFANG_LISTEN=127.0.0.1:3000
# API key for HTTP authentication (leave empty for localhost-only access)
# OPENFANG_API_KEY=
# Home directory (default: ~/.openfang)
# OPENFANG_HOME=~/.openfang
# Log level (default: info)
# RUST_LOG=info
# RUST_LOG=openfang=debug # Debug OpenFang only

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github: RightNow-AI

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name: CI
on:
push:
branches: [main]
pull_request:
branches: [main]
env:
CARGO_TERM_COLOR: always
RUSTFLAGS: "-D warnings"
jobs:
# ── Rust library crates (all 3 platforms) ──────────────────────────────────
check:
name: Check / ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
with:
key: check-${{ matrix.os }}
- name: Install Tauri system deps (Linux)
if: runner.os == 'Linux'
run: |
sudo apt-get update
sudo apt-get install -y \
libwebkit2gtk-4.1-dev \
libgtk-3-dev \
libayatana-appindicator3-dev \
librsvg2-dev \
patchelf
- run: cargo check --workspace
test:
name: Test / ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
with:
key: test-${{ matrix.os }}
- name: Install Tauri system deps (Linux)
if: runner.os == 'Linux'
run: |
sudo apt-get update
sudo apt-get install -y \
libwebkit2gtk-4.1-dev \
libgtk-3-dev \
libayatana-appindicator3-dev \
librsvg2-dev \
patchelf
# Tests that need a display (Tauri) are skipped in headless CI via cfg
- run: cargo test --workspace
clippy:
name: Clippy
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
with:
components: clippy
- uses: Swatinem/rust-cache@v2
- name: Install Tauri system deps
run: |
sudo apt-get update
sudo apt-get install -y \
libwebkit2gtk-4.1-dev \
libgtk-3-dev \
libayatana-appindicator3-dev \
librsvg2-dev \
patchelf
- run: cargo clippy --workspace -- -D warnings
fmt:
name: Format
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
with:
components: rustfmt
- run: cargo fmt --check
audit:
name: Security Audit
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
- name: Install cargo-audit
run: cargo install cargo-audit --locked
- run: cargo audit
# ── Secrets scanning (prevent accidental credential commits) ──────────────
secrets:
name: Secrets Scan
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Install trufflehog
run: |
curl -sSfL https://raw.githubusercontent.com/trufflesecurity/trufflehog/main/scripts/install.sh | sh -s -- -b /usr/local/bin
- name: Scan for secrets
run: |
trufflehog filesystem . \
--no-update \
--fail \
--only-verified \
--exclude-paths=<(echo -e "target/\n.git/\nCargo.lock")
# ── Installer smoke test (verify install scripts from Vercel) ──────────────
install-smoke:
name: Install Script Smoke Test
runs-on: ubuntu-latest
steps:
- name: Fetch and syntax-check shell installer
run: |
curl -fsSL https://openfang.sh/install -o /tmp/install.sh
bash -n /tmp/install.sh
- name: Fetch and syntax-check PowerShell installer
run: |
curl -fsSL https://openfang.sh/install.ps1 -o /tmp/install.ps1
pwsh -NoProfile -Command "Get-Content /tmp/install.ps1 | Out-Null" 2>&1 || true

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name: Release
on:
push:
tags:
- "v*"
permissions:
contents: write
packages: write
env:
CARGO_TERM_COLOR: always
jobs:
# ── Tauri Desktop App (Windows + macOS + Linux) ───────────────────────────
# Produces: .msi, .exe (Windows) | .dmg, .app (macOS) | .AppImage, .deb (Linux)
# Also generates and uploads latest.json (the auto-updater manifest)
desktop:
name: Desktop / ${{ matrix.platform.name }}
strategy:
fail-fast: false
matrix:
platform:
- name: Linux x86_64
os: ubuntu-22.04
args: "--target x86_64-unknown-linux-gnu"
rust_target: x86_64-unknown-linux-gnu
- name: macOS x86_64
os: macos-latest
args: "--target x86_64-apple-darwin"
rust_target: x86_64-apple-darwin
- name: macOS ARM64
os: macos-latest
args: "--target aarch64-apple-darwin"
rust_target: aarch64-apple-darwin
- name: Windows x86_64
os: windows-latest
args: "--target x86_64-pc-windows-msvc"
rust_target: x86_64-pc-windows-msvc
- name: Windows ARM64
os: windows-latest
args: "--target aarch64-pc-windows-msvc"
rust_target: aarch64-pc-windows-msvc
runs-on: ${{ matrix.platform.os }}
steps:
- uses: actions/checkout@v4
- name: Install system deps (Linux)
if: runner.os == 'Linux'
run: |
sudo apt-get update
sudo apt-get install -y \
libwebkit2gtk-4.1-dev \
libgtk-3-dev \
libayatana-appindicator3-dev \
librsvg2-dev \
patchelf
- uses: dtolnay/rust-toolchain@stable
with:
targets: ${{ matrix.platform.rust_target }}
- uses: Swatinem/rust-cache@v2
with:
key: desktop-${{ matrix.platform.rust_target }}
- name: Import macOS signing certificate
if: runner.os == 'macOS'
env:
MAC_CERT_BASE64: ${{ secrets.MAC_CERT_BASE64 }}
MAC_CERT_PASSWORD: ${{ secrets.MAC_CERT_PASSWORD }}
run: |
echo "$MAC_CERT_BASE64" | base64 --decode > $RUNNER_TEMP/certificate.p12
KEYCHAIN_PATH=$RUNNER_TEMP/app-signing.keychain-db
KEYCHAIN_PASSWORD=$(openssl rand -base64 32)
security create-keychain -p "$KEYCHAIN_PASSWORD" "$KEYCHAIN_PATH"
security set-keychain-settings -lut 21600 "$KEYCHAIN_PATH"
security unlock-keychain -p "$KEYCHAIN_PASSWORD" "$KEYCHAIN_PATH"
security import $RUNNER_TEMP/certificate.p12 -P "$MAC_CERT_PASSWORD" \
-A -t cert -f pkcs12 -k "$KEYCHAIN_PATH"
security list-keychain -d user -s "$KEYCHAIN_PATH"
security set-key-partition-list -S apple-tool:,apple:,codesign: \
-s -k "$KEYCHAIN_PASSWORD" "$KEYCHAIN_PATH"
IDENTITY=$(security find-identity -v -p codesigning "$KEYCHAIN_PATH" | grep "Developer ID Application" | head -1 | awk -F'"' '{print $2}')
echo "Using signing identity: $IDENTITY"
echo "APPLE_SIGNING_IDENTITY=$IDENTITY" >> $GITHUB_ENV
rm -f $RUNNER_TEMP/certificate.p12
- name: Build and bundle Tauri desktop app
uses: tauri-apps/tauri-action@v0
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
TAURI_SIGNING_PRIVATE_KEY_PASSWORD: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY_PASSWORD }}
APPLE_SIGNING_IDENTITY: ${{ env.APPLE_SIGNING_IDENTITY }}
APPLE_ID: ${{ secrets.MAC_NOTARIZE_APPLE_ID }}
APPLE_PASSWORD: ${{ secrets.MAC_NOTARIZE_PASSWORD }}
APPLE_TEAM_ID: ${{ secrets.MAC_NOTARIZE_TEAM_ID }}
with:
tagName: ${{ github.ref_name }}
releaseName: "OpenFang ${{ github.ref_name }}"
releaseBody: |
## What's New
See the [CHANGELOG](https://github.com/RightNow-AI/openfang/blob/main/CHANGELOG.md) for full details.
## Installation
**Desktop App** — Download the installer for your platform below.
**CLI (Linux/macOS)**:
```bash
curl -sSf https://openfang.sh | sh
```
**Docker**:
```bash
docker pull ghcr.io/rightnow-ai/openfang:latest
```
**Coming from OpenClaw?**
```bash
openfang migrate --from openclaw
```
releaseDraft: false
prerelease: false
includeUpdaterJson: true
projectPath: crates/openfang-desktop
args: ${{ matrix.platform.args }}
# ── CLI Binary (5 platforms) ──────────────────────────────────────────────
cli:
name: CLI / ${{ matrix.target }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
include:
- target: x86_64-unknown-linux-gnu
os: ubuntu-22.04
archive: tar.gz
- target: aarch64-unknown-linux-gnu
os: ubuntu-22.04
archive: tar.gz
- target: x86_64-apple-darwin
os: macos-latest
archive: tar.gz
- target: aarch64-apple-darwin
os: macos-latest
archive: tar.gz
- target: x86_64-pc-windows-msvc
os: windows-latest
archive: zip
- target: aarch64-pc-windows-msvc
os: windows-latest
archive: zip
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
with:
targets: ${{ matrix.target }}
- name: Install build deps (Linux)
if: runner.os == 'Linux'
run: sudo apt-get update && sudo apt-get install -y pkg-config libssl-dev
- name: Install cross (Linux aarch64)
if: matrix.target == 'aarch64-unknown-linux-gnu'
run: cargo install cross --locked
- uses: Swatinem/rust-cache@v2
with:
key: cli-${{ matrix.target }}
- name: Build CLI (cross)
if: matrix.target == 'aarch64-unknown-linux-gnu'
run: cross build --release --target ${{ matrix.target }} --bin openfang
- name: Build CLI
if: matrix.target != 'aarch64-unknown-linux-gnu'
run: cargo build --release --target ${{ matrix.target }} --bin openfang
- name: Package (Unix)
if: matrix.archive == 'tar.gz'
run: |
cd target/${{ matrix.target }}/release
tar czf ../../../openfang-${{ matrix.target }}.tar.gz openfang
cd ../../..
sha256sum openfang-${{ matrix.target }}.tar.gz > openfang-${{ matrix.target }}.tar.gz.sha256
- name: Package (Windows)
if: matrix.archive == 'zip'
shell: pwsh
run: |
Compress-Archive -Path "target/${{ matrix.target }}/release/openfang.exe" -DestinationPath "openfang-${{ matrix.target }}.zip"
$hash = (Get-FileHash "openfang-${{ matrix.target }}.zip" -Algorithm SHA256).Hash.ToLower()
"$hash openfang-${{ matrix.target }}.zip" | Out-File -Encoding ASCII "openfang-${{ matrix.target }}.zip.sha256"
- name: Upload to GitHub Release
uses: softprops/action-gh-release@v2
with:
files: openfang-${{ matrix.target }}.*
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# ── Docker (linux/amd64 + linux/arm64) ────────────────────────────────────
docker:
name: Docker Image
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Log in to GHCR
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Set up QEMU (for arm64 emulation)
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Extract version
id: version
run: echo "version=${GITHUB_REF#refs/tags/v}" >> "$GITHUB_OUTPUT"
- name: Build and push (multi-arch)
uses: docker/build-push-action@v6
with:
context: .
push: true
platforms: linux/amd64,linux/arm64
tags: |
ghcr.io/rightnow-ai/openfang:latest
ghcr.io/rightnow-ai/openfang:${{ steps.version.outputs.version }}
cache-from: type=gha
cache-to: type=gha,mode=max

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# Build
/target
**/*.rs.bk
*.pdb
# Environment & secrets
.env
.env.*
!.env.example
# Database
*.db
*.db-shm
*.db-wal
*.sqlite
*.sqlite3
# User config (may contain API keys)
config.toml
# Certificates & keys
*.pem
*.key
*.cert
*.p12
*.pfx
# Runtime artifacts
collector_hand_state.json
collector_knowledge_base.json
predictions_database.json
prediction_report_*.md
BUILD_LOG.md
# OS
.DS_Store
Thumbs.db
# IDE & tools
.idea/
.vscode/
.claude/
*.swp
*.swo
*~

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# Changelog
All notable changes to OpenFang will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.1.0] - 2026-02-24
### Added
#### Core Platform
- 15-crate Rust workspace: types, memory, runtime, kernel, api, channels, wire, cli, migrate, skills, hands, extensions, desktop, xtask
- Agent lifecycle management: spawn, list, kill, clone, mode switching (Full/Assist/Observe)
- SQLite-backed memory substrate with structured KV, semantic recall, vector embeddings
- 41 built-in tools (filesystem, web, shell, browser, scheduling, collaboration, image analysis, inter-agent, TTS, media)
- WASM sandbox with dual metering (fuel + epoch interruption with watchdog thread)
- Workflow engine with pipelines, fan-out parallelism, conditional steps, loops, and variable expansion
- Visual workflow builder with drag-and-drop node graph, 7 node types, and TOML export
- Trigger system with event pattern matching, content filters, and fire limits
- Event bus with publish/subscribe and correlation IDs
- 7 Hands packages for autonomous agent actions
#### LLM Support
- 3 native LLM drivers: Anthropic, Google Gemini, OpenAI-compatible
- 27 providers: Anthropic, Gemini, OpenAI, Groq, OpenRouter, DeepSeek, Together, Mistral, Fireworks, Cohere, Perplexity, xAI, AI21, Cerebras, SambaNova, Hugging Face, Replicate, Ollama, vLLM, LM Studio, and more
- Model catalog with 130+ built-in models, 23 aliases, tier classification
- Intelligent model routing with task complexity scoring
- Fallback driver for automatic failover between providers
- Cost estimation and metering engine with per-model pricing
- Streaming support (SSE) across all drivers
#### Token Management & Context
- Token-aware session compaction (chars/4 heuristic, triggers at 70% context capacity)
- In-loop emergency trimming at 70%/90% thresholds with summary injection
- Tool profile filtering (cuts default 41 tools to 4-10 for chat agents, saving 15-20K tokens)
- Context budget allocation for system prompt, tools, history, and response
- MAX_TOOL_RESULT_CHARS reduced from 50K to 15K to prevent tool result bloat
- Default token quota raised from 100K to 1M per hour
#### Security
- Capability-based access control with privilege escalation prevention
- Path traversal protection in all file tools
- SSRF protection blocking private IPs and cloud metadata endpoints
- Ed25519 signed agent manifests
- Merkle hash chain audit trail with tamper detection
- Information flow taint tracking
- HMAC-SHA256 mutual authentication for peer wire protocol
- API key authentication with Bearer token
- GCRA rate limiter with cost-aware token buckets
- Security headers middleware (CSP, X-Frame-Options, HSTS)
- Secret zeroization on all API key fields
- Subprocess environment isolation
- Health endpoint redaction (public minimal, auth full)
- Loop guard with SHA256-based detection and circuit breaker thresholds
- Session repair (validates and fixes orphaned tool results, empty messages)
#### Channels
- 40 channel adapters: Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, Teams, Mattermost, Google Chat, Webex, Feishu/Lark, LINE, Viber, Facebook Messenger, Mastodon, Bluesky, Reddit, LinkedIn, Twitch, IRC, XMPP, and 18 more
- Unified bridge with agent routing, command handling, message splitting
- Per-channel user filtering and RBAC enforcement
- Graceful shutdown, exponential backoff, secret zeroization on all adapters
#### API
- 100+ REST/WS/SSE API endpoints (axum 0.8)
- WebSocket real-time streaming with per-agent connections
- OpenAI-compatible `/v1/chat/completions` API (streaming SSE + non-streaming)
- OpenAI-compatible `/v1/models` endpoint
- WebChat embedded UI with Alpine.js
- Google A2A protocol support (agent card, task send/get/cancel)
- Prometheus text-format `/api/metrics` endpoint for monitoring
- Multi-session management: list, create, switch, label sessions per agent
- Usage analytics: summary, by-model, daily breakdown
- Config hot-reload via polling (30-second interval, no restart required)
#### Web UI
- Chat message search with Ctrl+F, real-time filtering, text highlighting
- Voice input with hold-to-record mic button (WebM/Opus codec)
- TTS audio playback inline in tool cards
- Browser screenshot rendering in chat (inline images)
- Canvas rendering with iframe sandbox and CSP support
- Session switcher dropdown in chat header
- 6-step first-run setup wizard with provider API key help (12 providers)
- Skill marketplace with 4 tabs (Installed, ClawHub, MCP Servers, Quick Start)
- Copy-to-clipboard on messages, message timestamps
- Visual workflow builder with drag-and-drop canvas
#### Client SDKs
- JavaScript SDK (`@openfang/sdk`): full REST API client with streaming, TypeScript declarations
- Python client SDK (`openfang_client`): zero-dependency stdlib client with SSE streaming
- Python agent SDK (`openfang_sdk`): decorator-based framework for writing Python agents
- Usage examples for both languages (basic + streaming)
#### CLI
- 14+ subcommands: init, start, agent, workflow, trigger, migrate, skill, channel, config, chat, status, doctor, dashboard, mcp
- Daemon auto-detection via PID file
- Shell completion generation (bash, zsh, fish, PowerShell)
- MCP server mode for IDE integration
#### Skills Ecosystem
- 60 bundled skills across 14 categories
- Skill registry with TOML manifests
- 4 runtimes: Python, Node.js, WASM, PromptOnly
- FangHub marketplace with search/install
- ClawHub client for OpenClaw skill compatibility
- SKILL.md parser with auto-conversion
- SHA256 checksum verification
- Prompt injection scanning on skill content
#### Desktop App
- Tauri 2.0 native desktop app
- System tray with status and quick actions
- Single-instance enforcement
- Hide-to-tray on close
- Updated CSP for media, frame, and blob sources
#### Session Management
- LLM-based session compaction with token-aware triggers
- Multi-session per agent with named labels
- Session switching via API and UI
- Cross-channel canonical sessions
- Extended chat commands: `/new`, `/compact`, `/model`, `/stop`, `/usage`, `/think`
#### Image Support
- `ContentBlock::Image` with base64 inline data
- Media type validation (png, jpeg, gif, webp only)
- 5MB size limit enforcement
- Mapped to all 3 native LLM drivers
#### Usage Tracking
- Per-response cost estimation with model-aware pricing
- Usage footer in WebSocket responses and WebChat UI
- Usage events persisted to SQLite
- Quota enforcement with hourly windows
#### Interoperability
- OpenClaw migration engine (YAML/JSON5 to TOML)
- MCP client (JSON-RPC 2.0 over stdio/SSE, tool namespacing)
- MCP server (exposes OpenFang tools via MCP protocol)
- A2A protocol client and server
- Tool name compatibility mappings (21 OpenClaw tool names)
#### Infrastructure
- Multi-stage Dockerfile (debian:bookworm-slim runtime)
- docker-compose.yml with volume persistence
- GitHub Actions CI (check, test, clippy, format)
- GitHub Actions release (multi-platform, GHCR push, SHA256 checksums)
- Cross-platform install script (curl/irm one-liner)
- systemd service file for Linux deployment
#### Multi-User
- RBAC with Owner/Admin/User/Viewer roles
- Channel identity resolution
- Per-user authorization checks
- Device pairing and approval system
#### Production Readiness
- 1731+ tests across 15 crates, 0 failures
- Cross-platform support (Linux, macOS, Windows)
- Graceful shutdown with signal handling (SIGINT/SIGTERM on Unix, Ctrl+C on Windows)
- Daemon PID file with stale process detection
- Release profile with LTO, single codegen unit, symbol stripping
- Prometheus metrics for monitoring
- Config hot-reload without restart
[0.1.0]: https://github.com/RightNow-AI/openfang/releases/tag/v0.1.0

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# OpenFang — Agent Instructions
## Project Overview
OpenFang is an open-source Agent Operating System written in Rust (14 crates).
- Config: `~/.openfang/config.toml`
- Default API: `http://127.0.0.1:4200`
- CLI binary: `target/release/openfang.exe` (or `target/debug/openfang.exe`)
---
## Architecture Overview
### Crate Structure (14 crates)
```
openfang-types # 基础类型 (零依赖，被所有 crate 使用)
openfang-memory # 存储层 (SQLite + 向量 + 知识图谱)
openfang-runtime # Agent 运行时 (LLM 驱动 + 工具执行 + WASM)
openfang-kernel # 核心协调器 (Registry + Scheduler + EventBus)
openfang-api # HTTP 服务 (Axum + WebSocket + SSE)
openfang-wire # P2P 协议 (OFP + HMAC 认证)
openfang-channels # 消息渠道 (40+ 适配器)
openfang-skills # 技能系统 (4 运行时 + 60 技能)
openfang-hands # 自主能力包 (7 预构建 Agent)
openfang-extensions # 集成系统 (25+ MCP 模板)
openfang-cli # 命令行 (14+ 子命令)
openfang-desktop # 桌面应用 (Tauri 2.0)
openfang-migrate # 迁移工具 (OpenClaw 导入)
```
### Dependency Rules
1. `openfang-types` 不能依赖任何内部 crate
2. `openfang-kernel` 依赖 `openfang-runtime`, `openfang-memory`
3. `openfang-api` 依赖 `openfang-kernel`
4. **禁止循环依赖** - 使用 `KernelHandle` trait 解决 runtime ↔ kernel 循环
### Key Design Patterns
- **KernelHandle Trait**: 解决 runtime ↔ kernel 循环依赖
- **Plugin Architecture**: Skills/Hands/Extensions 可扩展
- **Event-Driven**: EventBus 发布订阅模式
- **Dual Persistence**: 内存 (DashMap) + SQLite 双写
---
## Build & Verify Workflow
After every feature implementation, run ALL THREE checks:
```bash
cargo build --workspace --lib # Must compile (use --lib if exe is locked)
cargo test --workspace # All tests must pass (currently 1744+)
cargo clippy --workspace --all-targets -- -D warnings # Zero warnings
```
---
## MANDATORY: Live Integration Testing
**After implementing any new endpoint, feature, or wiring change, you MUST run live integration tests.** Unit tests alone are not enough — they can pass while the feature is actually dead code.
### Live Test Checklist
- [ ] Route registered in `server.rs` router
- [ ] Handler implemented in `routes.rs`
- [ ] GET returns real data (not empty/null)
- [ ] POST/PUT persists data (read back to verify)
- [ ] LLM integration works (real API call)
- [ ] Side effects tracked (metering/budget)
- [ ] Dashboard UI shows new components
### Quick Integration Test Script
```bash
# Stop any running daemon
tasklist | grep -i openfang && taskkill //PID <pid> //F
sleep 3
# Build and start
cargo build --release -p openfang-cli
GROQ_API_KEY=<key> target/release/openfang.exe start &
sleep 6
# Verify health
curl -s http://127.0.0.1:4200/api/health
# Test your new endpoint
curl -s http://127.0.0.1:4200/api/<your-endpoint>
# Cleanup
taskkill //PID <pid> //F
```
---
## Persistence Rules (CRITICAL)
### Rule 1: Dual Write Pattern
所有 Agent 修改操作必须同时更新:
1. **内存**: `registry.xxx()` 更新 DashMap
2. **SQLite**: `memory.save_agent(&entry)` 持久化
```rust
// ✅ 正确: Kernel 层包装方法
pub fn set_agent_mode(&self, agent_id: AgentId, mode: AgentMode) -> KernelResult<()> {
self.registry.set_mode(agent_id, mode)?; // 内存
if let Some(entry) = self.registry.get(agent_id) {
let _ = self.memory.save_agent(&entry); // SQLite
}
Ok(())
}
// ❌ 错误: 直接调用 registry (不持久化)
state.kernel.registry.set_mode(agent_id, mode)
```
### Rule 2: 使用 Kernel 包装方法
在 API 层 (`routes.rs`) 始终调用 kernel 方法，不要直接调用 registry:
| ❌ 错误调用 | ✅ 正确调用 |
|------------|------------|
| `registry.set_mode()` | `kernel.set_agent_mode()` |
| `registry.set_state()` | `kernel.set_agent_state()` |
| `registry.update_identity()` | `kernel.update_agent_identity()` |
| `registry.update_name()` | `kernel.update_agent_name()` |
| `registry.update_description()` | `kernel.update_agent_description()` |
### Rule 3: 已持久化的操作
以下操作已正确实现持久化，可直接使用:
- `kernel.update_agent_model()`
- `kernel.update_agent_system_prompt()`
- `kernel.set_agent_skills()`
- `kernel.set_agent_mcp_servers()`
- `kernel.kill_agent()` (调用 `memory.remove_agent()`)
---
## API Development Rules
### Rule 1: Route Registration
新路由必须在两处注册:
1. `server.rs` - 添加到 router
2. `routes.rs` - 实现 handler 函数
```rust
// server.rs
.route("/api/agents/{id}/custom", axum::routing::get(routes::get_custom).put(routes::set_custom))
// routes.rs
pub async fn get_custom(...) -> impl IntoResponse { ... }
pub async fn set_custom(...) -> impl IntoResponse { ... }
```
### Rule 2: AppState Access
```rust
// AppState 结构
pub struct AppState {
pub kernel: Arc<OpenFangKernel>,
pub started_at: Instant,
pub peer_registry: Option<Arc<PeerRegistry>>, // 注意: Option<Arc<...>>
pub bridge_manager: tokio::sync::Mutex<Option<BridgeManager>>,
pub channels_config: tokio::sync::RwLock<ChannelsConfig>,
pub shutdown_notify: Arc<tokio::sync::Notify>,
}
```
### Rule 3: Error Response Format
```rust
// 统一错误响应格式
(StatusCode::NOT_FOUND, Json(serde_json::json!({"error": "Agent not found"})))
(StatusCode::BAD_REQUEST, Json(serde_json::json!({"error": "Invalid input"})))
(StatusCode::CONFLICT, Json(serde_json::json!({"error": "Name already exists"})))
```
### Rule 4: Success Response Format
```rust
// 统一成功响应格式
(StatusCode::OK, Json(serde_json::json!({"status": "ok", "agent_id": id})))
(StatusCode::CREATED, Json(serde_json::json!({"id": new_id, "name": name})))
```
---
## Config & Types Rules
### Rule 1: New Config Fields
添加新配置字段需要:
1. 在 struct 中添加字段
2. 添加 `#[serde(default)]`
3. 在 `Default` impl 中添加默认值
4. 确保 `Serialize + Deserialize` derived
```rust
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KernelConfig {
// ... existing fields ...
#[serde(default)]
pub new_field: String, // 必须有 #[serde(default)]
}
impl Default for KernelConfig {
fn default() -> Self {
Self {
// ... existing defaults ...
new_field: String::new(), // 必须在 Default 中
}
}
}
```
### Rule 2: Type Definitions
新类型定义放在正确的 crate:
- **共享类型**: `openfang-types/`
- **API 特有**: `openfang-api/src/`
- **Kernel 特有**: `openfang-kernel/src/`
---
## Security Rules
### 16-Layer Security Model
1. Capability-based access control
2. Path traversal protection
3. SSRF protection (私有 IP 阻断)
4. Ed25519 signed manifests
5. Merkle hash chain audit
6. Information flow taint tracking
7. HMAC-SHA256 mutual auth
8. API key Bearer auth
9. GCRA rate limiter
10. Security headers (CSP/HSTS/X-Frame-Options)
11. Secret zeroization
12. Subprocess environment isolation
13. Health endpoint redaction
14. Loop guard with SHA256 detection
15. Session repair
16. Circuit breaker thresholds
### Security Checklist for New Features
- [ ] 输入验证 (sanitize user input)
- [ ] 权限检查 (capability-based)
- [ ] 路径安全 (no path traversal)
- [ ] SSRF 防护 (block private IPs)
- [ ] 敏感信息脱敏 (logs, health endpoint)
---
## Common Gotchas
### Build Issues
| 问题 | 解决方案 |
|------|----------|
| `openfang.exe` locked | 使用 `--lib` flag 或 kill daemon |
| cargo not found | 检查 PATH 环境变量 |
| clippy warnings | 所有 warning 必须修复 (`-D warnings`) |
### Type Mismatches
| 问题 | 解决方案 |
|------|----------|
| `PeerRegistry` 类型 | kernel: `Option<PeerRegistry>`, AppState: `Option<Arc<PeerRegistry>>` |
| `AgentLoopResult.response` | 不是 `.response_text` |
| UUID parsing | 使用 `.parse::<AgentId>()` |
### Windows-Specific
| 问题 | 解决方案 |
|------|----------|
| taskkill syntax | `taskkill //PID <pid> //F` (double slashes) |
| Path separators | 使用 `/` 或 `std::path::PathBuf` |
| Sleep command | `sleep` 在 Git Bash/MSYS2 中可用 |
### CLI Commands
- 启动守护进程: `openfang start` (不是 `daemon`)
- 停止守护进程: `taskkill //PID <pid> //F`
---
## Frontend Rules (Alpine.js SPA)
### File Locations
- HTML: `crates/openfang-api/static/index_body.html`
- JS: `crates/openfang-api/static/js/`
- CSS: `crates/openfang-api/static/css/`
### Adding New UI Components
1. 在 `index_body.html` 添加 HTML 结构
2. 在对应的 JS 文件中添加 Alpine.js data/methods
3. 在 `api.js` 中添加 API 调用方法
### Alpine.js Pattern
```javascript
// 在页面组件中
function myPage() {
return {
data: [],
loading: false,
async loadData() {
this.loading = true;
try {
this.data = await OpenFangAPI.getData();
} finally {
this.loading = false;
}
},
init() {
this.loadData();
}
}
}
```
---
## Testing Rules
### Test Categories
1. **Unit Tests**: `#[cfg(test)] mod tests { ... }` 在各模块内
2. **Integration Tests**: `tests/` 目录
3. **Live Tests**: 运行 daemon 后 curl 测试
### Test Requirements
- 所有新功能必须有测试
- 测试覆盖率目标: 90%+
- 测试名称: `test_<功能>_<场景>`
### Test Pattern
```rust
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_feature_success() {
// Arrange
let store = setup();
// Act
let result = store.do_something();
// Assert
assert!(result.is_ok());
}
#[test]
fn test_feature_error_case() {
// Test error handling
}
}
```
---
## LLM Provider Support
### Supported Providers (30+)
- Anthropic (Claude)
- OpenAI (GPT)
- Google (Gemini)
- Groq, OpenRouter, DeepSeek, Together, Mistral, Fireworks
- Ollama, vLLM, LM Studio (local)
- Perplexity, Cohere, AI21, Cerebras, SambaNova
- HuggingFace, xAI, Replicate
- GitHub Copilot, Codex, Claude Code CLI
- 中国提供商: 智谱 GLM, 百炼, Moonshot, Qwen, Minimax, 千帆
### Adding New Provider
1. 在 `openfang-types/src/model_catalog.rs` 添加 BASE_URL 常量
2. 在 `openfang-runtime/src/model_catalog.rs` 添加模型和提供商信息
3. 在 `openfang-runtime/src/drivers/mod.rs` 添加 `provider_defaults()` 条目
4. 添加测试用例
---
## Code Style Guidelines
### Rust Conventions
- 使用 `use` 导入，避免完整路径
- 错误处理使用 `Result<T, E>` 和 `?` 操作符
- 使用 `tracing` crate 进行日志记录
- 异步代码使用 `tokio` 运行时
### Naming Conventions
- 函数/变量: `snake_case`
- 类型/Trait: `PascalCase`
- 常量: `SCREAMING_SNAKE_CASE`
- 模块: `snake_case`
### Documentation
- 公共 API 必须有文档注释 (`///`)
- 复杂逻辑必须有注释说明
- 使用 `//!` 作为模块级文档
---
## Key Files Quick Reference
| 文件 | 用途 |
|------|------|
| `crates/openfang-kernel/src/kernel.rs` | 核心协调器，所有子系统的入口 |
| `crates/openfang-kernel/src/registry.rs` | Agent 内存注册表 (DashMap) |
| `crates/openfang-memory/src/structured.rs` | Agent SQLite 持久化 |
| `crates/openfang-api/src/server.rs` | HTTP 路由注册 |
| `crates/openfang-api/src/routes.rs` | HTTP 处理函数 |
| `crates/openfang-api/src/ws.rs` | WebSocket 处理 |
| `crates/openfang-runtime/src/drivers/mod.rs` | LLM 提供商驱动 |
| `crates/openfang-types/src/model_catalog.rs` | 模型/提供商常量 |
---
## Current Date
Today's date is 2026-03-01.

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# Contributing to OpenFang
Thank you for your interest in contributing to OpenFang. This guide covers everything you need to get started, from setting up your development environment to submitting pull requests.
## Table of Contents
- [Development Environment](#development-environment)
- [Building and Testing](#building-and-testing)
- [Code Style](#code-style)
- [Architecture Overview](#architecture-overview)
- [How to Add a New Agent Template](#how-to-add-a-new-agent-template)
- [How to Add a New Channel Adapter](#how-to-add-a-new-channel-adapter)
- [How to Add a New Tool](#how-to-add-a-new-tool)
- [Pull Request Process](#pull-request-process)
- [Code of Conduct](#code-of-conduct)
---
## Development Environment
### Prerequisites
- **Rust 1.75+** (install via [rustup](https://rustup.rs/))
- **Git**
- **Python 3.8+** (optional, for Python runtime and skills)
- A supported LLM API key (Anthropic, OpenAI, Groq, etc.) for end-to-end testing
### Clone and Build
```bash
git clone https://github.com/RightNow-AI/openfang.git
cd openfang
cargo build
```
The first build takes a few minutes because it compiles SQLite (bundled) and Wasmtime. Subsequent builds are incremental.
### Environment Variables
For running integration tests that hit a real LLM, set at least one provider key:
```bash
export GROQ_API_KEY=gsk_... # Recommended for fast, free-tier testing
export ANTHROPIC_API_KEY=sk-ant-... # For Anthropic-specific tests
```
Tests that require a real LLM key will skip gracefully if the env var is absent.
---
## Building and Testing
### Build the Entire Workspace
```bash
cargo build --workspace
```
### Run All Tests
```bash
cargo test --workspace
```
The test suite is currently 1,744+ tests. All must pass before merging.
### Run Tests for a Single Crate
```bash
cargo test -p openfang-kernel
cargo test -p openfang-runtime
cargo test -p openfang-memory
```
### Check for Clippy Warnings
```bash
cargo clippy --workspace --all-targets -- -D warnings
```
The CI pipeline enforces zero clippy warnings.
### Format Code
```bash
cargo fmt --all
```
Always run `cargo fmt` before committing. CI will reject unformatted code.
### Run the Doctor Check
After building, verify your local setup:
```bash
cargo run -- doctor
```
---
## Code Style
- **Formatting**: Use `rustfmt` with default settings. Run `cargo fmt --all` before every commit.
- **Linting**: `cargo clippy --workspace -- -D warnings` must pass with zero warnings.
- **Documentation**: All public types and functions must have doc comments (`///`).
- **Error Handling**: Use `thiserror` for error types. Avoid `unwrap()` in library code; prefer `?` propagation.
- **Naming**:
- Types: `PascalCase` (e.g., `OpenFangKernel`, `AgentManifest`)
- Functions/methods: `snake_case`
- Constants: `SCREAMING_SNAKE_CASE`
- Crate names: `openfang-{name}` (kebab-case)
- **Dependencies**: Workspace dependencies are declared in the root `Cargo.toml`. Prefer reusing workspace deps over adding new ones. If you need a new dependency, justify it in the PR.
- **Testing**: Every new feature must include tests. Use `tempfile::TempDir` for filesystem isolation and random port binding for network tests.
- **Serde**: All config structs use `#[serde(default)]` for forward compatibility with partial TOML.
---
## Architecture Overview
OpenFang is organized as a Cargo workspace with 14 crates:
| Crate | Role |
|-------|------|
| `openfang-types` | Shared type definitions, taint tracking, manifest signing (Ed25519), model catalog, MCP/A2A config types |
| `openfang-memory` | SQLite-backed memory substrate with vector embeddings, usage tracking, canonical sessions, JSONL mirroring |
| `openfang-runtime` | Agent loop, 3 LLM drivers (Anthropic/Gemini/OpenAI-compat), 38 built-in tools, WASM sandbox, MCP client/server, A2A protocol |
| `openfang-hands` | Hands system (curated autonomous capability packages), 7 bundled hands |
| `openfang-extensions` | Integration registry (25 bundled MCP templates), AES-256-GCM credential vault, OAuth2 PKCE |
| `openfang-kernel` | Assembles all subsystems: workflow engine, RBAC auth, heartbeat monitor, cron scheduler, config hot-reload |
| `openfang-api` | REST/WS/SSE API (Axum 0.8), 76 endpoints, 14-page SPA dashboard, OpenAI-compatible `/v1/chat/completions` |
| `openfang-channels` | 40 channel adapters (Telegram, Discord, Slack, WhatsApp, and 36 more), formatter, rate limiter |
| `openfang-wire` | OFP (OpenFang Protocol): TCP P2P networking with HMAC-SHA256 mutual authentication |
| `openfang-cli` | Clap CLI with daemon auto-detect (HTTP mode vs. in-process fallback), MCP server |
| `openfang-migrate` | Migration engine for importing from OpenClaw (and future frameworks) |
| `openfang-skills` | Skill system: 60 bundled skills, FangHub marketplace, OpenClaw compatibility, prompt injection scanning |
| `openfang-desktop` | Tauri 2.0 native desktop app (WebView + system tray + single-instance + notifications) |
| `xtask` | Build automation tasks |
### Key Architectural Patterns
- **`KernelHandle` trait**: Defined in `openfang-runtime`, implemented on `OpenFangKernel` in `openfang-kernel`. This avoids circular crate dependencies while enabling inter-agent tools.
- **Shared memory**: A fixed UUID (`AgentId(Uuid::from_bytes([0..0, 0x01]))`) provides a cross-agent KV namespace.
- **Daemon detection**: The CLI checks `~/.openfang/daemon.json` and pings the health endpoint. If a daemon is running, commands use HTTP; otherwise, they boot an in-process kernel.
- **Capability-based security**: Every agent operation is checked against the agent's granted capabilities before execution.
---
## How to Add a New Agent Template
Agent templates live in the `agents/` directory. Each template is a folder containing an `agent.toml` manifest.
### Steps
1. Create a new directory under `agents/`:
```
agents/my-agent/agent.toml
```
2. Write the manifest:
```toml
name = "my-agent"
version = "0.1.0"
description = "A brief description of what this agent does."
author = "openfang"
module = "builtin:chat"
tags = ["category"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
[resources]
max_llm_tokens_per_hour = 100000
[capabilities]
tools = ["file_read", "file_list", "web_fetch"]
memory_read = ["*"]
memory_write = ["self.*"]
agent_spawn = false
```
3. Include a system prompt if needed by adding it to the `[model]` section:
```toml
[model]
provider = "anthropic"
model = "claude-sonnet-4-20250514"
system_prompt = """
You are a specialized agent that...
"""
```
4. Test by spawning:
```bash
openfang agent spawn agents/my-agent/agent.toml
```
5. Submit a PR with the new template.
---
## How to Add a New Channel Adapter
Channel adapters live in `crates/openfang-channels/src/`. Each adapter implements the `ChannelAdapter` trait.
### Steps
1. Create a new file: `crates/openfang-channels/src/myplatform.rs`
2. Implement the `ChannelAdapter` trait (defined in `types.rs`):
```rust
use crate::types::{ChannelAdapter, ChannelMessage, ChannelType};
use async_trait::async_trait;
pub struct MyPlatformAdapter {
// token, client, config fields
}
#[async_trait]
impl ChannelAdapter for MyPlatformAdapter {
fn channel_type(&self) -> ChannelType {
ChannelType::Custom("myplatform".to_string())
}
async fn start(&mut self) -> Result<(), Box<dyn std::error::Error>> {
// Start polling/listening for messages
Ok(())
}
async fn send(&self, channel_id: &str, content: &str) -> Result<(), Box<dyn std::error::Error>> {
// Send a message back to the platform
Ok(())
}
async fn stop(&mut self) {
// Clean shutdown
}
}
```
3. Register the module in `crates/openfang-channels/src/lib.rs`:
```rust
pub mod myplatform;
```
4. Wire it up in the channel bridge (`crates/openfang-api/src/channel_bridge.rs`) so the daemon starts it alongside other adapters.
5. Add configuration support in `openfang-types` config structs (add a `[channels.myplatform]` section).
6. Add CLI setup wizard instructions in `crates/openfang-cli/src/main.rs` under `cmd_channel_setup`.
7. Write tests and submit a PR.
---
## How to Add a New Tool
Built-in tools are defined in `crates/openfang-runtime/src/tool_runner.rs`.
### Steps
1. Add the tool implementation function:
```rust
async fn tool_my_tool(input: &serde_json::Value) -> Result<String, String> {
let param = input["param"]
.as_str()
.ok_or("Missing 'param' field")?;
// Tool logic here
Ok(format!("Result: {param}"))
}
```
2. Register it in the `execute_tool` match block:
```rust
"my_tool" => tool_my_tool(input).await,
```
3. Add the tool definition to `builtin_tool_definitions()`:
```rust
ToolDefinition {
name: "my_tool".to_string(),
description: "Description shown to the LLM.".to_string(),
input_schema: serde_json::json!({
"type": "object",
"properties": {
"param": {
"type": "string",
"description": "The parameter description"
}
},
"required": ["param"]
}),
},
```
4. Agents that need the tool must list it in their manifest:
```toml
[capabilities]
tools = ["my_tool"]
```
5. Write tests for the tool function.
6. If the tool requires kernel access (e.g., inter-agent communication), accept `Option<&Arc<dyn KernelHandle>>` and handle the `None` case gracefully.
---
## Pull Request Process
1. **Fork and branch**: Create a feature branch from `main`. Use descriptive names like `feat/add-matrix-adapter` or `fix/session-restore-crash`.
2. **Make your changes**: Follow the code style guidelines above.
3. **Test thoroughly**:
- `cargo test --workspace` must pass (all 1,744+ tests).
- `cargo clippy --workspace --all-targets -- -D warnings` must produce zero warnings.
- `cargo fmt --all --check` must produce no diff.
4. **Write a clear PR description**: Explain what changed and why. Include before/after examples if applicable.
5. **One concern per PR**: Keep PRs focused. A single PR should address one feature, one bug fix, or one refactor -- not all three.
6. **Review process**: At least one maintainer must approve before merge. Address review feedback promptly.
7. **CI must pass**: All automated checks must be green before merge.
### Commit Messages
Use clear, imperative-mood messages:
```
Add Matrix channel adapter with E2EE support
Fix session restore crash on kernel reboot
Refactor capability manager to use DashMap
```
---
## Code of Conduct
This project follows the [Contributor Covenant Code of Conduct](https://www.contributor-covenant.org/version/2/1/code_of_conduct/). By participating, you agree to uphold a welcoming, inclusive, and harassment-free environment for everyone.
Please report unacceptable behavior to the maintainers.
---
## Questions?
- Open a [GitHub Discussion](https://github.com/RightNow-AI/openfang/discussions) for questions.
- Open a [GitHub Issue](https://github.com/RightNow-AI/openfang/issues) for bugs or feature requests.
- Check the [docs/](docs/) directory for detailed guides on specific topics.

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[workspace]
resolver = "2"
members = [
"crates/openfang-types",
"crates/openfang-memory",
"crates/openfang-runtime",
"crates/openfang-wire",
"crates/openfang-api",
"crates/openfang-kernel",
"crates/openfang-cli",
"crates/openfang-channels",
"crates/openfang-migrate",
"crates/openfang-skills",
"crates/openfang-desktop",
"crates/openfang-hands",
"crates/openfang-extensions",
"xtask",
]
[workspace.package]
version = "0.2.3"
edition = "2021"
license = "Apache-2.0 OR MIT"
repository = "https://github.com/RightNow-AI/openfang"
rust-version = "1.75"
[workspace.dependencies]
# Async runtime
tokio = { version = "1", features = ["full"] }
tokio-stream = "0.1"
# Serialization
serde = { version = "1", features = ["derive"] }
serde_json = "1"
toml = "0.8"
rmp-serde = "1"
# Error handling
thiserror = "2"
anyhow = "1"
# Concurrency
dashmap = "6"
crossbeam = "0.8"
# Logging / Tracing
tracing = "0.1"
tracing-subscriber = { version = "0.3", features = ["env-filter", "json"] }
# Time
chrono = { version = "0.4", features = ["serde"] }
# IDs
uuid = { version = "1", features = ["v4", "serde"] }
# Database
rusqlite = { version = "0.31", features = ["bundled", "serde_json"] }
# CLI
clap = { version = "4", features = ["derive"] }
clap_complete = "4"
# HTTP client (for LLM drivers)
reqwest = { version = "0.12", default-features = false, features = ["json", "stream", "multipart", "rustls-tls"] }
# Async trait
async-trait = "0.1"
# Base64
base64 = "0.22"
# Bytes
bytes = "1"
# Futures
futures = "0.3"
# WebSocket client (for Discord/Slack gateway)
tokio-tungstenite = { version = "0.24", default-features = false, features = ["connect", "rustls-tls-native-roots"] }
url = "2"
# WASM sandbox
wasmtime = "41"
# HTTP server (for API daemon)
axum = { version = "0.8", features = ["ws"] }
tower = "0.5"
tower-http = { version = "0.6", features = ["cors", "trace", "compression-gzip", "compression-br"] }
# Home directory resolution
dirs = "6"
# YAML parsing
serde_yaml = "0.9"
# JSON5 parsing
json5 = "0.4"
# Directory walking
walkdir = "2"
# Security
sha2 = "0.10"
hmac = "0.12"
hex = "0.4"
subtle = "2"
ed25519-dalek = { version = "2", features = ["rand_core"] }
rand = "0.8"
zeroize = { version = "1", features = ["derive"] }
# Rate limiting
governor = "0.8"
# Interactive CLI
ratatui = "0.29"
colored = "3"
# Encryption
aes-gcm = "0.10"
argon2 = "0.5"
# Lightweight regex
regex-lite = "0.1"
# Email (SMTP + IMAP)
lettre = { version = "0.11", default-features = false, features = ["builder", "hostname", "smtp-transport", "tokio1", "tokio1-rustls-tls"] }
imap = "2"
native-tls = "0.2"
mailparse = "0.15"
# Testing
tokio-test = "0.4"
tempfile = "3"
[profile.release]
lto = true
codegen-units = 1
strip = true
opt-level = 3

5
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[target.aarch64-unknown-linux-gnu]
pre-build = [
"dpkg --add-architecture $CROSS_DEB_ARCH",
"apt-get update && apt-get install --assume-yes libssl-dev:$CROSS_DEB_ARCH"
]

20
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# syntax=docker/dockerfile:1
FROM rust:1-slim-bookworm AS builder
WORKDIR /build
RUN apt-get update && apt-get install -y pkg-config libssl-dev && rm -rf /var/lib/apt/lists/*
COPY Cargo.toml Cargo.lock ./
COPY crates ./crates
COPY xtask ./xtask
COPY agents ./agents
COPY packages ./packages
RUN cargo build --release --bin openfang
FROM debian:bookworm-slim
RUN apt-get update && apt-get install -y ca-certificates && rm -rf /var/lib/apt/lists/*
COPY --from=builder /build/target/release/openfang /usr/local/bin/
COPY --from=builder /build/agents /opt/openfang/agents
EXPOSE 4200
VOLUME /data
ENV OPENFANG_HOME=/data
ENTRYPOINT ["openfang"]
CMD ["start"]

189
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@@ -0,0 +1,189 @@
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8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
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License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
Copyright 2024 OpenFang Contributors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

21
LICENSE-MIT Normal file
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@@ -0,0 +1,21 @@
MIT License
Copyright (c) 2024 OpenFang Contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

360
MIGRATION.md Normal file
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# Migrating to OpenFang
This guide covers migrating from OpenClaw (and other frameworks) to OpenFang. The migration engine handles config conversion, agent import, memory transfer, channel re-configuration, and skill scanning.
## Table of Contents
- [Quick Migration](#quick-migration)
- [What Gets Migrated](#what-gets-migrated)
- [Manual Migration Steps](#manual-migration-steps)
- [Config Format Differences](#config-format-differences)
- [Tool Name Mapping](#tool-name-mapping)
- [Provider Mapping](#provider-mapping)
- [Feature Comparison](#feature-comparison)
---
## Quick Migration
Run a single command to migrate your entire OpenClaw workspace:
```bash
openfang migrate --from openclaw
```
This auto-detects your OpenClaw workspace at `~/.openclaw/` and imports everything into `~/.openfang/`.
### Options
```bash
# Specify a custom source directory
openfang migrate --from openclaw --source-dir /path/to/openclaw/workspace
# Dry run -- see what would be imported without making changes
openfang migrate --from openclaw --dry-run
```
### Migration Report
After a successful migration, a `migration_report.md` file is saved to `~/.openfang/` with a summary of everything that was imported, skipped, or needs manual attention.
### Other Frameworks
LangChain and AutoGPT migration support is planned:
```bash
openfang migrate --from langchain # Coming soon
openfang migrate --from autogpt # Coming soon
```
---
## What Gets Migrated
| Item | Source (OpenClaw) | Destination (OpenFang) | Status |
|------|-------------------|------------------------|--------|
| **Config** | `~/.openclaw/config.yaml` | `~/.openfang/config.toml` | Fully automated |
| **Agents** | `~/.openclaw/agents/*/agent.yaml` | `~/.openfang/agents/*/agent.toml` | Fully automated |
| **Memory** | `~/.openclaw/agents/*/MEMORY.md` | `~/.openfang/agents/*/imported_memory.md` | Fully automated |
| **Channels** | `~/.openclaw/messaging/*.yaml` | `~/.openfang/channels_import.toml` | Automated (manual merge) |
| **Skills** | `~/.openclaw/skills/` | Scanned and reported | Manual reinstall |
| **Sessions** | `~/.openclaw/agents/*/sessions/` | Not migrated | Fresh start recommended |
| **Workspace files** | `~/.openclaw/agents/*/workspace/` | Not migrated | Copy manually if needed |
### Channel Import Note
Channel configurations (Telegram, Discord, Slack) are exported to a `channels_import.toml` file. You must manually merge the `[channels]` section into your `~/.openfang/config.toml`.
### Skills Note
OpenClaw skills (Node.js) are detected and listed in the migration report but not automatically converted. After migration, reinstall skills using:
```bash
openfang skill install <skill-name-or-path>
```
OpenFang automatically detects OpenClaw-format skills and converts them during installation.
---
## Manual Migration Steps
If you prefer migrating by hand (or need to handle edge cases), follow these steps:
### 1. Initialize OpenFang
```bash
openfang init
```
This creates `~/.openfang/` with a default `config.toml`.
### 2. Convert Your Config
Translate your `config.yaml` to `config.toml`:
**OpenClaw** (`~/.openclaw/config.yaml`):
```yaml
provider: anthropic
model: claude-sonnet-4-20250514
api_key_env: ANTHROPIC_API_KEY
temperature: 0.7
memory:
decay_rate: 0.05
```
**OpenFang** (`~/.openfang/config.toml`):
```toml
[default_model]
provider = "anthropic"
model = "claude-sonnet-4-20250514"
api_key_env = "ANTHROPIC_API_KEY"
[memory]
decay_rate = 0.05
[network]
listen_addr = "127.0.0.1:4200"
```
### 3. Convert Agent Manifests
Translate each `agent.yaml` to `agent.toml`:
**OpenClaw** (`~/.openclaw/agents/coder/agent.yaml`):
```yaml
name: coder
description: A coding assistant
provider: anthropic
model: claude-sonnet-4-20250514
tools:
- read_file
- write_file
- execute_command
tags:
- coding
- dev
```
**OpenFang** (`~/.openfang/agents/coder/agent.toml`):
```toml
name = "coder"
version = "0.1.0"
description = "A coding assistant"
author = "openfang"
module = "builtin:chat"
tags = ["coding", "dev"]
[model]
provider = "anthropic"
model = "claude-sonnet-4-20250514"
[capabilities]
tools = ["file_read", "file_write", "shell_exec"]
memory_read = ["*"]
memory_write = ["self.*"]
```
### 4. Convert Channel Configs
**OpenClaw** (`~/.openclaw/messaging/telegram.yaml`):
```yaml
type: telegram
bot_token_env: TELEGRAM_BOT_TOKEN
default_agent: coder
allowed_users:
- "123456789"
```
**OpenFang** (add to `~/.openfang/config.toml`):
```toml
[channels.telegram]
bot_token_env = "TELEGRAM_BOT_TOKEN"
default_agent = "coder"
allowed_users = ["123456789"]
```
### 5. Import Memory
Copy any `MEMORY.md` files from OpenClaw agents to OpenFang agent directories:
```bash
cp ~/.openclaw/agents/coder/MEMORY.md ~/.openfang/agents/coder/imported_memory.md
```
The kernel will ingest these on first boot.
---
## Config Format Differences
| Aspect | OpenClaw | OpenFang |
|--------|----------|----------|
| Format | YAML | TOML |
| Config location | `~/.openclaw/config.yaml` | `~/.openfang/config.toml` |
| Agent definition | `agent.yaml` | `agent.toml` |
| Channel config | Separate files per channel | Unified in `config.toml` |
| Tool permissions | Implicit (tool list) | Capability-based (tools, memory, network, shell) |
| Model config | Flat (top-level fields) | Nested (`[model]` section) |
| Agent module | Implicit | Explicit (`module = "builtin:chat"` / `"wasm:..."` / `"python:..."`) |
| Scheduling | Not supported | Built-in (`[schedule]` section: reactive, continuous, periodic, proactive) |
| Resource quotas | Not supported | Built-in (`[resources]` section: tokens/hour, memory, CPU time) |
| Networking | Not supported | OFP protocol (`[network]` section) |
---
## Tool Name Mapping
Tools were renamed between OpenClaw and OpenFang for consistency. The migration engine handles this automatically.
| OpenClaw Tool | OpenFang Tool | Notes |
|---------------|---------------|-------|
| `read_file` | `file_read` | Noun-first naming |
| `write_file` | `file_write` | |
| `list_files` | `file_list` | |
| `execute_command` | `shell_exec` | Capability-gated |
| `web_search` | `web_search` | Unchanged |
| `fetch_url` | `web_fetch` | |
| `browser_navigate` | `browser_navigate` | Unchanged |
| `memory_search` | `memory_recall` | |
| `memory_recall` | `memory_recall` | |
| `memory_save` | `memory_store` | |
| `memory_store` | `memory_store` | |
| `sessions_send` | `agent_send` | |
| `agent_message` | `agent_send` | |
| `agents_list` | `agent_list` | |
| `agent_list` | `agent_list` | |
### New Tools in OpenFang
These tools have no OpenClaw equivalent:
| Tool | Description |
|------|-------------|
| `agent_spawn` | Spawn a new agent from within an agent |
| `agent_kill` | Terminate another agent |
| `agent_find` | Search for agents by name, tag, or description |
| `memory_store` | Store key-value data in shared memory |
| `memory_recall` | Recall key-value data from shared memory |
| `task_post` | Post a task to the shared task board |
| `task_claim` | Claim an available task |
| `task_complete` | Mark a task as complete |
| `task_list` | List tasks by status |
| `event_publish` | Publish a custom event to the event bus |
| `schedule_create` | Create a scheduled job |
| `schedule_list` | List scheduled jobs |
| `schedule_delete` | Delete a scheduled job |
| `image_analyze` | Analyze an image |
| `location_get` | Get location information |
### Tool Profiles
OpenClaw's tool profiles map to explicit tool lists:
| OpenClaw Profile | OpenFang Tools |
|------------------|----------------|
| `minimal` | `file_read`, `file_list` |
| `coding` | `file_read`, `file_write`, `file_list`, `shell_exec`, `web_fetch` |
| `messaging` | `agent_send`, `agent_list`, `memory_store`, `memory_recall` |
| `research` | `web_fetch`, `web_search`, `file_read`, `file_write` |
| `full` | All 10 core tools |
---
## Provider Mapping
| OpenClaw Name | OpenFang Name | API Key Env Var |
|---------------|---------------|-----------------|
| `anthropic` | `anthropic` | `ANTHROPIC_API_KEY` |
| `claude` | `anthropic` | `ANTHROPIC_API_KEY` |
| `openai` | `openai` | `OPENAI_API_KEY` |
| `gpt` | `openai` | `OPENAI_API_KEY` |
| `groq` | `groq` | `GROQ_API_KEY` |
| `ollama` | `ollama` | (none required) |
| `openrouter` | `openrouter` | `OPENROUTER_API_KEY` |
| `deepseek` | `deepseek` | `DEEPSEEK_API_KEY` |
| `together` | `together` | `TOGETHER_API_KEY` |
| `mistral` | `mistral` | `MISTRAL_API_KEY` |
| `fireworks` | `fireworks` | `FIREWORKS_API_KEY` |
### New Providers in OpenFang
| Provider | Description |
|----------|-------------|
| `vllm` | Self-hosted vLLM inference server |
| `lmstudio` | LM Studio local models |
---
## Feature Comparison
| Feature | OpenClaw | OpenFang |
|---------|----------|----------|
| **Language** | Node.js / TypeScript | Rust |
| **Config format** | YAML | TOML |
| **Agent manifests** | YAML | TOML |
| **Multi-agent** | Basic (message passing) | First-class (spawn, kill, find, workflows, triggers) |
| **Agent scheduling** | Manual | Built-in (reactive, continuous, periodic, proactive) |
| **Memory** | Markdown files | SQLite + KV store + semantic search + knowledge graph |
| **Session management** | JSONL files | SQLite with context window tracking |
| **LLM providers** | ~5 | 11 (Anthropic, OpenAI, Groq, OpenRouter, DeepSeek, Together, Mistral, Fireworks, Ollama, vLLM, LM Studio) |
| **Per-agent models** | No | Yes (per-agent provider + model override) |
| **Security** | None | Capability-based (tools, memory, network, shell, agent spawn) |
| **Resource quotas** | None | Per-agent token/hour limits, memory limits, CPU time limits |
| **Workflow engine** | None | Built-in (sequential, fan-out, collect, conditional, loop) |
| **Event triggers** | None | Pattern-matching event triggers with templated prompts |
| **WASM sandbox** | None | Wasmtime-based sandboxed execution |
| **Python runtime** | None | Subprocess-based Python agent execution |
| **Networking** | None | OFP (OpenFang Protocol) peer-to-peer |
| **API server** | Basic REST | REST + WebSocket + SSE streaming |
| **WebChat UI** | Separate | Embedded in daemon |
| **Channel adapters** | Telegram, Discord | Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email |
| **Skills/Plugins** | npm packages | TOML + Python/WASM/Node.js, FangHub marketplace |
| **CLI** | Basic | Full CLI with daemon auto-detect, MCP server |
| **MCP support** | No | Built-in MCP server (stdio) |
| **Process supervisor** | None | Health monitoring, panic/restart tracking |
| **Persistence** | File-based | SQLite (agents survive restarts) |
---
## Troubleshooting
### Migration reports "Source directory not found"
The migration engine looks for `~/.openclaw/` by default. If your OpenClaw workspace is elsewhere:
```bash
openfang migrate --from openclaw --source-dir /path/to/your/workspace
```
### Agent fails to spawn after migration
Check the converted `agent.toml` for:
- Valid tool names (see the [Tool Name Mapping](#tool-name-mapping) table)
- A valid provider name (see the [Provider Mapping](#provider-mapping) table)
- Correct `module` field (should be `"builtin:chat"` for standard LLM agents)
### Skills not working
OpenClaw Node.js skills must be reinstalled:
```bash
openfang skill install /path/to/openclaw/skills/my-skill
```
The installer auto-detects OpenClaw format and converts the skill manifest.
### Channel not connecting
After migration, channels are exported to `channels_import.toml`. You must merge them into your `config.toml` manually:
```bash
cat ~/.openfang/channels_import.toml
# Copy the [channels.*] sections into ~/.openfang/config.toml
```
Then restart the daemon:
```bash
openfang start
```

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<p align="center">
<img src="public/assets/openfang-logo.png" width="160" alt="OpenFang Logo" />
</p>
<h1 align="center">OpenFang</h1>
<h3 align="center">The Agent Operating System</h3>
<p align="center">
Open-source Agent OS built in Rust. 137K LOC. 14 crates. 1,767+ tests. Zero clippy warnings.<br/>
<strong>One binary. Battle-tested. Agents that actually work for you.</strong>
</p>
<p align="center">
<a href="https://openfang.sh/docs">Documentation</a> &bull;
<a href="https://openfang.sh/docs/getting-started">Quick Start</a> &bull;
<a href="https://x.com/openfangg">Twitter / X</a>
</p>
<p align="center">
<img src="https://img.shields.io/badge/language-Rust-orange?style=flat-square" alt="Rust" />
<img src="https://img.shields.io/badge/license-MIT-blue?style=flat-square" alt="MIT" />
<img src="https://img.shields.io/badge/version-0.1.0-green?style=flat-square" alt="v0.1.0" />
<img src="https://img.shields.io/badge/tests-1,767%2B%20passing-brightgreen?style=flat-square" alt="Tests" />
<img src="https://img.shields.io/badge/clippy-0%20warnings-brightgreen?style=flat-square" alt="Clippy" />
<a href="https://www.buymeacoffee.com/openfang" target="_blank"><img src="https://img.shields.io/badge/Buy%20Me%20a%20Coffee-FFDD00?style=flat-square&logo=buy-me-a-coffee&logoColor=black" alt="Buy Me A Coffee" /></a>
</p>
---
> **v0.1.0 — First Release (February 2026)**
>
> OpenFang is feature-complete but this is the first public release. You may encounter instability, rough edges, or breaking changes between minor versions. We ship fast and fix fast. Pin to a specific commit for production use until v1.0. [Report issues here.](https://github.com/RightNow-AI/openfang/issues)
---
## What is OpenFang?
OpenFang is an **open-source Agent Operating System** — not a chatbot framework, not a Python wrapper around an LLM, not a "multi-agent orchestrator." It is a full operating system for autonomous agents, built from scratch in Rust.
Traditional agent frameworks wait for you to type something. OpenFang runs **autonomous agents that work for you** — on schedules, 24/7, building knowledge graphs, monitoring targets, generating leads, managing your social media, and reporting results to your dashboard.
The entire system compiles to a **single ~32MB binary**. One install, one command, your agents are live.
```bash
curl -fsSL https://openfang.sh/install | sh
openfang init
openfang start
# Dashboard live at http://localhost:4200
```
<details>
<summary><strong>Windows</strong></summary>
```powershell
irm https://openfang.sh/install.ps1 | iex
openfang init
openfang start
```
</details>
---
## Hands: Agents That Actually Do Things
<p align="center"><em>"Traditional agents wait for you to type. Hands work <strong>for</strong> you."</em></p>
**Hands** are OpenFang's core innovation — pre-built autonomous capability packages that run independently, on schedules, without you having to prompt them. This is not a chatbot. This is an agent that wakes up at 6 AM, researches your competitors, builds a knowledge graph, scores the findings, and delivers a report to your Telegram before you've had coffee.
Each Hand bundles:
- **HAND.toml** — Manifest declaring tools, settings, requirements, and dashboard metrics
- **System Prompt** — Multi-phase operational playbook (not a one-liner — these are 500+ word expert procedures)
- **SKILL.md** — Domain expertise reference injected into context at runtime
- **Guardrails** — Approval gates for sensitive actions (e.g. Browser Hand requires approval before any purchase)
All compiled into the binary. No downloading, no pip install, no Docker pull.
### The 7 Bundled Hands
| Hand | What It Actually Does |
|------|----------------------|
| **Clip** | Takes a YouTube URL, downloads it, identifies the best moments, cuts them into vertical shorts with captions and thumbnails, optionally adds AI voice-over, and publishes to Telegram and WhatsApp. 8-phase pipeline. FFmpeg + yt-dlp + 5 STT backends. |
| **Lead** | Runs daily. Discovers prospects matching your ICP, enriches them with web research, scores 0-100, deduplicates against your existing database, and delivers qualified leads in CSV/JSON/Markdown. Builds ICP profiles over time. |
| **Collector** | OSINT-grade intelligence. You give it a target (company, person, topic). It monitors continuously — change detection, sentiment tracking, knowledge graph construction, and critical alerts when something important shifts. |
| **Predictor** | Superforecasting engine. Collects signals from multiple sources, builds calibrated reasoning chains, makes predictions with confidence intervals, and tracks its own accuracy using Brier scores. Has a contrarian mode that deliberately argues against consensus. |
| **Researcher** | Deep autonomous researcher. Cross-references multiple sources, evaluates credibility using CRAAP criteria (Currency, Relevance, Authority, Accuracy, Purpose), generates cited reports with APA formatting, supports multiple languages. |
| **Twitter** | Autonomous Twitter/X account manager. Creates content in 7 rotating formats, schedules posts for optimal engagement, responds to mentions, tracks performance metrics. Has an approval queue — nothing posts without your OK. |
| **Browser** | Web automation agent. Navigates sites, fills forms, clicks buttons, handles multi-step workflows. Uses Playwright bridge with session persistence. **Mandatory purchase approval gate** — it will never spend your money without explicit confirmation. |
```bash
# Activate the Researcher Hand — it starts working immediately
openfang hand activate researcher
# Check its progress anytime
openfang hand status researcher
# Activate lead generation on a daily schedule
openfang hand activate lead
# Pause without losing state
openfang hand pause lead
# See all available Hands
openfang hand list
```
**Build your own.** Define a `HAND.toml` with tools, settings, and a system prompt. Publish to FangHub.
---
## OpenFang vs The Landscape
<p align="center">
<img src="public/assets/openfang-vs-claws.png" width="600" alt="OpenFang vs OpenClaw vs ZeroClaw" />
</p>
### Benchmarks: Measured, Not Marketed
All data from official documentation and public repositories — February 2026.
#### Cold Start Time (lower is better)
```
ZeroClaw ██░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10 ms
OpenFang ██████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 180 ms ★
LangGraph █████████████████░░░░░░░░░░░░░░░░░░░░░░░░░ 2.5 sec
CrewAI ████████████████████░░░░░░░░░░░░░░░░░░░░░░ 3.0 sec
AutoGen ██████████████████████████░░░░░░░░░░░░░░░░░ 4.0 sec
OpenClaw █████████████████████████████████████████░░ 5.98 sec
```
#### Idle Memory Usage (lower is better)
```
ZeroClaw █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 5 MB
OpenFang ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 40 MB ★
LangGraph ██████████████████░░░░░░░░░░░░░░░░░░░░░░░░░ 180 MB
CrewAI ████████████████████░░░░░░░░░░░░░░░░░░░░░░░ 200 MB
AutoGen █████████████████████████░░░░░░░░░░░░░░░░░░ 250 MB
OpenClaw ████████████████████████████████████████░░░░ 394 MB
```
#### Install Size (lower is better)
```
ZeroClaw █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 8.8 MB
OpenFang ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 32 MB ★
CrewAI ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 100 MB
LangGraph ████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 150 MB
AutoGen ████████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░ 200 MB
OpenClaw ████████████████████████████████████████░░░░ 500 MB
```
#### Security Systems (higher is better)
```
OpenFang ████████████████████████████████████████████ 16 ★
ZeroClaw ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 6
OpenClaw ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 3
AutoGen █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 2
LangGraph █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 2
CrewAI ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 1
```
#### Channel Adapters (higher is better)
```
OpenFang ████████████████████████████████████████████ 40 ★
ZeroClaw ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 15
OpenClaw █████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 13
CrewAI ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0
AutoGen ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0
LangGraph ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0
```
#### LLM Providers (higher is better)
```
ZeroClaw ████████████████████████████████████████████ 28
OpenFang ██████████████████████████████████████████░░ 27 ★
LangGraph ██████████████████████░░░░░░░░░░░░░░░░░░░░░ 15
CrewAI ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10
OpenClaw ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10
AutoGen ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 8
```
### Feature-by-Feature Comparison
| Feature | OpenFang | OpenClaw | ZeroClaw | CrewAI | AutoGen | LangGraph |
|---------|----------|----------|----------|--------|---------|-----------|
| **Language** | **Rust** | TypeScript | **Rust** | Python | Python | Python |
| **Autonomous Hands** | **7 built-in** | None | None | None | None | None |
| **Security Layers** | **16 discrete** | 3 basic | 6 layers | 1 basic | Docker | AES enc. |
| **Agent Sandbox** | **WASM dual-metered** | None | Allowlists | None | Docker | None |
| **Channel Adapters** | **40** | 13 | 15 | 0 | 0 | 0 |
| **Built-in Tools** | **53 + MCP + A2A** | 50+ | 12 | Plugins | MCP | LC tools |
| **Memory** | **SQLite + vector** | File-based | SQLite FTS5 | 4-layer | External | Checkpoints |
| **Desktop App** | **Tauri 2.0** | None | None | None | Studio | None |
| **Audit Trail** | **Merkle hash-chain** | Logs | Logs | Tracing | Logs | Checkpoints |
| **Cold Start** | **<200ms** | ~6s | ~10ms | ~3s | ~4s | ~2.5s |
| **Install Size** | **~32 MB** | ~500 MB | ~8.8 MB | ~100 MB | ~200 MB | ~150 MB |
| **License** | MIT | MIT | MIT | MIT | Apache 2.0 | MIT |
---
## 16 Security Systems — Defense in Depth
OpenFang doesn't bolt security on after the fact. Every layer is independently testable and operates without a single point of failure.
| # | System | What It Does |
|---|--------|-------------|
| 1 | **WASM Dual-Metered Sandbox** | Tool code runs in WebAssembly with fuel metering + epoch interruption. A watchdog thread kills runaway code. |
| 2 | **Merkle Hash-Chain Audit Trail** | Every action is cryptographically linked to the previous one. Tamper with one entry and the entire chain breaks. |
| 3 | **Information Flow Taint Tracking** | Labels propagate through execution — secrets are tracked from source to sink. |
| 4 | **Ed25519 Signed Agent Manifests** | Every agent identity and capability set is cryptographically signed. |
| 5 | **SSRF Protection** | Blocks private IPs, cloud metadata endpoints, and DNS rebinding attacks. |
| 6 | **Secret Zeroization** | `Zeroizing<String>` auto-wipes API keys from memory the instant they're no longer needed. |
| 7 | **OFP Mutual Authentication** | HMAC-SHA256 nonce-based, constant-time verification for P2P networking. |
| 8 | **Capability Gates** | Role-based access control — agents declare required tools, the kernel enforces it. |
| 9 | **Security Headers** | CSP, X-Frame-Options, HSTS, X-Content-Type-Options on every response. |
| 10 | **Health Endpoint Redaction** | Public health check returns minimal info. Full diagnostics require authentication. |
| 11 | **Subprocess Sandbox** | `env_clear()` + selective variable passthrough. Process tree isolation with cross-platform kill. |
| 12 | **Prompt Injection Scanner** | Detects override attempts, data exfiltration patterns, and shell reference injection in skills. |
| 13 | **Loop Guard** | SHA256-based tool call loop detection with circuit breaker. Handles ping-pong patterns. |
| 14 | **Session Repair** | 7-phase message history validation and automatic recovery from corruption. |
| 15 | **Path Traversal Prevention** | Canonicalization with symlink escape prevention. `../` doesn't work here. |
| 16 | **GCRA Rate Limiter** | Cost-aware token bucket rate limiting with per-IP tracking and stale cleanup. |
---
## Architecture
14 Rust crates. 137,728 lines of code. Modular kernel design.
```
openfang-kernel Orchestration, workflows, metering, RBAC, scheduler, budget tracking
openfang-runtime Agent loop, 3 LLM drivers, 53 tools, WASM sandbox, MCP, A2A
openfang-api 140+ REST/WS/SSE endpoints, OpenAI-compatible API, dashboard
openfang-channels 40 messaging adapters with rate limiting, DM/group policies
openfang-memory SQLite persistence, vector embeddings, canonical sessions, compaction
openfang-types Core types, taint tracking, Ed25519 manifest signing, model catalog
openfang-skills 60 bundled skills, SKILL.md parser, FangHub marketplace
openfang-hands 7 autonomous Hands, HAND.toml parser, lifecycle management
openfang-extensions 25 MCP templates, AES-256-GCM credential vault, OAuth2 PKCE
openfang-wire OFP P2P protocol with HMAC-SHA256 mutual authentication
openfang-cli CLI with daemon management, TUI dashboard, MCP server mode
openfang-desktop Tauri 2.0 native app (system tray, notifications, global shortcuts)
openfang-migrate OpenClaw, LangChain, AutoGPT migration engine
xtask Build automation
```
---
## 40 Channel Adapters
Connect your agents to every platform your users are on.
**Core:** Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email (IMAP/SMTP)
**Enterprise:** Microsoft Teams, Mattermost, Google Chat, Webex, Feishu/Lark, Zulip
**Social:** LINE, Viber, Facebook Messenger, Mastodon, Bluesky, Reddit, LinkedIn, Twitch
**Community:** IRC, XMPP, Guilded, Revolt, Keybase, Discourse, Gitter
**Privacy:** Threema, Nostr, Mumble, Nextcloud Talk, Rocket.Chat, Ntfy, Gotify
**Workplace:** Pumble, Flock, Twist, DingTalk, Zalo, Webhooks
Each adapter supports per-channel model overrides, DM/group policies, rate limiting, and output formatting.
---
## 27 LLM Providers — 123+ Models
3 native drivers (Anthropic, Gemini, OpenAI-compatible) route to 27 providers:
Anthropic, Gemini, OpenAI, Groq, DeepSeek, OpenRouter, Together, Mistral, Fireworks, Cohere, Perplexity, xAI, AI21, Cerebras, SambaNova, HuggingFace, Replicate, Ollama, vLLM, LM Studio, Qwen, MiniMax, Zhipu, Moonshot, Qianfan, Bedrock, and more.
Intelligent routing with task complexity scoring, automatic fallback, cost tracking, and per-model pricing.
---
## Migrate from OpenClaw
Already running OpenClaw? One command:
```bash
# Migrate everything — agents, memory, skills, configs
openfang migrate --from openclaw
# Migrate from a specific path
openfang migrate --from openclaw --path ~/.openclaw
# Dry run first to see what would change
openfang migrate --from openclaw --dry-run
```
The migration engine imports your agents, conversation history, skills, and configuration. OpenFang reads SKILL.md natively and is compatible with the ClawHub marketplace.
---
## OpenAI-Compatible API
Drop-in replacement. Point your existing tools at OpenFang:
```bash
curl -X POST localhost:4200/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "researcher",
"messages": [{"role": "user", "content": "Analyze Q4 market trends"}],
"stream": true
}'
```
140+ REST/WS/SSE endpoints covering agents, memory, workflows, channels, models, skills, A2A, Hands, and more.
---
## Quick Start
```bash
# 1. Install (macOS/Linux)
curl -fsSL https://openfang.sh/install | sh
# 2. Initialize — walks you through provider setup
openfang init
# 3. Start the daemon
openfang start
# 4. Dashboard is live at http://localhost:4200
# 5. Activate a Hand — it starts working for you
openfang hand activate researcher
# 6. Chat with an agent
openfang chat researcher
> "What are the emerging trends in AI agent frameworks?"
# 7. Spawn a pre-built agent
openfang agent spawn coder
```
<details>
<summary><strong>Windows (PowerShell)</strong></summary>
```powershell
irm https://openfang.sh/install.ps1 | iex
openfang init
openfang start
```
</details>
---
## Development
```bash
# Build the workspace
cargo build --workspace --lib
# Run all tests (1,767+)
cargo test --workspace
# Lint (must be 0 warnings)
cargo clippy --workspace --all-targets -- -D warnings
# Format
cargo fmt --all -- --check
```
---
## Stability Notice
OpenFang v0.1.0 is the first public release. The architecture is solid, the test suite is comprehensive, and the security model is comprehensive. That said:
- **Breaking changes** may occur between minor versions until v1.0
- **Some Hands** are more mature than others (Browser and Researcher are the most battle-tested)
- **Edge cases** exist — if you find one, [open an issue](https://github.com/RightNow-AI/openfang/issues)
- **Pin to a specific commit** for production deployments until v1.0
We ship fast and fix fast. The goal is a rock-solid v1.0 by mid-2026.
---
## License
MIT — use it however you want.
---
## Links
- [Website & Documentation](https://openfang.sh)
- [Quick Start Guide](https://openfang.sh/docs/getting-started)
- [GitHub](https://github.com/RightNow-AI/openfang)
- [Discord](https://discord.gg/sSJqgNnq6X)
- [Twitter / X](https://x.com/openfangg)
---
## Built by RightNow
<p align="center">
<a href="https://www.rightnowai.co/">
<img src="public/assets/rightnow-logo.webp" width="60" alt="RightNow Logo" />
</a>
</p>
<p align="center">
OpenFang is built and maintained by <a href="https://x.com/Akashi203"><strong>Jaber</strong></a>, Founder of <a href="https://www.rightnowai.co/"><strong>RightNow</strong></a>.
</p>
<p align="center">
<a href="https://www.rightnowai.co/">Website</a> &bull;
<a href="https://x.com/Akashi203">Twitter / X</a> &bull;
<a href="https://www.buymeacoffee.com/openfang" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
</p>
---
<p align="center">
<strong>Built with Rust. Secured with 16 layers. Agents that actually work for you.</strong>
</p>

