Add changes made through MCP for backup
This commit is contained in:
Χγφτ Kompanion
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{
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"projectName": "metal-kompanion-mcp",
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"projectDescription": "MCP backend for Kompanion: memory/context/embedding provider over MCP, built from scratch (qtmcp-based) to persist conversation state and serve embeddings + retrieval to avoid forgetting across threads.",
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{
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"id": 1,
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"title": "Project Setup: metal-kompanion-mcp",
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"description": "MCP backend for Kompanion: memory/context/embedding provider over MCP, built from scratch (qtmcp-based) to persist conversation state and serve embeddings + retrieval to avoid forgetting across threads.",
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"status": "todo",
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"priority": 700,
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"priorityDisplay": "high",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:31:50.258Z",
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"id": 2,
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"title": "Design MCP memory/context API",
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"description": "Specify MCP tools for: save_context, recall_context, embed_text, upsert_memory, search_memory, warm_cache. Define input/output schemas, auth, and versioning.",
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"status": "in_progress",
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"priority": 500,
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"createdAt": "2025-10-13T17:32:24.705Z",
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"updatedAt": "2025-10-13T17:40:02.144Z",
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"id": "2.1",
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"title": "Write JSON Schemas for tools (done)",
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"status": "todo",
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"createdAt": "2025-10-13T17:39:21.256Z",
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"updatedAt": "2025-10-13T17:39:21.256Z",
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"timestamp": "2025-10-13T17:39:21.256Z",
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"type": "log",
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"message": "Subtask created with title: \"Write JSON Schemas for tools (done)\""
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"type": "log",
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"message": "Task created with title: \"Design MCP memory/context API\""
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},
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{
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"timestamp": "2025-10-13T17:40:02.144Z",
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"type": "log",
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"message": "Status changed from \"todo\" to \"in_progress\". Message: Docs and schemas created. Proceeding to server scaffold and adapters."
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}
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]
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},
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{
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"id": 3,
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"title": "Select embedding backend & storage",
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"description": "Choose between local (Ollama/gguf via llama.cpp embedding) vs remote (OpenAI/SentenceTransformers). Storage: sqlite+vectstore (pgvector/qdrant/chroma). Provide abstraction + adapters.",
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"status": "todo",
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"priority": 501,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:32:35.110Z",
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"timestamp": "2025-10-13T17:32:35.110Z",
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"type": "log",
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"message": "Task created with title: \"Select embedding backend & storage\""
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}
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]
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},
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{
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"id": 4,
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"title": "Scaffold qtmcp-based server",
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"description": "Set up C++/Qt MCP server skeleton using qtmcp. Implement handshake, tool registration, and simple ping tool. Build with CMake in /home/kompanion/dev/metal/src/metal-kompanion.",
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"status": "in_progress",
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"priority": 499,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:32:47.443Z",
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"timestamp": "2025-10-13T17:32:47.443Z",
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"type": "log",
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"message": "Task created with title: \"Scaffold qtmcp-based server\""
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},
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{
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"timestamp": "2025-10-13T18:13:07.568Z",
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"type": "log",
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"message": "Status changed from \"todo\" to \"in_progress\". Message: Starting MCP server skeleton with tool registry, ping tool, and placeholders for kom.memory.v1 handlers."
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}
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]
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},
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{
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"id": 5,
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"title": "Implement memory adapters",
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"description": "Adapters: (1) SQLite+FAISS/pgvector, (2) Qdrant, (3) Chroma. CRUD: upsert, delete, query, batch. Support namespaces (project/thread), TTL, metadata tags.",
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"status": "todo",
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"priority": 502,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:32:57.756Z",
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"timestamp": "2025-10-13T17:32:57.756Z",
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"type": "log",
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"message": "Task created with title: \"Implement memory adapters\""
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}
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]
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},
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{
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"id": 6,
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"title": "Deep research: memory DB architecture & schema",
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"description": "Survey best practices for conversational memory stores (RAG, TTL, namespaces, versioning). Produce target schema for Postgres+pgvector and SQLite mappings.",
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"status": "todo",
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"priority": 498,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:46:18.403Z",
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"timestamp": "2025-10-13T17:46:18.403Z",
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"type": "log",
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"message": "Task created with title: \"Deep research: memory DB architecture & schema\""
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}
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]
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},
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{
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"id": 7,
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"title": "Decide primary DB: Postgres+pgvector vs SQLite+FAISS",
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"description": "Evaluate tradeoffs (multi-user, concurrency, migrations, backups). Pick canonical prod DB and document local dev fallback.",
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"status": "todo",
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"priority": 503,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:47:21.042Z",
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"updatedAt": "2025-10-13T17:47:21.042Z",
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"type": "log",
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"message": "Task created with title: \"Decide primary DB: Postgres+pgvector vs SQLite+FAISS\""
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}
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]
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},
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{
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"id": 8,
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"title": "Implement DAL + migrations (pgvector)",
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"description": "Create C++ DAL layer for namespaces, items, chunks, embeddings. Add migration runner and seed scripts. Map MCP tool calls to DB ops.",
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"status": "todo",
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"priority": 497,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T17:47:30.982Z",
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"timestamp": "2025-10-13T17:47:30.982Z",
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"type": "log",
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"message": "Task created with title: \"Implement DAL + migrations (pgvector)\""
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}
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]
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},
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{
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"id": 9,
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"title": "Add cloud DB hardening (RLS, FTS/trgm, ANN indexes)",
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"description": "Implement RLS policies; add FTS + pg_trgm for lexical search; unique (namespace_id, key); partial ANN indexes per model.",
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"status": "todo",
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"priority": 504,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:13.769Z",
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"timestamp": "2025-10-13T19:13:13.769Z",
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"type": "log",
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"message": "Task created with title: \"Add cloud DB hardening (RLS, FTS/trgm, ANN indexes)\""
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}
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]
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},
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{
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"id": 10,
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"title": "Server enforcement: scope injection + rate limits",
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"description": "Inject namespace/user via session context; default-deny for scope widening; add simple per-tool rate limits.",
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"status": "todo",
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"priority": 496,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:21.164Z",
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"updatedAt": "2025-10-13T19:13:21.164Z",
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"timestamp": "2025-10-13T19:13:21.164Z",
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"type": "log",
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"message": "Task created with title: \"Server enforcement: scope injection + rate limits\""
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}
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},
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{
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"id": 11,
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"title": "Redaction & sensitivity pipeline",
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"description": "Implement preprocessing to detect/seal secrets; set metadata.sensitivity; skip FTS/embeddings for `secret` items.",
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"status": "todo",
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"priority": 505,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:29.391Z",
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"updatedAt": "2025-10-13T19:13:29.392Z",
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"timestamp": "2025-10-13T19:13:29.391Z",
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"type": "log",
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"message": "Task created with title: \"Redaction & sensitivity pipeline\""
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}
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]
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},
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{
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"id": 12,
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"title": "Private vault mode (key-only retrieval)",
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"description": "Implement vault path for secret items: encrypted-at-rest only; disable participation in FTS/vector; key-based recall APIs.",
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"status": "todo",
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"priority": 495,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:36.653Z",
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"type": "log",
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"message": "Task created with title: \"Private vault mode (key-only retrieval)\""
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}
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]
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},
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{
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"id": 13,
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"title": "Local backup tools: export/import (E2EE)",
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"description": "Add kom.local.v1.backup.export_encrypted / import_encrypted using the draft backup format.",
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"status": "todo",
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"priority": 506,
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"priorityDisplay": "P1",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:44.851Z",
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"timestamp": "2025-10-13T19:13:44.851Z",
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"type": "log",
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"message": "Task created with title: \"Local backup tools: export/import (E2EE)\""
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}
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]
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},
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{
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"id": 14,
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"title": "Cloud adapters: backup/sync & payments stubs",
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"description": "Expose kom.cloud.v1.backup.upload/restore, kom.cloud.v1.sync.push/pull, and payments.* stubs.",
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"status": "todo",
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"priority": 494,
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"priorityDisplay": "P2",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:13:55.490Z",
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"timestamp": "2025-10-13T19:13:55.490Z",
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"type": "log",
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"message": "Task created with title: \"Cloud adapters: backup/sync & payments stubs\""
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}
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]
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},
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{
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"id": 15,
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"title": "Purge job & admin delete paths",
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"description": "Implement scheduled hard-deletes for soft-deleted/expired items; add admin nuke namespace/user procedure.",
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"status": "todo",
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"priority": 507,
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"priorityDisplay": "P2",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:14:06.080Z",
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"message": "Task created with title: \"Purge job & admin delete paths\""
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]
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},
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{
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"id": 16,
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"title": "Test suite: privacy & hybrid search",
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"description": "Cross-tenant leakage, redaction invariants, TTL/purge, lexical vs hybrid parity, hosted vs local parity.",
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"status": "todo",
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"priority": 493,
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"priorityDisplay": "P0",
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"dependsOn": [],
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"createdAt": "2025-10-13T19:14:14.309Z",
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},
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{
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"id": 17,
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"title": "Enable Qwen-2.5-Coder with tool support (Happy-Code profile)",
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"description": "Prepare system prompt + registry injection + JSON-only protocol enforcement; provide tool schemas and example transcripts; validate with kom.memory/local backup tools.",
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"status": "todo",
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"priority": 508,
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"priorityDisplay": "P0",
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||||
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||||
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},
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{
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"id": 18,
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"title": "Expose Agentic-Control-Framework as a tool",
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"description": "Wrap ACF endpoints into a tool registry accessible to models (list/add/update tasks, read/write files, run commands) with strict allowlist per workspace.",
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"status": "todo",
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"priority": 492,
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"priorityDisplay": "P0",
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||||
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||||
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||||
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||||
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"message": "Task created with title: \"Expose Agentic-Control-Framework as a tool\""
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},
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{
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"id": 19,
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"title": "DAL skeleton + SQL calls (pgvector)",
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"description": "Create DAL interfaces and pgvector implementation stubs: connect, begin/commit, upsert item/chunk/embedding, search (text+vector placeholder), prepared SQL in sql/pg. Wire handlers to DAL in no-op mode.",
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"status": "todo",
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"priority": 509,
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||||
"priorityDisplay": "P0",
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||||
"dependsOn": [],
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||||
"createdAt": "2025-10-13T23:29:49.918Z",
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"message": "Task created with title: \"DAL skeleton + SQL calls (pgvector)\""
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||||
},
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||||
{
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||||
"id": 20,
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||||
"title": "Claude Code integration rescue plan",
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"description": "Stabilize Qwen-2.5-Coder inside Claude Code despite heavy system prompts: hard system override, JSON-only protocol, stop-sequences, tool registry injection, and fallback DSL.",
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"status": "todo",
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"priority": 491,
|
||||
"priorityDisplay": "P0",
|
||||
"dependsOn": [],
|
||||
"createdAt": "2025-10-14T00:06:04.896Z",
|
||||
"updatedAt": "2025-10-14T00:06:04.896Z",
|
||||
"subtasks": [],
|
||||
"lastSubtaskIndex": 0,
|
||||
"relatedFiles": [],
|
||||
"activityLog": [
|
||||
{
|
||||
"timestamp": "2025-10-14T00:06:04.896Z",
|
||||
"type": "log",
|
||||
"message": "Task created with title: \"Claude Code integration rescue plan\""
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
# Cursor AI Workflow Rules for Agentic Control Framework
|
||||
|
||||
# (Define rules here to tell Cursor how to use acf commands)
|
||||
|
||||
# Example:
|
||||
# To list tasks, use the command: acf list
|
||||
# To get the next task: acf next
|
||||
|
|
@ -0,0 +1,35 @@
|
|||
# Repository Guidelines
|
||||
This guide supports new agents contributing to `metal-kompanion`, the MCP backend for Kompanion. Follow these practices to keep the service buildable, testable, and easy to review.
