* feat: introduce hindsight-api-slim and hindsight-all-slim packages Closes #552 - Move all source code from hindsight-api/ to new hindsight-api-slim/ - hindsight-api-slim has heavy ML deps (torch, sentence-transformers, transformers, einops, flashrank, mlx, mlx-lm, safetensors) and pg0-embedded as optional extras: [local-ml], [embedded-db], [all] - hindsight-api becomes a zero-code meta-package depending on hindsight-api-slim[all] for full backward compatibility - Add hindsight-all-slim meta-package: hindsight-api-slim + client + embed - hindsight-all updated to depend on hindsight-api-slim[all] - pg0.py: lazy-import pg0 with clear ImportError pointing to [embedded-db] - Dockerfile: replace sed hack with proper uv sync --extra flags - Update release.yml, test.yml, lint.sh, release.sh, CLAUDE.md and all path references throughout the repo * refactor: rename hindsight/ directory to hindsight-all/ * docs: document hindsight-api-slim and hindsight-all-slim package variants Add package variants table and extras explanation to installation.md * docs: remove emojis from installation.md, use professional tone * docs: link Docker slim variant to pip package variants section * docs: consolidate Docker image variants into single table * ci: fix working-directory paths after package restructure - Replace all hindsight-api → hindsight-api-slim in test.yml - Replace hindsight → hindsight-all in test.yml - Add --extra embedded-db to test-embed API install step * ci: add local-ml and embedded-db extras to API sync steps These extras were previously implicit in the old hindsight-api package (which bundled everything). Now that hindsight-api-slim uses optional extras, we must explicitly request local-ml and embedded-db in CI. * ci: add API install step with embedded-db to test-embed smoke test The smoke test starts hindsight-api as a daemon, which requires pg0-embedded. Add a dedicated install step for hindsight-api-slim with embedded-db extra so the daemon can start successfully. * ci: remove --no-install-project when using optional extras When --no-install-project is combined with --extra, the optional deps are not installed because extras require the project to be active. Remove --no-install-project from steps that need local-ml or embedded-db. * ci: fix ordering of uv sync steps to preserve optional extras When uv sync runs for a different workspace member, it removes optional extras installed for other members. Fix by always running extra-requiring API sync last, after other workspace member syncs. Also remove --no-install-project from embedded-db sync in test-embed, as --no-install-project prevents optional extras from being active. * ci: add local-ml extra to test-embed API install for smoke test The smoke test starts the full API server which needs sentence-transformers for local embeddings (default provider). Add local-ml extra to the install. * ci: simplify extras with --all-extras and add slim pip smoke test - Replace explicit --extra local-ml --extra embedded-db with --all-extras for cleaner, more maintainable sync steps - Add test-pip-slim job: tests hindsight-api-slim[embedded-db] without local ML models, using Cohere for embeddings/reranking (mirrors Docker slim smoke test approach) * ci: simplify slim smoke test to health check only (mirrors Docker test)
52 lines
1.4 KiB
Python
52 lines
1.4 KiB
Python
"""
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Embedding generation utilities for memory units.
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"""
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import asyncio
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import logging
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logger = logging.getLogger(__name__)
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def generate_embedding(embeddings_backend, text: str) -> list[float]:
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"""
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Generate embedding for text using the provided embeddings backend.
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Args:
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embeddings_backend: Embeddings instance to use for encoding
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text: Text to embed
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Returns:
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Embedding vector (dimension depends on embeddings backend)
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"""
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try:
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embeddings = embeddings_backend.encode([text])
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return embeddings[0]
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except Exception as e:
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raise Exception(f"Failed to generate embedding: {str(e)}")
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async def generate_embeddings_batch(embeddings_backend, texts: list[str]) -> list[list[float]]:
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"""
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Generate embeddings for multiple texts using the provided embeddings backend.
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Runs the embedding generation in a thread pool to avoid blocking the event loop
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for CPU-bound operations.
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Args:
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embeddings_backend: Embeddings instance to use for encoding
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texts: List of texts to embed
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Returns:
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List of embeddings in same order as input texts
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"""
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try:
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loop = asyncio.get_event_loop()
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embeddings = await loop.run_in_executor(
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None,
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embeddings_backend.encode,
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texts,
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)
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return embeddings
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except Exception as e:
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raise Exception(f"Failed to generate batch embeddings: {str(e)}")
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