Hermes Intelligence Pipeline closes breakpoints in ZCLAW's existing intelligence components with 4 self-contained modules: Chunk 1 — Self-improvement Loop: - ExperienceStore (zclaw-growth): FTS5+TF-IDF wrapper with scope prefix - ExperienceExtractor (desktop/intelligence): template-based extraction from successful proposals with implicit keyword detection Chunk 2 — User Modeling: - UserProfileStore (zclaw-memory): SQLite-backed structured profiles with industry/role/expertise/comm_style/recent_topics/pain_points - UserProfiler (desktop/intelligence): fact classification by category (Preference/Knowledge/Behavior) with profile summary formatting Chunk 3 — NL Cron Chinese Time Parser: - NlScheduleParser (zclaw-runtime): 6 pattern matchers for Chinese time expressions (每天/每周/工作日/间隔/每月/一次性) producing cron expressions - Period-aware hour adjustment (下午3点→15, 晚上8点→20) - Schedule intent detection + task description extraction Chunk 4 — Trajectory Compression: - TrajectoryStore (zclaw-memory): trajectory_events + compressed_trajectories - TrajectoryRecorderMiddleware (zclaw-runtime/middleware): priority 650, async non-blocking event recording via tokio::spawn - TrajectoryCompressor (desktop/intelligence): dedup, request classification, satisfaction detection, execution chain JSON Schema migrations: v2→v3 (user_profiles), v3→v4 (trajectory tables)
282 lines
9.5 KiB
Rust
282 lines
9.5 KiB
Rust
//! Agent middleware system — composable hooks for cross-cutting concerns.
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//!
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//! Inspired by [DeerFlow 2.0](https://github.com/bytedance/deer-flow)'s 9-layer middleware chain,
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//! this module provides a standardised way to inject behaviour before/after LLM completions
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//! and tool calls without modifying the core `AgentLoop` logic.
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//!
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//! # Priority convention
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//!
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//! | Range | Category | Example |
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//! |---------|----------------|-----------------------------|
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//! | 100-199 | Context shaping| Compaction, MemoryInject |
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//! | 200-399 | Capability | SkillIndex, Guardrail |
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//! | 400-599 | Safety | LoopGuard, Guardrail |
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//! | 600-799 | Telemetry | TokenCalibration, Tracking |
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use std::sync::Arc;
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use async_trait::async_trait;
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use serde_json::Value;
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use zclaw_types::{AgentId, Result, SessionId};
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use crate::driver::ContentBlock;
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// ---------------------------------------------------------------------------
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// Decisions returned by middleware hooks
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// ---------------------------------------------------------------------------
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/// Decision returned by `before_completion`.
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#[derive(Debug, Clone)]
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pub enum MiddlewareDecision {
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/// Continue to the next middleware / proceed with the LLM call.
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Continue,
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/// Abort the agent loop and return *reason* to the caller.
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Stop(String),
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}
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/// Decision returned by `before_tool_call`.
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#[derive(Debug, Clone)]
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pub enum ToolCallDecision {
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/// Allow the tool call to proceed unchanged.
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Allow,
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/// Block the call and return *message* as a tool-error to the LLM.
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Block(String),
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/// Allow the call but replace the tool input with *new_input*.
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ReplaceInput(Value),
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/// Terminate the entire agent loop immediately (e.g. circuit breaker).
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AbortLoop(String),
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}
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// ---------------------------------------------------------------------------
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// Middleware context — shared mutable state passed through the chain
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// ---------------------------------------------------------------------------
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/// Carries the mutable state that middleware may inspect or modify.
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pub struct MiddlewareContext {
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/// The agent that owns this loop.
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pub agent_id: AgentId,
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/// Current session.
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pub session_id: SessionId,
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/// The raw user input that started this turn.
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pub user_input: String,
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// -- mutable state -------------------------------------------------------
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/// System prompt — middleware may prepend/append context.
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pub system_prompt: String,
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/// Conversation messages sent to the LLM.
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pub messages: Vec<zclaw_types::Message>,
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/// Accumulated LLM content blocks from the current response.
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pub response_content: Vec<ContentBlock>,
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/// Token usage reported by the LLM driver (updated after each call).
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pub input_tokens: u32,
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pub output_tokens: u32,
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}
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impl std::fmt::Debug for MiddlewareContext {
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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f.debug_struct("MiddlewareContext")
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.field("agent_id", &self.agent_id)
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.field("session_id", &self.session_id)
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.field("messages", &self.messages.len())
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.field("input_tokens", &self.input_tokens)
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.field("output_tokens", &self.output_tokens)
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.finish()
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}
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}
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// ---------------------------------------------------------------------------
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// Core trait
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// ---------------------------------------------------------------------------
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/// A composable middleware hook for the agent loop.
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///
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/// Each middleware focuses on one cross-cutting concern and is executed
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/// in `priority` order (ascending). All hook methods have default no-op
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/// implementations so implementors only override what they need.
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#[async_trait]
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pub trait AgentMiddleware: Send + Sync {
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/// Human-readable name for logging / debugging.
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fn name(&self) -> &str;
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/// Execution priority — lower values run first.
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fn priority(&self) -> i32 {
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500
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}
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/// Hook executed **before** the LLM completion request is sent.
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///
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/// Use this to inject context (memory, skill index, etc.) or to
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/// trigger pre-processing (compaction, summarisation).