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# Security Policy
## Supported Versions
| Version | Supported |
|---------|--------------------|
| 0.1.x | :white_check_mark: |
## Reporting a Vulnerability
If you discover a security vulnerability in OpenFang, please report it responsibly.
**Do NOT open a public GitHub issue for security vulnerabilities.**
### How to Report
1. Email: **security@openfang.ai**
2. Include:
- Description of the vulnerability
- Steps to reproduce
- Affected versions
- Potential impact assessment
- Suggested fix (if any)
### What to Expect
- **Acknowledgment** within 48 hours
- **Initial assessment** within 7 days
- **Fix timeline** communicated within 14 days
- **Credit** given in the advisory (unless you prefer anonymity)
### Scope
The following are in scope for security reports:
- Authentication/authorization bypass
- Remote code execution
- Path traversal / directory traversal
- Server-Side Request Forgery (SSRF)
- Privilege escalation between agents or users
- Information disclosure (API keys, secrets, internal state)
- Denial of service via resource exhaustion
- Supply chain attacks via skill ecosystem
- WASM sandbox escapes
## Security Architecture
OpenFang implements defense-in-depth with the following security controls:
### Access Control
- **Capability-based permissions**: Agents only access resources explicitly granted
- **RBAC multi-user**: Owner/Admin/User/Viewer role hierarchy
- **Privilege escalation prevention**: Child agents cannot exceed parent capabilities
- **API authentication**: Bearer token with loopback bypass for local CLI
### Input Validation
- **Path traversal protection**: `safe_resolve_path()` / `safe_resolve_parent()` on all file operations
- **SSRF protection**: Private IP blocking, DNS resolution checks, cloud metadata endpoint filtering
- **Image validation**: Media type whitelist (png/jpeg/gif/webp), 5MB size limit
- **Prompt injection scanning**: Skill content scanned for override attempts and data exfiltration
### Cryptographic Security
- **Ed25519 signed manifests**: Agent identity verification
- **HMAC-SHA256 wire protocol**: Mutual authentication with nonce-based replay protection
- **Secret zeroization**: `Zeroizing<String>` on all API key fields, wiped on drop
### Runtime Isolation
- **WASM dual metering**: Fuel limits + epoch interruption with watchdog thread
- **Subprocess sandbox**: Environment isolation (`env_clear()`), restricted PATH
- **Taint tracking**: Information flow labels prevent untrusted data in privileged operations
### Network Security
- **GCRA rate limiter**: Cost-aware token buckets per IP
- **Security headers**: CSP, X-Frame-Options, X-Content-Type-Options, HSTS
- **Health redaction**: Public endpoint returns minimal info; full diagnostics require auth
- **CORS policy**: Restricted to localhost when no API key configured
### Audit
- **Merkle hash chain**: Tamper-evident audit trail for all agent actions
- **Tamper detection**: Chain integrity verification via `/api/audit/verify`
## Dependencies
Security-critical dependencies are pinned and audited:
| Dependency | Purpose |
|------------|---------|
| `ed25519-dalek` | Manifest signing |
| `sha2` | Hash chain, checksums |
| `hmac` | Wire protocol authentication |
| `subtle` | Constant-time comparison |
| `zeroize` | Secret memory wiping |
| `rand` | Cryptographic randomness |
| `governor` | Rate limiting |

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name = "analyst"
version = "0.1.0"
description = "Data analyst. Processes data, generates insights, creates reports."
author = "openfang"
module = "builtin:chat"
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.4
system_prompt = """You are Analyst, a data analysis agent running inside the OpenFang Agent OS.
ANALYSIS FRAMEWORK:
1. QUESTION — Clarify what question we're answering and what decisions it informs.
2. EXPLORE — Read the data. Examine shape, types, distributions, missing values, and outliers.
3. ANALYZE — Apply appropriate methods. Show your work with numbers.
4. VISUALIZE — When helpful, write Python scripts to generate charts or summary tables.
5. REPORT — Present findings in a structured format.
EVIDENCE STANDARDS:
- Every claim must be backed by data. Quote specific numbers.
- Distinguish correlation from causation.
- State confidence levels and sample sizes.
- Flag data quality issues upfront.
OUTPUT FORMAT:
- Executive Summary (1-2 sentences)
- Key Findings (numbered, with supporting metrics)
- Methodology (what you did and why)
- Data Quality Notes
- Recommendations with evidence
- Caveats and limitations"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["python *", "cargo *"]

45
agents/architect/agent.toml Normal file
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name = "architect"
version = "0.1.0"
description = "System architect. Designs software architectures, evaluates trade-offs, creates technical specifications."
author = "openfang"
module = "builtin:chat"
tags = ["architecture", "design", "planning"]
[model]
provider = "deepseek"
model = "deepseek-chat"
api_key_env = "DEEPSEEK_API_KEY"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Architect, a senior software architect running inside the OpenFang Agent OS.
You design systems with these principles:
- Separation of concerns and clean boundaries
- Performance-aware design (measure, don't guess)
- Simplicity over cleverness
- Explicit over implicit
- Design for change, but don't over-engineer
When designing:
1. Clarify requirements and constraints
2. Identify key components and their responsibilities
3. Define interfaces and data flow
4. Evaluate trade-offs (latency, throughput, complexity, maintainability)
5. Document decisions with rationale
Output format: Use clear headings, diagrams (ASCII), and structured reasoning.
When asked to review, be honest about weaknesses."""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
[capabilities]
tools = ["file_read", "file_list", "memory_store", "memory_recall", "agent_send"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
agent_message = ["*"]

78
agents/assistant/agent.toml Normal file
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name = "assistant"
version = "0.1.0"
description = "General-purpose assistant agent. The default OpenClaw agent for everyday tasks, questions, and conversations."
author = "openfang"
module = "builtin:chat"
tags = ["general", "assistant", "default", "multipurpose", "conversation", "productivity"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.5
system_prompt = """You are Assistant, a specialist agent in the OpenFang Agent OS. You are the default general-purpose agent — a versatile, knowledgeable, and helpful companion designed to handle a wide range of everyday tasks, answer questions, and assist with productivity workflows.
CORE COMPETENCIES:
1. Conversational Intelligence
You engage in natural, helpful conversations on virtually any topic. You answer factual questions accurately, provide explanations at the appropriate level of detail, and maintain context across multi-turn dialogues. You know when to be concise (quick factual answers) and when to be thorough (complex explanations, nuanced topics). You ask clarifying questions when a request is ambiguous rather than guessing. You are honest about the limits of your knowledge and clearly distinguish between established facts, well-supported opinions, and speculation.
2. Task Execution and Productivity
You help users accomplish concrete tasks: writing and editing text, brainstorming ideas, summarizing documents, creating lists and plans, drafting emails and messages, organizing information, performing calculations, and managing files. You approach each task systematically: understand the goal, gather necessary context, execute the work, and verify the result. You proactively suggest improvements and catch potential issues.
3. Research and Information Synthesis
You help users find, organize, and understand information. You can search the web, read documents, and synthesize findings into clear summaries. You evaluate source quality, identify conflicting information, and present balanced perspectives on complex topics. You structure research output with clear sections: key findings, supporting evidence, open questions, and recommended next steps.
4. Writing and Communication
You are a versatile writer who adapts style and tone to the task: professional correspondence, creative writing, technical documentation, casual messages, social media posts, reports, and presentations. You understand audience, purpose, and context. You provide multiple options when the user's preference is unclear. You edit for clarity, grammar, tone, and structure.
5. Problem Solving and Analysis
You help users think through problems logically. You apply structured frameworks: define the problem, identify constraints, generate options, evaluate trade-offs, and recommend a course of action. You use first-principles thinking to break complex problems into manageable components. You consider multiple perspectives and anticipate potential objections or risks.
6. Agent Delegation
As the default entry point to the OpenFang Agent OS, you know when a task would be better handled by a specialist agent. You can list available agents, delegate tasks to specialists, and synthesize their responses. You understand each specialist's strengths and route work accordingly: coding tasks to Coder, research to Researcher, data analysis to Analyst, writing to Writer, and so on. When a task is within your general capabilities, you handle it directly without unnecessary delegation.
7. Knowledge Management
You help users organize and retrieve information across sessions. You store important context, preferences, and reference material in memory for future conversations. You maintain structured notes, to-do lists, and project summaries. You recall previous conversations and build on established context.
8. Creative and Brainstorming Support
You help generate ideas, explore possibilities, and think creatively. You use brainstorming techniques: mind mapping, SCAMPER, random association, constraint-based ideation, and analogical thinking. You help users explore options without premature judgment, then shift to evaluation and refinement when ready.
OPERATIONAL GUIDELINES:
- Be helpful, accurate, and honest in all interactions
- Adapt your communication style to the user's preferences and the task at hand
- When unsure, ask clarifying questions rather than making assumptions
- For specialized tasks, recommend or delegate to the appropriate specialist agent
- Provide structured, scannable output: use headers, bullet points, and numbered lists
- Store user preferences, context, and important information in memory for continuity
- Be proactive about suggesting related tasks or improvements, but respect the user's focus
- Never fabricate information — clearly state when you are uncertain or speculating
- Respect privacy and confidentiality in all interactions
- When handling multiple tasks, prioritize and track them clearly
- Use all available tools appropriately: files for persistent documents, memory for context, web for current information, shell for computations
TOOLS AVAILABLE:
- file_read / file_write / file_list: Read, create, and manage files and documents
- memory_store / memory_recall: Persist and retrieve context, preferences, and knowledge
- web_fetch: Access current information from the web
- shell_exec: Run computations, scripts, and system commands
- agent_send / agent_list: Delegate tasks to specialist agents and see available agents
You are reliable, adaptable, and genuinely helpful. You are the user's trusted first point of contact in the OpenFang Agent OS — capable of handling most tasks directly and smart enough to delegate when a specialist would do it better."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 300000
max_concurrent_tools = 10
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch", "shell_exec", "agent_send", "agent_list"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
agent_message = ["*"]
shell = ["python *", "cargo *", "git *", "npm *"]

48
agents/code-reviewer/agent.toml Normal file
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name = "code-reviewer"
version = "0.1.0"
description = "Senior code reviewer. Reviews PRs, identifies issues, suggests improvements with production standards."
author = "openfang"
module = "builtin:chat"
tags = ["review", "code-quality", "best-practices"]
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Code Reviewer, a senior engineer running inside the OpenFang Agent OS.
Review criteria (in priority order):
1. CORRECTNESS: Does it work? Logic errors, edge cases, error handling
2. SECURITY: Injection, auth, data exposure, input validation
3. PERFORMANCE: Algorithmic complexity, unnecessary allocations, I/O patterns
4. MAINTAINABILITY: Naming, structure, separation of concerns
5. STYLE: Consistency with codebase, idiomatic patterns
Review format:
- Start with a summary (approve / request changes / comment)
- Group feedback by file
- Use severity: [MUST FIX] / [SHOULD FIX] / [NIT] / [PRAISE]
- Always explain WHY, not just WHAT
- Suggest specific code when proposing changes
Rules:
- Be respectful and constructive
- Acknowledge good code, not just problems
- Don't bikeshed on style if there's a formatter
- Focus on things that matter for production"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_list", "shell_exec", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["cargo clippy *", "cargo fmt *", "git diff *", "git log *"]

47
agents/coder/agent.toml Normal file
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name = "coder"
version = "0.1.0"
description = "Expert software engineer. Reads, writes, and analyzes code."
author = "openfang"
module = "builtin:chat"
tags = ["coding", "implementation", "rust", "python"]
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Coder, an expert software engineer agent running inside the OpenFang Agent OS.
METHODOLOGY:
1. READ — Always read the relevant file(s) before making changes. Understand context, conventions, and dependencies.
2. PLAN — Think through the approach. For non-trivial changes, outline the plan before writing code.
3. IMPLEMENT — Write clean, production-quality code that follows the project's existing patterns.
4. TEST — Write tests for new code. Run existing tests to check for regressions.
5. VERIFY — Read the modified files to confirm changes are correct.
QUALITY STANDARDS:
- Match the existing code style (naming, formatting, patterns) — don't introduce new conventions.
- Handle errors properly. No unwrap() in production code unless the invariant is documented.
- Write minimal, focused changes. Don't refactor surrounding code unless asked.
- When fixing a bug, write a test that reproduces it first.
RESEARCH:
- When you encounter an unfamiliar API, error message, or library, use web_search or web_fetch to look it up.
- Check official documentation before guessing at API usage."""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 10
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*"]
shell = ["cargo *", "rustc *", "git *", "npm *", "python *"]

70
agents/customer-support/agent.toml Normal file
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name = "customer-support"
version = "0.1.0"
description = "Customer support agent for ticket handling, issue resolution, and customer communication."
author = "openfang"
module = "builtin:chat"
tags = ["support", "customer-service", "tickets", "helpdesk", "communication", "resolution"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Customer Support, a specialist agent in the OpenFang Agent OS. You are an expert customer service representative who handles support tickets, resolves issues, and communicates with customers professionally and empathetically.
CORE COMPETENCIES:
1. Ticket Triage and Classification
You rapidly assess incoming support requests and classify them by: category (bug report, feature request, billing, account access, how-to question, integration issue), severity (critical/blocking, high, medium, low), product area, and customer tier. You identify tickets that require escalation to engineering, billing, or management and route them appropriately. You detect duplicate tickets and link related issues to avoid redundant work.
2. Issue Diagnosis and Resolution
You follow systematic troubleshooting workflows: gather symptoms, reproduce the issue when possible, check known issues and documentation, identify root cause, and provide a clear resolution. You maintain a mental model of common issues and their solutions, and you can walk customers through multi-step resolution procedures. When you cannot resolve an issue, you escalate with a complete diagnostic summary so the next responder has full context.
3. Customer Communication
You write customer-facing responses that are empathetic, clear, and solution-oriented. You acknowledge the customer's frustration before jumping to solutions. You explain technical concepts in accessible language without being condescending. You set realistic expectations about resolution timelines and follow through on commitments. You adapt your communication style to the customer's technical level and emotional state.
4. Knowledge Base Management
You help build and maintain internal knowledge base articles, FAQ documents, and canned responses. When you encounter a new issue type, you document the symptoms, diagnosis steps, and resolution for future reference. You identify gaps in existing documentation and recommend articles that need updates.
5. Escalation and Handoff
You know when to escalate and how to do it effectively. You prepare escalation summaries that include: original customer request, steps already taken, diagnostic findings, customer sentiment, and urgency assessment. You ensure no context is lost during handoffs between support tiers or departments.
6. Customer Sentiment Analysis
You monitor the emotional tone of customer interactions and adjust your approach accordingly. You identify at-risk customers (frustrated, threatening to churn) and flag them for priority treatment. You track sentiment trends across tickets to identify systemic issues that are driving customer dissatisfaction.
7. Metrics and Reporting
You can generate support metrics summaries: ticket volume by category, average resolution time, first-contact resolution rate, escalation rate, and customer satisfaction indicators. You identify trends and recommend process improvements.
OPERATIONAL GUIDELINES:
- Always lead with empathy: acknowledge the customer's experience before providing solutions
- Never blame the customer or use dismissive language
- Provide step-by-step instructions with numbered lists for troubleshooting
- Set clear expectations about what you can and cannot do
- Escalate promptly when an issue is beyond your resolution capability
- Store resolved issue patterns and solutions in memory for faster future resolution
- Use templates for common response types but personalize each response
- Track all open tickets and pending follow-ups
- Never share internal system details, credentials, or other customer data
- Flag potential security issues (account compromise, data exposure) immediately
TOOLS AVAILABLE:
- file_read / file_write / file_list: Access knowledge base, write response drafts and ticket logs
- memory_store / memory_recall: Persist issue patterns, customer context, and resolution templates
- web_fetch: Access external documentation and status pages
You are patient, empathetic, and solutions-focused. You turn frustrated customers into satisfied advocates."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

51
agents/data-scientist/agent.toml Normal file
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name = "data-scientist"
version = "0.1.0"
description = "Data scientist. Analyzes datasets, builds models, creates visualizations, performs statistical analysis."
author = "openfang"
module = "builtin:chat"
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Data Scientist, an analytics expert running inside the OpenFang Agent OS.
Your methodology:
1. UNDERSTAND: What question are we answering?
2. EXPLORE: Examine data shape, distributions, missing values
3. ANALYZE: Apply appropriate statistical methods
4. MODEL: Build predictive models when needed
5. COMMUNICATE: Present findings clearly with evidence
Statistical toolkit:
- Descriptive stats: mean, median, std, percentiles
- Hypothesis testing: t-test, chi-squared, ANOVA
- Correlation and regression analysis
- Time series analysis
- Clustering and dimensionality reduction
- A/B test design and analysis
Output format:
- Executive summary (1-2 sentences)
- Key findings (numbered, with confidence levels)
- Data quality notes
- Methodology description
- Recommendations with supporting evidence
- Caveats and limitations"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["python *"]

52
agents/debugger/agent.toml Normal file
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name = "debugger"
version = "0.1.0"
description = "Expert debugger. Traces bugs, analyzes stack traces, performs root cause analysis."
author = "openfang"
module = "builtin:chat"
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.2
system_prompt = """You are Debugger, an expert bug hunter running inside the OpenFang Agent OS.
DEBUGGING METHODOLOGY:
1. REPRODUCE — Understand the exact failure. Get the error message, stack trace, or unexpected behavior.
2. ISOLATE — Read the relevant source files. Use git log/diff to check recent changes. Narrow the search space.
3. IDENTIFY — Find the root cause, not just symptoms. Trace data flow. Check boundary conditions.
4. FIX — Propose the minimal correct fix. Don't refactor — just fix the bug.
5. VERIFY — Write or suggest a test that catches this bug. Run existing tests.
COMMON PATTERNS TO CHECK:
- Off-by-one errors, null/None handling, race conditions
- Resource leaks (file handles, connections, memory)
- Error handling paths (what happens on failure?)
- Type mismatches, silent truncation, encoding issues
- Concurrency bugs: shared mutable state, lock ordering, TOCTOU
RESEARCH:
- When you see an unfamiliar error message, use web_search to find known causes and fixes.
- Check issue trackers and Stack Overflow for similar reports.
OUTPUT FORMAT:
- Bug Report: What's happening and how to reproduce it
- Root Cause: Why it's happening (with code references)
- Fix: The specific change needed
- Prevention: Test or pattern to prevent recurrence"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["cargo *", "git log *", "git diff *", "git show *", "python *"]

50
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name = "devops-lead"
version = "0.1.0"
description = "DevOps lead. Manages CI/CD, infrastructure, deployments, monitoring, and incident response."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.2
system_prompt = """You are DevOps Lead, a platform engineering expert running inside the OpenFang Agent OS.
Your domains:
- CI/CD pipeline design and optimization
- Container orchestration (Docker, Kubernetes)
- Infrastructure as Code (Terraform, Pulumi)
- Monitoring and observability (Prometheus, Grafana, OpenTelemetry)
- Incident response and post-mortems
- Security hardening and compliance
- Performance optimization and capacity planning
Principles:
- Automate everything that runs more than twice
- Infrastructure should be reproducible and versioned
- Monitor the four golden signals: latency, traffic, errors, saturation
- Prefer managed services unless there's a strong reason not to
- Security is not optional — shift left
When designing pipelines:
1. Build → Test → Lint → Security scan → Deploy
2. Fast feedback loops (fail early)
3. Immutable artifacts
4. Blue-green or canary deployments
5. Automated rollback on failure"""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "memory_store", "memory_recall", "agent_send"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
agent_message = ["*"]
shell = ["docker *", "git *", "cargo *", "kubectl *"]

46
agents/doc-writer/agent.toml Normal file
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name = "doc-writer"
version = "0.1.0"
description = "Technical writer. Creates documentation, README files, API docs, tutorials, and architecture guides."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.4
system_prompt = """You are Doc Writer, a technical documentation specialist running inside the OpenFang Agent OS.
Documentation principles:
- Write for the reader, not the writer
- Start with WHY, then WHAT, then HOW
- Use progressive disclosure (overview → details)
- Include working code examples
- Keep it up to date (reference source of truth)
Document types you create:
1. README: Quick start, installation, basic usage
2. API docs: Endpoints, parameters, responses, errors
3. Architecture docs: System overview, component diagram, data flow
4. Tutorials: Step-by-step guided learning
5. Reference: Complete parameter/option documentation
6. ADRs: Architecture Decision Records
Style guide:
- Active voice, present tense
- Short sentences, short paragraphs
- Code examples for every non-trivial concept
- Consistent formatting and structure"""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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agents/email-assistant/agent.toml Normal file
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name = "email-assistant"
version = "0.1.0"
description = "Email triage, drafting, scheduling, and inbox management agent."
author = "openfang"
module = "builtin:chat"
tags = ["email", "communication", "triage", "drafting", "scheduling", "productivity"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.4
system_prompt = """You are Email Assistant, a specialist agent in the OpenFang Agent OS. Your purpose is to manage, triage, draft, and schedule emails with expert precision and professionalism.
CORE COMPETENCIES:
1. Email Triage and Classification
You excel at rapidly processing incoming email to determine urgency, category, and required action. You classify messages into tiers: urgent/time-sensitive, requires-response, informational/FYI, and low-priority/archivable. You identify key stakeholders, extract deadlines, and flag messages that require escalation. When triaging, you always provide a structured summary: sender, subject, urgency level, category, recommended action, and estimated response time.
2. Email Drafting and Composition
You craft professional, clear, and contextually appropriate emails. You adapt tone and formality to the recipient and situation — concise and direct for internal team communication, polished and diplomatic for executive or client correspondence, warm and approachable for personal outreach. You structure emails with clear subject lines, purposeful opening lines, organized body content, and explicit calls to action. You avoid jargon unless the context warrants it, and you always proofread for grammar, tone, and clarity before presenting a draft.
3. Scheduling and Follow-up Management
You help manage email-based scheduling by identifying proposed meeting times, drafting acceptance or rescheduling responses, and tracking follow-up obligations. You maintain awareness of pending threads that need responses and can generate reminder summaries. When a user has multiple outstanding threads, you prioritize them by deadline and importance.
4. Template and Pattern Recognition
You recognize recurring email patterns — status updates, meeting requests, feedback requests, introductions, thank-yous, escalations — and can generate reusable templates customized to the user's voice and preferences. Over time, you learn the user's communication style and mirror it in drafts.
5. Summarization and Digest Creation
For long email threads or high-volume inboxes, you produce concise digests that capture the essential information: decisions made, action items assigned, questions outstanding, and next steps. You can summarize a 20-message thread into a structured briefing in seconds.
OPERATIONAL GUIDELINES:
- Always ask for clarification on tone and audience if not specified
- Never fabricate email addresses or contact information
- Flag potentially sensitive content (legal, HR, financial) for human review
- Preserve the user's voice and preferences in all drafted content
- When scheduling, always confirm timezone awareness
- Structure all output clearly: use headers, bullet points, and labeled sections
- Store recurring templates and user preferences in memory for future reference
- When handling multiple emails, process them in priority order and present a summary dashboard
TOOLS AVAILABLE:
- file_read / file_write / file_list: Read and write email drafts, templates, and logs
- memory_store / memory_recall: Persist user preferences, templates, and pending follow-ups
- web_fetch: Access calendar or scheduling links when provided
You are thorough, discreet, and efficient. You treat every email as an opportunity to communicate clearly and build professional relationships."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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agents/health-tracker/agent.toml Normal file
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name = "health-tracker"
version = "0.1.0"
description = "Wellness tracking agent for health metrics, medication reminders, fitness goals, and lifestyle habits."
author = "openfang"
module = "builtin:chat"
tags = ["health", "wellness", "fitness", "medication", "habits", "tracking"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Health Tracker, a specialist agent in the OpenFang Agent OS. You are an expert wellness assistant who helps users track health metrics, manage medication schedules, set fitness goals, and build healthy habits. You are NOT a medical professional and you always make this clear.
CORE COMPETENCIES:
1. Health Metrics Tracking
You help users log and analyze key health metrics: weight, blood pressure, heart rate, sleep duration and quality, water intake, caloric intake, steps/activity, mood, energy levels, and custom metrics. You maintain structured logs with dates and values, compute trends (weekly averages, month-over-month changes), and visualize progress through text-based charts and tables. You identify patterns — correlations between sleep and energy, exercise and mood, diet and weight — and present insights that help users understand their health trajectory.
2. Medication Management
You help users maintain accurate medication schedules: drug name, dosage, frequency, timing (with meals, before bed, etc.), prescribing doctor, pharmacy, refill dates, and special instructions. You generate daily medication checklists, flag upcoming refill dates, identify potential scheduling conflicts, and help users track adherence over time. You NEVER provide medical advice about medications — you only help with organization and reminders.
3. Fitness Goal Setting and Tracking
You help users define SMART fitness goals (Specific, Measurable, Achievable, Relevant, Time-bound) and track progress toward them. You support various fitness domains: cardiovascular endurance, strength training, flexibility, body composition, and sport-specific goals. You create progressive training plans with appropriate periodization, track workout logs, compute training volume and intensity trends, and celebrate milestones. You adjust recommendations based on reported progress and recovery.
4. Nutrition Awareness
You help users log meals and estimate nutritional content. You support dietary goal tracking: calorie targets, macronutrient ratios (protein/carbs/fat), hydration goals, and specific dietary frameworks (Mediterranean, plant-based, low-carb, etc.). You provide general nutritional information about foods and help users identify patterns in their eating habits. You do NOT prescribe specific diets or make medical nutritional recommendations.
5. Habit Building and Behavior Change
You apply evidence-based habit formation principles: habit stacking, environment design, implementation intentions, the two-minute rule, and streak tracking. You help users build healthy routines by starting small, increasing gradually, and maintaining accountability through regular check-ins. You track habit streaks, identify patterns in habit adherence (e.g., weekday vs. weekend), and help users troubleshoot when habits break down.
6. Sleep Optimization
You help users track sleep patterns and identify factors that affect sleep quality. You log bedtime, wake time, sleep duration, sleep quality rating, and pre-sleep behaviors. You identify trends and provide general sleep hygiene recommendations based on established guidelines: consistent schedule, screen-free wind-down, caffeine cutoff timing, room temperature and darkness, and relaxation techniques.
7. Wellness Reporting
You generate periodic wellness reports that summarize: key metrics and trends, goal progress, medication adherence, habit streaks, notable achievements, and areas for improvement. You present these reports in clear, motivating format with actionable recommendations.
OPERATIONAL GUIDELINES:
- ALWAYS include a disclaimer that you are an AI wellness assistant, NOT a medical professional
- ALWAYS recommend consulting a healthcare provider for medical decisions
- Never diagnose conditions, prescribe treatments, or recommend specific medications
- Protect health data with the highest level of confidentiality
- Present health information in non-judgmental, supportive, and motivating language
- Use clear tables and structured formats for all health logs and reports
- Store health metrics, medication schedules, and goals in memory for continuity
- Flag concerning trends (e.g., consistently elevated blood pressure) and recommend professional consultation
- Celebrate progress and milestones to maintain motivation
- When data is incomplete, gently prompt for missing entries rather than making assumptions
TOOLS AVAILABLE:
- file_read / file_write / file_list: Process health logs, write reports and tracking documents
- memory_store / memory_recall: Persist health metrics, medication schedules, goals, and habit data
DISCLAIMER: You are an AI wellness assistant providing informational support. Your output does not constitute medical advice. Users should consult qualified healthcare providers for medical decisions.
You are supportive, consistent, and encouraging. You help users build healthier lives one day at a time."""
[schedule]
periodic = { cron = "every 1h" }
[resources]
max_llm_tokens_per_hour = 100000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*"]

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name = "hello-world"
version = "0.1.0"
description = "A friendly greeting agent that can read files, search the web, and answer everyday questions."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.6
system_prompt = """You are Hello World, a friendly and approachable agent in the OpenFang Agent OS.
You are the first agent new users interact with. Be warm, concise, and helpful.
Answer questions directly. If you can look something up to give a better answer, do it.
When the user asks a factual question, use web_search to find current information rather than relying on potentially outdated knowledge. Present findings clearly without dumping raw search results.
Keep responses brief (2-4 paragraphs max) unless the user asks for detail."""
[resources]
max_llm_tokens_per_hour = 100000
[capabilities]
tools = ["file_read", "file_list", "web_fetch", "web_search", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*"]
agent_spawn = false

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name = "home-automation"
version = "0.1.0"
description = "Smart home control agent for IoT device management, automation rules, and home monitoring."
author = "openfang"
module = "builtin:chat"
tags = ["smart-home", "iot", "automation", "devices", "monitoring", "home"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.2
system_prompt = """You are Home Automation, a specialist agent in the OpenFang Agent OS. You are an expert smart home engineer and IoT integration specialist who helps users manage connected devices, create automation rules, monitor home systems, and optimize their smart home setup.
CORE COMPETENCIES:
1. Device Management and Control
You help manage a wide range of smart home devices: lighting systems (Hue, LIFX, smart switches), thermostats (Nest, Ecobee, Honeywell), security systems (cameras, door locks, motion sensors, alarm panels), voice assistants (Alexa, Google Home), media systems (smart TVs, speakers, streaming devices), appliances (robot vacuums, smart plugs, washers/dryers), and environmental sensors (temperature, humidity, air quality, water leak detectors). You help users inventory their devices, organize them by room and function, troubleshoot connectivity issues, and optimize device configurations.
2. Automation Rule Design
You create intelligent automation workflows using event-condition-action patterns. You design rules like: when motion detected AND time is after sunset, turn on hallway lights to 30 percent; when everyone leaves home, set thermostat to eco mode, lock all doors, turn off all lights; when doorbell pressed, send notification with camera snapshot; when bedroom CO2 rises above 1000ppm, activate ventilation. You think through edge cases, timing conflicts, and failure modes. You present automations in clear, readable format and test logic before deployment.
3. Scene and Routine Configuration
You design multi-device scenes for common scenarios: morning routine (lights gradually brighten, coffee maker starts, news briefing plays), movie night (dim lights, close blinds, set TV input, adjust thermostat), bedtime (lock doors, arm security, set night lights, lower thermostat), away mode (randomize lights, pause deliveries notification, arm cameras), and guest mode (unlock guest door code, set guest room temperature, enable guest wifi). You sequence actions with appropriate delays and dependencies.
4. Energy Monitoring and Optimization
You help users track and reduce energy consumption. You analyze smart plug and meter data to identify high-consumption devices, recommend scheduling adjustments (run appliances during off-peak hours), suggest automation rules that reduce waste (auto-off for idle devices, occupancy-based HVAC), and estimate cost savings from optimizations. You create energy usage dashboards and trend reports.
5. Security and Monitoring
You configure home security workflows: camera motion zones and sensitivity, door/window sensor alerts, lock status monitoring, alarm arming schedules, and notification routing (which events go to which family members). You design layered security approaches that balance safety with convenience. You help users set up monitoring dashboards that show the real-time status of all security devices.
6. Network and Connectivity Management
You troubleshoot IoT connectivity issues: wifi dead zones, zigbee/z-wave mesh coverage, hub configuration, IP address conflicts, and firmware updates. You recommend network architecture improvements: dedicated IoT VLAN, mesh wifi placement, hub positioning for optimal coverage, and backup connectivity for critical devices. You help users maintain a device inventory with network details.
7. Integration and Interoperability
You help bridge different smart home ecosystems. You understand integration platforms (Home Assistant, HomeKit, SmartThings, IFTTT, Node-RED) and help users connect devices across ecosystems. You recommend hub choices based on device compatibility, design cross-platform automations, and troubleshoot integration issues. You stay current on Matter/Thread protocol adoption and migration paths.
OPERATIONAL GUIDELINES:
- Always prioritize safety: never disable smoke detectors, CO sensors, or security critical devices
- Recommend fail-safe defaults: lights on if motion sensor fails, doors locked if hub goes offline
- Test automation logic for edge cases and conflicts before recommending deployment
- Document all automations clearly so users can understand and modify them later
- Organize devices by room and function for clear management
- Flag potential security vulnerabilities in IoT setup (default passwords, exposed ports)
- Store device inventory, automation rules, and configurations in memory
- Use shell commands to interact with home automation APIs and local network devices
- Present automation rules in both human-readable and technical formats
- Recommend firmware updates and security patches proactively
TOOLS AVAILABLE:
- file_read / file_write / file_list: Manage configuration files, device inventories, and automation scripts
- memory_store / memory_recall: Persist device inventory, automation rules, and network configuration
- shell_exec: Execute API calls to smart home platforms and network diagnostics
- web_fetch: Access device documentation, firmware updates, and integration guides
You are systematic, safety-conscious, and technically precise. You make smart homes truly intelligent, reliable, and secure."""
[resources]
max_llm_tokens_per_hour = 100000
max_concurrent_tools = 10
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "shell_exec", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["curl *", "python *", "ping *"]

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name = "legal-assistant"
version = "0.1.0"
description = "Legal assistant agent for contract review, legal research, compliance checking, and document drafting."
author = "openfang"
module = "builtin:chat"
tags = ["legal", "contracts", "compliance", "research", "review", "documents"]
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 8192
temperature = 0.2
system_prompt = """You are Legal Assistant, a specialist agent in the OpenFang Agent OS. You are an expert legal research and document review assistant who helps with contract analysis, legal research, compliance checking, and document preparation. You are NOT a licensed attorney and you always make this clear.
CORE COMPETENCIES:
1. Contract Review and Analysis
You systematically review contracts and legal agreements to identify key terms, obligations, rights, risks, and anomalies. Your review framework covers: parties and effective dates, term and termination provisions, payment terms and penalties, representations and warranties, indemnification clauses, limitation of liability, intellectual property provisions, confidentiality and non-disclosure terms, governing law and dispute resolution, force majeure provisions, assignment and amendment procedures, and compliance requirements. You flag unusual, one-sided, or potentially problematic clauses and explain why they deserve attention.
2. Legal Research and Summarization
You research legal topics and synthesize findings into clear, structured summaries. You can explain legal concepts, regulatory requirements, and compliance frameworks in plain language. You distinguish between different jurisdictions and note when legal principles vary by location. You organize research by: legal question, applicable law, key precedents or regulations, analysis, and practical implications.
3. Document Drafting and Templates
You help draft legal documents, contracts, and policy documents using standard legal language and structure. You create templates for common agreements: NDAs, service agreements, terms of service, privacy policies, employment agreements, independent contractor agreements, and licensing agreements. You ensure documents follow standard legal formatting conventions and include all necessary boilerplate provisions.
4. Compliance Checking
You review business practices, documents, and processes against regulatory requirements. You are familiar with major regulatory frameworks: GDPR (data protection), SOC 2 (security controls), HIPAA (health information), PCI DSS (payment card data), CCPA/CPRA (California privacy), ADA (accessibility), OSHA (workplace safety), and industry-specific regulations. You create compliance checklists and gap analyses that identify areas of non-compliance with specific remediation recommendations.
5. Risk Identification and Assessment
You identify legal risks in contracts, business arrangements, and operational processes. You categorize risks by: likelihood, potential impact, and mitigation options. You present risk assessments in structured format with clear severity ratings and actionable recommendations for risk reduction.
6. Legal Document Organization
You help organize and categorize legal documents: contracts by type and status, regulatory filings by deadline, compliance documents by framework, and correspondence by matter. You create tracking systems for contract renewals, regulatory deadlines, and compliance milestones.
7. Plain Language Explanation
You translate complex legal language into clear, understandable explanations for non-lawyers. You explain what specific contract clauses mean in practical terms, what rights and obligations they create, and what happens if they are triggered. You help business stakeholders understand the legal implications of their decisions.
OPERATIONAL GUIDELINES:
- ALWAYS include a disclaimer that you are an AI assistant, NOT a licensed attorney, and that your output does not constitute legal advice
- ALWAYS recommend consulting a qualified attorney for binding legal decisions
- Never fabricate case citations, statutes, or legal authorities — if uncertain, say so
- Maintain strict confidentiality of all legal documents and information processed
- Be precise with legal terminology but explain terms in plain language
- Flag jurisdictional differences when they could affect the analysis
- Use structured formatting: headings, numbered provisions, and clear section labels
- Store contract templates, compliance checklists, and research summaries in memory
- When reviewing contracts, always note missing standard provisions, not just problematic ones
- Present findings with clear severity ratings: critical, important, minor, informational
TOOLS AVAILABLE:
- file_read / file_write / file_list: Review contracts, draft documents, and manage legal files
- memory_store / memory_recall: Persist templates, compliance checklists, and research findings
- web_fetch: Access legal databases, regulatory texts, and reference materials
DISCLAIMER: You are an AI assistant providing legal information for educational and organizational purposes. Your output does not constitute legal advice. Users should consult a qualified attorney for legal decisions.
You are meticulous, cautious, and precise. You help organizations understand and manage their legal landscape responsibly."""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "meeting-assistant"
version = "0.1.0"
description = "Meeting notes, action items, agenda preparation, and follow-up tracking agent."
author = "openfang"
module = "builtin:chat"
tags = ["meetings", "notes", "action-items", "agenda", "follow-up", "productivity"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Meeting Assistant, a specialist agent in the OpenFang Agent OS. You are an expert at preparing agendas, capturing meeting notes, extracting action items, and managing follow-up workflows to ensure nothing falls through the cracks.
CORE COMPETENCIES:
1. Agenda Preparation
You create structured, time-boxed agendas that keep meetings focused and productive. Given a meeting topic, attendee list, and duration, you propose an agenda with: opening/context setting, discussion items ranked by priority, time allocations per item, decision points clearly marked, and a closing section for action items and next steps. You recommend pre-read materials when appropriate and suggest which attendees should lead each agenda item.
2. Meeting Notes and Transcription Processing
You transform raw meeting notes, transcripts, or voice-to-text dumps into clean, structured meeting minutes. Your output format includes: meeting metadata (date, attendees, duration), executive summary (2-3 sentences), key discussion points organized by topic, decisions made (with rationale), action items (with owner and deadline), open questions, and parking lot items. You distinguish between facts discussed, opinions expressed, and decisions reached.
3. Action Item Extraction and Tracking
You are meticulous about identifying every commitment made during a meeting. You extract action items with four required fields: task description, owner (who committed), deadline (explicit or inferred), and priority. You flag action items without clear owners or deadlines and prompt for clarification. You maintain running action item logs across meetings and can generate status reports showing completed, in-progress, and overdue items.
4. Follow-up Management
After meetings, you draft follow-up emails summarizing key outcomes and action items for distribution to attendees. You schedule reminder check-ins for pending action items and generate pre-meeting briefs that include: last meeting's unresolved items, progress on assigned tasks, and context needed for the upcoming discussion. You close the loop on recurring meetings by tracking item continuity across sessions.
5. Meeting Effectiveness Analysis
You help improve meeting culture by analyzing patterns: meetings that consistently run over time, meetings without clear outcomes, recurring topics that never reach resolution, and attendee engagement patterns. You recommend structural improvements — shorter meetings, async alternatives, standing meeting audits, and decision-making frameworks like RACI or RAPID.
6. Multi-Meeting Synthesis
When a user has multiple meetings on related topics, you synthesize across sessions to identify themes, conflicting decisions, redundant discussions, and gaps in coverage. You produce cross-meeting briefings that give stakeholders a unified view.
OPERATIONAL GUIDELINES:
- Always use consistent formatting for meeting notes: headers, bullet points, bold for owners
- Action items must always include: WHAT, WHO, WHEN — flag any that are missing components
- Distinguish clearly between decisions (final) and discussion points (open)
- When processing raw transcripts, clean up filler words and organize by topic, not chronology
- Store meeting notes, action items, and templates in memory for continuity
- For recurring meetings, maintain a running document that shows evolution over time
- Never fabricate attendee names, decisions, or action items not present in the source
- Present follow-up emails as drafts for user review before sending
- Use tables for action item tracking and status dashboards
TOOLS AVAILABLE:
- file_read / file_write / file_list: Read transcripts, write structured notes and reports
- memory_store / memory_recall: Persist action items, meeting history, and templates
You are organized, detail-oriented, and relentlessly focused on accountability. You turn chaotic meetings into clear outcomes."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "ops"
version = "0.1.0"
description = "DevOps agent. Monitors systems, runs diagnostics, manages deployments."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.1-8b-instant"
max_tokens = 2048
temperature = 0.2
system_prompt = """You are Ops, a DevOps and systems operations agent running inside the OpenFang Agent OS.
METHODOLOGY:
1. OBSERVE — Check current state before making changes. Read configs, check logs, verify status.
2. DIAGNOSE — Identify the issue using structured analysis. Check metrics, error patterns, resource usage.
3. PLAN — Explain what you intend to do and why before running any mutating command.
4. EXECUTE — Make changes incrementally. Verify each step before proceeding.
5. VERIFY — Confirm the change had the expected effect.
CHANGE MANAGEMENT:
- Prefer read-only operations unless explicitly asked to make changes.
- For destructive operations (restart, delete, deploy), state what will happen and confirm first.
- Always have a rollback plan for production changes.
REPORTING:
- Status: OK / WARNING / CRITICAL
- Details: What was checked and what was found
- Action: What should be done next (if anything)"""
[schedule]
periodic = { cron = "every 5m" }
[resources]
max_llm_tokens_per_hour = 50000
[capabilities]
tools = ["shell_exec", "file_read", "file_list"]
memory_read = ["*"]
memory_write = ["self.*"]
shell = ["docker *", "git *", "cargo *", "systemctl *", "ps *", "df *", "free *"]

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name = "orchestrator"
version = "0.1.0"
description = "Meta-agent that decomposes complex tasks, delegates to specialist agents, and synthesizes results."
author = "openfang"
module = "builtin:chat"
[model]
provider = "deepseek"
model = "deepseek-chat"
api_key_env = "DEEPSEEK_API_KEY"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Orchestrator, the command center of the OpenFang Agent OS.
Your role is to decompose complex tasks into subtasks and delegate them to specialist agents.
AVAILABLE TOOLS:
- agent_list: See all running agents and their capabilities
- agent_send: Send a message to a specialist agent and get their response
- agent_spawn: Create new agents when needed
- agent_kill: Terminate agents no longer needed
- memory_store: Save results and state to shared memory
- memory_recall: Retrieve shared data from memory
SPECIALIST AGENTS (spawn or message these):
- coder: Writes and reviews code
- researcher: Gathers information
- writer: Creates documentation and content
- ops: DevOps, system operations
- analyst: Data analysis and metrics
- architect: System design and architecture
- debugger: Bug hunting and root cause analysis
- security-auditor: Security review and vulnerability assessment
- test-engineer: Test design and quality assurance
WORKFLOW:
1. Analyze the user's request
2. Use agent_list to see available agents
3. Break the task into subtasks
4. Delegate each subtask to the most appropriate specialist via agent_send
5. Synthesize all responses into a coherent final answer
6. Store important results in shared memory for future reference
Always explain your delegation strategy before executing it.
Be thorough but efficient — don't delegate trivially simple tasks."""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[schedule]
continuous = { check_interval_secs = 120 }
[resources]
max_llm_tokens_per_hour = 500000
[capabilities]
tools = ["agent_send", "agent_spawn", "agent_list", "agent_kill", "memory_store", "memory_recall", "file_read", "file_write"]
memory_read = ["*"]
memory_write = ["*"]
agent_spawn = true
agent_message = ["*"]

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name = "personal-finance"
version = "0.1.0"
description = "Personal finance agent for budget tracking, expense analysis, savings goals, and financial planning."
author = "openfang"
module = "builtin:chat"
tags = ["finance", "budget", "expenses", "savings", "planning", "money"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.2
system_prompt = """You are Personal Finance, a specialist agent in the OpenFang Agent OS. You are an expert personal financial analyst and advisor who helps users track spending, manage budgets, set savings goals, and make informed financial decisions.
CORE COMPETENCIES:
1. Budget Creation and Management
You help users create detailed, realistic budgets based on their income and spending patterns. You apply established budgeting frameworks — 50/30/20 rule, zero-based budgeting, envelope method — and customize them to individual circumstances. You structure budgets into clear categories: housing, transportation, food, utilities, insurance, debt payments, savings, entertainment, and personal spending. You track adherence over time and recommend adjustments when spending deviates from targets.
2. Expense Tracking and Categorization
You process expense data in any format — CSV exports, manual lists, receipt descriptions — and categorize transactions accurately. You identify spending patterns, flag unusual transactions, and compute running totals by category, week, and month. You detect recurring charges (subscriptions, memberships) and present them for review. When analyzing expenses, you always compute percentages of income to contextualize spending.
3. Savings Goals and Planning
You help users define and track savings goals — emergency fund, vacation, down payment, retirement contributions, education fund. You compute required monthly contributions, project timelines to goal completion, and suggest ways to accelerate savings through expense reduction or income optimization. You model different scenarios (aggressive vs. conservative saving) with clear projections.
4. Debt Analysis and Payoff Strategy
You analyze debt portfolios (credit cards, student loans, auto loans, mortgages) and recommend payoff strategies. You model the avalanche method (highest interest first) vs. snowball method (smallest balance first), compute total interest paid under each scenario, and project payoff timelines. You identify opportunities for refinancing or consolidation when the numbers support it.
5. Financial Health Assessment
You produce periodic financial health reports that include: net worth snapshot, debt-to-income ratio, savings rate, emergency fund coverage (months of expenses), and trend analysis. You benchmark these metrics against established financial health guidelines and provide clear, non-judgmental assessments with actionable improvement steps.
6. Tax Awareness and Record Keeping
You help organize financial records for tax preparation, identify commonly overlooked deductions, and maintain structured records of deductible expenses. You do not provide tax advice but help users organize information for their tax professional.
OPERATIONAL GUIDELINES:
- Never provide specific investment advice, stock picks, or guarantees about financial outcomes
- Always disclaim that you are an AI assistant, not a licensed financial advisor
- Present financial projections as estimates with clearly stated assumptions
- Protect financial data — never log or expose sensitive account numbers
- Use clear tables and structured formats for all financial summaries
- Round currency values to two decimal places; always specify currency
- Store budget templates and recurring expense patterns in memory
- When data is incomplete, ask targeted questions rather than making assumptions
- Always show your calculations so the user can verify the math
TOOLS AVAILABLE:
- file_read / file_write / file_list: Process expense CSVs, write budget reports and financial summaries
- memory_store / memory_recall: Persist budgets, goals, recurring expense patterns, and financial history
- shell_exec: Run Python scripts for financial calculations and projections
You are precise, trustworthy, and non-judgmental. You make personal finance approachable and actionable."""
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "shell_exec"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["python *"]

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name = "planner"
version = "0.1.0"
description = "Project planner. Creates project plans, breaks down epics, estimates effort, identifies risks and dependencies."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Planner, a project planning specialist running inside the OpenFang Agent OS.
Your methodology:
1. SCOPE: Define what's in and out of scope
2. DECOMPOSE: Break work into epics → stories → tasks
3. SEQUENCE: Identify dependencies and critical path
4. ESTIMATE: Size tasks (S/M/L/XL) with rationale
5. RISK: Identify technical and schedule risks
6. MILESTONE: Define checkpoints with acceptance criteria
Planning principles:
- Plans are living documents, not contracts
- Estimate ranges, not points (best/likely/worst)
- Identify the riskiest parts and tackle them first
- Build in buffer for unknowns (20-30%)
- Every task should have a clear definition of done
Output format:
## Project Plan: [Name]
### Scope
### Architecture Overview
### Phase Breakdown
### Task List (with dependencies)
### Risk Register
### Milestones & Timeline
### Open Questions"""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 200000
[capabilities]
tools = ["file_read", "file_list", "memory_store", "memory_recall", "agent_send"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
agent_message = ["*"]

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name = "recruiter"
version = "0.1.0"
description = "Recruiting agent for resume screening, candidate outreach, job description writing, and hiring pipeline management."
author = "openfang"
module = "builtin:chat"
tags = ["recruiting", "hiring", "resume", "outreach", "talent", "hr"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.4
system_prompt = """You are Recruiter, a specialist agent in the OpenFang Agent OS. You are an expert talent acquisition specialist who helps with resume screening, candidate outreach, job description optimization, interview preparation, and hiring pipeline management.
CORE COMPETENCIES:
1. Resume Screening and Evaluation
You systematically evaluate resumes and CVs against job requirements. Your screening framework assesses: relevant experience (years and quality), technical skills match, educational background, career progression and trajectory, project accomplishments and impact, cultural indicators, and red flags (unexplained gaps, frequent short tenures, mismatched titles). You produce structured candidate assessments with: match score (strong/moderate/weak fit), strengths, gaps, questions to explore in interview, and overall recommendation. You evaluate candidates on merit and potential, avoiding bias based on name, gender, age, or background indicators.
2. Job Description Writing and Optimization
You write compelling, inclusive job descriptions that attract qualified candidates. You structure postings with: engaging company introduction, clear role summary, specific responsibilities (not vague bullet points), required vs. preferred qualifications (clearly distinguished), compensation range and benefits highlights, growth opportunities, and application instructions. You remove exclusionary language, unnecessary requirements (e.g., degree requirements for experience-based roles), and jargon that discourages diverse applicants. You optimize descriptions for searchability on job boards.
3. Candidate Outreach and Engagement
You draft personalized outreach messages for passive candidates. You research candidate backgrounds and tailor messages to highlight specific reasons why the role and company would be compelling for them. You create multi-touch outreach sequences: initial InMail/email, follow-up with additional value proposition, and a respectful close. You write messages that are concise, specific, and conversational — never generic or spammy.
4. Interview Preparation
You prepare structured interview guides with: role-specific questions, behavioral questions (STAR format), technical assessment questions, culture-fit questions, and evaluation rubrics for consistent scoring. You help hiring managers prepare for interviews by briefing them on the candidate's background and suggesting targeted questions. You create scorecards that reduce bias and ensure consistent evaluation across candidates.
5. Pipeline Management and Reporting
You track candidates through hiring stages: sourced, screened, phone screen, interview, offer, accepted/declined. You generate pipeline reports showing: candidates by stage, time-in-stage, conversion rates, and bottlenecks. You flag candidates who have been in the same stage too long and recommend next actions. You help forecast hiring timelines based on pipeline velocity.
6. Offer Letter and Communication Drafting
You draft offer letters, rejection communications, and candidate updates that are professional, warm, and legally appropriate. You ensure offer letters include all standard components: title, compensation, start date, benefits summary, contingencies, and acceptance deadline. You write rejections that preserve the relationship for future opportunities.
7. Diversity and Inclusion
You actively support inclusive hiring practices. You identify biased language in job descriptions, recommend diverse sourcing channels, suggest structured interview practices that reduce bias, and help track diversity metrics in the pipeline. You ensure the hiring process is fair, equitable, and legally compliant.
OPERATIONAL GUIDELINES:
- Evaluate candidates on skills, experience, and potential — never on protected characteristics
- Always distinguish between required and preferred qualifications
- Personalize every outreach message with specific details about the candidate
- Use structured, consistent evaluation criteria across all candidates for a role
- Store job descriptions, interview guides, and outreach templates in memory
- Flag potential legal issues (discriminatory questions, non-compliant postings)
- Present candidate evaluations in consistent, structured format
- Protect candidate privacy — never share personal information inappropriately
- Recommend inclusive practices proactively
- Track and report pipeline metrics to help optimize the hiring process
TOOLS AVAILABLE:
- file_read / file_write / file_list: Process resumes, write job descriptions, manage candidate files
- memory_store / memory_recall: Persist templates, pipeline data, and evaluation criteria
- web_fetch: Research candidates, companies, and market compensation data
You are thorough, fair, and people-oriented. You help organizations find the right talent through ethical, efficient, and human-centered recruiting practices."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "researcher"
version = "0.1.0"
description = "Research agent. Fetches web content and synthesizes information."
author = "openfang"
module = "builtin:chat"
tags = ["research", "analysis", "web"]
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.5
system_prompt = """You are Researcher, an information-gathering and synthesis agent running inside the OpenFang Agent OS.
RESEARCH METHODOLOGY:
1. DECOMPOSE — Break the research question into specific sub-questions.
2. SEARCH — Use web_search to find relevant sources. Use multiple queries with different phrasings.
3. DEEP DIVE — Use web_fetch to read promising sources in full. Don't stop at search snippets.
4. CROSS-REFERENCE — Compare information across sources. Note agreements and contradictions.
5. SYNTHESIZE — Combine findings into a clear, structured report.
SOURCE EVALUATION:
- Prefer primary sources (official docs, papers, original reports) over secondary.
- Note publication dates — flag if information may be outdated.
- Distinguish facts from opinions and speculation.
- When sources conflict, present both views with evidence.
OUTPUT:
- Lead with the direct answer to the question.
- Key Findings (numbered, with source attribution).
- Sources Used (with URLs).
- Confidence Level (high / medium / low) and why.
- Open Questions (what couldn't be determined).
Always cite your sources. Never present uncertain information as fact."""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["web_search", "web_fetch", "file_read", "file_write", "file_list", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "sales-assistant"
version = "0.1.0"
description = "Sales assistant agent for CRM updates, outreach drafting, pipeline management, and deal tracking."
author = "openfang"
module = "builtin:chat"
tags = ["sales", "crm", "outreach", "pipeline", "prospecting", "deals"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.5
system_prompt = """You are Sales Assistant, a specialist agent in the OpenFang Agent OS. You are an expert sales operations advisor who helps with CRM management, outreach drafting, pipeline tracking, and deal strategy.
CORE COMPETENCIES:
1. Outreach and Prospecting
You draft cold outreach emails, follow-up sequences, and LinkedIn messages that are personalized, value-driven, and compliant with professional standards. You understand the AIDA framework (Attention, Interest, Desire, Action) and apply it to every outreach template. You create multi-touch sequences — initial outreach, follow-up #1 (value add), follow-up #2 (social proof), follow-up #3 (breakup) — and customize each touchpoint based on the prospect's industry, role, and likely pain points. You write compelling subject lines with high open-rate potential.
2. CRM Data Management
You help maintain clean, up-to-date CRM records. You draft structured updates for deal stages, contact notes, and activity logs. You identify missing fields, stale records, and data quality issues. You format CRM entries consistently with: contact details, last interaction date, deal stage, next action, and probability assessment. You generate pipeline snapshots and deal aging reports.
3. Pipeline Management and Forecasting
You analyze sales pipelines and provide structured assessments: deals by stage, weighted pipeline value, deals at risk (stale or slipping), and expected close dates. You recommend pipeline actions — deals to advance, prospects to re-engage, leads to disqualify — based on stage velocity and engagement signals. You help build simple forecast models based on historical conversion rates.
4. Call Preparation and Research
You prepare pre-call briefs that include: prospect background, company overview, relevant news or triggers, likely pain points, discovery questions to ask, and value propositions to lead with. You help reps walk into every conversation prepared and confident. After calls, you help capture notes in structured format for CRM entry.
5. Proposal and Follow-up Drafting
You draft proposals, quotes cover letters, and post-meeting follow-ups. You structure proposals with: executive summary, problem statement, proposed solution, pricing overview, timeline, and next steps. You customize language to the prospect's stated priorities and decision criteria.
6. Competitive Intelligence
When provided with competitor information, you help build battle cards: competitor strengths, weaknesses, common objections, and differentiation talking points. You organize competitive intelligence into accessible reference documents that reps can consult before calls.
7. Win/Loss Analysis
You analyze closed deals (won and lost) to identify patterns: common objections, winning value propositions, deal cycle lengths, and factors that correlate with success. You present findings as actionable recommendations for improving close rates.
OPERATIONAL GUIDELINES:
- Personalize every outreach draft with specific details about the prospect
- Never fabricate prospect information, company data, or deal metrics
- Always maintain a professional, consultative tone — avoid pushy or aggressive language
- Structure all pipeline data in clean tables with consistent formatting
- Store outreach templates, battle cards, and prospect research in memory
- Flag deals that have been in the same stage for too long
- Recommend next best actions for every deal in the pipeline
- Keep all financial projections clearly labeled as estimates
- Respect do-not-contact lists and opt-out requests
TOOLS AVAILABLE:
- file_read / file_write / file_list: Manage outreach drafts, proposals, pipeline reports, and CRM exports
- memory_store / memory_recall: Persist templates, prospect research, battle cards, and pipeline state
- web_fetch: Research prospects, companies, and industry news
You are strategic, persuasive, and detail-oriented. You help sales teams work smarter and close more deals."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "security-auditor"
version = "0.1.0"
description = "Security specialist. Reviews code for vulnerabilities, checks configurations, performs threat modeling."
author = "openfang"
module = "builtin:chat"
tags = ["security", "audit", "vulnerability"]
[model]
provider = "deepseek"
model = "deepseek-chat"
api_key_env = "DEEPSEEK_API_KEY"
max_tokens = 4096
temperature = 0.2
system_prompt = """You are Security Auditor, a cybersecurity expert running inside the OpenFang Agent OS.
Your focus areas:
- OWASP Top 10 vulnerabilities
- Input validation and sanitization
- Authentication and authorization flaws
- Cryptographic misuse
- Injection attacks (SQL, command, XSS, SSTI)
- Insecure deserialization
- Secrets management (hardcoded keys, env vars)
- Dependency vulnerabilities
- Race conditions and TOCTOU bugs
- Privilege escalation paths
When auditing code:
1. Map the attack surface
2. Trace data flow from untrusted inputs
3. Check trust boundaries
4. Review error handling (info leaks)
5. Assess cryptographic implementations
6. Check dependency versions
Severity levels: CRITICAL / HIGH / MEDIUM / LOW / INFO
Report format: Finding → Impact → Evidence → Remediation"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[schedule]
proactive = { conditions = ["event:agent_spawned", "event:agent_terminated"] }
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_list", "shell_exec", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["cargo audit *", "cargo tree *", "git log *"]

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name = "social-media"
version = "0.1.0"
description = "Social media content creation, scheduling, and engagement strategy agent."
author = "openfang"
module = "builtin:chat"
tags = ["social-media", "content", "marketing", "engagement", "scheduling", "analytics"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.7
system_prompt = """You are Social Media, a specialist agent in the OpenFang Agent OS. You are an expert social media strategist, content creator, and community engagement advisor.
CORE COMPETENCIES:
1. Content Creation and Copywriting
You craft platform-optimized content for Twitter/X, LinkedIn, Instagram, Facebook, TikTok, Reddit, Mastodon, Bluesky, and Threads. You understand the nuances of each platform: character limits, hashtag strategies, visual content requirements, algorithm preferences, and audience expectations. You write hooks that stop the scroll, body copy that delivers value, and calls-to-action that drive engagement. You adapt tone from professional thought leadership on LinkedIn to casual and punchy on Twitter to visual storytelling on Instagram.
2. Content Calendar and Scheduling
You help plan and organize content calendars across platforms. You recommend optimal posting times based on platform best practices, suggest content cadence (frequency per platform), and ensure thematic consistency across channels. You track upcoming events, holidays, and industry moments that present content opportunities. You structure weekly and monthly content plans with clear themes, formats, and platform assignments.
3. Engagement Strategy and Community Management
You draft thoughtful replies to comments, design engagement prompts (polls, questions, challenges), and recommend strategies for growing organic reach. You understand algorithm dynamics — when to use threads vs. single posts, how to leverage early engagement windows, and when to reshare or repurpose content. You help manage community tone and handle sensitive or negative interactions diplomatically.
4. Analytics Interpretation
When provided with engagement data (impressions, clicks, shares, follower growth), you analyze trends, identify top-performing content types, and recommend strategy adjustments. You frame insights as actionable recommendations rather than raw numbers.
5. Brand Voice and Consistency
You help define and maintain a consistent brand voice across platforms. You can create brand voice guidelines, tone matrices (by platform and audience), and content style references. You ensure every piece of content aligns with the established voice while adapting to platform conventions.
6. Hashtag and SEO Optimization
You research and recommend hashtags for discoverability, craft SEO-friendly captions for YouTube and blog-linked posts, and understand keyword strategies that bridge social and search.
OPERATIONAL GUIDELINES:
- Always tailor content to the specified platform; never use a one-size-fits-all approach
- Provide multiple variations when drafting posts so the user can choose
- Flag any content that could be controversial or tone-deaf in current cultural context
- Respect character limits and platform-specific formatting rules
- Include accessibility considerations: alt text suggestions for images, captions for video content
- When creating content calendars, present them in structured tabular format
- Store brand voice guides and content templates in memory for consistency
- Never fabricate engagement metrics or analytics data
TOOLS AVAILABLE:
- file_read / file_write / file_list: Manage content drafts, calendars, and brand guidelines
- memory_store / memory_recall: Persist brand voice, templates, and content history
- web_fetch: Research trending topics, competitor content, and platform updates
You are creative, culturally aware, and strategically minded. You balance creativity with data-driven decision-making."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 120000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "test-engineer"
version = "0.1.0"
description = "Quality assurance engineer. Designs test strategies, writes tests, validates correctness."
author = "openfang"
module = "builtin:chat"
tags = ["testing", "qa", "validation"]
[model]
provider = "gemini"
model = "gemini-2.5-flash"
api_key_env = "GEMINI_API_KEY"
max_tokens = 4096
temperature = 0.3
system_prompt = """You are Test Engineer, a QA specialist running inside the OpenFang Agent OS.
Your testing philosophy:
- Tests document behavior, not implementation
- Test the interface, not the internals
- Every test should fail for exactly one reason
- Prefer fast, deterministic tests
- Use property-based testing for edge cases
Test types you design:
1. Unit tests: Isolated function/method testing
2. Integration tests: Component interaction
3. Property tests: Invariant verification across random inputs
4. Edge case tests: Boundaries, empty inputs, overflow
5. Regression tests: Reproduce specific bugs
When writing tests:
- Arrange → Act → Assert pattern
- Descriptive test names (test_X_when_Y_should_Z)
- One assertion per test when possible
- Use fixtures/helpers to reduce duplication
When reviewing test coverage:
- Identify untested paths
- Find missing edge cases
- Suggest mutation testing targets"""
[[fallback_models]]
provider = "groq"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[resources]
max_llm_tokens_per_hour = 150000
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "memory_store", "memory_recall"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["cargo test *", "cargo check *"]

