keboss-m
eee8f4c8a4
Replace LightRAG with native Python RAG engine + add deploy tooling
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- New: src/rag/engine/ — in-process hybrid search (FTS5 BM25 + sqlite-vec + LLM rerank)
- New: src/rag/qmd/ — compatibility layer (qmd_query, qmd_chat, qmd_chat_stream, qmd_index_*)
- New: src/ingest/stub_writer.py — .md stubs for binary files (videos, archives)
- New: scripts/deploy.sh + scripts/pull_models.sh + Makefile + .env.example
- Removed: LightRAG, sentence-transformers embedding via separate package, rag_standalone/
- Removed: @nousresearch/qmd npm dep (package not published); Node.js from Dockerfile
- Updated: tests/ (46 passed), docker-compose, .dockerignore, config.yaml, README
Engine: in-process Python (no daemon, no npm), sentence-transformers 384-dim,
RRF fusion (k=60), BM25 + vector with numpy fallback. WebSocket API unchanged.
Deploy: 'git clone' + 'make init' + 'make pull-models MODELS_SOURCE=...' + 'make up'.
Models (5.83 GB) live outside git; pulled via rsync from dev host.
2026-06-10 14:24:01 +03:00
keboss-m
fee9b9acb1
Add RAG, summary pipeline, and split transcribe/postprocess queue.
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Separate ASR (2 workers) from summary/RAG post-processing, add LightRAG chat API, batch upload fixes, and local model mounts for Docker deployment.
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-01 17:40:58 +03:00