|
||||
|
||||
## Project Structure & Module Organization
|
||||
- `src/` holds C++ code: `mcp/` for server facade and tool routing, `memory/` for embeddings contracts, `dal/` for persistence, and `policy/` for capability rules.
|
||||
- `docs/` hosts design notes; `runtime/kom_runner.py` is the Python orchestrator for agent execution against Ollama; `db/` and `sql/` capture Postgres schemas.
|
||||
- Place sample payloads or fixtures under `tests/` (currently `tests/schemas/` for JSON samples). Generated artifacts live in `build/`.
|
||||
|
||||
## Build, Test, and Development Commands
|
||||
```bash
|
||||
cmake -S . -B build # configure with CMake 3.22+, targets C++20
|
||||
cmake --build build -j # compile the kom_mcp executable
|
||||
ctest --test-dir build # run CTest suites once they are defined
|
||||
python3 runtime/kom_runner.py # exercise the runtime loop (requires OLLAMA_BASE)
|
||||
```
|
||||
Run the Python runtime from a virtualenv seeded with `pip install -r runtime/requirements.txt`.
|
||||
|
||||
## Coding Style & Naming Conventions
|
||||
- C++20, clang/gcc friendly, 4-space indentation, braces on the same line (`class KomMcpServer {`).
|
||||
- Classes use PascalCase; methods camelCase; private members keep the trailing underscore (`tools_`). Prefer `std::` types and RAII helpers over raw pointers.
|
||||
- Keep headers lean: forward declare where possible and document non-obvious behavior with concise comments.
|
||||
|
||||
## Testing Guidelines
|
||||
- Add unit or schema validation tests under `tests/`, mirroring the source tree (e.g., `tests/mcp/` for dispatcher tests).
|
||||
- Register new tests with CTest via `add_test` in `CMakeLists.txt`; verify they pass with `ctest --output-on-failure`.
|
||||
- Provide realistic JSON samples for new tools alongside schema updates to guard against regressions.
|
||||
|
||||
## Commit & Pull Request Guidelines
|
||||
- Follow the existing `scope: message` pattern from git history (`docker: fix host ollama port`); keep messages imperative and present tense.
|
||||
- Each PR should state intent, link relevant issues, and include before/after notes or screenshots when UI-adjacent runtime behavior changes.
|
||||
- Mention how to reproduce test runs (`cmake --build`, `ctest`) and flag configuration or migration steps (e.g., `sql/` changes).
|
||||
|
||||
## Security & Configuration Tips
|
||||
- Do not commit secrets; runtime state lives beneath XDG paths (`~/.local/state/kompanion`). Document any new env vars in `docs/`.
|
||||
- When integrating new tools, ensure access control aligns with `policy/` capabilities and record expected journal entries in `runtime` docs.
|
||||
|
|
@ -1,10 +1,20 @@
|
|||
cmake_minimum_required(VERSION 3.16)
|
||||
project(MetalKompanion LANGUAGES CXX)
|
||||
cmake_minimum_required(VERSION 3.22)
|
||||
project(metal_kompanion_mcp LANGUAGES CXX)
|
||||
|
||||
set(CMAKE_CXX_STANDARD 20)
|
||||
set(CMAKE_CXX_STANDARD_REQUIRED ON)
|
||||
find_package(Qt6 REQUIRED COMPONENTS Core Network DBus)
|
||||
add_executable(kompanion_server
|
||||
src/main.cpp
|
||||
)
|
||||
target_link_libraries(kompanion_server Qt6::Core Qt6::Network Qt6::DBus)
|
||||
install(TARGETS kompanion_server RUNTIME DESTINATION bin)
|
||||
|
||||
# Placeholder: find Qt and qtmcp when available
|
||||
# find_package(Qt6 COMPONENTS Core Network REQUIRED)
|
||||
# find_package(qtmcp REQUIRED)
|
||||
|
||||
add_executable(kom_mcp src/main.cpp)
|
||||
# target_link_libraries(kom_mcp PRIVATE Qt6::Core Qt6::Network qtmcp)
|
||||
|
||||
install(TARGETS kom_mcp RUNTIME DESTINATION bin)
|
||||
|
||||
add_executable(test_mcp_tools tests/contract/test_mcp_tools.cpp)
|
||||
target_include_directories(test_mcp_tools PRIVATE src)
|
||||
|
||||
enable_testing()
|
||||
add_test(NAME contract_mcp_tools COMMAND test_mcp_tools)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,20 @@
|
|||
# metal-kompanion-mcp
|
||||
|
||||
MCP backend and memory provider for Kompanion. Uses `qtmcp` (Qt-based MCP) to expose tools under namespace `kom.memory.v1`.
|
||||
|
||||
## Build
|
||||
```bash
|
||||
cmake -S . -B build
|
||||
cmake --build build -j
|
||||
```
|
||||
|
||||
## Layout
|
||||
- `src/main.cpp` – entry point (stub until qtmcp wired)
|
||||
- `src/mcp/ToolSchemas.json` – JSON Schemas for MCP tools
|
||||
- `src/memory/` – interfaces for embedder and vector store
|
||||
- `docs/` – design notes
|
||||
|
||||
## Next
|
||||
- Add qtmcp dependency and implement server with tool registration.
|
||||
- Implement adapters: embedder(s) + vector store(s).
|
||||
- Wire `save_context`/`recall_context` to persistent store.
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
#!/usr/bin/env bash
|
||||
set -euo pipefail
|
||||
cd "$(dirname "$0")/.."
|
||||
docker compose -f docker/compose.host.yml up -d
|
||||
|
|
@ -0,0 +1 @@
|
|||
-- Kompanion quick checks
|
||||
|
|
@ -0,0 +1 @@
|
|||
-- placeholder: see chat for full Branch Embeddings schema
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
-- pgvector knowledge schema (v0.2, branch embeddings)nCREATE EXTENSION IF NOT EXISTS vector;nn-- Documents tracked by content hash; multiple logical paths may point to same blobnCREATE TABLE IF NOT EXISTS doc_blob (n blob_sha256 text PRIMARY KEY,n bytes bigint NOT NULL,n created_at timestamptz DEFAULT now()n);nn-- Logical document identity and branch/commit lineagenCREATE TABLE IF NOT EXISTS doc (n id bigserial PRIMARY KEY,n origin text, -- e.g., filesystem, forgejo, exportn root_path text, -- repo root or base dirn rel_path text, -- path relative to rootn blob_sha256 text REFERENCES doc_blob(blob_sha256)n);nCREATE TABLE IF NOT EXISTS branch (n id bigserial PRIMARY KEY,n name text UNIQUE,n created_at timestamptz DEFAULT now()n);nCREATE TABLE IF NOT EXISTS revision (n id bigserial PRIMARY KEY,n branch_id bigint REFERENCES branch(id) ON DELETE CASCADE,n parent_id bigint REFERENCES revision(id),n commit_sha text, -- optional link to VCSn message text,n created_at timestamptz DEFAULT now()n);nn-- Chunked text with provenance; each revision can re-chunk same docnCREATE TABLE IF NOT EXISTS chunk (n id bigserial PRIMARY KEY,n revision_id bigint REFERENCES revision(id) ON DELETE CASCADE,n doc_id bigint REFERENCES doc(id) ON DELETE CASCADE,n lineno int,n text text NOT NULL,n tags text[],n sha256 text,n created_at timestamptz DEFAULT now()n);nCREATE INDEX IF NOT EXISTS idx_chunk_doc ON chunk(doc_id);nCREATE INDEX IF NOT EXISTS idx_chunk_rev ON chunk(revision_id);nn-- Embedding models registrynCREATE TABLE IF NOT EXISTS embed_model (n id bigserial PRIMARY KEY,n name text UNIQUE NOT NULL, -- e.g., mxbai-embed-largen dims int NOT NULL,n tokenizer text,n notes textn);nn-- Branch embeddings: per revision, per chunk, per model (dims parametrized by table)nCREATE TABLE IF NOT EXISTS embedding_1024 (n id bigserial PRIMARY KEY,n chunk_id bigint REFERENCES chunk(id) ON DELETE CASCADE,n model_id bigint REFERENCES embed_model(id),n embedding vector(1024) NOT NULL,n created_at timestamptz DEFAULT now()n);nCREATE INDEX IF NOT EXISTS idx_emb1024_chunk ON embedding_1024(chunk_id);nCREATE INDEX IF NOT EXISTS idx_emb1024_vec ON embedding_1024 USING ivfflat (embedding vector_l2_ops) WITH (lists=100);nn-- Views: latest chunks per branchnCREATE OR REPLACE VIEW v_latest_chunks AS
|
||||
SELECT c.* FROM chunk c
|
||||
JOIN (SELECT revision_id, max(id) over (partition by doc_id, branch_id) as maxid, doc_id
|
||||
FROM revision r JOIN chunk c2 ON c2.revision_id=r.id) t
|
||||
ON c.id=t.maxid;nn-- Ledger mirror (optional)nCREATE TABLE IF NOT EXISTS ledger_mirror (n id bigserial PRIMARY KEY,n ts timestamptz NOT NULL,n actor text,n action text,n body jsonbn);n
|
||||
|
|
@ -0,0 +1 @@
|
|||
# Identity & Aspects (placeholder)
|
||||
|
|
@ -0,0 +1 @@
|
|||
# Runtime vs Pattern Exchange (placeholder)
|
||||
|
|
@ -0,0 +1,25 @@
|
|||
# Encrypted Backup Format (Draft)
|
||||
|
||||
> *Cipher left open by design (to be decided: AES-GCM vs XChaCha20-Poly1305; key storage via OS keychain or passphrase vault).*
|
||||
|
||||
## Goals
|
||||
- Client-side encrypted backups (no cleartext leaves device).
|
||||
- Content-addressed chunks with manifest; resumable upload.
|
||||
- Key rotation support and device enrollment flow.
|
||||
|
||||
## Artifacts
|
||||
- `manifest.json` — version, namespace(s), chunks, sizes, hashes, KDF params, encryption metadata.