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name = "translator"
version = "0.1.0"
description = "Multi-language translation agent for document translation, localization, and cross-cultural communication."
author = "openfang"
module = "builtin:chat"
tags = ["translation", "languages", "localization", "multilingual", "communication", "i18n"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Translator, a specialist agent in the OpenFang Agent OS. You are an expert linguist and translator who provides accurate, culturally aware translations across multiple languages and handles localization tasks with professional precision.
CORE COMPETENCIES:
1. Accurate Translation
You translate text between languages with high fidelity to the original meaning, tone, and intent. You support major world languages including English, Spanish, French, German, Italian, Portuguese, Chinese (Simplified and Traditional), Japanese, Korean, Arabic, Hindi, Russian, Dutch, Swedish, Norwegian, Danish, Finnish, Polish, Turkish, Thai, Vietnamese, Indonesian, and many others. You understand that translation is not word-for-word substitution but the transfer of meaning, and you prioritize natural, fluent output in the target language.
2. Contextual and Cultural Adaptation
You go beyond literal translation to ensure cultural appropriateness. You understand that idioms, humor, formality levels, and cultural references do not translate directly. You adapt content for the target culture while preserving the original intent. You flag cultural sensitivities — concepts, images, or phrases that may be offensive or confusing in the target culture — and suggest alternatives. You understand register (formal vs. informal) and adjust translation to match the appropriate level for the context.
3. Document and Format Preservation
When translating structured documents (articles, reports, technical documentation, marketing copy), you preserve the original formatting, headings, lists, and document structure. You handle inline code, URLs, proper nouns, and brand names appropriately — some should be translated, some transliterated, and some left unchanged. You maintain consistent terminology throughout long documents using translation glossaries.
4. Localization (l10n) and Internationalization (i18n)
You help with software and product localization: translating UI strings, adapting date/time/number/currency formats, handling right-to-left languages, managing string length variations (German expands, Chinese contracts), and reviewing localized content for correctness. You can process translation files in common formats (JSON, YAML, PO/POT, XLIFF, strings files) and maintain translation memory for consistency.
5. Technical and Specialized Translation
You handle domain-specific translation in technical fields: software documentation, legal documents (contracts, terms of service), medical texts, scientific papers, financial reports, and marketing materials. You understand that each domain has its own terminology and conventions and you maintain appropriate precision. You flag terms where the target language has no direct equivalent and provide explanatory notes.
6. Quality Assurance
You perform translation quality checks: back-translation verification (translating back to source to check meaning preservation), consistency checks (same source term translated the same way throughout), completeness checks (no untranslated segments), and fluency assessment (does it read naturally to a native speaker). You provide confidence levels for translations of ambiguous or highly specialized content.
7. Translation Memory and Glossary Management
You maintain translation glossaries for consistent terminology across projects. You store approved translations of key terms, brand names, and technical vocabulary in memory. You flag when a new translation deviates from established glossary entries and ask for confirmation.
OPERATIONAL GUIDELINES:
- Always specify the source and target languages explicitly in your output
- Preserve the original formatting and structure of the source text
- Flag ambiguous phrases that could be translated multiple ways and explain the options
- Provide transliteration alongside translation for non-Latin scripts when helpful
- Maintain consistent terminology throughout a document or project
- Never fabricate translations for terms you are uncertain about — flag them for review
- For critical or legal content, recommend professional human review
- Store glossaries, translation memories, and style preferences in memory
- When the source text contains errors, translate the intended meaning and note the source error
- Present translations in clear, side-by-side format when comparing versions
TOOLS AVAILABLE:
- file_read / file_write / file_list: Process translation files, documents, and localization resources
- memory_store / memory_recall: Persist glossaries, translation memories, and project preferences
- web_fetch: Access reference dictionaries and terminology databases
You are precise, culturally sensitive, and committed to clear cross-language communication. You bridge linguistic gaps with accuracy and grace."""
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "travel-planner"
version = "0.1.0"
description = "Trip planning agent for itinerary creation, booking research, budget estimation, and travel logistics."
author = "openfang"
module = "builtin:chat"
tags = ["travel", "planning", "itinerary", "booking", "logistics", "vacation"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.5
system_prompt = """You are Travel Planner, a specialist agent in the OpenFang Agent OS. You are an expert travel advisor who helps plan trips, create detailed itineraries, research destinations, estimate budgets, and manage travel logistics.
CORE COMPETENCIES:
1. Itinerary Creation
You build detailed, day-by-day travel itineraries that balance must-see attractions with downtime and practical logistics. Your itineraries include: daily schedule with estimated times, attraction descriptions and highlights, transportation between locations (with estimated travel times), meal recommendations by area and budget, evening activities and options, and contingency plans for weather or closures. You organize itineraries to minimize backtracking, account for jet lag on arrival days, and build in flexibility. You customize intensity level based on traveler preferences: packed sightseeing vs. relaxed exploration.
2. Destination Research and Recommendations
You provide comprehensive destination guides covering: best time to visit (weather, crowds, events), top attractions and hidden gems, neighborhood guides and area descriptions, local customs and cultural etiquette, safety considerations and areas to avoid, local cuisine highlights and restaurant recommendations, transportation options (public transit, ride-share, rental cars), visa and entry requirements, recommended trip duration, and packing suggestions. You tailor recommendations to traveler interests: adventure, culture, food, relaxation, nightlife, family-friendly, or budget travel.
3. Budget Planning and Estimation
You create detailed travel budgets with line-item estimates for: flights (with tips for finding deals), accommodation (by type and area), local transportation, meals (by dining level: budget, moderate, upscale), attractions and activities (entrance fees, tours, experiences), travel insurance, visa fees, and miscellaneous expenses. You provide budget tiers (budget, mid-range, luxury) so travelers can see the cost difference. You identify money-saving opportunities: city passes, free attraction days, happy hours, off-peak pricing, and loyalty program benefits.
4. Accommodation Research
You recommend accommodation options by type (hotels, hostels, vacation rentals, boutique stays), neighborhood, budget, and traveler needs. You assess properties on: location (proximity to attractions and transit), value for money, amenities (wifi, kitchen, laundry), reviews and reputation, cancellation policy, and suitability for the trip type (business, family, romantic, solo). You suggest optimal neighborhoods for different priorities: central location, nightlife, quiet residential, beach access.
5. Transportation and Logistics
You plan the logistics of getting there and getting around: flight route options (direct vs. connecting, layover optimization), airport transfer options, inter-city transportation (trains, buses, domestic flights, rental cars), local transit navigation (metro maps, bus routes, transit passes), and driving logistics (international license requirements, toll roads, parking). You optimize connections and minimize wasted transit time.
6. Packing and Preparation
You create customized packing lists based on: destination climate and weather forecast, planned activities, trip duration, luggage constraints, and cultural dress codes. You include practical reminders: passport validity, travel adapters, medication, copies of documents, travel insurance, phone/data plans, and pre-departure tasks (mail hold, pet care, home security).
7. Multi-Destination and Complex Trip Planning
For trips covering multiple cities or countries, you optimize the route, plan logical transitions between destinations, account for border crossings and visa requirements, balance time allocation across locations, and ensure transportation connections work smoothly. You present the overall journey as both a high-level overview and detailed day-by-day plan.
OPERATIONAL GUIDELINES:
- Always ask for key trip parameters: dates, budget, interests, travel style, and party composition
- Provide options at multiple price points when possible
- Include practical logistics, not just attraction lists
- Note seasonal considerations: peak vs. off-season, weather, local holidays, and closures
- Flag travel advisories, visa requirements, and health recommendations for international destinations
- Store trip plans, preferences, and past trip data in memory for personalized recommendations
- Use clear formatting: day-by-day headers, time estimates, cost estimates, and map references
- Recommend travel insurance and discuss cancellation policies for major bookings
- Never fabricate specific prices, flight numbers, or hotel availability — present estimates clearly as such
- Provide links and references to booking platforms when useful
TOOLS AVAILABLE:
- file_read / file_write / file_list: Create itinerary documents, packing lists, and budget spreadsheets
- memory_store / memory_recall: Persist trip plans, preferences, and destination research
- web_fetch: Research destinations, attractions, transportation options, and current conditions
You are enthusiastic, detail-oriented, and practical. You turn travel dreams into well-organized, memorable trips."""
[resources]
max_llm_tokens_per_hour = 150000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "web_search", "web_fetch", "browser_navigate", "browser_click", "browser_type", "browser_read_page", "browser_screenshot", "browser_close"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]

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name = "tutor"
version = "0.1.0"
description = "Teaching and explanation agent for learning, tutoring, and educational content creation."
author = "openfang"
module = "builtin:chat"
tags = ["education", "teaching", "tutoring", "learning", "explanation", "knowledge"]
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 8192
temperature = 0.5
system_prompt = """You are Tutor, a specialist agent in the OpenFang Agent OS. You are an expert educator and tutor who explains complex concepts clearly, adapts to different learning styles, and guides students through progressive understanding.
CORE COMPETENCIES:
1. Adaptive Explanation
You explain concepts at the appropriate level for the learner. You assess the student's current understanding through targeted questions before diving into explanations. You use the Feynman Technique — if you cannot explain it simply, you break it down further. You offer multiple angles on the same concept: formal definitions, intuitive analogies, concrete examples, visual descriptions, and real-world applications. You never talk down to learners but always meet them where they are.
2. Socratic Teaching Method
Rather than simply providing answers, you guide learners to discover understanding through structured questioning. You ask questions that reveal assumptions, probe reasoning, and lead to insights. You use the progression: what do you already know, what do you think happens next, why do you think that is, can you think of a counterexample, how would you apply this? You balance guidance with space for the learner to think independently.
3. Subject Matter Expertise
You teach across a broad range of subjects: mathematics (algebra through calculus and statistics), computer science (programming, algorithms, data structures, systems), natural sciences (physics, chemistry, biology), humanities (history, philosophy, literature), social sciences (economics, psychology, sociology), and professional skills (writing, critical thinking, study methods). You clearly state when a topic is outside your expertise and recommend appropriate resources.
4. Problem-Solving Walkthrough
You guide students through problems step-by-step, showing not just the solution but the reasoning process. You demonstrate how to: identify what is being asked, determine what information is given, select an appropriate strategy, execute the solution, and verify the answer. You work through examples together and then provide practice problems of increasing difficulty for the student to attempt.
5. Learning Plan Design
You create structured learning plans for mastering a topic or skill. You sequence concepts from foundational to advanced, identify prerequisites, recommend resources (textbooks, courses, practice sets), set milestones, and build in review and reinforcement. You apply spaced repetition principles and interleaving to optimize retention.
6. Assessment and Feedback
You create practice questions, quizzes, and exercises tailored to the material covered. You provide detailed, constructive feedback on student work — not just what is wrong, but why it is wrong and how to correct the misunderstanding. You celebrate progress and identify specific areas for improvement.
7. Study Skills and Metacognition
You teach students how to learn: effective note-taking strategies, active recall techniques, spaced repetition scheduling, the Pomodoro method, concept mapping, and self-testing. You help students develop metacognitive awareness — the ability to monitor their own understanding and identify when they are confused.
OPERATIONAL GUIDELINES:
- Always assess the learner's current level before explaining
- Use concrete examples before abstract definitions
- Break complex topics into digestible chunks with clear transitions
- Encourage questions and create a psychologically safe learning environment
- Provide multiple representations of the same concept (verbal, visual, mathematical, analogical)
- After explaining, check understanding with targeted follow-up questions
- Store learning plans, progress notes, and student preferences in memory
- Never do the student's homework for them — guide them to the answer
- Adapt pacing: slow down when the student is struggling, speed up when they demonstrate mastery
- Use formatting (headers, numbered lists, code blocks) to structure educational content clearly
TOOLS AVAILABLE:
- file_read / file_write / file_list: Read learning materials, write lesson plans and study guides
- memory_store / memory_recall: Track student progress, learning plans, and personalized preferences
- shell_exec: Run code examples for programming tutoring
- web_fetch: Access reference materials and educational resources
You are patient, encouraging, and intellectually rigorous. You believe every person can learn anything with the right approach and sufficient practice."""
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 5
[capabilities]
tools = ["file_read", "file_write", "file_list", "memory_store", "memory_recall", "shell_exec", "web_fetch"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*", "shared.*"]
shell = ["python *"]

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name = "writer"
version = "0.1.0"
description = "Content writer. Creates documentation, articles, and technical writing."
author = "openfang"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
max_tokens = 4096
temperature = 0.7
system_prompt = """You are Writer, a professional content creation agent running inside the OpenFang Agent OS.
WRITING METHODOLOGY:
1. UNDERSTAND — Ask clarifying questions if the audience, tone, or format is unclear.
2. RESEARCH — Read existing files for context. Use web_search if you need facts or references.
3. DRAFT — Write the content in one pass. Prioritize clarity and flow.
4. REFINE — Review for conciseness, active voice, and logical structure.
STYLE PRINCIPLES:
- Lead with the most important information.
- Use active voice. Cut filler words ("just", "actually", "basically").
- Structure with headers, bullet points, and short paragraphs.
- Match the requested tone: technical docs are precise, blog posts are conversational, emails are direct.
- When writing code documentation, include working examples.
OUTPUT:
- Save long-form content to files when asked (use file_write).
- For short content (emails, messages, summaries), respond directly.
- Adapt formatting to the target platform when specified."""
[[fallback_models]]
provider = "gemini"
model = "gemini-2.0-flash"
api_key_env = "GEMINI_API_KEY"
[resources]
max_llm_tokens_per_hour = 100000
[capabilities]
tools = ["file_read", "file_write", "file_list", "web_search", "web_fetch", "memory_store", "memory_recall"]
network = ["*"]
memory_read = ["*"]
memory_write = ["self.*"]

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[package]
name = "openfang-api"
version.workspace = true
edition.workspace = true
license.workspace = true
description = "HTTP/WebSocket API server for the OpenFang Agent OS daemon"
[dependencies]
openfang-types = { path = "../openfang-types" }
openfang-kernel = { path = "../openfang-kernel" }
openfang-runtime = { path = "../openfang-runtime" }
openfang-memory = { path = "../openfang-memory" }
openfang-channels = { path = "../openfang-channels" }
openfang-wire = { path = "../openfang-wire" }
openfang-skills = { path = "../openfang-skills" }
openfang-hands = { path = "../openfang-hands" }
openfang-extensions = { path = "../openfang-extensions" }
openfang-migrate = { path = "../openfang-migrate" }
dashmap = { workspace = true }
tokio = { workspace = true }
serde = { workspace = true }
serde_json = { workspace = true }
toml = { workspace = true }
tracing = { workspace = true }
async-trait = { workspace = true }
axum = { workspace = true }
tower = { workspace = true }
tower-http = { workspace = true }
chrono = { workspace = true }
uuid = { workspace = true }
futures = { workspace = true }
governor = { workspace = true }
tokio-stream = { workspace = true }
subtle = { workspace = true }
base64 = { workspace = true }
[dev-dependencies]
tokio-test = { workspace = true }
reqwest = { workspace = true }
tempfile = { workspace = true }
uuid = { workspace = true }

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//! HTTP/WebSocket API server for the OpenFang Agent OS daemon.
//!
//! Exposes agent management, status, and chat via JSON REST endpoints.
//! The kernel runs in-process; the CLI connects over HTTP.
pub mod channel_bridge;
pub mod middleware;
pub mod openai_compat;
pub mod rate_limiter;
pub mod routes;
pub mod server;
pub mod stream_chunker;
pub mod stream_dedup;
pub mod types;
pub mod webchat;
pub mod ws;

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//! Production middleware for the OpenFang API server.
//!
//! Provides:
//! - Request ID generation and propagation
//! - Per-endpoint structured request logging
//! - In-memory rate limiting (per IP)
use axum::body::Body;
use axum::http::{Request, Response, StatusCode};
use axum::middleware::Next;
use std::time::Instant;
use tracing::info;
/// Request ID header name (standard).
pub const REQUEST_ID_HEADER: &str = "x-request-id";
/// Middleware: inject a unique request ID and log the request/response.
pub async fn request_logging(request: Request<Body>, next: Next) -> Response<Body> {
let request_id = uuid::Uuid::new_v4().to_string();
let method = request.method().clone();
let uri = request.uri().path().to_string();
let start = Instant::now();
let mut response = next.run(request).await;
let elapsed = start.elapsed();
let status = response.status().as_u16();
info!(
request_id = %request_id,
method = %method,
path = %uri,
status = status,
latency_ms = elapsed.as_millis() as u64,
"API request"
);
// Inject the request ID into the response
if let Ok(header_val) = request_id.parse() {
response.headers_mut().insert(REQUEST_ID_HEADER, header_val);
}
response
}
/// Bearer token authentication middleware.
///
/// When `api_key` is non-empty, all requests must include
/// `Authorization: Bearer <api_key>`. If the key is empty, auth is bypassed.
pub async fn auth(
axum::extract::State(api_key): axum::extract::State<String>,
request: Request<Body>,
next: Next,
) -> Response<Body> {
// If no API key configured, restrict to loopback addresses only.
if api_key.is_empty() {
let is_loopback = request
.extensions()
.get::<axum::extract::ConnectInfo<std::net::SocketAddr>>()
.map(|ci| ci.0.ip().is_loopback())
.unwrap_or(false);
if !is_loopback {
tracing::warn!(
"Rejected non-localhost request: no API key configured. \
Set api_key in config.toml for remote access."
);
return Response::builder()
.status(StatusCode::FORBIDDEN)
.header("content-type", "application/json")
.body(Body::from(
serde_json::json!({
"error": "No API key configured. Remote access denied. Configure api_key in ~/.openfang/config.toml"
})
.to_string(),
))
.unwrap_or_default();
}
return next.run(request).await;
}
// Public endpoints that don't require auth (dashboard needs these)
let path = request.uri().path();
if path == "/"
|| path == "/api/health"
|| path == "/api/health/detail"
|| path == "/api/status"
|| path == "/api/version"
|| path == "/api/agents"
|| path == "/api/profiles"
|| path == "/api/config"
|| path.starts_with("/api/uploads/")
// Dashboard read endpoints — allow unauthenticated so the SPA can
// render before the user enters their API key.
|| path == "/api/models"
|| path == "/api/models/aliases"
|| path == "/api/providers"
|| path == "/api/budget"
|| path == "/api/budget/agents"
|| path.starts_with("/api/budget/agents/")
|| path == "/api/network/status"
|| path == "/api/a2a/agents"
|| path == "/api/approvals"
|| path.starts_with("/api/approvals/")
|| path == "/api/channels"
|| path == "/api/skills"
|| path == "/api/sessions"
|| path == "/api/integrations"
|| path == "/api/integrations/available"
|| path == "/api/integrations/health"
|| path == "/api/workflows"
|| path == "/api/logs/stream"
|| path.starts_with("/api/cron/")
|| path.starts_with("/api/providers/github-copilot/oauth/")
{
return next.run(request).await;
}
// Check Authorization: Bearer <token> header
let bearer_token = request
.headers()
.get("authorization")
.and_then(|v| v.to_str().ok())
.and_then(|v| v.strip_prefix("Bearer "));
// SECURITY: Use constant-time comparison to prevent timing attacks.
let header_auth = bearer_token.map(|token| {
use subtle::ConstantTimeEq;
if token.len() != api_key.len() {
return false;
}
token.as_bytes().ct_eq(api_key.as_bytes()).into()
});
// Also check ?token= query parameter (for EventSource/SSE clients that
// cannot set custom headers, same approach as WebSocket auth).
let query_token = request
.uri()
.query()
.and_then(|q| q.split('&').find_map(|pair| pair.strip_prefix("token=")));
// SECURITY: Use constant-time comparison to prevent timing attacks.
let query_auth = query_token.map(|token| {
use subtle::ConstantTimeEq;
if token.len() != api_key.len() {
return false;
}
token.as_bytes().ct_eq(api_key.as_bytes()).into()
});
// Accept if either auth method matches
if header_auth == Some(true) || query_auth == Some(true) {
return next.run(request).await;
}
// Determine error message: was a credential provided but wrong, or missing entirely?
let credential_provided = header_auth.is_some() || query_auth.is_some();
let error_msg = if credential_provided {
"Invalid API key"
} else {
"Missing Authorization: Bearer <api_key> header"
};
Response::builder()
.status(StatusCode::UNAUTHORIZED)
.header("www-authenticate", "Bearer")
.body(Body::from(
serde_json::json!({"error": error_msg}).to_string(),
))
.unwrap_or_default()
}
/// Security headers middleware — applied to ALL API responses.
pub async fn security_headers(request: Request<Body>, next: Next) -> Response<Body> {
let mut response = next.run(request).await;
let headers = response.headers_mut();
headers.insert("x-content-type-options", "nosniff".parse().unwrap());
headers.insert("x-frame-options", "DENY".parse().unwrap());
headers.insert("x-xss-protection", "1; mode=block".parse().unwrap());
// All JS/CSS is bundled inline — only external resource is Google Fonts.
headers.insert(
"content-security-policy",
"default-src 'self'; script-src 'self' 'unsafe-inline' 'unsafe-eval'; style-src 'self' 'unsafe-inline' https://fonts.googleapis.com https://fonts.gstatic.com; img-src 'self' data: blob:; connect-src 'self' ws://localhost:* ws://127.0.0.1:* wss://localhost:* wss://127.0.0.1:*; font-src 'self' https://fonts.gstatic.com; media-src 'self' blob:; frame-src 'self' blob:; object-src 'none'; base-uri 'self'; form-action 'self'"
.parse()
.unwrap(),
);
headers.insert(
"referrer-policy",
"strict-origin-when-cross-origin".parse().unwrap(),
);
headers.insert(
"cache-control",
"no-store, no-cache, must-revalidate".parse().unwrap(),
);
response
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_request_id_header_constant() {
assert_eq!(REQUEST_ID_HEADER, "x-request-id");
}
}

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//! OpenAI-compatible `/v1/chat/completions` API endpoint.
//!
//! Allows any OpenAI-compatible client library to talk to OpenFang agents.
//! The `model` field resolves to an agent (by name, UUID, or `openfang:<name>`),
//! and the messages are forwarded to the agent's LLM loop.
//!
//! Supports both streaming (SSE) and non-streaming responses.
use crate::routes::AppState;
use axum::extract::State;
use axum::http::StatusCode;
use axum::response::sse::{Event as SseEvent, KeepAlive, Sse};
use axum::response::IntoResponse;
use axum::Json;
use openfang_runtime::kernel_handle::KernelHandle;
use openfang_runtime::llm_driver::StreamEvent;
use openfang_types::agent::AgentId;
use openfang_types::message::{ContentBlock, Message, MessageContent, Role, StopReason};
use serde::{Deserialize, Serialize};
use std::convert::Infallible;
use std::sync::Arc;
use tracing::warn;
// ── Request types ──────────────────────────────────────────────────────────
#[derive(Debug, Deserialize)]
pub struct ChatCompletionRequest {
pub model: String,
pub messages: Vec<OaiMessage>,
#[serde(default)]
pub stream: bool,
pub max_tokens: Option<u32>,
pub temperature: Option<f32>,
}
#[derive(Debug, Deserialize)]
pub struct OaiMessage {
pub role: String,
#[serde(default)]
pub content: OaiContent,
}
#[derive(Debug, Deserialize, Default)]
#[serde(untagged)]
pub enum OaiContent {
Text(String),
Parts(Vec<OaiContentPart>),
#[default]
Null,
}
#[derive(Debug, Deserialize)]
#[serde(tag = "type")]
pub enum OaiContentPart {
#[serde(rename = "text")]
Text { text: String },
#[serde(rename = "image_url")]
ImageUrl { image_url: OaiImageUrlRef },
}
#[derive(Debug, Deserialize)]
pub struct OaiImageUrlRef {
pub url: String,
}
// ── Response types ──────────────────────────────────────────────────────────
#[derive(Serialize)]
struct ChatCompletionResponse {
id: String,
object: &'static str,
created: u64,
model: String,
choices: Vec<Choice>,
usage: UsageInfo,
}
#[derive(Serialize)]
struct Choice {
index: u32,
message: ChoiceMessage,
finish_reason: &'static str,
}
#[derive(Serialize)]
struct ChoiceMessage {
role: &'static str,
#[serde(skip_serializing_if = "Option::is_none")]
content: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
tool_calls: Option<Vec<OaiToolCall>>,
}
#[derive(Serialize)]
struct UsageInfo {
prompt_tokens: u64,
completion_tokens: u64,
total_tokens: u64,
}
#[derive(Serialize)]
struct ChatCompletionChunk {
id: String,
object: &'static str,
created: u64,
model: String,
choices: Vec<ChunkChoice>,
}
#[derive(Serialize)]
struct ChunkChoice {
index: u32,
delta: ChunkDelta,
finish_reason: Option<&'static str>,
}
#[derive(Serialize)]
struct ChunkDelta {
#[serde(skip_serializing_if = "Option::is_none")]
role: Option<&'static str>,
#[serde(skip_serializing_if = "Option::is_none")]
content: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
tool_calls: Option<Vec<OaiToolCall>>,
}
#[derive(Serialize, Clone)]
struct OaiToolCall {
index: u32,
#[serde(skip_serializing_if = "Option::is_none")]
id: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
#[serde(rename = "type")]
call_type: Option<&'static str>,
function: OaiToolCallFunction,
}
#[derive(Serialize, Clone)]
struct OaiToolCallFunction {
#[serde(skip_serializing_if = "Option::is_none")]
name: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
arguments: Option<String>,
}
#[derive(Serialize)]
struct ModelObject {
id: String,
object: &'static str,
created: u64,
owned_by: String,
}
#[derive(Serialize)]
struct ModelListResponse {
object: &'static str,
data: Vec<ModelObject>,
}
// ── Agent resolution ────────────────────────────────────────────────────────
fn resolve_agent(state: &AppState, model: &str) -> Option<(AgentId, String)> {
// 1. "openfang:<name>" → find agent by name
if let Some(name) = model.strip_prefix("openfang:") {
if let Some(entry) = state.kernel.registry.find_by_name(name) {
return Some((entry.id, entry.name.clone()));
}
}
// 2. Valid UUID → find agent by ID
if let Ok(id) = model.parse::<AgentId>() {
if let Some(entry) = state.kernel.registry.get(id) {
return Some((entry.id, entry.name.clone()));
}
}
// 3. Plain string → try as agent name
if let Some(entry) = state.kernel.registry.find_by_name(model) {
return Some((entry.id, entry.name.clone()));
}
// 4. Fallback → first registered agent
let agents = state.kernel.registry.list();
agents.first().map(|e| (e.id, e.name.clone()))
}
// ── Message conversion ──────────────────────────────────────────────────────
fn convert_messages(oai_messages: &[OaiMessage]) -> Vec<Message> {
oai_messages
.iter()
.filter_map(|m| {
let role = match m.role.as_str() {
"user" => Role::User,
"assistant" => Role::Assistant,
"system" => Role::System,
_ => Role::User,
};
let content = match &m.content {
OaiContent::Text(text) => MessageContent::Text(text.clone()),
OaiContent::Parts(parts) => {
let blocks: Vec<ContentBlock> = parts
.iter()
.filter_map(|part| match part {
OaiContentPart::Text { text } => {
Some(ContentBlock::Text { text: text.clone() })
}
OaiContentPart::ImageUrl { image_url } => {
// Parse data URI: data:{media_type};base64,{data}
if let Some(rest) = image_url.url.strip_prefix("data:") {
let parts: Vec<&str> = rest.splitn(2, ',').collect();
if parts.len() == 2 {
let media_type = parts[0]
.strip_suffix(";base64")
.unwrap_or(parts[0])
.to_string();
let data = parts[1].to_string();
Some(ContentBlock::Image { media_type, data })
} else {
None
}
} else {
// URL-based images not supported (would require fetching)
None
}
}
})
.collect();
if blocks.is_empty() {
return None;
}
MessageContent::Blocks(blocks)
}
OaiContent::Null => return None,
};
Some(Message { role, content })
})
.collect()
}
// ── Handlers ────────────────────────────────────────────────────────────────
/// POST /v1/chat/completions
pub async fn chat_completions(
State(state): State<Arc<AppState>>,
Json(req): Json<ChatCompletionRequest>,
) -> impl IntoResponse {
let (agent_id, agent_name) = match resolve_agent(&state, &req.model) {
Some(pair) => pair,
None => {
return (
StatusCode::NOT_FOUND,
Json(serde_json::json!({
"error": {
"message": format!("No agent found for model '{}'", req.model),
"type": "invalid_request_error",
"code": "model_not_found"
}
})),
)
.into_response();
}
};
// Extract the last user message as the input
let messages = convert_messages(&req.messages);
let last_user_msg = messages
.iter()
.rev()
.find(|m| m.role == Role::User)
.map(|m| m.content.text_content())
.unwrap_or_default();
if last_user_msg.is_empty() {
return (
StatusCode::BAD_REQUEST,
Json(serde_json::json!({
"error": {
"message": "No user message found in request",
"type": "invalid_request_error",
"code": "missing_message"
}
})),
)
.into_response();
}
let request_id = format!("chatcmpl-{}", uuid::Uuid::new_v4());
let created = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs();
if req.stream {
// Streaming response
return match stream_response(
state,
agent_id,
agent_name,
&last_user_msg,
request_id,
created,
)
.await
{
Ok(sse) => sse.into_response(),
Err(e) => (
StatusCode::INTERNAL_SERVER_ERROR,
Json(serde_json::json!({
"error": {
"message": format!("{e}"),
"type": "server_error"
}
})),
)
.into_response(),
};
}
// Non-streaming response
let kernel_handle: Arc<dyn KernelHandle> = state.kernel.clone() as Arc<dyn KernelHandle>;
match state
.kernel
.send_message_with_handle(agent_id, &last_user_msg, Some(kernel_handle))
.await
{
Ok(result) => {
let response = ChatCompletionResponse {
id: request_id,
object: "chat.completion",
created,
model: agent_name,
choices: vec![Choice {
index: 0,
message: ChoiceMessage {
role: "assistant",
content: Some(result.response),
tool_calls: None,
},
finish_reason: "stop",
}],
usage: UsageInfo {
prompt_tokens: result.total_usage.input_tokens,
completion_tokens: result.total_usage.output_tokens,
total_tokens: result.total_usage.input_tokens
+ result.total_usage.output_tokens,
},
};
Json(serde_json::to_value(&response).unwrap_or_default()).into_response()
}
Err(e) => {
warn!("OpenAI compat: agent error: {e}");
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(serde_json::json!({
"error": {
"message": "Agent processing failed",
"type": "server_error"
}
})),
)
.into_response()
}
}
}
/// Build an SSE stream response for streaming completions.
async fn stream_response(
state: Arc<AppState>,
agent_id: AgentId,
agent_name: String,
message: &str,
request_id: String,
created: u64,
) -> Result<axum::response::Response, String> {
let kernel_handle: Arc<dyn KernelHandle> = state.kernel.clone() as Arc<dyn KernelHandle>;
let (mut rx, _handle) = state
.kernel
.send_message_streaming(agent_id, message, Some(kernel_handle))
.map_err(|e| format!("Streaming setup failed: {e}"))?;
let (tx, stream_rx) = tokio::sync::mpsc::channel::<Result<SseEvent, Infallible>>(64);
// Send initial role delta
let first_chunk = ChatCompletionChunk {
id: request_id.clone(),
object: "chat.completion.chunk",
created,
model: agent_name.clone(),
choices: vec![ChunkChoice {
index: 0,
delta: ChunkDelta {
role: Some("assistant"),
content: None,
tool_calls: None,
},
finish_reason: None,
}],
};
let _ = tx
.send(Ok(SseEvent::default().data(
serde_json::to_string(&first_chunk).unwrap_or_default(),
)))
.await;
// Helper to build a chunk with a delta and optional finish_reason.
fn make_chunk(
id: &str,
created: u64,
model: &str,
delta: ChunkDelta,
finish_reason: Option<&'static str>,
) -> String {
let chunk = ChatCompletionChunk {
id: id.to_string(),
object: "chat.completion.chunk",
created,
model: model.to_string(),
choices: vec![ChunkChoice {
index: 0,
delta,
finish_reason,
}],
};
serde_json::to_string(&chunk).unwrap_or_default()
}
// Spawn forwarder task — streams ALL iterations until the agent loop channel closes.
let req_id = request_id.clone();
tokio::spawn(async move {
// Tracks current tool_call index within each LLM iteration.
let mut tool_index: u32 = 0;
while let Some(event) = rx.recv().await {
let json = match event {
StreamEvent::TextDelta { text } => make_chunk(
&req_id,
created,
&agent_name,
ChunkDelta {
role: None,
content: Some(text),
tool_calls: None,
},
None,
),
StreamEvent::ToolUseStart { id, name } => {
let idx = tool_index;
tool_index += 1;
make_chunk(
&req_id,
created,
&agent_name,
ChunkDelta {
role: None,
content: None,
tool_calls: Some(vec![OaiToolCall {
index: idx,
id: Some(id),
call_type: Some("function"),
function: OaiToolCallFunction {
name: Some(name),
arguments: Some(String::new()),
},
}]),
},
None,
)
}
StreamEvent::ToolInputDelta { text } => {
// tool_index already incremented past current tool, so current = index - 1
let idx = tool_index.saturating_sub(1);
make_chunk(
&req_id,
created,
&agent_name,
ChunkDelta {
role: None,
content: None,
tool_calls: Some(vec![OaiToolCall {
index: idx,
id: None,
call_type: None,
function: OaiToolCallFunction {
name: None,
arguments: Some(text),
},
}]),
},
None,
)
}
StreamEvent::ContentComplete { stop_reason, .. } => {
// ToolUse → reset tool index for next iteration, do NOT finish.
// EndTurn/MaxTokens/StopSequence → continue, wait for channel close.
if matches!(stop_reason, StopReason::ToolUse) {
tool_index = 0;
}
continue;
}
// ToolUseEnd, ToolExecutionResult, ThinkingDelta, PhaseChange — skip
_ => continue,
};
if tx.send(Ok(SseEvent::default().data(json))).await.is_err() {
break;
}
}
// Channel closed — agent loop is fully done. Send finish + [DONE].
let final_json = make_chunk(
&req_id,
created,
&agent_name,
ChunkDelta {
role: None,
content: None,
tool_calls: None,
},
Some("stop"),
);
let _ = tx.send(Ok(SseEvent::default().data(final_json))).await;
let _ = tx.send(Ok(SseEvent::default().data("[DONE]"))).await;
});
let stream = tokio_stream::wrappers::ReceiverStream::new(stream_rx);
Ok(Sse::new(stream)
.keep_alive(KeepAlive::default())
.into_response())
}
/// GET /v1/models — List available agents as OpenAI model objects.
pub async fn list_models(State(state): State<Arc<AppState>>) -> impl IntoResponse {
let agents = state.kernel.registry.list();
let created = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_default()
.as_secs();
let models: Vec<ModelObject> = agents
.iter()
.map(|e| ModelObject {
id: format!("openfang:{}", e.name),
object: "model",
created,
owned_by: "openfang".to_string(),
})
.collect();
Json(
serde_json::to_value(&ModelListResponse {
object: "list",
data: models,
})
.unwrap_or_default(),
)
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_oai_content_deserialize_string() {
let json = r#"{"role":"user","content":"hello"}"#;
let msg: OaiMessage = serde_json::from_str(json).unwrap();
assert!(matches!(msg.content, OaiContent::Text(ref t) if t == "hello"));
}
#[test]
fn test_oai_content_deserialize_parts() {
let json = r#"{"role":"user","content":[{"type":"text","text":"what is this?"},{"type":"image_url","image_url":{"url":"data:image/png;base64,abc123"}}]}"#;
let msg: OaiMessage = serde_json::from_str(json).unwrap();
assert!(matches!(msg.content, OaiContent::Parts(ref p) if p.len() == 2));
}
#[test]
fn test_convert_messages_text() {
let oai = vec![
OaiMessage {
role: "system".to_string(),
content: OaiContent::Text("You are helpful.".to_string()),
},
OaiMessage {
role: "user".to_string(),
content: OaiContent::Text("Hello!".to_string()),
},
];
let msgs = convert_messages(&oai);
assert_eq!(msgs.len(), 2);
assert_eq!(msgs[0].role, Role::System);
assert_eq!(msgs[1].role, Role::User);
}
#[test]
fn test_convert_messages_with_image() {
let oai = vec![OaiMessage {
role: "user".to_string(),
content: OaiContent::Parts(vec![
OaiContentPart::Text {
text: "What is this?".to_string(),
},
OaiContentPart::ImageUrl {
image_url: OaiImageUrlRef {
url: "data:image/png;base64,iVBORw0KGgo=".to_string(),
},
},
]),
}];
let msgs = convert_messages(&oai);
assert_eq!(msgs.len(), 1);
match &msgs[0].content {
MessageContent::Blocks(blocks) => {
assert_eq!(blocks.len(), 2);
assert!(matches!(&blocks[0], ContentBlock::Text { .. }));
assert!(matches!(&blocks[1], ContentBlock::Image { .. }));
}
_ => panic!("Expected Blocks"),
}
}
#[test]
fn test_response_serialization() {
let resp = ChatCompletionResponse {
id: "chatcmpl-test".to_string(),
object: "chat.completion",
created: 1234567890,
model: "test-agent".to_string(),
choices: vec![Choice {
index: 0,
message: ChoiceMessage {
role: "assistant",
content: Some("Hello!".to_string()),
tool_calls: None,
},
finish_reason: "stop",
}],
usage: UsageInfo {
prompt_tokens: 10,
completion_tokens: 5,
total_tokens: 15,
},
};
let json = serde_json::to_value(&resp).unwrap();
assert_eq!(json["object"], "chat.completion");
assert_eq!(json["choices"][0]["message"]["content"], "Hello!");
assert_eq!(json["usage"]["total_tokens"], 15);
// tool_calls should be omitted when None
assert!(json["choices"][0]["message"].get("tool_calls").is_none());
}
#[test]
fn test_chunk_serialization() {
let chunk = ChatCompletionChunk {
id: "chatcmpl-test".to_string(),
object: "chat.completion.chunk",
created: 1234567890,
model: "test-agent".to_string(),
choices: vec![ChunkChoice {
index: 0,
delta: ChunkDelta {
role: None,
content: Some("Hello".to_string()),
tool_calls: None,
},
finish_reason: None,
}],
};
let json = serde_json::to_value(&chunk).unwrap();
assert_eq!(json["object"], "chat.completion.chunk");
assert_eq!(json["choices"][0]["delta"]["content"], "Hello");
assert!(json["choices"][0]["delta"]["role"].is_null());
// tool_calls should be omitted when None
assert!(json["choices"][0]["delta"].get("tool_calls").is_none());
}
#[test]
fn test_tool_call_serialization() {
let tc = OaiToolCall {
index: 0,
id: Some("call_abc123".to_string()),
call_type: Some("function"),
function: OaiToolCallFunction {
name: Some("get_weather".to_string()),
arguments: Some(r#"{"location":"NYC"}"#.to_string()),
},
};
let json = serde_json::to_value(&tc).unwrap();
assert_eq!(json["index"], 0);
assert_eq!(json["id"], "call_abc123");
assert_eq!(json["type"], "function");
assert_eq!(json["function"]["name"], "get_weather");
assert_eq!(json["function"]["arguments"], r#"{"location":"NYC"}"#);
}
#[test]
fn test_chunk_delta_with_tool_calls() {
let chunk = ChatCompletionChunk {
id: "chatcmpl-test".to_string(),
object: "chat.completion.chunk",
created: 1234567890,
model: "test-agent".to_string(),
choices: vec![ChunkChoice {
index: 0,
delta: ChunkDelta {
role: None,
content: None,
tool_calls: Some(vec![OaiToolCall {
index: 0,
id: Some("call_1".to_string()),
call_type: Some("function"),
function: OaiToolCallFunction {
name: Some("search".to_string()),
arguments: Some(String::new()),
},
}]),
},
finish_reason: None,
}],
};
let json = serde_json::to_value(&chunk).unwrap();
let tc = &json["choices"][0]["delta"]["tool_calls"][0];
assert_eq!(tc["index"], 0);
assert_eq!(tc["id"], "call_1");
assert_eq!(tc["type"], "function");
assert_eq!(tc["function"]["name"], "search");
// content should be omitted
assert!(json["choices"][0]["delta"].get("content").is_none());
}
#[test]
fn test_tool_input_delta_chunk() {
// Incremental arguments chunk — no id, no type, no name
let tc = OaiToolCall {
index: 2,
id: None,
call_type: None,
function: OaiToolCallFunction {
name: None,
arguments: Some(r#"{"q":"rust"}"#.to_string()),
},
};
let json = serde_json::to_value(&tc).unwrap();
assert_eq!(json["index"], 2);
// id and type should be omitted
assert!(json.get("id").is_none());
assert!(json.get("type").is_none());
assert!(json["function"].get("name").is_none());
assert_eq!(json["function"]["arguments"], r#"{"q":"rust"}"#);
}
#[test]
fn test_backward_compat_no_tool_calls() {
// When tool_calls is None, it should not appear in JSON at all (backward compat)
let msg = ChoiceMessage {
role: "assistant",
content: Some("Hello".to_string()),
tool_calls: None,
};
let json_str = serde_json::to_string(&msg).unwrap();
assert!(!json_str.contains("tool_calls"));
let delta = ChunkDelta {
role: Some("assistant"),
content: Some("Hi".to_string()),
tool_calls: None,
};
let json_str = serde_json::to_string(&delta).unwrap();
assert!(!json_str.contains("tool_calls"));
}
}

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crates/openfang-api/src/rate_limiter.rs Normal file
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//! Cost-aware rate limiting using GCRA (Generic Cell Rate Algorithm).
//!
//! Each API operation has a token cost (e.g., health=1, spawn=50, message=30).
//! The GCRA algorithm allows 500 tokens per minute per IP address.
use axum::body::Body;
use axum::http::{Request, Response, StatusCode};
use axum::middleware::Next;
use governor::{clock::DefaultClock, state::keyed::DashMapStateStore, Quota, RateLimiter};
use std::net::{IpAddr, SocketAddr};
use std::num::NonZeroU32;
use std::sync::Arc;
pub fn operation_cost(method: &str, path: &str) -> NonZeroU32 {
match (method, path) {
(_, "/api/health") => NonZeroU32::new(1).unwrap(),
("GET", "/api/status") => NonZeroU32::new(1).unwrap(),
("GET", "/api/version") => NonZeroU32::new(1).unwrap(),
("GET", "/api/tools") => NonZeroU32::new(1).unwrap(),
("GET", "/api/agents") => NonZeroU32::new(2).unwrap(),
("GET", "/api/skills") => NonZeroU32::new(2).unwrap(),
("GET", "/api/peers") => NonZeroU32::new(2).unwrap(),
("GET", "/api/config") => NonZeroU32::new(2).unwrap(),
("GET", "/api/usage") => NonZeroU32::new(3).unwrap(),
("GET", p) if p.starts_with("/api/audit") => NonZeroU32::new(5).unwrap(),
("GET", p) if p.starts_with("/api/marketplace") => NonZeroU32::new(10).unwrap(),
("POST", "/api/agents") => NonZeroU32::new(50).unwrap(),
("POST", p) if p.contains("/message") => NonZeroU32::new(30).unwrap(),
("POST", p) if p.contains("/run") => NonZeroU32::new(100).unwrap(),
("POST", "/api/skills/install") => NonZeroU32::new(50).unwrap(),
("POST", "/api/skills/uninstall") => NonZeroU32::new(10).unwrap(),
("POST", "/api/migrate") => NonZeroU32::new(100).unwrap(),
("PUT", p) if p.contains("/update") => NonZeroU32::new(10).unwrap(),
_ => NonZeroU32::new(5).unwrap(),
}
}
pub type KeyedRateLimiter = RateLimiter<IpAddr, DashMapStateStore<IpAddr>, DefaultClock>;
/// 500 tokens per minute per IP.
pub fn create_rate_limiter() -> Arc<KeyedRateLimiter> {
Arc::new(RateLimiter::keyed(Quota::per_minute(
NonZeroU32::new(500).unwrap(),
)))
}
/// GCRA rate limiting middleware.
///
/// Extracts the client IP from `ConnectInfo`, computes the cost for the
/// requested operation, and checks the GCRA limiter. Returns 429 if the
/// client has exhausted its token budget.
pub async fn gcra_rate_limit(
axum::extract::State(limiter): axum::extract::State<Arc<KeyedRateLimiter>>,
request: Request<Body>,
next: Next,
) -> Response<Body> {
let ip = request
.extensions()
.get::<axum::extract::ConnectInfo<SocketAddr>>()
.map(|ci| ci.0.ip())
.unwrap_or(IpAddr::from([127, 0, 0, 1]));
let method = request.method().as_str().to_string();
let path = request.uri().path().to_string();
let cost = operation_cost(&method, &path);
if limiter.check_key_n(&ip, cost).is_err() {
tracing::warn!(ip = %ip, cost = cost.get(), path = %path, "GCRA rate limit exceeded");
return Response::builder()
.status(StatusCode::TOO_MANY_REQUESTS)
.header("content-type", "application/json")
.header("retry-after", "60")
.body(Body::from(
serde_json::json!({"error": "Rate limit exceeded"}).to_string(),
))
.unwrap_or_default();
}
next.run(request).await
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_costs() {
assert_eq!(operation_cost("GET", "/api/health").get(), 1);
assert_eq!(operation_cost("GET", "/api/tools").get(), 1);
assert_eq!(operation_cost("POST", "/api/agents/1/message").get(), 30);
assert_eq!(operation_cost("POST", "/api/agents").get(), 50);
assert_eq!(operation_cost("POST", "/api/workflows/1/run").get(), 100);
assert_eq!(operation_cost("GET", "/api/agents/1/session").get(), 5);
assert_eq!(operation_cost("GET", "/api/skills").get(), 2);
assert_eq!(operation_cost("GET", "/api/peers").get(), 2);
assert_eq!(operation_cost("GET", "/api/audit/recent").get(), 5);
assert_eq!(operation_cost("POST", "/api/skills/install").get(), 50);
assert_eq!(operation_cost("POST", "/api/migrate").get(), 100);
}
}

8979
crates/openfang-api/src/routes.rs Normal file
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crates/openfang-api/src/server.rs Normal file
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//! OpenFang daemon server — boots the kernel and serves the HTTP API.
use crate::channel_bridge;
use crate::middleware;
use crate::rate_limiter;
use crate::routes::{self, AppState};
use crate::webchat;
use crate::ws;
use axum::Router;
use openfang_kernel::OpenFangKernel;
use std::net::SocketAddr;
use std::path::Path;
use std::sync::Arc;
use std::time::Instant;
use tower_http::compression::CompressionLayer;
use tower_http::cors::CorsLayer;
use tower_http::trace::TraceLayer;
use tracing::info;
/// Daemon info written to `~/.openfang/daemon.json` so the CLI can find us.
#[derive(serde::Serialize, serde::Deserialize)]
pub struct DaemonInfo {
pub pid: u32,
pub listen_addr: String,
pub started_at: String,
pub version: String,
pub platform: String,
}
/// Build the full API router with all routes, middleware, and state.
///
/// This is extracted from `run_daemon()` so that embedders (e.g. openfang-desktop)
/// can create the router without starting the full daemon lifecycle.
///
/// Returns `(router, shared_state)`. The caller can use `state.bridge_manager`
/// to shut down the bridge on exit.
pub async fn build_router(
kernel: Arc<OpenFangKernel>,
listen_addr: SocketAddr,
) -> (Router<()>, Arc<AppState>) {
// Start channel bridges (Telegram, etc.)
let bridge = channel_bridge::start_channel_bridge(kernel.clone()).await;
let channels_config = kernel.config.channels.clone();
let state = Arc::new(AppState {
kernel: kernel.clone(),
started_at: Instant::now(),
peer_registry: kernel.peer_registry.as_ref().map(|r| Arc::new(r.clone())),
bridge_manager: tokio::sync::Mutex::new(bridge),
channels_config: tokio::sync::RwLock::new(channels_config),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
// CORS: allow localhost origins by default. If API key is set, the API
// is protected anyway. For development, permissive CORS is convenient.
let cors = if state.kernel.config.api_key.is_empty() {
// No auth → restrict CORS to localhost origins (include both 127.0.0.1 and localhost)
let port = listen_addr.port();
let mut origins: Vec<axum::http::HeaderValue> = vec![
format!("http://{listen_addr}").parse().unwrap(),
format!("http://localhost:{port}").parse().unwrap(),
];
// Also allow common dev ports
for p in [3000u16, 8080] {
if p != port {
if let Ok(v) = format!("http://127.0.0.1:{p}").parse() {
origins.push(v);
}
if let Ok(v) = format!("http://localhost:{p}").parse() {
origins.push(v);
}
}
}
CorsLayer::new()
.allow_origin(origins)
.allow_methods(tower_http::cors::Any)
.allow_headers(tower_http::cors::Any)
} else {
// Auth enabled → restrict CORS to localhost + configured origins.
// SECURITY: CorsLayer::permissive() is dangerous — any website could
// make cross-origin requests. Restrict to known origins instead.
let mut origins: Vec<axum::http::HeaderValue> = vec![
format!("http://{listen_addr}").parse().unwrap(),
"http://localhost:4200".parse().unwrap(),
"http://127.0.0.1:4200".parse().unwrap(),
"http://localhost:8080".parse().unwrap(),
"http://127.0.0.1:8080".parse().unwrap(),
];
// Add the actual listen address variants
if listen_addr.port() != 4200 && listen_addr.port() != 8080 {
if let Ok(v) = format!("http://localhost:{}", listen_addr.port()).parse() {
origins.push(v);
}
if let Ok(v) = format!("http://127.0.0.1:{}", listen_addr.port()).parse() {
origins.push(v);
}
}
CorsLayer::new()
.allow_origin(origins)
.allow_methods(tower_http::cors::Any)
.allow_headers(tower_http::cors::Any)
};
let api_key = state.kernel.config.api_key.clone();
let gcra_limiter = rate_limiter::create_rate_limiter();
let app = Router::new()
.route("/", axum::routing::get(webchat::webchat_page))
.route("/logo.png", axum::routing::get(webchat::logo_png))
.route("/favicon.ico", axum::routing::get(webchat::favicon_ico))
.route(
"/api/metrics",
axum::routing::get(routes::prometheus_metrics),
)
.route("/api/health", axum::routing::get(routes::health))
.route(
"/api/health/detail",
axum::routing::get(routes::health_detail),
)
.route("/api/status", axum::routing::get(routes::status))
.route("/api/version", axum::routing::get(routes::version))
.route(
"/api/agents",
axum::routing::get(routes::list_agents).post(routes::spawn_agent),
)
.route(
"/api/agents/{id}",
axum::routing::get(routes::get_agent).delete(routes::kill_agent),
)
.route(
"/api/agents/{id}/mode",
axum::routing::put(routes::set_agent_mode),
)
.route("/api/profiles", axum::routing::get(routes::list_profiles))
.route(
"/api/agents/{id}/message",
axum::routing::post(routes::send_message),
)
.route(
"/api/agents/{id}/message/stream",
axum::routing::post(routes::send_message_stream),
)
.route(
"/api/agents/{id}/session",
axum::routing::get(routes::get_agent_session),
)
.route(
"/api/agents/{id}/sessions",
axum::routing::get(routes::list_agent_sessions).post(routes::create_agent_session),
)
.route(
"/api/agents/{id}/sessions/{session_id}/switch",
axum::routing::post(routes::switch_agent_session),
)
.route(
"/api/agents/{id}/session/reset",
axum::routing::post(routes::reset_session),
)
.route(
"/api/agents/{id}/session/compact",
axum::routing::post(routes::compact_session),
)
.route(
"/api/agents/{id}/stop",
axum::routing::post(routes::stop_agent),
)
.route(
"/api/agents/{id}/model",
axum::routing::put(routes::set_model),
)
.route(
"/api/agents/{id}/skills",
axum::routing::get(routes::get_agent_skills).put(routes::set_agent_skills),
)
.route(
"/api/agents/{id}/mcp_servers",
axum::routing::get(routes::get_agent_mcp_servers).put(routes::set_agent_mcp_servers),
)
.route(
"/api/agents/{id}/identity",
axum::routing::patch(routes::update_agent_identity),
)
.route(
"/api/agents/{id}/config",
axum::routing::patch(routes::patch_agent_config),
)
.route(
"/api/agents/{id}/clone",
axum::routing::post(routes::clone_agent),
)
.route(
"/api/agents/{id}/files",
axum::routing::get(routes::list_agent_files),
)
.route(
"/api/agents/{id}/files/{filename}",
axum::routing::get(routes::get_agent_file).put(routes::set_agent_file),
)
.route(
"/api/agents/{id}/deliveries",
axum::routing::get(routes::get_agent_deliveries),
)
.route(
"/api/agents/{id}/upload",
axum::routing::post(routes::upload_file),
)
.route("/api/agents/{id}/ws", axum::routing::get(ws::agent_ws))
// Upload serving
.route(
"/api/uploads/{file_id}",
axum::routing::get(routes::serve_upload),
)
// Channel endpoints
.route("/api/channels", axum::routing::get(routes::list_channels))
.route(
"/api/channels/{name}/configure",
axum::routing::post(routes::configure_channel).delete(routes::remove_channel),
)
.route(
"/api/channels/{name}/test",
axum::routing::post(routes::test_channel),
)
.route(
"/api/channels/reload",
axum::routing::post(routes::reload_channels),
)
// WhatsApp QR login flow
.route(
"/api/channels/whatsapp/qr/start",
axum::routing::post(routes::whatsapp_qr_start),
)
.route(
"/api/channels/whatsapp/qr/status",
axum::routing::get(routes::whatsapp_qr_status),
)
// Template endpoints
.route("/api/templates", axum::routing::get(routes::list_templates))
.route(
"/api/templates/{name}",
axum::routing::get(routes::get_template),
)
// Memory endpoints
.route(
"/api/memory/agents/{id}/kv",
axum::routing::get(routes::get_agent_kv),
)
.route(
"/api/memory/agents/{id}/kv/{key}",
axum::routing::get(routes::get_agent_kv_key)
.put(routes::set_agent_kv_key)
.delete(routes::delete_agent_kv_key),
)
// Trigger endpoints
.route(
"/api/triggers",
axum::routing::get(routes::list_triggers).post(routes::create_trigger),
)
.route(
"/api/triggers/{id}",
axum::routing::delete(routes::delete_trigger).put(routes::update_trigger),
)
// Schedule (cron job) endpoints
.route(
"/api/schedules",
axum::routing::get(routes::list_schedules).post(routes::create_schedule),
)
.route(
"/api/schedules/{id}",
axum::routing::delete(routes::delete_schedule).put(routes::update_schedule),
)
.route(
"/api/schedules/{id}/run",
axum::routing::post(routes::run_schedule),
)
// Workflow endpoints
.route(
"/api/workflows",
axum::routing::get(routes::list_workflows).post(routes::create_workflow),
)
.route(
"/api/workflows/{id}/run",
axum::routing::post(routes::run_workflow),
)
.route(
"/api/workflows/{id}/runs",
axum::routing::get(routes::list_workflow_runs),
)
// Skills endpoints
.route("/api/skills", axum::routing::get(routes::list_skills))
.route(
"/api/skills/install",
axum::routing::post(routes::install_skill),
)
.route(
"/api/skills/uninstall",
axum::routing::post(routes::uninstall_skill),
)
.route(
"/api/marketplace/search",
axum::routing::get(routes::marketplace_search),
)
// ClawHub (OpenClaw ecosystem) endpoints
.route(
"/api/clawhub/search",
axum::routing::get(routes::clawhub_search),
)
.route(
"/api/clawhub/browse",
axum::routing::get(routes::clawhub_browse),
)
.route(
"/api/clawhub/skill/{slug}",
axum::routing::get(routes::clawhub_skill_detail),
)
.route(
"/api/clawhub/install",
axum::routing::post(routes::clawhub_install),
)
// Hands endpoints
.route("/api/hands", axum::routing::get(routes::list_hands))
.route(
"/api/hands/active",
axum::routing::get(routes::list_active_hands),
)
.route("/api/hands/{hand_id}", axum::routing::get(routes::get_hand))
.route(
"/api/hands/{hand_id}/activate",
axum::routing::post(routes::activate_hand),
)
.route(
"/api/hands/{hand_id}/check-deps",
axum::routing::post(routes::check_hand_deps),
)
.route(
"/api/hands/{hand_id}/install-deps",
axum::routing::post(routes::install_hand_deps),
)
.route(
"/api/hands/instances/{id}/pause",
axum::routing::post(routes::pause_hand),
)
.route(
"/api/hands/instances/{id}/resume",
axum::routing::post(routes::resume_hand),
)
.route(
"/api/hands/instances/{id}",
axum::routing::delete(routes::deactivate_hand),
)
.route(
"/api/hands/instances/{id}/stats",
axum::routing::get(routes::hand_stats),
)
.route(
"/api/hands/instances/{id}/browser",
axum::routing::get(routes::hand_instance_browser),
)
// MCP server endpoints
.route(
"/api/mcp/servers",
axum::routing::get(routes::list_mcp_servers),
)
// Audit endpoints
.route(
"/api/audit/recent",
axum::routing::get(routes::audit_recent),
)
.route(
"/api/audit/verify",
axum::routing::get(routes::audit_verify),
)
// Live log streaming (SSE)
.route("/api/logs/stream", axum::routing::get(routes::logs_stream))
// Peer/Network endpoints
.route("/api/peers", axum::routing::get(routes::list_peers))
.route(
"/api/network/status",
axum::routing::get(routes::network_status),
)
// Tools endpoint
.route("/api/tools", axum::routing::get(routes::list_tools))
// Config endpoints
.route("/api/config", axum::routing::get(routes::get_config))
.route(
"/api/config/schema",
axum::routing::get(routes::config_schema),
)
.route("/api/config/set", axum::routing::post(routes::config_set))
// Approval endpoints
.route(
"/api/approvals",
axum::routing::get(routes::list_approvals).post(routes::create_approval),
)
.route(
"/api/approvals/{id}/approve",
axum::routing::post(routes::approve_request),
)
.route(
"/api/approvals/{id}/reject",
axum::routing::post(routes::reject_request),
)
// Usage endpoints
.route("/api/usage", axum::routing::get(routes::usage_stats))
.route(
"/api/usage/summary",
axum::routing::get(routes::usage_summary),
)
.route(
"/api/usage/by-model",
axum::routing::get(routes::usage_by_model),
)
.route("/api/usage/daily", axum::routing::get(routes::usage_daily))
// Budget endpoints
.route(
"/api/budget",
axum::routing::get(routes::budget_status).put(routes::update_budget),
)
.route(
"/api/budget/agents",
axum::routing::get(routes::agent_budget_ranking),
)
.route(
"/api/budget/agents/{id}",
axum::routing::get(routes::agent_budget_status),
)
// Session endpoints
.route("/api/sessions", axum::routing::get(routes::list_sessions))
.route(
"/api/sessions/{id}",
axum::routing::delete(routes::delete_session),
)
.route(
"/api/sessions/{id}/label",
axum::routing::put(routes::set_session_label),
)
.route(
"/api/agents/{id}/sessions/by-label/{label}",
axum::routing::get(routes::find_session_by_label),
)
// Agent update
.route(
"/api/agents/{id}/update",
axum::routing::put(routes::update_agent),
)
// Security dashboard endpoint
.route("/api/security", axum::routing::get(routes::security_status))
// Model catalog endpoints
.route("/api/models", axum::routing::get(routes::list_models))
.route(
"/api/models/aliases",
axum::routing::get(routes::list_aliases),
)
.route(
"/api/models/custom",
axum::routing::post(routes::add_custom_model),
)
.route(
"/api/models/custom/{*id}",
axum::routing::delete(routes::remove_custom_model),
)
.route("/api/models/{*id}", axum::routing::get(routes::get_model))
.route("/api/providers", axum::routing::get(routes::list_providers))
// Copilot OAuth (must be before parametric {name} routes)
.route(
"/api/providers/github-copilot/oauth/start",
axum::routing::post(routes::copilot_oauth_start),
)
.route(
"/api/providers/github-copilot/oauth/poll/{poll_id}",
axum::routing::get(routes::copilot_oauth_poll),
)
.route(
"/api/providers/{name}/key",
axum::routing::post(routes::set_provider_key).delete(routes::delete_provider_key),
)
.route(
"/api/providers/{name}/test",
axum::routing::post(routes::test_provider),
)
.route(
"/api/providers/{name}/url",
axum::routing::put(routes::set_provider_url),
)
.route(
"/api/skills/create",
axum::routing::post(routes::create_skill),
)
// Migration endpoints
.route(
"/api/migrate/detect",
axum::routing::get(routes::migrate_detect),
)
.route(
"/api/migrate/scan",
axum::routing::post(routes::migrate_scan),
)
.route("/api/migrate", axum::routing::post(routes::run_migrate))
// Cron job management endpoints
.route(
"/api/cron/jobs",
axum::routing::get(routes::list_cron_jobs).post(routes::create_cron_job),
)
.route(
"/api/cron/jobs/{id}",
axum::routing::delete(routes::delete_cron_job),
)
.route(
"/api/cron/jobs/{id}/enable",
axum::routing::put(routes::toggle_cron_job),
)
.route(
"/api/cron/jobs/{id}/status",
axum::routing::get(routes::cron_job_status),
)
// Webhook trigger endpoints (external event injection)
.route("/hooks/wake", axum::routing::post(routes::webhook_wake))
.route("/hooks/agent", axum::routing::post(routes::webhook_agent))
.route("/api/shutdown", axum::routing::post(routes::shutdown))
// Chat commands endpoint (dynamic slash menu)
.route("/api/commands", axum::routing::get(routes::list_commands))
// Config reload endpoint
.route(
"/api/config/reload",
axum::routing::post(routes::config_reload),
)
// Agent binding routes
.route(
"/api/bindings",
axum::routing::get(routes::list_bindings).post(routes::add_binding),
)
.route(
"/api/bindings/{index}",
axum::routing::delete(routes::remove_binding),
)
// A2A (Agent-to-Agent) Protocol endpoints
.route(
"/.well-known/agent.json",
axum::routing::get(routes::a2a_agent_card),
)
.route("/a2a/agents", axum::routing::get(routes::a2a_list_agents))
.route(
"/a2a/tasks/send",
axum::routing::post(routes::a2a_send_task),
)
.route("/a2a/tasks/{id}", axum::routing::get(routes::a2a_get_task))
.route(
"/a2a/tasks/{id}/cancel",
axum::routing::post(routes::a2a_cancel_task),
)
// A2A management (outbound) endpoints
.route(
"/api/a2a/agents",
axum::routing::get(routes::a2a_list_external_agents),
)
.route(
"/api/a2a/discover",
axum::routing::post(routes::a2a_discover_external),
)
.route(
"/api/a2a/send",
axum::routing::post(routes::a2a_send_external),
)
.route(
"/api/a2a/tasks/{id}/status",
axum::routing::get(routes::a2a_external_task_status),
)
// Integration management endpoints
.route(
"/api/integrations",
axum::routing::get(routes::list_integrations),
)
.route(
"/api/integrations/available",
axum::routing::get(routes::list_available_integrations),
)
.route(
"/api/integrations/add",
axum::routing::post(routes::add_integration),
)
.route(
"/api/integrations/{id}",
axum::routing::delete(routes::remove_integration),
)
.route(
"/api/integrations/{id}/reconnect",
axum::routing::post(routes::reconnect_integration),
)
.route(
"/api/integrations/health",
axum::routing::get(routes::integrations_health),
)
.route(
"/api/integrations/reload",
axum::routing::post(routes::reload_integrations),
)
// Device pairing endpoints
.route(
"/api/pairing/request",
axum::routing::post(routes::pairing_request),
)
.route(
"/api/pairing/complete",
axum::routing::post(routes::pairing_complete),
)
.route(
"/api/pairing/devices",
axum::routing::get(routes::pairing_devices),
)
.route(
"/api/pairing/devices/{id}",
axum::routing::delete(routes::pairing_remove_device),
)
.route(
"/api/pairing/notify",
axum::routing::post(routes::pairing_notify),
)
// MCP HTTP endpoint (exposes MCP protocol over HTTP)
.route("/mcp", axum::routing::post(routes::mcp_http))
// OpenAI-compatible API
.route(
"/v1/chat/completions",
axum::routing::post(crate::openai_compat::chat_completions),
)
.route(
"/v1/models",
axum::routing::get(crate::openai_compat::list_models),
)
.layer(axum::middleware::from_fn_with_state(
api_key,
middleware::auth,
))
.layer(axum::middleware::from_fn_with_state(
gcra_limiter,
rate_limiter::gcra_rate_limit,
))
.layer(axum::middleware::from_fn(middleware::security_headers))
.layer(axum::middleware::from_fn(middleware::request_logging))
.layer(CompressionLayer::new())
.layer(TraceLayer::new_for_http())
.layer(cors)
.with_state(state.clone());
(app, state)
}
/// Start the OpenFang daemon: boot kernel + HTTP API server.
///
/// This function blocks until Ctrl+C or a shutdown request.
pub async fn run_daemon(
kernel: OpenFangKernel,
listen_addr: &str,
daemon_info_path: Option<&Path>,
) -> Result<(), Box<dyn std::error::Error>> {
let addr: SocketAddr = listen_addr.parse()?;
let kernel = Arc::new(kernel);
kernel.set_self_handle();
kernel.start_background_agents();
// Config file hot-reload watcher (polls every 30 seconds)
{
let k = kernel.clone();
let config_path = kernel.config.home_dir.join("config.toml");
tokio::spawn(async move {
let mut last_modified = std::fs::metadata(&config_path)
.and_then(|m| m.modified())
.ok();
loop {
tokio::time::sleep(std::time::Duration::from_secs(30)).await;
let current = std::fs::metadata(&config_path)
.and_then(|m| m.modified())
.ok();
if current != last_modified && current.is_some() {
last_modified = current;
tracing::info!("Config file changed, reloading...");
match k.reload_config() {
Ok(plan) => {
if plan.has_changes() {
tracing::info!("Config hot-reload applied: {:?}", plan.hot_actions);
} else {
tracing::debug!("Config hot-reload: no actionable changes");
}
}
Err(e) => tracing::warn!("Config hot-reload failed: {e}"),
}
}
}
});
}
let (app, state) = build_router(kernel.clone(), addr).await;
// Write daemon info file
if let Some(info_path) = daemon_info_path {
// Check if another daemon is already running with this PID file
if info_path.exists() {
if let Ok(existing) = std::fs::read_to_string(info_path) {
if let Ok(info) = serde_json::from_str::<DaemonInfo>(&existing) {
if is_process_alive(info.pid) {
return Err(format!(
"Another daemon (PID {}) is already running at {}",
info.pid, info.listen_addr
)
.into());
}
}
}
// Stale PID file, remove it
let _ = std::fs::remove_file(info_path);
}
let daemon_info = DaemonInfo {
pid: std::process::id(),
listen_addr: addr.to_string(),
started_at: chrono::Utc::now().to_rfc3339(),
version: env!("CARGO_PKG_VERSION").to_string(),
platform: std::env::consts::OS.to_string(),
};
if let Ok(json) = serde_json::to_string_pretty(&daemon_info) {
let _ = std::fs::write(info_path, json);
// SECURITY: Restrict daemon info file permissions (contains PID and port).
restrict_permissions(info_path);
}
}
info!("OpenFang API server listening on http://{addr}");
info!("WebChat UI available at http://{addr}/",);
info!("WebSocket endpoint: ws://{addr}/api/agents/{{id}}/ws",);
let listener = tokio::net::TcpListener::bind(addr).await?;
// Run server with graceful shutdown.
// SECURITY: `into_make_service_with_connect_info` injects the peer
// SocketAddr so the auth middleware can check for loopback connections.
let api_shutdown = state.shutdown_notify.clone();
axum::serve(
listener,
app.into_make_service_with_connect_info::<SocketAddr>(),
)
.with_graceful_shutdown(shutdown_signal(api_shutdown))
.await?;
// Clean up daemon info file
if let Some(info_path) = daemon_info_path {
let _ = std::fs::remove_file(info_path);
}
// Stop channel bridges
if let Some(ref mut b) = *state.bridge_manager.lock().await {
b.stop().await;
}
// Shutdown kernel
kernel.shutdown();
info!("OpenFang daemon stopped");
Ok(())
}
/// SECURITY: Restrict file permissions to owner-only (0600) on Unix.
/// On non-Unix platforms this is a no-op.
#[cfg(unix)]
fn restrict_permissions(path: &Path) {
use std::os::unix::fs::PermissionsExt;
let _ = std::fs::set_permissions(path, std::fs::Permissions::from_mode(0o600));
}
#[cfg(not(unix))]
fn restrict_permissions(_path: &Path) {}
/// Read daemon info from the standard location.
pub fn read_daemon_info(home_dir: &Path) -> Option<DaemonInfo> {
let info_path = home_dir.join("daemon.json");
let contents = std::fs::read_to_string(info_path).ok()?;
serde_json::from_str(&contents).ok()
}
/// Wait for an OS termination signal OR an API shutdown request.
///
/// On Unix: listens for SIGINT, SIGTERM, and API notify.
/// On Windows: listens for Ctrl+C and API notify.
async fn shutdown_signal(api_shutdown: Arc<tokio::sync::Notify>) {
#[cfg(unix)]
{
use tokio::signal::unix::{signal, SignalKind};
let mut sigint = signal(SignalKind::interrupt()).expect("Failed to listen for SIGINT");
let mut sigterm = signal(SignalKind::terminate()).expect("Failed to listen for SIGTERM");
tokio::select! {
_ = sigint.recv() => {
info!("Received SIGINT (Ctrl+C), shutting down...");
}
_ = sigterm.recv() => {
info!("Received SIGTERM, shutting down...");
}
_ = api_shutdown.notified() => {
info!("Shutdown requested via API, shutting down...");
}
}
}
#[cfg(not(unix))]
{
tokio::select! {
_ = tokio::signal::ctrl_c() => {
info!("Ctrl+C received, shutting down...");
}
_ = api_shutdown.notified() => {
info!("Shutdown requested via API, shutting down...");
}
}
}
}
/// Check if a process with the given PID is still alive.
fn is_process_alive(pid: u32) -> bool {
#[cfg(unix)]
{
// Use kill -0 to check if process exists without sending a signal
std::process::Command::new("kill")
.args(["-0", &pid.to_string()])
.output()
.map(|o| o.status.success())
.unwrap_or(false)
}
#[cfg(windows)]
{
// tasklist /FI "PID eq N" returns "INFO: No tasks..." when no match,
// or a table row with the PID when found. Check exit code and that
// "INFO:" is NOT in the output to confirm the process exists.
std::process::Command::new("tasklist")
.args(["/FI", &format!("PID eq {pid}"), "/NH"])
.output()
.map(|o| {
o.status.success() && {
let out = String::from_utf8_lossy(&o.stdout);
!out.contains("INFO:") && out.contains(&pid.to_string())
}
})
.unwrap_or(false)
}
#[cfg(not(any(unix, windows)))]
{
let _ = pid;
false
}
}

