Replace LightRAG with native Python RAG engine + add deploy tooling
- 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 11:24:01 +00:00
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FROM python:3.11-slim-bookworm
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# Native RAG engine — никаких внешних сервисов не требуется
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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build-essential \
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libsndfile1 \
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curl \
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ca-certificates \
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tesseract-ocr \
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tesseract-ocr-rus \
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tesseract-ocr-eng \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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COPY requirements.txt pip.conf ./
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RUN pip install --no-cache-dir --timeout 300 -r requirements.txt
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COPY . .
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RUN mkdir -p uploads processed tmp data
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EXPOSE 8000
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CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
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