Sam Rolfe
628ba96998
- Frontend: Vite + React + TypeScript chat interface - Backend: FastAPI gateway with LangGraph routing - Knowledge Service: ChromaDB RAG with Gitea scraper - LangGraph Service: Multi-agent orchestration - Airflow: Scheduled Gitea ingestion DAG - Documentation: Complete plan and implementation guides Architecture: - Modular Docker Compose per service - External ai-mesh network for communication - Fast rebuilds with /app/packages pattern - Intelligent agent routing (no hardcoded keywords) Services: - Frontend (5173): React chat UI - Chat Gateway (8000): FastAPI entry point - LangGraph (8090): Agent orchestration - Knowledge (8080): ChromaDB RAG - Airflow (8081): Scheduled ingestion - PostgreSQL (5432): Chat history Excludes: node_modules, .venv, chroma_db, logs, .env files Includes: All source code, configs, docs, docker files
48 lines
1.8 KiB
Org Mode
48 lines
1.8 KiB
Org Mode
#+TITLE: Phase 3: Knowledge Engine & Agent Orchestration
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#+AUTHOR: Giordano (via opencode)
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#+OPTIONS: toc:2
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* GOAL
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Build a "Deep Knowledge Agent" (DKA) that acts as a secure, quarantined bridge between the Chat Gateway and private data sources.
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* ARCHITECTURE OVERVIEW
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** Layers
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1. Public Gateway: FastAPI (The "Voice").
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2. Orchestration Layer: LangGraph Supervisor (The "Router").
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3. Quarantined Agent: DKA / Librarian (The "Keeper of Secrets").
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- Strictly Read-Only.
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- Accesses ChromaDB and Media stores.
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4. Specialist Agent: Opencode (The "Engineer").
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** Data Sources (The "Knowledge Mesh")
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- [ ] *Code*: Gitea (Repos, Markdown docs).
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- [ ] *Notes*: Trilium Next, Obsidian, Flatnotes, HedgeDoc.
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- [ ] *Wiki*: DokuWiki.
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- [ ] *Inventory*: HomeBox (Physical gear, photos).
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- [ ] *Tasks*: Vikunja.
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- [ ] *Media*: Immich (Photos/Videos metadata via Gemini Vision).
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** Agent Tooling & Orchestration
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- [ ] *Orchestrators*: CAO CLI, Agent Pipe.
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- [ ] *External Agents*: Goose, Aider, Opencode (Specialist).
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* COMPONENT DETAILS
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** The Librarian (DKA - LangGraph)
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- Purpose: Semantic retrieval and data synthesis from vectors.
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- Tools:
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- ~query_chroma~: Search the vector database.
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- ~fetch_media_link~: Returns a signed URL/path for Immich/HomeBox images.
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- Constraints:
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- NO ~bash~ or ~write~ tools.
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** The Ingestion Pipeline (Airflow/Custom Python)
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- [ ] *Multi-Source Scrapers*: API-based (Gitea, Immich) and File-based (Obsidian).
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- [ ] *Vision Integration*: Gemini analyzes Immich photos to create searchable text descriptions.
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- [ ] *Storage*: ChromaDB (Vectors) + PostgreSQL (Metadata/Hashes).
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* TODO LIST [0/4]
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- [ ] Create 'knowledge_service' directory.
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- [ ] Implement ~test_rag.py~ (Hello World retrieval).
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- [ ] Build basic scraper for ~hobbies.org~.
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- [ ] Integrate DKA logic into the FastAPI Gateway.
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