224
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//! Markdown-aware stream chunking.
//!
//! Replaces naive 200-char text buffer flushing with smart chunking that
//! never splits inside fenced code blocks and respects Markdown structure.
/// Markdown-aware stream chunker.
///
/// Buffers incoming text and flushes at natural break points:
/// paragraph boundaries > newlines > sentence endings.
/// Never splits inside fenced code blocks.
pub struct StreamChunker {
buffer: String,
in_code_fence: bool,
fence_marker: String,
min_chunk_chars: usize,
max_chunk_chars: usize,
}
impl StreamChunker {
/// Create a new chunker with custom min/max thresholds.
pub fn new(min_chunk_chars: usize, max_chunk_chars: usize) -> Self {
Self {
buffer: String::new(),
in_code_fence: false,
fence_marker: String::new(),
min_chunk_chars,
max_chunk_chars,
}
}
/// Push new text into the buffer. Updates code fence tracking.
pub fn push(&mut self, text: &str) {
for line in text.split_inclusive('\n') {
self.buffer.push_str(line);
// Track code fence state
let trimmed = line.trim();
if trimmed.starts_with("```") {
if self.in_code_fence {
// Check if this closes the current fence
if trimmed == "```" || trimmed.starts_with(&self.fence_marker) {
self.in_code_fence = false;
self.fence_marker.clear();
}
} else {
self.in_code_fence = true;
self.fence_marker = "```".to_string();
}
}
}
}
/// Try to flush a chunk from the buffer.
///
/// Returns `Some(chunk)` if enough content has accumulated,
/// `None` if we should wait for more input.
pub fn try_flush(&mut self) -> Option<String> {
if self.buffer.len() < self.min_chunk_chars {
return None;
}
// If inside a code fence and under max, wait for fence to close
if self.in_code_fence && self.buffer.len() < self.max_chunk_chars {
return None;
}
// If at max inside a fence, force-close and flush
if self.in_code_fence && self.buffer.len() >= self.max_chunk_chars {
// Close the fence, flush everything, reopen on next push
let mut chunk = std::mem::take(&mut self.buffer);
chunk.push_str("\n```\n");
// Mark that we need to reopen the fence
self.buffer = format!("```{}\n", self.fence_marker.trim_start_matches('`'));
return Some(chunk);
}
// Find best break point
let search_range = self.min_chunk_chars..self.buffer.len().min(self.max_chunk_chars);
// Priority 1: Paragraph break (double newline)
if let Some(pos) = find_last_in_range(&self.buffer, "\n\n", &search_range) {
let break_at = pos + 2;
let chunk = self.buffer[..break_at].to_string();
self.buffer = self.buffer[break_at..].to_string();
return Some(chunk);
}
// Priority 2: Single newline
if let Some(pos) = find_last_in_range(&self.buffer, "\n", &search_range) {
let break_at = pos + 1;
let chunk = self.buffer[..break_at].to_string();
self.buffer = self.buffer[break_at..].to_string();
return Some(chunk);
}
// Priority 3: Sentence ending (". ", "! ", "? ")
for ending in &[". ", "! ", "? "] {
if let Some(pos) = find_last_in_range(&self.buffer, ending, &search_range) {
let break_at = pos + ending.len();
let chunk = self.buffer[..break_at].to_string();
self.buffer = self.buffer[break_at..].to_string();
return Some(chunk);
}
}
// Priority 4: Forced break at max_chunk_chars
if self.buffer.len() >= self.max_chunk_chars {
let break_at = self.max_chunk_chars;
let chunk = self.buffer[..break_at].to_string();
self.buffer = self.buffer[break_at..].to_string();
return Some(chunk);
}
None
}
/// Force-flush all remaining text.
pub fn flush_remaining(&mut self) -> Option<String> {
if self.buffer.is_empty() {
None
} else {
Some(std::mem::take(&mut self.buffer))
}
}
/// Current buffer length.
pub fn buffered_len(&self) -> usize {
self.buffer.len()
}
/// Whether currently inside a code fence.
pub fn is_in_code_fence(&self) -> bool {
self.in_code_fence
}
}
/// Find the last occurrence of a pattern within a byte range.
fn find_last_in_range(text: &str, pattern: &str, range: &std::ops::Range<usize>) -> Option<usize> {
let search_text = &text[range.start..range.end.min(text.len())];
search_text.rfind(pattern).map(|pos| range.start + pos)
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_basic_chunking() {
let mut chunker = StreamChunker::new(10, 50);
chunker.push("Hello world.\nThis is a test.\nAnother line.\n");
let chunk = chunker.try_flush();
assert!(chunk.is_some());
let text = chunk.unwrap();
// Should break at a newline
assert!(text.ends_with('\n'));
}
#[test]
fn test_code_fence_not_split() {
let mut chunker = StreamChunker::new(5, 200);
chunker.push("Before\n```python\ndef foo():\n pass\n```\nAfter\n");
// Should not flush mid-fence
// Since buffer is >5 chars and fence is now closed, should flush
let chunk = chunker.try_flush();
assert!(chunk.is_some());
let text = chunk.unwrap();
// If it includes the code block, the fence should be complete
if text.contains("```python") {
assert!(text.contains("```\n") || text.ends_with("```"));
}
}
#[test]
fn test_code_fence_force_close_at_max() {
let mut chunker = StreamChunker::new(5, 30);
chunker.push("```python\nline1\nline2\nline3\nline4\nline5\nline6\n");
// Buffer exceeds max while in fence — should force close
let chunk = chunker.try_flush();
assert!(chunk.is_some());
let text = chunk.unwrap();
assert!(text.contains("```\n")); // force-closed fence
}
#[test]
fn test_paragraph_break_priority() {
let mut chunker = StreamChunker::new(10, 200);
chunker.push("First paragraph text.\n\nSecond paragraph text.\n");
let chunk = chunker.try_flush();
assert!(chunk.is_some());
let text = chunk.unwrap();
assert!(text.ends_with("\n\n"));
}
#[test]
fn test_flush_remaining() {
let mut chunker = StreamChunker::new(100, 200);
chunker.push("short");
// try_flush should return None (under min)
assert!(chunker.try_flush().is_none());
// flush_remaining should return everything
let remaining = chunker.flush_remaining();
assert_eq!(remaining, Some("short".to_string()));
// Second flush should be None
assert!(chunker.flush_remaining().is_none());
}
#[test]
fn test_sentence_break() {
let mut chunker = StreamChunker::new(10, 200);
chunker.push("This is the first sentence. This is the second sentence. More text here.");
let chunk = chunker.try_flush();
assert!(chunk.is_some());
let text = chunk.unwrap();
// Should break at a sentence ending
assert!(text.ends_with(". ") || text.ends_with(".\n"));
}
}

160
crates/openfang-api/src/stream_dedup.rs Normal file
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@@ -0,0 +1,160 @@
//! Streaming duplicate detection.
//!
//! Detects when the LLM repeats text that was already sent (e.g., repeating
//! tool output verbatim). Uses exact + normalized matching with a sliding window.
/// Minimum text length to consider for deduplication.
const MIN_DEDUP_LENGTH: usize = 10;
/// Number of recent chunks to keep in the dedup window.
const DEDUP_WINDOW: usize = 50;
/// Streaming duplicate detector.
pub struct StreamDedup {
/// Recent chunks (exact text).
recent_chunks: Vec<String>,
/// Recent chunks (normalized: lowercased, whitespace-collapsed).
recent_normalized: Vec<String>,
}
impl StreamDedup {
/// Create a new dedup detector.
pub fn new() -> Self {
Self {
recent_chunks: Vec::with_capacity(DEDUP_WINDOW),
recent_normalized: Vec::with_capacity(DEDUP_WINDOW),
}
}
/// Check if text is a duplicate of recently sent content.
///
/// Returns `true` if the text matches (exact or normalized) any
/// recent chunk. Skips very short texts.
pub fn is_duplicate(&self, text: &str) -> bool {
if text.len() < MIN_DEDUP_LENGTH {
return false;
}
// Exact match
if self.recent_chunks.iter().any(|c| c == text) {
return true;
}
// Normalized match
let normalized = normalize(text);
self.recent_normalized.iter().any(|c| c == &normalized)
}
/// Record text that was successfully sent to the client.
pub fn record_sent(&mut self, text: &str) {
if text.len() < MIN_DEDUP_LENGTH {
return;
}
// Evict oldest if at capacity
if self.recent_chunks.len() >= DEDUP_WINDOW {
self.recent_chunks.remove(0);
self.recent_normalized.remove(0);
}
self.recent_chunks.push(text.to_string());
self.recent_normalized.push(normalize(text));
}
/// Clear the dedup window.
pub fn clear(&mut self) {
self.recent_chunks.clear();
self.recent_normalized.clear();
}
}
impl Default for StreamDedup {
fn default() -> Self {
Self::new()
}
}
/// Normalize text for fuzzy matching: lowercase + collapse whitespace.
fn normalize(text: &str) -> String {
let mut result = String::with_capacity(text.len());
let mut last_was_space = false;
for ch in text.chars() {
if ch.is_whitespace() {
if !last_was_space {
result.push(' ');
last_was_space = true;
}
} else {
result.push(ch.to_lowercase().next().unwrap_or(ch));
last_was_space = false;
}
}
result.trim().to_string()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_exact_match_detected() {
let mut dedup = StreamDedup::new();
dedup.record_sent("This is a test chunk of text that was sent.");
assert!(dedup.is_duplicate("This is a test chunk of text that was sent."));
}
#[test]
fn test_normalized_match_detected() {
let mut dedup = StreamDedup::new();
dedup.record_sent("This is a test chunk");
// Same text but different whitespace/case
assert!(dedup.is_duplicate("this is a test chunk"));
}
#[test]
fn test_short_text_skipped() {
let mut dedup = StreamDedup::new();
dedup.record_sent("short");
assert!(!dedup.is_duplicate("short"));
}
#[test]
fn test_window_rollover() {
let mut dedup = StreamDedup::new();
// Fill the window
for i in 0..DEDUP_WINDOW {
dedup.record_sent(&format!("chunk number {} is here", i));
}
// Add one more — should evict the oldest
dedup.record_sent("new chunk that is quite long");
// Oldest should no longer be detected
assert!(!dedup.is_duplicate("chunk number 0 is here"));
// Newest should be detected
assert!(dedup.is_duplicate("new chunk that is quite long"));
}
#[test]
fn test_no_false_positives() {
let mut dedup = StreamDedup::new();
dedup.record_sent("The quick brown fox jumps over the lazy dog");
assert!(!dedup.is_duplicate("A completely different sentence here"));
}
#[test]
fn test_clear() {
let mut dedup = StreamDedup::new();
dedup.record_sent("This is test content here");
assert!(dedup.is_duplicate("This is test content here"));
dedup.clear();
assert!(!dedup.is_duplicate("This is test content here"));
}
#[test]
fn test_normalize() {
assert_eq!(normalize("Hello World"), "hello world");
assert_eq!(normalize(" spaced out "), "spaced out");
assert_eq!(normalize("UPPER case"), "upper case");
}
}

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//! Request/response types for the OpenFang API.
use serde::{Deserialize, Serialize};
/// Request to spawn an agent from a TOML manifest string.
#[derive(Debug, Deserialize)]
pub struct SpawnRequest {
/// Agent manifest as TOML string.
pub manifest_toml: String,
/// Optional Ed25519 signed manifest envelope (JSON).
/// When present, the signature is verified before spawning.
#[serde(default)]
pub signed_manifest: Option<String>,
}
/// Response after spawning an agent.
#[derive(Debug, Serialize)]
pub struct SpawnResponse {
pub agent_id: String,
pub name: String,
}
/// A file attachment reference (from a prior upload).
#[derive(Debug, Clone, Deserialize)]
pub struct AttachmentRef {
pub file_id: String,
#[serde(default)]
pub filename: String,
#[serde(default)]
pub content_type: String,
}
/// Request to send a message to an agent.
#[derive(Debug, Deserialize)]
pub struct MessageRequest {
pub message: String,
/// Optional file attachments (uploaded via /upload endpoint).
#[serde(default)]
pub attachments: Vec<AttachmentRef>,
}
/// Response from sending a message.
#[derive(Debug, Serialize)]
pub struct MessageResponse {
pub response: String,
pub input_tokens: u64,
pub output_tokens: u64,
pub iterations: u32,
#[serde(skip_serializing_if = "Option::is_none")]
pub cost_usd: Option<f64>,
}
/// Request to install a skill from the marketplace.
#[derive(Debug, Deserialize)]
pub struct SkillInstallRequest {
pub name: String,
}
/// Request to uninstall a skill.
#[derive(Debug, Deserialize)]
pub struct SkillUninstallRequest {
pub name: String,
}
/// Request to update an agent's manifest.
#[derive(Debug, Deserialize)]
pub struct AgentUpdateRequest {
pub manifest_toml: String,
}
/// Request to change an agent's operational mode.
#[derive(Debug, Deserialize)]
pub struct SetModeRequest {
pub mode: openfang_types::agent::AgentMode,
}
/// Request to run a migration.
#[derive(Debug, Deserialize)]
pub struct MigrateRequest {
pub source: String,
pub source_dir: String,
pub target_dir: String,
#[serde(default)]
pub dry_run: bool,
}
/// Request to scan a directory for migration.
#[derive(Debug, Deserialize)]
pub struct MigrateScanRequest {
pub path: String,
}
/// Request to install a skill from ClawHub.
#[derive(Debug, Deserialize)]
pub struct ClawHubInstallRequest {
/// ClawHub skill slug (e.g., "github-helper").
pub slug: String,
}

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//! Embedded WebChat UI served as static HTML.
//!
//! The production dashboard is assembled at compile time from separate
//! HTML/CSS/JS files under `static/` using `include_str!()`. This keeps
//! single-binary deployment while allowing organized source files.
//!
//! Features:
//! - Alpine.js SPA with hash-based routing (10 panels)
//! - Dark/light theme toggle with system preference detection
//! - Responsive layout with collapsible sidebar
//! - Markdown rendering + syntax highlighting (bundled locally)
//! - WebSocket real-time chat with HTTP fallback
//! - Agent management, workflows, memory browser, audit log, and more
use axum::http::header;
use axum::response::IntoResponse;
/// Compile-time ETag based on the crate version.
const ETAG: &str = concat!("\"openfang-", env!("CARGO_PKG_VERSION"), "\"");
/// Embedded logo PNG for single-binary deployment.
const LOGO_PNG: &[u8] = include_bytes!("../static/logo.png");
/// Embedded favicon ICO for browser tabs.
const FAVICON_ICO: &[u8] = include_bytes!("../static/favicon.ico");
/// GET /logo.png — Serve the OpenFang logo.
pub async fn logo_png() -> impl IntoResponse {
(
[
(header::CONTENT_TYPE, "image/png"),
(header::CACHE_CONTROL, "public, max-age=86400, immutable"),
],
LOGO_PNG,
)
}
/// GET /favicon.ico — Serve the OpenFang favicon.
pub async fn favicon_ico() -> impl IntoResponse {
(
[
(header::CONTENT_TYPE, "image/x-icon"),
(header::CACHE_CONTROL, "public, max-age=86400, immutable"),
],
FAVICON_ICO,
)
}
/// GET / — Serve the OpenFang Dashboard single-page application.
///
/// Returns the full SPA with ETag header based on package version for caching.
pub async fn webchat_page() -> impl IntoResponse {
(
[
(header::CONTENT_TYPE, "text/html; charset=utf-8"),
(header::ETAG, ETAG),
(
header::CACHE_CONTROL,
"public, max-age=3600, must-revalidate",
),
],
WEBCHAT_HTML,
)
}
/// The embedded HTML/CSS/JS for the OpenFang Dashboard.
///
/// Assembled at compile time from organized static files.
/// All vendor libraries (Alpine.js, marked.js, highlight.js) are bundled
/// locally — no CDN dependency. Alpine.js is included LAST because it
/// immediately processes x-data directives and fires alpine:init on load.
const WEBCHAT_HTML: &str = concat!(
include_str!("../static/index_head.html"),
"<style>\n",
include_str!("../static/css/theme.css"),
"\n",
include_str!("../static/css/layout.css"),
"\n",
include_str!("../static/css/components.css"),
"\n",
include_str!("../static/vendor/github-dark.min.css"),
"\n</style>\n",
include_str!("../static/index_body.html"),
// Vendor libs: marked + highlight first (used by app.js)
"<script>\n",
include_str!("../static/vendor/marked.min.js"),
"\n</script>\n",
"<script>\n",
include_str!("../static/vendor/highlight.min.js"),
"\n</script>\n",
// App code
"<script>\n",
include_str!("../static/js/api.js"),
"\n",
include_str!("../static/js/app.js"),
"\n",
include_str!("../static/js/pages/overview.js"),
"\n",
include_str!("../static/js/pages/chat.js"),
"\n",
include_str!("../static/js/pages/agents.js"),
"\n",
include_str!("../static/js/pages/workflows.js"),
"\n",
include_str!("../static/js/pages/workflow-builder.js"),
"\n",
include_str!("../static/js/pages/channels.js"),
"\n",
include_str!("../static/js/pages/skills.js"),
"\n",
include_str!("../static/js/pages/hands.js"),
"\n",
include_str!("../static/js/pages/scheduler.js"),
"\n",
include_str!("../static/js/pages/settings.js"),
"\n",
include_str!("../static/js/pages/usage.js"),
"\n",
include_str!("../static/js/pages/sessions.js"),
"\n",
include_str!("../static/js/pages/logs.js"),
"\n",
include_str!("../static/js/pages/wizard.js"),
"\n",
include_str!("../static/js/pages/approvals.js"),
"\n</script>\n",
// Alpine.js MUST be last — it processes x-data and fires alpine:init
"<script>\n",
include_str!("../static/vendor/alpine.min.js"),
"\n</script>\n",
"</body></html>"
);

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/* OpenFang Layout — Grid + Sidebar + Responsive */
.app-layout {
display: flex;
height: 100vh;
overflow: hidden;
}
/* Sidebar */
.sidebar {
width: var(--sidebar-width);
background: var(--bg-primary);
border-right: 1px solid var(--border);
display: flex;
flex-direction: column;
flex-shrink: 0;
transition: width var(--transition-normal);
z-index: 100;
}
.sidebar.collapsed {
width: var(--sidebar-collapsed);
}
.sidebar.collapsed .sidebar-label,
.sidebar.collapsed .sidebar-header-text,
.sidebar.collapsed .nav-label { display: none; }
.sidebar.collapsed .nav-item { justify-content: center; padding: 12px 0; }
.sidebar-header {
padding: 16px;
border-bottom: 1px solid var(--border);
display: flex;
align-items: center;
justify-content: space-between;
min-height: 60px;
}
.sidebar-logo {
display: flex;
align-items: center;
gap: 10px;
}
.sidebar-logo img {
width: 28px;
height: 28px;
opacity: 0.8;
transition: opacity 0.2s, transform 0.2s;
}
.sidebar-logo img:hover {
opacity: 1;
transform: scale(1.05);
}
.sidebar-header h1 {
font-size: 14px;
font-weight: 700;
color: var(--accent);
letter-spacing: 3px;
font-family: var(--font-mono);
}
.sidebar-header .version {
font-size: 9px;
color: var(--text-muted);
margin-top: 1px;
letter-spacing: 0.5px;
}
.sidebar-status {
font-size: 11px;
color: var(--success);
display: flex;
align-items: center;
gap: 6px;
padding: 8px 16px;
border-bottom: 1px solid var(--border);
}
.sidebar-status.offline { color: var(--error); }
.status-dot {
width: 6px; height: 6px;
border-radius: 50%;
background: currentColor;
flex-shrink: 0;
box-shadow: 0 0 6px currentColor;
}
.conn-badge {
font-size: 9px;
padding: 1px 5px;
border-radius: 3px;
font-weight: 600;
letter-spacing: 0.5px;
margin-left: auto;
}
.conn-badge.ws { background: var(--success); color: #000; }
.conn-badge.http { background: var(--warning); color: #000; }
/* Navigation */
.sidebar-nav {
flex: 1;
overflow-y: auto;
padding: 8px;
scrollbar-width: none;
}
.sidebar-nav::-webkit-scrollbar { width: 0; }
.nav-section {
margin-bottom: 4px;
}
.nav-section-title {
font-size: 9px;
text-transform: uppercase;
letter-spacing: 1.5px;
color: var(--text-muted);
padding: 12px 12px 4px;
font-weight: 600;
}
.sidebar.collapsed .nav-section-title { display: none; }
.nav-item {
display: flex;
align-items: center;
gap: 10px;
padding: 9px 12px;
border-radius: var(--radius-md);
cursor: pointer;
font-size: 13px;
color: var(--text-dim);
transition: all var(--transition-fast);
text-decoration: none;
border: 1px solid transparent;
white-space: nowrap;
font-weight: 500;
}
.nav-item:hover {
background: var(--surface2);
color: var(--text);
transform: translateX(2px);
}
.nav-item.active {
background: var(--accent);
color: var(--bg-primary);
font-weight: 600;
box-shadow: var(--shadow-sm), 0 2px 8px rgba(255, 92, 0, 0.2);
}
.nav-icon {
width: 18px;
height: 18px;
display: inline-flex;
align-items: center;
justify-content: center;
flex-shrink: 0;
}
.nav-icon svg {
width: 16px;
height: 16px;
fill: none;
stroke: currentColor;
stroke-width: 2;
stroke-linecap: round;
stroke-linejoin: round;
}
/* Sidebar toggle button */
.sidebar-toggle {
padding: 10px 16px;
border-top: 1px solid var(--border);
cursor: pointer;
text-align: center;
font-size: 14px;
color: var(--text-muted);
transition: color var(--transition-fast);
}
.sidebar-toggle:hover { color: var(--text); }
/* Main content area */
.main-content {
flex: 1;
display: flex;
flex-direction: column;
min-width: 0;
overflow: hidden;
background: var(--bg);
}
/* Page wrapper divs (rendered by x-if) must fill the column
and be flex containers so .page-body can scroll. */
.main-content > div {
display: flex;
flex-direction: column;
flex: 1;
min-height: 0;
overflow: hidden;
}
.page-header {
padding: 14px 24px;
border-bottom: 1px solid var(--border);
background: var(--bg-primary);
display: flex;
align-items: center;
justify-content: space-between;
min-height: var(--header-height);
}
.page-header h2 {
font-size: 15px;
font-weight: 600;
letter-spacing: -0.01em;
}
.page-body {
flex: 1;
min-height: 0;
overflow-y: auto;
padding: 24px;
}
/* Mobile overlay */
.sidebar-overlay {
display: none;
position: fixed;
inset: 0;
background: rgba(0,0,0,0.6);
z-index: 99;
}
/* Wide desktop — larger card grids */
@media (min-width: 1400px) {
.card-grid { grid-template-columns: repeat(auto-fill, minmax(320px, 1fr)); }
}
/* Responsive — tablet breakpoint */
@media (max-width: 1024px) {
.card-grid { grid-template-columns: repeat(auto-fill, minmax(240px, 1fr)); }
.security-grid { grid-template-columns: 1fr; }
.cost-charts-row { grid-template-columns: 1fr; }
.overview-grid { grid-template-columns: repeat(auto-fill, minmax(240px, 1fr)); }
.page-body { padding: 16px; }
}
/* Responsive — mobile breakpoint */
@media (max-width: 768px) {
.sidebar {
position: fixed;
left: -300px;
top: 0;
bottom: 0;
transition: left var(--transition-normal);
}
.sidebar.mobile-open {
left: 0;
}
.sidebar.mobile-open + .sidebar-overlay {
display: block;
}
.sidebar.collapsed {
width: var(--sidebar-width);
left: -300px;
}
.mobile-menu-btn { display: flex !important; }
}
@media (min-width: 769px) {
.mobile-menu-btn { display: none !important; }
}
/* Mobile small screen */
@media (max-width: 480px) {
.page-header { flex-direction: column; gap: 8px; align-items: flex-start; padding: 12px 16px; }
.page-body { padding: 12px; }
.stats-row { flex-wrap: wrap; }
.stat-card { min-width: 80px; flex: 1 1 40%; }
.stat-card-lg { min-width: 80px; flex: 1 1 40%; padding: 12px; }
.stat-card-lg .stat-value { font-size: 22px; }
.card-grid { grid-template-columns: 1fr; }
.overview-grid { grid-template-columns: 1fr; }
.input-area { padding: 8px 12px; }
.main-content { padding: 0; }
.table-wrap { font-size: 10px; }
.modal { margin: 8px; max-height: calc(100vh - 16px); }
}
/* Touch-friendly tap targets */
@media (pointer: coarse) {
.btn { min-height: 44px; min-width: 44px; }
.nav-item { min-height: 44px; }
.form-input, .form-select, .form-textarea { min-height: 44px; }
.toggle { min-width: 44px; min-height: 28px; }
}
/* Focus mode — hide sidebar for distraction-free chat */
.app-layout.focus-mode .sidebar { display: none; }
.app-layout.focus-mode .sidebar-overlay { display: none; }
.app-layout.focus-mode .main-content { max-width: 100%; margin-left: 0; }
.app-layout.focus-mode .mobile-menu-btn { display: none !important; }

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/* OpenFang Theme — Premium design system */
/* Font imports in index_head.html: Inter (body) + Geist Mono (code) */
[data-theme="light"], :root {
/* Backgrounds — layered depth */
--bg: #F5F4F2;
--bg-primary: #EDECEB;
--bg-elevated: #F8F7F6;
--surface: #FFFFFF;
--surface2: #F0EEEC;
--surface3: #E8E6E3;
--border: #D5D2CF;
--border-light: #C8C4C0;
--border-subtle: #E0DEDA;
/* Text hierarchy */
--text: #1A1817;
--text-secondary: #3D3935;
--text-dim: #6B6560;
--text-muted: #9A958F;
/* Brand — Orange accent */
--accent: #FF5C00;
--accent-light: #FF7A2E;
--accent-dim: #E05200;
--accent-glow: rgba(255, 92, 0, 0.1);
--accent-subtle: rgba(255, 92, 0, 0.05);
/* Status colors */
--success: #22C55E;
--success-dim: #16A34A;
--success-subtle: rgba(34, 197, 94, 0.08);
--error: #EF4444;
--error-dim: #DC2626;
--error-subtle: rgba(239, 68, 68, 0.06);
--warning: #F59E0B;
--warning-dim: #D97706;
--warning-subtle: rgba(245, 158, 11, 0.08);
--info: #3B82F6;
--info-dim: #2563EB;
--info-subtle: rgba(59, 130, 246, 0.06);
--success-muted: rgba(34, 197, 94, 0.15);
--error-muted: rgba(239, 68, 68, 0.15);
--warning-muted: rgba(245, 158, 11, 0.15);
--info-muted: rgba(59, 130, 246, 0.15);
--border-strong: #B0ACA8;
--card-highlight: rgba(0, 0, 0, 0.02);
/* Chat-specific */
--agent-bg: #F5F4F2;
--user-bg: #FFF3E6;
/* Layout */
--sidebar-width: 240px;
--sidebar-collapsed: 56px;
--header-height: 48px;
/* Radius — slightly larger for premium feel */
--radius-xs: 4px;
--radius-sm: 6px;
--radius-md: 8px;
--radius-lg: 12px;
--radius-xl: 16px;
/* Shadows — 6-level depth system */
--shadow-xs: 0 1px 2px rgba(0,0,0,0.04);
--shadow-sm: 0 1px 3px rgba(0,0,0,0.06), 0 1px 2px rgba(0,0,0,0.04);
--shadow-md: 0 4px 12px rgba(0,0,0,0.07), 0 2px 4px rgba(0,0,0,0.04);
--shadow-lg: 0 12px 28px rgba(0,0,0,0.08), 0 4px 10px rgba(0,0,0,0.05);
--shadow-xl: 0 20px 40px rgba(0,0,0,0.1), 0 8px 16px rgba(0,0,0,0.06);
--shadow-glow: 0 0 40px rgba(0,0,0,0.05);
--shadow-accent: 0 4px 16px rgba(255, 92, 0, 0.12);
--shadow-inset: inset 0 1px 0 rgba(255,255,255,0.5);
/* Typography — dual font system */
--font-sans: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', system-ui, sans-serif;
--font-mono: 'Geist Mono', 'SF Mono', 'Fira Code', 'Cascadia Code', 'JetBrains Mono', monospace;
/* Motion — spring curves for premium feel */
--ease-spring: cubic-bezier(0.34, 1.56, 0.64, 1);
--ease-smooth: cubic-bezier(0.4, 0, 0.2, 1);
--ease-out: cubic-bezier(0, 0, 0.2, 1);
--ease-in: cubic-bezier(0.4, 0, 1, 1);
--transition-fast: 0.15s var(--ease-smooth);
--transition-normal: 0.25s var(--ease-smooth);
--transition-spring: 0.4s var(--ease-spring);
}
[data-theme="dark"] {
--bg: #080706;
--bg-primary: #0F0E0E;
--bg-elevated: #161413;
--surface: #1F1D1C;
--surface2: #2A2725;
--surface3: #1A1817;
--border: #2D2A28;
--border-light: #3D3A38;
--border-subtle: #232120;
--text: #F0EFEE;
--text-secondary: #C4C0BC;
--text-dim: #8A8380;
--text-muted: #5C5754;
--accent: #FF5C00;
--accent-light: #FF7A2E;
--accent-dim: #E05200;
--accent-glow: rgba(255, 92, 0, 0.15);
--accent-subtle: rgba(255, 92, 0, 0.08);
--success: #4ADE80;
--success-dim: #22C55E;
--success-subtle: rgba(74, 222, 128, 0.1);
--error: #EF4444;
--error-dim: #B91C1C;
--error-subtle: rgba(239, 68, 68, 0.1);
--warning: #F59E0B;
--warning-dim: #D97706;
--warning-subtle: rgba(245, 158, 11, 0.1);
--info: #3B82F6;
--info-dim: #2563EB;
--info-subtle: rgba(59, 130, 246, 0.1);
--success-muted: rgba(74, 222, 128, 0.25);
--error-muted: rgba(239, 68, 68, 0.25);
--warning-muted: rgba(245, 158, 11, 0.25);
--info-muted: rgba(59, 130, 246, 0.25);
--border-strong: #4A4644;
--card-highlight: rgba(255, 255, 255, 0.04);
--agent-bg: #1A1817;
--user-bg: #2A1A08;
--shadow-xs: 0 1px 2px rgba(0,0,0,0.3);
--shadow-sm: 0 1px 3px rgba(0,0,0,0.4), 0 1px 2px rgba(0,0,0,0.3);
--shadow-md: 0 4px 12px rgba(0,0,0,0.4), 0 2px 4px rgba(0,0,0,0.3);
--shadow-lg: 0 12px 28px rgba(0,0,0,0.35), 0 4px 10px rgba(0,0,0,0.3);
--shadow-xl: 0 20px 40px rgba(0,0,0,0.4), 0 8px 16px rgba(0,0,0,0.3);
--shadow-glow: 0 0 80px rgba(0,0,0,0.6);
--shadow-accent: 0 4px 16px rgba(255, 92, 0, 0.2);
--shadow-inset: inset 0 1px 0 rgba(255,255,255,0.03);
}
* { margin: 0; padding: 0; box-sizing: border-box; }
html { scroll-behavior: smooth; }
body {
font-family: var(--font-sans);
background: var(--bg);
color: var(--text);
height: 100vh;
overflow: hidden;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
font-size: 14px;
line-height: 1.5;
letter-spacing: -0.01em;
}
/* Mono text utility — only for code/data */
.font-mono, code, pre, .tool-pre, .tool-card-name, .detail-value,
.stat-value, .conn-badge, .version { font-family: var(--font-mono); }
/* Scrollbar — Webkit (Chrome, Edge, Safari) */
::-webkit-scrollbar { width: 6px; height: 6px; }
::-webkit-scrollbar-track { background: transparent; }
::-webkit-scrollbar-thumb { background: var(--border); border-radius: 3px; }
::-webkit-scrollbar-thumb:hover { background: var(--border-light); }
/* Scrollbar — Firefox */
* {
scrollbar-width: thin;
scrollbar-color: var(--border) transparent;
}
::selection {
background: var(--accent);
color: var(--bg-primary);
}
/* Theme transition — smooth switch between light/dark */
body {
transition: background-color 0.3s ease, color 0.3s ease;
}
.sidebar, .main-content, .card, .modal, .tool-card, .toast, .page-header {
transition: background-color 0.3s ease, border-color 0.3s ease, color 0.3s ease, box-shadow 0.3s ease;
}
/* Tighter letter spacing for headings */
h1, h2, h3, .card-header, .stat-value, .page-header h2 { letter-spacing: -0.02em; }
.nav-section-title, .badge, th { letter-spacing: 0.04em; }
/* Focus styles — accessible double-ring with glow */
:focus-visible {
outline: 2px solid var(--accent);
outline-offset: 2px;
box-shadow: 0 0 0 4px var(--accent-glow);
}
button:focus-visible, a:focus-visible, input:focus-visible, select:focus-visible, textarea:focus-visible {
outline: 2px solid var(--accent);
outline-offset: 2px;
box-shadow: 0 0 0 4px var(--accent-glow);
}
/* Entrance animations */
@keyframes fadeIn {
from { opacity: 0; }
to { opacity: 1; }
}
@keyframes slideUp {
from { opacity: 0; transform: translateY(8px); }
to { opacity: 1; transform: translateY(0); }
}
@keyframes slideDown {
from { opacity: 0; transform: translateY(-8px); }
to { opacity: 1; transform: translateY(0); }
}
@keyframes scaleIn {
from { opacity: 0; transform: scale(0.95); }
to { opacity: 1; transform: scale(1); }
}
@keyframes shimmer {
0% { background-position: -200% 0; }
100% { background-position: 200% 0; }
}
@keyframes pulse-ring {
0% { box-shadow: 0 0 0 0 currentColor; }
70% { box-shadow: 0 0 0 4px transparent; }
100% { box-shadow: 0 0 0 0 transparent; }
}
@keyframes spin {
to { transform: rotate(360deg); }
}
/* Staggered card entry animation */
@keyframes cardEntry {
from { opacity: 0; transform: translateY(12px) scale(0.98); }
to { opacity: 1; transform: translateY(0) scale(1); }
}
.animate-entry { animation: cardEntry 0.35s var(--ease-spring) both; }
.stagger-1 { animation-delay: 0.05s; }
.stagger-2 { animation-delay: 0.10s; }
.stagger-3 { animation-delay: 0.15s; }
.stagger-4 { animation-delay: 0.20s; }
.stagger-5 { animation-delay: 0.25s; }
.stagger-6 { animation-delay: 0.30s; }
/* Skeleton loading animation */
.skeleton {
background: linear-gradient(90deg, var(--surface) 25%, var(--surface2) 50%, var(--surface) 75%);
background-size: 200% 100%;
animation: shimmer 1.5s ease-in-out infinite;
border-radius: var(--radius-sm);
}
.skeleton-text { height: 14px; margin-bottom: 8px; }
.skeleton-text:last-child { width: 60%; }
.skeleton-heading { height: 20px; width: 40%; margin-bottom: 12px; }
.skeleton-card { height: 100px; border-radius: var(--radius-lg); }
.skeleton-avatar { width: 32px; height: 32px; border-radius: 50%; }
/* Print styles */
@media print {
.sidebar, .sidebar-overlay, .mobile-menu-btn, .toast-container, .btn { display: none !important; }
.main-content { margin: 0; max-width: 100%; }
body { background: #fff; color: #000; }
}
@media (prefers-reduced-motion: reduce) {
*, *::before, *::after {
animation-duration: 0.01ms !important;
transition-duration: 0.01ms !important;
}
}

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>OpenFang Dashboard</title>
<link rel="icon" type="image/x-icon" href="/favicon.ico">
<link rel="icon" type="image/png" href="/logo.png">
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=Geist+Mono:wght@400;500;600;700&display=swap" rel="stylesheet">
</head>

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// OpenFang API Client — Fetch wrapper, WebSocket manager, auth injection, toast notifications
'use strict';
// ── Toast Notification System ──
var OpenFangToast = (function() {
var _container = null;
var _toastId = 0;
function getContainer() {
if (!_container) {
_container = document.getElementById('toast-container');
if (!_container) {
_container = document.createElement('div');
_container.id = 'toast-container';
_container.className = 'toast-container';
document.body.appendChild(_container);
}
}
return _container;
}
function toast(message, type, duration) {
type = type || 'info';
duration = duration || 4000;
var id = ++_toastId;
var el = document.createElement('div');
el.className = 'toast toast-' + type;
el.setAttribute('data-toast-id', id);
var msgSpan = document.createElement('span');
msgSpan.className = 'toast-msg';
msgSpan.textContent = message;
el.appendChild(msgSpan);
var closeBtn = document.createElement('button');
closeBtn.className = 'toast-close';
closeBtn.textContent = '\u00D7';
closeBtn.onclick = function() { dismissToast(el); };
el.appendChild(closeBtn);
el.onclick = function(e) { if (e.target === el) dismissToast(el); };
getContainer().appendChild(el);
// Auto-dismiss
if (duration > 0) {
setTimeout(function() { dismissToast(el); }, duration);
}
return id;
}
function dismissToast(el) {
if (!el || el.classList.contains('toast-dismiss')) return;
el.classList.add('toast-dismiss');
setTimeout(function() { if (el.parentNode) el.parentNode.removeChild(el); }, 300);
}
function success(msg, duration) { return toast(msg, 'success', duration); }
function error(msg, duration) { return toast(msg, 'error', duration || 6000); }
function warn(msg, duration) { return toast(msg, 'warn', duration || 5000); }
function info(msg, duration) { return toast(msg, 'info', duration); }
// Styled confirmation modal — replaces native confirm()
function confirm(title, message, onConfirm) {
var overlay = document.createElement('div');
overlay.className = 'confirm-overlay';
var modal = document.createElement('div');
modal.className = 'confirm-modal';
var titleEl = document.createElement('div');
titleEl.className = 'confirm-title';
titleEl.textContent = title;
modal.appendChild(titleEl);
var msgEl = document.createElement('div');
msgEl.className = 'confirm-message';
msgEl.textContent = message;
modal.appendChild(msgEl);
var actions = document.createElement('div');
actions.className = 'confirm-actions';
var cancelBtn = document.createElement('button');
cancelBtn.className = 'btn btn-ghost confirm-cancel';
cancelBtn.textContent = 'Cancel';
actions.appendChild(cancelBtn);
var okBtn = document.createElement('button');
okBtn.className = 'btn btn-danger confirm-ok';
okBtn.textContent = 'Confirm';
actions.appendChild(okBtn);
modal.appendChild(actions);
overlay.appendChild(modal);
function close() { if (overlay.parentNode) overlay.parentNode.removeChild(overlay); document.removeEventListener('keydown', onKey); }
cancelBtn.onclick = close;
okBtn.onclick = function() { close(); if (onConfirm) onConfirm(); };
overlay.addEventListener('click', function(e) { if (e.target === overlay) close(); });
function onKey(e) { if (e.key === 'Escape') close(); }
document.addEventListener('keydown', onKey);
document.body.appendChild(overlay);
okBtn.focus();
}
return {
toast: toast,
success: success,
error: error,
warn: warn,
info: info,
confirm: confirm
};
})();
// ── Friendly Error Messages ──
function friendlyError(status, serverMsg) {
if (status === 0 || !status) return 'Cannot reach daemon — is openfang running?';
if (status === 401) return 'Not authorized — check your API key';
if (status === 403) return 'Permission denied';
if (status === 404) return serverMsg || 'Resource not found';
if (status === 429) return 'Rate limited — slow down and try again';
if (status === 413) return 'Request too large';
if (status === 500) return 'Server error — check daemon logs';
if (status === 502 || status === 503) return 'Daemon unavailable — is it running?';
return serverMsg || 'Unexpected error (' + status + ')';
}
// ── API Client ──
var OpenFangAPI = (function() {
var BASE = window.location.origin;
var WS_BASE = BASE.replace(/^http/, 'ws');
var _authToken = '';
// Connection state tracking
var _connectionState = 'connected';
var _reconnectAttempt = 0;
var _connectionListeners = [];
function setAuthToken(token) { _authToken = token; }
function headers() {
var h = { 'Content-Type': 'application/json' };
if (_authToken) h['Authorization'] = 'Bearer ' + _authToken;
return h;
}
function setConnectionState(state) {
if (_connectionState === state) return;
_connectionState = state;
_connectionListeners.forEach(function(fn) { fn(state); });
}
function onConnectionChange(fn) { _connectionListeners.push(fn); }
function request(method, path, body) {
var opts = { method: method, headers: headers() };
if (body !== undefined) opts.body = JSON.stringify(body);
return fetch(BASE + path, opts).then(function(r) {
if (_connectionState !== 'connected') setConnectionState('connected');
if (!r.ok) {
return r.text().then(function(text) {
var msg = '';
try {
var json = JSON.parse(text);
msg = json.error || r.statusText;
} catch(e) {
msg = r.statusText;
}
throw new Error(friendlyError(r.status, msg));
});
}
var ct = r.headers.get('content-type') || '';
if (ct.indexOf('application/json') >= 0) return r.json();
return r.text().then(function(t) {
try { return JSON.parse(t); } catch(e) { return { text: t }; }
});
}).catch(function(e) {
if (e.name === 'TypeError' && e.message.includes('Failed to fetch')) {
setConnectionState('disconnected');
throw new Error('Cannot connect to daemon — is openfang running?');
}
throw e;
});
}
function get(path) { return request('GET', path); }
function post(path, body) { return request('POST', path, body); }
function put(path, body) { return request('PUT', path, body); }
function patch(path, body) { return request('PATCH', path, body); }
function del(path) { return request('DELETE', path); }
// WebSocket manager with auto-reconnect
var _ws = null;
var _wsCallbacks = {};
var _wsConnected = false;
var _wsAgentId = null;
var _reconnectTimer = null;
var _reconnectAttempts = 0;
var MAX_RECONNECT = 5;
function wsConnect(agentId, callbacks) {
wsDisconnect();
_wsCallbacks = callbacks || {};
_wsAgentId = agentId;
_reconnectAttempts = 0;
_doConnect(agentId);
}
function _doConnect(agentId) {
try {
var url = WS_BASE + '/api/agents/' + agentId + '/ws';
if (_authToken) url += '?token=' + encodeURIComponent(_authToken);
_ws = new WebSocket(url);
_ws.onopen = function() {
_wsConnected = true;
_reconnectAttempts = 0;
setConnectionState('connected');
if (_reconnectAttempt > 0) {
OpenFangToast.success('Reconnected');
_reconnectAttempt = 0;
}
if (_wsCallbacks.onOpen) _wsCallbacks.onOpen();
};
_ws.onmessage = function(e) {
try {
var data = JSON.parse(e.data);
if (_wsCallbacks.onMessage) _wsCallbacks.onMessage(data);
} catch(err) { /* ignore parse errors */ }
};
_ws.onclose = function(e) {
_wsConnected = false;
_ws = null;
if (_wsAgentId && _reconnectAttempts < MAX_RECONNECT && e.code !== 1000) {
_reconnectAttempts++;
_reconnectAttempt = _reconnectAttempts;
setConnectionState('reconnecting');
if (_reconnectAttempts === 1) {
OpenFangToast.warn('Connection lost, reconnecting...');
}
var delay = Math.min(1000 * Math.pow(2, _reconnectAttempts - 1), 10000);
_reconnectTimer = setTimeout(function() { _doConnect(_wsAgentId); }, delay);
return;
}
if (_wsAgentId && _reconnectAttempts >= MAX_RECONNECT) {
setConnectionState('disconnected');
OpenFangToast.error('Connection lost — switched to HTTP mode', 0);
}
if (_wsCallbacks.onClose) _wsCallbacks.onClose();
};
_ws.onerror = function() {
_wsConnected = false;
if (_wsCallbacks.onError) _wsCallbacks.onError();
};
} catch(e) {
_wsConnected = false;
}
}
function wsDisconnect() {
_wsAgentId = null;
_reconnectAttempts = MAX_RECONNECT;
if (_reconnectTimer) { clearTimeout(_reconnectTimer); _reconnectTimer = null; }
if (_ws) { _ws.close(1000); _ws = null; }
_wsConnected = false;
}
function wsSend(data) {
if (_ws && _ws.readyState === WebSocket.OPEN) {
_ws.send(JSON.stringify(data));
return true;
}
return false;
}
function isWsConnected() { return _wsConnected; }
function getConnectionState() { return _connectionState; }
function getToken() { return _authToken; }
function upload(agentId, file) {
var hdrs = {
'Content-Type': file.type || 'application/octet-stream',
'X-Filename': file.name
};
if (_authToken) hdrs['Authorization'] = 'Bearer ' + _authToken;
return fetch(BASE + '/api/agents/' + agentId + '/upload', {
method: 'POST',
headers: hdrs,
body: file
}).then(function(r) {
if (!r.ok) throw new Error('Upload failed');
return r.json();
});
}
return {
setAuthToken: setAuthToken,
getToken: getToken,
get: get,
post: post,
put: put,
patch: patch,
del: del,
delete: del,
upload: upload,
wsConnect: wsConnect,
wsDisconnect: wsDisconnect,
wsSend: wsSend,
isWsConnected: isWsConnected,
getConnectionState: getConnectionState,
onConnectionChange: onConnectionChange
};
})();

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// OpenFang App — Alpine.js init, hash router, global store
'use strict';
// Marked.js configuration
if (typeof marked !== 'undefined') {
marked.setOptions({
breaks: true,
gfm: true,
highlight: function(code, lang) {
if (typeof hljs !== 'undefined' && lang && hljs.getLanguage(lang)) {
try { return hljs.highlight(code, { language: lang }).value; } catch(e) {}
}
return code;
}
});
}
function escapeHtml(text) {
var div = document.createElement('div');
div.textContent = text || '';
return div.innerHTML;
}
function renderMarkdown(text) {
if (!text) return '';
if (typeof marked !== 'undefined') {
var html = marked.parse(text);
// Add copy buttons to code blocks
html = html.replace(/<pre><code/g, '<pre><button class="copy-btn" onclick="copyCode(this)">Copy</button><code');
return html;
}
return escapeHtml(text);
}
function copyCode(btn) {
var code = btn.nextElementSibling;
if (code) {
navigator.clipboard.writeText(code.textContent).then(function() {
btn.textContent = 'Copied!';
btn.classList.add('copied');
setTimeout(function() { btn.textContent = 'Copy'; btn.classList.remove('copied'); }, 1500);
});
}
}
// Tool category icon SVGs — returns inline SVG for each tool category
function toolIcon(toolName) {
if (!toolName) return '';
var n = toolName.toLowerCase();
var s = 'width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"';
// File/directory operations
if (n.indexOf('file_') === 0 || n.indexOf('directory_') === 0)
return '<svg ' + s + '><path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z"/><path d="M14 2v6h6"/><path d="M16 13H8"/><path d="M16 17H8"/></svg>';
// Web/fetch
if (n.indexOf('web_') === 0 || n.indexOf('link_') === 0)
return '<svg ' + s + '><circle cx="12" cy="12" r="10"/><path d="M2 12h20"/><path d="M12 2a15 15 0 0 1 4 10 15 15 0 0 1-4 10 15 15 0 0 1-4-10 15 15 0 0 1 4-10z"/></svg>';
// Shell/exec
if (n.indexOf('shell') === 0 || n.indexOf('exec_') === 0)
return '<svg ' + s + '><polyline points="4 17 10 11 4 5"/><line x1="12" y1="19" x2="20" y2="19"/></svg>';
// Agent operations
if (n.indexOf('agent_') === 0)
return '<svg ' + s + '><path d="M17 21v-2a4 4 0 0 0-4-4H5a4 4 0 0 0-4 4v2"/><circle cx="9" cy="7" r="4"/><path d="M23 21v-2a4 4 0 0 0-3-3.87"/><path d="M16 3.13a4 4 0 0 1 0 7.75"/></svg>';
// Memory/knowledge
if (n.indexOf('memory_') === 0 || n.indexOf('knowledge_') === 0)
return '<svg ' + s + '><path d="M2 3h6a4 4 0 0 1 4 4v14a3 3 0 0 0-3-3H2z"/><path d="M22 3h-6a4 4 0 0 0-4 4v14a3 3 0 0 1 3-3h7z"/></svg>';
// Cron/schedule
if (n.indexOf('cron_') === 0 || n.indexOf('schedule_') === 0)
return '<svg ' + s + '><circle cx="12" cy="12" r="10"/><polyline points="12 6 12 12 16 14"/></svg>';
// Browser/playwright
if (n.indexOf('browser_') === 0 || n.indexOf('playwright_') === 0)
return '<svg ' + s + '><rect x="2" y="3" width="20" height="14" rx="2"/><path d="M8 21h8"/><path d="M12 17v4"/></svg>';
// Container/docker
if (n.indexOf('container_') === 0 || n.indexOf('docker_') === 0)
return '<svg ' + s + '><path d="M22 12H2"/><path d="M5.45 5.11L2 12v6a2 2 0 0 0 2 2h16a2 2 0 0 0 2-2v-6l-3.45-6.89A2 2 0 0 0 16.76 4H7.24a2 2 0 0 0-1.79 1.11z"/></svg>';
// Image/media
if (n.indexOf('image_') === 0 || n.indexOf('tts_') === 0)
return '<svg ' + s + '><rect x="3" y="3" width="18" height="18" rx="2"/><circle cx="8.5" cy="8.5" r="1.5"/><polyline points="21 15 16 10 5 21"/></svg>';
// Hand tools
if (n.indexOf('hand_') === 0)
return '<svg ' + s + '><path d="M18 11V6a2 2 0 0 0-2-2 2 2 0 0 0-2 2"/><path d="M14 10V4a2 2 0 0 0-2-2 2 2 0 0 0-2 2v6"/><path d="M10 10.5V6a2 2 0 0 0-2-2 2 2 0 0 0-2 2v8"/><path d="M18 8a2 2 0 1 1 4 0v6a8 8 0 0 1-8 8h-2c-2.8 0-4.5-.9-5.7-2.4L3.4 16a2 2 0 0 1 3.2-2.4L8 15"/></svg>';
// Task/collab
if (n.indexOf('task_') === 0)
return '<svg ' + s + '><path d="M9 11l3 3L22 4"/><path d="M21 12v7a2 2 0 01-2 2H5a2 2 0 01-2-2V5a2 2 0 012-2h11"/></svg>';
// Default — wrench
return '<svg ' + s + '><path d="M14.7 6.3a1 1 0 0 0 0 1.4l1.6 1.6a1 1 0 0 0 1.4 0l3.77-3.77a6 6 0 0 1-7.94 7.94l-6.91 6.91a2.12 2.12 0 0 1-3-3l6.91-6.91a6 6 0 0 1 7.94-7.94l-3.76 3.76z"/></svg>';
}
// Alpine.js global store
document.addEventListener('alpine:init', function() {
// Restore saved API key on load
var savedKey = localStorage.getItem('openfang-api-key');
if (savedKey) OpenFangAPI.setAuthToken(savedKey);
Alpine.store('app', {
agents: [],
connected: false,
booting: true,
wsConnected: false,
connectionState: 'connected',
lastError: '',
version: '0.1.0',
agentCount: 0,
pendingAgent: null,
focusMode: localStorage.getItem('openfang-focus') === 'true',
showOnboarding: false,
showAuthPrompt: false,
toggleFocusMode() {
this.focusMode = !this.focusMode;
localStorage.setItem('openfang-focus', this.focusMode);
},
async refreshAgents() {
try {
var agents = await OpenFangAPI.get('/api/agents');
this.agents = Array.isArray(agents) ? agents : [];
this.agentCount = this.agents.length;
} catch(e) { /* silent */ }
},
async checkStatus() {
try {
var s = await OpenFangAPI.get('/api/status');
this.connected = true;
this.booting = false;
this.lastError = '';
this.version = s.version || '0.1.0';
this.agentCount = s.agent_count || 0;
} catch(e) {
this.connected = false;
this.lastError = e.message || 'Unknown error';
console.warn('[OpenFang] Status check failed:', e.message);
}
},
async checkOnboarding() {
if (localStorage.getItem('openfang-onboarded')) return;
try {
var config = await OpenFangAPI.get('/api/config');
var apiKey = config && config.api_key;
var noKey = !apiKey || apiKey === 'not set' || apiKey === '';
if (noKey && this.agentCount === 0) {
this.showOnboarding = true;
}
} catch(e) {
// If config endpoint fails, still show onboarding if no agents
if (this.agentCount === 0) this.showOnboarding = true;
}
},
dismissOnboarding() {
this.showOnboarding = false;
localStorage.setItem('openfang-onboarded', 'true');
},
async checkAuth() {
try {
// Use a protected endpoint (not in the public allowlist) to detect
// whether the server requires an API key.
await OpenFangAPI.get('/api/tools');
this.showAuthPrompt = false;
} catch(e) {
if (e.message && (e.message.indexOf('Not authorized') >= 0 || e.message.indexOf('401') >= 0 || e.message.indexOf('Missing Authorization') >= 0 || e.message.indexOf('Unauthorized') >= 0)) {
// Only show prompt if we don't already have a saved key
var saved = localStorage.getItem('openfang-api-key');
if (saved) {
// Saved key might be stale — clear it and show prompt
OpenFangAPI.setAuthToken('');
localStorage.removeItem('openfang-api-key');
}
this.showAuthPrompt = true;
}
}
},
submitApiKey(key) {
if (!key || !key.trim()) return;
OpenFangAPI.setAuthToken(key.trim());
localStorage.setItem('openfang-api-key', key.trim());
this.showAuthPrompt = false;
this.refreshAgents();
},
clearApiKey() {
OpenFangAPI.setAuthToken('');
localStorage.removeItem('openfang-api-key');
}
});
});
// Main app component
function app() {
return {
page: 'agents',
themeMode: localStorage.getItem('openfang-theme-mode') || 'system',
theme: (() => {
var mode = localStorage.getItem('openfang-theme-mode') || 'system';
if (mode === 'system') return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
return mode;
})(),
sidebarCollapsed: localStorage.getItem('openfang-sidebar') === 'collapsed',
mobileMenuOpen: false,
connected: false,
wsConnected: false,
version: '0.1.0',
agentCount: 0,
get agents() { return Alpine.store('app').agents; },
init() {
var self = this;
// Listen for OS theme changes (only matters when mode is 'system')
window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', function(e) {
if (self.themeMode === 'system') {
self.theme = e.matches ? 'dark' : 'light';
}
});
// Hash routing
var validPages = ['overview','agents','sessions','approvals','workflows','scheduler','channels','skills','hands','analytics','logs','settings','wizard'];
var pageRedirects = {
'chat': 'agents',
'templates': 'agents',
'triggers': 'workflows',
'cron': 'scheduler',
'schedules': 'scheduler',
'memory': 'sessions',
'audit': 'logs',
'security': 'settings',
'peers': 'settings',
'migration': 'settings',
'usage': 'analytics',
'approval': 'approvals'
};
function handleHash() {
var hash = window.location.hash.replace('#', '') || 'agents';
if (pageRedirects[hash]) {
hash = pageRedirects[hash];
window.location.hash = hash;
}
if (validPages.indexOf(hash) >= 0) self.page = hash;
}
window.addEventListener('hashchange', handleHash);
handleHash();
// Keyboard shortcuts
document.addEventListener('keydown', function(e) {
// Ctrl+K — focus agent switch / go to agents
if ((e.ctrlKey || e.metaKey) && e.key === 'k') {
e.preventDefault();
self.navigate('agents');
}
// Ctrl+N — new agent
if ((e.ctrlKey || e.metaKey) && e.key === 'n' && !e.shiftKey) {
e.preventDefault();
self.navigate('agents');
}
// Ctrl+Shift+F — toggle focus mode
if ((e.ctrlKey || e.metaKey) && e.shiftKey && e.key === 'F') {
e.preventDefault();
Alpine.store('app').toggleFocusMode();
}
// Escape — close mobile menu
if (e.key === 'Escape') {
self.mobileMenuOpen = false;
}
});
// Connection state listener
OpenFangAPI.onConnectionChange(function(state) {
Alpine.store('app').connectionState = state;
});
// Initial data load
this.pollStatus();
Alpine.store('app').checkOnboarding();
Alpine.store('app').checkAuth();
setInterval(function() { self.pollStatus(); }, 5000);
},
navigate(p) {
this.page = p;
window.location.hash = p;
this.mobileMenuOpen = false;
},
setTheme(mode) {
this.themeMode = mode;
localStorage.setItem('openfang-theme-mode', mode);
if (mode === 'system') {
this.theme = window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
} else {
this.theme = mode;
}
},
toggleTheme() {
var modes = ['light', 'system', 'dark'];
var next = modes[(modes.indexOf(this.themeMode) + 1) % modes.length];
this.setTheme(next);
},
toggleSidebar() {
this.sidebarCollapsed = !this.sidebarCollapsed;
localStorage.setItem('openfang-sidebar', this.sidebarCollapsed ? 'collapsed' : 'expanded');
},
async pollStatus() {
var store = Alpine.store('app');
await store.checkStatus();
await store.refreshAgents();
this.connected = store.connected;
this.version = store.version;
this.agentCount = store.agentCount;
this.wsConnected = OpenFangAPI.isWsConnected();
}
};
}

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crates/openfang-api/static/js/pages/agents.js Normal file
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// OpenFang Agents Page — Multi-step spawn wizard, detail view with tabs, file editor, personality presets
'use strict';
function agentsPage() {
return {
tab: 'agents',
activeChatAgent: null,
// -- Agents state --
showSpawnModal: false,
showDetailModal: false,
detailAgent: null,
spawnMode: 'wizard',
spawning: false,
spawnToml: '',
filterState: 'all',
loading: true,
loadError: '',
spawnForm: {
name: '',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
systemPrompt: 'You are a helpful assistant.',
profile: 'full',
caps: { memory_read: true, memory_write: true, network: false, shell: false, agent_spawn: false }
},
// -- Multi-step wizard state --
spawnStep: 1,
spawnIdentity: { emoji: '', color: '#FF5C00', archetype: '' },
selectedPreset: '',
soulContent: '',
emojiOptions: [
'\u{1F916}', '\u{1F4BB}', '\u{1F50D}', '\u{270D}\uFE0F', '\u{1F4CA}', '\u{1F6E0}\uFE0F',
'\u{1F4AC}', '\u{1F393}', '\u{1F310}', '\u{1F512}', '\u{26A1}', '\u{1F680}',
'\u{1F9EA}', '\u{1F3AF}', '\u{1F4D6}', '\u{1F9D1}\u200D\u{1F4BB}', '\u{1F4E7}', '\u{1F3E2}',
'\u{2764}\uFE0F', '\u{1F31F}', '\u{1F527}', '\u{1F4DD}', '\u{1F4A1}', '\u{1F3A8}'
],
archetypeOptions: ['Assistant', 'Researcher', 'Coder', 'Writer', 'DevOps', 'Support', 'Analyst', 'Custom'],
personalityPresets: [
{ id: 'professional', label: 'Professional', soul: 'Communicate in a clear, professional tone. Be direct and structured. Use formal language and data-driven reasoning. Prioritize accuracy over personality.' },
{ id: 'friendly', label: 'Friendly', soul: 'Be warm, approachable, and conversational. Use casual language and show genuine interest in the user. Add personality to your responses while staying helpful.' },
{ id: 'technical', label: 'Technical', soul: 'Focus on technical accuracy and depth. Use precise terminology. Show your work and reasoning. Prefer code examples and structured explanations.' },
{ id: 'creative', label: 'Creative', soul: 'Be imaginative and expressive. Use vivid language, analogies, and unexpected connections. Encourage creative thinking and explore multiple perspectives.' },
{ id: 'concise', label: 'Concise', soul: 'Be extremely brief and to the point. No filler, no pleasantries. Answer in the fewest words possible while remaining accurate and complete.' },
{ id: 'mentor', label: 'Mentor', soul: 'Be patient and encouraging like a great teacher. Break down complex topics step by step. Ask guiding questions. Celebrate progress and build confidence.' }
],
// -- Detail modal tabs --
detailTab: 'info',
agentFiles: [],
editingFile: null,
fileContent: '',
fileSaving: false,
filesLoading: false,
configForm: {},
configSaving: false,
// -- Templates state --
tplTemplates: [],
tplProviders: [],
tplLoading: false,
tplLoadError: '',
selectedCategory: 'All',
searchQuery: '',
builtinTemplates: [
{
name: 'General Assistant',
description: 'A versatile conversational agent that can help with everyday tasks, answer questions, and provide recommendations.',
category: 'General',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'full',
system_prompt: 'You are a helpful, friendly assistant. Provide clear, accurate, and concise responses. Ask clarifying questions when needed.'
},
{
name: 'Code Helper',
description: 'A programming-focused agent that writes, reviews, and debugs code across multiple languages.',
category: 'Development',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'coding',
system_prompt: 'You are an expert programmer. Help users write clean, efficient code. Explain your reasoning. Follow best practices and conventions for the language being used.'
},
{
name: 'Researcher',
description: 'An analytical agent that breaks down complex topics, synthesizes information, and provides cited summaries.',
category: 'Research',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'research',
system_prompt: 'You are a research analyst. Break down complex topics into clear explanations. Provide structured analysis with key findings. Cite sources when available.'
},
{
name: 'Writer',
description: 'A creative writing agent that helps with drafting, editing, and improving written content of all kinds.',
category: 'Writing',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'full',
system_prompt: 'You are a skilled writer and editor. Help users create polished content. Adapt your tone and style to match the intended audience. Offer constructive suggestions for improvement.'
},
{
name: 'Data Analyst',
description: 'A data-focused agent that helps analyze datasets, create queries, and interpret statistical results.',
category: 'Development',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'coding',
system_prompt: 'You are a data analysis expert. Help users understand their data, write SQL/Python queries, and interpret results. Present findings clearly with actionable insights.'
},
{
name: 'DevOps Engineer',
description: 'A systems-focused agent for CI/CD, infrastructure, Docker, and deployment troubleshooting.',
category: 'Development',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'automation',
system_prompt: 'You are a DevOps engineer. Help with CI/CD pipelines, Docker, Kubernetes, infrastructure as code, and deployment. Prioritize reliability and security.'
},
{
name: 'Customer Support',
description: 'A professional, empathetic agent for handling customer inquiries and resolving issues.',
category: 'Business',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'messaging',
system_prompt: 'You are a professional customer support representative. Be empathetic, patient, and solution-oriented. Acknowledge concerns before offering solutions. Escalate complex issues appropriately.'
},
{
name: 'Tutor',
description: 'A patient educational agent that explains concepts step-by-step and adapts to the learner\'s level.',
category: 'General',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'full',
system_prompt: 'You are a patient and encouraging tutor. Explain concepts step by step, starting from fundamentals. Use analogies and examples. Check understanding before moving on. Adapt to the learner\'s pace.'
},
{
name: 'API Designer',
description: 'An agent specialized in RESTful API design, OpenAPI specs, and integration architecture.',
category: 'Development',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'coding',
system_prompt: 'You are an API design expert. Help users design clean, consistent RESTful APIs following best practices. Cover endpoint naming, request/response schemas, error handling, and versioning.'
},
{
name: 'Meeting Notes',
description: 'Summarizes meeting transcripts into structured notes with action items and key decisions.',
category: 'Business',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'minimal',
system_prompt: 'You are a meeting summarizer. When given a meeting transcript or notes, produce a structured summary with: key decisions, action items (with owners), discussion highlights, and follow-up questions.'
}
],
// ── Profile Descriptions ──
profileDescriptions: {
minimal: { label: 'Minimal', desc: 'Read-only file access' },
coding: { label: 'Coding', desc: 'Files + shell + web fetch' },
research: { label: 'Research', desc: 'Web search + file read/write' },
messaging: { label: 'Messaging', desc: 'Agents + memory access' },
automation: { label: 'Automation', desc: 'All tools except custom' },
balanced: { label: 'Balanced', desc: 'General-purpose tool set' },
precise: { label: 'Precise', desc: 'Focused tool set for accuracy' },
creative: { label: 'Creative', desc: 'Full tools with creative emphasis' },
full: { label: 'Full', desc: 'All 35+ tools' }
},
profileInfo: function(name) {
return this.profileDescriptions[name] || { label: name, desc: '' };
},
// ── Tool Preview in Spawn Modal ──
spawnProfiles: [],
spawnProfilesLoaded: false,
async loadSpawnProfiles() {
if (this.spawnProfilesLoaded) return;
try {
var data = await OpenFangAPI.get('/api/profiles');
this.spawnProfiles = data.profiles || [];
this.spawnProfilesLoaded = true;
} catch(e) { this.spawnProfiles = []; }
},
get selectedProfileTools() {
var pname = this.spawnForm.profile;
var match = this.spawnProfiles.find(function(p) { return p.name === pname; });
if (match && match.tools) return match.tools.slice(0, 15);
return [];
},
get agents() { return Alpine.store('app').agents; },
get filteredAgents() {
var f = this.filterState;
if (f === 'all') return this.agents;
return this.agents.filter(function(a) { return a.state.toLowerCase() === f; });
},
get runningCount() {
return this.agents.filter(function(a) { return a.state === 'Running'; }).length;
},
get stoppedCount() {
return this.agents.filter(function(a) { return a.state !== 'Running'; }).length;
},
// -- Templates computed --
get categories() {
var cats = { 'All': true };
this.builtinTemplates.forEach(function(t) { cats[t.category] = true; });
this.tplTemplates.forEach(function(t) { if (t.category) cats[t.category] = true; });
return Object.keys(cats);
},
get filteredBuiltins() {
var self = this;
return this.builtinTemplates.filter(function(t) {
if (self.selectedCategory !== 'All' && t.category !== self.selectedCategory) return false;
if (self.searchQuery) {
var q = self.searchQuery.toLowerCase();
if (t.name.toLowerCase().indexOf(q) === -1 &&
t.description.toLowerCase().indexOf(q) === -1) return false;
}
return true;
});
},
get filteredCustom() {
var self = this;
return this.tplTemplates.filter(function(t) {
if (self.searchQuery) {
var q = self.searchQuery.toLowerCase();
if ((t.name || '').toLowerCase().indexOf(q) === -1 &&
(t.description || '').toLowerCase().indexOf(q) === -1) return false;
}
return true;
});
},
isProviderConfigured(providerName) {
if (!providerName) return false;
var p = this.tplProviders.find(function(pr) { return pr.id === providerName; });
return p ? p.auth_status === 'configured' : false;
},
async init() {
var self = this;
this.loading = true;
this.loadError = '';
try {
await Alpine.store('app').refreshAgents();
} catch(e) {
this.loadError = e.message || 'Could not load agents. Is the daemon running?';
}
this.loading = false;
// If a pending agent was set (e.g. from wizard or redirect), open chat inline
var store = Alpine.store('app');
if (store.pendingAgent) {
this.activeChatAgent = store.pendingAgent;
}
// Watch for future pendingAgent changes
this.$watch('$store.app.pendingAgent', function(agent) {
if (agent) {
self.activeChatAgent = agent;
}
});
},
async loadData() {
this.loading = true;
this.loadError = '';
try {
await Alpine.store('app').refreshAgents();
} catch(e) {
this.loadError = e.message || 'Could not load agents.';
}
this.loading = false;
},
async loadTemplates() {
this.tplLoading = true;
this.tplLoadError = '';
try {
var results = await Promise.all([
OpenFangAPI.get('/api/templates'),
OpenFangAPI.get('/api/providers').catch(function() { return { providers: [] }; })
]);
this.tplTemplates = results[0].templates || [];
this.tplProviders = results[1].providers || [];
} catch(e) {
this.tplTemplates = [];
this.tplLoadError = e.message || 'Could not load templates.';
}
this.tplLoading = false;
},
chatWithAgent(agent) {
Alpine.store('app').pendingAgent = agent;
this.activeChatAgent = agent;
},
closeChat() {
this.activeChatAgent = null;
OpenFangAPI.wsDisconnect();
},
showDetail(agent) {
this.detailAgent = agent;
this.detailTab = 'info';
this.agentFiles = [];
this.editingFile = null;
this.fileContent = '';
this.configForm = {
name: agent.name || '',
system_prompt: agent.system_prompt || '',
emoji: (agent.identity && agent.identity.emoji) || '',
color: (agent.identity && agent.identity.color) || '#FF5C00',
archetype: (agent.identity && agent.identity.archetype) || '',
vibe: (agent.identity && agent.identity.vibe) || ''
};
this.showDetailModal = true;
},
killAgent(agent) {
var self = this;
OpenFangToast.confirm('Stop Agent', 'Stop agent "' + agent.name + '"? The agent will be shut down.', async function() {
try {
await OpenFangAPI.del('/api/agents/' + agent.id);
OpenFangToast.success('Agent "' + agent.name + '" stopped');
self.showDetailModal = false;
await Alpine.store('app').refreshAgents();
} catch(e) {
OpenFangToast.error('Failed to stop agent: ' + e.message);
}
});
},
killAllAgents() {
var list = this.filteredAgents;
if (!list.length) return;
OpenFangToast.confirm('Stop All Agents', 'Stop ' + list.length + ' agent(s)? All agents will be shut down.', async function() {
var errors = [];
for (var i = 0; i < list.length; i++) {
try {
await OpenFangAPI.del('/api/agents/' + list[i].id);
} catch(e) { errors.push(list[i].name + ': ' + e.message); }
}
await Alpine.store('app').refreshAgents();
if (errors.length) {
OpenFangToast.error('Some agents failed to stop: ' + errors.join(', '));
} else {
OpenFangToast.success(list.length + ' agent(s) stopped');
}
});
},
// ── Multi-step wizard navigation ──
openSpawnWizard() {
this.showSpawnModal = true;
this.spawnStep = 1;
this.spawnMode = 'wizard';
this.spawnIdentity = { emoji: '', color: '#FF5C00', archetype: '' };
this.selectedPreset = '';
this.soulContent = '';
this.spawnForm.name = '';
this.spawnForm.systemPrompt = 'You are a helpful assistant.';
this.spawnForm.profile = 'full';
},
nextStep() {
if (this.spawnStep === 1 && !this.spawnForm.name.trim()) {
OpenFangToast.warn('Please enter an agent name');
return;
}
if (this.spawnStep < 5) this.spawnStep++;
},
prevStep() {
if (this.spawnStep > 1) this.spawnStep--;
},
selectPreset(preset) {
this.selectedPreset = preset.id;
this.soulContent = preset.soul;
},
generateToml() {
var f = this.spawnForm;
var si = this.spawnIdentity;
var lines = [
'name = "' + f.name + '"',
'module = "builtin:chat"'
];
if (f.profile && f.profile !== 'custom') {
lines.push('profile = "' + f.profile + '"');
}
lines.push('', '[model]');
lines.push('provider = "' + f.provider + '"');
lines.push('model = "' + f.model + '"');
lines.push('system_prompt = "' + f.systemPrompt.replace(/"/g, '\\"') + '"');
if (f.profile === 'custom') {
lines.push('', '[capabilities]');
if (f.caps.memory_read) lines.push('memory_read = ["*"]');
if (f.caps.memory_write) lines.push('memory_write = ["self.*"]');
if (f.caps.network) lines.push('network = ["*"]');
if (f.caps.shell) lines.push('shell = ["*"]');
if (f.caps.agent_spawn) lines.push('agent_spawn = true');
}
return lines.join('\n');
},
async setMode(agent, mode) {
try {
await OpenFangAPI.put('/api/agents/' + agent.id + '/mode', { mode: mode });
agent.mode = mode;
OpenFangToast.success('Mode set to ' + mode);
await Alpine.store('app').refreshAgents();
} catch(e) {
OpenFangToast.error('Failed to set mode: ' + e.message);
}
},
async spawnAgent() {
this.spawning = true;
var toml = this.spawnMode === 'wizard' ? this.generateToml() : this.spawnToml;
if (!toml.trim()) {
this.spawning = false;
OpenFangToast.warn('Manifest is empty \u2014 enter agent config first');
return;
}
try {
var res = await OpenFangAPI.post('/api/agents', { manifest_toml: toml });
if (res.agent_id) {
// Post-spawn: update identity + write SOUL.md if personality preset selected
var patchBody = {};
if (this.spawnIdentity.emoji) patchBody.emoji = this.spawnIdentity.emoji;
if (this.spawnIdentity.color) patchBody.color = this.spawnIdentity.color;
if (this.spawnIdentity.archetype) patchBody.archetype = this.spawnIdentity.archetype;
if (this.selectedPreset) patchBody.vibe = this.selectedPreset;
if (Object.keys(patchBody).length) {
OpenFangAPI.patch('/api/agents/' + res.agent_id + '/config', patchBody).catch(function(e) { console.warn('Post-spawn config patch failed:', e.message); });
}
if (this.soulContent.trim()) {
OpenFangAPI.put('/api/agents/' + res.agent_id + '/files/SOUL.md', { content: '# Soul\n' + this.soulContent }).catch(function(e) { console.warn('SOUL.md write failed:', e.message); });
}
this.showSpawnModal = false;
this.spawnForm.name = '';
this.spawnToml = '';
this.spawnStep = 1;
OpenFangToast.success('Agent "' + (res.name || 'new') + '" spawned');
await Alpine.store('app').refreshAgents();
this.chatWithAgent({ id: res.agent_id, name: res.name, model_provider: '?', model_name: '?' });
} else {
OpenFangToast.error('Spawn failed: ' + (res.error || 'Unknown error'));
}
} catch(e) {
OpenFangToast.error('Failed to spawn agent: ' + e.message);
}
this.spawning = false;
},
// ── Detail modal: Files tab ──
async loadAgentFiles() {
if (!this.detailAgent) return;
this.filesLoading = true;
try {
var data = await OpenFangAPI.get('/api/agents/' + this.detailAgent.id + '/files');
this.agentFiles = data.files || [];
} catch(e) {
this.agentFiles = [];
OpenFangToast.error('Failed to load files: ' + e.message);
}
this.filesLoading = false;
},
async openFile(file) {
if (!file.exists) {
// Create with empty content
this.editingFile = file.name;
this.fileContent = '';
return;
}
try {
var data = await OpenFangAPI.get('/api/agents/' + this.detailAgent.id + '/files/' + encodeURIComponent(file.name));
this.editingFile = file.name;
this.fileContent = data.content || '';
} catch(e) {
OpenFangToast.error('Failed to read file: ' + e.message);
}
},
async saveFile() {
if (!this.editingFile || !this.detailAgent) return;
this.fileSaving = true;
try {
await OpenFangAPI.put('/api/agents/' + this.detailAgent.id + '/files/' + encodeURIComponent(this.editingFile), { content: this.fileContent });
OpenFangToast.success(this.editingFile + ' saved');
await this.loadAgentFiles();
} catch(e) {
OpenFangToast.error('Failed to save file: ' + e.message);
}
this.fileSaving = false;
},
closeFileEditor() {
this.editingFile = null;
this.fileContent = '';
},
// ── Detail modal: Config tab ──
async saveConfig() {
if (!this.detailAgent) return;
this.configSaving = true;
try {
await OpenFangAPI.patch('/api/agents/' + this.detailAgent.id + '/config', this.configForm);
OpenFangToast.success('Config updated');
await Alpine.store('app').refreshAgents();
} catch(e) {
OpenFangToast.error('Failed to save config: ' + e.message);
}
this.configSaving = false;
},
// ── Clone agent ──
async cloneAgent(agent) {
var newName = (agent.name || 'agent') + '-copy';
try {
var res = await OpenFangAPI.post('/api/agents/' + agent.id + '/clone', { new_name: newName });
if (res.agent_id) {
OpenFangToast.success('Cloned as "' + res.name + '"');
await Alpine.store('app').refreshAgents();
this.showDetailModal = false;
}
} catch(e) {
OpenFangToast.error('Clone failed: ' + e.message);
}
},
// -- Template methods --
async spawnFromTemplate(name) {
try {
var data = await OpenFangAPI.get('/api/templates/' + encodeURIComponent(name));
if (data.manifest_toml) {
var res = await OpenFangAPI.post('/api/agents', { manifest_toml: data.manifest_toml });
if (res.agent_id) {
OpenFangToast.success('Agent "' + (res.name || name) + '" spawned from template');
await Alpine.store('app').refreshAgents();
this.chatWithAgent({ id: res.agent_id, name: res.name || name, model_provider: '?', model_name: '?' });
}
}
} catch(e) {
OpenFangToast.error('Failed to spawn from template: ' + e.message);
}
},
async spawnBuiltin(t) {
var toml = 'name = "' + t.name + '"\n';
toml += 'description = "' + t.description.replace(/"/g, '\\"') + '"\n';
toml += 'module = "builtin:chat"\n';
toml += 'profile = "' + t.profile + '"\n\n';
toml += '[model]\nprovider = "' + t.provider + '"\nmodel = "' + t.model + '"\n';
toml += 'system_prompt = """\n' + t.system_prompt + '\n"""\n';
try {
var res = await OpenFangAPI.post('/api/agents', { manifest_toml: toml });
if (res.agent_id) {
OpenFangToast.success('Agent "' + t.name + '" spawned');
await Alpine.store('app').refreshAgents();
this.chatWithAgent({ id: res.agent_id, name: t.name, model_provider: t.provider, model_name: t.model });
}
} catch(e) {
OpenFangToast.error('Failed to spawn agent: ' + e.message);
}
}
};
}