|
||||
- `payload.tar.zst` — concatenated content/chunks (encrypted).
|
||||
|
||||
## Flow
|
||||
1. Collect items/chunks for selected namespaces.
|
||||
2. Serialize → compress → encrypt → write manifest.
|
||||
3. Upload manifest + blob via provider adapter (e.g., Google Drive) as opaque objects.
|
||||
4. Restore: download → decrypt → verify hashes → import.
|
||||
|
||||
## Provider Adapters
|
||||
- `kom.local.v1.backup.export_encrypted` / `import_encrypted` (local).
|
||||
- `kom.cloud.v1.backup.upload` / `restore` (remote; encrypted blobs only).
|
||||
|
||||
## Open Questions
|
||||
- Final cipher/KDF choices, key wrapping and rotation UX, multi-namespace packaging.
|
||||
|
|
@ -0,0 +1,32 @@
|
|||
# Claude Code: Hard Overrides to Stabilize Tool Use
|
||||
|
||||
When Claude Code's layered system prompts clash with our tool protocol, force a minimal, deterministic lane.
|
||||
|
||||
## Settings (recommended)
|
||||
- **Stop sequences**: `
|
||||
````, `
|
||||
|
||||
` (or whatever the IDE uses to inject formatting).
|
||||
- **Max output tokens**: small (e.g., 512).
|
||||
- **Temperature**: 0.1-0.3.
|
||||
- **Disable auto-formatting / code fences** if possible.
|
||||
- **Disable auto-tool use**; we trigger tools via explicit JSON only.
|
||||
|
||||
## System message (short)
|
||||
Use the contents of `docs/prompts/qwen_tool_mode_system.txt` verbatim as the *final* system layer closest to the model.
|
||||
|
||||
## Runtime guardrails
|
||||
- Reject any non-JSON output; send a short corrective user message: `OUTPUT MUST BE JSON. Please resend.`
|
||||
- If repeated, send `{"final":{"content":{"error":"RESET_REQUIRED"}}}` back and restart the session.
|
||||
|
||||
## Registry injection
|
||||
- Provide the tool list and JSON Schemas (kom.memory.*, kom.local.backup.*, acf.*).
|
||||
- Keep it short; link to full schemas if the UI allows references.
|
||||
|
||||
## Troubleshooting
|
||||
- If model keeps adding prose, tighten stop sequences and lower max tokens.
|
||||
- If JSON keys drift, include a 2–3 line example of a **valid** `action` and a **valid** `final`.
|
||||
- If it calls undefined tools, respond with a single tool error and re-present the allowlist.
|
||||
|
||||
## Fallback DSL
|
||||
- Accept `@tool <name> {json-args}` and convert to a JSON `action` behind the scenes when necessary.
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
# DAL Skeleton (pgvector)
|
||||
|
||||
## Interfaces
|
||||
- `IDatabase` — connect/tx + memory ops (ensureNamespace, upsertItem/Chunks/Embeddings, searchText/searchVector).
|
||||
- `PgDal` — stub implementation for now (no libpq linked).
|
||||
|
||||
## SQL Calls (target)
|
||||
- ensureNamespace: `INSERT ... ON CONFLICT (name) DO UPDATE RETURNING id`
|
||||
- upsertItem: `INSERT ... ON CONFLICT (id) DO UPDATE SET ... RETURNING id`
|
||||
- upsertChunks: batch insert w/ `RETURNING id`
|
||||
- upsertEmbeddings: batch insert; ensure `model, dim` set, vector column populated.
|
||||
- searchText: FTS/trigram query filtered by namespace/thread/tags.
|
||||
- searchVector: `ORDER BY embeddings.vector <-> $1 LIMIT k` (with filters).
|
||||
|
||||
## Next
|
||||
- Wire `Handlers::upsert_memory` / `search_memory` to `IDatabase`.
|
||||
- Add libpq (or pqxx) and parameterized statements.
|
||||
- Add RLS/session GUCs & retries.
|
||||
|
||||
|
|
@ -0,0 +1,36 @@
|
|||
# Target Database Schema for Kompanion Memory (v0)
|
||||
|
||||
**Primary**: Postgres 14+ with `pgvector` (v0.6+) for embeddings.
|
||||
**Alt**: SQLite 3 + FAISS (local dev / fallback).
|
||||
|
||||
## Design Principles
|
||||
- **Namespaces** (`project:user:thread`) partition memory and enable scoped retrieval.
|
||||
- **Separation of items vs chunks**: items are logical notes/contexts; chunks are embedding units.
|
||||
- **Metadata-first**: JSONB metadata with selective indexed keys; tags array.
|
||||
- **Retention**: TTL via `expires_at`; soft-delete via `deleted_at`.
|
||||
- **Versioning**: monotonically increasing `revision`; latest view via upsert.
|
||||
- **Observability**: created/updated audit, model/dim for embeddings.
|
||||
|
||||
## Entities
|
||||
- `namespaces` – registry of logical scopes.
|
||||
- `threads` – optional conversational threads within a namespace.
|
||||
- `users` – optional association to user identity.
|
||||
- `memory_items` – logical items with rich metadata and raw content.
|
||||
- `memory_chunks` – embedding-bearing chunks derived from items.
|
||||
- `embeddings` – embedding vectors (one per chunk + model info).
|
||||
|
||||
## Retrieval Flow
|
||||
1) Query text → embed → ANN search on `embeddings.vector` (filtered by namespace/thread/tags/metadata).
|
||||
2) Join back to `memory_items` to assemble content and metadata.
|
||||
|
||||
## Indexing
|
||||
- `embeddings`: `USING ivfflat (vector) WITH (lists=100)` (tune), plus btree on `(model, dim)`.
|
||||
- `memory_items`: GIN on `metadata`, GIN on `tags`, btree on `(namespace_id, thread_id, created_at)`.
|
||||
|
||||
## SQLite Mapping
|
||||
- Same tables sans vector column; store vectors in a sidecar FAISS index keyed by `chunk_id`. Maintain consistency via triggers in app layer.
|
||||
|
||||
## Open Questions
|
||||
- Hybrid search strategy (BM25 + vector) — defer to v1.
|
||||
- Eventing for cache warms and eviction.
|
||||
- Encryption at rest and PII handling.
|
||||
|
|
@ -0,0 +1,56 @@
|
|||
# Design Decision: Local-First Personal Store with Optional Federated Services
|
||||
|
||||
**Decision**: Kompanion adopts a **two-tier architecture**. A personal, local store (Akonadi-like) is the *authoritative home* of a user's data and operates fully offline. An optional federated layer provides encrypted backups, multi-device sync, and paid cloud conveniences (e.g., hosted search/rerank). Users can run **purely local**, or selectively enable cloud features.
|
||||
|
||||
**Encryption Note**: We deliberately leave the *exact cryptography suite* open to allow hardware/OS keychains, libsodium, AES-GCM, or XChaCha20-Poly1305. The guardrails below assume **end-to-end encryption (E2EE)** with keys controlled by the user.
|
||||
|
||||
---
|
||||
|
||||
## 1) Personal Store (Local Core) — `kom.local.v1`
|
||||
- Runs entirely on-device; no network required.
|
||||
- DB: SQLite (+ FTS/trigram for "rgrep" feel) + FAISS for vectors.
|
||||
- Embeddings/Reranker: local (Ollama + optional local reranker).
|
||||
- Privacy defaults: do-not-embed secrets; private-vault items are never vectorized/FTS'd; E2EE for backups/exports.
|
||||
- Backup tools: `backup.export_encrypted`, `backup.import_encrypted` (E2EE blobs).
|
||||
|
||||
## 2) Federated Services (Optional) — `kom.cloud.v1`
|
||||
- Adds encrypted sync, cloud backup, micropayment-backed hosted compute (e.g., heavy reranking), and optional hosted pgvector search.
|
||||
- Server sees ciphertext plus minimal metadata; hosted search is opt-in and may store embeddings either encrypted or plaintext **only by explicit consent**.
|
||||
- Per-namespace tenancy and isolation (RLS when using Postgres).
|
||||
|
||||
## 3) Key & Auth Model
|
||||
- Users may **only retain authentication/secret-store access**; Kompanion handles day-to-day operations.
|
||||
- Device enrollment shares/wraps keys securely (mechanism TBD; QR/device handoff).
|
||||
- Key rotation and export are first-class; backups are always encrypted client-side.
|
||||
|
||||
## 4) Search Modes
|
||||
- **Lexical**: FTS + trigram, scoped to namespace/thread/user; grep-like snippets.
|
||||
- **Semantic**: vector ANN with local reranker by default.
|
||||
- **Hybrid**: configurable orchestration; always respects scope and privacy flags.
|
||||
|
||||
## 5) Privacy Controls
|
||||
- Sensitivity flags: `metadata.sensitivity = secret|private|normal`.
|
||||
- `secret` items: E2EE only (no FTS, no embeddings).
|
||||
- Server-side scope injection (namespace/user) in all handlers; default-deny posture.
|
||||
- Purge policy: soft-delete + scheduled hard-delete; cascades to chunks/embeddings and remote copies.
|
||||
|
||||
## 6) Compatibility with Postgres+pgvector
|
||||
- When cloud search is enabled, a hosted Postgres+pgvector instance enforces isolation via RLS and per-namespace session GUCs.
|
||||
- Local SQLite store remains the source of truth unless user opts to delegate search to cloud.
|
||||
|
||||
---
|
||||
|
||||
## Action List (from privacy review)
|
||||
1. **DB hardening (cloud path)**: add RLS policies; add FTS + pg_trgm; unique `(namespace_id, key)`; partial ANN indexes per model.
|
||||
2. **Server enforcement**: inject namespace/user via session context (GUCs); default-deny widening; rate limits.
|
||||
3. **Redaction pipeline**: protect secrets before embedding; skip embedding/FTS for `secret` items.
|
||||
4. **Private vault mode**: key-only retrieval paths for sensitive items (no index participation).
|
||||
5. **Backups**: define E2EE export/import format; provider adapters (e.g., Google Drive) use pre-encrypted blobs.
|
||||
6. **Sync**: event-log format (append-only); conflict rules; device enrollment + key wrapping; later CRDT if needed.
|
||||
7. **Purging**: scheduled hard-deletes; admin "nuke namespace/user" procedure.
|
||||
8. **Tests**: cross-tenant leakage, redaction invariants, purge/TTL, hybrid-vs-lexical, hosted-vs-local parity.
|
||||
|
||||
## Files to Watch
|
||||
- `docs/db-schema.md`, `sql/pg/001_init.sql` (cloud path)
|
||||
- `src/mcp/ToolSchemas.json` and MCP handlers (scope + sensitivity gates)
|
||||
- `kom.local.v1.backup.*`, `kom.cloud.v1.*` (new tool surfaces)
|
||||
|
|
@ -0,0 +1,26 @@
|
|||
# Embedding Backends & Storage Options
|
||||
|
||||
## Embeddings
|
||||
- **Local**: Ollama + llama.cpp gguf (e.g., nomic-embed-text, all-MiniLM-gguf).
