Suriya
5e373ea20c
The image was 2.45GB, of which the venv is 1.73GB. The build was already multi-stage and already installed CPU-only torch, so the remaining weight was not build tooling - it was payload inside the installed packages that the running service can never execute. Removed in the build stage, before the runtime stage copies /opt/venv, so the bytes never enter the final image: - bundled test suites (~237MB; torch/test is 83MB, pandas/tests 40MB) - torch/include (62MB), C++ headers for compiling against libtorch - torch/bin (50MB), gtest binaries and protoc; torch_shm_manager is kept pytest and httpx2 move to requirements-dev.txt: the image copies app/, cli/, scripts/, data/ and serve.py, never tests/, so the test stack was unusable there regardless. sympy was checked and deliberately kept - 'import sentence_transformers' does pull it in through torch.fx, so removing it would break embeddings. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
82 lines
3.1 KiB
Plaintext
82 lines
3.1 KiB
Plaintext
# --- Web API ---
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fastapi>=0.115.0
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uvicorn[standard]>=0.30.6
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pydantic>=2.9.2
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python-multipart>=0.0.6
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# --- Config ---
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python-dotenv>=1.0.1
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# --- Authentication ---
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# Signs/verifies the access tokens issued by /api/auth/login. Pure Python, no
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# compiled extension - nothing extra to build on the slim image. Password
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# hashing uses hashlib.pbkdf2_hmac from the standard library, so there is
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# deliberately no bcrypt/argon2/passlib dependency here.
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PyJWT>=2.9.0
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# --- MCP (Model Context Protocol) ---
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# Serves the catalog as tools for AI clients at /mcp (see app/mcp_server.py),
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# mounted onto the FastAPI app so it needs no separate process or container.
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# Requires Python >=3.10; the Dockerfile's python:3.11-slim satisfies that, and
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# app/main.py degrades to serving the REST API alone if the import fails.
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fastmcp>=3.4.7
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# --- Database / pgvector ---
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psycopg[binary]>=3.2.3
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pgvector>=0.2.5
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# --- Embeddings (RAG retrieval) ---
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# sentence-transformers pulls in its own CPU-friendly torch wheel
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# automatically - no need to pin torch separately. Imports are LAZY
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# (see app/services/embeddings_service.py) so the API still boots fast
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# even before this is installed/loaded.
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sentence-transformers>=3.0.1
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# --- HTTP clients ---
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requests>=2.31.0
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aiohttp>=3.9.5
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httpx>=0.27.2
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# --- Catalog ingestion pipeline (discovery / images / pricing) ---
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# Only required if you plan to run cli/ingest_brand.py or
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# POST /api/catalog/generate to pull in NEW brands. If you only ever use
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# the bundled seed data (scripts/seed_sample_data.py) + RAG chat/search,
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# you can skip everything below this line.
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beautifulsoup4>=4.12.3
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lxml>=4.9.3
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python-slugify>=8.0.4
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ddgs>=9.14.4
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Pillow>=10.0.0
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aiofiles>=23.2.1
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# Playwright (Python) - last-resort image-search fallback only.
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# Run `playwright install chromium` once after pip install to enable it;
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# the pipeline works fine without it (just one fewer fallback source).
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# playwright>=1.47.0
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# Commented out, not deleted. It is the last-resort image-search tier, and the
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# Dockerfile never installs its browser binary - so in a container the tier is
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# skipped at runtime no matter what, while the package still costs 137MB. The
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# import is lazy (app/services/playwright_image_fallback.py does it inside the
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# function), so its absence is handled on the existing "not installed" path.
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# Uncomment, and run `playwright install chromium`, if you ever want that tier.
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# --- S3 / DigitalOcean Spaces (optional product image storage) ---
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boto3>=1.34.162
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# --- ML / analytics (app/intelligence/*, incl. nutrition similarity & ---
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# --- clustering) - CPU-only estimators only (GradientBoosting/Random- ---
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# --- Forest/KMeans/NearestNeighbors), no GPU dependency, per the 8GB ---
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# --- RAM / CPU-only environment this project targets. Was already an ---
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# --- implicit dependency (app/intelligence/*.py imports these) but was ---
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# --- missing from this file - declared explicitly now. ---
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scikit-learn>=1.5.2
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pandas>=2.2.2
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numpy>=1.26.4
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scipy>=1.13.1
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joblib>=1.4.2
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# --- Dev/test tooling ---
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# Moved to requirements-dev.txt so the Docker image does not carry the test
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# stack it can never run. To work on this project, install both:
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# pip install -r requirements.txt -r requirements-dev.txt
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