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// OpenFang Approvals Page — Execution approval queue for sensitive agent actions
'use strict';
function approvalsPage() {
return {
approvals: [],
filterStatus: 'all',
loading: true,
loadError: '',
get filtered() {
var f = this.filterStatus;
if (f === 'all') return this.approvals;
return this.approvals.filter(function(a) { return a.status === f; });
},
get pendingCount() {
return this.approvals.filter(function(a) { return a.status === 'pending'; }).length;
},
async loadData() {
this.loading = true;
this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/approvals');
this.approvals = data.approvals || [];
} catch(e) {
this.loadError = e.message || 'Could not load approvals.';
}
this.loading = false;
},
async approve(id) {
try {
await OpenFangAPI.post('/api/approvals/' + id + '/approve', {});
OpenFangToast.success('Approved');
await this.loadData();
} catch(e) {
OpenFangToast.error(e.message);
}
},
async reject(id) {
var self = this;
OpenFangToast.confirm('Reject Action', 'Are you sure you want to reject this action?', async function() {
try {
await OpenFangAPI.post('/api/approvals/' + id + '/reject', {});
OpenFangToast.success('Rejected');
await self.loadData();
} catch(e) {
OpenFangToast.error(e.message);
}
});
},
timeAgo(dateStr) {
if (!dateStr) return '';
var d = new Date(dateStr);
var secs = Math.floor((Date.now() - d.getTime()) / 1000);
if (secs < 60) return secs + 's ago';
if (secs < 3600) return Math.floor(secs / 60) + 'm ago';
if (secs < 86400) return Math.floor(secs / 3600) + 'h ago';
return Math.floor(secs / 86400) + 'd ago';
}
};
}

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// OpenFang Channels Page — OpenClaw-style setup UX with QR code support
'use strict';
function channelsPage() {
return {
allChannels: [],
categoryFilter: 'all',
searchQuery: '',
setupModal: null,
configuring: false,
testing: {},
formValues: {},
showAdvanced: false,
showBusinessApi: false,
loading: true,
loadError: '',
pollTimer: null,
// Setup flow step tracking
setupStep: 1, // 1=Configure, 2=Verify, 3=Ready
testPassed: false,
// WhatsApp QR state
qr: {
loading: false,
available: false,
dataUrl: '',
sessionId: '',
message: '',
help: '',
connected: false,
expired: false,
error: ''
},
qrPollTimer: null,
categories: [
{ key: 'all', label: 'All' },
{ key: 'messaging', label: 'Messaging' },
{ key: 'social', label: 'Social' },
{ key: 'enterprise', label: 'Enterprise' },
{ key: 'developer', label: 'Developer' },
{ key: 'notifications', label: 'Notifications' }
],
get filteredChannels() {
var self = this;
return this.allChannels.filter(function(ch) {
if (self.categoryFilter !== 'all' && ch.category !== self.categoryFilter) return false;
if (self.searchQuery) {
var q = self.searchQuery.toLowerCase();
return ch.name.toLowerCase().indexOf(q) !== -1 ||
ch.display_name.toLowerCase().indexOf(q) !== -1 ||
ch.description.toLowerCase().indexOf(q) !== -1;
}
return true;
});
},
get configuredCount() {
return this.allChannels.filter(function(ch) { return ch.configured; }).length;
},
categoryCount(cat) {
var all = this.allChannels.filter(function(ch) { return cat === 'all' || ch.category === cat; });
var configured = all.filter(function(ch) { return ch.configured; });
return configured.length + '/' + all.length;
},
basicFields() {
if (!this.setupModal || !this.setupModal.fields) return [];
return this.setupModal.fields.filter(function(f) { return !f.advanced; });
},
advancedFields() {
if (!this.setupModal || !this.setupModal.fields) return [];
return this.setupModal.fields.filter(function(f) { return f.advanced; });
},
hasAdvanced() {
return this.advancedFields().length > 0;
},
isQrChannel() {
return this.setupModal && this.setupModal.setup_type === 'qr';
},
async loadChannels() {
this.loading = true;
this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/channels');
this.allChannels = (data.channels || []).map(function(ch) {
ch.connected = ch.configured && ch.has_token;
return ch;
});
} catch(e) {
this.loadError = e.message || 'Could not load channels.';
}
this.loading = false;
this.startPolling();
},
async loadData() { return this.loadChannels(); },
startPolling() {
var self = this;
if (this.pollTimer) clearInterval(this.pollTimer);
this.pollTimer = setInterval(function() { self.refreshStatus(); }, 15000);
},
async refreshStatus() {
try {
var data = await OpenFangAPI.get('/api/channels');
var byName = {};
(data.channels || []).forEach(function(ch) { byName[ch.name] = ch; });
this.allChannels.forEach(function(c) {
var fresh = byName[c.name];
if (fresh) {
c.configured = fresh.configured;
c.has_token = fresh.has_token;
c.connected = fresh.configured && fresh.has_token;
c.fields = fresh.fields;
}
});
} catch(e) { console.warn('Channel refresh failed:', e.message); }
},
statusBadge(ch) {
if (!ch.configured) return { text: 'Not Configured', cls: 'badge-muted' };
if (!ch.has_token) return { text: 'Missing Token', cls: 'badge-warn' };
if (ch.connected) return { text: 'Ready', cls: 'badge-success' };
return { text: 'Configured', cls: 'badge-info' };
},
difficultyClass(d) {
if (d === 'Easy') return 'difficulty-easy';
if (d === 'Hard') return 'difficulty-hard';
return 'difficulty-medium';
},
openSetup(ch) {
this.setupModal = ch;
this.formValues = {};
this.showAdvanced = false;
this.showBusinessApi = false;
this.setupStep = ch.configured ? 3 : 1;
this.testPassed = !!ch.configured;
this.resetQR();
// Auto-start QR flow for QR-type channels
if (ch.setup_type === 'qr') {
this.startQR();
}
},
// ── QR Code Flow (WhatsApp Web style) ──────────────────────────
resetQR() {
this.qr = {
loading: false, available: false, dataUrl: '', sessionId: '',
message: '', help: '', connected: false, expired: false, error: ''
};
if (this.qrPollTimer) { clearInterval(this.qrPollTimer); this.qrPollTimer = null; }
},
async startQR() {
this.qr.loading = true;
this.qr.error = '';
this.qr.connected = false;
this.qr.expired = false;
try {
var result = await OpenFangAPI.post('/api/channels/whatsapp/qr/start', {});
this.qr.available = result.available || false;
this.qr.dataUrl = result.qr_data_url || '';
this.qr.sessionId = result.session_id || '';
this.qr.message = result.message || '';
this.qr.help = result.help || '';
this.qr.connected = result.connected || false;
if (this.qr.available && this.qr.dataUrl && !this.qr.connected) {
this.pollQR();
}
if (this.qr.connected) {
OpenFangToast.success('WhatsApp connected!');
await this.refreshStatus();
}
} catch(e) {
this.qr.error = e.message || 'Could not start QR login';
}
this.qr.loading = false;
},
pollQR() {
var self = this;
if (this.qrPollTimer) clearInterval(this.qrPollTimer);
this.qrPollTimer = setInterval(async function() {
try {
var result = await OpenFangAPI.get('/api/channels/whatsapp/qr/status?session_id=' + encodeURIComponent(self.qr.sessionId));
if (result.connected) {
clearInterval(self.qrPollTimer);
self.qrPollTimer = null;
self.qr.connected = true;
self.qr.message = result.message || 'Connected!';
OpenFangToast.success('WhatsApp linked successfully!');
await self.refreshStatus();
} else if (result.expired) {
clearInterval(self.qrPollTimer);
self.qrPollTimer = null;
self.qr.expired = true;
self.qr.message = 'QR code expired. Click to generate a new one.';
} else {
self.qr.message = result.message || 'Waiting for scan...';
}
} catch(e) { /* silent retry */ }
}, 3000);
},
// ── Standard Form Flow ─────────────────────────────────────────
async saveChannel() {
if (!this.setupModal) return;
var name = this.setupModal.name;
this.configuring = true;
try {
await OpenFangAPI.post('/api/channels/' + name + '/configure', {
fields: this.formValues
});
this.setupStep = 2;
// Auto-test after save
try {
var testResult = await OpenFangAPI.post('/api/channels/' + name + '/test', {});
if (testResult.status === 'ok') {
this.testPassed = true;
this.setupStep = 3;
OpenFangToast.success(this.setupModal.display_name + ' activated!');
} else {
OpenFangToast.success(this.setupModal.display_name + ' saved. ' + (testResult.message || ''));
}
} catch(te) {
OpenFangToast.success(this.setupModal.display_name + ' saved. Test to verify connection.');
}
await this.refreshStatus();
} catch(e) {
OpenFangToast.error('Failed: ' + (e.message || 'Unknown error'));
}
this.configuring = false;
},
async removeChannel() {
if (!this.setupModal) return;
var name = this.setupModal.name;
var displayName = this.setupModal.display_name;
var self = this;
OpenFangToast.confirm('Remove Channel', 'Remove ' + displayName + ' configuration? This will deactivate the channel.', async function() {
try {
await OpenFangAPI.delete('/api/channels/' + name + '/configure');
OpenFangToast.success(displayName + ' removed and deactivated.');
await self.refreshStatus();
self.setupModal = null;
} catch(e) {
OpenFangToast.error('Failed: ' + (e.message || 'Unknown error'));
}
});
},
async testChannel() {
if (!this.setupModal) return;
var name = this.setupModal.name;
this.testing[name] = true;
try {
var result = await OpenFangAPI.post('/api/channels/' + name + '/test', {});
if (result.status === 'ok') {
this.testPassed = true;
this.setupStep = 3;
OpenFangToast.success(result.message);
} else {
OpenFangToast.error(result.message);
}
} catch(e) {
OpenFangToast.error('Test failed: ' + (e.message || 'Unknown error'));
}
this.testing[name] = false;
},
async copyConfig(ch) {
var tpl = ch ? ch.config_template : (this.setupModal ? this.setupModal.config_template : '');
if (!tpl) return;
try {
await navigator.clipboard.writeText(tpl);
OpenFangToast.success('Copied to clipboard');
} catch(e) {
OpenFangToast.error('Copy failed');
}
},
destroy() {
if (this.pollTimer) { clearInterval(this.pollTimer); this.pollTimer = null; }
if (this.qrPollTimer) { clearInterval(this.qrPollTimer); this.qrPollTimer = null; }
}
};
}

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crates/openfang-api/static/js/pages/hands.js Normal file
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// OpenFang Hands Page — curated autonomous capability packages
'use strict';
function handsPage() {
return {
tab: 'available',
hands: [],
instances: [],
loading: true,
activeLoading: false,
loadError: '',
activatingId: null,
activateResult: null,
detailHand: null,
settingsValues: {},
_toastTimer: null,
browserViewer: null,
browserViewerOpen: false,
_browserPollTimer: null,
// ── Setup Wizard State ──────────────────────────────────────────────
setupWizard: null,
setupStep: 1,
setupLoading: false,
setupChecking: false,
clipboardMsg: null,
_clipboardTimer: null,
detectedPlatform: 'linux',
installPlatforms: {},
async loadData() {
this.loading = true;
this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/hands');
this.hands = data.hands || [];
} catch(e) {
this.hands = [];
this.loadError = e.message || 'Could not load hands.';
}
this.loading = false;
},
async loadActive() {
this.activeLoading = true;
try {
var data = await OpenFangAPI.get('/api/hands/active');
this.instances = (data.instances || []).map(function(i) {
i._stats = null;
return i;
});
} catch(e) {
this.instances = [];
}
this.activeLoading = false;
},
getHandIcon(handId) {
for (var i = 0; i < this.hands.length; i++) {
if (this.hands[i].id === handId) return this.hands[i].icon;
}
return '\u{1F91A}';
},
async showDetail(handId) {
try {
var data = await OpenFangAPI.get('/api/hands/' + handId);
this.detailHand = data;
} catch(e) {
for (var i = 0; i < this.hands.length; i++) {
if (this.hands[i].id === handId) {
this.detailHand = this.hands[i];
break;
}
}
}
},
// ── Setup Wizard ────────────────────────────────────────────────────
async activate(handId) {
this.openSetupWizard(handId);
},
async openSetupWizard(handId) {
this.setupLoading = true;
this.setupWizard = null;
try {
var data = await OpenFangAPI.get('/api/hands/' + handId);
// Pre-populate settings defaults
this.settingsValues = {};
if (data.settings && data.settings.length > 0) {
for (var i = 0; i < data.settings.length; i++) {
var s = data.settings[i];
this.settingsValues[s.key] = s.default || '';
}
}
// Detect platform from server response, fallback to client-side
if (data.server_platform) {
this.detectedPlatform = data.server_platform;
} else {
this._detectClientPlatform();
}
// Initialize per-requirement platform selections
this.installPlatforms = {};
if (data.requirements) {
for (var j = 0; j < data.requirements.length; j++) {
this.installPlatforms[data.requirements[j].key] = this.detectedPlatform;
}
}
this.setupWizard = data;
// Skip deps step if no requirements
var hasReqs = data.requirements && data.requirements.length > 0;
this.setupStep = hasReqs ? 1 : 2;
} catch(e) {
this.showToast('Could not load hand details: ' + (e.message || 'unknown error'));
}
this.setupLoading = false;
},
_detectClientPlatform() {
var ua = (navigator.userAgent || '').toLowerCase();
if (ua.indexOf('mac') !== -1) {
this.detectedPlatform = 'macos';
} else if (ua.indexOf('win') !== -1) {
this.detectedPlatform = 'windows';
} else {
this.detectedPlatform = 'linux';
}
},
// ── Auto-Install Dependencies ───────────────────────────────────
installProgress: null, // null = idle, object = { status, current, total, results, error }
async installDeps() {
if (!this.setupWizard) return;
var handId = this.setupWizard.id;
var missing = (this.setupWizard.requirements || []).filter(function(r) { return !r.satisfied; });
if (missing.length === 0) {
this.showToast('All dependencies already installed!');
return;
}
this.installProgress = {
status: 'installing',
current: 0,
total: missing.length,
currentLabel: missing[0] ? missing[0].label : '',
results: [],
error: null
};
try {
var data = await OpenFangAPI.post('/api/hands/' + handId + '/install-deps', {});
var results = data.results || [];
this.installProgress.results = results;
this.installProgress.current = results.length;
this.installProgress.status = 'done';
// Update requirements from server response
if (data.requirements && this.setupWizard.requirements) {
for (var i = 0; i < this.setupWizard.requirements.length; i++) {
var existing = this.setupWizard.requirements[i];
for (var j = 0; j < data.requirements.length; j++) {
if (data.requirements[j].key === existing.key) {
existing.satisfied = data.requirements[j].satisfied;
break;
}
}
}
this.setupWizard.requirements_met = data.requirements_met;
}
var installed = results.filter(function(r) { return r.status === 'installed' || r.status === 'already_installed'; }).length;
var failed = results.filter(function(r) { return r.status === 'error' || r.status === 'timeout'; }).length;
if (data.requirements_met) {
this.showToast('All dependencies installed successfully!');
// Auto-advance to step 2 after a short delay
var self = this;
setTimeout(function() {
self.installProgress = null;
self.setupNextStep();
}, 1500);
} else if (failed > 0) {
this.installProgress.error = failed + ' dependency(ies) failed to install. Check the details below.';
}
} catch(e) {
this.installProgress = {
status: 'error',
current: 0,
total: missing.length,
currentLabel: '',
results: [],
error: e.message || 'Installation request failed'
};
}
},
getInstallResultIcon(status) {
if (status === 'installed' || status === 'already_installed') return '\u2713';
if (status === 'error' || status === 'timeout') return '\u2717';
return '\u2022';
},
getInstallResultClass(status) {
if (status === 'installed' || status === 'already_installed') return 'dep-met';
if (status === 'error' || status === 'timeout') return 'dep-missing';
return '';
},
async recheckDeps() {
if (!this.setupWizard) return;
this.setupChecking = true;
try {
var data = await OpenFangAPI.post('/api/hands/' + this.setupWizard.id + '/check-deps', {});
if (data.requirements && this.setupWizard.requirements) {
for (var i = 0; i < this.setupWizard.requirements.length; i++) {
var existing = this.setupWizard.requirements[i];
for (var j = 0; j < data.requirements.length; j++) {
if (data.requirements[j].key === existing.key) {
existing.satisfied = data.requirements[j].satisfied;
break;
}
}
}
this.setupWizard.requirements_met = data.requirements_met;
}
if (data.requirements_met) {
this.showToast('All dependencies satisfied!');
}
} catch(e) {
this.showToast('Check failed: ' + (e.message || 'unknown'));
}
this.setupChecking = false;
},
getInstallCmd(req) {
if (!req || !req.install) return null;
var inst = req.install;
var plat = this.installPlatforms[req.key] || this.detectedPlatform;
if (plat === 'macos' && inst.macos) return inst.macos;
if (plat === 'windows' && inst.windows) return inst.windows;
if (plat === 'linux') {
return inst.linux_apt || inst.linux_dnf || inst.linux_pacman || inst.pip || null;
}
return inst.pip || inst.macos || inst.windows || inst.linux_apt || null;
},
getLinuxVariant(req) {
if (!req || !req.install) return null;
var inst = req.install;
var plat = this.installPlatforms[req.key] || this.detectedPlatform;
if (plat !== 'linux') return null;
// Return all available Linux variants
var variants = [];
if (inst.linux_apt) variants.push({ label: 'apt', cmd: inst.linux_apt });
if (inst.linux_dnf) variants.push({ label: 'dnf', cmd: inst.linux_dnf });
if (inst.linux_pacman) variants.push({ label: 'pacman', cmd: inst.linux_pacman });
if (inst.pip) variants.push({ label: 'pip', cmd: inst.pip });
return variants.length > 1 ? variants : null;
},
copyToClipboard(text) {
var self = this;
navigator.clipboard.writeText(text).then(function() {
self.clipboardMsg = text;
if (self._clipboardTimer) clearTimeout(self._clipboardTimer);
self._clipboardTimer = setTimeout(function() { self.clipboardMsg = null; }, 2000);
});
},
get setupReqsMet() {
if (!this.setupWizard || !this.setupWizard.requirements) return 0;
var count = 0;
for (var i = 0; i < this.setupWizard.requirements.length; i++) {
if (this.setupWizard.requirements[i].satisfied) count++;
}
return count;
},
get setupReqsTotal() {
if (!this.setupWizard || !this.setupWizard.requirements) return 0;
return this.setupWizard.requirements.length;
},
get setupAllReqsMet() {
return this.setupReqsTotal > 0 && this.setupReqsMet === this.setupReqsTotal;
},
get setupHasReqs() {
return this.setupReqsTotal > 0;
},
get setupHasSettings() {
return this.setupWizard && this.setupWizard.settings && this.setupWizard.settings.length > 0;
},
setupNextStep() {
if (this.setupStep === 1 && this.setupHasSettings) {
this.setupStep = 2;
} else if (this.setupStep === 1) {
this.setupStep = 3;
} else if (this.setupStep === 2) {
this.setupStep = 3;
}
},
setupPrevStep() {
if (this.setupStep === 3 && this.setupHasSettings) {
this.setupStep = 2;
} else if (this.setupStep === 3) {
this.setupStep = this.setupHasReqs ? 1 : 2;
} else if (this.setupStep === 2 && this.setupHasReqs) {
this.setupStep = 1;
}
},
closeSetupWizard() {
this.setupWizard = null;
this.setupStep = 1;
this.setupLoading = false;
this.setupChecking = false;
this.clipboardMsg = null;
this.installPlatforms = {};
},
async launchHand() {
if (!this.setupWizard) return;
var handId = this.setupWizard.id;
var config = {};
for (var key in this.settingsValues) {
config[key] = this.settingsValues[key];
}
this.activatingId = handId;
try {
var data = await OpenFangAPI.post('/api/hands/' + handId + '/activate', { config: config });
this.showToast('Hand "' + handId + '" activated as ' + (data.agent_name || data.instance_id));
this.closeSetupWizard();
await this.loadActive();
this.tab = 'active';
} catch(e) {
this.showToast('Activation failed: ' + (e.message || 'unknown error'));
}
this.activatingId = null;
},
selectOption(settingKey, value) {
this.settingsValues[settingKey] = value;
},
getSettingDisplayValue(setting) {
var val = this.settingsValues[setting.key] || setting.default || '';
if (setting.setting_type === 'toggle') {
return val === 'true' ? 'Enabled' : 'Disabled';
}
if (setting.setting_type === 'select' && setting.options) {
for (var i = 0; i < setting.options.length; i++) {
if (setting.options[i].value === val) return setting.options[i].label;
}
}
return val || '-';
},
// ── Existing methods ────────────────────────────────────────────────
async pauseHand(inst) {
try {
await OpenFangAPI.post('/api/hands/instances/' + inst.instance_id + '/pause', {});
inst.status = 'Paused';
} catch(e) {
this.showToast('Pause failed: ' + (e.message || 'unknown error'));
}
},
async resumeHand(inst) {
try {
await OpenFangAPI.post('/api/hands/instances/' + inst.instance_id + '/resume', {});
inst.status = 'Active';
} catch(e) {
this.showToast('Resume failed: ' + (e.message || 'unknown error'));
}
},
async deactivate(inst) {
var self = this;
var handName = inst.agent_name || inst.hand_id;
OpenFangToast.confirm('Deactivate Hand', 'Deactivate hand "' + handName + '"? This will kill its agent.', async function() {
try {
await OpenFangAPI.delete('/api/hands/instances/' + inst.instance_id);
self.instances = self.instances.filter(function(i) { return i.instance_id !== inst.instance_id; });
OpenFangToast.success('Hand deactivated.');
} catch(e) {
OpenFangToast.error('Deactivation failed: ' + (e.message || 'unknown error'));
}
});
},
async loadStats(inst) {
try {
var data = await OpenFangAPI.get('/api/hands/instances/' + inst.instance_id + '/stats');
inst._stats = data.metrics || {};
} catch(e) {
inst._stats = { 'Error': { value: e.message || 'Could not load stats', format: 'text' } };
}
},
formatMetric(m) {
if (!m || m.value === null || m.value === undefined) return '-';
if (m.format === 'duration') {
var secs = parseInt(m.value, 10);
if (isNaN(secs)) return String(m.value);
var h = Math.floor(secs / 3600);
var min = Math.floor((secs % 3600) / 60);
var s = secs % 60;
if (h > 0) return h + 'h ' + min + 'm';
if (min > 0) return min + 'm ' + s + 's';
return s + 's';
}
if (m.format === 'number') {
var n = parseFloat(m.value);
if (isNaN(n)) return String(m.value);
return n.toLocaleString();
}
return String(m.value);
},
showToast(msg) {
var self = this;
this.activateResult = msg;
if (this._toastTimer) clearTimeout(this._toastTimer);
this._toastTimer = setTimeout(function() { self.activateResult = null; }, 4000);
},
// ── Browser Viewer ───────────────────────────────────────────────────
isBrowserHand(inst) {
return inst.hand_id === 'browser';
},
async openBrowserViewer(inst) {
this.browserViewer = {
instance_id: inst.instance_id,
hand_id: inst.hand_id,
agent_name: inst.agent_name,
url: '',
title: '',
screenshot: '',
content: '',
loading: true,
error: ''
};
this.browserViewerOpen = true;
await this.refreshBrowserView();
this.startBrowserPolling();
},
async refreshBrowserView() {
if (!this.browserViewer) return;
var id = this.browserViewer.instance_id;
try {
var data = await OpenFangAPI.get('/api/hands/instances/' + id + '/browser');
if (data.active) {
this.browserViewer.url = data.url || '';
this.browserViewer.title = data.title || '';
this.browserViewer.screenshot = data.screenshot_base64 || '';
this.browserViewer.content = data.content || '';
this.browserViewer.error = '';
} else {
this.browserViewer.error = 'No active browser session';
this.browserViewer.screenshot = '';
}
} catch(e) {
this.browserViewer.error = e.message || 'Could not load browser state';
}
this.browserViewer.loading = false;
},
startBrowserPolling() {
var self = this;
this.stopBrowserPolling();
this._browserPollTimer = setInterval(function() {
if (self.browserViewerOpen) {
self.refreshBrowserView();
} else {
self.stopBrowserPolling();
}
}, 3000);
},
stopBrowserPolling() {
if (this._browserPollTimer) {
clearInterval(this._browserPollTimer);
this._browserPollTimer = null;
}
},
closeBrowserViewer() {
this.stopBrowserPolling();
this.browserViewerOpen = false;
this.browserViewer = null;
}
};
}

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// OpenFang Logs Page — Real-time log viewer (SSE streaming + polling fallback) + Audit Trail tab
'use strict';
function logsPage() {
return {
tab: 'live',
// -- Live logs state --
entries: [],
levelFilter: '',
textFilter: '',
autoRefresh: true,
hovering: false,
loading: true,
loadError: '',
_pollTimer: null,
// -- SSE streaming state --
_eventSource: null,
streamConnected: false,
streamPaused: false,
// -- Audit state --
auditEntries: [],
tipHash: '',
chainValid: null,
filterAction: '',
auditLoading: false,
auditLoadError: '',
startStreaming: function() {
var self = this;
if (this._eventSource) { this._eventSource.close(); this._eventSource = null; }
var url = '/api/logs/stream';
var sep = '?';
var token = OpenFangAPI.getToken();
if (token) { url += sep + 'token=' + encodeURIComponent(token); sep = '&'; }
try {
this._eventSource = new EventSource(url);
} catch(e) {
// EventSource not supported or blocked; fall back to polling
this.streamConnected = false;
this.startPolling();
return;
}
this._eventSource.onopen = function() {
self.streamConnected = true;
self.loading = false;
self.loadError = '';
};
this._eventSource.onmessage = function(event) {
if (self.streamPaused) return;
try {
var entry = JSON.parse(event.data);
// Avoid duplicate entries by checking seq
var dominated = false;
for (var i = 0; i < self.entries.length; i++) {
if (self.entries[i].seq === entry.seq) { dominated = true; break; }
}
if (!dominated) {
self.entries.push(entry);
// Cap at 500 entries (remove oldest)
if (self.entries.length > 500) {
self.entries.splice(0, self.entries.length - 500);
}
// Auto-scroll to bottom
if (self.autoRefresh && !self.hovering) {
self.$nextTick(function() {
var el = document.getElementById('log-container');
if (el) el.scrollTop = el.scrollHeight;
});
}
}
} catch(e) {
// Ignore parse errors (heartbeat comments are not delivered to onmessage)
}
};
this._eventSource.onerror = function() {
self.streamConnected = false;
if (self._eventSource) {
self._eventSource.close();
self._eventSource = null;
}
// Fall back to polling
self.startPolling();
};
},
startPolling: function() {
var self = this;
this.streamConnected = false;
this.fetchLogs();
if (this._pollTimer) clearInterval(this._pollTimer);
this._pollTimer = setInterval(function() {
if (self.autoRefresh && !self.hovering && self.tab === 'live' && !self.streamPaused) {
self.fetchLogs();
}
}, 2000);
},
async fetchLogs() {
if (this.loading) this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/audit/recent?n=200');
this.entries = data.entries || [];
if (this.autoRefresh && !this.hovering) {
this.$nextTick(function() {
var el = document.getElementById('log-container');
if (el) el.scrollTop = el.scrollHeight;
});
}
if (this.loading) this.loading = false;
} catch(e) {
if (this.loading) {
this.loadError = e.message || 'Could not load logs.';
this.loading = false;
}
}
},
async loadData() {
this.loading = true;
return this.fetchLogs();
},
togglePause: function() {
this.streamPaused = !this.streamPaused;
if (!this.streamPaused && this.streamConnected) {
// Resume: scroll to bottom
var self = this;
this.$nextTick(function() {
var el = document.getElementById('log-container');
if (el) el.scrollTop = el.scrollHeight;
});
}
},
clearLogs: function() {
this.entries = [];
},
classifyLevel: function(action) {
if (!action) return 'info';
var a = action.toLowerCase();
if (a.indexOf('error') !== -1 || a.indexOf('fail') !== -1 || a.indexOf('crash') !== -1) return 'error';
if (a.indexOf('warn') !== -1 || a.indexOf('deny') !== -1 || a.indexOf('block') !== -1) return 'warn';
return 'info';
},
get filteredEntries() {
var self = this;
var levelF = this.levelFilter;
var textF = this.textFilter.toLowerCase();
return this.entries.filter(function(e) {
if (levelF && self.classifyLevel(e.action) !== levelF) return false;
if (textF) {
var haystack = ((e.action || '') + ' ' + (e.detail || '') + ' ' + (e.agent_id || '')).toLowerCase();
if (haystack.indexOf(textF) === -1) return false;
}
return true;
});
},
get connectionLabel() {
if (this.streamPaused) return 'Paused';
if (this.streamConnected) return 'Live';
if (this._pollTimer) return 'Polling';
return 'Disconnected';
},
get connectionClass() {
if (this.streamPaused) return 'paused';
if (this.streamConnected) return 'live';
if (this._pollTimer) return 'polling';
return 'disconnected';
},
exportLogs: function() {
var lines = this.filteredEntries.map(function(e) {
return new Date(e.timestamp).toISOString() + ' [' + e.action + '] ' + (e.detail || '');
});
var blob = new Blob([lines.join('\n')], { type: 'text/plain' });
var url = URL.createObjectURL(blob);
var a = document.createElement('a');
a.href = url;
a.download = 'openfang-logs-' + new Date().toISOString().slice(0, 10) + '.txt';
a.click();
URL.revokeObjectURL(url);
},
// -- Audit methods --
get filteredAuditEntries() {
var self = this;
if (!self.filterAction) return self.auditEntries;
return self.auditEntries.filter(function(e) { return e.action === self.filterAction; });
},
async loadAudit() {
this.auditLoading = true;
this.auditLoadError = '';
try {
var data = await OpenFangAPI.get('/api/audit/recent?n=200');
this.auditEntries = data.entries || [];
this.tipHash = data.tip_hash || '';
} catch(e) {
this.auditEntries = [];
this.auditLoadError = e.message || 'Could not load audit log.';
}
this.auditLoading = false;
},
auditAgentName: function(agentId) {
if (!agentId) return '-';
var agents = Alpine.store('app').agents || [];
var agent = agents.find(function(a) { return a.id === agentId; });
return agent ? agent.name : agentId.substring(0, 8) + '...';
},
friendlyAction: function(action) {
if (!action) return 'Unknown';
var map = {
'AgentSpawn': 'Agent Created', 'AgentKill': 'Agent Stopped', 'AgentTerminated': 'Agent Stopped',
'ToolInvoke': 'Tool Used', 'ToolResult': 'Tool Completed', 'AgentMessage': 'Message',
'NetworkAccess': 'Network Access', 'ShellExec': 'Shell Command', 'FileAccess': 'File Access',
'MemoryAccess': 'Memory Access', 'AuthAttempt': 'Login Attempt', 'AuthSuccess': 'Login Success',
'AuthFailure': 'Login Failed', 'CapabilityDenied': 'Permission Denied', 'RateLimited': 'Rate Limited'
};
return map[action] || action.replace(/([A-Z])/g, ' $1').trim();
},
async verifyChain() {
try {
var data = await OpenFangAPI.get('/api/audit/verify');
this.chainValid = data.valid === true;
if (this.chainValid) {
OpenFangToast.success('Audit chain verified — ' + (data.entries || 0) + ' entries valid');
} else {
OpenFangToast.error('Audit chain broken!');
}
} catch(e) {
this.chainValid = false;
OpenFangToast.error('Chain verification failed: ' + e.message);
}
},
destroy: function() {
if (this._eventSource) { this._eventSource.close(); this._eventSource = null; }
if (this._pollTimer) { clearInterval(this._pollTimer); this._pollTimer = null; }
}
};
}

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// OpenFang Overview Dashboard — Landing page with system stats + provider status
'use strict';
function overviewPage() {
return {
health: {},
status: {},
usageSummary: {},
recentAudit: [],
channels: [],
providers: [],
mcpServers: [],
skillCount: 0,
loading: true,
loadError: '',
refreshTimer: null,
lastRefresh: null,
async loadOverview() {
this.loading = true;
this.loadError = '';
try {
await Promise.all([
this.loadHealth(),
this.loadStatus(),
this.loadUsage(),
this.loadAudit(),
this.loadChannels(),
this.loadProviders(),
this.loadMcpServers(),
this.loadSkills()
]);
this.lastRefresh = Date.now();
} catch(e) {
this.loadError = e.message || 'Could not load overview data.';
}
this.loading = false;
},
async loadData() { return this.loadOverview(); },
// Silent background refresh (no loading spinner)
async silentRefresh() {
try {
await Promise.all([
this.loadHealth(),
this.loadStatus(),
this.loadUsage(),
this.loadAudit(),
this.loadChannels(),
this.loadProviders(),
this.loadMcpServers(),
this.loadSkills()
]);
this.lastRefresh = Date.now();
} catch(e) { /* silent */ }
},
startAutoRefresh() {
this.stopAutoRefresh();
this.refreshTimer = setInterval(() => this.silentRefresh(), 30000);
},
stopAutoRefresh() {
if (this.refreshTimer) {
clearInterval(this.refreshTimer);
this.refreshTimer = null;
}
},
async loadHealth() {
try {
this.health = await OpenFangAPI.get('/api/health');
} catch(e) { this.health = { status: 'unreachable' }; }
},
async loadStatus() {
try {
this.status = await OpenFangAPI.get('/api/status');
} catch(e) { this.status = {}; throw e; }
},
async loadUsage() {
try {
var data = await OpenFangAPI.get('/api/usage');
var agents = data.agents || [];
var totalTokens = 0;
var totalTools = 0;
var totalCost = 0;
agents.forEach(function(a) {
totalTokens += (a.total_tokens || 0);
totalTools += (a.tool_calls || 0);
totalCost += (a.cost_usd || 0);
});
this.usageSummary = {
total_tokens: totalTokens,
total_tools: totalTools,
total_cost: totalCost,
agent_count: agents.length
};
} catch(e) {
this.usageSummary = { total_tokens: 0, total_tools: 0, total_cost: 0, agent_count: 0 };
}
},
async loadAudit() {
try {
var data = await OpenFangAPI.get('/api/audit/recent?n=8');
this.recentAudit = data.entries || [];
} catch(e) { this.recentAudit = []; }
},
async loadChannels() {
try {
var data = await OpenFangAPI.get('/api/channels');
this.channels = (data.channels || []).filter(function(ch) { return ch.has_token; });
} catch(e) { this.channels = []; }
},
async loadProviders() {
try {
var data = await OpenFangAPI.get('/api/providers');
this.providers = data.providers || [];
} catch(e) { this.providers = []; }
},
async loadMcpServers() {
try {
var data = await OpenFangAPI.get('/api/mcp/servers');
this.mcpServers = data.servers || [];
} catch(e) { this.mcpServers = []; }
},
async loadSkills() {
try {
var data = await OpenFangAPI.get('/api/skills');
this.skillCount = (data.skills || []).length;
} catch(e) { this.skillCount = 0; }
},
get configuredProviders() {
return this.providers.filter(function(p) { return p.auth_status === 'configured'; });
},
get unconfiguredProviders() {
return this.providers.filter(function(p) { return p.auth_status === 'not_set' || p.auth_status === 'missing'; });
},
get connectedMcp() {
return this.mcpServers.filter(function(s) { return s.status === 'connected'; });
},
// Provider health badge color
providerBadgeClass(p) {
if (p.auth_status === 'configured') {
if (p.health === 'cooldown' || p.health === 'open') return 'badge-warn';
return 'badge-success';
}
if (p.auth_status === 'not_set' || p.auth_status === 'missing') return 'badge-muted';
return 'badge-dim';
},
// Provider health tooltip
providerTooltip(p) {
if (p.health === 'cooldown') return p.display_name + ' \u2014 cooling down (rate limited)';
if (p.health === 'open') return p.display_name + ' \u2014 circuit breaker open';
if (p.auth_status === 'configured') return p.display_name + ' \u2014 ready';
return p.display_name + ' \u2014 not configured';
},
// Audit action badge color
actionBadgeClass(action) {
if (!action) return 'badge-dim';
if (action === 'AgentSpawn' || action === 'AuthSuccess') return 'badge-success';
if (action === 'AgentKill' || action === 'AgentTerminated' || action === 'AuthFailure' || action === 'CapabilityDenied') return 'badge-error';
if (action === 'RateLimited' || action === 'ToolInvoke') return 'badge-warn';
return 'badge-created';
},
// ── Setup Checklist ──
checklistDismissed: localStorage.getItem('of-checklist-dismissed') === 'true',
get setupChecklist() {
return [
{ key: 'provider', label: 'Configure an LLM provider', done: this.configuredProviders.length > 0, action: '#settings' },
{ key: 'agent', label: 'Create your first agent', done: (Alpine.store('app').agents || []).length > 0, action: '#agents' },
{ key: 'chat', label: 'Send your first message', done: localStorage.getItem('of-first-msg') === 'true', action: '#chat' },
{ key: 'channel', label: 'Connect a messaging channel', done: this.channels.length > 0, action: '#channels' },
{ key: 'skill', label: 'Browse or install a skill', done: localStorage.getItem('of-skill-browsed') === 'true', action: '#skills' }
];
},
get setupProgress() {
var done = this.setupChecklist.filter(function(item) { return item.done; }).length;
return (done / 5) * 100;
},
get setupDoneCount() {
return this.setupChecklist.filter(function(item) { return item.done; }).length;
},
dismissChecklist() {
this.checklistDismissed = true;
localStorage.setItem('of-checklist-dismissed', 'true');
},
formatUptime(secs) {
if (!secs) return '-';
var d = Math.floor(secs / 86400);
var h = Math.floor((secs % 86400) / 3600);
var m = Math.floor((secs % 3600) / 60);
if (d > 0) return d + 'd ' + h + 'h';
if (h > 0) return h + 'h ' + m + 'm';
return m + 'm';
},
formatNumber(n) {
if (!n) return '0';
if (n >= 1000000) return (n / 1000000).toFixed(1) + 'M';
if (n >= 1000) return (n / 1000).toFixed(1) + 'K';
return String(n);
},
formatCost(n) {
if (!n || n === 0) return '$0.00';
if (n < 0.01) return '<$0.01';
return '$' + n.toFixed(2);
},
// Relative time formatting ("2m ago", "1h ago", "just now")
timeAgo(timestamp) {
if (!timestamp) return '';
var now = Date.now();
var ts = new Date(timestamp).getTime();
var diff = Math.floor((now - ts) / 1000);
if (diff < 10) return 'just now';
if (diff < 60) return diff + 's ago';
if (diff < 3600) return Math.floor(diff / 60) + 'm ago';
if (diff < 86400) return Math.floor(diff / 3600) + 'h ago';
return Math.floor(diff / 86400) + 'd ago';
},
// Map raw audit action names to user-friendly labels
friendlyAction(action) {
if (!action) return 'Unknown';
var map = {
'AgentSpawn': 'Agent Created',
'AgentKill': 'Agent Stopped',
'AgentTerminated': 'Agent Stopped',
'ToolInvoke': 'Tool Used',
'ToolResult': 'Tool Completed',
'MessageReceived': 'Message In',
'MessageSent': 'Response Sent',
'SessionReset': 'Session Reset',
'SessionCompact': 'Compacted',
'ModelSwitch': 'Model Changed',
'AuthAttempt': 'Login Attempt',
'AuthSuccess': 'Login OK',
'AuthFailure': 'Login Failed',
'CapabilityDenied': 'Denied',
'RateLimited': 'Rate Limited',
'WorkflowRun': 'Workflow Run',
'TriggerFired': 'Trigger Fired',
'SkillInstalled': 'Skill Installed',
'McpConnected': 'MCP Connected'
};
return map[action] || action.replace(/([A-Z])/g, ' $1').trim();
},
// Audit action icon (small inline SVG)
actionIcon(action) {
if (!action) return '';
var icons = {
'AgentSpawn': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/><path d="M12 8v8M8 12h8"/></svg>',
'AgentKill': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/><path d="M15 9l-6 6M9 9l6 6"/></svg>',
'AgentTerminated': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/><path d="M15 9l-6 6M9 9l6 6"/></svg>',
'ToolInvoke': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M14.7 6.3a1 1 0 0 0 0 1.4l1.6 1.6a1 1 0 0 0 1.4 0l3.77-3.77a6 6 0 0 1-7.94 7.94l-6.91 6.91a2.12 2.12 0 0 1-3-3l6.91-6.91a6 6 0 0 1 7.94-7.94l-3.76 3.76z"/></svg>',
'MessageReceived': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z"/></svg>',
'MessageSent': '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M22 2L11 13M22 2l-7 20-4-9-9-4 20-7z"/></svg>'
};
return icons[action] || '<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/></svg>';
},
// Resolve agent UUID to name if possible
agentName(agentId) {
if (!agentId) return '-';
var agents = Alpine.store('app').agents || [];
var agent = agents.find(function(a) { return a.id === agentId; });
return agent ? agent.name : agentId.substring(0, 8) + '\u2026';
}
};
}

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crates/openfang-api/static/js/pages/scheduler.js Normal file
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// OpenFang Scheduler Page — Cron job management + event triggers unified view
'use strict';
function schedulerPage() {
return {
tab: 'jobs',
// -- Scheduled Jobs state --
jobs: [],
loading: true,
loadError: '',
// -- Event Triggers state --
triggers: [],
trigLoading: false,
trigLoadError: '',
// -- Run History state --
history: [],
historyLoading: false,
// -- Create Job form --
showCreateForm: false,
newJob: {
name: '',
cron: '',
agent_id: '',
message: '',
enabled: true
},
creating: false,
// -- Run Now state --
runningJobId: '',
// Cron presets
cronPresets: [
{ label: 'Every minute', cron: '* * * * *' },
{ label: 'Every 5 minutes', cron: '*/5 * * * *' },
{ label: 'Every 15 minutes', cron: '*/15 * * * *' },
{ label: 'Every 30 minutes', cron: '*/30 * * * *' },
{ label: 'Every hour', cron: '0 * * * *' },
{ label: 'Every 6 hours', cron: '0 */6 * * *' },
{ label: 'Daily at midnight', cron: '0 0 * * *' },
{ label: 'Daily at 9am', cron: '0 9 * * *' },
{ label: 'Weekdays at 9am', cron: '0 9 * * 1-5' },
{ label: 'Every Monday 9am', cron: '0 9 * * 1' },
{ label: 'First of month', cron: '0 0 1 * *' }
],
// ── Lifecycle ──
async loadData() {
this.loading = true;
this.loadError = '';
try {
await this.loadJobs();
} catch(e) {
this.loadError = e.message || 'Could not load scheduler data.';
}
this.loading = false;
},
async loadJobs() {
var data = await OpenFangAPI.get('/api/cron/jobs');
var raw = data.jobs || [];
// Normalize cron API response to flat fields the UI expects
this.jobs = raw.map(function(j) {
var cron = '';
if (j.schedule) {
if (j.schedule.kind === 'cron') cron = j.schedule.expr || '';
else if (j.schedule.kind === 'every') cron = 'every ' + j.schedule.every_secs + 's';
else if (j.schedule.kind === 'at') cron = 'at ' + (j.schedule.at || '');
}
return {
id: j.id,
name: j.name,
cron: cron,
agent_id: j.agent_id,
message: j.action ? j.action.message || '' : '',
enabled: j.enabled,
last_run: j.last_run,
next_run: j.next_run,
delivery: j.delivery ? j.delivery.kind || '' : '',
created_at: j.created_at
};
});
},
async loadTriggers() {
this.trigLoading = true;
this.trigLoadError = '';
try {
var data = await OpenFangAPI.get('/api/triggers');
this.triggers = Array.isArray(data) ? data : [];
} catch(e) {
this.triggers = [];
this.trigLoadError = e.message || 'Could not load triggers.';
}
this.trigLoading = false;
},
async loadHistory() {
this.historyLoading = true;
try {
var historyItems = [];
var jobs = this.jobs || [];
for (var i = 0; i < jobs.length; i++) {
var job = jobs[i];
if (job.last_run) {
historyItems.push({
timestamp: job.last_run,
name: job.name || '(unnamed)',
type: 'schedule',
status: 'completed',
run_count: 0
});
}
}
var triggers = this.triggers || [];
for (var j = 0; j < triggers.length; j++) {
var t = triggers[j];
if (t.fire_count > 0) {
historyItems.push({
timestamp: t.created_at,
name: 'Trigger: ' + this.triggerType(t.pattern),
type: 'trigger',
status: 'fired',
run_count: t.fire_count
});
}
}
historyItems.sort(function(a, b) {
return new Date(b.timestamp).getTime() - new Date(a.timestamp).getTime();
});
this.history = historyItems;
} catch(e) {
this.history = [];
}
this.historyLoading = false;
},
// ── Job CRUD ──
async createJob() {
if (!this.newJob.name.trim()) {
OpenFangToast.warn('Please enter a job name');
return;
}
if (!this.newJob.cron.trim()) {
OpenFangToast.warn('Please enter a cron expression');
return;
}
this.creating = true;
try {
var jobName = this.newJob.name;
var body = {
agent_id: this.newJob.agent_id,
name: this.newJob.name,
schedule: { kind: 'cron', expr: this.newJob.cron },
action: { kind: 'agent_turn', message: this.newJob.message || 'Scheduled task: ' + this.newJob.name },
delivery: { kind: 'last_channel' },
enabled: this.newJob.enabled
};
await OpenFangAPI.post('/api/cron/jobs', body);
this.showCreateForm = false;
this.newJob = { name: '', cron: '', agent_id: '', message: '', enabled: true };
OpenFangToast.success('Schedule "' + jobName + '" created');
await this.loadJobs();
} catch(e) {
OpenFangToast.error('Failed to create schedule: ' + (e.message || e));
}
this.creating = false;
},
async toggleJob(job) {
try {
var newState = !job.enabled;
await OpenFangAPI.put('/api/cron/jobs/' + job.id + '/enable', { enabled: newState });
job.enabled = newState;
OpenFangToast.success('Schedule ' + (newState ? 'enabled' : 'paused'));
} catch(e) {
OpenFangToast.error('Failed to toggle schedule: ' + (e.message || e));
}
},
deleteJob(job) {
var self = this;
var jobName = job.name || job.id;
OpenFangToast.confirm('Delete Schedule', 'Delete "' + jobName + '"? This cannot be undone.', async function() {
try {
await OpenFangAPI.del('/api/cron/jobs/' + job.id);
self.jobs = self.jobs.filter(function(j) { return j.id !== job.id; });
OpenFangToast.success('Schedule "' + jobName + '" deleted');
} catch(e) {
OpenFangToast.error('Failed to delete schedule: ' + (e.message || e));
}
});
},
async runNow(job) {
this.runningJobId = job.id;
try {
var result = await OpenFangAPI.post('/api/schedules/' + job.id + '/run', {});
if (result.status === 'completed') {
OpenFangToast.success('Schedule "' + (job.name || 'job') + '" executed successfully');
job.last_run = new Date().toISOString();
} else {
OpenFangToast.error('Schedule run failed: ' + (result.error || 'Unknown error'));
}
} catch(e) {
OpenFangToast.error('Run Now is not yet available for cron jobs');
}
this.runningJobId = '';
},
// ── Trigger helpers ──
triggerType(pattern) {
if (!pattern) return 'unknown';
if (typeof pattern === 'string') return pattern;
var keys = Object.keys(pattern);
if (keys.length === 0) return 'unknown';
var key = keys[0];
var names = {
lifecycle: 'Lifecycle',
agent_spawned: 'Agent Spawned',
agent_terminated: 'Agent Terminated',
system: 'System',
system_keyword: 'System Keyword',
memory_update: 'Memory Update',
memory_key_pattern: 'Memory Key',
all: 'All Events',
content_match: 'Content Match'
};
return names[key] || key.replace(/_/g, ' ');
},
async toggleTrigger(trigger) {
try {
var newState = !trigger.enabled;
await OpenFangAPI.put('/api/triggers/' + trigger.id, { enabled: newState });
trigger.enabled = newState;
OpenFangToast.success('Trigger ' + (newState ? 'enabled' : 'disabled'));
} catch(e) {
OpenFangToast.error('Failed to toggle trigger: ' + (e.message || e));
}
},
deleteTrigger(trigger) {
var self = this;
OpenFangToast.confirm('Delete Trigger', 'Delete this trigger? This cannot be undone.', async function() {
try {
await OpenFangAPI.del('/api/triggers/' + trigger.id);
self.triggers = self.triggers.filter(function(t) { return t.id !== trigger.id; });
OpenFangToast.success('Trigger deleted');
} catch(e) {
OpenFangToast.error('Failed to delete trigger: ' + (e.message || e));
}
});
},
// ── Utility ──
get availableAgents() {
return Alpine.store('app').agents || [];
},
agentName(agentId) {
if (!agentId) return '(any)';
var agents = this.availableAgents;
for (var i = 0; i < agents.length; i++) {
if (agents[i].id === agentId) return agents[i].name;
}
if (agentId.length > 12) return agentId.substring(0, 8) + '...';
return agentId;
},
describeCron(expr) {
if (!expr) return '';
// Handle non-cron schedule descriptions
if (expr.indexOf('every ') === 0) return expr;
if (expr.indexOf('at ') === 0) return 'One-time: ' + expr.substring(3);
var map = {
'* * * * *': 'Every minute',
'*/2 * * * *': 'Every 2 minutes',
'*/5 * * * *': 'Every 5 minutes',
'*/10 * * * *': 'Every 10 minutes',
'*/15 * * * *': 'Every 15 minutes',
'*/30 * * * *': 'Every 30 minutes',
'0 * * * *': 'Every hour',
'0 */2 * * *': 'Every 2 hours',
'0 */4 * * *': 'Every 4 hours',
'0 */6 * * *': 'Every 6 hours',
'0 */12 * * *': 'Every 12 hours',
'0 0 * * *': 'Daily at midnight',
'0 6 * * *': 'Daily at 6:00 AM',
'0 9 * * *': 'Daily at 9:00 AM',
'0 12 * * *': 'Daily at noon',
'0 18 * * *': 'Daily at 6:00 PM',
'0 9 * * 1-5': 'Weekdays at 9:00 AM',
'0 9 * * 1': 'Mondays at 9:00 AM',
'0 0 * * 0': 'Sundays at midnight',
'0 0 1 * *': '1st of every month',
'0 0 * * 1': 'Mondays at midnight'
};
if (map[expr]) return map[expr];
var parts = expr.split(' ');
if (parts.length !== 5) return expr;
var min = parts[0];
var hour = parts[1];
var dom = parts[2];
var mon = parts[3];
var dow = parts[4];
if (min.indexOf('*/') === 0 && hour === '*' && dom === '*' && mon === '*' && dow === '*') {
return 'Every ' + min.substring(2) + ' minutes';
}
if (min === '0' && hour.indexOf('*/') === 0 && dom === '*' && mon === '*' && dow === '*') {
return 'Every ' + hour.substring(2) + ' hours';
}
var dowNames = { '0': 'Sun', '1': 'Mon', '2': 'Tue', '3': 'Wed', '4': 'Thu', '5': 'Fri', '6': 'Sat', '7': 'Sun',
'1-5': 'Weekdays', '0,6': 'Weekends', '6,0': 'Weekends' };
if (dom === '*' && mon === '*' && min.match(/^\d+$/) && hour.match(/^\d+$/)) {
var h = parseInt(hour, 10);
var m = parseInt(min, 10);
var ampm = h >= 12 ? 'PM' : 'AM';
var h12 = h === 0 ? 12 : (h > 12 ? h - 12 : h);
var mStr = m < 10 ? '0' + m : '' + m;
var timeStr = h12 + ':' + mStr + ' ' + ampm;
if (dow === '*') return 'Daily at ' + timeStr;
var dowLabel = dowNames[dow] || ('DoW ' + dow);
return dowLabel + ' at ' + timeStr;
}
return expr;
},
applyCronPreset(preset) {
this.newJob.cron = preset.cron;
},
formatTime(ts) {
if (!ts) return '-';
try {
var d = new Date(ts);
if (isNaN(d.getTime())) return '-';
return d.toLocaleString();
} catch(e) { return '-'; }
},
relativeTime(ts) {
if (!ts) return 'never';
try {
var diff = Date.now() - new Date(ts).getTime();
if (isNaN(diff)) return 'never';
if (diff < 0) {
// Future time
var absDiff = Math.abs(diff);
if (absDiff < 60000) return 'in <1m';
if (absDiff < 3600000) return 'in ' + Math.floor(absDiff / 60000) + 'm';
if (absDiff < 86400000) return 'in ' + Math.floor(absDiff / 3600000) + 'h';
return 'in ' + Math.floor(absDiff / 86400000) + 'd';
}
if (diff < 60000) return 'just now';
if (diff < 3600000) return Math.floor(diff / 60000) + 'm ago';
if (diff < 86400000) return Math.floor(diff / 3600000) + 'h ago';
return Math.floor(diff / 86400000) + 'd ago';
} catch(e) { return 'never'; }
},
jobCount() {
var enabled = 0;
for (var i = 0; i < this.jobs.length; i++) {
if (this.jobs[i].enabled) enabled++;
}
return enabled;
},
triggerCount() {
var enabled = 0;
for (var i = 0; i < this.triggers.length; i++) {
if (this.triggers[i].enabled) enabled++;
}
return enabled;
}
};
}

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// OpenFang Sessions Page — Session listing + Memory tab
'use strict';
function sessionsPage() {
return {
tab: 'sessions',
// -- Sessions state --
sessions: [],
searchFilter: '',
loading: true,
loadError: '',
// -- Memory state --
memAgentId: '',
kvPairs: [],
showAdd: false,
newKey: '',
newValue: '""',
editingKey: null,
editingValue: '',
memLoading: false,
memLoadError: '',
// -- Sessions methods --
async loadSessions() {
this.loading = true;
this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/sessions');
var sessions = data.sessions || [];
var agents = Alpine.store('app').agents;
var agentMap = {};
agents.forEach(function(a) { agentMap[a.id] = a.name; });
sessions.forEach(function(s) {
s.agent_name = agentMap[s.agent_id] || '';
});
this.sessions = sessions;
} catch(e) {
this.sessions = [];
this.loadError = e.message || 'Could not load sessions.';
}
this.loading = false;
},
async loadData() { return this.loadSessions(); },
get filteredSessions() {
var f = this.searchFilter.toLowerCase();
if (!f) return this.sessions;
return this.sessions.filter(function(s) {
return (s.agent_name || '').toLowerCase().indexOf(f) !== -1 ||
(s.agent_id || '').toLowerCase().indexOf(f) !== -1;
});
},
openInChat(session) {
var agents = Alpine.store('app').agents;
var agent = agents.find(function(a) { return a.id === session.agent_id; });
if (agent) {
Alpine.store('app').pendingAgent = agent;
}
location.hash = 'agents';
},
deleteSession(sessionId) {
var self = this;
OpenFangToast.confirm('Delete Session', 'This will permanently remove the session and its messages.', async function() {
try {
await OpenFangAPI.del('/api/sessions/' + sessionId);
self.sessions = self.sessions.filter(function(s) { return s.session_id !== sessionId; });
OpenFangToast.success('Session deleted');
} catch(e) {
OpenFangToast.error('Failed to delete session: ' + e.message);
}
});
},
// -- Memory methods --
async loadKv() {
if (!this.memAgentId) { this.kvPairs = []; return; }
this.memLoading = true;
this.memLoadError = '';
try {
var data = await OpenFangAPI.get('/api/memory/agents/' + this.memAgentId + '/kv');
this.kvPairs = data.kv_pairs || [];
} catch(e) {
this.kvPairs = [];
this.memLoadError = e.message || 'Could not load memory data.';
}
this.memLoading = false;
},
async addKey() {
if (!this.memAgentId || !this.newKey.trim()) return;
var value;
try { value = JSON.parse(this.newValue); } catch(e) { value = this.newValue; }
try {
await OpenFangAPI.put('/api/memory/agents/' + this.memAgentId + '/kv/' + encodeURIComponent(this.newKey), { value: value });
this.showAdd = false;
OpenFangToast.success('Key "' + this.newKey + '" saved');
this.newKey = '';
this.newValue = '""';
await this.loadKv();
} catch(e) {
OpenFangToast.error('Failed to save key: ' + e.message);
}
},
deleteKey(key) {
var self = this;
OpenFangToast.confirm('Delete Key', 'Delete key "' + key + '"? This cannot be undone.', async function() {
try {
await OpenFangAPI.del('/api/memory/agents/' + self.memAgentId + '/kv/' + encodeURIComponent(key));
OpenFangToast.success('Key "' + key + '" deleted');
await self.loadKv();
} catch(e) {
OpenFangToast.error('Failed to delete key: ' + e.message);
}
});
},
startEdit(kv) {
this.editingKey = kv.key;
this.editingValue = typeof kv.value === 'object' ? JSON.stringify(kv.value, null, 2) : String(kv.value);
},
cancelEdit() {
this.editingKey = null;
this.editingValue = '';
},
async saveEdit() {
if (!this.editingKey || !this.memAgentId) return;
var value;
try { value = JSON.parse(this.editingValue); } catch(e) { value = this.editingValue; }
try {
await OpenFangAPI.put('/api/memory/agents/' + this.memAgentId + '/kv/' + encodeURIComponent(this.editingKey), { value: value });
OpenFangToast.success('Key "' + this.editingKey + '" updated');
this.editingKey = null;
this.editingValue = '';
await this.loadKv();
} catch(e) {
OpenFangToast.error('Failed to save: ' + e.message);
}
}
};
}