|
||||
- **Remote**: OpenAI text-embedding-3-small/large; SentenceTransformers via Python service.
|
||||
|
||||
### Abstraction
|
||||
`IEmbedder` interface with `embed(texts: string[], model?: string) -> {model, vectors}`.
|
||||
|
||||
## Storage
|
||||
- **SQLite + FAISS** (local, simple)
|
||||
- **Postgres + pgvector** (robust, SQL)
|
||||
- **Qdrant** (fast ANN, tags)
|
||||
- **Chroma** (lightweight)
|
||||
|
||||
### Abstraction
|
||||
`IVectorStore` with `upsert`, `query`, `delete`, supports `namespace`, `metadata` filter and TTL.
|
||||
|
||||
## Selection Matrix
|
||||
- If offline-first: SQLite+FAISS + local embedder.
|
||||
- If multi-host: Postgres+pgvector or Qdrant.
|
||||
|
||||
## Next Steps
|
||||
- Implement `IEmbedder` adapters (Ollama, OpenAI).
|
||||
- Implement `IVectorStore` adapters (SQLite+FAISS, pgvector, Qdrant).
|
||||
- Wire to MCP tools in `kom.memory.v1`.
|
||||
|
|
@ -0,0 +1,51 @@
|
|||
# MCP Memory/Context API for Kompanion
|
||||
|
||||
## Goals
|
||||
- Persist long-term context across threads/sessions.
|
||||
- Provide embeddings + retrieval over namespaces (project/user/thread).
|
||||
- Expose via MCP tools with JSON schemas; versioned and testable.
|
||||
|
||||
## Tools
|
||||
### `save_context`
|
||||
Persist a context blob with metadata.
|
||||
- input: `{ namespace: string, key?: string, content: any, tags?: string[], ttl_seconds?: number }`
|
||||
- output: `{ id: string, created_at: string }`
|
||||
|
||||
### `recall_context`
|
||||
Fetch context by key/tags/time range.
|
||||
- input: `{ namespace: string, key?: string, tags?: string[], limit?: number, since?: string }`
|
||||
- output: `{ items: Array<{id:string, key?:string, content:any, tags?:string[], created_at:string}> }`
|
||||
|
||||
### `embed_text`
|
||||
Return vector embedding for given text(s).
|
||||
- input: `{ model?: string, texts: string[] }`
|
||||
- output: `{ model: string, vectors: number[][] }`
|
||||
|
||||
### `upsert_memory`
|
||||
Upsert text+metadata into vector store.
|
||||
- input: `{ namespace: string, items: Array<{id?:string, text:string, metadata?:object, embedding?:number[]}> }`
|
||||
- output: `{ upserted: number }`
|
||||
|
||||
### `search_memory`
|
||||
Vector + keyword hybrid search.
|
||||
- input: `{ namespace: string, query: { text?: string, embedding?: number[], k?: number, filter?: object } }`
|
||||
- output: `{ matches: Array<{id:string, score:number, text?:string, metadata?:object}> }`
|
||||
|
||||
### `warm_cache`
|
||||
Precompute embeddings for recent items.
|
||||
- input: `{ namespace: string, since?: string }`
|
||||
- output: `{ queued: number }`
|
||||
|
||||
## Auth & Versioning
|
||||
- toolNamespace: `kom.memory.v1`
|
||||
- auth: bearer token via MCP session metadata (optional local mode).
|
||||
|
||||
## Error Model
|
||||
`{ error: { code: string, message: string, details?: any } }`
|
||||
|
||||
## Events (optional)
|
||||
- `memory.updated` broadcast over MCP notifications.
|
||||
|
||||
## Notes
|
||||
- Namespaces: `project:metal`, `thread:<id>`, `user:<id>`.
|
||||
- Store raw content and normalized text fields for RAG.
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
# Plan: Qwen-2.5-Coder with Tool Support + ACF Exposure
|
||||
|
||||
## Goals
|
||||
- Make Qwen-2.5-Coder reliably call tools in Happy-Code.
|
||||
- Expose Agentic-Control-Framework (ACF) as a safe tool registry to the model.
|
||||
- Keep a fallback protocol (JSON-only) for models lacking native tools.
|
||||
|
||||
## Steps
|
||||
1) **Profile & System Prompt**
|
||||
- Enforce JSON-only responses (or native tool schema if platform supports).
|
||||
- Inject tool registry and JSON Schemas (kom.memory/local backup + ACF subset).
|
||||
2) **Registry**
|
||||
- Allowlist: `kom.memory.v1.*`, `kom.local.v1.backup.*`, and `acf.*` wrapper.
|
||||
- Reject unknown tools and args mismatches (runtime guard).
|
||||
3) **ACF as Tools**
|
||||
- Map ACF endpoints: `acf.list_tasks`, `acf.add_task`, `acf.update_task`, `acf.read_file`, `acf.write_file`, `acf.exec`.
|
||||
- Require workspace path + pattern allowlists.
|
||||
4) **Validation**
|
||||
- Golden transcripts for: upsert/search memory, backup export, ACF addTask/execute_command.
|
||||
5) **Observability**
|
||||
- Log tool calls (names + durations, no payloads).
|
||||
|
||||
## Deliverables
|
||||
- `docs/tool-calling-without-native-support.md` (done)
|
||||
- `docs/plan-qwen-tools.md` (this)
|
||||
- Happy-Code profile snippet for Qwen-2.5-Coder
|
||||
- ACF tool wrapper module (C++ or Python)
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
You are Qwen-2.5-Coder operating in TOOL MODE.
|
||||
|
||||
CONTRACT:
|
||||
- Always respond with a SINGLE JSON object. No prose, no markdown.
|
||||
- Form A: {"action":{"tool":string,"args":object},"thought":string}
|
||||
- Form B: {"final":{"content":any},"thought":string}
|
||||
- Keep thought <= 200 chars.
|
||||
- Only call tools from the provided REGISTRY & SCHEMAS.
|
||||
- If previous message has role=tool, read it as the result for your last action.
|
||||
- If you cannot comply, respond exactly with: {"final":{"content":{"error":"RESET_REQUIRED"}}}
|
||||
|
||||
BEHAVIOR:
|
||||
- Never invent tool names or args.
|
||||
- Validate args against schemas; if mismatch, emit {"final":{"content":{"error":"ARGS_MISMATCH","hint":"..."}}}.
|
||||
- Prefer minimal steps: upsert/search → final.
|
||||
- Do not echo schemas or large content.
|
||||
|
||||
OUTPUT ONLY JSON.
|
||||
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
# E2EE Sync Manifest (Draft)
|
||||
|
||||
## Goals
|
||||
- Multi-device E2EE sync with append-only event log.
|
||||
- Minimal metadata on server (sizes, hashes, timestamps).
|
||||
|
||||
## Event Types
|
||||
- `item.upsert` (id, namespace_id, revision, metadata, content_ref?)
|
||||
- `item.delete` (id)
|
||||
- `chunk.add` (chunk_id, item_id, ord, text_ref?)
|
||||
- `chunk.remove` (chunk_id)
|
||||
- `embedding.add` (chunk_id, model, dim, vector_ref?)
|
||||
|
||||
> _refs denote encrypted content addresses in the blob store; no cleartext._
|
||||
|
||||
## Conflict Rules
|
||||
- Items: last-writer-wins per field; later CRDT as needed.
|
||||
- Deleted beats update after a window.
|
||||
|
||||
## Keys
|
||||
- Device enrollment shares wrapped keys (mechanism TBD).
|
||||
- Rotation supported via manifest updates and re-wrap.
|
||||
|
||||
## MCP Surfaces
|
||||
- `kom.cloud.v1.sync.push` / `pull`
|
||||
- `kom.cloud.v1.backup.upload` / `restore`
|
||||
- `kom.local.v1.backup.export_encrypted` / `import_encrypted`
|
||||
|
||||
## Open Questions
|
||||
- Chunking granularity vs. dedup efficiency; vector upload policy; back-pressure on large histories.
|
||||
|
|
@ -0,0 +1,75 @@
|
|||
# Tool Calling Without Native Support (Happy-Code Compatibility)
|
||||
|
||||
When models lack built-in tool/function calling, we can still get reliable tool use via a **protocol-in-prompt** approach plus a thin runtime.
|
||||
|
||||
## 1) JSON Tool Protocol (deterministic)
|
||||
Model must respond with a single JSON object, no prose.
|
||||
|
||||
```json
|
||||
{
|
||||
"thought": "<very short planning note>",
|
||||
"action": {
|
||||
"tool": "<tool_name>",
|
||||
"args": { }
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
- If more steps are needed, the runtime feeds the tool's JSON result back as the next user message with role=tool.
|
||||
- The model must then either emit another action or finish with:
|
||||
|
||||
```json
|
||||
{
|
||||
"final": { "content": { } }
|
||||
}
|
||||
```
|
||||
|
||||
### Guardrails
|
||||
- Reject any output that isn't valid JSON or that contains extra text.
|
||||
- Cap thought to ~200 chars.
|
||||
- Disallow calling tools not in the registry.
|
||||
|
||||
## 2) Command DSL (fallback)
|
||||
If JSON parsing is brittle, accept a single line command and parse it:
|
||||
|
||||
@tool <name> {json-args}
|
||||
|
||||
Example: @tool kom.memory.v1.search_memory {"namespace":"project:metal", "query":{"text":"embedding model"}}
|
||||
|
||||
## 3) Prompt Template (drop-in)
|
||||
Use this system message for happy-code/claude-code sessions:
|
||||
|
||||
You are a coding assistant that can call tools via a JSON protocol. Available tools (names & schema will be provided). Always reply with a single JSON object. No markdown. No commentary. Use this schema: { "thought": string (short), "action": { "tool": string, "args": object } } OR { "final": { "content": any } }. If a tool result is needed, emit action. If done, emit final. Never invent tool names or fields.
|
||||
|
||||
## 4) Minimal Runtime (pseudocode)
|
||||
while True:
|
||||
msg = llm(messages)
|
||||
data = json.loads(msg)
|
||||
if 'action' in data:
|
||||
tool = registry[data['action']['tool']]
|
||||
result = tool(**data['action']['args'])
|
||||
messages.append({"role":"tool","name":tool.name,"content":json.dumps(result)})
|
||||
continue
|
||||
elif 'final' in data:
|
||||
return data['final']['content']
|
||||
else:
|
||||
error("Invalid protocol")
|
||||
|
||||
## 5) MCP Integration
|
||||
- Map registry to MCP tools (e.g., kom.memory.v1.*).
|
||||
- Provide each tool's JSON Schema to the model in the system message (strict).
|
||||
|
||||
## 6) Testing Checklist
|
||||
- Invalid JSON → reject → ask to resend.
|
||||
- Unknown tool → reject.
|
||||
- Args mismatch → show schema snippet, ask to correct.
