4b15ead8e7
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)
21 lines
542 B
Rust
21 lines
542 B
Rust
//! ZCLAW Memory Substrate
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//!
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//! SQLite-backed storage for agents, sessions, and memory.
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mod store;
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mod session;
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mod schema;
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pub mod fact;
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pub mod user_profile_store;
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pub mod trajectory_store;
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pub use store::*;
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pub use session::*;
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pub use schema::*;
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pub use fact::{Fact, FactCategory, ExtractedFactBatch};
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pub use user_profile_store::{UserProfileStore, UserProfile, Level, CommStyle};
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pub use trajectory_store::{
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TrajectoryEvent, TrajectoryStore, TrajectoryStepType,
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CompressedTrajectory, CompletionStatus, SatisfactionSignal,
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};
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