shinalok
a05d2f474e
IDEA-8: GraphRAG — NetworkX 기반 지식 그래프
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- td_knowledge_graph 테이블 (user_id, subject, relation, object 트리플)
- GraphService: MultiDiGraph 인메모리 캐시 + MySQL 영속화
- add_relation / query_entity LangChain 도구
- call_model에 그래프 요약 자동 주입 (시스템 프롬프트)
- GRAPH_ENABLED=true 환경변수로 활성화
- requirements.txt에 networkx>=3.0 추가
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-06-04 10:08:39 +09:00
shinalok
0b50444e43
IDEA-2/1/5/7: 스마트 알림, 대화 기반 RAG, CRAG, 파라미터 자동 튜닝
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- IDEA-2 스마트 알림: td_reminders 테이블, set_reminder/list_reminders 도구,
SchedulerService(asyncio 60초 루프, D-7/D-1/D-0 Telegram push),
FastAPI lifespan 연동, GET /reminders/{user_id} 엔드포인트
- IDEA-1 대화 기반 RAG: IngestionService.store_text() 추가,
AgentService._maybe_index_conversation() — 응답 후 LLM 판단 → Qdrant 저장
(CONV_RAG_ENABLED=true 활성화, background task로 응답 속도 무관)
- IDEA-5 CRAG: AgentState에 crag_fallback_used 플래그 추가,
crag_check LangGraph 노드 — search_documents 결과 없으면 web_search 자동 주입,
route_after_crag으로 fallback 1회 루프 제어 (CRAG_ENABLED=true 활성화)
- IDEA-7 RAG Auto-Eval: eval/auto_tune.py — API 서버 없이 파라미터 조합별
context_precision/recall 비교, 최적 설정 추천
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-06-04 10:04:05 +09:00
shinalok
68f741af72
Phase 17: Multimodal image understanding via analyze_image tool
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Dual-model approach (C): Qwen3-8B handles conversation, Qwen2.5-VL-7B
analyzes images on demand via analyze_image LangChain tool.
- services/model/mlx_vision_model.py: MlxVisionModel (mlx-vlm wrapper, lazy load)
- services/agent/tools.py: make_vision_tool(vision_model, image_path)
- agent_service.py: stream_response(image_path=None), dynamic tool binding
via config["image_path"] — thread-safe per-request rebinding
- container.py: vision_model Singleton provider
- config.py: vision_enabled, vision_model_id, vision_max_tokens
- api.py: image_base64 in ChatRequest, decode to temp file, cleanup after stream
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-06-02 13:52:10 +09:00
shinalok
e9a6d00059
Phase 23: WebUI separation — api.py + youlbot-webui project
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- api.py: /chat SSE done event now includes run_id for feedback linking
(format: data: {"__done": true, "run_id": "uuid"})
- api.py: Add POST /feedback endpoint with LangSmith integration
- ROADMAP.md: Add Phase 23 documentation
Note: youlbot-webui/ created at /Users/sal/workspace/youlbot-webui/
(separate project, tracked independently)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-05-30 22:00:22 +09:00
shinalok
2e9e8a33fe
Implement Phase 22: REST API (FastAPI + SSE streaming)
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- api.py: FastAPI 앱 신규 생성
- GET /health, POST /chat (SSE), POST /reset, POST /ingest, GET/DELETE /documents
- SSE 포맷: data: <JSON 토큰>\n\n / data: [DONE]\n\n
- Bearer Token 인증 (API_TOKEN 미설정 시 개발 모드)
- user_id 파라미터로 멀티유저 지원 (기존 AgentService·DB 구조 재사용)
- config.py: api_token 필드 추가
- app.py: _get_agent에 query_rewrite_enabled 누락 수정
- requirements.txt: fastapi, uvicorn[standard], python-multipart 추가
- ROADMAP: Phase 22 ✅ , Telegram Bot 클라이언트 예시 추가
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-05-29 20:11:49 +09:00
shinalok