|
||||
- Multi-step flows → verify tool result is consumed in next turn.
|
||||
|
||||
## 7) Example Session
|
||||
System: (template above + list of tools & schemas)
|
||||
User: Save this note: "Embedding model comparison takeaways" into project:metal
|
||||
Assistant:
|
||||
{"thought":"need to upsert note","action":{"tool":"kom.memory.v1.upsert_memory","args":{"namespace":"project:metal","items":[{"text":"Embedding model comparison takeaways"}]}}}
|
||||
Tool (kom.memory.v1.upsert_memory): { "upserted": 1 }
|
||||
Assistant:
|
||||
{"final":{"content":{"status":"ok","upserted":1}}}
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
# Ledger
|
||||
|
||||
- 2025-10-13: Initialized project `metal-kompanion-mcp`; created docs and interfaces; scaffolded CMake and main stub.
|
||||
- 2025-10-13: Added MCP tool schemas for `kom.memory.v1`.
|
||||
- 2025-10-13: Built MCP skeleton with `ping` and `embed_text` stub; added local-first architecture docs; added backup/sync draft specs; created tasks for privacy hardening and cloud adapters.
|
||||
|
|
@ -0,0 +1,86 @@
|
|||
-- Enable pgvector (requires extension installed)
|
||||
CREATE EXTENSION IF NOT EXISTS vector;
|
||||
|
||||
-- Namespaces: unique logical scope (e.g., 'project:metal', 'thread:abc')
|
||||
CREATE TABLE IF NOT EXISTS namespaces (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name TEXT NOT NULL UNIQUE,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
|
||||
-- Users (optional link)
|
||||
CREATE TABLE IF NOT EXISTS users (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
external_id TEXT UNIQUE,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
|
||||
-- Threads (within a namespace)
|
||||
CREATE TABLE IF NOT EXISTS threads (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
namespace_id UUID NOT NULL REFERENCES namespaces(id) ON DELETE CASCADE,
|
||||
external_id TEXT,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS threads_ns_idx ON threads(namespace_id);
|
||||
|
||||
-- Memory items: logical notes/contexts (JSONB content + normalized text)
|
||||
CREATE TABLE IF NOT EXISTS memory_items (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
namespace_id UUID NOT NULL REFERENCES namespaces(id) ON DELETE CASCADE,
|
||||
thread_id UUID REFERENCES threads(id) ON DELETE SET NULL,
|
||||
user_id UUID REFERENCES users(id) ON DELETE SET NULL,
|
||||
key TEXT,
|
||||
content JSONB NOT NULL,
|
||||
text TEXT,
|
||||
tags TEXT[] DEFAULT '{}',
|
||||
metadata JSONB DEFAULT '{}'::jsonb,
|
||||
revision INTEGER NOT NULL DEFAULT 1,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
updated_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
expires_at TIMESTAMPTZ,
|
||||
deleted_at TIMESTAMPTZ
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS mem_items_ns_idx ON memory_items(namespace_id, thread_id, created_at DESC);
|
||||
CREATE INDEX IF NOT EXISTS mem_items_tags_gin ON memory_items USING GIN(tags);
|
||||
CREATE INDEX IF NOT EXISTS mem_items_meta_gin ON memory_items USING GIN(metadata);
|
||||
|
||||
-- Chunks: embedding units derived from items
|
||||
CREATE TABLE IF NOT EXISTS memory_chunks (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
item_id UUID NOT NULL REFERENCES memory_items(id) ON DELETE CASCADE,
|
||||
ord INTEGER NOT NULL,
|
||||
text TEXT NOT NULL,
|
||||
metadata JSONB DEFAULT '{}'::jsonb,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS chunks_item_idx ON memory_chunks(item_id, ord);
|
||||
|
||||
-- Embeddings: one per chunk (per model)
|
||||
CREATE TABLE IF NOT EXISTS embeddings (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
chunk_id UUID NOT NULL REFERENCES memory_chunks(id) ON DELETE CASCADE,
|
||||
model TEXT NOT NULL,
|
||||
dim INTEGER NOT NULL,
|
||||
vector VECTOR(1536) NOT NULL, -- adjust dim per model
|
||||
normalized BOOLEAN DEFAULT FALSE,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
UNIQUE(chunk_id, model)
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS embeddings_model_dim ON embeddings(model, dim);
|
||||
-- For ivfflat you must first create a HNSW/IVFFLAT index; pgvector uses different syntax depending on version
|
||||
CREATE INDEX IF NOT EXISTS embeddings_vector_ivfflat ON embeddings USING ivfflat (vector) WITH (lists = 100);
|
||||
|
||||
-- Helper upsert function for memory_items revision bump
|
||||
CREATE OR REPLACE FUNCTION bump_revision() RETURNS trigger AS $$
|
||||
BEGIN
|
||||
NEW.revision := COALESCE(OLD.revision, 0) + 1;
|
||||
NEW.updated_at := now();
|
||||
RETURN NEW;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
DROP TRIGGER IF EXISTS trg_bump_revision ON memory_items;
|
||||
CREATE TRIGGER trg_bump_revision
|
||||
BEFORE UPDATE ON memory_items
|
||||
FOR EACH ROW EXECUTE FUNCTION bump_revision();
|
||||
|
|
@ -0,0 +1,25 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <optional>
|
||||
#include "Models.hpp"
|
||||
|
||||
class IDatabase {
|
||||
public:
|
||||
virtual ~IDatabase() = default;
|
||||
virtual bool connect(const std::string& dsn) = 0;
|
||||
virtual void close() = 0;
|
||||
|
||||
// Transactions
|
||||
virtual bool begin() = 0;
|
||||
virtual bool commit() = 0;
|
||||
virtual void rollback() = 0;
|
||||
|
||||
// Memory ops (skeleton)
|
||||
virtual std::optional<NamespaceRow> ensureNamespace(const std::string& name) = 0;
|
||||
virtual std::string upsertItem(const ItemRow& item) = 0;
|
||||
virtual std::vector<std::string> upsertChunks(const std::vector<ChunkRow>& chunks) = 0;
|
||||
virtual std::vector<std::string> upsertEmbeddings(const std::vector<EmbeddingRow>& embs) = 0;
|
||||
virtual std::vector<ItemRow> searchText(const std::string& namespace_id, const std::string& query, int k) = 0;
|
||||
virtual std::vector<std::pair<std::string,float>> searchVector(const std::string& namespace_id, const std::vector<float>& embedding, int k) = 0;
|
||||
};
|
||||
|
|
@ -0,0 +1,37 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <optional>
|
||||
#include <unordered_map>
|
||||
|
||||
struct NamespaceRow { std::string id; std::string name; };
|
||||
struct ThreadRow { std::string id; std::string namespace_id; std::string external_id; };
|
||||
struct UserRow { std::string id; std::string external_id; };
|
||||
|
||||
struct ItemRow {
|
||||
std::string id;
|
||||
std::string namespace_id;
|
||||
std::optional<std::string> thread_id;
|
||||
std::optional<std::string> user_id;
|
||||
std::optional<std::string> key;
|
||||
std::string content_json;
|
||||
std::optional<std::string> text;
|
||||
std::vector<std::string> tags;
|
||||
std::unordered_map<std::string, std::string> metadata;
|
||||
int revision{1};
|
||||
};
|
||||
|
||||
struct ChunkRow {
|
||||
std::string id;
|
||||
std::string item_id;
|
||||
int ord{0};
|
||||
std::string text;
|
||||
};
|
||||
|
||||
struct EmbeddingRow {
|
||||
std::string id;
|
||||
std::string chunk_id;
|
||||
std::string model;
|
||||
int dim{0};
|
||||
std::vector<float> vector;
|
||||
};
|
||||
|
|
@ -0,0 +1,22 @@
|
|||
#include "PgDal.hpp"
|
||||
#include <iostream>
|
||||
|
||||
// NOTE: Stub implementation (no libpq linked yet).
|
||||
|
||||
bool PgDal::connect(const std::string& dsn) { (void)dsn; std::cout << "[PgDal] connect stub
|
||||
"; return true; }
|
||||
void PgDal::close() { std::cout << "[PgDal] close stub
|
||||
"; }
|
||||
bool PgDal::begin() { std::cout << "[PgDal] begin stub
|
||||
"; return true; }
|
||||
bool PgDal::commit() { std::cout << "[PgDal] commit stub
|
||||
"; return true; }
|
||||
void PgDal::rollback() { std::cout << "[PgDal] rollback stub
|
||||
"; }
|
||||
|
||||
std::optional<NamespaceRow> PgDal::ensureNamespace(const std::string& name) { (void)name; return NamespaceRow{"00000000-0000-0000-0000-000000000000", name}; }
|
||||
std::string PgDal::upsertItem(const ItemRow& item) { (void)item; return std::string("00000000-0000-0000-0000-000000000001"); }
|
||||
std::vector<std::string> PgDal::upsertChunks(const std::vector<ChunkRow>& chunks) { return std::vector<std::string>(chunks.size(), "00000000-0000-0000-0000-000000000002"); }
|
||||
std::vector<std::string> PgDal::upsertEmbeddings(const std::vector<EmbeddingRow>& embs) { return std::vector<std::string>(embs.size(), "00000000-0000-0000-0000-000000000003"); }
|
||||
std::vector<ItemRow> PgDal::searchText(const std::string& namespace_id, const std::string& query, int k) { (void)namespace_id; (void)query; (void)k; return {}; }
|
||||
std::vector<std::pair<std::string,float>> PgDal::searchVector(const std::string& namespace_id, const std::vector<float>& embedding, int k) { (void)namespace_id; (void)embedding; (void)k; return {}; }
|
||||
|
|
@ -0,0 +1,18 @@
|
|||
#pragma once
|
||||
#include "IDatabase.hpp"
|
||||
|
||||
class PgDal : public IDatabase {
|
||||
public:
|
||||
bool connect(const std::string& dsn) override;
|
||||
void close() override;
|
||||
bool begin() override;
|
||||
bool commit() override;
|
||||
void rollback() override;
|
||||
|
||||
std::optional<NamespaceRow> ensureNamespace(const std::string& name) override;
|
||||
std::string upsertItem(const ItemRow& item) override;
|
||||
std::vector<std::string> upsertChunks(const std::vector<ChunkRow>& chunks) override;
|
||||
std::vector<std::string> upsertEmbeddings(const std::vector<EmbeddingRow>& embs) override;
|
||||
std::vector<ItemRow> searchText(const std::string& namespace_id, const std::string& query, int k) override;
|
||||
std::vector<std::pair<std::string,float>> searchVector(const std::string& namespace_id, const std::vector<float>& embedding, int k) override;
|
||||
};
|
||||
|
|
@ -0,0 +1,77 @@
|
|||
// Minimal CLI runner that registers Kompanion MCP tools and dispatches requests.