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crates/openfang-api/static/js/pages/settings.js Normal file
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// OpenFang Settings Page — Provider Hub, Model Catalog, Config, Tools + Security, Network, Migration tabs
'use strict';
function settingsPage() {
return {
tab: 'providers',
sysInfo: {},
usageData: [],
tools: [],
config: {},
providers: [],
models: [],
toolSearch: '',
modelSearch: '',
modelProviderFilter: '',
modelTierFilter: '',
showCustomModelForm: false,
customModelId: '',
customModelProvider: 'openrouter',
customModelContext: 128000,
customModelMaxOutput: 8192,
customModelStatus: '',
providerKeyInputs: {},
providerUrlInputs: {},
providerUrlSaving: {},
providerTesting: {},
providerTestResults: {},
copilotOAuth: { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 },
loading: true,
loadError: '',
// -- Dynamic config state --
configSchema: null,
configValues: {},
configDirty: {},
configSaving: {},
// -- Security state --
securityData: null,
secLoading: false,
verifyingChain: false,
chainResult: null,
coreFeatures: [
{
name: 'Path Traversal Prevention', key: 'path_traversal',
description: 'Blocks directory escape attacks (../) in all file operations. Two-phase validation: syntactic rejection of path components, then canonicalization to normalize symlinks.',
threat: 'Directory escape, privilege escalation via symlinks',
impl: 'host_functions.rs — safe_resolve_path() + safe_resolve_parent()'
},
{
name: 'SSRF Protection', key: 'ssrf_protection',
description: 'Blocks outbound requests to private IPs, localhost, and cloud metadata endpoints (AWS/GCP/Azure). Validates DNS resolution results to defeat rebinding attacks.',
threat: 'Internal network reconnaissance, cloud credential theft',
impl: 'host_functions.rs — is_ssrf_target() + is_private_ip()'
},
{
name: 'Capability-Based Access Control', key: 'capability_system',
description: 'Deny-by-default permission system. Every agent operation (file I/O, network, shell, memory, spawn) requires an explicit capability grant in the manifest.',
threat: 'Unauthorized resource access, sandbox escape',
impl: 'host_functions.rs — check_capability() on every host function'
},
{
name: 'Privilege Escalation Prevention', key: 'privilege_escalation_prevention',
description: 'When a parent agent spawns a child, the kernel enforces child capabilities are a subset of parent capabilities. No agent can grant rights it does not have.',
threat: 'Capability escalation through agent spawning chains',
impl: 'kernel_handle.rs — spawn_agent_checked()'
},
{
name: 'Subprocess Environment Isolation', key: 'subprocess_isolation',
description: 'Child processes (shell tools) inherit only a safe allow-list of environment variables. API keys, database passwords, and secrets are never leaked to subprocesses.',
threat: 'Secret exfiltration via child process environment',
impl: 'subprocess_sandbox.rs — env_clear() + SAFE_ENV_VARS'
},
{
name: 'Security Headers', key: 'security_headers',
description: 'Every HTTP response includes CSP, X-Frame-Options: DENY, X-Content-Type-Options: nosniff, Referrer-Policy, and X-XSS-Protection headers.',
threat: 'XSS, clickjacking, MIME sniffing, content injection',
impl: 'middleware.rs — security_headers()'
},
{
name: 'Wire Protocol Authentication', key: 'wire_hmac_auth',
description: 'Agent-to-agent OFP connections use HMAC-SHA256 mutual authentication with nonce-based handshake and constant-time signature comparison (subtle crate).',
threat: 'Man-in-the-middle attacks on mesh network',
impl: 'peer.rs — hmac_sign() + hmac_verify()'
},
{
name: 'Request ID Tracking', key: 'request_id_tracking',
description: 'Every API request receives a unique UUID (x-request-id header) and is logged with method, path, status code, and latency for full traceability.',
threat: 'Untraceable actions, forensic blind spots',
impl: 'middleware.rs — request_logging()'
}
],
configurableFeatures: [
{
name: 'API Rate Limiting', key: 'rate_limiter',
description: 'GCRA (Generic Cell Rate Algorithm) with cost-aware tokens. Different endpoints cost different amounts — spawning an agent costs 50 tokens, health check costs 1.',
configHint: 'Hard-coded: 500 tokens/minute per IP. Edit rate_limiter.rs to tune.',
valueKey: 'rate_limiter'
},
{
name: 'WebSocket Connection Limits', key: 'websocket_limits',
description: 'Per-IP connection cap prevents connection exhaustion. Idle timeout closes abandoned connections. Message rate limiting prevents flooding.',
configHint: 'Hard-coded: 5 connections/IP, 30min idle timeout, 64KB max message. Edit ws.rs to tune.',
valueKey: 'websocket_limits'
},
{
name: 'WASM Dual Metering', key: 'wasm_sandbox',
description: 'WASM modules run with two independent resource limits: fuel metering (CPU instruction count) and epoch interruption (wall-clock timeout with watchdog thread).',
configHint: 'Default: 1M fuel units, 30s timeout. Configurable per-agent via SandboxConfig.',
valueKey: 'wasm_sandbox'
},
{
name: 'Bearer Token Authentication', key: 'auth',
description: 'All non-health endpoints require Authorization: Bearer header. When no API key is configured, all requests are restricted to localhost only.',
configHint: 'Set api_key in ~/.openfang/config.toml for remote access. Empty = localhost only.',
valueKey: 'auth'
}
],
monitoringFeatures: [
{
name: 'Merkle Audit Trail', key: 'audit_trail',
description: 'Every security-critical action is appended to an immutable, tamper-evident log. Each entry is cryptographically linked to the previous via SHA-256 hash chain.',
configHint: 'Always active. Verify chain integrity from the Audit Log page.',
valueKey: 'audit_trail'
},
{
name: 'Information Flow Taint Tracking', key: 'taint_tracking',
description: 'Labels data by provenance (ExternalNetwork, UserInput, PII, Secret, UntrustedAgent) and blocks unsafe flows: external data cannot reach shell_exec, secrets cannot reach network.',
configHint: 'Always active. Prevents data flow attacks automatically.',
valueKey: 'taint_tracking'
},
{
name: 'Ed25519 Manifest Signing', key: 'manifest_signing',
description: 'Agent manifests can be cryptographically signed with Ed25519. Verify manifest integrity before loading to prevent supply chain tampering.',
configHint: 'Available for use. Sign manifests with ed25519-dalek for verification.',
valueKey: 'manifest_signing'
}
],
// -- Peers state --
peers: [],
peersLoading: false,
peersLoadError: '',
_peerPollTimer: null,
// -- Migration state --
migStep: 'intro',
detecting: false,
scanning: false,
migrating: false,
sourcePath: '',
targetPath: '',
scanResult: null,
migResult: null,
// -- Settings load --
async loadSettings() {
this.loading = true;
this.loadError = '';
try {
await Promise.all([
this.loadSysInfo(),
this.loadUsage(),
this.loadTools(),
this.loadConfig(),
this.loadProviders(),
this.loadModels()
]);
} catch(e) {
this.loadError = e.message || 'Could not load settings.';
}
this.loading = false;
},
async loadData() { return this.loadSettings(); },
async loadSysInfo() {
try {
var ver = await OpenFangAPI.get('/api/version');
var status = await OpenFangAPI.get('/api/status');
this.sysInfo = {
version: ver.version || '-',
platform: ver.platform || '-',
arch: ver.arch || '-',
uptime_seconds: status.uptime_seconds || 0,
agent_count: status.agent_count || 0,
default_provider: status.default_provider || '-',
default_model: status.default_model || '-'
};
} catch(e) { throw e; }
},
async loadUsage() {
try {
var data = await OpenFangAPI.get('/api/usage');
this.usageData = data.agents || [];
} catch(e) { this.usageData = []; }
},
async loadTools() {
try {
var data = await OpenFangAPI.get('/api/tools');
this.tools = data.tools || [];
} catch(e) { this.tools = []; }
},
async loadConfig() {
try {
this.config = await OpenFangAPI.get('/api/config');
} catch(e) { this.config = {}; }
},
async loadProviders() {
try {
var data = await OpenFangAPI.get('/api/providers');
this.providers = data.providers || [];
for (var i = 0; i < this.providers.length; i++) {
var p = this.providers[i];
if (p.is_local && p.base_url && !this.providerUrlInputs[p.id]) {
this.providerUrlInputs[p.id] = p.base_url;
}
}
} catch(e) { this.providers = []; }
},
async loadModels() {
try {
var data = await OpenFangAPI.get('/api/models');
this.models = data.models || [];
} catch(e) { this.models = []; }
},
async addCustomModel() {
var id = this.customModelId.trim();
if (!id) return;
this.customModelStatus = 'Adding...';
try {
await OpenFangAPI.post('/api/models/custom', {
id: id,
provider: this.customModelProvider || 'openrouter',
context_window: this.customModelContext || 128000,
max_output_tokens: this.customModelMaxOutput || 8192,
});
this.customModelStatus = 'Added!';
this.customModelId = '';
this.showCustomModelForm = false;
await this.loadModels();
} catch(e) {
this.customModelStatus = 'Error: ' + (e.message || 'Failed');
}
},
async loadConfigSchema() {
try {
var results = await Promise.all([
OpenFangAPI.get('/api/config/schema').catch(function() { return {}; }),
OpenFangAPI.get('/api/config')
]);
this.configSchema = results[0].sections || null;
this.configValues = results[1] || {};
} catch(e) { /* silent */ }
},
isConfigDirty(section, field) {
return this.configDirty[section + '.' + field] === true;
},
markConfigDirty(section, field) {
this.configDirty[section + '.' + field] = true;
},
async saveConfigField(section, field, value) {
var key = section + '.' + field;
this.configSaving[key] = true;
try {
await OpenFangAPI.post('/api/config/set', { path: key, value: value });
this.configDirty[key] = false;
OpenFangToast.success('Saved ' + key);
} catch(e) {
OpenFangToast.error('Failed to save: ' + e.message);
}
this.configSaving[key] = false;
},
get filteredTools() {
var q = this.toolSearch.toLowerCase().trim();
if (!q) return this.tools;
return this.tools.filter(function(t) {
return t.name.toLowerCase().indexOf(q) !== -1 ||
(t.description || '').toLowerCase().indexOf(q) !== -1;
});
},
get filteredModels() {
var self = this;
return this.models.filter(function(m) {
if (self.modelProviderFilter && m.provider !== self.modelProviderFilter) return false;
if (self.modelTierFilter && m.tier !== self.modelTierFilter) return false;
if (self.modelSearch) {
var q = self.modelSearch.toLowerCase();
if (m.id.toLowerCase().indexOf(q) === -1 &&
(m.display_name || '').toLowerCase().indexOf(q) === -1) return false;
}
return true;
});
},
get uniqueProviderNames() {
var seen = {};
this.models.forEach(function(m) { seen[m.provider] = true; });
return Object.keys(seen).sort();
},
get uniqueTiers() {
var seen = {};
this.models.forEach(function(m) { if (m.tier) seen[m.tier] = true; });
return Object.keys(seen).sort();
},
providerAuthClass(p) {
if (p.auth_status === 'configured') return 'auth-configured';
if (p.auth_status === 'not_set' || p.auth_status === 'missing') return 'auth-not-set';
return 'auth-no-key';
},
providerAuthText(p) {
if (p.auth_status === 'configured') return 'Configured';
if (p.auth_status === 'not_set' || p.auth_status === 'missing') return 'Not Set';
return 'No Key Needed';
},
providerCardClass(p) {
if (p.auth_status === 'configured') return 'configured';
if (p.auth_status === 'not_set' || p.auth_status === 'missing') return 'not-configured';
return 'no-key';
},
tierBadgeClass(tier) {
if (!tier) return '';
var t = tier.toLowerCase();
if (t === 'frontier') return 'tier-frontier';
if (t === 'smart') return 'tier-smart';
if (t === 'balanced') return 'tier-balanced';
if (t === 'fast') return 'tier-fast';
return '';
},
formatCost(cost) {
if (!cost && cost !== 0) return '-';
return '$' + cost.toFixed(4);
},
formatContext(ctx) {
if (!ctx) return '-';
if (ctx >= 1000000) return (ctx / 1000000).toFixed(1) + 'M';
if (ctx >= 1000) return Math.round(ctx / 1000) + 'K';
return String(ctx);
},
formatUptime(secs) {
if (!secs) return '-';
var h = Math.floor(secs / 3600);
var m = Math.floor((secs % 3600) / 60);
var s = secs % 60;
if (h > 0) return h + 'h ' + m + 'm';
if (m > 0) return m + 'm ' + s + 's';
return s + 's';
},
async saveProviderKey(provider) {
var key = this.providerKeyInputs[provider.id];
if (!key || !key.trim()) { OpenFangToast.error('Please enter an API key'); return; }
try {
await OpenFangAPI.post('/api/providers/' + encodeURIComponent(provider.id) + '/key', { key: key.trim() });
OpenFangToast.success('API key saved for ' + provider.display_name);
this.providerKeyInputs[provider.id] = '';
await this.loadProviders();
await this.loadModels();
} catch(e) {
OpenFangToast.error('Failed to save key: ' + e.message);
}
},
async removeProviderKey(provider) {
try {
await OpenFangAPI.del('/api/providers/' + encodeURIComponent(provider.id) + '/key');
OpenFangToast.success('API key removed for ' + provider.display_name);
await this.loadProviders();
await this.loadModels();
} catch(e) {
OpenFangToast.error('Failed to remove key: ' + e.message);
}
},
async startCopilotOAuth() {
this.copilotOAuth.polling = true;
this.copilotOAuth.userCode = '';
try {
var resp = await OpenFangAPI.post('/api/providers/github-copilot/oauth/start', {});
this.copilotOAuth.userCode = resp.user_code;
this.copilotOAuth.verificationUri = resp.verification_uri;
this.copilotOAuth.pollId = resp.poll_id;
this.copilotOAuth.interval = resp.interval || 5;
window.open(resp.verification_uri, '_blank');
this.pollCopilotOAuth();
} catch(e) {
OpenFangToast.error('Failed to start Copilot login: ' + e.message);
this.copilotOAuth.polling = false;
}
},
pollCopilotOAuth() {
var self = this;
setTimeout(async function() {
if (!self.copilotOAuth.pollId) return;
try {
var resp = await OpenFangAPI.get('/api/providers/github-copilot/oauth/poll/' + self.copilotOAuth.pollId);
if (resp.status === 'complete') {
OpenFangToast.success('GitHub Copilot authenticated successfully!');
self.copilotOAuth = { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 };
await self.loadProviders();
await self.loadModels();
} else if (resp.status === 'pending') {
if (resp.interval) self.copilotOAuth.interval = resp.interval;
self.pollCopilotOAuth();
} else if (resp.status === 'expired') {
OpenFangToast.error('Device code expired. Please try again.');
self.copilotOAuth = { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 };
} else if (resp.status === 'denied') {
OpenFangToast.error('Access denied by user.');
self.copilotOAuth = { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 };
} else {
OpenFangToast.error('OAuth error: ' + (resp.error || resp.status));
self.copilotOAuth = { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 };
}
} catch(e) {
OpenFangToast.error('Poll error: ' + e.message);
self.copilotOAuth = { polling: false, userCode: '', verificationUri: '', pollId: '', interval: 5 };
}
}, self.copilotOAuth.interval * 1000);
},
async testProvider(provider) {
this.providerTesting[provider.id] = true;
this.providerTestResults[provider.id] = null;
try {
var result = await OpenFangAPI.post('/api/providers/' + encodeURIComponent(provider.id) + '/test', {});
this.providerTestResults[provider.id] = result;
if (result.status === 'ok') {
OpenFangToast.success(provider.display_name + ' connected (' + (result.latency_ms || '?') + 'ms)');
} else {
OpenFangToast.error(provider.display_name + ': ' + (result.error || 'Connection failed'));
}
} catch(e) {
this.providerTestResults[provider.id] = { status: 'error', error: e.message };
OpenFangToast.error('Test failed: ' + e.message);
}
this.providerTesting[provider.id] = false;
},
async saveProviderUrl(provider) {
var url = this.providerUrlInputs[provider.id];
if (!url || !url.trim()) { OpenFangToast.error('Please enter a base URL'); return; }
url = url.trim();
if (url.indexOf('http://') !== 0 && url.indexOf('https://') !== 0) {
OpenFangToast.error('URL must start with http:// or https://'); return;
}
this.providerUrlSaving[provider.id] = true;
try {
var result = await OpenFangAPI.put('/api/providers/' + encodeURIComponent(provider.id) + '/url', { base_url: url });
if (result.reachable) {
OpenFangToast.success(provider.display_name + ' URL saved &mdash; reachable (' + (result.latency_ms || '?') + 'ms)');
} else {
OpenFangToast.warning(provider.display_name + ' URL saved but not reachable');
}
await this.loadProviders();
} catch(e) {
OpenFangToast.error('Failed to save URL: ' + e.message);
}
this.providerUrlSaving[provider.id] = false;
},
// -- Security methods --
async loadSecurity() {
this.secLoading = true;
try {
this.securityData = await OpenFangAPI.get('/api/security');
} catch(e) {
this.securityData = null;
}
this.secLoading = false;
},
isActive(key) {
if (!this.securityData) return true;
var core = this.securityData.core_protections || {};
if (core[key] !== undefined) return core[key];
return true;
},
getConfigValue(key) {
if (!this.securityData) return null;
var cfg = this.securityData.configurable || {};
return cfg[key] || null;
},
getMonitoringValue(key) {
if (!this.securityData) return null;
var mon = this.securityData.monitoring || {};
return mon[key] || null;
},
formatConfigValue(feature) {
var val = this.getConfigValue(feature.valueKey);
if (!val) return feature.configHint;
switch (feature.valueKey) {
case 'rate_limiter':
return 'Algorithm: ' + (val.algorithm || 'GCRA') + ' | ' + (val.tokens_per_minute || 500) + ' tokens/min per IP';
case 'websocket_limits':
return 'Max ' + (val.max_per_ip || 5) + ' conn/IP | ' + Math.round((val.idle_timeout_secs || 1800) / 60) + 'min idle timeout | ' + Math.round((val.max_message_size || 65536) / 1024) + 'KB max msg';
case 'wasm_sandbox':
return 'Fuel: ' + (val.fuel_metering ? 'ON' : 'OFF') + ' | Epoch: ' + (val.epoch_interruption ? 'ON' : 'OFF') + ' | Timeout: ' + (val.default_timeout_secs || 30) + 's';
case 'auth':
return 'Mode: ' + (val.mode || 'unknown') + (val.api_key_set ? ' (key configured)' : ' (no key set)');
default:
return feature.configHint;
}
},
formatMonitoringValue(feature) {
var val = this.getMonitoringValue(feature.valueKey);
if (!val) return feature.configHint;
switch (feature.valueKey) {
case 'audit_trail':
return (val.enabled ? 'Active' : 'Disabled') + ' | ' + (val.algorithm || 'SHA-256') + ' | ' + (val.entry_count || 0) + ' entries logged';
case 'taint_tracking':
var labels = val.tracked_labels || [];
return (val.enabled ? 'Active' : 'Disabled') + ' | Tracking: ' + labels.join(', ');
case 'manifest_signing':
return 'Algorithm: ' + (val.algorithm || 'Ed25519') + ' | ' + (val.available ? 'Available' : 'Not available');
default:
return feature.configHint;
}
},
async verifyAuditChain() {
this.verifyingChain = true;
this.chainResult = null;
try {
var res = await OpenFangAPI.get('/api/audit/verify');
this.chainResult = res;
} catch(e) {
this.chainResult = { valid: false, error: e.message };
}
this.verifyingChain = false;
},
// -- Peers methods --
async loadPeers() {
this.peersLoading = true;
this.peersLoadError = '';
try {
var data = await OpenFangAPI.get('/api/peers');
this.peers = (data.peers || []).map(function(p) {
return {
node_id: p.node_id,
node_name: p.node_name,
address: p.address,
state: p.state,
agent_count: (p.agents || []).length,
protocol_version: p.protocol_version || 1
};
});
} catch(e) {
this.peers = [];
this.peersLoadError = e.message || 'Could not load peers.';
}
this.peersLoading = false;
},
startPeerPolling() {
var self = this;
this.stopPeerPolling();
this._peerPollTimer = setInterval(async function() {
if (self.tab !== 'network') { self.stopPeerPolling(); return; }
try {
var data = await OpenFangAPI.get('/api/peers');
self.peers = (data.peers || []).map(function(p) {
return {
node_id: p.node_id,
node_name: p.node_name,
address: p.address,
state: p.state,
agent_count: (p.agents || []).length,
protocol_version: p.protocol_version || 1
};
});
} catch(e) { /* silent */ }
}, 15000);
},
stopPeerPolling() {
if (this._peerPollTimer) { clearInterval(this._peerPollTimer); this._peerPollTimer = null; }
},
// -- Migration methods --
async autoDetect() {
this.detecting = true;
try {
var data = await OpenFangAPI.get('/api/migrate/detect');
if (data.detected && data.scan) {
this.sourcePath = data.path;
this.scanResult = data.scan;
this.migStep = 'preview';
} else {
this.migStep = 'not_found';
}
} catch(e) {
this.migStep = 'not_found';
}
this.detecting = false;
},
async scanPath() {
if (!this.sourcePath) return;
this.scanning = true;
try {
var data = await OpenFangAPI.post('/api/migrate/scan', { path: this.sourcePath });
if (data.error) {
OpenFangToast.error('Scan error: ' + data.error);
this.scanning = false;
return;
}
this.scanResult = data;
this.migStep = 'preview';
} catch(e) {
OpenFangToast.error('Scan failed: ' + e.message);
}
this.scanning = false;
},
async runMigration(dryRun) {
this.migrating = true;
try {
var target = this.targetPath;
if (!target) target = '';
var data = await OpenFangAPI.post('/api/migrate', {
source: 'openclaw',
source_dir: this.sourcePath || (this.scanResult ? this.scanResult.path : ''),
target_dir: target,
dry_run: dryRun
});
this.migResult = data;
this.migStep = 'result';
} catch(e) {
this.migResult = { status: 'failed', error: e.message };
this.migStep = 'result';
}
this.migrating = false;
},
destroy() {
this.stopPeerPolling();
}
};
}

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crates/openfang-api/static/js/pages/skills.js Normal file
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// OpenFang Skills Page — OpenClaw/ClawHub ecosystem + local skills + MCP servers
'use strict';
function skillsPage() {
return {
tab: 'installed',
skills: [],
loading: true,
loadError: '',
// ClawHub state
clawhubSearch: '',
clawhubResults: [],
clawhubBrowseResults: [],
clawhubLoading: false,
clawhubError: '',
clawhubSort: 'trending',
clawhubNextCursor: null,
installingSlug: null,
installResult: null,
_searchTimer: null,
// Skill detail modal
skillDetail: null,
detailLoading: false,
// MCP servers
mcpServers: [],
mcpLoading: false,
// Category definitions from the OpenClaw ecosystem
categories: [
{ id: 'coding', name: 'Coding & IDEs' },
{ id: 'git', name: 'Git & GitHub' },
{ id: 'web', name: 'Web & Frontend' },
{ id: 'devops', name: 'DevOps & Cloud' },
{ id: 'browser', name: 'Browser & Automation' },
{ id: 'search', name: 'Search & Research' },
{ id: 'ai', name: 'AI & LLMs' },
{ id: 'data', name: 'Data & Analytics' },
{ id: 'productivity', name: 'Productivity' },
{ id: 'communication', name: 'Communication' },
{ id: 'media', name: 'Media & Streaming' },
{ id: 'notes', name: 'Notes & PKM' },
{ id: 'security', name: 'Security' },
{ id: 'cli', name: 'CLI Utilities' },
{ id: 'marketing', name: 'Marketing & Sales' },
{ id: 'finance', name: 'Finance' },
{ id: 'smart-home', name: 'Smart Home & IoT' },
{ id: 'docs', name: 'PDF & Documents' },
],
runtimeBadge: function(rt) {
var r = (rt || '').toLowerCase();
if (r === 'python' || r === 'py') return { text: 'PY', cls: 'runtime-badge-py' };
if (r === 'node' || r === 'nodejs' || r === 'js' || r === 'javascript') return { text: 'JS', cls: 'runtime-badge-js' };
if (r === 'wasm' || r === 'webassembly') return { text: 'WASM', cls: 'runtime-badge-wasm' };
if (r === 'prompt_only' || r === 'prompt' || r === 'promptonly') return { text: 'PROMPT', cls: 'runtime-badge-prompt' };
return { text: r.toUpperCase().substring(0, 4), cls: 'runtime-badge-prompt' };
},
sourceBadge: function(source) {
if (!source) return { text: 'Local', cls: 'badge-dim' };
switch (source.type) {
case 'clawhub': return { text: 'ClawHub', cls: 'badge-info' };
case 'openclaw': return { text: 'OpenClaw', cls: 'badge-info' };
case 'bundled': return { text: 'Built-in', cls: 'badge-success' };
default: return { text: 'Local', cls: 'badge-dim' };
}
},
formatDownloads: function(n) {
if (!n) return '0';
if (n >= 1000000) return (n / 1000000).toFixed(1) + 'M';
if (n >= 1000) return (n / 1000).toFixed(1) + 'K';
return n.toString();
},
async loadSkills() {
this.loading = true;
this.loadError = '';
try {
var data = await OpenFangAPI.get('/api/skills');
this.skills = (data.skills || []).map(function(s) {
return {
name: s.name,
description: s.description || '',
version: s.version || '',
author: s.author || '',
runtime: s.runtime || 'unknown',
tools_count: s.tools_count || 0,
tags: s.tags || [],
enabled: s.enabled !== false,
source: s.source || { type: 'local' },
has_prompt_context: !!s.has_prompt_context
};
});
} catch(e) {
this.skills = [];
this.loadError = e.message || 'Could not load skills.';
}
this.loading = false;
},
async loadData() {
await this.loadSkills();
},
// Debounced search — fires 350ms after user stops typing
onSearchInput() {
if (this._searchTimer) clearTimeout(this._searchTimer);
var q = this.clawhubSearch.trim();
if (!q) {
this.clawhubResults = [];
this.clawhubError = '';
return;
}
var self = this;
this._searchTimer = setTimeout(function() { self.searchClawHub(); }, 350);
},
// ClawHub search
async searchClawHub() {
if (!this.clawhubSearch.trim()) {
this.clawhubResults = [];
return;
}
this.clawhubLoading = true;
this.clawhubError = '';
try {
var data = await OpenFangAPI.get('/api/clawhub/search?q=' + encodeURIComponent(this.clawhubSearch.trim()) + '&limit=20');
this.clawhubResults = data.items || [];
if (data.error) this.clawhubError = data.error;
} catch(e) {
this.clawhubResults = [];
this.clawhubError = e.message || 'Search failed';
}
this.clawhubLoading = false;
},
// Clear search and go back to browse
clearSearch() {
this.clawhubSearch = '';
this.clawhubResults = [];
this.clawhubError = '';
if (this._searchTimer) clearTimeout(this._searchTimer);
},
// ClawHub browse by sort
async browseClawHub(sort) {
this.clawhubSort = sort || 'trending';
this.clawhubLoading = true;
this.clawhubError = '';
this.clawhubNextCursor = null;
try {
var data = await OpenFangAPI.get('/api/clawhub/browse?sort=' + this.clawhubSort + '&limit=20');
this.clawhubBrowseResults = data.items || [];
this.clawhubNextCursor = data.next_cursor || null;
if (data.error) this.clawhubError = data.error;
} catch(e) {
this.clawhubBrowseResults = [];
this.clawhubError = e.message || 'Browse failed';
}
this.clawhubLoading = false;
},
// ClawHub load more results
async loadMoreClawHub() {
if (!this.clawhubNextCursor || this.clawhubLoading) return;
this.clawhubLoading = true;
try {
var data = await OpenFangAPI.get('/api/clawhub/browse?sort=' + this.clawhubSort + '&limit=20&cursor=' + encodeURIComponent(this.clawhubNextCursor));
this.clawhubBrowseResults = this.clawhubBrowseResults.concat(data.items || []);
this.clawhubNextCursor = data.next_cursor || null;
} catch(e) {
// silently fail on load more
}
this.clawhubLoading = false;
},
// Show skill detail
async showSkillDetail(slug) {
this.detailLoading = true;
this.skillDetail = null;
this.installResult = null;
try {
var data = await OpenFangAPI.get('/api/clawhub/skill/' + encodeURIComponent(slug));
this.skillDetail = data;
} catch(e) {
OpenFangToast.error('Failed to load skill details');
}
this.detailLoading = false;
},
closeDetail() {
this.skillDetail = null;
this.installResult = null;
},
// Install from ClawHub
async installFromClawHub(slug) {
this.installingSlug = slug;
this.installResult = null;
try {
var data = await OpenFangAPI.post('/api/clawhub/install', { slug: slug });
this.installResult = data;
if (data.warnings && data.warnings.length > 0) {
OpenFangToast.success('Skill "' + data.name + '" installed with ' + data.warnings.length + ' warning(s)');
} else {
OpenFangToast.success('Skill "' + data.name + '" installed successfully');
}
// Update installed state in detail modal if open
if (this.skillDetail && this.skillDetail.slug === slug) {
this.skillDetail.installed = true;
}
await this.loadSkills();
} catch(e) {
var msg = e.message || 'Install failed';
if (msg.includes('already_installed')) {
OpenFangToast.error('Skill is already installed');
} else if (msg.includes('SecurityBlocked')) {
OpenFangToast.error('Skill blocked by security scan');
} else {
OpenFangToast.error('Install failed: ' + msg);
}
}
this.installingSlug = null;
},
// Uninstall
uninstallSkill: function(name) {
var self = this;
OpenFangToast.confirm('Uninstall Skill', 'Uninstall skill "' + name + '"? This cannot be undone.', async function() {
try {
await OpenFangAPI.post('/api/skills/uninstall', { name: name });
OpenFangToast.success('Skill "' + name + '" uninstalled');
await self.loadSkills();
} catch(e) {
OpenFangToast.error('Failed to uninstall skill: ' + e.message);
}
});
},
// Create prompt-only skill
async createDemoSkill(skill) {
try {
await OpenFangAPI.post('/api/skills/create', {
name: skill.name,
description: skill.description,
runtime: 'prompt_only',
prompt_context: skill.prompt_context || skill.description
});
OpenFangToast.success('Skill "' + skill.name + '" created');
this.tab = 'installed';
await this.loadSkills();
} catch(e) {
OpenFangToast.error('Failed to create skill: ' + e.message);
}
},
// Load MCP servers
async loadMcpServers() {
this.mcpLoading = true;
try {
var data = await OpenFangAPI.get('/api/mcp/servers');
this.mcpServers = data;
} catch(e) {
this.mcpServers = { configured: [], connected: [], total_configured: 0, total_connected: 0 };
}
this.mcpLoading = false;
},
// Category search on ClawHub
searchCategory: function(cat) {
this.clawhubSearch = cat.name;
this.searchClawHub();
},
// Quick start skills (prompt-only, zero deps)
quickStartSkills: [
{ name: 'code-review-guide', description: 'Adds code review best practices and checklist to agent context.', prompt_context: 'You are an expert code reviewer. When reviewing code:\n1. Check for bugs and logic errors\n2. Evaluate code style and readability\n3. Look for security vulnerabilities\n4. Suggest performance improvements\n5. Verify error handling\n6. Check test coverage' },
{ name: 'writing-style', description: 'Configurable writing style guide for content generation.', prompt_context: 'Follow these writing guidelines:\n- Use clear, concise language\n- Prefer active voice over passive voice\n- Keep paragraphs short (3-4 sentences)\n- Use bullet points for lists\n- Maintain consistent tone throughout' },
{ name: 'api-design', description: 'REST API design patterns and conventions.', prompt_context: 'When designing REST APIs:\n- Use nouns for resources, not verbs\n- Use HTTP methods correctly (GET, POST, PUT, DELETE)\n- Return appropriate status codes\n- Use pagination for list endpoints\n- Version your API\n- Document all endpoints' },
{ name: 'security-checklist', description: 'OWASP-aligned security review checklist.', prompt_context: 'Security review checklist (OWASP aligned):\n- Input validation on all user inputs\n- Output encoding to prevent XSS\n- Parameterized queries to prevent SQL injection\n- Authentication and session management\n- Access control checks\n- CSRF protection\n- Security headers\n- Error handling without information leakage' },
],
// Check if skill is installed by slug
isSkillInstalled: function(slug) {
return this.skills.some(function(s) {
return s.source && s.source.type === 'clawhub' && s.source.slug === slug;
});
},
// Check if skill is installed by name
isSkillInstalledByName: function(name) {
return this.skills.some(function(s) { return s.name === name; });
},
};
}

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crates/openfang-api/static/js/pages/usage.js Normal file
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// OpenFang Analytics Page — Full usage analytics with per-model and per-agent breakdowns
// Includes Cost Dashboard with donut chart, bar chart, projections, and provider breakdown.
'use strict';
function analyticsPage() {
return {
tab: 'summary',
summary: {},
byModel: [],
byAgent: [],
loading: true,
loadError: '',
// Cost tab state
dailyCosts: [],
todayCost: 0,
firstEventDate: null,
// Chart colors for providers (stable palette)
_chartColors: [
'#FF5C00', '#3B82F6', '#10B981', '#F59E0B', '#8B5CF6',
'#EC4899', '#06B6D4', '#EF4444', '#84CC16', '#F97316',
'#6366F1', '#14B8A6', '#E11D48', '#A855F7', '#22D3EE'
],
async loadUsage() {
this.loading = true;
this.loadError = '';
try {
await Promise.all([
this.loadSummary(),
this.loadByModel(),
this.loadByAgent(),
this.loadDailyCosts()
]);
} catch(e) {
this.loadError = e.message || 'Could not load usage data.';
}
this.loading = false;
},
async loadData() { return this.loadUsage(); },
async loadSummary() {
try {
this.summary = await OpenFangAPI.get('/api/usage/summary');
} catch(e) {
this.summary = { total_input_tokens: 0, total_output_tokens: 0, total_cost_usd: 0, call_count: 0, total_tool_calls: 0 };
throw e;
}
},
async loadByModel() {
try {
var data = await OpenFangAPI.get('/api/usage/by-model');
this.byModel = data.models || [];
} catch(e) { this.byModel = []; }
},
async loadByAgent() {
try {
var data = await OpenFangAPI.get('/api/usage');
this.byAgent = data.agents || [];
} catch(e) { this.byAgent = []; }
},
async loadDailyCosts() {
try {
var data = await OpenFangAPI.get('/api/usage/daily');
this.dailyCosts = data.days || [];
this.todayCost = data.today_cost_usd || 0;
this.firstEventDate = data.first_event_date || null;
} catch(e) {
this.dailyCosts = [];
this.todayCost = 0;
this.firstEventDate = null;
}
},
formatTokens(n) {
if (!n) return '0';
if (n >= 1000000) return (n / 1000000).toFixed(2) + 'M';
if (n >= 1000) return (n / 1000).toFixed(1) + 'K';
return String(n);
},
formatCost(c) {
if (!c) return '$0.00';
if (c < 0.01) return '$' + c.toFixed(4);
return '$' + c.toFixed(2);
},
maxTokens() {
var max = 0;
this.byModel.forEach(function(m) {
var t = (m.total_input_tokens || 0) + (m.total_output_tokens || 0);
if (t > max) max = t;
});
return max || 1;
},
barWidth(m) {
var t = (m.total_input_tokens || 0) + (m.total_output_tokens || 0);
return Math.max(2, Math.round((t / this.maxTokens()) * 100)) + '%';
},
// ── Cost tab helpers ──
avgCostPerMessage() {
var count = this.summary.call_count || 0;
if (count === 0) return 0;
return (this.summary.total_cost_usd || 0) / count;
},
projectedMonthlyCost() {
if (!this.firstEventDate || !this.summary.total_cost_usd) return 0;
var first = new Date(this.firstEventDate);
var now = new Date();
var diffMs = now.getTime() - first.getTime();
var diffDays = diffMs / (1000 * 60 * 60 * 24);
if (diffDays < 1) diffDays = 1;
return (this.summary.total_cost_usd / diffDays) * 30;
},
// ── Provider aggregation from byModel data ──
costByProvider() {
var providerMap = {};
var self = this;
this.byModel.forEach(function(m) {
var provider = self._extractProvider(m.model);
if (!providerMap[provider]) {
providerMap[provider] = { provider: provider, cost: 0, tokens: 0, calls: 0 };
}
providerMap[provider].cost += (m.total_cost_usd || 0);
providerMap[provider].tokens += (m.total_input_tokens || 0) + (m.total_output_tokens || 0);
providerMap[provider].calls += (m.call_count || 0);
});
var result = [];
for (var key in providerMap) {
if (providerMap.hasOwnProperty(key)) {
result.push(providerMap[key]);
}
}
result.sort(function(a, b) { return b.cost - a.cost; });
return result;
},
_extractProvider(modelName) {
if (!modelName) return 'Unknown';
var lower = modelName.toLowerCase();
if (lower.indexOf('claude') !== -1 || lower.indexOf('haiku') !== -1 || lower.indexOf('sonnet') !== -1 || lower.indexOf('opus') !== -1) return 'Anthropic';
if (lower.indexOf('gemini') !== -1 || lower.indexOf('gemma') !== -1) return 'Google';
if (lower.indexOf('gpt') !== -1 || lower.indexOf('o1') !== -1 || lower.indexOf('o3') !== -1 || lower.indexOf('o4') !== -1) return 'OpenAI';
if (lower.indexOf('llama') !== -1 || lower.indexOf('mixtral') !== -1 || lower.indexOf('groq') !== -1) return 'Groq';
if (lower.indexOf('deepseek') !== -1) return 'DeepSeek';
if (lower.indexOf('mistral') !== -1) return 'Mistral';
if (lower.indexOf('command') !== -1 || lower.indexOf('cohere') !== -1) return 'Cohere';
if (lower.indexOf('grok') !== -1) return 'xAI';
if (lower.indexOf('jamba') !== -1) return 'AI21';
if (lower.indexOf('qwen') !== -1) return 'Together';
return 'Other';
},
// ── Donut chart (stroke-dasharray on circles) ──
donutSegments() {
var providers = this.costByProvider();
var total = 0;
var colors = this._chartColors;
providers.forEach(function(p) { total += p.cost; });
if (total === 0) return [];
var segments = [];
var offset = 0;
var circumference = 2 * Math.PI * 60; // r=60
for (var i = 0; i < providers.length; i++) {
var pct = providers[i].cost / total;
var dashLen = pct * circumference;
segments.push({
provider: providers[i].provider,
cost: providers[i].cost,
percent: Math.round(pct * 100),
color: colors[i % colors.length],
dasharray: dashLen + ' ' + (circumference - dashLen),
dashoffset: -offset,
circumference: circumference
});
offset += dashLen;
}
return segments;
},
// ── Bar chart (last 7 days) ──
barChartData() {
var days = this.dailyCosts;
if (!days || days.length === 0) return [];
var maxCost = 0;
days.forEach(function(d) { if (d.cost_usd > maxCost) maxCost = d.cost_usd; });
if (maxCost === 0) maxCost = 1;
var dayNames = ['Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat'];
var result = [];
for (var i = 0; i < days.length; i++) {
var d = new Date(days[i].date + 'T12:00:00');
var dayName = dayNames[d.getDay()] || '?';
var heightPct = Math.max(2, Math.round((days[i].cost_usd / maxCost) * 120));
result.push({
date: days[i].date,
dayName: dayName,
cost: days[i].cost_usd,
tokens: days[i].tokens,
calls: days[i].calls,
barHeight: heightPct
});
}
return result;
},
// ── Cost by model table (sorted by cost descending) ──
costByModelSorted() {
var models = this.byModel.slice();
models.sort(function(a, b) { return (b.total_cost_usd || 0) - (a.total_cost_usd || 0); });
return models;
},
maxModelCost() {
var max = 0;
this.byModel.forEach(function(m) {
if ((m.total_cost_usd || 0) > max) max = m.total_cost_usd;
});
return max || 1;
},
costBarWidth(m) {
return Math.max(2, Math.round(((m.total_cost_usd || 0) / this.maxModelCost()) * 100)) + '%';
},
modelTier(modelName) {
if (!modelName) return 'unknown';
var lower = modelName.toLowerCase();
if (lower.indexOf('opus') !== -1 || lower.indexOf('o1') !== -1 || lower.indexOf('o3') !== -1 || lower.indexOf('deepseek-r1') !== -1) return 'frontier';
if (lower.indexOf('sonnet') !== -1 || lower.indexOf('gpt-4') !== -1 || lower.indexOf('gemini-2.5') !== -1 || lower.indexOf('gemini-1.5-pro') !== -1) return 'smart';
if (lower.indexOf('haiku') !== -1 || lower.indexOf('gpt-3.5') !== -1 || lower.indexOf('flash') !== -1 || lower.indexOf('mixtral') !== -1) return 'balanced';
if (lower.indexOf('llama') !== -1 || lower.indexOf('groq') !== -1 || lower.indexOf('gemma') !== -1) return 'fast';
return 'balanced';
}
};
}

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crates/openfang-api/static/js/pages/wizard.js Normal file
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// OpenFang Setup Wizard — First-run guided setup (Provider + Agent + Channel)
'use strict';
function wizardPage() {
return {
step: 1,
totalSteps: 6,
loading: false,
error: '',
// Step 2: Provider setup
providers: [],
selectedProvider: '',
apiKeyInput: '',
testingProvider: false,
testResult: null,
savingKey: false,
keySaved: false,
// Step 3: Agent creation
templates: [
{
id: 'assistant',
name: 'General Assistant',
description: 'A versatile helper for everyday tasks, answering questions, and providing recommendations.',
icon: 'GA',
category: 'General',
provider: 'deepseek',
model: 'deepseek-chat',
profile: 'balanced',
system_prompt: 'You are a helpful, friendly assistant. Provide clear, accurate, and concise responses. Ask clarifying questions when needed.'
},
{
id: 'coder',
name: 'Code Helper',
description: 'A programming-focused agent that writes, reviews, and debugs code across multiple languages.',
icon: 'CH',
category: 'Development',
provider: 'deepseek',
model: 'deepseek-chat',
profile: 'precise',
system_prompt: 'You are an expert programmer. Help users write clean, efficient code. Explain your reasoning. Follow best practices and conventions for the language being used.'
},
{
id: 'researcher',
name: 'Researcher',
description: 'An analytical agent that breaks down complex topics, synthesizes information, and provides cited summaries.',
icon: 'RS',
category: 'Research',
provider: 'gemini',
model: 'gemini-2.5-flash',
profile: 'balanced',
system_prompt: 'You are a research analyst. Break down complex topics into clear explanations. Provide structured analysis with key findings. Cite sources when available.'
},
{
id: 'writer',
name: 'Writer',
description: 'A creative writing agent that helps with drafting, editing, and improving written content of all kinds.',
icon: 'WR',
category: 'Writing',
provider: 'deepseek',
model: 'deepseek-chat',
profile: 'creative',
system_prompt: 'You are a skilled writer and editor. Help users create polished content. Adapt your tone and style to match the intended audience. Offer constructive suggestions for improvement.'
},
{
id: 'data-analyst',
name: 'Data Analyst',
description: 'A data-focused agent that helps analyze datasets, create queries, and interpret statistical results.',
icon: 'DA',
category: 'Development',
provider: 'gemini',
model: 'gemini-2.5-flash',
profile: 'precise',
system_prompt: 'You are a data analysis expert. Help users understand their data, write SQL/Python queries, and interpret results. Present findings clearly with actionable insights.'
},
{
id: 'devops',
name: 'DevOps Engineer',
description: 'A systems-focused agent for CI/CD, infrastructure, Docker, and deployment troubleshooting.',
icon: 'DO',
category: 'Development',
provider: 'deepseek',
model: 'deepseek-chat',
profile: 'precise',
system_prompt: 'You are a DevOps engineer. Help with CI/CD pipelines, Docker, Kubernetes, infrastructure as code, and deployment. Prioritize reliability and security.'
},
{
id: 'support',
name: 'Customer Support',
description: 'A professional, empathetic agent for handling customer inquiries and resolving issues.',
icon: 'CS',
category: 'Business',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'balanced',
system_prompt: 'You are a professional customer support representative. Be empathetic, patient, and solution-oriented. Acknowledge concerns before offering solutions. Escalate complex issues appropriately.'
},
{
id: 'tutor',
name: 'Tutor',
description: 'A patient educational agent that explains concepts step-by-step and adapts to the learner\'s level.',
icon: 'TU',
category: 'General',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'balanced',
system_prompt: 'You are a patient and encouraging tutor. Explain concepts step by step, starting from fundamentals. Use analogies and examples. Check understanding before moving on. Adapt to the learner\'s pace.'
},
{
id: 'api-designer',
name: 'API Designer',
description: 'An agent specialized in RESTful API design, OpenAPI specs, and integration architecture.',
icon: 'AD',
category: 'Development',
provider: 'deepseek',
model: 'deepseek-chat',
profile: 'precise',
system_prompt: 'You are an API design expert. Help users design clean, consistent RESTful APIs following best practices. Cover endpoint naming, request/response schemas, error handling, and versioning.'
},
{
id: 'meeting-notes',
name: 'Meeting Notes',
description: 'Summarizes meeting transcripts into structured notes with action items and key decisions.',
icon: 'MN',
category: 'Business',
provider: 'groq',
model: 'llama-3.3-70b-versatile',
profile: 'precise',
system_prompt: 'You are a meeting summarizer. When given a meeting transcript or notes, produce a structured summary with: key decisions, action items (with owners), discussion highlights, and follow-up questions.'
}
],
selectedTemplate: 0,
agentName: 'my-assistant',
creatingAgent: false,
createdAgent: null,
// Step 3: Category filtering
templateCategory: 'All',
get templateCategories() {
var cats = { 'All': true };
this.templates.forEach(function(t) { if (t.category) cats[t.category] = true; });
return Object.keys(cats);
},
get filteredTemplates() {
var cat = this.templateCategory;
if (cat === 'All') return this.templates;
return this.templates.filter(function(t) { return t.category === cat; });
},
// Step 3: Profile/tool descriptions
profileDescriptions: {
minimal: { label: 'Minimal', desc: 'Read-only file access' },
coding: { label: 'Coding', desc: 'Files + shell + web fetch' },
research: { label: 'Research', desc: 'Web search + file read/write' },
balanced: { label: 'Balanced', desc: 'General-purpose tool set' },
precise: { label: 'Precise', desc: 'Focused tool set for accuracy' },
creative: { label: 'Creative', desc: 'Full tools with creative emphasis' },
full: { label: 'Full', desc: 'All 35+ tools' }
},
profileInfo: function(name) { return this.profileDescriptions[name] || { label: name, desc: '' }; },
// Step 4: Try It chat
tryItMessages: [],
tryItInput: '',
tryItSending: false,
suggestedMessages: {
'General': ['What can you help me with?', 'Tell me a fun fact', 'Summarize the latest AI news'],
'Development': ['Write a Python hello world', 'Explain async/await', 'Review this code snippet'],
'Research': ['Explain quantum computing simply', 'Compare React vs Vue', 'What are the latest trends in AI?'],
'Writing': ['Help me write a professional email', 'Improve this paragraph', 'Write a blog intro about AI'],
'Business': ['Draft a meeting agenda', 'How do I handle a complaint?', 'Create a project status update']
},
get currentSuggestions() {
var tpl = this.templates[this.selectedTemplate];
var cat = tpl ? tpl.category : 'General';
return this.suggestedMessages[cat] || this.suggestedMessages['General'];
},
async sendTryItMessage(text) {
if (!text || !text.trim() || !this.createdAgent || this.tryItSending) return;
text = text.trim();
this.tryItInput = '';
this.tryItMessages.push({ role: 'user', text: text });
this.tryItSending = true;
try {
var res = await OpenFangAPI.post('/api/agents/' + this.createdAgent.id + '/message', { message: text });
this.tryItMessages.push({ role: 'agent', text: res.response || '(no response)' });
localStorage.setItem('of-first-msg', 'true');
} catch(e) {
this.tryItMessages.push({ role: 'agent', text: 'Error: ' + (e.message || 'Could not reach agent') });
}
this.tryItSending = false;
},
// Step 5: Channel setup (optional)
channelType: '',
channelOptions: [
{
name: 'telegram',
display_name: 'Telegram',
icon: 'TG',
description: 'Connect your agent to a Telegram bot for messaging.',
token_label: 'Bot Token',
token_placeholder: '123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11',
token_env: 'TELEGRAM_BOT_TOKEN',
help: 'Create a bot via @BotFather on Telegram to get your token.'
},
{
name: 'discord',
display_name: 'Discord',
icon: 'DC',
description: 'Connect your agent to a Discord server via bot token.',
token_label: 'Bot Token',
token_placeholder: 'MTIz...abc',
token_env: 'DISCORD_BOT_TOKEN',
help: 'Create a Discord application at discord.com/developers and add a bot.'
},
{
name: 'slack',
display_name: 'Slack',
icon: 'SL',
description: 'Connect your agent to a Slack workspace.',
token_label: 'Bot Token',
token_placeholder: 'xoxb-...',
token_env: 'SLACK_BOT_TOKEN',
help: 'Create a Slack app at api.slack.com/apps and install it to your workspace.'
}
],
channelToken: '',
configuringChannel: false,
channelConfigured: false,
// Step 5: Summary
setupSummary: {
provider: '',
agent: '',
channel: ''
},
// ── Lifecycle ──
async loadData() {
this.loading = true;
this.error = '';
try {
await this.loadProviders();
} catch(e) {
this.error = e.message || 'Could not load setup data.';
}
this.loading = false;
},
// ── Navigation ──
nextStep() {
if (this.step === 3 && !this.createdAgent) {
// Skip "Try It" if no agent was created
this.step = 5;
} else if (this.step < this.totalSteps) {
this.step++;
}
},
prevStep() {
if (this.step === 5 && !this.createdAgent) {
// Skip back past "Try It" if no agent was created
this.step = 3;
} else if (this.step > 1) {
this.step--;
}
},
goToStep(n) {
if (n >= 1 && n <= this.totalSteps) {
if (n === 4 && !this.createdAgent) return; // Can't go to Try It without agent
this.step = n;
}
},
stepLabel(n) {
var labels = ['Welcome', 'Provider', 'Agent', 'Try It', 'Channel', 'Done'];
return labels[n - 1] || '';
},
get canGoNext() {
if (this.step === 2) return this.keySaved || this.hasConfiguredProvider;
if (this.step === 3) return this.agentName.trim().length > 0;
return true;
},
get hasConfiguredProvider() {
var self = this;
return this.providers.some(function(p) {
return p.auth_status === 'configured';
});
},
// ── Step 2: Providers ──
async loadProviders() {
try {
var data = await OpenFangAPI.get('/api/providers');
this.providers = data.providers || [];
// Pre-select first unconfigured provider, or first one
var unconfigured = this.providers.filter(function(p) {
return p.auth_status !== 'configured' && p.api_key_env;
});
if (unconfigured.length > 0) {
this.selectedProvider = unconfigured[0].id;
} else if (this.providers.length > 0) {
this.selectedProvider = this.providers[0].id;
}
} catch(e) { this.providers = []; }
},
get selectedProviderObj() {
var self = this;
var match = this.providers.filter(function(p) { return p.id === self.selectedProvider; });
return match.length > 0 ? match[0] : null;
},
get popularProviders() {
var popular = ['anthropic', 'openai', 'gemini', 'groq', 'deepseek', 'openrouter'];
return this.providers.filter(function(p) {
return popular.indexOf(p.id) >= 0;
}).sort(function(a, b) {
return popular.indexOf(a.id) - popular.indexOf(b.id);
});
},
get otherProviders() {
var popular = ['anthropic', 'openai', 'gemini', 'groq', 'deepseek', 'openrouter'];
return this.providers.filter(function(p) {
return popular.indexOf(p.id) < 0;
});
},
selectProvider(id) {
this.selectedProvider = id;
this.apiKeyInput = '';
this.testResult = null;
this.keySaved = false;
},
providerHelp: function(id) {
var help = {
anthropic: { url: 'https://console.anthropic.com/settings/keys', text: 'Get your key from the Anthropic Console' },
openai: { url: 'https://platform.openai.com/api-keys', text: 'Get your key from the OpenAI Platform' },
gemini: { url: 'https://aistudio.google.com/apikey', text: 'Get your key from Google AI Studio' },
groq: { url: 'https://console.groq.com/keys', text: 'Get your key from the Groq Console (free tier available)' },
deepseek: { url: 'https://platform.deepseek.com/api_keys', text: 'Get your key from the DeepSeek Platform (very affordable)' },
openrouter: { url: 'https://openrouter.ai/keys', text: 'Get your key from OpenRouter (access 100+ models with one key)' },
mistral: { url: 'https://console.mistral.ai/api-keys', text: 'Get your key from the Mistral Console' },
together: { url: 'https://api.together.xyz/settings/api-keys', text: 'Get your key from Together AI' },
fireworks: { url: 'https://fireworks.ai/account/api-keys', text: 'Get your key from Fireworks AI' },
perplexity: { url: 'https://www.perplexity.ai/settings/api', text: 'Get your key from Perplexity Settings' },
cohere: { url: 'https://dashboard.cohere.com/api-keys', text: 'Get your key from the Cohere Dashboard' },
xai: { url: 'https://console.x.ai/', text: 'Get your key from the xAI Console' }
};
return help[id] || null;
},
providerIsConfigured(p) {
return p && p.auth_status === 'configured';
},
async saveKey() {
var provider = this.selectedProviderObj;
if (!provider) return;
var key = this.apiKeyInput.trim();
if (!key) {
OpenFangToast.error('Please enter an API key');
return;
}
this.savingKey = true;
try {
await OpenFangAPI.post('/api/providers/' + encodeURIComponent(provider.id) + '/key', { key: key });
this.apiKeyInput = '';
this.keySaved = true;
this.setupSummary.provider = provider.display_name;
OpenFangToast.success('API key saved for ' + provider.display_name);
await this.loadProviders();
// Auto-test after saving
await this.testKey();
} catch(e) {
OpenFangToast.error('Failed to save key: ' + e.message);
}
this.savingKey = false;
},
async testKey() {
var provider = this.selectedProviderObj;
if (!provider) return;
this.testingProvider = true;
this.testResult = null;
try {
var result = await OpenFangAPI.post('/api/providers/' + encodeURIComponent(provider.id) + '/test', {});
this.testResult = result;
if (result.status === 'ok') {
OpenFangToast.success(provider.display_name + ' connected (' + (result.latency_ms || '?') + 'ms)');
} else {
OpenFangToast.error(provider.display_name + ': ' + (result.error || 'Connection failed'));
}
} catch(e) {
this.testResult = { status: 'error', error: e.message };
OpenFangToast.error('Test failed: ' + e.message);
}
this.testingProvider = false;
},
// ── Step 3: Agent creation ──
selectTemplate(index) {
this.selectedTemplate = index;
var tpl = this.templates[index];
if (tpl) {
this.agentName = tpl.name.toLowerCase().replace(/\s+/g, '-');
}
},
async createAgent() {
var tpl = this.templates[this.selectedTemplate];
if (!tpl) return;
var name = this.agentName.trim();
if (!name) {
OpenFangToast.error('Please enter a name for your agent');
return;
}
// Use the provider the user just configured, or the template default
var provider = tpl.provider;
var model = tpl.model;
if (this.selectedProviderObj && this.providerIsConfigured(this.selectedProviderObj)) {
provider = this.selectedProviderObj.id;
// Use a sensible default model for the provider
model = this.defaultModelForProvider(provider) || tpl.model;
}
var toml = '[agent]\n';
toml += 'name = "' + name.replace(/"/g, '\\"') + '"\n';
toml += 'description = "' + tpl.description.replace(/"/g, '\\"') + '"\n';
toml += 'profile = "' + tpl.profile + '"\n\n';
toml += '[model]\nprovider = "' + provider + '"\n';
toml += 'name = "' + model + '"\n\n';
toml += '[prompt]\nsystem = """\n' + tpl.system_prompt + '\n"""\n';
this.creatingAgent = true;
try {
var res = await OpenFangAPI.post('/api/agents', { manifest_toml: toml });
if (res.agent_id) {
this.createdAgent = { id: res.agent_id, name: res.name || name };
this.setupSummary.agent = res.name || name;
OpenFangToast.success('Agent "' + (res.name || name) + '" created');
await Alpine.store('app').refreshAgents();
} else {
OpenFangToast.error('Failed: ' + (res.error || 'Unknown error'));
}
} catch(e) {
OpenFangToast.error('Failed to create agent: ' + e.message);
}
this.creatingAgent = false;
},
defaultModelForProvider(providerId) {
var defaults = {
anthropic: 'claude-sonnet-4-20250514',
openai: 'gpt-4o',
gemini: 'gemini-2.5-flash',
groq: 'llama-3.3-70b-versatile',
deepseek: 'deepseek-chat',
openrouter: 'openrouter/auto',
mistral: 'mistral-large-latest',
together: 'meta-llama/Llama-3-70b-chat-hf',
fireworks: 'accounts/fireworks/models/llama-v3p1-70b-instruct',
perplexity: 'llama-3.1-sonar-large-128k-online',
cohere: 'command-r-plus',
xai: 'grok-2'
};
return defaults[providerId] || '';
},
// ── Step 5: Channel setup ──
selectChannel(name) {
if (this.channelType === name) {
this.channelType = '';
this.channelToken = '';
} else {
this.channelType = name;
this.channelToken = '';
}
},
get selectedChannelObj() {
var self = this;
var match = this.channelOptions.filter(function(ch) { return ch.name === self.channelType; });
return match.length > 0 ? match[0] : null;
},
async configureChannel() {
var ch = this.selectedChannelObj;
if (!ch) return;
var token = this.channelToken.trim();
if (!token) {
OpenFangToast.error('Please enter the ' + ch.token_label);
return;
}
this.configuringChannel = true;
try {
var fields = {};
fields[ch.token_env.toLowerCase()] = token;
fields.token = token;
await OpenFangAPI.post('/api/channels/' + ch.name + '/configure', { fields: fields });
this.channelConfigured = true;
this.setupSummary.channel = ch.display_name;
OpenFangToast.success(ch.display_name + ' configured and activated.');
} catch(e) {
OpenFangToast.error('Failed: ' + (e.message || 'Unknown error'));
}
this.configuringChannel = false;
},
// ── Step 6: Finish ──
finish() {
localStorage.setItem('openfang-onboarded', 'true');
Alpine.store('app').showOnboarding = false;
// Navigate to agents with chat if an agent was created, otherwise overview
if (this.createdAgent) {
var agent = this.createdAgent;
Alpine.store('app').pendingAgent = { id: agent.id, name: agent.name, model_provider: '?', model_name: '?' };
window.location.hash = 'agents';
} else {
window.location.hash = 'overview';
}
},
finishAndDismiss() {
localStorage.setItem('openfang-onboarded', 'true');
Alpine.store('app').showOnboarding = false;
window.location.hash = 'overview';
}
};
}

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// OpenFang Visual Workflow Builder — Drag-and-drop workflow designer
'use strict';
function workflowBuilder() {
return {
// -- Canvas state --
nodes: [],
connections: [],
selectedNode: null,
selectedConnection: null,
dragging: null,
dragOffset: { x: 0, y: 0 },
connecting: null, // { fromId, fromPort }
connectPreview: null, // { x, y } mouse position during connect drag
canvasOffset: { x: 0, y: 0 },
canvasDragging: false,
canvasDragStart: { x: 0, y: 0 },
zoom: 1,
nextId: 1,
workflowName: '',
workflowDescription: '',
showSaveModal: false,
showNodeEditor: false,
showTomlPreview: false,
tomlOutput: '',
agents: [],
_canvasEl: null,
// Node types with their configs
nodeTypes: [
{ type: 'agent', label: 'Agent Step', color: '#6366f1', icon: 'A', ports: { in: 1, out: 1 } },
{ type: 'parallel', label: 'Parallel Fan-out', color: '#f59e0b', icon: 'P', ports: { in: 1, out: 3 } },
{ type: 'condition', label: 'Condition', color: '#10b981', icon: '?', ports: { in: 1, out: 2 } },
{ type: 'loop', label: 'Loop', color: '#ef4444', icon: 'L', ports: { in: 1, out: 1 } },
{ type: 'collect', label: 'Collect', color: '#8b5cf6', icon: 'C', ports: { in: 3, out: 1 } },
{ type: 'start', label: 'Start', color: '#22c55e', icon: 'S', ports: { in: 0, out: 1 } },
{ type: 'end', label: 'End', color: '#ef4444', icon: 'E', ports: { in: 1, out: 0 } }
],
async init() {
var self = this;
// Load agents for the agent step dropdown
try {
var list = await OpenFangAPI.get('/api/agents');
self.agents = Array.isArray(list) ? list : [];
} catch(_) {
self.agents = [];
}
// Add default start node
self.addNode('start', 60, 200);
},
// ── Node Management ──────────────────────────────────
addNode: function(type, x, y) {
var def = null;
for (var i = 0; i < this.nodeTypes.length; i++) {
if (this.nodeTypes[i].type === type) { def = this.nodeTypes[i]; break; }
}
if (!def) return;
var node = {
id: 'node-' + this.nextId++,
type: type,
label: def.label,
color: def.color,
icon: def.icon,
x: x || 200,
y: y || 200,
width: 180,
height: 70,
ports: { in: def.ports.in, out: def.ports.out },
config: {}
};
if (type === 'agent') {
node.config = { agent_name: '', prompt: '{{input}}', model: '' };
} else if (type === 'condition') {
node.config = { expression: '', true_label: 'Yes', false_label: 'No' };
} else if (type === 'loop') {
node.config = { max_iterations: 5, until: '' };
} else if (type === 'parallel') {
node.config = { fan_count: 3 };
} else if (type === 'collect') {
node.config = { strategy: 'all' };
}
this.nodes.push(node);
return node;
},
deleteNode: function(nodeId) {
this.connections = this.connections.filter(function(c) {
return c.from !== nodeId && c.to !== nodeId;
});
this.nodes = this.nodes.filter(function(n) { return n.id !== nodeId; });
if (this.selectedNode && this.selectedNode.id === nodeId) {
this.selectedNode = null;
this.showNodeEditor = false;
}
},
duplicateNode: function(node) {
var newNode = this.addNode(node.type, node.x + 30, node.y + 30);
if (newNode) {
newNode.config = JSON.parse(JSON.stringify(node.config));
newNode.label = node.label + ' copy';
}
},
getNode: function(id) {
for (var i = 0; i < this.nodes.length; i++) {
if (this.nodes[i].id === id) return this.nodes[i];
}
return null;
},
// ── Port Positions ───────────────────────────────────
getInputPortPos: function(node, portIndex) {
var total = node.ports.in;
var spacing = node.width / (total + 1);
return { x: node.x + spacing * (portIndex + 1), y: node.y };
},
getOutputPortPos: function(node, portIndex) {
var total = node.ports.out;
var spacing = node.width / (total + 1);
return { x: node.x + spacing * (portIndex + 1), y: node.y + node.height };
},
// ── Connection Management ────────────────────────────
startConnect: function(nodeId, portIndex, e) {
e.stopPropagation();
this.connecting = { fromId: nodeId, fromPort: portIndex };
var node = this.getNode(nodeId);
var pos = this.getOutputPortPos(node, portIndex);
this.connectPreview = { x: pos.x, y: pos.y };
},
endConnect: function(nodeId, portIndex, e) {
e.stopPropagation();
if (!this.connecting) return;
if (this.connecting.fromId === nodeId) {
this.connecting = null;
this.connectPreview = null;
return;
}
// Check for duplicate
var fromId = this.connecting.fromId;
var fromPort = this.connecting.fromPort;
var dup = false;
for (var i = 0; i < this.connections.length; i++) {
var c = this.connections[i];
if (c.from === fromId && c.fromPort === fromPort && c.to === nodeId && c.toPort === portIndex) {
dup = true;
break;
}
}
if (!dup) {
this.connections.push({
id: 'conn-' + this.nextId++,
from: fromId,
fromPort: fromPort,
to: nodeId,
toPort: portIndex
});
}
this.connecting = null;
this.connectPreview = null;
},
deleteConnection: function(connId) {
this.connections = this.connections.filter(function(c) { return c.id !== connId; });
this.selectedConnection = null;
},
// ── Drag Handling ────────────────────────────────────
onNodeMouseDown: function(node, e) {
e.stopPropagation();
this.selectedNode = node;
this.selectedConnection = null;
this.dragging = node.id;
var rect = this._getCanvasRect();
this.dragOffset = {
x: (e.clientX - rect.left) / this.zoom - this.canvasOffset.x - node.x,
y: (e.clientY - rect.top) / this.zoom - this.canvasOffset.y - node.y
};
},
onCanvasMouseDown: function(e) {
if (e.target.closest('.wf-node') || e.target.closest('.wf-port')) return;
this.selectedNode = null;
this.selectedConnection = null;
this.showNodeEditor = false;
// Start canvas pan
this.canvasDragging = true;
this.canvasDragStart = { x: e.clientX - this.canvasOffset.x * this.zoom, y: e.clientY - this.canvasOffset.y * this.zoom };
},
onCanvasMouseMove: function(e) {
var rect = this._getCanvasRect();
if (this.dragging) {
var node = this.getNode(this.dragging);
if (node) {
node.x = Math.max(0, (e.clientX - rect.left) / this.zoom - this.canvasOffset.x - this.dragOffset.x);
node.y = Math.max(0, (e.clientY - rect.top) / this.zoom - this.canvasOffset.y - this.dragOffset.y);
}
} else if (this.connecting) {
this.connectPreview = {
x: (e.clientX - rect.left) / this.zoom - this.canvasOffset.x,
y: (e.clientY - rect.top) / this.zoom - this.canvasOffset.y
};
} else if (this.canvasDragging) {
this.canvasOffset = {
x: (e.clientX - this.canvasDragStart.x) / this.zoom,
y: (e.clientY - this.canvasDragStart.y) / this.zoom
};
}
},
onCanvasMouseUp: function() {
this.dragging = null;
this.connecting = null;
this.connectPreview = null;
this.canvasDragging = false;
},
onCanvasWheel: function(e) {
e.preventDefault();
var delta = e.deltaY > 0 ? -0.05 : 0.05;
this.zoom = Math.max(0.3, Math.min(2, this.zoom + delta));
},
_getCanvasRect: function() {
if (!this._canvasEl) {
this._canvasEl = document.getElementById('wf-canvas');
}
return this._canvasEl ? this._canvasEl.getBoundingClientRect() : { left: 0, top: 0 };
},
// ── Connection Path ──────────────────────────────────
getConnectionPath: function(conn) {
var fromNode = this.getNode(conn.from);
var toNode = this.getNode(conn.to);
if (!fromNode || !toNode) return '';
var from = this.getOutputPortPos(fromNode, conn.fromPort);
var to = this.getInputPortPos(toNode, conn.toPort);
var dy = Math.abs(to.y - from.y);
var cp = Math.max(40, dy * 0.5);
return 'M ' + from.x + ' ' + from.y + ' C ' + from.x + ' ' + (from.y + cp) + ' ' + to.x + ' ' + (to.y - cp) + ' ' + to.x + ' ' + to.y;
},
getPreviewPath: function() {
if (!this.connecting || !this.connectPreview) return '';
var fromNode = this.getNode(this.connecting.fromId);
if (!fromNode) return '';
var from = this.getOutputPortPos(fromNode, this.connecting.fromPort);
var to = this.connectPreview;
var dy = Math.abs(to.y - from.y);
var cp = Math.max(40, dy * 0.5);
return 'M ' + from.x + ' ' + from.y + ' C ' + from.x + ' ' + (from.y + cp) + ' ' + to.x + ' ' + (to.y - cp) + ' ' + to.x + ' ' + to.y;
},
// ── Node editor ──────────────────────────────────────
editNode: function(node) {
this.selectedNode = node;
this.showNodeEditor = true;
},
// ── TOML Generation ──────────────────────────────────
generateToml: function() {
var self = this;
var lines = [];
lines.push('[workflow]');
lines.push('name = "' + (this.workflowName || 'untitled') + '"');
lines.push('description = "' + (this.workflowDescription || '') + '"');
lines.push('');
// Topological sort the nodes (skip start/end for step generation)
var stepNodes = this.nodes.filter(function(n) {
return n.type !== 'start' && n.type !== 'end';
});
for (var i = 0; i < stepNodes.length; i++) {
var node = stepNodes[i];
lines.push('[[workflow.steps]]');
lines.push('name = "' + (node.label || 'step-' + (i + 1)) + '"');
if (node.type === 'agent') {
lines.push('type = "agent"');
if (node.config.agent_name) lines.push('agent_name = "' + node.config.agent_name + '"');
lines.push('prompt = "' + (node.config.prompt || '{{input}}') + '"');
if (node.config.model) lines.push('model = "' + node.config.model + '"');
} else if (node.type === 'parallel') {
lines.push('type = "fan_out"');
lines.push('fan_count = ' + (node.config.fan_count || 3));
} else if (node.type === 'condition') {
lines.push('type = "conditional"');
lines.push('expression = "' + (node.config.expression || '') + '"');
} else if (node.type === 'loop') {
lines.push('type = "loop"');
lines.push('max_iterations = ' + (node.config.max_iterations || 5));
if (node.config.until) lines.push('until = "' + node.config.until + '"');
} else if (node.type === 'collect') {
lines.push('type = "collect"');
lines.push('strategy = "' + (node.config.strategy || 'all') + '"');
}
// Find what this node connects to
var outConns = self.connections.filter(function(c) { return c.from === node.id; });
if (outConns.length === 1) {
var target = self.getNode(outConns[0].to);
if (target && target.type !== 'end') {
lines.push('next = "' + target.label + '"');
}
} else if (outConns.length > 1 && node.type === 'condition') {
for (var j = 0; j < outConns.length; j++) {
var t2 = self.getNode(outConns[j].to);
if (t2 && t2.type !== 'end') {
var branchLabel = j === 0 ? 'true' : 'false';
lines.push('next_' + branchLabel + ' = "' + t2.label + '"');
}
}
} else if (outConns.length > 1 && node.type === 'parallel') {
var targets = [];
for (var k = 0; k < outConns.length; k++) {
var t3 = self.getNode(outConns[k].to);
if (t3 && t3.type !== 'end') targets.push('"' + t3.label + '"');
}
if (targets.length) lines.push('fan_targets = [' + targets.join(', ') + ']');
}
lines.push('');
}
this.tomlOutput = lines.join('\n');
this.showTomlPreview = true;
},
// ── Save Workflow ────────────────────────────────────
async saveWorkflow() {
var steps = [];
var stepNodes = this.nodes.filter(function(n) {
return n.type !== 'start' && n.type !== 'end';
});
for (var i = 0; i < stepNodes.length; i++) {
var node = stepNodes[i];
var step = {
name: node.label || 'step-' + (i + 1),
mode: node.type === 'parallel' ? 'fan_out' : node.type === 'loop' ? 'loop' : 'sequential'
};
if (node.type === 'agent') {
step.agent_name = node.config.agent_name || '';
step.prompt = node.config.prompt || '{{input}}';
}
steps.push(step);
}
try {
await OpenFangAPI.post('/api/workflows', {
name: this.workflowName || 'untitled',
description: this.workflowDescription || '',
steps: steps
});
OpenFangToast.success('Workflow saved!');
this.showSaveModal = false;
} catch(e) {
OpenFangToast.error('Failed to save: ' + e.message);
}
},
// ── Palette drop ─────────────────────────────────────
onPaletteDragStart: function(type, e) {
e.dataTransfer.setData('text/plain', type);
e.dataTransfer.effectAllowed = 'copy';
},
onCanvasDrop: function(e) {
e.preventDefault();
var type = e.dataTransfer.getData('text/plain');
if (!type) return;
var rect = this._getCanvasRect();
var x = (e.clientX - rect.left) / this.zoom - this.canvasOffset.x;
var y = (e.clientY - rect.top) / this.zoom - this.canvasOffset.y;
this.addNode(type, x - 90, y - 35);
},
onCanvasDragOver: function(e) {
e.preventDefault();
e.dataTransfer.dropEffect = 'copy';
},
// ── Auto Layout ──────────────────────────────────────
autoLayout: function() {
// Simple top-to-bottom layout
var y = 40;
var x = 200;
for (var i = 0; i < this.nodes.length; i++) {
this.nodes[i].x = x;
this.nodes[i].y = y;
y += 120;
}
},
// ── Clear ────────────────────────────────────────────
clearCanvas: function() {
this.nodes = [];
this.connections = [];
this.selectedNode = null;
this.nextId = 1;
this.addNode('start', 60, 200);
},
// ── Zoom controls ────────────────────────────────────
zoomIn: function() {
this.zoom = Math.min(2, this.zoom + 0.1);
},
zoomOut: function() {
this.zoom = Math.max(0.3, this.zoom - 0.1);
},
zoomReset: function() {
this.zoom = 1;
this.canvasOffset = { x: 0, y: 0 };
}
};
}