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async fn before_completion(&self, _ctx: &mut MiddlewareContext) -> Result<MiddlewareDecision> {
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Ok(MiddlewareDecision::Continue)
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}
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/// Hook executed **before** each tool call.
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///
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/// Return `Block` to prevent execution and feed an error back to
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/// the LLM, or `ReplaceInput` to sanitise / modify the arguments.
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async fn before_tool_call(
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&self,
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_ctx: &MiddlewareContext,
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_tool_name: &str,
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_tool_input: &Value,
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) -> Result<ToolCallDecision> {
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Ok(ToolCallDecision::Allow)
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}
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/// Hook executed **after** each tool call.
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async fn after_tool_call(
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&self,
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_ctx: &mut MiddlewareContext,
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_tool_name: &str,
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_result: &Value,
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) -> Result<()> {
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Ok(())
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}
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/// Hook executed **after** the entire agent loop turn completes.
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///
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/// Use this for post-processing (memory extraction, telemetry, etc.).
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async fn after_completion(&self, _ctx: &MiddlewareContext) -> Result<()> {
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Ok(())
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}
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}
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// ---------------------------------------------------------------------------
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// Middleware chain — ordered collection with run methods
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// ---------------------------------------------------------------------------
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/// An ordered chain of `AgentMiddleware` instances.
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pub struct MiddlewareChain {
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middlewares: Vec<Arc<dyn AgentMiddleware>>,
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}
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impl MiddlewareChain {
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/// Create an empty chain.
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pub fn new() -> Self {
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Self { middlewares: Vec::new() }
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}
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/// Register a middleware. The chain is kept sorted by `priority`
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/// (ascending) and by registration order within the same priority.
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pub fn register(&mut self, mw: Arc<dyn AgentMiddleware>) {
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let p = mw.priority();
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let pos = self.middlewares.iter().position(|m| m.priority() > p).unwrap_or(self.middlewares.len());
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self.middlewares.insert(pos, mw);
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}
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/// Run all `before_completion` hooks in order.
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pub async fn run_before_completion(&self, ctx: &mut MiddlewareContext) -> Result<MiddlewareDecision> {
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for mw in &self.middlewares {
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match mw.before_completion(ctx).await? {
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MiddlewareDecision::Continue => {}
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MiddlewareDecision::Stop(reason) => {
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tracing::info!("[MiddlewareChain] '{}' requested stop: {}", mw.name(), reason);
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return Ok(MiddlewareDecision::Stop(reason));
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}
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}
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}
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Ok(MiddlewareDecision::Continue)
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}
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/// Run all `before_tool_call` hooks in order.
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pub async fn run_before_tool_call(
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&self,
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ctx: &MiddlewareContext,
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tool_name: &str,
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tool_input: &Value,
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) -> Result<ToolCallDecision> {
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for mw in &self.middlewares {
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match mw.before_tool_call(ctx, tool_name, tool_input).await? {
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ToolCallDecision::Allow => {}
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other => {
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tracing::info!("[MiddlewareChain] '{}' decided {:?} for tool '{}'", mw.name(), other, tool_name);
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return Ok(other);
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}
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}
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}
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Ok(ToolCallDecision::Allow)
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}
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/// Run all `before_tool_call` hooks with mutable context.
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pub async fn run_before_tool_call_mut(
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&self,
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ctx: &mut MiddlewareContext,
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tool_name: &str,
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tool_input: &Value,
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) -> Result<ToolCallDecision> {
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for mw in &self.middlewares {
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match mw.before_tool_call(ctx, tool_name, tool_input).await? {
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ToolCallDecision::Allow => {}
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other => {
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tracing::info!("[MiddlewareChain] '{}' decided {:?} for tool '{}'", mw.name(), other, tool_name);
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return Ok(other);
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}
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}
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}
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Ok(ToolCallDecision::Allow)
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}
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/// Run all `after_tool_call` hooks in order.
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pub async fn run_after_tool_call(
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&self,
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ctx: &mut MiddlewareContext,
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tool_name: &str,
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result: &Value,
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) -> Result<()> {
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for mw in &self.middlewares {
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mw.after_tool_call(ctx, tool_name, result).await?;
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}
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Ok(())
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}
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/// Run all `after_completion` hooks in order.
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pub async fn run_after_completion(&self, ctx: &MiddlewareContext) -> Result<()> {
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for mw in &self.middlewares {
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mw.after_completion(ctx).await?;
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}
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Ok(())
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}
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/// Number of registered middlewares.
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pub fn len(&self) -> usize {
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self.middlewares.len()
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}
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/// Whether the chain is empty.
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pub fn is_empty(&self) -> bool {
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self.middlewares.is_empty()
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}
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}
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impl Clone for MiddlewareChain {
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fn clone(&self) -> Self {
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Self {
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middlewares: self.middlewares.clone(), // Arc clone — cheap ref-count bump
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}
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}
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}
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impl Default for MiddlewareChain {
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fn default() -> Self {
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Self::new()
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}
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}
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// ---------------------------------------------------------------------------
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// Sub-modules — concrete middleware implementations
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// ---------------------------------------------------------------------------
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pub mod butler_router;
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pub mod compaction;
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pub mod dangling_tool;
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pub mod data_masking;
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pub mod guardrail;
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pub mod loop_guard;
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pub mod memory;
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pub mod skill_index;
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pub mod subagent_limit;
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pub mod title;
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pub mod token_calibration;
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pub mod tool_error;
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pub mod tool_output_guard;
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pub mod trajectory_recorder;
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