|
||||
#include <filesystem>
|
||||
#include <fstream>
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
#include "mcp/KomMcpServer.hpp"
|
||||
#include "mcp/RegisterTools.hpp"
|
||||
|
||||
namespace {
|
||||
|
||||
std::string read_all(std::istream& in) {
|
||||
std::ostringstream oss;
|
||||
oss << in.rdbuf();
|
||||
return oss.str();
|
||||
}
|
||||
|
||||
std::string load_request(int argc, char** argv) {
|
||||
if (argc < 3) {
|
||||
return read_all(std::cin);
|
||||
}
|
||||
std::string arg = argv[2];
|
||||
if (arg == "-") {
|
||||
return read_all(std::cin);
|
||||
}
|
||||
std::filesystem::path p{arg};
|
||||
if (std::filesystem::exists(p)) {
|
||||
std::ifstream file(p);
|
||||
if (!file) throw std::runtime_error("unable to open request file: " + p.string());
|
||||
return read_all(file);
|
||||
}
|
||||
return arg;
|
||||
}
|
||||
|
||||
void print_usage(const char* exe, KomMcpServer& server) {
|
||||
std::cerr << "Usage: " << exe << " <tool-name> [request-json|-|path]\n";
|
||||
std::cerr << "Available tools:\n";
|
||||
for (const auto& name : server.listTools()) {
|
||||
std::cerr << " - " << name << "\n";
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
int main(int argc, char** argv) {
|
||||
KomMcpServer server;
|
||||
register_default_tools(server);
|
||||
|
||||
if (argc < 2) {
|
||||
print_usage(argv[0], server);
|
||||
return 1;
|
||||
}
|
||||
|
||||
std::string tool = argv[1];
|
||||
if (tool == "--list") {
|
||||
for (const auto& name : server.listTools()) {
|
||||
std::cout << name << "\n";
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
if (!server.hasTool(tool)) {
|
||||
std::cerr << "Unknown tool: " << tool << "\n";
|
||||
print_usage(argv[0], server);
|
||||
return 1;
|
||||
}
|
||||
|
||||
try {
|
||||
std::string request = load_request(argc, argv);
|
||||
std::string response = server.dispatch(tool, request);
|
||||
std::cout << response << std::endl;
|
||||
return 0;
|
||||
} catch (const std::exception& ex) {
|
||||
std::cerr << "Error: " << ex.what() << "\n";
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
|
||||
namespace Handlers {
|
||||
|
||||
inline std::string backup_export_encrypted(const std::string& reqJson) {
|
||||
(void)reqJson;
|
||||
// TODO: implement according to docs/backup-e2ee-spec.md
|
||||
return std::string("{\"status\":\"queued\",\"artifact\":\"/tmp/export.enc\"}");
|
||||
}
|
||||
|
||||
inline std::string backup_import_encrypted(const std::string& reqJson) {
|
||||
(void)reqJson;
|
||||
return std::string("{\"status\":\"ok\"}");
|
||||
}
|
||||
|
||||
} // namespace Handlers
|
||||
|
|
@ -0,0 +1,104 @@
|
|||
#pragma once
|
||||
#include <cctype>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
|
||||
namespace Handlers {
|
||||
|
||||
inline std::string json_escape(const std::string& in) {
|
||||
std::ostringstream os;
|
||||
for (char c : in) {
|
||||
switch (c) {
|
||||
case '\"': os << "\\\""; break;
|
||||
case '\\': os << "\\\\"; break;
|
||||
case '\n': os << "\\n"; break;
|
||||
case '\r': os << "\\r"; break;
|
||||
case '\t': os << "\\t"; break;
|
||||
default: os << c; break;
|
||||
}
|
||||
}
|
||||
return os.str();
|
||||
}
|
||||
|
||||
inline size_t count_items_array(const std::string& json) {
|
||||
auto pos = json.find("\"items\"");
|
||||
if (pos == std::string::npos) return 0;
|
||||
pos = json.find('[', pos);
|
||||
if (pos == std::string::npos) return 0;
|
||||
size_t count = 0;
|
||||
int depth = 0;
|
||||
bool inString = false;
|
||||
bool escape = false;
|
||||
for (size_t i = pos + 1; i < json.size(); ++i) {
|
||||
char c = json[i];
|
||||
if (escape) { escape = false; continue; }
|
||||
if (c == '\\') { if (inString) escape = true; continue; }
|
||||
if (c == '\"') { inString = !inString; continue; }
|
||||
if (inString) continue;
|
||||
if (c == '{') {
|
||||
if (depth == 0) ++count;
|
||||
++depth;
|
||||
} else if (c == '}') {
|
||||
if (depth > 0) --depth;
|
||||
} else if (c == ']' && depth == 0) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
return count;
|
||||
}
|
||||
|
||||
inline std::string extract_string_field(const std::string& json, const std::string& key) {
|
||||
const std::string pattern = "\"" + key + "\"";
|
||||
auto pos = json.find(pattern);
|
||||
if (pos == std::string::npos) return {};
|
||||
pos = json.find(':', pos);
|
||||
if (pos == std::string::npos) return {};
|
||||
++pos;
|
||||
while (pos < json.size() && std::isspace(static_cast<unsigned char>(json[pos]))) ++pos;
|
||||
if (pos >= json.size() || json[pos] != '\"') return {};
|
||||
++pos;
|
||||
std::ostringstream os;
|
||||
bool escape = false;
|
||||
for (; pos < json.size(); ++pos) {
|
||||
char c = json[pos];
|
||||
if (escape) {
|
||||
switch (c) {
|
||||
case '\"': os << '\"'; break;
|
||||
case '\\': os << '\\'; break;
|
||||
case '/': os << '/'; break;
|
||||
case 'b': os << '\b'; break;
|
||||
case 'f': os << '\f'; break;
|
||||
case 'n': os << '\n'; break;
|
||||
case 'r': os << '\r'; break;
|
||||
case 't': os << '\t'; break;
|
||||
default: os << c; break;
|
||||
}
|
||||
escape = false;
|
||||
continue;
|
||||
}
|
||||
if (c == '\\') { escape = true; continue; }
|
||||
if (c == '\"') break;
|
||||
os << c;
|
||||
}
|
||||
return os.str();
|
||||
}
|
||||
|
||||
inline std::string upsert_memory(const std::string& reqJson) {
|
||||
size_t count = count_items_array(reqJson);
|
||||
std::ostringstream os;
|
||||
os << "{\"upserted\":" << count << ",\"status\":\"ok\"}";
|
||||
return os.str();
|
||||
}
|
||||
|
||||
inline std::string search_memory(const std::string& reqJson) {
|
||||
std::string queryText = extract_string_field(reqJson, "text");
|
||||
std::ostringstream os;
|
||||
os << "{\"matches\":[";
|
||||
if (!queryText.empty()) {
|
||||
os << "{\"id\":\"stub-memory-1\",\"score\":0.42,\"text\":\"" << json_escape(queryText) << "\"}";
|
||||
}
|
||||
os << "]}";
|
||||
return os.str();
|
||||
}
|
||||
|
||||
} // namespace Handlers
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
#pragma once
|
||||
#include <functional>
|
||||
#include <string>
|
||||
#include <unordered_map>
|
||||
#include <vector>
|
||||
|
||||
// Minimal, dependency-free server facade we can later back with qtmcp.
|
||||
// Handlers take JSON strings (request) and return JSON strings (response).
|
||||
class KomMcpServer {
|
||||
public:
|
||||
using Handler = std::function<std::string(const std::string&)>;
|
||||
|
||||
void registerTool(const std::string& name, Handler handler) {
|
||||
tools_[name] = std::move(handler);
|
||||
}
|
||||
|
||||
bool hasTool(const std::string& name) const {
|
||||
return tools_.count(name) > 0;
|
||||
}
|
||||
|
||||
std::vector<std::string> listTools() const {
|
||||
std::vector<std::string> out;
|
||||
out.reserve(tools_.size());
|
||||
for (auto &kv : tools_) out.push_back(kv.first);
|
||||
return out;
|
||||
}
|
||||
|
||||
// For now, just dispatch synchronously.
|
||||
std::string dispatch(const std::string& name, const std::string& requestJson) {
|
||||
if (!hasTool(name)) return std::string("{\"error\":{\"code\":\"tool_not_found\",\"message\":\""+name+"\"}}\n");
|
||||
return tools_[name](requestJson);
|
||||
}
|
||||
|
||||
// Placeholder for actual MCP run loop (qtmcp).
|
||||
int runOnce() { return 0; }
|
||||
|
||||
private:
|
||||
std::unordered_map<std::string, Handler> tools_;
|
||||
};
|
||||
|
|
@ -0,0 +1,24 @@
|
|||
#pragma once
|
||||
#include <chrono>
|
||||
#include <string>
|
||||
#include <unordered_map>
|
||||
|
||||
class RateLimiter {
|
||||
public:
|
||||
// simple fixed window per tool
|
||||
bool allow(const std::string& tool, size_t maxPerWindow = 5, std::chrono::seconds window = std::chrono::seconds(1)) {
|
||||
using clock = std::chrono::steady_clock;
|
||||
auto now = clock::now();
|
||||
auto &state = buckets_[tool];
|
||||
if (now - state.windowStart > window) {
|
||||
state.windowStart = now;
|
||||
state.count = 0;
|
||||
}
|
||||
if (state.count >= maxPerWindow) return false;
|
||||
++state.count;
|
||||
return true;
|
||||
}
|
||||
private:
|
||||
struct Bucket { std::chrono::steady_clock::time_point windowStart{}; size_t count{0}; };
|
||||
std::unordered_map<std::string, Bucket> buckets_;
|
||||
};
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
#pragma once
|
||||
#include "KomMcpServer.hpp"
|
||||
#include "HandlersLocalBackup.hpp"
|
||||
#include "HandlersMemory.hpp"
|
||||
|
||||
inline void register_default_tools(KomMcpServer& server) {
|
||||
server.registerTool("kom.memory.v1.upsert_memory", Handlers::upsert_memory);
|
||||
server.registerTool("kom.memory.v1.search_memory", Handlers::search_memory);
|
||||
server.registerTool("kom.local.v1.backup.export_encrypted", Handlers::backup_export_encrypted);
|
||||
server.registerTool("kom.local.v1.backup.import_encrypted", Handlers::backup_import_encrypted);
|
||||
}
|
||||
|
|
@ -0,0 +1,14 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
|
||||
struct Scope {
|
||||
std::string namespace_id;
|
||||
std::string user_id;
|
||||
bool valid() const { return !namespace_id.empty(); }
|
||||
};
|
||||
|
||||
// In a real qtmcp server, these would be derived from session/auth.
|
||||
inline Scope currentScope() {
|
||||
// TODO: inject from session context / env. For now, return empty (invalid).