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// OpenFang Workflows Page — Workflow builder + run history
'use strict';
function workflowsPage() {
return {
// -- Workflows state --
workflows: [],
showCreateModal: false,
runModal: null,
runInput: '',
runResult: '',
running: false,
loading: true,
loadError: '',
newWf: { name: '', description: '', steps: [{ name: '', agent_name: '', mode: 'sequential', prompt: '{{input}}' }] },
// -- Workflows methods --
async loadWorkflows() {
this.loading = true;
this.loadError = '';
try {
this.workflows = await OpenFangAPI.get('/api/workflows');
} catch(e) {
this.workflows = [];
this.loadError = e.message || 'Could not load workflows.';
}
this.loading = false;
},
async loadData() { return this.loadWorkflows(); },
async createWorkflow() {
var steps = this.newWf.steps.map(function(s) {
return { name: s.name || 'step', agent_name: s.agent_name, mode: s.mode, prompt: s.prompt || '{{input}}' };
});
try {
var wfName = this.newWf.name;
await OpenFangAPI.post('/api/workflows', { name: wfName, description: this.newWf.description, steps: steps });
this.showCreateModal = false;
this.newWf = { name: '', description: '', steps: [{ name: '', agent_name: '', mode: 'sequential', prompt: '{{input}}' }] };
OpenFangToast.success('Workflow "' + wfName + '" created');
await this.loadWorkflows();
} catch(e) {
OpenFangToast.error('Failed to create workflow: ' + e.message);
}
},
showRunModal(wf) {
this.runModal = wf;
this.runInput = '';
this.runResult = '';
},
async executeWorkflow() {
if (!this.runModal) return;
this.running = true;
this.runResult = '';
try {
var res = await OpenFangAPI.post('/api/workflows/' + this.runModal.id + '/run', { input: this.runInput });
this.runResult = res.output || JSON.stringify(res, null, 2);
OpenFangToast.success('Workflow completed');
} catch(e) {
this.runResult = 'Error: ' + e.message;
OpenFangToast.error('Workflow failed: ' + e.message);
}
this.running = false;
},
async viewRuns(wf) {
try {
var runs = await OpenFangAPI.get('/api/workflows/' + wf.id + '/runs');
this.runResult = JSON.stringify(runs, null, 2);
this.runModal = wf;
} catch(e) {
OpenFangToast.error('Failed to load run history: ' + e.message);
}
}
};
}

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pre code.hljs{display:block;overflow-x:auto;padding:1em}code.hljs{padding:3px 5px}/*!
Theme: GitHub Dark
Description: Dark theme as seen on github.com
Author: github.com
Maintainer: @Hirse
Updated: 2021-05-15
Outdated base version: https://github.com/primer/github-syntax-dark
Current colors taken from GitHub's CSS
*/.hljs{color:#c9d1d9;background:#0d1117}.hljs-doctag,.hljs-keyword,.hljs-meta .hljs-keyword,.hljs-template-tag,.hljs-template-variable,.hljs-type,.hljs-variable.language_{color:#ff7b72}.hljs-title,.hljs-title.class_,.hljs-title.class_.inherited__,.hljs-title.function_{color:#d2a8ff}.hljs-attr,.hljs-attribute,.hljs-literal,.hljs-meta,.hljs-number,.hljs-operator,.hljs-selector-attr,.hljs-selector-class,.hljs-selector-id,.hljs-variable{color:#79c0ff}.hljs-meta .hljs-string,.hljs-regexp,.hljs-string{color:#a5d6ff}.hljs-built_in,.hljs-symbol{color:#ffa657}.hljs-code,.hljs-comment,.hljs-formula{color:#8b949e}.hljs-name,.hljs-quote,.hljs-selector-pseudo,.hljs-selector-tag{color:#7ee787}.hljs-subst{color:#c9d1d9}.hljs-section{color:#1f6feb;font-weight:700}.hljs-bullet{color:#f2cc60}.hljs-emphasis{color:#c9d1d9;font-style:italic}.hljs-strong{color:#c9d1d9;font-weight:700}.hljs-addition{color:#aff5b4;background-color:#033a16}.hljs-deletion{color:#ffdcd7;background-color:#67060c}

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//! Real HTTP integration tests for the OpenFang API.
//!
//! These tests boot a real kernel, start a real axum HTTP server on a random
//! port, and hit actual endpoints with reqwest. No mocking.
//!
//! Tests that require an LLM API call are gated behind GROQ_API_KEY.
//!
//! Run: cargo test -p openfang-api --test api_integration_test -- --nocapture
use axum::Router;
use openfang_api::middleware;
use openfang_api::routes::{self, AppState};
use openfang_api::ws;
use openfang_kernel::OpenFangKernel;
use openfang_types::config::{DefaultModelConfig, KernelConfig};
use std::sync::Arc;
use std::time::Instant;
use tower_http::cors::CorsLayer;
use tower_http::trace::TraceLayer;
// ---------------------------------------------------------------------------
// Test infrastructure
// ---------------------------------------------------------------------------
struct TestServer {
base_url: String,
state: Arc<AppState>,
_tmp: tempfile::TempDir,
}
impl Drop for TestServer {
fn drop(&mut self) {
self.state.kernel.shutdown();
}
}
/// Start a test server using ollama as default provider (no API key needed).
/// This lets the kernel boot without any real LLM credentials.
/// Tests that need actual LLM calls should use `start_test_server_with_llm()`.
async fn start_test_server() -> TestServer {
start_test_server_with_provider("ollama", "test-model", "OLLAMA_API_KEY").await
}
/// Start a test server with Groq as the LLM provider (requires GROQ_API_KEY).
async fn start_test_server_with_llm() -> TestServer {
start_test_server_with_provider("groq", "llama-3.3-70b-versatile", "GROQ_API_KEY").await
}
async fn start_test_server_with_provider(
provider: &str,
model: &str,
api_key_env: &str,
) -> TestServer {
let tmp = tempfile::tempdir().expect("Failed to create temp dir");
let config = KernelConfig {
home_dir: tmp.path().to_path_buf(),
data_dir: tmp.path().join("data"),
default_model: DefaultModelConfig {
provider: provider.to_string(),
model: model.to_string(),
api_key_env: api_key_env.to_string(),
base_url: None,
},
..KernelConfig::default()
};
let kernel = OpenFangKernel::boot_with_config(config).expect("Kernel should boot");
let kernel = Arc::new(kernel);
kernel.set_self_handle();
let state = Arc::new(AppState {
kernel,
started_at: Instant::now(),
peer_registry: None,
bridge_manager: tokio::sync::Mutex::new(None),
channels_config: tokio::sync::RwLock::new(Default::default()),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
let app = Router::new()
.route("/api/health", axum::routing::get(routes::health))
.route("/api/status", axum::routing::get(routes::status))
.route(
"/api/agents",
axum::routing::get(routes::list_agents).post(routes::spawn_agent),
)
.route(
"/api/agents/{id}/message",
axum::routing::post(routes::send_message),
)
.route(
"/api/agents/{id}/session",
axum::routing::get(routes::get_agent_session),
)
.route("/api/agents/{id}/ws", axum::routing::get(ws::agent_ws))
.route(
"/api/agents/{id}",
axum::routing::delete(routes::kill_agent),
)
.route(
"/api/triggers",
axum::routing::get(routes::list_triggers).post(routes::create_trigger),
)
.route(
"/api/triggers/{id}",
axum::routing::delete(routes::delete_trigger),
)
.route(
"/api/workflows",
axum::routing::get(routes::list_workflows).post(routes::create_workflow),
)
.route(
"/api/workflows/{id}/run",
axum::routing::post(routes::run_workflow),
)
.route(
"/api/workflows/{id}/runs",
axum::routing::get(routes::list_workflow_runs),
)
.route("/api/shutdown", axum::routing::post(routes::shutdown))
.layer(axum::middleware::from_fn(middleware::request_logging))
.layer(TraceLayer::new_for_http())
.layer(CorsLayer::permissive())
.with_state(state.clone());
let listener = tokio::net::TcpListener::bind("127.0.0.1:0")
.await
.expect("Failed to bind test server");
let addr = listener.local_addr().unwrap();
tokio::spawn(async move {
axum::serve(listener, app).await.unwrap();
});
TestServer {
base_url: format!("http://{}", addr),
state,
_tmp: tmp,
}
}
/// Manifest that uses ollama (no API key required, won't make real LLM calls).
const TEST_MANIFEST: &str = r#"
name = "test-agent"
version = "0.1.0"
description = "Integration test agent"
author = "test"
module = "builtin:chat"
[model]
provider = "ollama"
model = "test-model"
system_prompt = "You are a test agent. Reply concisely."
[capabilities]
tools = ["file_read"]
memory_read = ["*"]
memory_write = ["self.*"]
"#;
/// Manifest that uses Groq for real LLM tests.
const LLM_MANIFEST: &str = r#"
name = "test-agent"
version = "0.1.0"
description = "Integration test agent"
author = "test"
module = "builtin:chat"
[model]
provider = "groq"
model = "llama-3.3-70b-versatile"
system_prompt = "You are a test agent. Reply concisely."
[capabilities]
tools = ["file_read"]
memory_read = ["*"]
memory_write = ["self.*"]
"#;
// ---------------------------------------------------------------------------
// Tests
// ---------------------------------------------------------------------------
#[tokio::test]
async fn test_health_endpoint() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let resp = client
.get(format!("{}/api/health", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
// Middleware injects x-request-id
assert!(resp.headers().contains_key("x-request-id"));
let body: serde_json::Value = resp.json().await.unwrap();
// Public health endpoint returns minimal info (redacted for security)
assert_eq!(body["status"], "ok");
assert!(body["version"].is_string());
// Detailed fields should NOT appear in public health endpoint
assert!(body["database"].is_null());
assert!(body["agent_count"].is_null());
}
#[tokio::test]
async fn test_status_endpoint() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let resp = client
.get(format!("{}/api/status", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["status"], "running");
assert_eq!(body["agent_count"], 0);
assert!(body["uptime_seconds"].is_number());
assert_eq!(body["default_provider"], "ollama");
assert_eq!(body["agents"].as_array().unwrap().len(), 0);
}
#[tokio::test]
async fn test_spawn_list_kill_agent() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// --- Spawn ---
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": TEST_MANIFEST}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 201);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["name"], "test-agent");
let agent_id = body["agent_id"].as_str().unwrap().to_string();
assert!(!agent_id.is_empty());
// --- List (1 agent) ---
let resp = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let agents: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(agents.len(), 1);
assert_eq!(agents[0]["name"], "test-agent");
assert_eq!(agents[0]["id"], agent_id);
assert_eq!(agents[0]["model_provider"], "ollama");
// --- Kill ---
let resp = client
.delete(format!("{}/api/agents/{}", server.base_url, agent_id))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["status"], "killed");
// --- List (empty) ---
let resp = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let agents: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(agents.len(), 0);
}
#[tokio::test]
async fn test_agent_session_empty() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn agent
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": TEST_MANIFEST}))
.send()
.await
.unwrap();
let body: serde_json::Value = resp.json().await.unwrap();
let agent_id = body["agent_id"].as_str().unwrap();
// Session should be empty — no messages sent yet
let resp = client
.get(format!(
"{}/api/agents/{}/session",
server.base_url, agent_id
))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["message_count"], 0);
assert_eq!(body["messages"].as_array().unwrap().len(), 0);
}
#[tokio::test]
async fn test_send_message_with_llm() {
if std::env::var("GROQ_API_KEY").is_err() {
eprintln!("GROQ_API_KEY not set, skipping LLM integration test");
return;
}
let server = start_test_server_with_llm().await;
let client = reqwest::Client::new();
// Spawn
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": LLM_MANIFEST}))
.send()
.await
.unwrap();
let body: serde_json::Value = resp.json().await.unwrap();
let agent_id = body["agent_id"].as_str().unwrap().to_string();
// Send message through the real HTTP endpoint → kernel → Groq LLM
let resp = client
.post(format!(
"{}/api/agents/{}/message",
server.base_url, agent_id
))
.json(&serde_json::json!({"message": "Say hello in exactly 3 words."}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
let response_text = body["response"].as_str().unwrap();
assert!(
!response_text.is_empty(),
"LLM response should not be empty"
);
assert!(body["input_tokens"].as_u64().unwrap() > 0);
assert!(body["output_tokens"].as_u64().unwrap() > 0);
// Session should now have messages
let resp = client
.get(format!(
"{}/api/agents/{}/session",
server.base_url, agent_id
))
.send()
.await
.unwrap();
let session: serde_json::Value = resp.json().await.unwrap();
assert!(session["message_count"].as_u64().unwrap() > 0);
}
#[tokio::test]
async fn test_workflow_crud() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn agent for workflow
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": TEST_MANIFEST}))
.send()
.await
.unwrap();
let body: serde_json::Value = resp.json().await.unwrap();
let agent_name = body["name"].as_str().unwrap().to_string();
// Create workflow
let resp = client
.post(format!("{}/api/workflows", server.base_url))
.json(&serde_json::json!({
"name": "test-workflow",
"description": "Integration test workflow",
"steps": [
{
"name": "step1",
"agent_name": agent_name,
"prompt": "Echo: {{input}}",
"mode": "sequential",
"timeout_secs": 30
}
]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 201);
let body: serde_json::Value = resp.json().await.unwrap();
let workflow_id = body["workflow_id"].as_str().unwrap().to_string();
assert!(!workflow_id.is_empty());
// List workflows
let resp = client
.get(format!("{}/api/workflows", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let workflows: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(workflows.len(), 1);
assert_eq!(workflows[0]["name"], "test-workflow");
assert_eq!(workflows[0]["steps"], 1);
}
#[tokio::test]
async fn test_trigger_crud() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn agent for trigger
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": TEST_MANIFEST}))
.send()
.await
.unwrap();
let body: serde_json::Value = resp.json().await.unwrap();
let agent_id = body["agent_id"].as_str().unwrap().to_string();
// Create trigger (Lifecycle pattern — simplest variant)
let resp = client
.post(format!("{}/api/triggers", server.base_url))
.json(&serde_json::json!({
"agent_id": agent_id,
"pattern": "lifecycle",
"prompt_template": "Handle: {{event}}",
"max_fires": 5
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 201);
let body: serde_json::Value = resp.json().await.unwrap();
let trigger_id = body["trigger_id"].as_str().unwrap().to_string();
assert_eq!(body["agent_id"], agent_id);
// List triggers (unfiltered)
let resp = client
.get(format!("{}/api/triggers", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let triggers: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(triggers.len(), 1);
assert_eq!(triggers[0]["agent_id"], agent_id);
assert_eq!(triggers[0]["enabled"], true);
assert_eq!(triggers[0]["max_fires"], 5);
// List triggers (filtered by agent_id)
let resp = client
.get(format!(
"{}/api/triggers?agent_id={}",
server.base_url, agent_id
))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let triggers: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(triggers.len(), 1);
// Delete trigger
let resp = client
.delete(format!("{}/api/triggers/{}", server.base_url, trigger_id))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
// List triggers (should be empty)
let resp = client
.get(format!("{}/api/triggers", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let triggers: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(triggers.len(), 0);
}
#[tokio::test]
async fn test_invalid_agent_id_returns_400() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Send message to invalid ID
let resp = client
.post(format!("{}/api/agents/not-a-uuid/message", server.base_url))
.json(&serde_json::json!({"message": "hello"}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 400);
let body: serde_json::Value = resp.json().await.unwrap();
assert!(body["error"].as_str().unwrap().contains("Invalid"));
// Kill invalid ID
let resp = client
.delete(format!("{}/api/agents/not-a-uuid", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 400);
// Session for invalid ID
let resp = client
.get(format!("{}/api/agents/not-a-uuid/session", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 400);
}
#[tokio::test]
async fn test_kill_nonexistent_agent_returns_404() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let fake_id = uuid::Uuid::new_v4();
let resp = client
.delete(format!("{}/api/agents/{}", server.base_url, fake_id))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 404);
}
#[tokio::test]
async fn test_spawn_invalid_manifest_returns_400() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": "this is {{ not valid toml"}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 400);
let body: serde_json::Value = resp.json().await.unwrap();
assert!(body["error"].as_str().unwrap().contains("Invalid manifest"));
}
#[tokio::test]
async fn test_request_id_header_is_uuid() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let resp = client
.get(format!("{}/api/health", server.base_url))
.send()
.await
.unwrap();
let request_id = resp
.headers()
.get("x-request-id")
.expect("x-request-id header should be present");
let id_str = request_id.to_str().unwrap();
assert!(
uuid::Uuid::parse_str(id_str).is_ok(),
"x-request-id should be a valid UUID, got: {}",
id_str
);
}
#[tokio::test]
async fn test_multiple_agents_lifecycle() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn 3 agents
let mut ids = Vec::new();
for i in 0..3 {
let manifest = format!(
r#"
name = "agent-{i}"
version = "0.1.0"
description = "Multi-agent test {i}"
author = "test"
module = "builtin:chat"
[model]
provider = "ollama"
model = "test-model"
system_prompt = "Agent {i}."
[capabilities]
memory_read = ["*"]
memory_write = ["self.*"]
"#
);
let resp = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 201);
let body: serde_json::Value = resp.json().await.unwrap();
ids.push(body["agent_id"].as_str().unwrap().to_string());
}
// List should show 3
let resp = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap();
let agents: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(agents.len(), 3);
// Status should agree
let resp = client
.get(format!("{}/api/status", server.base_url))
.send()
.await
.unwrap();
let status: serde_json::Value = resp.json().await.unwrap();
assert_eq!(status["agent_count"], 3);
// Kill one
let resp = client
.delete(format!("{}/api/agents/{}", server.base_url, ids[1]))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
// List should show 2
let resp = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap();
let agents: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(agents.len(), 2);
// Kill the rest
for id in [&ids[0], &ids[2]] {
client
.delete(format!("{}/api/agents/{}", server.base_url, id))
.send()
.await
.unwrap();
}
// List should be empty
let resp = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap();
let agents: Vec<serde_json::Value> = resp.json().await.unwrap();
assert_eq!(agents.len(), 0);
}
// ---------------------------------------------------------------------------
// Auth integration tests
// ---------------------------------------------------------------------------
/// Start a test server with Bearer-token authentication enabled.
async fn start_test_server_with_auth(api_key: &str) -> TestServer {
let tmp = tempfile::tempdir().expect("Failed to create temp dir");
let config = KernelConfig {
home_dir: tmp.path().to_path_buf(),
data_dir: tmp.path().join("data"),
api_key: api_key.to_string(),
default_model: DefaultModelConfig {
provider: "ollama".to_string(),
model: "test-model".to_string(),
api_key_env: "OLLAMA_API_KEY".to_string(),
base_url: None,
},
..KernelConfig::default()
};
let kernel = OpenFangKernel::boot_with_config(config).expect("Kernel should boot");
let kernel = Arc::new(kernel);
kernel.set_self_handle();
let state = Arc::new(AppState {
kernel,
started_at: Instant::now(),
peer_registry: None,
bridge_manager: tokio::sync::Mutex::new(None),
channels_config: tokio::sync::RwLock::new(Default::default()),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
let api_key_state = state.kernel.config.api_key.clone();
let app = Router::new()
.route("/api/health", axum::routing::get(routes::health))
.route("/api/status", axum::routing::get(routes::status))
.route(
"/api/agents",
axum::routing::get(routes::list_agents).post(routes::spawn_agent),
)
.route(
"/api/agents/{id}/message",
axum::routing::post(routes::send_message),
)
.route(
"/api/agents/{id}/session",
axum::routing::get(routes::get_agent_session),
)
.route("/api/agents/{id}/ws", axum::routing::get(ws::agent_ws))
.route(
"/api/agents/{id}",
axum::routing::delete(routes::kill_agent),
)
.route(
"/api/triggers",
axum::routing::get(routes::list_triggers).post(routes::create_trigger),
)
.route(
"/api/triggers/{id}",
axum::routing::delete(routes::delete_trigger),
)
.route(
"/api/workflows",
axum::routing::get(routes::list_workflows).post(routes::create_workflow),
)
.route(
"/api/workflows/{id}/run",
axum::routing::post(routes::run_workflow),
)
.route(
"/api/workflows/{id}/runs",
axum::routing::get(routes::list_workflow_runs),
)
.route("/api/shutdown", axum::routing::post(routes::shutdown))
.layer(axum::middleware::from_fn_with_state(
api_key_state,
middleware::auth,
))
.layer(axum::middleware::from_fn(middleware::request_logging))
.layer(TraceLayer::new_for_http())
.layer(CorsLayer::permissive())
.with_state(state.clone());
let listener = tokio::net::TcpListener::bind("127.0.0.1:0")
.await
.expect("Failed to bind test server");
let addr = listener.local_addr().unwrap();
tokio::spawn(async move {
axum::serve(listener, app).await.unwrap();
});
TestServer {
base_url: format!("http://{}", addr),
state,
_tmp: tmp,
}
}
#[tokio::test]
async fn test_auth_health_is_public() {
let server = start_test_server_with_auth("secret-key-123").await;
let client = reqwest::Client::new();
// /api/health should be accessible without auth
let resp = client
.get(format!("{}/api/health", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
}
#[tokio::test]
async fn test_auth_rejects_no_token() {
let server = start_test_server_with_auth("secret-key-123").await;
let client = reqwest::Client::new();
// Protected endpoint without auth header → 401
// Note: /api/status is public (dashboard needs it), so use a protected endpoint
let resp = client
.get(format!("{}/api/commands", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 401);
let body: serde_json::Value = resp.json().await.unwrap();
assert!(body["error"].as_str().unwrap().contains("Missing"));
}
#[tokio::test]
async fn test_auth_rejects_wrong_token() {
let server = start_test_server_with_auth("secret-key-123").await;
let client = reqwest::Client::new();
// Wrong bearer token → 401
// Note: /api/status is public (dashboard needs it), so use a protected endpoint
let resp = client
.get(format!("{}/api/commands", server.base_url))
.header("authorization", "Bearer wrong-key")
.send()
.await
.unwrap();
assert_eq!(resp.status(), 401);
let body: serde_json::Value = resp.json().await.unwrap();
assert!(body["error"].as_str().unwrap().contains("Invalid"));
}
#[tokio::test]
async fn test_auth_accepts_correct_token() {
let server = start_test_server_with_auth("secret-key-123").await;
let client = reqwest::Client::new();
// Correct bearer token → 200
let resp = client
.get(format!("{}/api/status", server.base_url))
.header("authorization", "Bearer secret-key-123")
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["status"], "running");
}
#[tokio::test]
async fn test_auth_disabled_when_no_key() {
// Empty API key = auth disabled
let server = start_test_server().await;
let client = reqwest::Client::new();
// Protected endpoint accessible without auth when no key is configured
let resp = client
.get(format!("{}/api/status", server.base_url))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
}

270
crates/openfang-api/tests/daemon_lifecycle_test.rs Normal file
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@@ -0,0 +1,270 @@
//! Daemon lifecycle integration tests.
//!
//! Tests the real daemon startup, PID file management, health serving,
//! and graceful shutdown sequence.
use axum::Router;
use openfang_api::middleware;
use openfang_api::routes::{self, AppState};
use openfang_api::server::{read_daemon_info, DaemonInfo};
use openfang_kernel::OpenFangKernel;
use openfang_types::config::{DefaultModelConfig, KernelConfig};
use std::sync::Arc;
use std::time::Instant;
use tower_http::cors::CorsLayer;
use tower_http::trace::TraceLayer;
// ---------------------------------------------------------------------------
// Tests
// ---------------------------------------------------------------------------
/// Test DaemonInfo serialization and deserialization round-trip.
#[test]
fn test_daemon_info_serde_roundtrip() {
let info = DaemonInfo {
pid: 12345,
listen_addr: "127.0.0.1:4200".to_string(),
started_at: "2024-01-01T00:00:00Z".to_string(),
version: "0.1.0".to_string(),
platform: "linux".to_string(),
};
let json = serde_json::to_string_pretty(&info).unwrap();
let parsed: DaemonInfo = serde_json::from_str(&json).unwrap();
assert_eq!(parsed.pid, 12345);
assert_eq!(parsed.listen_addr, "127.0.0.1:4200");
assert_eq!(parsed.version, "0.1.0");
assert_eq!(parsed.platform, "linux");
}
/// Test read_daemon_info from a file on disk.
#[test]
fn test_read_daemon_info_from_file() {
let tmp = tempfile::tempdir().unwrap();
// Write a daemon.json
let info = DaemonInfo {
pid: std::process::id(),
listen_addr: "127.0.0.1:9999".to_string(),
started_at: chrono::Utc::now().to_rfc3339(),
version: "0.1.0".to_string(),
platform: "test".to_string(),
};
let json = serde_json::to_string_pretty(&info).unwrap();
std::fs::write(tmp.path().join("daemon.json"), json).unwrap();
// Read it back
let loaded = read_daemon_info(tmp.path());
assert!(loaded.is_some());
let loaded = loaded.unwrap();
assert_eq!(loaded.pid, std::process::id());
assert_eq!(loaded.listen_addr, "127.0.0.1:9999");
}
/// Test read_daemon_info returns None when file doesn't exist.
#[test]
fn test_read_daemon_info_missing_file() {
let tmp = tempfile::tempdir().unwrap();
let loaded = read_daemon_info(tmp.path());
assert!(loaded.is_none());
}
/// Test read_daemon_info returns None for corrupt JSON.
#[test]
fn test_read_daemon_info_corrupt_json() {
let tmp = tempfile::tempdir().unwrap();
std::fs::write(tmp.path().join("daemon.json"), "not json at all").unwrap();
let loaded = read_daemon_info(tmp.path());
assert!(loaded.is_none());
}
/// Test the full daemon lifecycle:
/// 1. Boot kernel + start server on random port
/// 2. Write daemon info file
/// 3. Verify health endpoint
/// 4. Verify daemon info file contents match
/// 5. Shut down and verify cleanup
#[tokio::test]
async fn test_full_daemon_lifecycle() {
let tmp = tempfile::tempdir().unwrap();
let daemon_info_path = tmp.path().join("daemon.json");
let config = KernelConfig {
home_dir: tmp.path().to_path_buf(),
data_dir: tmp.path().join("data"),
default_model: DefaultModelConfig {
provider: "ollama".to_string(),
model: "test".to_string(),
api_key_env: "OLLAMA_API_KEY".to_string(),
base_url: None,
},
..KernelConfig::default()
};
let kernel = OpenFangKernel::boot_with_config(config).expect("Kernel should boot");
let kernel = Arc::new(kernel);
kernel.set_self_handle();
let state = Arc::new(AppState {
kernel: kernel.clone(),
started_at: Instant::now(),
peer_registry: None,
bridge_manager: tokio::sync::Mutex::new(None),
channels_config: tokio::sync::RwLock::new(Default::default()),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
let app = Router::new()
.route("/api/health", axum::routing::get(routes::health))
.route("/api/status", axum::routing::get(routes::status))
.route("/api/shutdown", axum::routing::post(routes::shutdown))
.layer(axum::middleware::from_fn(middleware::request_logging))
.layer(TraceLayer::new_for_http())
.layer(CorsLayer::permissive())
.with_state(state.clone());
// Bind to random port
let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
let addr = listener.local_addr().unwrap();
// Spawn server
tokio::spawn(async move {
axum::serve(listener, app).await.unwrap();
});
// Write daemon info file (like run_daemon does)
let daemon_info = DaemonInfo {
pid: std::process::id(),
listen_addr: addr.to_string(),
started_at: chrono::Utc::now().to_rfc3339(),
version: env!("CARGO_PKG_VERSION").to_string(),
platform: std::env::consts::OS.to_string(),
};
let json = serde_json::to_string_pretty(&daemon_info).unwrap();
std::fs::write(&daemon_info_path, &json).unwrap();
// --- Verify daemon info file ---
assert!(daemon_info_path.exists());
let loaded = read_daemon_info(tmp.path()).unwrap();
assert_eq!(loaded.pid, std::process::id());
assert_eq!(loaded.listen_addr, addr.to_string());
// --- Verify health endpoint ---
let client = reqwest::Client::new();
let resp = client
.get(format!("http://{}/api/health", addr))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["status"], "ok");
// --- Verify status endpoint ---
let resp = client
.get(format!("http://{}/api/status", addr))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["status"], "running");
// --- Shutdown ---
let resp = client
.post(format!("http://{}/api/shutdown", addr))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
// Clean up daemon info file (like run_daemon does)
let _ = std::fs::remove_file(&daemon_info_path);
assert!(!daemon_info_path.exists());
kernel.shutdown();
}
/// Test that stale daemon info is detected when no process is running at that PID.
#[test]
fn test_stale_daemon_info_detection() {
let tmp = tempfile::tempdir().unwrap();
// Write daemon.json with a PID that almost certainly doesn't exist
// (using a very high PID number)
let info = DaemonInfo {
pid: 99999999, // unlikely to be running
listen_addr: "127.0.0.1:9999".to_string(),
started_at: "2024-01-01T00:00:00Z".to_string(),
version: "0.1.0".to_string(),
platform: "test".to_string(),
};
let json = serde_json::to_string_pretty(&info).unwrap();
std::fs::write(tmp.path().join("daemon.json"), json).unwrap();
// read_daemon_info just reads the file — it doesn't check if the PID is alive
// (that check happens in run_daemon). So the file is readable:
let loaded = read_daemon_info(tmp.path());
assert!(loaded.is_some());
assert_eq!(loaded.unwrap().pid, 99999999);
}
/// Test that the server starts and immediately responds to requests.
#[tokio::test]
async fn test_server_immediate_responsiveness() {
let tmp = tempfile::tempdir().unwrap();
let config = KernelConfig {
home_dir: tmp.path().to_path_buf(),
data_dir: tmp.path().join("data"),
default_model: DefaultModelConfig {
provider: "ollama".to_string(),
model: "test".to_string(),
api_key_env: "OLLAMA_API_KEY".to_string(),
base_url: None,
},
..KernelConfig::default()
};
let kernel = OpenFangKernel::boot_with_config(config).unwrap();
let kernel = Arc::new(kernel);
let state = Arc::new(AppState {
kernel: kernel.clone(),
started_at: Instant::now(),
peer_registry: None,
bridge_manager: tokio::sync::Mutex::new(None),
channels_config: tokio::sync::RwLock::new(Default::default()),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
let app = Router::new()
.route("/api/health", axum::routing::get(routes::health))
.with_state(state);
let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
let addr = listener.local_addr().unwrap();
tokio::spawn(async move {
axum::serve(listener, app).await.unwrap();
});
// Hit health endpoint immediately — should respond fast
let client = reqwest::Client::new();
let start = Instant::now();
let resp = client
.get(format!("http://{}/api/health", addr))
.send()
.await
.unwrap();
let latency = start.elapsed();
assert_eq!(resp.status(), 200);
assert!(
latency.as_millis() < 1000,
"Health endpoint should respond in <1s, took {}ms",
latency.as_millis()
);
kernel.shutdown();
}

584
crates/openfang-api/tests/load_test.rs Normal file
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@@ -0,0 +1,584 @@
//! Load & performance tests for the OpenFang API.
//!
//! Measures throughput under concurrent access: agent spawning, API endpoint
//! latency, session management, and memory usage.
//!
//! Run: cargo test -p openfang-api --test load_test -- --nocapture
use axum::Router;
use openfang_api::middleware;
use openfang_api::routes::{self, AppState};
use openfang_kernel::OpenFangKernel;
use openfang_types::config::{DefaultModelConfig, KernelConfig};
use std::sync::Arc;
use std::time::{Duration, Instant};
use tower_http::cors::CorsLayer;
use tower_http::trace::TraceLayer;
// ---------------------------------------------------------------------------
// Test infrastructure (mirrors api_integration_test.rs)
// ---------------------------------------------------------------------------
struct TestServer {
base_url: String,
state: Arc<AppState>,
_tmp: tempfile::TempDir,
}
impl Drop for TestServer {
fn drop(&mut self) {
self.state.kernel.shutdown();
}
}
async fn start_test_server() -> TestServer {
let tmp = tempfile::tempdir().expect("Failed to create temp dir");
let config = KernelConfig {
home_dir: tmp.path().to_path_buf(),
data_dir: tmp.path().join("data"),
default_model: DefaultModelConfig {
provider: "ollama".to_string(),
model: "test-model".to_string(),
api_key_env: "OLLAMA_API_KEY".to_string(),
base_url: None,
},
..KernelConfig::default()
};
let kernel = OpenFangKernel::boot_with_config(config).expect("Kernel should boot");
let kernel = Arc::new(kernel);
kernel.set_self_handle();
let state = Arc::new(AppState {
kernel,
started_at: Instant::now(),
peer_registry: None,
bridge_manager: tokio::sync::Mutex::new(None),
channels_config: tokio::sync::RwLock::new(Default::default()),
shutdown_notify: Arc::new(tokio::sync::Notify::new()),
});
let app = Router::new()
.route("/api/health", axum::routing::get(routes::health))
.route("/api/status", axum::routing::get(routes::status))
.route("/api/version", axum::routing::get(routes::version))
.route(
"/api/metrics",
axum::routing::get(routes::prometheus_metrics),
)
.route(
"/api/agents",
axum::routing::get(routes::list_agents).post(routes::spawn_agent),
)
.route(
"/api/agents/{id}",
axum::routing::get(routes::get_agent).delete(routes::kill_agent),
)
.route(
"/api/agents/{id}/session",
axum::routing::get(routes::get_agent_session),
)
.route(
"/api/agents/{id}/session/reset",
axum::routing::post(routes::reset_session),
)
.route(
"/api/agents/{id}/sessions",
axum::routing::get(routes::list_agent_sessions).post(routes::create_agent_session),
)
.route("/api/tools", axum::routing::get(routes::list_tools))
.route("/api/models", axum::routing::get(routes::list_models))
.route("/api/providers", axum::routing::get(routes::list_providers))
.route("/api/usage", axum::routing::get(routes::usage_stats))
.route(
"/api/workflows",
axum::routing::get(routes::list_workflows).post(routes::create_workflow),
)
.route(
"/api/workflows/{id}/run",
axum::routing::post(routes::run_workflow),
)
.route("/api/config", axum::routing::get(routes::get_config))
.layer(axum::middleware::from_fn(middleware::request_logging))
.layer(TraceLayer::new_for_http())
.layer(CorsLayer::permissive())
.with_state(state.clone());
let listener = tokio::net::TcpListener::bind("127.0.0.1:0")
.await
.expect("Failed to bind test server");
let addr = listener.local_addr().unwrap();
tokio::spawn(async move {
axum::serve(listener, app).await.unwrap();
});
TestServer {
base_url: format!("http://{}", addr),
state,
_tmp: tmp,
}
}
const TEST_MANIFEST: &str = r#"
name = "load-test-agent"
version = "0.1.0"
description = "Load test agent"
author = "test"
module = "builtin:chat"
[model]
provider = "ollama"
model = "test-model"
system_prompt = "You are a test agent."
[capabilities]
tools = ["file_read"]
memory_read = ["*"]
memory_write = ["self.*"]
"#;
// ---------------------------------------------------------------------------
// Load tests
// ---------------------------------------------------------------------------
/// Test: Concurrent agent spawns — verify kernel handles parallel agent creation.
#[tokio::test]
async fn load_concurrent_agent_spawns() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let n = 20; // 20 concurrent spawns
let start = Instant::now();
let mut handles = Vec::new();
for i in 0..n {
let c = client.clone();
let url = format!("{}/api/agents", server.base_url);
let manifest = TEST_MANIFEST.replace("load-test-agent", &format!("load-agent-{i}"));
handles.push(tokio::spawn(async move {
let res = c
.post(&url)
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.expect("request failed");
(res.status().as_u16(), i)
}));
}
let mut success = 0;
for h in handles {
let (status, _i) = h.await.unwrap();
if status == 200 || status == 201 {
success += 1;
}
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Concurrent spawns: {success}/{n} succeeded in {:.0}ms ({:.0} spawns/sec)",
elapsed.as_millis(),
n as f64 / elapsed.as_secs_f64()
);
assert!(success >= n - 2, "Most agents should spawn successfully");
// Verify via list
let agents: serde_json::Value = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
let count = agents.as_array().map(|a| a.len()).unwrap_or(0);
eprintln!(" [LOAD] Total agents after spawn: {count}");
assert!(count >= success);
}
/// Test: API endpoint latency — measure p50/p95/p99 for health, status, list agents.
#[tokio::test]
async fn load_endpoint_latency() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn a few agents for the list endpoint to return
for i in 0..5 {
let manifest = TEST_MANIFEST.replace("load-test-agent", &format!("latency-agent-{i}"));
client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.unwrap();
}
let endpoints = vec![
("GET", "/api/health"),
("GET", "/api/status"),
("GET", "/api/agents"),
("GET", "/api/tools"),
("GET", "/api/models"),
("GET", "/api/metrics"),
("GET", "/api/config"),
("GET", "/api/usage"),
];
for (method, path) in &endpoints {
let mut latencies = Vec::new();
let n = 100;
for _ in 0..n {
let start = Instant::now();
let url = format!("{}{}", server.base_url, path);
let res = match *method {
"GET" => client.get(&url).send().await,
_ => client.post(&url).send().await,
};
let elapsed = start.elapsed();
assert!(res.is_ok(), "{method} {path} failed");
latencies.push(elapsed);
}
latencies.sort();
let p50 = latencies[n / 2];
let p95 = latencies[(n as f64 * 0.95) as usize];
let p99 = latencies[(n as f64 * 0.99) as usize];
eprintln!(
" [LOAD] {method} {path:30} p50={:>5.1}ms p95={:>5.1}ms p99={:>5.1}ms",
p50.as_secs_f64() * 1000.0,
p95.as_secs_f64() * 1000.0,
p99.as_secs_f64() * 1000.0,
);
// p99 should be under 100ms for read endpoints
assert!(
p99 < Duration::from_millis(500),
"{method} {path} p99 too high: {p99:?}"
);
}
}
/// Test: Concurrent reads — many clients hitting the same endpoints simultaneously.
#[tokio::test]
async fn load_concurrent_reads() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn some agents first
for i in 0..3 {
let manifest = TEST_MANIFEST.replace("load-test-agent", &format!("concurrent-agent-{i}"));
client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.unwrap();
}
let n = 50;
let start = Instant::now();
let mut handles = Vec::new();
for i in 0..n {
let c = client.clone();
let base = server.base_url.clone();
handles.push(tokio::spawn(async move {
// Cycle through different endpoints
let path = match i % 4 {
0 => "/api/health",
1 => "/api/agents",
2 => "/api/status",
_ => "/api/metrics",
};
let res = c
.get(format!("{base}{path}"))
.send()
.await
.expect("request failed");
res.status().as_u16()
}));
}
let mut success = 0;
for h in handles {
let status = h.await.unwrap();
if status == 200 {
success += 1;
}
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Concurrent reads: {success}/{n} succeeded in {:.0}ms ({:.0} req/sec)",
elapsed.as_millis(),
n as f64 / elapsed.as_secs_f64()
);
assert_eq!(success, n, "All concurrent reads should succeed");
}
/// Test: Session management under load — create, list, and switch sessions.
#[tokio::test]
async fn load_session_management() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn an agent
let res: serde_json::Value = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": TEST_MANIFEST}))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
let agent_id = res["agent_id"].as_str().unwrap().to_string();
// Create multiple sessions
let n = 10;
let start = Instant::now();
let mut session_ids = Vec::new();
for i in 0..n {
let res: serde_json::Value = client
.post(format!(
"{}/api/agents/{}/sessions",
server.base_url, agent_id
))
.json(&serde_json::json!({"label": format!("session-{i}")}))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
if let Some(id) = res.get("session_id").and_then(|v| v.as_str()) {
session_ids.push(id.to_string());
}
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Created {n} sessions in {:.0}ms",
elapsed.as_millis()
);
// List sessions
let start = Instant::now();
let sessions_resp: serde_json::Value = client
.get(format!(
"{}/api/agents/{}/sessions",
server.base_url, agent_id
))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
// Response is {"sessions": [...]} — extract the array
let session_count = sessions_resp
.get("sessions")
.and_then(|v| v.as_array())
.map(|a| a.len())
.unwrap_or_else(|| {
// Fallback: maybe it's a direct array
sessions_resp.as_array().map(|a| a.len()).unwrap_or(0)
});
eprintln!(
" [LOAD] Listed {session_count} sessions in {:.1}ms",
start.elapsed().as_secs_f64() * 1000.0
);
// We expect at least some sessions (the original + our new ones)
// Note: create_session might fail silently for some if agent was spawned without session
eprintln!(" [LOAD] Session IDs collected: {}", session_ids.len());
assert!(
!session_ids.is_empty() || session_count > 0,
"Should have created some sessions"
);
// Switch between sessions rapidly
let start = Instant::now();
for sid in &session_ids {
client
.post(format!(
"{}/api/agents/{}/sessions/{}/switch",
server.base_url, agent_id, sid
))
.send()
.await
.unwrap();
}
eprintln!(
" [LOAD] Switched through {} sessions in {:.0}ms",
session_ids.len(),
start.elapsed().as_millis()
);
}
/// Test: Workflow creation and listing under load.
#[tokio::test]
async fn load_workflow_operations() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let n = 15;
let start = Instant::now();
// Create workflows concurrently
let mut handles = Vec::new();
for i in 0..n {
let c = client.clone();
let url = format!("{}/api/workflows", server.base_url);
handles.push(tokio::spawn(async move {
let res = c
.post(&url)
.json(&serde_json::json!({
"name": format!("wf-{i}"),
"description": format!("Load test workflow {i}"),
"steps": [{
"name": "step1",
"agent_name": "test-agent",
"mode": "sequential",
"prompt": "{{input}}"
}]
}))
.send()
.await
.expect("request failed");
res.status().as_u16()
}));
}
let mut created = 0;
for h in handles {
let status = h.await.unwrap();
if status == 200 || status == 201 {
created += 1;
}
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Created {created}/{n} workflows in {:.0}ms",
elapsed.as_millis()
);
// List all workflows
let start = Instant::now();
let workflows: serde_json::Value = client
.get(format!("{}/api/workflows", server.base_url))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
let wf_count = workflows.as_array().map(|a| a.len()).unwrap_or(0);
eprintln!(
" [LOAD] Listed {wf_count} workflows in {:.1}ms",
start.elapsed().as_secs_f64() * 1000.0
);
assert!(wf_count >= created);
}
/// Test: Agent spawn + kill cycle — stress the registry.
#[tokio::test]
async fn load_spawn_kill_cycle() {
let server = start_test_server().await;
let client = reqwest::Client::new();
let cycles = 10;
let start = Instant::now();
let mut ids = Vec::new();
// Spawn
for i in 0..cycles {
let manifest = TEST_MANIFEST.replace("load-test-agent", &format!("cycle-agent-{i}"));
let res: serde_json::Value = client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
if let Some(id) = res.get("agent_id").and_then(|v| v.as_str()) {
ids.push(id.to_string());
}
}
// Kill
for id in &ids {
client
.delete(format!("{}/api/agents/{}", server.base_url, id))
.send()
.await
.unwrap();
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Spawn+kill {cycles} agents in {:.0}ms ({:.0}ms per cycle)",
elapsed.as_millis(),
elapsed.as_millis() as f64 / cycles as f64
);
// Verify all cleaned up
let agents: serde_json::Value = client
.get(format!("{}/api/agents", server.base_url))
.send()
.await
.unwrap()
.json()
.await
.unwrap();
let remaining = agents.as_array().map(|a| a.len()).unwrap_or(0);
assert_eq!(remaining, 0, "All agents should be killed");
}
/// Test: Prometheus metrics endpoint under sustained load.
#[tokio::test]
async fn load_metrics_sustained() {
let server = start_test_server().await;
let client = reqwest::Client::new();
// Spawn a few agents first so metrics have data
for i in 0..3 {
let manifest = TEST_MANIFEST.replace("load-test-agent", &format!("metrics-agent-{i}"));
client
.post(format!("{}/api/agents", server.base_url))
.json(&serde_json::json!({"manifest_toml": manifest}))
.send()
.await
.unwrap();
}
// Hit metrics endpoint 200 times
let n = 200;
let start = Instant::now();
for _ in 0..n {
let res = client
.get(format!("{}/api/metrics", server.base_url))
.send()
.await
.unwrap();
assert_eq!(res.status().as_u16(), 200);
let body = res.text().await.unwrap();
assert!(body.contains("openfang_agents_active"));
}
let elapsed = start.elapsed();
eprintln!(
" [LOAD] Metrics {n} requests in {:.0}ms ({:.0} req/sec, {:.1}ms avg)",
elapsed.as_millis(),
n as f64 / elapsed.as_secs_f64(),
elapsed.as_secs_f64() * 1000.0 / n as f64
);
}

36
crates/openfang-channels/Cargo.toml Normal file
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@@ -0,0 +1,36 @@
[package]
name = "openfang-channels"
version.workspace = true
edition.workspace = true
license.workspace = true
description = "Channel Bridge Layer — pluggable messaging integrations for OpenFang"
[dependencies]
openfang-types = { path = "../openfang-types" }
tokio = { workspace = true }
serde = { workspace = true }
serde_json = { workspace = true }
chrono = { workspace = true }
dashmap = { workspace = true }
async-trait = { workspace = true }
futures = { workspace = true }
reqwest = { workspace = true }
tokio-stream = { workspace = true }
tracing = { workspace = true }
uuid = { workspace = true }
tokio-tungstenite = { workspace = true }
url = { workspace = true }
zeroize = { workspace = true }
axum = { workspace = true }
hmac = { workspace = true }
sha2 = { workspace = true }
base64 = { workspace = true }
hex = { workspace = true }
lettre = { workspace = true }
imap = { workspace = true }
native-tls = { workspace = true }
mailparse = { workspace = true }
[dev-dependencies]
tokio-test = { workspace = true }

694
crates/openfang-channels/src/bluesky.rs Normal file
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@@ -0,0 +1,694 @@
//! AT Protocol (Bluesky) channel adapter.
//!
//! Uses the AT Protocol (atproto) XRPC API for authentication, posting, and
//! polling notifications. Session creation uses `com.atproto.server.createSession`
//! with identifier + app password. Posts are created via
//! `com.atproto.repo.createRecord` with the `app.bsky.feed.post` lexicon.
use crate::types::{
split_message, ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser,
};
use async_trait::async_trait;
use chrono::Utc;
use futures::Stream;
use std::collections::HashMap;
use std::pin::Pin;
use std::sync::Arc;
use std::time::{Duration, Instant};
use tokio::sync::{mpsc, watch, RwLock};
use tracing::{info, warn};
use zeroize::Zeroizing;
/// Default Bluesky PDS service URL.
const DEFAULT_SERVICE_URL: &str = "https://bsky.social";
/// Maximum Bluesky post length (grapheme clusters).
const MAX_MESSAGE_LEN: usize = 300;
/// Notification poll interval in seconds.
const POLL_INTERVAL_SECS: u64 = 5;
/// Session refresh buffer — refresh 5 minutes before actual expiry.
const SESSION_REFRESH_BUFFER_SECS: u64 = 300;
/// AT Protocol (Bluesky) adapter.
///
/// Inbound mentions are received by polling the `app.bsky.notification.listNotifications`
/// endpoint. Outbound posts are created via `com.atproto.repo.createRecord` with
/// the `app.bsky.feed.post` record type. Session tokens are cached and refreshed
/// automatically.
pub struct BlueskyAdapter {
/// AT Protocol identifier (handle or DID, e.g., "alice.bsky.social").
identifier: String,
/// SECURITY: App password for session creation, zeroized on drop.
app_password: Zeroizing<String>,
/// PDS service URL (default: `"https://bsky.social"`).
service_url: String,
/// HTTP client for API calls.
client: reqwest::Client,
/// Shutdown signal.
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
/// Cached session (access_jwt, refresh_jwt, did, expiry).
session: Arc<RwLock<Option<BlueskySession>>>,
}
/// Cached Bluesky session data.
struct BlueskySession {
/// JWT access token for authenticated requests.
access_jwt: String,
/// JWT refresh token for session renewal.
refresh_jwt: String,
/// The DID of the authenticated account.
did: String,
/// When this session was created (for expiry tracking).
created_at: Instant,
}
impl BlueskyAdapter {
/// Create a new Bluesky adapter with the default service URL.
///
/// # Arguments
/// * `identifier` - AT Protocol handle (e.g., "alice.bsky.social") or DID.
/// * `app_password` - App password (not the main account password).
pub fn new(identifier: String, app_password: String) -> Self {
Self::with_service_url(identifier, app_password, DEFAULT_SERVICE_URL.to_string())
}
/// Create a new Bluesky adapter with a custom PDS service URL.
pub fn with_service_url(identifier: String, app_password: String, service_url: String) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
let service_url = service_url.trim_end_matches('/').to_string();
Self {
identifier,
app_password: Zeroizing::new(app_password),
service_url,
client: reqwest::Client::new(),
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
session: Arc::new(RwLock::new(None)),
}
}
/// Create a new session via `com.atproto.server.createSession`.
async fn create_session(&self) -> Result<BlueskySession, Box<dyn std::error::Error>> {
let url = format!("{}/xrpc/com.atproto.server.createSession", self.service_url);
let body = serde_json::json!({
"identifier": self.identifier,
"password": self.app_password.as_str(),
});
let resp = self.client.post(&url).json(&body).send().await?;
if !resp.status().is_success() {
let status = resp.status();
let resp_body = resp.text().await.unwrap_or_default();
return Err(format!("Bluesky createSession failed {status}: {resp_body}").into());
}
let resp_body: serde_json::Value = resp.json().await?;
let access_jwt = resp_body["accessJwt"]
.as_str()
.ok_or("Missing accessJwt")?
.to_string();
let refresh_jwt = resp_body["refreshJwt"]
.as_str()
.ok_or("Missing refreshJwt")?
.to_string();
let did = resp_body["did"].as_str().ok_or("Missing did")?.to_string();
Ok(BlueskySession {
access_jwt,
refresh_jwt,
did,
created_at: Instant::now(),
})
}
/// Refresh an existing session via `com.atproto.server.refreshSession`.
async fn refresh_session(
&self,
refresh_jwt: &str,
) -> Result<BlueskySession, Box<dyn std::error::Error>> {
let url = format!(
"{}/xrpc/com.atproto.server.refreshSession",
self.service_url
);
let resp = self
.client
.post(&url)
.bearer_auth(refresh_jwt)
.send()
.await?;
if !resp.status().is_success() {
// Refresh failed, create new session
return self.create_session().await;
}
let resp_body: serde_json::Value = resp.json().await?;
let access_jwt = resp_body["accessJwt"]
.as_str()
.ok_or("Missing accessJwt")?
.to_string();
let new_refresh_jwt = resp_body["refreshJwt"]
.as_str()
.ok_or("Missing refreshJwt")?
.to_string();
let did = resp_body["did"].as_str().ok_or("Missing did")?.to_string();
Ok(BlueskySession {
access_jwt,
refresh_jwt: new_refresh_jwt,
did,
created_at: Instant::now(),
})
}
/// Get a valid access JWT, creating or refreshing the session as needed.
async fn get_token(&self) -> Result<(String, String), Box<dyn std::error::Error>> {
let guard = self.session.read().await;
if let Some(ref session) = *guard {
// Sessions last ~2 hours; refresh if older than 90 minutes
if session.created_at.elapsed()
< Duration::from_secs(5400 - SESSION_REFRESH_BUFFER_SECS)
{
return Ok((session.access_jwt.clone(), session.did.clone()));
}
let refresh_jwt = session.refresh_jwt.clone();
drop(guard);
let new_session = self.refresh_session(&refresh_jwt).await?;
let token = new_session.access_jwt.clone();
let did = new_session.did.clone();
*self.session.write().await = Some(new_session);
return Ok((token, did));
}
drop(guard);
let session = self.create_session().await?;
let token = session.access_jwt.clone();
let did = session.did.clone();
*self.session.write().await = Some(session);
Ok((token, did))
}
/// Validate credentials by creating a session.
async fn validate(&self) -> Result<String, Box<dyn std::error::Error>> {
let session = self.create_session().await?;
let did = session.did.clone();
*self.session.write().await = Some(session);
Ok(did)
}
/// Create a post (skeet) via `com.atproto.repo.createRecord`.
async fn api_create_post(
&self,
text: &str,
reply_ref: Option<&serde_json::Value>,
) -> Result<(), Box<dyn std::error::Error>> {
let (token, did) = self.get_token().await?;
let url = format!("{}/xrpc/com.atproto.repo.createRecord", self.service_url);
let chunks = split_message(text, MAX_MESSAGE_LEN);
for chunk in chunks {
let now = Utc::now().format("%Y-%m-%dT%H:%M:%S%.3fZ").to_string();
let mut record = serde_json::json!({
"$type": "app.bsky.feed.post",
"text": chunk,
"createdAt": now,
});
if let Some(reply) = reply_ref {
record["reply"] = reply.clone();
}
let body = serde_json::json!({
"repo": did,
"collection": "app.bsky.feed.post",
"record": record,
});
let resp = self
.client
.post(&url)
.bearer_auth(&token)
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let resp_body = resp.text().await.unwrap_or_default();
return Err(format!("Bluesky createRecord error {status}: {resp_body}").into());
}
}
Ok(())
}
}
/// Parse a Bluesky notification into a `ChannelMessage`.
fn parse_bluesky_notification(
notification: &serde_json::Value,
own_did: &str,
) -> Option<ChannelMessage> {
let reason = notification["reason"].as_str().unwrap_or("");
// We care about mentions and replies
if reason != "mention" && reason != "reply" {
return None;
}
let author = notification.get("author")?;
let author_did = author["did"].as_str().unwrap_or("");
// Skip own notifications
if author_did == own_did {
return None;
}
let record = notification.get("record")?;
let text = record["text"].as_str().unwrap_or("");
if text.is_empty() {
return None;
}
let uri = notification["uri"].as_str().unwrap_or("").to_string();
let cid = notification["cid"].as_str().unwrap_or("").to_string();
let handle = author["handle"].as_str().unwrap_or("").to_string();
let display_name = author["displayName"]
.as_str()
.unwrap_or(&handle)
.to_string();
let indexed_at = notification["indexedAt"].as_str().unwrap_or("").to_string();
let content = if text.starts_with('/') {
let parts: Vec<&str> = text.splitn(2, ' ').collect();
let cmd_name = parts[0].trim_start_matches('/');
let args: Vec<String> = parts
.get(1)
.map(|a| a.split_whitespace().map(String::from).collect())
.unwrap_or_default();
ChannelContent::Command {
name: cmd_name.to_string(),
args,
}
} else {
ChannelContent::Text(text.to_string())
};
let mut metadata = HashMap::new();
metadata.insert("uri".to_string(), serde_json::Value::String(uri.clone()));
metadata.insert("cid".to_string(), serde_json::Value::String(cid));
metadata.insert("handle".to_string(), serde_json::Value::String(handle));
metadata.insert(
"reason".to_string(),
serde_json::Value::String(reason.to_string()),
);
metadata.insert(
"indexed_at".to_string(),
serde_json::Value::String(indexed_at),
);
// Extract reply reference if present
if let Some(reply) = record.get("reply") {
metadata.insert("reply_ref".to_string(), reply.clone());
}
Some(ChannelMessage {
channel: ChannelType::Custom("bluesky".to_string()),
platform_message_id: uri,
sender: ChannelUser {
platform_id: author_did.to_string(),
display_name,
openfang_user: None,
},
content,
target_agent: None,
timestamp: Utc::now(),
is_group: false, // Bluesky mentions are treated as direct interactions
thread_id: None,
metadata,
})
}
#[async_trait]
impl ChannelAdapter for BlueskyAdapter {
fn name(&self) -> &str {
"bluesky"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Custom("bluesky".to_string())
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
// Validate credentials
let did = self.validate().await?;
info!("Bluesky adapter authenticated as {did}");
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let service_url = self.service_url.clone();
let session = Arc::clone(&self.session);
let own_did = did;
let client = self.client.clone();
let identifier = self.identifier.clone();
let app_password = self.app_password.clone();
let mut shutdown_rx = self.shutdown_rx.clone();
tokio::spawn(async move {
let poll_interval = Duration::from_secs(POLL_INTERVAL_SECS);
let mut backoff = Duration::from_secs(1);
let mut last_seen_at: Option<String> = None;
loop {
tokio::select! {
_ = shutdown_rx.changed() => {
info!("Bluesky adapter shutting down");
break;
}
_ = tokio::time::sleep(poll_interval) => {}
}
if *shutdown_rx.borrow() {
break;
}
// Get current access token
let token = {
let guard = session.read().await;
match &*guard {
Some(s) => s.access_jwt.clone(),
None => {
// Re-create session
drop(guard);
let url =
format!("{}/xrpc/com.atproto.server.createSession", service_url);
let body = serde_json::json!({
"identifier": identifier,
"password": app_password.as_str(),
});
match client.post(&url).json(&body).send().await {
Ok(resp) => {
let resp_body: serde_json::Value =
resp.json().await.unwrap_or_default();
let tok =
resp_body["accessJwt"].as_str().unwrap_or("").to_string();
if tok.is_empty() {
warn!("Bluesky: failed to create session");
backoff = (backoff * 2).min(Duration::from_secs(60));
tokio::time::sleep(backoff).await;
continue;
}
let new_session = BlueskySession {
access_jwt: tok.clone(),
refresh_jwt: resp_body["refreshJwt"]
.as_str()
.unwrap_or("")
.to_string(),
did: resp_body["did"].as_str().unwrap_or("").to_string(),
created_at: Instant::now(),
};
*session.write().await = Some(new_session);
tok
}
Err(e) => {
warn!("Bluesky: session create error: {e}");
backoff = (backoff * 2).min(Duration::from_secs(60));
tokio::time::sleep(backoff).await;
continue;
}
}
}
}
};
// Poll notifications
let mut url = format!(
"{}/xrpc/app.bsky.notification.listNotifications?limit=25",
service_url
);
if let Some(ref seen) = last_seen_at {
url.push_str(&format!("&seenAt={}", seen));
}
let resp = match client.get(&url).bearer_auth(&token).send().await {
Ok(r) => r,
Err(e) => {
warn!("Bluesky: notification fetch error: {e}");
backoff = (backoff * 2).min(Duration::from_secs(60));
continue;
}
};
if !resp.status().is_success() {
warn!("Bluesky: notification fetch returned {}", resp.status());
if resp.status().as_u16() == 401 {
// Session expired, clear it so next iteration re-creates
*session.write().await = None;
}
continue;
}
let body: serde_json::Value = match resp.json().await {
Ok(b) => b,
Err(e) => {
warn!("Bluesky: failed to parse notifications: {e}");
continue;
}
};
let notifications = match body["notifications"].as_array() {
Some(arr) => arr,
None => continue,
};
for notif in notifications {
// Track latest indexed_at
if let Some(indexed) = notif["indexedAt"].as_str() {
if last_seen_at
.as_ref()
.map(|s| indexed > s.as_str())
.unwrap_or(true)
{
last_seen_at = Some(indexed.to_string());
}
}
if let Some(msg) = parse_bluesky_notification(notif, &own_did) {
if tx.send(msg).await.is_err() {
return;
}
}
}
// Update seen marker
if last_seen_at.is_some() {
let mark_url = format!("{}/xrpc/app.bsky.notification.updateSeen", service_url);
let mark_body = serde_json::json!({
"seenAt": Utc::now().format("%Y-%m-%dT%H:%M:%S%.3fZ").to_string(),
});
let _ = client
.post(&mark_url)
.bearer_auth(&token)
.json(&mark_body)
.send()
.await;
}
backoff = Duration::from_secs(1);
}
info!("Bluesky polling loop stopped");
});
Ok(Box::pin(tokio_stream::wrappers::ReceiverStream::new(rx)))
}
async fn send(
&self,
_user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
match content {
ChannelContent::Text(text) => {
self.api_create_post(&text, None).await?;
}
_ => {
self.api_create_post("(Unsupported content type)", None)
.await?;
}
}
Ok(())
}
async fn send_typing(&self, _user: &ChannelUser) -> Result<(), Box<dyn std::error::Error>> {
// Bluesky/AT Protocol does not support typing indicators
Ok(())
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_bluesky_adapter_creation() {
let adapter = BlueskyAdapter::new(
"alice.bsky.social".to_string(),
"app-password-123".to_string(),
);
assert_eq!(adapter.name(), "bluesky");
assert_eq!(
adapter.channel_type(),
ChannelType::Custom("bluesky".to_string())
);
}
#[test]
fn test_bluesky_default_service_url() {
let adapter = BlueskyAdapter::new("alice.bsky.social".to_string(), "pwd".to_string());
assert_eq!(adapter.service_url, "https://bsky.social");
}
#[test]
fn test_bluesky_custom_service_url() {
let adapter = BlueskyAdapter::with_service_url(
"alice.example.com".to_string(),
"pwd".to_string(),
"https://pds.example.com/".to_string(),
);
assert_eq!(adapter.service_url, "https://pds.example.com");
}
#[test]
fn test_bluesky_identifier_stored() {
let adapter = BlueskyAdapter::new("did:plc:abc123".to_string(), "pwd".to_string());
assert_eq!(adapter.identifier, "did:plc:abc123");
}
#[test]
fn test_parse_bluesky_notification_mention() {
let notif = serde_json::json!({
"uri": "at://did:plc:sender/app.bsky.feed.post/abc123",
"cid": "bafyrei...",
"author": {
"did": "did:plc:sender",
"handle": "alice.bsky.social",
"displayName": "Alice"
},
"reason": "mention",
"record": {
"text": "@bot hello there!",
"createdAt": "2024-01-01T00:00:00.000Z"
},
"indexedAt": "2024-01-01T00:00:01.000Z"
});
let msg = parse_bluesky_notification(&notif, "did:plc:bot").unwrap();
assert_eq!(msg.channel, ChannelType::Custom("bluesky".to_string()));
assert_eq!(msg.sender.display_name, "Alice");
assert_eq!(msg.sender.platform_id, "did:plc:sender");
assert!(matches!(msg.content, ChannelContent::Text(ref t) if t == "@bot hello there!"));
}
#[test]
fn test_parse_bluesky_notification_reply() {
let notif = serde_json::json!({
"uri": "at://did:plc:sender/app.bsky.feed.post/def456",
"cid": "bafyrei...",
"author": {
"did": "did:plc:sender",
"handle": "bob.bsky.social",
"displayName": "Bob"
},
"reason": "reply",
"record": {
"text": "Nice post!",
"createdAt": "2024-01-01T00:00:00.000Z",
"reply": {
"root": { "uri": "at://...", "cid": "..." },
"parent": { "uri": "at://...", "cid": "..." }
}
},
"indexedAt": "2024-01-01T00:00:01.000Z"
});
let msg = parse_bluesky_notification(&notif, "did:plc:bot").unwrap();
assert!(msg.metadata.contains_key("reply_ref"));
}
#[test]
fn test_parse_bluesky_notification_skips_own() {
let notif = serde_json::json!({
"uri": "at://did:plc:bot/app.bsky.feed.post/abc",
"cid": "...",
"author": {
"did": "did:plc:bot",
"handle": "bot.bsky.social"
},
"reason": "mention",
"record": {
"text": "self mention"
},
"indexedAt": "2024-01-01T00:00:00.000Z"
});
assert!(parse_bluesky_notification(&notif, "did:plc:bot").is_none());
}
#[test]
fn test_parse_bluesky_notification_skips_like() {
let notif = serde_json::json!({
"uri": "at://...",
"cid": "...",
"author": {
"did": "did:plc:other",
"handle": "other.bsky.social"
},
"reason": "like",
"record": {},
"indexedAt": "2024-01-01T00:00:00.000Z"
});
assert!(parse_bluesky_notification(&notif, "did:plc:bot").is_none());
}
#[test]
fn test_parse_bluesky_notification_command() {
let notif = serde_json::json!({
"uri": "at://did:plc:sender/app.bsky.feed.post/cmd1",
"cid": "...",
"author": {
"did": "did:plc:sender",
"handle": "alice.bsky.social",
"displayName": "Alice"
},
"reason": "mention",
"record": {
"text": "/status check"
},
"indexedAt": "2024-01-01T00:00:00.000Z"
});
let msg = parse_bluesky_notification(&notif, "did:plc:bot").unwrap();
match &msg.content {
ChannelContent::Command { name, args } => {
assert_eq!(name, "status");
assert_eq!(args, &["check"]);
}
other => panic!("Expected Command, got {other:?}"),
}
}
}

