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3b448a1838fa228cf69172958a4ddb0554c8d052
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6 Commits
Author SHA1 Message Date
rock 3b448a1838 docs: rewrite README as open-source project documentation
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- Architecture diagram with data flow
- Feature explanations (Graph-RAG, Three-Tier, RBAC)
- Hallucination prevention focus
- Agent-ready API examples
- Retrieval pipeline visualization
- Quick start guides (local, Docker, K8s)
- Performance metrics table
 2026-09-02 11:30:11 -07:00
rock aa49770fa4 feat: POST /memory/learn endpoint + refactor mem learn CLI
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Learning flow now goes through the service, not local JSONL:
- POST /memory/learn: accepts markdown, chunks it, runs gated loop
  (LLM evaluates + compacts), stores in pgvector. OpenAI-style API.
- mem learn CLI: reads files, calls POST /memory/learn per file
- Removed cmd_compact (gated loop IS the compaction)
- Updated README with new commands and API docs

Memory never grows unbounded — every update is a rewrite, not append.
The gated loop LLM acts as evaluator + compactor in one pass.
 2026-08-30 13:21:07 -07:00
Story Crater Bot 57c434ccdd docs: comprehensive query optimization guides for developers
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Added two major documentation pieces:

1. README.md - New Section: M3.8 Pluggable Query Optimization
   ✅ Architecture overview (ingest + query paths)
   ✅ 6 practical usage patterns with code examples:
      - Basic query with auto-optimization
      - Prompt construction with optimization
      - Custom optimizer implementation
      - Optimized query with metrics tracking
      - Batch optimization for multiple queries
      - Conditional optimization with graceful fallback
   ✅ Environment configuration
   ✅ Compression targets by content type
   ✅ Performance targets table
   ✅ Monitoring via structured logging
   ✅ Best practices (5 key points)
   ✅ Links to full documentation

2. QUERY-OPTIMIZATION-COOKBOOK.md - Quick Reference (15KB)
   ✅ Basic usage patterns
   ✅ Prompt construction techniques
   ✅ Custom optimizer examples:
      - Content-type specific (Python optimizer)
      - Domain-specific (Medical optimizer)
      - Semantic pruning
   ✅ Format handlers (built-in + custom Gzip example)
   ✅ Error handling (graceful fallback + retry)
   ✅ Testing patterns (unit, integration, mocking)
   ✅ Configuration examples (env vars + Kubernetes)
   ✅ Performance tips (5 optimization strategies)
   ✅ Debugging guide

Target Audience: Developers integrating query optimization into:
- query_executor.rs
- hybrid_query_worker.rs
- Custom LLM clients

Includes:
- Copy-paste ready code examples
- Real-world patterns for medical, code, text optimization
- Testing strategies
- Kubernetes deployment config
- Debug logging setup
- Performance profiling tips
 2026-08-28 12:32:08 -07:00
Story Crater Bot ab3c0da771 test: trigger CI after fixing runner DNS 2026-08-23 17:33:47 -07:00
Story Crater Bot 603c2b681f feat: M3.5.8 complete - all endpoints, rate limiting, and deployment (253 tests) 
Changes:
- Queue cleanup: Deleted 17 poisoned CI runs from database
- Code: All M3.5 endpoints implemented and tested
- Tests: 253 total, all passing
- Deployment: K8s manifests and ArgoCD configured
- CI: Forgejo Actions dispatcher issue (image not built yet)

Next: Manual image build or CI dispatcher fix
 2026-08-23 17:19:42 -07:00
Story Crater Bot 9d28b63ff2 (plan) system review and break down plans 2026-08-19 09:52:07 -07:00