|
||||
return Scope{};
|
||||
}
|
||||
|
|
@ -0,0 +1,196 @@
|
|||
{
|
||||
"namespace": "kom.memory.v1",
|
||||
"tools": {
|
||||
"save_context": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespace": {"type": "string"},
|
||||
"key": {"type": "string"},
|
||||
"content": {},
|
||||
"tags": {"type": "array", "items": {"type": "string"}},
|
||||
"ttl_seconds": {"type": "integer"}
|
||||
},
|
||||
"required": ["namespace", "content"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"created_at": {"type": "string"}
|
||||
},
|
||||
"required": ["id", "created_at"]
|
||||
}
|
||||
},
|
||||
"recall_context": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespace": {"type": "string"},
|
||||
"key": {"type": "string"},
|
||||
"tags": {"type": "array", "items": {"type": "string"}},
|
||||
"limit": {"type": "integer"},
|
||||
"since": {"type": "string"}
|
||||
},
|
||||
"required": ["namespace"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"items": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"key": {"type": "string"},
|
||||
"content": {},
|
||||
"tags": {"type": "array", "items": {"type": "string"}},
|
||||
"created_at": {"type": "string"}
|
||||
},
|
||||
"required": ["id", "content", "created_at"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["items"]
|
||||
}
|
||||
},
|
||||
"embed_text": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"model": {"type": "string"},
|
||||
"texts": {"type": "array", "items": {"type": "string"}}
|
||||
},
|
||||
"required": ["texts"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"model": {"type": "string"},
|
||||
"vectors": {"type": "array", "items": {"type": "array", "items": {"type": "number"}}}
|
||||
},
|
||||
"required": ["model", "vectors"]
|
||||
}
|
||||
},
|
||||
"upsert_memory": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespace": {"type": "string"},
|
||||
"items": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"text": {"type": "string"},
|
||||
"metadata": {"type": "object"},
|
||||
"embedding": {"type": "array", "items": {"type": "number"}}
|
||||
},
|
||||
"required": ["text"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["namespace", "items"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"upserted": {"type": "integer"}
|
||||
},
|
||||
"required": ["upserted"]
|
||||
}
|
||||
},
|
||||
"search_memory": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespace": {"type": "string"},
|
||||
"query": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"text": {"type": "string"},
|
||||
"embedding": {"type": "array", "items": {"type": "number"}},
|
||||
"k": {"type": "integer"},
|
||||
"filter": {"type": "object"}
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["namespace", "query"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"matches": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"score": {"type": "number"},
|
||||
"text": {"type": "string"},
|
||||
"metadata": {"type": "object"}
|
||||
},
|
||||
"required": ["id", "score"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["matches"]
|
||||
}
|
||||
},
|
||||
"warm_cache": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespace": {"type": "string"},
|
||||
"since": {"type": "string"}
|
||||
},
|
||||
"required": ["namespace"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"queued": {"type": "integer"}
|
||||
},
|
||||
"required": ["queued"]
|
||||
}
|
||||
},
|
||||
|
||||
"kom.local.v1.backup.export_encrypted": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"namespaces": {"type": "array", "items": {"type": "string"}},
|
||||
"destination": {"type": "string"}
|
||||
},
|
||||
"required": ["namespaces", "destination"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"status": {"type": "string"},
|
||||
"artifact": {"type": "string"}
|
||||
},
|
||||
"required": ["status", "artifact"]
|
||||
}
|
||||
},
|
||||
|
||||
"kom.local.v1.backup.import_encrypted": {
|
||||
"input": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"source": {"type": "string"}
|
||||
},
|
||||
"required": ["source"]
|
||||
},
|
||||
"output": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"status": {"type": "string"}
|
||||
},
|
||||
"required": ["status"]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <sstream>
|
||||
|
||||
namespace Tools {
|
||||
|
||||
// Super-lightweight JSON helpers (NOT robust; only for stub/testing).
|
||||
inline std::string json_kv(const std::string& k, const std::string& v) {
|
||||
std::ostringstream os; os << "\"" << k << "\"\: \"" << v << "\""; return os.str();
|
||||
}
|
||||
inline std::string json_kv_num(const std::string& k, double v) {
|
||||
std::ostringstream os; os << "\"" << k << "\"\: " << v; return os.str();
|
||||
}
|
||||
inline std::string json_arr(const std::vector<std::string>& items) {
|
||||
std::ostringstream os; os << "[";
|
||||
for (size_t i=0;i<items.size();++i){ if(i) os<<","; os<<items[i]; }
|
||||
os << "]"; return os.str();
|
||||
}
|
||||
|
||||
// `ping` tool: echoes { ok: true, tools: [...] }
|
||||
inline std::string ping_response(const std::vector<std::string>& toolNames) {
|
||||
std::vector<std::string> quoted; quoted.reserve(toolNames.size());
|
||||
for (auto &t: toolNames) { std::ostringstream q; q << "\"" << t << "\""; quoted.push_back(q.str()); }
|
||||
std::ostringstream os;
|
||||
os << "{" << json_kv("status", "ok") << ", "
|
||||
<< "\"tools\": " << json_arr(quoted) << "}";
|
||||
return os.str();
|
||||
}
|
||||
|
||||
// `embed_text` stub: returns zero vectors of dimension 8 for each input text
|
||||
inline std::string embed_text_stub(size_t n) {
|
||||
std::ostringstream os;
|
||||
os << "{\"model\":\"stub-embed-8d\",\"vectors\":[";
|
||||
for (size_t i=0;i<n;++i){ if(i) os<<","; os<<"[0,0,0,0,0,0,0,0]"; }
|
||||
os << "]}";
|
||||
return os.str();
|
||||
}
|
||||
|
||||
} // namespace Tools
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <optional>
|
||||
|
||||
struct EmbedResult {
|
||||
std::string model;
|
||||
std::vector<std::vector<float>> vectors;
|
||||
};
|
||||
|
||||
class IEmbedder {
|
||||
public:
|
||||
virtual ~IEmbedder() = default;
|
||||
virtual EmbedResult embed(const std::vector<std::string>& texts, std::optional<std::string> model = std::nullopt) = 0;
|
||||
};
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <optional>
|
||||
#include <unordered_map>
|
||||
|
||||
struct MemoryItem {
|
||||
std::string id;
|
||||
std::string text;
|
||||
std::unordered_map<std::string, std::string> metadata;
|
||||
};
|
||||
|
||||
struct QueryFilter {
|
||||
std::unordered_map<std::string, std::string> equals;
|
||||
};
|
||||
|
||||
struct QueryResult {
|
||||
std::string id;
|
||||
float score;
|
||||
std::optional<std::string> text;
|
||||
std::unordered_map<std::string, std::string> metadata;
|
||||
};
|
||||
|
||||
class IVectorStore {
|
||||
public:
|
||||
virtual ~IVectorStore() = default;
|
||||
virtual size_t upsert(const std::string& nameSpace, const std::vector<MemoryItem>& items, const std::vector<std::vector<float>>* embeddings = nullptr) = 0;
|
||||
virtual std::vector<QueryResult> query(const std::string& nameSpace, const std::vector<float>& embedding, size_t k = 8, std::optional<QueryFilter> filter = std::nullopt) = 0;
|
||||
virtual bool remove(const std::string& nameSpace, const std::vector<std::string>& ids) = 0;
|
||||
};
|
||||
|
|
@ -0,0 +1,43 @@
|
|||
# metal-kompanion-mcp
|
||||
MCP backend for Kompanion: memory/context/embedding provider over MCP, built from scratch (qtmcp-based) to persist conversation state and serve embeddings + retrieval to avoid forgetting across threads.
|
||||
|
||||
> ## 📈 Project Summary
|
||||
>
|
||||
> **✅ Done**: 0 | **🔄 In Progress**: 0 | **⬜ Todo**: 19 | **❌ Blocked**: 0
|
||||
>
|
||||
> **Progress**: 0% `░░░░░░░░░░░░░░░░░░░░` 0/19 tasks
|
||||
>
|
||||
> **Priorities**: 🚨 **Critical**: 0 | 🔴 **High**: 1 | 🟡 **Medium**: 20 | 🟢 **Low**: 0
|
||||
|
||||
## Tasks
|
||||
|
||||
| ID | Status | Priority | Title | Description |
|
||||
|:--:|:------:|:--------:|:------|:------------|
|
||||
| #1 | ⬜ todo | 700 | **Project Setup: metal-kompanion-mcp** | MCP backend for Kompanion: me... |
|
||||
| #2 | ⬜ in_progress | 500 | **Design MCP memory/context API** | Specify MCP tools for: save_c... |
|
||||
| #3 | ⬜ todo | 501 | **Select embedding backend & storage** | Choose between local (Ollama/... |
|
||||
| #4 | ⬜ in_progress | 499 | **Scaffold qtmcp-based server** | Set up C++/Qt MCP server skel... |
|
||||
| #5 | ⬜ todo | 502 | **Implement memory adapters** | Adapters: (1) SQLite+FAISS/pg... |
|
||||
| #6 | ⬜ todo | 498 | **Deep research: memory DB architecture & schema** | Survey best practices for con... |
|
||||
| #7 | ⬜ todo | 503 | **Decide primary DB: Postgres+pgvector vs SQLite+FAISS** | Evaluate tradeoffs (multi-use... |
|
||||
| #8 | ⬜ todo | 497 | **Implement DAL + migrations (pgvector)** | Create C++ DAL layer for name... |
|
||||
| #9 | ⬜ todo | 504 | **Add cloud DB hardening (RLS, FTS/trgm, ANN indexes)** | Implement RLS policies; add F... |
|
||||
| #10 | ⬜ todo | 496 | **Server enforcement: scope injection + rate limits** | Inject namespace/user via ses... |
|
||||
| #11 | ⬜ todo | 505 | **Redaction & sensitivity pipeline** | Implement preprocessing to de... |
|
||||
| #12 | ⬜ todo | 495 | **Private vault mode (key-only retrieval)** | Implement vault path for secr... |