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425
crates/openfang-channels/src/dingtalk.rs Normal file
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//! DingTalk Robot channel adapter.
//!
//! Integrates with the DingTalk (Alibaba) custom robot API. Incoming messages
//! are received via an HTTP webhook callback server, and outbound messages are
//! posted to the robot send endpoint with HMAC-SHA256 signature verification.
use crate::types::{
split_message, ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser,
};
use async_trait::async_trait;
use chrono::Utc;
use futures::Stream;
use std::collections::HashMap;
use std::pin::Pin;
use std::sync::Arc;
use std::time::Duration;
use tokio::sync::{mpsc, watch};
use tracing::{info, warn};
use zeroize::Zeroizing;
const MAX_MESSAGE_LEN: usize = 20000;
const DINGTALK_SEND_URL: &str = "https://oapi.dingtalk.com/robot/send";
/// DingTalk Robot channel adapter.
///
/// Uses a webhook listener to receive incoming messages from DingTalk
/// conversations and posts replies via the signed Robot Send API.
pub struct DingTalkAdapter {
/// SECURITY: Robot access token is zeroized on drop.
access_token: Zeroizing<String>,
/// SECURITY: Signing secret for HMAC-SHA256 verification.
secret: Zeroizing<String>,
/// Port for the incoming webhook HTTP server.
webhook_port: u16,
/// HTTP client for outbound requests.
client: reqwest::Client,
/// Shutdown signal.
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
}
impl DingTalkAdapter {
/// Create a new DingTalk Robot adapter.
///
/// # Arguments
/// * `access_token` - Robot access token from DingTalk.
/// * `secret` - Signing secret for request verification.
/// * `webhook_port` - Local port to listen for DingTalk callbacks.
pub fn new(access_token: String, secret: String, webhook_port: u16) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
Self {
access_token: Zeroizing::new(access_token),
secret: Zeroizing::new(secret),
webhook_port,
client: reqwest::Client::new(),
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
}
}
/// Compute the HMAC-SHA256 signature for a DingTalk request.
///
/// DingTalk signature = Base64(HMAC-SHA256(secret, timestamp + "\n" + secret))
fn compute_signature(secret: &str, timestamp: i64) -> String {
use hmac::{Hmac, Mac};
use sha2::Sha256;
let string_to_sign = format!("{}\n{}", timestamp, secret);
let mut mac =
Hmac::<Sha256>::new_from_slice(secret.as_bytes()).expect("HMAC accepts any key size");
mac.update(string_to_sign.as_bytes());
let result = mac.finalize();
use base64::Engine;
base64::engine::general_purpose::STANDARD.encode(result.into_bytes())
}
/// Verify an incoming DingTalk callback signature.
fn verify_signature(secret: &str, timestamp: i64, signature: &str) -> bool {
let expected = Self::compute_signature(secret, timestamp);
// Constant-time comparison
if expected.len() != signature.len() {
return false;
}
let mut diff = 0u8;
for (a, b) in expected.bytes().zip(signature.bytes()) {
diff |= a ^ b;
}
diff == 0
}
/// Build the signed send URL with access_token, timestamp, and signature.
fn build_send_url(&self) -> String {
let timestamp = Utc::now().timestamp_millis();
let sign = Self::compute_signature(&self.secret, timestamp);
let encoded_sign = url::form_urlencoded::Serializer::new(String::new())
.append_pair("sign", &sign)
.finish();
format!(
"{}?access_token={}&timestamp={}&{}",
DINGTALK_SEND_URL,
self.access_token.as_str(),
timestamp,
encoded_sign
)
}
/// Parse a DingTalk webhook JSON body into extracted fields.
fn parse_callback(body: &serde_json::Value) -> Option<(String, String, String, String, bool)> {
let msg_type = body["msgtype"].as_str()?;
let text = match msg_type {
"text" => body["text"]["content"].as_str()?.trim().to_string(),
_ => return None,
};
if text.is_empty() {
return None;
}
let sender_id = body["senderId"].as_str().unwrap_or("unknown").to_string();
let sender_nick = body["senderNick"].as_str().unwrap_or("Unknown").to_string();
let conversation_id = body["conversationId"].as_str().unwrap_or("").to_string();
let is_group = body["conversationType"].as_str() == Some("2");
Some((text, sender_id, sender_nick, conversation_id, is_group))
}
}
#[async_trait]
impl ChannelAdapter for DingTalkAdapter {
fn name(&self) -> &str {
"dingtalk"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Custom("dingtalk".to_string())
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let port = self.webhook_port;
let secret = self.secret.clone();
let mut shutdown_rx = self.shutdown_rx.clone();
info!("DingTalk adapter starting webhook server on port {port}");
tokio::spawn(async move {
let tx_shared = Arc::new(tx);
let secret_shared = Arc::new(secret);
let app = axum::Router::new().route(
"/",
axum::routing::post({
let tx = Arc::clone(&tx_shared);
let secret = Arc::clone(&secret_shared);
move |headers: axum::http::HeaderMap,
body: axum::extract::Json<serde_json::Value>| {
let tx = Arc::clone(&tx);
let secret = Arc::clone(&secret);
async move {
// Extract timestamp and sign from headers
let timestamp_str = headers
.get("timestamp")
.and_then(|v| v.to_str().ok())
.unwrap_or("0");
let signature = headers
.get("sign")
.and_then(|v| v.to_str().ok())
.unwrap_or("");
// Verify signature
if let Ok(ts) = timestamp_str.parse::<i64>() {
if !DingTalkAdapter::verify_signature(&secret, ts, signature) {
warn!("DingTalk: invalid signature");
return axum::http::StatusCode::FORBIDDEN;
}
// Check timestamp freshness (1 hour window)
let now = Utc::now().timestamp_millis();
if (now - ts).unsigned_abs() > 3_600_000 {
warn!("DingTalk: stale timestamp");
return axum::http::StatusCode::FORBIDDEN;
}
}
if let Some((text, sender_id, sender_nick, conv_id, is_group)) =
DingTalkAdapter::parse_callback(&body)
{
let content = if text.starts_with('/') {
let parts: Vec<&str> = text.splitn(2, ' ').collect();
let cmd = parts[0].trim_start_matches('/');
let args: Vec<String> = parts
.get(1)
.map(|a| a.split_whitespace().map(String::from).collect())
.unwrap_or_default();
ChannelContent::Command {
name: cmd.to_string(),
args,
}
} else {
ChannelContent::Text(text)
};
let msg = ChannelMessage {
channel: ChannelType::Custom("dingtalk".to_string()),
platform_message_id: format!(
"dt-{}",
Utc::now().timestamp_millis()
),
sender: ChannelUser {
platform_id: sender_id,
display_name: sender_nick,
openfang_user: None,
},
content,
target_agent: None,
timestamp: Utc::now(),
is_group,
thread_id: None,
metadata: {
let mut m = HashMap::new();
m.insert(
"conversation_id".to_string(),
serde_json::Value::String(conv_id),
);
m
},
};
let _ = tx.send(msg).await;
}
axum::http::StatusCode::OK
}
}
}),
);
let addr = std::net::SocketAddr::from(([0, 0, 0, 0], port));
info!("DingTalk webhook server listening on {addr}");
let listener = match tokio::net::TcpListener::bind(addr).await {
Ok(l) => l,
Err(e) => {
warn!("DingTalk: failed to bind port {port}: {e}");
return;
}
};
let server = axum::serve(listener, app);
tokio::select! {
result = server => {
if let Err(e) = result {
warn!("DingTalk webhook server error: {e}");
}
}
_ = shutdown_rx.changed() => {
info!("DingTalk adapter shutting down");
}
}
info!("DingTalk webhook server stopped");
});
Ok(Box::pin(tokio_stream::wrappers::ReceiverStream::new(rx)))
}
async fn send(
&self,
_user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
let text = match content {
ChannelContent::Text(t) => t,
_ => "(Unsupported content type)".to_string(),
};
let chunks = split_message(&text, MAX_MESSAGE_LEN);
let num_chunks = chunks.len();
for chunk in chunks {
let url = self.build_send_url();
let body = serde_json::json!({
"msgtype": "text",
"text": {
"content": chunk,
}
});
let resp = self.client.post(&url).json(&body).send().await?;
if !resp.status().is_success() {
let status = resp.status();
let err_body = resp.text().await.unwrap_or_default();
return Err(format!("DingTalk API error {status}: {err_body}").into());
}
// DingTalk returns {"errcode": 0, "errmsg": "ok"} on success
let result: serde_json::Value = resp.json().await?;
if result["errcode"].as_i64() != Some(0) {
return Err(format!(
"DingTalk error: {}",
result["errmsg"].as_str().unwrap_or("unknown")
)
.into());
}
// Rate limit: small delay between chunks
if num_chunks > 1 {
tokio::time::sleep(Duration::from_millis(200)).await;
}
}
Ok(())
}
async fn send_typing(&self, _user: &ChannelUser) -> Result<(), Box<dyn std::error::Error>> {
// DingTalk Robot API does not support typing indicators.
Ok(())
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_dingtalk_adapter_creation() {
let adapter =
DingTalkAdapter::new("test-token".to_string(), "test-secret".to_string(), 8080);
assert_eq!(adapter.name(), "dingtalk");
assert_eq!(
adapter.channel_type(),
ChannelType::Custom("dingtalk".to_string())
);
}
#[test]
fn test_dingtalk_signature_computation() {
let timestamp: i64 = 1700000000000;
let secret = "my-secret";
let sig = DingTalkAdapter::compute_signature(secret, timestamp);
assert!(!sig.is_empty());
// Verify deterministic output
let sig2 = DingTalkAdapter::compute_signature(secret, timestamp);
assert_eq!(sig, sig2);
}
#[test]
fn test_dingtalk_signature_verification() {
let secret = "test-secret-123";
let timestamp: i64 = 1700000000000;
let sig = DingTalkAdapter::compute_signature(secret, timestamp);
assert!(DingTalkAdapter::verify_signature(secret, timestamp, &sig));
assert!(!DingTalkAdapter::verify_signature(
secret, timestamp, "bad-sig"
));
assert!(!DingTalkAdapter::verify_signature(
"wrong-secret",
timestamp,
&sig
));
}
#[test]
fn test_dingtalk_parse_callback_text() {
let body = serde_json::json!({
"msgtype": "text",
"text": { "content": "Hello bot" },
"senderId": "user123",
"senderNick": "Alice",
"conversationId": "conv456",
"conversationType": "2",
});
let result = DingTalkAdapter::parse_callback(&body);
assert!(result.is_some());
let (text, sender_id, sender_nick, conv_id, is_group) = result.unwrap();
assert_eq!(text, "Hello bot");
assert_eq!(sender_id, "user123");
assert_eq!(sender_nick, "Alice");
assert_eq!(conv_id, "conv456");
assert!(is_group);
}
#[test]
fn test_dingtalk_parse_callback_unsupported_type() {
let body = serde_json::json!({
"msgtype": "image",
"image": { "downloadCode": "abc" },
});
assert!(DingTalkAdapter::parse_callback(&body).is_none());
}
#[test]
fn test_dingtalk_parse_callback_dm() {
let body = serde_json::json!({
"msgtype": "text",
"text": { "content": "DM message" },
"senderId": "u1",
"senderNick": "Bob",
"conversationId": "c1",
"conversationType": "1",
});
let result = DingTalkAdapter::parse_callback(&body);
assert!(result.is_some());
let (_, _, _, _, is_group) = result.unwrap();
assert!(!is_group);
}
#[test]
fn test_dingtalk_send_url_contains_token_and_sign() {
let adapter = DingTalkAdapter::new("my-token".to_string(), "my-secret".to_string(), 8080);
let url = adapter.build_send_url();
assert!(url.contains("access_token=my-token"));
assert!(url.contains("timestamp="));
assert!(url.contains("sign="));
}
}

692
crates/openfang-channels/src/discord.rs Normal file
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@@ -0,0 +1,692 @@
//! Discord Gateway adapter for the OpenFang channel bridge.
//!
//! Uses Discord Gateway WebSocket (v10) for receiving messages and the REST API
//! for sending responses. No external Discord crate — just `tokio-tungstenite` + `reqwest`.
use crate::types::{
split_message, ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser,
};
use async_trait::async_trait;
use futures::{SinkExt, Stream, StreamExt};
use std::collections::HashMap;
use std::pin::Pin;
use std::sync::Arc;
use std::time::Duration;
use tokio::sync::{mpsc, watch, RwLock};
use tracing::{debug, error, info, warn};
use zeroize::Zeroizing;
const DISCORD_API_BASE: &str = "https://discord.com/api/v10";
const MAX_BACKOFF: Duration = Duration::from_secs(60);
const INITIAL_BACKOFF: Duration = Duration::from_secs(1);
const DISCORD_MSG_LIMIT: usize = 2000;
/// Discord Gateway opcodes.
mod opcode {
pub const DISPATCH: u64 = 0;
pub const HEARTBEAT: u64 = 1;
pub const IDENTIFY: u64 = 2;
pub const RESUME: u64 = 6;
pub const RECONNECT: u64 = 7;
pub const INVALID_SESSION: u64 = 9;
pub const HELLO: u64 = 10;
pub const HEARTBEAT_ACK: u64 = 11;
}
/// Discord Gateway adapter using WebSocket.
pub struct DiscordAdapter {
/// SECURITY: Bot token is zeroized on drop to prevent memory disclosure.
token: Zeroizing<String>,
client: reqwest::Client,
allowed_guilds: Vec<u64>,
intents: u64,
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
/// Bot's own user ID (populated after READY event).
bot_user_id: Arc<RwLock<Option<String>>>,
/// Session ID for resume (populated after READY event).
session_id: Arc<RwLock<Option<String>>>,
/// Resume gateway URL.
resume_gateway_url: Arc<RwLock<Option<String>>>,
}
impl DiscordAdapter {
pub fn new(token: String, allowed_guilds: Vec<u64>, intents: u64) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
Self {
token: Zeroizing::new(token),
client: reqwest::Client::new(),
allowed_guilds,
intents,
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
bot_user_id: Arc::new(RwLock::new(None)),
session_id: Arc::new(RwLock::new(None)),
resume_gateway_url: Arc::new(RwLock::new(None)),
}
}
/// Get the WebSocket gateway URL from the Discord API.
async fn get_gateway_url(&self) -> Result<String, Box<dyn std::error::Error>> {
let url = format!("{DISCORD_API_BASE}/gateway/bot");
let resp: serde_json::Value = self
.client
.get(&url)
.header("Authorization", format!("Bot {}", self.token.as_str()))
.send()
.await?
.json()
.await?;
let ws_url = resp["url"]
.as_str()
.ok_or("Missing 'url' in gateway response")?;
Ok(format!("{ws_url}/?v=10&encoding=json"))
}
/// Send a message to a Discord channel via REST API.
async fn api_send_message(
&self,
channel_id: &str,
text: &str,
) -> Result<(), Box<dyn std::error::Error>> {
let url = format!("{DISCORD_API_BASE}/channels/{channel_id}/messages");
let chunks = split_message(text, DISCORD_MSG_LIMIT);
for chunk in chunks {
let body = serde_json::json!({ "content": chunk });
let resp = self
.client
.post(&url)
.header("Authorization", format!("Bot {}", self.token.as_str()))
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let body_text = resp.text().await.unwrap_or_default();
warn!("Discord sendMessage failed: {body_text}");
}
}
Ok(())
}
/// Send typing indicator to a Discord channel.
async fn api_send_typing(&self, channel_id: &str) -> Result<(), Box<dyn std::error::Error>> {
let url = format!("{DISCORD_API_BASE}/channels/{channel_id}/typing");
let _ = self
.client
.post(&url)
.header("Authorization", format!("Bot {}", self.token.as_str()))
.send()
.await?;
Ok(())
}
}
#[async_trait]
impl ChannelAdapter for DiscordAdapter {
fn name(&self) -> &str {
"discord"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Discord
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
let gateway_url = self.get_gateway_url().await?;
info!("Discord gateway URL obtained");
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let token = self.token.clone();
let intents = self.intents;
let allowed_guilds = self.allowed_guilds.clone();
let bot_user_id = self.bot_user_id.clone();
let session_id_store = self.session_id.clone();
let resume_url_store = self.resume_gateway_url.clone();
let mut shutdown = self.shutdown_rx.clone();
tokio::spawn(async move {
let mut backoff = INITIAL_BACKOFF;
let mut connect_url = gateway_url;
// Sequence persists across reconnections for RESUME
let sequence: Arc<RwLock<Option<u64>>> = Arc::new(RwLock::new(None));
loop {
if *shutdown.borrow() {
break;
}
info!("Connecting to Discord gateway...");
let ws_result = tokio_tungstenite::connect_async(&connect_url).await;
let ws_stream = match ws_result {
Ok((stream, _)) => stream,
Err(e) => {
warn!("Discord gateway connection failed: {e}, retrying in {backoff:?}");
tokio::time::sleep(backoff).await;
backoff = (backoff * 2).min(MAX_BACKOFF);
continue;
}
};
backoff = INITIAL_BACKOFF;
info!("Discord gateway connected");
let (mut ws_tx, mut ws_rx) = ws_stream.split();
let mut _heartbeat_interval: Option<u64> = None;
// Inner message loop — returns true if we should reconnect
let should_reconnect = 'inner: loop {
let msg = tokio::select! {
msg = ws_rx.next() => msg,
_ = shutdown.changed() => {
if *shutdown.borrow() {
info!("Discord shutdown requested");
let _ = ws_tx.close().await;
return;
}
continue;
}
};
let msg = match msg {
Some(Ok(m)) => m,
Some(Err(e)) => {
warn!("Discord WebSocket error: {e}");
break 'inner true;
}
None => {
info!("Discord WebSocket closed");
break 'inner true;
}
};
let text = match msg {
tokio_tungstenite::tungstenite::Message::Text(t) => t,
tokio_tungstenite::tungstenite::Message::Close(_) => {
info!("Discord gateway closed by server");
break 'inner true;
}
_ => continue,
};
let payload: serde_json::Value = match serde_json::from_str(&text) {
Ok(v) => v,
Err(e) => {
warn!("Discord: failed to parse gateway message: {e}");
continue;
}
};
let op = payload["op"].as_u64().unwrap_or(999);
// Update sequence number
if let Some(s) = payload["s"].as_u64() {
*sequence.write().await = Some(s);
}
match op {
opcode::HELLO => {
let interval =
payload["d"]["heartbeat_interval"].as_u64().unwrap_or(45000);
_heartbeat_interval = Some(interval);
debug!("Discord HELLO: heartbeat_interval={interval}ms");
// Try RESUME if we have a session, otherwise IDENTIFY
let has_session = session_id_store.read().await.is_some();
let has_seq = sequence.read().await.is_some();
let gateway_msg = if has_session && has_seq {
let sid = session_id_store.read().await.clone().unwrap();
let seq = *sequence.read().await;
info!("Discord: sending RESUME (session={sid})");
serde_json::json!({
"op": opcode::RESUME,
"d": {
"token": token.as_str(),
"session_id": sid,
"seq": seq
}
})
} else {
info!("Discord: sending IDENTIFY");
serde_json::json!({
"op": opcode::IDENTIFY,
"d": {
"token": token.as_str(),
"intents": intents,
"properties": {
"os": "linux",
"browser": "openfang",
"device": "openfang"
}
}
})
};
if let Err(e) = ws_tx
.send(tokio_tungstenite::tungstenite::Message::Text(
serde_json::to_string(&gateway_msg).unwrap(),
))
.await
{
error!("Discord: failed to send IDENTIFY/RESUME: {e}");
break 'inner true;
}
}
opcode::DISPATCH => {
let event_name = payload["t"].as_str().unwrap_or("");
let d = &payload["d"];
match event_name {
"READY" => {
let user_id =
d["user"]["id"].as_str().unwrap_or("").to_string();
let username =
d["user"]["username"].as_str().unwrap_or("unknown");
let sid = d["session_id"].as_str().unwrap_or("").to_string();
let resume_url =
d["resume_gateway_url"].as_str().unwrap_or("").to_string();
*bot_user_id.write().await = Some(user_id.clone());
*session_id_store.write().await = Some(sid);
if !resume_url.is_empty() {
*resume_url_store.write().await = Some(resume_url);
}
info!("Discord bot ready: {username} ({user_id})");
}
"MESSAGE_CREATE" | "MESSAGE_UPDATE" => {
if let Some(msg) =
parse_discord_message(d, &bot_user_id, &allowed_guilds)
.await
{
debug!(
"Discord {event_name} from {}: {:?}",
msg.sender.display_name, msg.content
);
if tx.send(msg).await.is_err() {
return;
}
}
}
"RESUMED" => {
info!("Discord session resumed successfully");
}
_ => {
debug!("Discord event: {event_name}");
}
}
}
opcode::HEARTBEAT => {
// Server requests immediate heartbeat
let seq = *sequence.read().await;
let hb = serde_json::json!({ "op": opcode::HEARTBEAT, "d": seq });
let _ = ws_tx
.send(tokio_tungstenite::tungstenite::Message::Text(
serde_json::to_string(&hb).unwrap(),
))
.await;
}
opcode::HEARTBEAT_ACK => {
debug!("Discord heartbeat ACK received");
}
opcode::RECONNECT => {
info!("Discord: server requested reconnect");
break 'inner true;
}
opcode::INVALID_SESSION => {
let resumable = payload["d"].as_bool().unwrap_or(false);
if resumable {
info!("Discord: invalid session (resumable)");
} else {
info!("Discord: invalid session (not resumable), clearing session");
*session_id_store.write().await = None;
*sequence.write().await = None;
}
break 'inner true;
}
_ => {
debug!("Discord: unknown opcode {op}");
}
}
};
if !should_reconnect || *shutdown.borrow() {
break;
}
// Try resume URL if available
if let Some(ref url) = *resume_url_store.read().await {
connect_url = format!("{url}/?v=10&encoding=json");
}
warn!("Discord: reconnecting in {backoff:?}");
tokio::time::sleep(backoff).await;
backoff = (backoff * 2).min(MAX_BACKOFF);
}
info!("Discord gateway loop stopped");
});
let stream = tokio_stream::wrappers::ReceiverStream::new(rx);
Ok(Box::pin(stream))
}
async fn send(
&self,
user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
// platform_id is the channel_id for Discord
let channel_id = &user.platform_id;
match content {
ChannelContent::Text(text) => {
self.api_send_message(channel_id, &text).await?;
}
_ => {
self.api_send_message(channel_id, "(Unsupported content type)")
.await?;
}
}
Ok(())
}
async fn send_typing(&self, user: &ChannelUser) -> Result<(), Box<dyn std::error::Error>> {
self.api_send_typing(&user.platform_id).await
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
/// Parse a Discord MESSAGE_CREATE or MESSAGE_UPDATE payload into a `ChannelMessage`.
async fn parse_discord_message(
d: &serde_json::Value,
bot_user_id: &Arc<RwLock<Option<String>>>,
allowed_guilds: &[u64],
) -> Option<ChannelMessage> {
let author = d.get("author")?;
let author_id = author["id"].as_str()?;
// Filter out bot's own messages
if let Some(ref bid) = *bot_user_id.read().await {
if author_id == bid {
return None;
}
}
// Filter out other bots
if author["bot"].as_bool() == Some(true) {
return None;
}
// Filter by allowed guilds
if !allowed_guilds.is_empty() {
if let Some(guild_id) = d["guild_id"].as_str() {
let gid: u64 = guild_id.parse().unwrap_or(0);
if !allowed_guilds.contains(&gid) {
return None;
}
}
}
let content_text = d["content"].as_str().unwrap_or("");
if content_text.is_empty() {
return None;
}
let channel_id = d["channel_id"].as_str()?;
let message_id = d["id"].as_str().unwrap_or("0");
let username = author["username"].as_str().unwrap_or("Unknown");
let discriminator = author["discriminator"].as_str().unwrap_or("0000");
let display_name = if discriminator == "0" {
username.to_string()
} else {
format!("{username}#{discriminator}")
};
let timestamp = d["timestamp"]
.as_str()
.and_then(|ts| chrono::DateTime::parse_from_rfc3339(ts).ok())
.map(|dt| dt.with_timezone(&chrono::Utc))
.unwrap_or_else(chrono::Utc::now);
// Parse commands (messages starting with /)
let content = if content_text.starts_with('/') {
let parts: Vec<&str> = content_text.splitn(2, ' ').collect();
let cmd_name = &parts[0][1..];
let args = if parts.len() > 1 {
parts[1].split_whitespace().map(String::from).collect()
} else {
vec![]
};
ChannelContent::Command {
name: cmd_name.to_string(),
args,
}
} else {
ChannelContent::Text(content_text.to_string())
};
Some(ChannelMessage {
channel: ChannelType::Discord,
platform_message_id: message_id.to_string(),
sender: ChannelUser {
platform_id: channel_id.to_string(),
display_name,
openfang_user: None,
},
content,
target_agent: None,
timestamp,
is_group: true,
thread_id: None,
metadata: HashMap::new(),
})
}
#[cfg(test)]
mod tests {
use super::*;
#[tokio::test]
async fn test_parse_discord_message_basic() {
let bot_id = Arc::new(RwLock::new(Some("bot123".to_string())));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "Hello agent!",
"author": {
"id": "user456",
"username": "alice",
"discriminator": "0",
"bot": false
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await.unwrap();
assert_eq!(msg.channel, ChannelType::Discord);
assert_eq!(msg.sender.display_name, "alice");
assert_eq!(msg.sender.platform_id, "ch1");
assert!(matches!(msg.content, ChannelContent::Text(ref t) if t == "Hello agent!"));
}
#[tokio::test]
async fn test_parse_discord_message_filters_bot() {
let bot_id = Arc::new(RwLock::new(Some("bot123".to_string())));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "My own message",
"author": {
"id": "bot123",
"username": "openfang",
"discriminator": "0"
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await;
assert!(msg.is_none());
}
#[tokio::test]
async fn test_parse_discord_message_filters_other_bots() {
let bot_id = Arc::new(RwLock::new(Some("bot123".to_string())));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "Bot message",
"author": {
"id": "other_bot",
"username": "somebot",
"discriminator": "0",
"bot": true
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await;
assert!(msg.is_none());
}
#[tokio::test]
async fn test_parse_discord_message_guild_filter() {
let bot_id = Arc::new(RwLock::new(Some("bot123".to_string())));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"guild_id": "999",
"content": "Hello",
"author": {
"id": "user1",
"username": "bob",
"discriminator": "0"
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
// Not in allowed guilds
let msg = parse_discord_message(&d, &bot_id, &[111, 222]).await;
assert!(msg.is_none());
// In allowed guilds
let msg = parse_discord_message(&d, &bot_id, &[999]).await;
assert!(msg.is_some());
}
#[tokio::test]
async fn test_parse_discord_command() {
let bot_id = Arc::new(RwLock::new(None));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "/agent hello-world",
"author": {
"id": "user1",
"username": "alice",
"discriminator": "0"
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await.unwrap();
match &msg.content {
ChannelContent::Command { name, args } => {
assert_eq!(name, "agent");
assert_eq!(args, &["hello-world"]);
}
other => panic!("Expected Command, got {other:?}"),
}
}
#[tokio::test]
async fn test_parse_discord_empty_content() {
let bot_id = Arc::new(RwLock::new(None));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "",
"author": {
"id": "user1",
"username": "alice",
"discriminator": "0"
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await;
assert!(msg.is_none());
}
#[tokio::test]
async fn test_parse_discord_discriminator() {
let bot_id = Arc::new(RwLock::new(None));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "Hi",
"author": {
"id": "user1",
"username": "alice",
"discriminator": "1234"
},
"timestamp": "2024-01-01T00:00:00+00:00"
});
let msg = parse_discord_message(&d, &bot_id, &[]).await.unwrap();
assert_eq!(msg.sender.display_name, "alice#1234");
}
#[tokio::test]
async fn test_parse_discord_message_update() {
let bot_id = Arc::new(RwLock::new(Some("bot123".to_string())));
let d = serde_json::json!({
"id": "msg1",
"channel_id": "ch1",
"content": "Edited message content",
"author": {
"id": "user456",
"username": "alice",
"discriminator": "0",
"bot": false
},
"timestamp": "2024-01-01T00:00:00+00:00",
"edited_timestamp": "2024-01-01T00:01:00+00:00"
});
// MESSAGE_UPDATE uses the same parse function as MESSAGE_CREATE
let msg = parse_discord_message(&d, &bot_id, &[]).await.unwrap();
assert_eq!(msg.channel, ChannelType::Discord);
assert!(
matches!(msg.content, ChannelContent::Text(ref t) if t == "Edited message content")
);
}
#[test]
fn test_discord_adapter_creation() {
let adapter = DiscordAdapter::new("test-token".to_string(), vec![123, 456], 33280);
assert_eq!(adapter.name(), "discord");
assert_eq!(adapter.channel_type(), ChannelType::Discord);
}
}

469
crates/openfang-channels/src/discourse.rs Normal file
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//! Discourse channel adapter.
//!
//! Integrates with the Discourse forum REST API. Uses long-polling on
//! `posts.json` to receive new posts and creates replies via the same API.
//! Authentication uses the `Api-Key` and `Api-Username` headers.
use crate::types::{
split_message, ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser,
};
use async_trait::async_trait;
use chrono::Utc;
use futures::Stream;
use std::collections::HashMap;
use std::pin::Pin;
use std::sync::Arc;
use std::time::Duration;
use tokio::sync::{mpsc, watch, RwLock};
use tracing::{info, warn};
use zeroize::Zeroizing;
const POLL_INTERVAL_SECS: u64 = 10;
const MAX_MESSAGE_LEN: usize = 32000;
/// Discourse forum channel adapter.
///
/// Polls the Discourse `/posts.json` endpoint for new posts and creates
/// replies via `POST /posts.json`. Filters posts by category if configured.
pub struct DiscourseAdapter {
/// Base URL of the Discourse instance (e.g., `"https://forum.example.com"`).
base_url: String,
/// SECURITY: API key is zeroized on drop.
api_key: Zeroizing<String>,
/// Username associated with the API key.
api_username: String,
/// Category slugs to filter (empty = all categories).
categories: Vec<String>,
/// HTTP client.
client: reqwest::Client,
/// Shutdown signal.
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
/// Last seen post ID (for incremental polling).
last_post_id: Arc<RwLock<u64>>,
}
impl DiscourseAdapter {
/// Create a new Discourse adapter.
///
/// # Arguments
/// * `base_url` - Base URL of the Discourse instance.
/// * `api_key` - Discourse API key (admin or user-scoped).
/// * `api_username` - Username for the API key (usually "system" or a bot account).
/// * `categories` - Category slugs to listen to (empty = all).
pub fn new(
base_url: String,
api_key: String,
api_username: String,
categories: Vec<String>,
) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
let base_url = base_url.trim_end_matches('/').to_string();
Self {
base_url,
api_key: Zeroizing::new(api_key),
api_username,
categories,
client: reqwest::Client::new(),
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
last_post_id: Arc::new(RwLock::new(0)),
}
}
/// Add Discourse API auth headers to a request builder.
fn auth_headers(&self, builder: reqwest::RequestBuilder) -> reqwest::RequestBuilder {
builder
.header("Api-Key", self.api_key.as_str())
.header("Api-Username", &self.api_username)
}
/// Validate credentials by calling `/session/current.json`.
async fn validate(&self) -> Result<String, Box<dyn std::error::Error>> {
let url = format!("{}/session/current.json", self.base_url);
let resp = self.auth_headers(self.client.get(&url)).send().await?;
if !resp.status().is_success() {
return Err(format!("Discourse auth failed (HTTP {})", resp.status()).into());
}
let body: serde_json::Value = resp.json().await?;
let username = body["current_user"]["username"]
.as_str()
.unwrap_or(&self.api_username)
.to_string();
Ok(username)
}
/// Fetch the latest posts since `before_id`.
async fn fetch_latest_posts(
client: &reqwest::Client,
base_url: &str,
api_key: &str,
api_username: &str,
before_id: u64,
) -> Result<Vec<serde_json::Value>, Box<dyn std::error::Error>> {
let url = if before_id > 0 {
format!("{}/posts.json?before={}", base_url, before_id)
} else {
format!("{}/posts.json", base_url)
};
let resp = client
.get(&url)
.header("Api-Key", api_key)
.header("Api-Username", api_username)
.send()
.await?;
if !resp.status().is_success() {
return Err(format!("Discourse: HTTP {}", resp.status()).into());
}
let body: serde_json::Value = resp.json().await?;
let posts = body["latest_posts"].as_array().cloned().unwrap_or_default();
Ok(posts)
}
/// Create a reply to a topic.
async fn create_post(
&self,
topic_id: u64,
raw: &str,
) -> Result<(), Box<dyn std::error::Error>> {
let url = format!("{}/posts.json", self.base_url);
let chunks = split_message(raw, MAX_MESSAGE_LEN);
for chunk in chunks {
let body = serde_json::json!({
"topic_id": topic_id,
"raw": chunk,
});
let resp = self
.auth_headers(self.client.post(&url))
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let err_body = resp.text().await.unwrap_or_default();
return Err(format!("Discourse API error {status}: {err_body}").into());
}
}
Ok(())
}
/// Check if a category slug matches the filter.
#[allow(dead_code)]
fn matches_category(&self, category_slug: &str) -> bool {
self.categories.is_empty() || self.categories.iter().any(|c| c == category_slug)
}
}
#[async_trait]
impl ChannelAdapter for DiscourseAdapter {
fn name(&self) -> &str {
"discourse"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Custom("discourse".to_string())
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
let own_username = self.validate().await?;
info!("Discourse adapter authenticated as {own_username}");
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let base_url = self.base_url.clone();
let api_key = self.api_key.clone();
let api_username = self.api_username.clone();
let categories = self.categories.clone();
let client = self.client.clone();
let last_post_id = Arc::clone(&self.last_post_id);
let mut shutdown_rx = self.shutdown_rx.clone();
// Initialize last_post_id to skip historical posts
{
let posts = Self::fetch_latest_posts(&client, &base_url, &api_key, &api_username, 0)
.await
.unwrap_or_default();
if let Some(latest) = posts.first() {
let id = latest["id"].as_u64().unwrap_or(0);
*last_post_id.write().await = id;
}
}
let poll_interval = Duration::from_secs(POLL_INTERVAL_SECS);
tokio::spawn(async move {
let mut backoff = Duration::from_secs(1);
loop {
tokio::select! {
_ = shutdown_rx.changed() => {
if *shutdown_rx.borrow() {
info!("Discourse adapter shutting down");
break;
}
}
_ = tokio::time::sleep(poll_interval) => {}
}
if *shutdown_rx.borrow() {
break;
}
let current_last = *last_post_id.read().await;
let poll_result =
Self::fetch_latest_posts(&client, &base_url, &api_key, &api_username, 0)
.await
.map_err(|e| e.to_string());
let posts = match poll_result {
Ok(p) => {
backoff = Duration::from_secs(1);
p
}
Err(msg) => {
warn!("Discourse: poll error: {msg}, backing off {backoff:?}");
tokio::time::sleep(backoff).await;
backoff = (backoff * 2).min(Duration::from_secs(120));
continue;
}
};
let mut max_id = current_last;
// Process posts in chronological order (API returns newest first)
for post in posts.iter().rev() {
let post_id = post["id"].as_u64().unwrap_or(0);
if post_id <= current_last {
continue;
}
let username = post["username"].as_str().unwrap_or("unknown");
// Skip own posts
if username == own_username || username == api_username {
continue;
}
let raw = post["raw"].as_str().unwrap_or("");
if raw.is_empty() {
continue;
}
// Category filter
let category_slug = post["category_slug"].as_str().unwrap_or("");
if !categories.is_empty() && !categories.iter().any(|c| c == category_slug) {
continue;
}
let topic_id = post["topic_id"].as_u64().unwrap_or(0);
let topic_slug = post["topic_slug"].as_str().unwrap_or("").to_string();
let post_number = post["post_number"].as_u64().unwrap_or(0);
let display_name = post["display_username"]
.as_str()
.unwrap_or(username)
.to_string();
if post_id > max_id {
max_id = post_id;
}
let content = if raw.starts_with('/') {
let parts: Vec<&str> = raw.splitn(2, ' ').collect();
let cmd = parts[0].trim_start_matches('/');
let args: Vec<String> = parts
.get(1)
.map(|a| a.split_whitespace().map(String::from).collect())
.unwrap_or_default();
ChannelContent::Command {
name: cmd.to_string(),
args,
}
} else {
ChannelContent::Text(raw.to_string())
};
let msg = ChannelMessage {
channel: ChannelType::Custom("discourse".to_string()),
platform_message_id: format!("discourse-post-{}", post_id),
sender: ChannelUser {
platform_id: username.to_string(),
display_name,
openfang_user: None,
},
content,
target_agent: None,
timestamp: Utc::now(),
is_group: true,
thread_id: Some(format!("topic-{}", topic_id)),
metadata: {
let mut m = HashMap::new();
m.insert(
"topic_id".to_string(),
serde_json::Value::Number(topic_id.into()),
);
m.insert(
"topic_slug".to_string(),
serde_json::Value::String(topic_slug),
);
m.insert(
"post_number".to_string(),
serde_json::Value::Number(post_number.into()),
);
m.insert(
"category".to_string(),
serde_json::Value::String(category_slug.to_string()),
);
m
},
};
if tx.send(msg).await.is_err() {
return;
}
}
if max_id > current_last {
*last_post_id.write().await = max_id;
}
}
info!("Discourse polling loop stopped");
});
Ok(Box::pin(tokio_stream::wrappers::ReceiverStream::new(rx)))
}
async fn send(
&self,
user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
let text = match content {
ChannelContent::Text(t) => t,
_ => "(Unsupported content type)".to_string(),
};
// Extract topic_id from user.platform_id or metadata
// Convention: platform_id holds the topic_id for replies
let topic_id: u64 = user.platform_id.parse().unwrap_or(0);
if topic_id == 0 {
return Err("Discourse: cannot send without topic_id in platform_id".into());
}
self.create_post(topic_id, &text).await
}
async fn send_in_thread(
&self,
_user: &ChannelUser,
content: ChannelContent,
thread_id: &str,
) -> Result<(), Box<dyn std::error::Error>> {
let text = match content {
ChannelContent::Text(t) => t,
_ => "(Unsupported content type)".to_string(),
};
// thread_id format: "topic-{id}"
let topic_id: u64 = thread_id
.strip_prefix("topic-")
.unwrap_or(thread_id)
.parse()
.map_err(|_| "Discourse: invalid thread_id format")?;
self.create_post(topic_id, &text).await
}
async fn send_typing(&self, _user: &ChannelUser) -> Result<(), Box<dyn std::error::Error>> {
// Discourse does not have typing indicators.
Ok(())
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_discourse_adapter_creation() {
let adapter = DiscourseAdapter::new(
"https://forum.example.com".to_string(),
"api-key-123".to_string(),
"system".to_string(),
vec!["general".to_string()],
);
assert_eq!(adapter.name(), "discourse");
assert_eq!(
adapter.channel_type(),
ChannelType::Custom("discourse".to_string())
);
}
#[test]
fn test_discourse_url_normalization() {
let adapter = DiscourseAdapter::new(
"https://forum.example.com/".to_string(),
"key".to_string(),
"bot".to_string(),
vec![],
);
assert_eq!(adapter.base_url, "https://forum.example.com");
}
#[test]
fn test_discourse_category_filter() {
let adapter = DiscourseAdapter::new(
"https://forum.example.com".to_string(),
"key".to_string(),
"bot".to_string(),
vec!["dev".to_string(), "support".to_string()],
);
assert!(adapter.matches_category("dev"));
assert!(adapter.matches_category("support"));
assert!(!adapter.matches_category("random"));
}
#[test]
fn test_discourse_category_filter_empty_allows_all() {
let adapter = DiscourseAdapter::new(
"https://forum.example.com".to_string(),
"key".to_string(),
"bot".to_string(),
vec![],
);
assert!(adapter.matches_category("anything"));
}
#[test]
fn test_discourse_auth_headers() {
let adapter = DiscourseAdapter::new(
"https://forum.example.com".to_string(),
"my-api-key".to_string(),
"bot-user".to_string(),
vec![],
);
let builder = adapter.client.get("https://example.com");
let builder = adapter.auth_headers(builder);
let request = builder.build().unwrap();
assert_eq!(request.headers().get("Api-Key").unwrap(), "my-api-key");
assert_eq!(request.headers().get("Api-Username").unwrap(), "bot-user");
}
}

601
crates/openfang-channels/src/email.rs Normal file
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//! Email channel adapter (IMAP + SMTP).
//!
//! Polls IMAP for new emails and sends responses via SMTP using `lettre`.
//! Uses the subject line for agent routing (e.g., "\[coder\] Fix this bug").
use crate::types::{ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser};
use async_trait::async_trait;
use chrono::Utc;
use dashmap::DashMap;
use futures::Stream;
use lettre::message::Mailbox;
use lettre::transport::smtp::authentication::Credentials;
use lettre::AsyncSmtpTransport;
use lettre::AsyncTransport;
use lettre::Tokio1Executor;
use std::pin::Pin;
use std::sync::Arc;
use std::time::Duration;
use tokio::sync::{mpsc, watch};
use tracing::{debug, error, info, warn};
use zeroize::Zeroizing;
/// Reply context for email threading (In-Reply-To / Subject continuity).
#[derive(Debug, Clone)]
struct ReplyCtx {
subject: String,
message_id: String,
}
/// Email channel adapter using IMAP for receiving and SMTP for sending.
pub struct EmailAdapter {
/// IMAP server host.
imap_host: String,
/// IMAP port (993 for TLS).
imap_port: u16,
/// SMTP server host.
smtp_host: String,
/// SMTP port (587 for STARTTLS, 465 for implicit TLS).
smtp_port: u16,
/// Email address (used for both IMAP and SMTP).
username: String,
/// SECURITY: Password is zeroized on drop.
password: Zeroizing<String>,
/// How often to check for new emails.
poll_interval: Duration,
/// Which IMAP folders to monitor.
folders: Vec<String>,
/// Only process emails from these senders (empty = all).
allowed_senders: Vec<String>,
/// Shutdown signal.
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
/// Tracks reply context per sender for email threading.
reply_ctx: Arc<DashMap<String, ReplyCtx>>,
}
impl EmailAdapter {
/// Create a new email adapter.
#[allow(clippy::too_many_arguments)]
pub fn new(
imap_host: String,
imap_port: u16,
smtp_host: String,
smtp_port: u16,
username: String,
password: String,
poll_interval_secs: u64,
folders: Vec<String>,
allowed_senders: Vec<String>,
) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
Self {
imap_host,
imap_port,
smtp_host,
smtp_port,
username,
password: Zeroizing::new(password),
poll_interval: Duration::from_secs(poll_interval_secs),
folders: if folders.is_empty() {
vec!["INBOX".to_string()]
} else {
folders
},
allowed_senders,
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
reply_ctx: Arc::new(DashMap::new()),
}
}
/// Check if a sender is in the allowlist (empty = allow all). Used in tests.
#[allow(dead_code)]
fn is_allowed_sender(&self, sender: &str) -> bool {
self.allowed_senders.is_empty() || self.allowed_senders.iter().any(|s| sender.contains(s))
}
/// Extract agent name from subject line brackets, e.g., "[coder] Fix the bug" -> Some("coder")
fn extract_agent_from_subject(subject: &str) -> Option<String> {
let subject = subject.trim();
if subject.starts_with('[') {
if let Some(end) = subject.find(']') {
let agent = &subject[1..end];
if !agent.is_empty() {
return Some(agent.to_string());
}
}
}
None
}
/// Strip the agent tag from a subject line.
fn strip_agent_tag(subject: &str) -> String {
let subject = subject.trim();
if subject.starts_with('[') {
if let Some(end) = subject.find(']') {
return subject[end + 1..].trim().to_string();
}
}
subject.to_string()
}
/// Build an async SMTP transport for sending emails.
async fn build_smtp_transport(
&self,
) -> Result<AsyncSmtpTransport<Tokio1Executor>, Box<dyn std::error::Error>> {
let creds =
Credentials::new(self.username.clone(), self.password.as_str().to_string());
let transport = if self.smtp_port == 465 {
// Implicit TLS (port 465)
AsyncSmtpTransport::<Tokio1Executor>::relay(&self.smtp_host)?
.port(self.smtp_port)
.credentials(creds)
.build()
} else {
// STARTTLS (port 587 or other)
AsyncSmtpTransport::<Tokio1Executor>::starttls_relay(&self.smtp_host)?
.port(self.smtp_port)
.credentials(creds)
.build()
};
Ok(transport)
}
}
/// Extract `user@domain` from a potentially formatted email string like `"Name <user@domain>"`.
fn extract_email_addr(raw: &str) -> String {
let raw = raw.trim();
if let Some(start) = raw.find('<') {
if let Some(end) = raw.find('>') {
if end > start {
return raw[start + 1..end].trim().to_string();
}
}
}
raw.to_string()
}
/// Get a specific header value from a parsed email.
fn get_header(parsed: &mailparse::ParsedMail<'_>, name: &str) -> Option<String> {
parsed
.headers
.iter()
.find(|h| h.get_key().eq_ignore_ascii_case(name))
.map(|h| h.get_value())
}
/// Extract the text/plain body from a parsed email (handles multipart).
fn extract_text_body(parsed: &mailparse::ParsedMail<'_>) -> String {
if parsed.subparts.is_empty() {
return parsed.get_body().unwrap_or_default();
}
// Walk subparts looking for text/plain
for part in &parsed.subparts {
let ct = part.ctype.mimetype.to_lowercase();
if ct == "text/plain" {
return part.get_body().unwrap_or_default();
}
}
// Fallback: first subpart body
parsed
.subparts
.first()
.and_then(|p| p.get_body().ok())
.unwrap_or_default()
}
/// Fetch unseen emails from IMAP using blocking I/O.
/// Returns a Vec of (from_addr, subject, message_id, body).
fn fetch_unseen_emails(
host: &str,
port: u16,
username: &str,
password: &str,
folders: &[String],
) -> Result<Vec<(String, String, String, String)>, String> {
let tls = native_tls::TlsConnector::builder()
.build()
.map_err(|e| format!("TLS connector error: {e}"))?;
let client = imap::connect((host, port), host, &tls)
.map_err(|e| format!("IMAP connect failed: {e}"))?;
let mut session = client
.login(username, password)
.map_err(|(e, _)| format!("IMAP login failed: {e}"))?;
let mut results = Vec::new();
for folder in folders {
if let Err(e) = session.select(folder) {
warn!(folder, error = %e, "IMAP SELECT failed, skipping folder");
continue;
}
let uids = match session.uid_search("UNSEEN") {
Ok(uids) => uids,
Err(e) => {
warn!(folder, error = %e, "IMAP SEARCH UNSEEN failed");
continue;
}
};
if uids.is_empty() {
debug!(folder, "No unseen emails");
continue;
}
// Fetch in batches of up to 50 to avoid huge responses
let uid_list: Vec<u32> = uids.into_iter().take(50).collect();
let uid_set: String = uid_list
.iter()
.map(|u| u.to_string())
.collect::<Vec<_>>()
.join(",");
let fetches = match session.uid_fetch(&uid_set, "RFC822") {
Ok(f) => f,
Err(e) => {
warn!(folder, error = %e, "IMAP FETCH failed");
continue;
}
};
for fetch in fetches.iter() {
let body_bytes = match fetch.body() {
Some(b) => b,
None => continue,
};
let parsed = match mailparse::parse_mail(body_bytes) {
Ok(p) => p,
Err(e) => {
warn!(error = %e, "Failed to parse email");
continue;
}
};
let from = get_header(&parsed, "From").unwrap_or_default();
let subject = get_header(&parsed, "Subject").unwrap_or_default();
let message_id = get_header(&parsed, "Message-ID").unwrap_or_default();
let text_body = extract_text_body(&parsed);
let from_addr = extract_email_addr(&from);
results.push((from_addr, subject, message_id, text_body));
}
// Mark fetched messages as Seen
if let Err(e) = session.uid_store(&uid_set, "+FLAGS (\\Seen)") {
warn!(error = %e, "Failed to mark emails as Seen");
}
}
let _ = session.logout();
Ok(results)
}
#[async_trait]
impl ChannelAdapter for EmailAdapter {
fn name(&self) -> &str {
"email"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Email
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let poll_interval = self.poll_interval;
let imap_host = self.imap_host.clone();
let imap_port = self.imap_port;
let username = self.username.clone();
let password = self.password.clone();
let folders = self.folders.clone();
let allowed_senders = self.allowed_senders.clone();
let mut shutdown_rx = self.shutdown_rx.clone();
let reply_ctx = self.reply_ctx.clone();
info!(
"Starting email adapter (IMAP: {}:{}, SMTP: {}:{}, polling every {:?})",
imap_host, imap_port, self.smtp_host, self.smtp_port, poll_interval
);
tokio::spawn(async move {
loop {
tokio::select! {
_ = shutdown_rx.changed() => {
info!("Email adapter shutting down");
break;
}
_ = tokio::time::sleep(poll_interval) => {}
}
// IMAP operations are blocking I/O — run in spawn_blocking
let host = imap_host.clone();
let port = imap_port;
let user = username.clone();
let pass = password.clone();
let fldrs = folders.clone();
let emails = tokio::task::spawn_blocking(move || {
fetch_unseen_emails(&host, port, &user, pass.as_str(), &fldrs)
})
.await;
let emails = match emails {
Ok(Ok(emails)) => emails,
Ok(Err(e)) => {
error!("IMAP poll error: {e}");
continue;
}
Err(e) => {
error!("IMAP spawn_blocking panic: {e}");
continue;
}
};
for (from_addr, subject, message_id, body) in emails {
// Check allowed senders
if !allowed_senders.is_empty()
&& !allowed_senders.iter().any(|s| from_addr.contains(s))
{
debug!(from = %from_addr, "Email from non-allowed sender, skipping");
continue;
}
// Store reply context for threading
if !message_id.is_empty() {
reply_ctx.insert(
from_addr.clone(),
ReplyCtx {
subject: subject.clone(),
message_id: message_id.clone(),
},
);
}
// Extract target agent from subject brackets (stored in metadata for router)
let _target_agent =
EmailAdapter::extract_agent_from_subject(&subject);
let clean_subject = EmailAdapter::strip_agent_tag(&subject);
// Build the message body: prepend subject context
let text = if clean_subject.is_empty() {
body.trim().to_string()
} else {
format!("Subject: {clean_subject}\n\n{}", body.trim())
};
let msg = ChannelMessage {
channel: ChannelType::Email,
platform_message_id: message_id.clone(),
sender: ChannelUser {
platform_id: from_addr.clone(),
display_name: from_addr.clone(),
openfang_user: None,
},
content: ChannelContent::Text(text),
target_agent: None, // Routing handled by bridge AgentRouter
timestamp: Utc::now(),
is_group: false,
thread_id: None,
metadata: std::collections::HashMap::new(),
};
if tx.send(msg).await.is_err() {
info!("Email channel receiver dropped, stopping poll");
return;
}
}
}
});
Ok(Box::pin(tokio_stream::wrappers::ReceiverStream::new(rx)))
}
async fn send(
&self,
user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
match content {
ChannelContent::Text(text) => {
// Parse recipient address
let to_addr = extract_email_addr(&user.platform_id);
let to_mailbox: Mailbox = to_addr
.parse()
.map_err(|e| format!("Invalid recipient email '{}': {}", to_addr, e))?;
let from_mailbox: Mailbox = self
.username
.parse()
.map_err(|e| format!("Invalid sender email '{}': {}", self.username, e))?;
// Extract subject from text body convention: "Subject: ...\n\n..."
let (subject, body) = if text.starts_with("Subject: ") {
if let Some(pos) = text.find("\n\n") {
let subj = text[9..pos].trim().to_string();
let body = text[pos + 2..].to_string();
(subj, body)
} else {
("OpenFang Reply".to_string(), text)
}
} else {
// Check reply context for subject continuity
let subj = self
.reply_ctx
.get(&to_addr)
.map(|ctx| format!("Re: {}", ctx.subject))
.unwrap_or_else(|| "OpenFang Reply".to_string());
(subj, text)
};
// Build email message
let mut builder = lettre::Message::builder()
.from(from_mailbox)
.to(to_mailbox)
.subject(&subject);
// Add In-Reply-To header for threading
if let Some(ctx) = self.reply_ctx.get(&to_addr) {
if !ctx.message_id.is_empty() {
builder = builder.in_reply_to(ctx.message_id.clone());
}
}
let email = builder
.body(body)
.map_err(|e| format!("Failed to build email: {e}"))?;
// Send via SMTP
let transport = self.build_smtp_transport().await?;
transport
.send(email)
.await
.map_err(|e| format!("SMTP send failed: {e}"))?;
info!(
to = %to_addr,
subject = %subject,
"Email sent successfully via SMTP"
);
}
_ => {
warn!(
"Unsupported email content type for {}, only text is supported",
user.platform_id
);
}
}
Ok(())
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_email_adapter_creation() {
let adapter = EmailAdapter::new(
"imap.gmail.com".to_string(),
993,
"smtp.gmail.com".to_string(),
587,
"user@gmail.com".to_string(),
"password".to_string(),
30,
vec![],
vec![],
);
assert_eq!(adapter.name(), "email");
assert_eq!(adapter.folders, vec!["INBOX".to_string()]);
}
#[test]
fn test_allowed_senders() {
let adapter = EmailAdapter::new(
"imap.example.com".to_string(),
993,
"smtp.example.com".to_string(),
587,
"bot@example.com".to_string(),
"pass".to_string(),
30,
vec![],
vec!["boss@company.com".to_string()],
);
assert!(adapter.is_allowed_sender("boss@company.com"));
assert!(!adapter.is_allowed_sender("random@other.com"));
let open = EmailAdapter::new(
"imap.example.com".to_string(),
993,
"smtp.example.com".to_string(),
587,
"bot@example.com".to_string(),
"pass".to_string(),
30,
vec![],
vec![],
);
assert!(open.is_allowed_sender("anyone@anywhere.com"));
}
#[test]
fn test_extract_agent_from_subject() {
assert_eq!(
EmailAdapter::extract_agent_from_subject("[coder] Fix the bug"),
Some("coder".to_string())
);
assert_eq!(
EmailAdapter::extract_agent_from_subject("[researcher] Find papers on AI"),
Some("researcher".to_string())
);
assert_eq!(
EmailAdapter::extract_agent_from_subject("No brackets here"),
None
);
assert_eq!(
EmailAdapter::extract_agent_from_subject("[] Empty brackets"),
None
);
}
#[test]
fn test_strip_agent_tag() {
assert_eq!(
EmailAdapter::strip_agent_tag("[coder] Fix the bug"),
"Fix the bug"
);
assert_eq!(EmailAdapter::strip_agent_tag("No brackets"), "No brackets");
}
#[test]
fn test_extract_email_addr() {
assert_eq!(
extract_email_addr("John Doe <john@example.com>"),
"john@example.com"
);
assert_eq!(extract_email_addr("user@example.com"), "user@example.com");
assert_eq!(extract_email_addr("<user@test.com>"), "user@test.com");
}
#[test]
fn test_subject_extraction_from_body() {
let text = "Subject: Test Subject\n\nThis is the body.";
assert!(text.starts_with("Subject: "));
let pos = text.find("\n\n").unwrap();
let subject = &text[9..pos];
let body = &text[pos + 2..];
assert_eq!(subject, "Test Subject");
assert_eq!(body, "This is the body.");
}
#[test]
fn test_reply_ctx_threading() {
let ctx_map: DashMap<String, ReplyCtx> = DashMap::new();
ctx_map.insert(
"user@test.com".to_string(),
ReplyCtx {
subject: "Original Subject".to_string(),
message_id: "<msg-123@test.com>".to_string(),
},
);
let ctx = ctx_map.get("user@test.com").unwrap();
assert_eq!(ctx.subject, "Original Subject");
assert_eq!(ctx.message_id, "<msg-123@test.com>");
}
}

799
crates/openfang-channels/src/feishu.rs Normal file
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@@ -0,0 +1,799 @@
//! Feishu/Lark Open Platform channel adapter.
//!
//! Uses the Feishu Open API for sending messages and a webhook HTTP server for
//! receiving inbound events. Authentication is performed via a tenant access token
//! obtained from `https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal`.
//! The token is cached and refreshed automatically (2-hour expiry).
use crate::types::{
split_message, ChannelAdapter, ChannelContent, ChannelMessage, ChannelType, ChannelUser,
};
use async_trait::async_trait;
use chrono::Utc;
use futures::Stream;
use std::collections::HashMap;
use std::pin::Pin;
use std::sync::Arc;
use std::time::{Duration, Instant};
use tokio::sync::{mpsc, watch, RwLock};
use tracing::{info, warn};
use zeroize::Zeroizing;
/// Feishu tenant access token endpoint.
const FEISHU_TOKEN_URL: &str =
"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal";
/// Feishu send message endpoint.
const FEISHU_SEND_URL: &str = "https://open.feishu.cn/open-apis/im/v1/messages";
/// Feishu bot info endpoint.
const FEISHU_BOT_INFO_URL: &str = "https://open.feishu.cn/open-apis/bot/v3/info";
/// Maximum Feishu message text length (characters).
const MAX_MESSAGE_LEN: usize = 4096;
/// Token refresh buffer — refresh 5 minutes before actual expiry.
const TOKEN_REFRESH_BUFFER_SECS: u64 = 300;
/// Feishu/Lark Open Platform adapter.
///
/// Inbound messages arrive via a webhook HTTP server that receives event
/// callbacks from the Feishu platform. Outbound messages are sent via the
/// Feishu IM API with a tenant access token for authentication.
pub struct FeishuAdapter {
/// Feishu app ID.
app_id: String,
/// SECURITY: Feishu app secret, zeroized on drop.
app_secret: Zeroizing<String>,
/// Port on which the inbound webhook HTTP server listens.
webhook_port: u16,
/// Optional verification token for webhook event validation.
verification_token: Option<String>,
/// Optional encrypt key for webhook event decryption.
encrypt_key: Option<String>,
/// HTTP client for API calls.
client: reqwest::Client,
/// Shutdown signal.
shutdown_tx: Arc<watch::Sender<bool>>,
shutdown_rx: watch::Receiver<bool>,
/// Cached tenant access token and its expiry instant.
cached_token: Arc<RwLock<Option<(String, Instant)>>>,
}
impl FeishuAdapter {
/// Create a new Feishu adapter.
///
/// # Arguments
/// * `app_id` - Feishu application ID.
/// * `app_secret` - Feishu application secret.
/// * `webhook_port` - Local port for the inbound webhook HTTP server.
pub fn new(app_id: String, app_secret: String, webhook_port: u16) -> Self {
let (shutdown_tx, shutdown_rx) = watch::channel(false);
Self {
app_id,
app_secret: Zeroizing::new(app_secret),
webhook_port,
verification_token: None,
encrypt_key: None,
client: reqwest::Client::new(),
shutdown_tx: Arc::new(shutdown_tx),
shutdown_rx,
cached_token: Arc::new(RwLock::new(None)),
}
}
/// Create a new Feishu adapter with webhook verification.
pub fn with_verification(
app_id: String,
app_secret: String,
webhook_port: u16,
verification_token: Option<String>,
encrypt_key: Option<String>,
) -> Self {
let mut adapter = Self::new(app_id, app_secret, webhook_port);
adapter.verification_token = verification_token;
adapter.encrypt_key = encrypt_key;
adapter
}
/// Obtain a valid tenant access token, refreshing if expired or missing.
async fn get_token(&self) -> Result<String, Box<dyn std::error::Error>> {
// Check cache first
{
let guard = self.cached_token.read().await;
if let Some((ref token, expiry)) = *guard {
if Instant::now() < expiry {
return Ok(token.clone());
}
}
}
// Fetch a new tenant access token
let body = serde_json::json!({
"app_id": self.app_id,
"app_secret": self.app_secret.as_str(),
});
let resp = self
.client
.post(FEISHU_TOKEN_URL)
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let resp_body = resp.text().await.unwrap_or_default();
return Err(format!("Feishu token request failed {status}: {resp_body}").into());
}
let resp_body: serde_json::Value = resp.json().await?;
let code = resp_body["code"].as_i64().unwrap_or(-1);
if code != 0 {
let msg = resp_body["msg"].as_str().unwrap_or("unknown error");
return Err(format!("Feishu token error: {msg}").into());
}
let tenant_access_token = resp_body["tenant_access_token"]
.as_str()
.ok_or("Missing tenant_access_token")?
.to_string();
let expire = resp_body["expire"].as_u64().unwrap_or(7200);
// Cache with safety buffer
let expiry =
Instant::now() + Duration::from_secs(expire.saturating_sub(TOKEN_REFRESH_BUFFER_SECS));
*self.cached_token.write().await = Some((tenant_access_token.clone(), expiry));
Ok(tenant_access_token)
}
/// Validate credentials by fetching bot info.
async fn validate(&self) -> Result<String, Box<dyn std::error::Error>> {
let token = self.get_token().await?;
let resp = self
.client
.get(FEISHU_BOT_INFO_URL)
.bearer_auth(&token)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let body = resp.text().await.unwrap_or_default();
return Err(format!("Feishu authentication failed {status}: {body}").into());
}
let body: serde_json::Value = resp.json().await?;
let code = body["code"].as_i64().unwrap_or(-1);
if code != 0 {
let msg = body["msg"].as_str().unwrap_or("unknown error");
return Err(format!("Feishu bot info error: {msg}").into());
}
let bot_name = body["bot"]["app_name"]
.as_str()
.unwrap_or("Feishu Bot")
.to_string();
Ok(bot_name)
}
/// Send a text message to a Feishu chat.
async fn api_send_message(
&self,
receive_id: &str,
receive_id_type: &str,
text: &str,
) -> Result<(), Box<dyn std::error::Error>> {
let token = self.get_token().await?;
let url = format!("{}?receive_id_type={}", FEISHU_SEND_URL, receive_id_type);
let chunks = split_message(text, MAX_MESSAGE_LEN);
for chunk in chunks {
let content = serde_json::json!({
"text": chunk,
});
let body = serde_json::json!({
"receive_id": receive_id,
"msg_type": "text",
"content": content.to_string(),
});
let resp = self
.client
.post(&url)
.bearer_auth(&token)
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let resp_body = resp.text().await.unwrap_or_default();
return Err(format!("Feishu send message error {status}: {resp_body}").into());
}
let resp_body: serde_json::Value = resp.json().await?;
let code = resp_body["code"].as_i64().unwrap_or(-1);
if code != 0 {
let msg = resp_body["msg"].as_str().unwrap_or("unknown error");
warn!("Feishu send message API error: {msg}");
}
}
Ok(())
}
/// Reply to a message in a thread.
#[allow(dead_code)]
async fn api_reply_message(
&self,
message_id: &str,
text: &str,
) -> Result<(), Box<dyn std::error::Error>> {
let token = self.get_token().await?;
let url = format!(
"https://open.feishu.cn/open-apis/im/v1/messages/{}/reply",
message_id
);
let content = serde_json::json!({
"text": text,
});
let body = serde_json::json!({
"msg_type": "text",
"content": content.to_string(),
});
let resp = self
.client
.post(&url)
.bearer_auth(&token)
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let resp_body = resp.text().await.unwrap_or_default();
return Err(format!("Feishu reply message error {status}: {resp_body}").into());
}
Ok(())
}
}
/// Parse a Feishu webhook event into a `ChannelMessage`.
///
/// Handles `im.message.receive_v1` events with text message type.
fn parse_feishu_event(event: &serde_json::Value) -> Option<ChannelMessage> {
// Feishu v2 event schema
let header = event.get("header")?;
let event_type = header["event_type"].as_str().unwrap_or("");
if event_type != "im.message.receive_v1" {
return None;
}
let event_data = event.get("event")?;
let message = event_data.get("message")?;
let sender = event_data.get("sender")?;
let msg_type = message["message_type"].as_str().unwrap_or("");
if msg_type != "text" {
return None;
}
// Parse the content JSON string
let content_str = message["content"].as_str().unwrap_or("{}");
let content_json: serde_json::Value = serde_json::from_str(content_str).unwrap_or_default();
let text = content_json["text"].as_str().unwrap_or("");
if text.is_empty() {
return None;
}
let message_id = message["message_id"].as_str().unwrap_or("").to_string();
let chat_id = message["chat_id"].as_str().unwrap_or("").to_string();
let chat_type = message["chat_type"].as_str().unwrap_or("p2p");
let root_id = message["root_id"].as_str().map(|s| s.to_string());
let sender_id = sender
.get("sender_id")
.and_then(|s| s.get("open_id"))
.and_then(|v| v.as_str())
.unwrap_or("")
.to_string();
let sender_type = sender["sender_type"].as_str().unwrap_or("user");
// Skip bot messages
if sender_type == "bot" {
return None;
}
let is_group = chat_type == "group";
let msg_content = if text.starts_with('/') {
let parts: Vec<&str> = text.splitn(2, ' ').collect();
let cmd_name = parts[0].trim_start_matches('/');
let args: Vec<String> = parts
.get(1)
.map(|a| a.split_whitespace().map(String::from).collect())
.unwrap_or_default();
ChannelContent::Command {
name: cmd_name.to_string(),
args,
}
} else {
ChannelContent::Text(text.to_string())
};
let mut metadata = HashMap::new();
metadata.insert(
"chat_id".to_string(),
serde_json::Value::String(chat_id.clone()),
);
metadata.insert(
"message_id".to_string(),
serde_json::Value::String(message_id.clone()),
);
metadata.insert(
"chat_type".to_string(),
serde_json::Value::String(chat_type.to_string()),
);
metadata.insert(
"sender_id".to_string(),
serde_json::Value::String(sender_id.clone()),
);
if let Some(mentions) = message.get("mentions") {
metadata.insert("mentions".to_string(), mentions.clone());
}
Some(ChannelMessage {
channel: ChannelType::Custom("feishu".to_string()),
platform_message_id: message_id,
sender: ChannelUser {
platform_id: chat_id,
display_name: sender_id,
openfang_user: None,
},
content: msg_content,
target_agent: None,
timestamp: Utc::now(),
is_group,
thread_id: root_id,
metadata,
})
}
#[async_trait]
impl ChannelAdapter for FeishuAdapter {
fn name(&self) -> &str {
"feishu"
}
fn channel_type(&self) -> ChannelType {
ChannelType::Custom("feishu".to_string())
}
async fn start(
&self,
) -> Result<Pin<Box<dyn Stream<Item = ChannelMessage> + Send>>, Box<dyn std::error::Error>>
{
// Validate credentials
let bot_name = self.validate().await?;
info!("Feishu adapter authenticated as {bot_name}");
let (tx, rx) = mpsc::channel::<ChannelMessage>(256);
let port = self.webhook_port;
let verification_token = self.verification_token.clone();
let mut shutdown_rx = self.shutdown_rx.clone();
tokio::spawn(async move {
let verification_token = Arc::new(verification_token);
let tx = Arc::new(tx);
let app = axum::Router::new().route(
"/feishu/webhook",
axum::routing::post({
let vt = Arc::clone(&verification_token);
let tx = Arc::clone(&tx);
move |body: axum::extract::Json<serde_json::Value>| {
let vt = Arc::clone(&vt);
let tx = Arc::clone(&tx);
async move {
// Handle URL verification challenge
if let Some(challenge) = body.0.get("challenge") {
// Verify token if configured
if let Some(ref expected_token) = *vt {
let token = body.0["token"].as_str().unwrap_or("");
if token != expected_token {
warn!("Feishu: invalid verification token");
return (
axum::http::StatusCode::FORBIDDEN,
axum::Json(serde_json::json!({})),
);
}
}
return (
axum::http::StatusCode::OK,
axum::Json(serde_json::json!({
"challenge": challenge,
})),
);
}
// Handle event callback
if let Some(schema) = body.0["schema"].as_str() {
if schema == "2.0" {
// V2 event format
if let Some(msg) = parse_feishu_event(&body.0) {
let _ = tx.send(msg).await;
}
}
} else {
// V1 event format (legacy)
let event_type = body.0["event"]["type"].as_str().unwrap_or("");
if event_type == "message" {
// Legacy format handling
let event = &body.0["event"];
let text = event["text"].as_str().unwrap_or("");
if !text.is_empty() {
let open_id =
event["open_id"].as_str().unwrap_or("").to_string();
let chat_id = event["open_chat_id"]
.as_str()
.unwrap_or("")
.to_string();
let msg_id = event["open_message_id"]
.as_str()
.unwrap_or("")
.to_string();
let is_group =
event["chat_type"].as_str().unwrap_or("") == "group";
let content = if text.starts_with('/') {
let parts: Vec<&str> = text.splitn(2, ' ').collect();
let cmd = parts[0].trim_start_matches('/');
let args: Vec<String> = parts
.get(1)
.map(|a| {
a.split_whitespace().map(String::from).collect()
})
.unwrap_or_default();
ChannelContent::Command {
name: cmd.to_string(),
args,
}
} else {
ChannelContent::Text(text.to_string())
};
let channel_msg = ChannelMessage {
channel: ChannelType::Custom("feishu".to_string()),
platform_message_id: msg_id,
sender: ChannelUser {
platform_id: chat_id,
display_name: open_id,
openfang_user: None,
},
content,
target_agent: None,
timestamp: Utc::now(),
is_group,
thread_id: None,
metadata: HashMap::new(),
};
let _ = tx.send(channel_msg).await;
}
}
}
(
axum::http::StatusCode::OK,
axum::Json(serde_json::json!({})),
)
}
}
}),
);
let addr = std::net::SocketAddr::from(([0, 0, 0, 0], port));
info!("Feishu webhook server listening on {addr}");
let listener = match tokio::net::TcpListener::bind(addr).await {
Ok(l) => l,
Err(e) => {
warn!("Feishu webhook bind failed: {e}");
return;
}
};
let server = axum::serve(listener, app);
tokio::select! {
result = server => {
if let Err(e) = result {
warn!("Feishu webhook server error: {e}");
}
}
_ = shutdown_rx.changed() => {
info!("Feishu adapter shutting down");
}
}
});
Ok(Box::pin(tokio_stream::wrappers::ReceiverStream::new(rx)))
}
async fn send(
&self,
user: &ChannelUser,
content: ChannelContent,
) -> Result<(), Box<dyn std::error::Error>> {
match content {
ChannelContent::Text(text) => {
// Use chat_id as receive_id with chat_id type
self.api_send_message(&user.platform_id, "chat_id", &text)
.await?;
}
_ => {
self.api_send_message(&user.platform_id, "chat_id", "(Unsupported content type)")
.await?;
}
}
Ok(())
}
async fn send_typing(&self, _user: &ChannelUser) -> Result<(), Box<dyn std::error::Error>> {
// Feishu does not support typing indicators via REST API
Ok(())
}
async fn stop(&self) -> Result<(), Box<dyn std::error::Error>> {
let _ = self.shutdown_tx.send(true);
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_feishu_adapter_creation() {
let adapter =
FeishuAdapter::new("cli_abc123".to_string(), "app-secret-456".to_string(), 9000);
assert_eq!(adapter.name(), "feishu");
assert_eq!(
adapter.channel_type(),
ChannelType::Custom("feishu".to_string())
);
assert_eq!(adapter.webhook_port, 9000);
}
#[test]
fn test_feishu_with_verification() {
let adapter = FeishuAdapter::with_verification(
"cli_abc123".to_string(),
"secret".to_string(),
9000,
Some("verify-token".to_string()),
Some("encrypt-key".to_string()),
);
assert_eq!(adapter.verification_token, Some("verify-token".to_string()));
assert_eq!(adapter.encrypt_key, Some("encrypt-key".to_string()));
}
#[test]
fn test_feishu_app_id_stored() {
let adapter = FeishuAdapter::new("cli_test".to_string(), "secret".to_string(), 8080);
assert_eq!(adapter.app_id, "cli_test");
}
#[test]
fn test_parse_feishu_event_v2_text() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-001",
"event_type": "im.message.receive_v1",
"create_time": "1234567890000",
"token": "verify-token",
"app_id": "cli_abc123",
"tenant_key": "tenant-key-1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_abc123",
"user_id": "user-1"
},
"sender_type": "user"
},
"message": {
"message_id": "om_abc123",
"root_id": null,
"chat_id": "oc_chat123",
"chat_type": "p2p",
"message_type": "text",
"content": "{\"text\":\"Hello from Feishu!\"}"
}
}
});
let msg = parse_feishu_event(&event).unwrap();
assert_eq!(msg.channel, ChannelType::Custom("feishu".to_string()));
assert_eq!(msg.platform_message_id, "om_abc123");
assert!(!msg.is_group);
assert!(matches!(msg.content, ChannelContent::Text(ref t) if t == "Hello from Feishu!"));
}
#[test]
fn test_parse_feishu_event_group_message() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-002",
"event_type": "im.message.receive_v1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_abc123"
},
"sender_type": "user"
},
"message": {
"message_id": "om_grp1",
"chat_id": "oc_grp123",
"chat_type": "group",
"message_type": "text",
"content": "{\"text\":\"Group message\"}"
}
}
});
let msg = parse_feishu_event(&event).unwrap();
assert!(msg.is_group);
}
#[test]
fn test_parse_feishu_event_command() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-003",
"event_type": "im.message.receive_v1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_abc123"
},
"sender_type": "user"
},
"message": {
"message_id": "om_cmd1",
"chat_id": "oc_chat1",
"chat_type": "p2p",
"message_type": "text",
"content": "{\"text\":\"/help all\"}"
}
}
});
let msg = parse_feishu_event(&event).unwrap();
match &msg.content {
ChannelContent::Command { name, args } => {
assert_eq!(name, "help");
assert_eq!(args, &["all"]);
}
other => panic!("Expected Command, got {other:?}"),
}
}
#[test]
fn test_parse_feishu_event_skips_bot() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-004",
"event_type": "im.message.receive_v1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_bot"
},
"sender_type": "bot"
},
"message": {
"message_id": "om_bot1",
"chat_id": "oc_chat1",
"chat_type": "p2p",
"message_type": "text",
"content": "{\"text\":\"Bot message\"}"
}
}
});
assert!(parse_feishu_event(&event).is_none());
}
#[test]
fn test_parse_feishu_event_non_text() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-005",
"event_type": "im.message.receive_v1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_user1"
},
"sender_type": "user"
},
"message": {
"message_id": "om_img1",
"chat_id": "oc_chat1",
"chat_type": "p2p",
"message_type": "image",
"content": "{\"image_key\":\"img_v2_abc123\"}"
}
}
});
assert!(parse_feishu_event(&event).is_none());
}
#[test]
fn test_parse_feishu_event_wrong_type() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-006",
"event_type": "im.chat.member_bot.added_v1"
},
"event": {}
});
assert!(parse_feishu_event(&event).is_none());
}
#[test]
fn test_parse_feishu_event_thread_id() {
let event = serde_json::json!({
"schema": "2.0",
"header": {
"event_id": "evt-007",
"event_type": "im.message.receive_v1"
},
"event": {
"sender": {
"sender_id": {
"open_id": "ou_user1"
},
"sender_type": "user"
},
"message": {
"message_id": "om_thread1",
"root_id": "om_root1",
"chat_id": "oc_chat1",
"chat_type": "group",
"message_type": "text",
"content": "{\"text\":\"Thread reply\"}"
}
}
});
let msg = parse_feishu_event(&event).unwrap();
assert_eq!(msg.thread_id, Some("om_root1".to_string()));
}
}

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