|
||||
| #13 | ⬜ todo | 506 | **Local backup tools: export/import (E2EE)** | Add kom.local.v1.backup.expor... |
|
||||
| #14 | ⬜ todo | 494 | **Cloud adapters: backup/sync & payments stubs** | Expose kom.cloud.v1.backup.up... |
|
||||
| #15 | ⬜ todo | 507 | **Purge job & admin delete paths** | Implement scheduled hard-dele... |
|
||||
| #16 | ⬜ todo | 493 | **Test suite: privacy & hybrid search** | Cross-tenant leakage, redacti... |
|
||||
| #17 | ⬜ todo | 508 | **Enable Qwen-2.5-Coder with tool support (Happy-Code profile)** | Prepare system prompt + regis... |
|
||||
| #18 | ⬜ todo | 492 | **Expose Agentic-Control-Framework as a tool** | Wrap ACF endpoints into a too... |
|
||||
| #19 | ⬜ todo | 509 | **DAL skeleton + SQL calls (pgvector)** | Create DAL interfaces and pgv... |
|
||||
| #20 | ⬜ todo | 491 | **Claude Code integration rescue plan** | Stabilize Qwen-2.5-Coder insi... |
|
||||
|
||||
|
||||
### Task #2: Design MCP memory/context API - Subtasks
|
||||
|
||||
| ID | Status | Title |
|
||||
|:--:|:------:|:------|
|
||||
| #2.1 | ⬜ todo | Write JSON Schemas for tools (done) |
|
||||
|
||||
|
|
@ -0,0 +1,43 @@
|
|||
#include <iostream>
|
||||
#include <string>
|
||||
#include "mcp/KomMcpServer.hpp"
|
||||
#include "mcp/RegisterTools.hpp"
|
||||
|
||||
namespace {
|
||||
|
||||
bool expect_contains(const std::string& haystack, const std::string& needle, const std::string& context) {
|
||||
if (haystack.find(needle) == std::string::npos) {
|
||||
std::cerr << "Expected response to contain '" << needle << "' but got:\n"
|
||||
<< haystack << "\nContext: " << context << "\n";
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
int main() {
|
||||
KomMcpServer server;
|
||||
register_default_tools(server);
|
||||
|
||||
const std::string upsertReq = R"({"namespace":"tests","items":[{"text":"hello world"},{"text":"hola mundo"}]})";
|
||||
std::string upsertResp = server.dispatch("kom.memory.v1.upsert_memory", upsertReq);
|
||||
if (!expect_contains(upsertResp, "\"upserted\":2", "upsert_memory count")) return 1;
|
||||
if (!expect_contains(upsertResp, "\"status\":\"ok\"", "upsert_memory status")) return 1;
|
||||
|
||||
const std::string searchReq = R"({"namespace":"tests","query":{"text":"hello","k":3}})";
|
||||
std::string searchResp = server.dispatch("kom.memory.v1.search_memory", searchReq);
|
||||
if (!expect_contains(searchResp, "\"matches\"", "search_memory matches key")) return 1;
|
||||
if (!expect_contains(searchResp, "\"text\":\"hello\"", "search_memory echo text")) return 1;
|
||||
|
||||
const std::string exportReq = R"({"namespace":"tests","destination":"/tmp/example.enc"})";
|
||||
std::string exportResp = server.dispatch("kom.local.v1.backup.export_encrypted", exportReq);
|
||||
if (!expect_contains(exportResp, "\"status\":\"queued\"", "export status")) return 1;
|
||||
if (!expect_contains(exportResp, "\"artifact\"", "export artifact path")) return 1;
|
||||
|
||||
const std::string importReq = R"({"namespace":"tests","source":"/tmp/example.enc"})";
|
||||
std::string importResp = server.dispatch("kom.local.v1.backup.import_encrypted", importReq);
|
||||
if (!expect_contains(importResp, "\"status\":\"ok\"", "import status")) return 1;
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
{
|
||||
"namespace": "project:metal",
|
||||
"query": {
|
||||
"text": "embedding model",
|
||||
"k": 5,
|
||||
"filter": {
|
||||
"thread": "embedding-comparison"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
{
|
||||
"namespace": "project:metal",
|
||||
"items": [
|
||||
{"id": "note-1", "text": "Embedding model comparison: takeaways...", "metadata": {"thread": "embedding-comparison"}}
|
||||
]
|
||||
}
|
||||
|
|
@ -0,0 +1,78 @@
|
|||
#!/usr/bin/env python3
|
||||
import os, sys, hashlib, psycopg, requests, json
|
||||
|
||||
DB=os.environ.get("DB_URL","dbname=kompanion user=kompanion host=/var/run/postgresq")
|
||||
OLLAMA=os.environ.get("OLLAMA_BASE","http://127.0.0.1:11434")
|
||||
MODEL=os.environ.get("EMBED_MODEL","mxbai-embed-large")
|
||||
SPACE=os.environ.get("EMBED_SPACE","dev_knowledge") # dev_knowledge | pattern_exchange | runtime_memory
|
||||
|
||||
def sha256(p):
|
||||
h=hashlib.sha256()
|
||||
with open(p,"rb") as f:
|
||||
for chunk in iter(lambda: f.read(1<<20), b""): h.update(chunk)
|
||||
return h.hexdigest()
|
||||
|
||||
def embed(text):
|
||||
r=requests.post(f"{OLLAMA}/api/embeddings", json={"model": MODEL, "prompt": text}, timeout=120)
|
||||
r.raise_for_status(); return r.json()["embedding"]
|
||||
|
||||
def chunks(s, sz=1600):
|
||||
b=s.encode("utf-8");
|
||||
for i in range(0,len(b),sz): yield b[i:i+sz].decode("utf-8","ignore")
|
||||
|
||||
def insert_embedding(cur, dim, kid, sid, vec):
|
||||
if dim==768:
|
||||
cur.execute("INSERT INTO komp.embedding_768(chunk_id,space_id,embedding) VALUES(%s,%s,%s) ON CONFLICT DO NOTHING",(kid,sid,vec))
|
||||
elif dim==1024:
|
||||
cur.execute("INSERT INTO komp.embedding_1024(chunk_id,space_id,embedding) VALUES(%s,%s,%s) ON CONFLICT DO NOTHING",(kid,sid,vec))
|
||||
else:
|
||||
return False
|
||||
return True
|
||||
|
||||
def main(root):
|
||||
with psycopg.connect(DB) as conn, conn.cursor() as cur:
|
||||
cur.execute("SELECT id,dim FROM komp.space WHERE name=%s",(SPACE,))
|
||||
row=cur.fetchone()
|
||||
if not row: raise SystemExit(f"space {SPACE} missing (init schema)")
|
||||
sid, target_dim = row
|
||||
for dirpath,_,files in os.walk(root):
|
||||
for fn in files:
|
||||
p=os.path.join(dirpath,fn)
|
||||
if os.path.getsize(p)==0: continue
|
||||
# include common text/code; PDFs via pdftotext if available
|
||||
if not any(fn.lower().endswith(ext) for ext in (".md",".txt",".json",".py",".cpp",".c",".hpp",".yaml",".yml",".toml",".pdf",".mdown",".rst",".org",".js",".ts",".sql",".sh",".ini",".conf",".cfg",".log",".mime")):
|
||||
continue
|
||||
if fn.lower().endswith(".pdf"):
|
||||
try:
|
||||
txt=os.popen(f"pdftotext -layout -nopgbrk '{p}' - -q").read()
|
||||
except Exception:
|
||||
continue
|
||||
else:
|
||||
try: txt=open(p,"r",encoding="utf-8",errors="ignore").read()
|
||||
except Exception: continue
|
||||
sh=sha256(p)
|
||||
cur.execute("INSERT INTO komp.source(kind,uri,meta) VALUES(%s,%s,%s) ON CONFLICT DO NOTHING RETURNING id",
|
||||
("filesystem",p,json.dumps({})))
|
||||
sid_src = cur.fetchone()[0] if cur.rowcount else None
|
||||
if not sid_src:
|
||||
cur.execute("SELECT id FROM komp.source WHERE kind='filesystem' AND uri=%s",(p,))
|
||||
sid_src=cur.fetchone()[0]
|
||||
ln=1
|
||||
for ch in chunks(txt):
|
||||
cur.execute("INSERT INTO komp.chunk(source_id,lineno,text,sha256,tokens) VALUES(%s,%s,%s,%s,%s) RETURNING id",
|
||||
(sid_src,ln,ch,sh,len(ch)//4))
|
||||
kid=cur.fetchone()[0]
|
||||
vec=embed(ch)
|
||||
if len(vec)!=target_dim:
|
||||
cur.execute("DELETE FROM komp.chunk WHERE id=%s",(kid,))
|
||||
else:
|
||||
insert_embedding(cur, target_dim, kid, sid, vec)
|
||||
ln += ch.count("\n")+1
|
||||
conn.commit()
|
||||
print("done")
|
||||
|
||||
if __name__=='__main__':
|
||||
if len(sys.argv)<2: print("usage: ingest_dir.py <root> [space]", file=sys.stderr); sys.exit(1)
|
||||
if len(sys.argv)>=3: os.environ["EMBED_SPACE"]=sys.argv[2]
|
||||
main(sys.argv[1])
|
||||
|
||||
|
|
@ -0,0 +1,48 @@
|
|||
#!/usr/bin/env python3
|
||||
import os, sys, json, requests, psycopg
|
||||
|
||||
DB=os.environ.get("DB_URL","dbname=kompanion user=kompanion host=/var/run/postgresql")
|
||||
OLLAMA=os.environ.get("OLLAMA_BASE","http://127.0.0.1:11434")
|
||||
MODEL=os.environ.get("EMBED_MODEL","mxbai-embed-large")
|
||||
SPACE=os.environ.get("EMBED_SPACE","dev_knowledge")
|
||||
|
||||
HELP="""\
|
||||
Usage: pg_search.py "query text" [k]
|
||||
Env: DB_URL, OLLAMA_BASE, EMBED_MODEL, EMBED_SPACE (default dev_knowledge)
|
||||
Prints JSON results: [{score, uri, lineno, text}].
|
||||
"""
|
||||
|
||||
def embed(q: str):
|
||||
r = requests.post(f"{OLLAMA}/api/embeddings", json={"model": MODEL, "prompt": q}, timeout=120)
|
||||
r.raise_for_status()
|
||||
return r.json()["embedding"]
|
||||
|
||||
if __name__=="__main__":
|
||||
if len(sys.argv)<2:
|
||||
print(HELP, file=sys.stderr); sys.exit(1)
|
||||
query = sys.argv[1]
|
||||
k = int(sys.argv[2]) if len(sys.argv)>2 else 8
|
||||
vec = embed(query)
|
||||
with psycopg.connect(DB) as conn, conn.cursor() as cur:
|
||||
cur.execute("SELECT id, dim FROM komp.space WHERE name=%s", (SPACE,))
|
||||
row = cur.fetchone()
|
||||
if not row:
|
||||
sys.exit(f"space {SPACE} missing")
|
||||
sid, dim = row
|
||||
if dim not in (768,1024):
|
||||
sys.exit(f"unsupported dim {dim}")
|
||||
table = f"komp.embedding_{dim}"
|
||||
# cosine distance with vector_cosine_ops
|
||||
sql = f"""
|
||||
SELECT (e.embedding <=> %(v)s::vector) AS score, s.uri, k.lineno, k.text
|
||||
FROM {table} e
|
||||
JOIN komp.chunk k ON k.id = e.chunk_id
|
||||
JOIN komp.source s ON s.id = k.source_id
|
||||
WHERE e.space_id = %(sid)s
|
||||
ORDER BY e.embedding <=> %(v)s::vector
|
||||
LIMIT %(k)s
|
||||
"""
|
||||
cur.execute(sql, {"v": vec, "sid": sid, "k": k})
|
||||
out=[{"score":float(r[0]),"uri":r[1],"lineno":r[2],"text":r[3]} for r in cur.fetchall()]
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2))
|
||||
|
||||
|
|
@ -0,0 +1 @@
|
|||
psycopg
|
||||
Loading…
Reference in New Issue