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BigQuery vector search lets you use GoogleSQL to do semantic search, using vector indexes for fast but approximate results, or using brute force for exact results. This PR integrates LangChain vectorstore with BigQuery Vector Search. <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Vlad Kolesnikov <vladkol@google.com> |
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| .. | ||
| adapters | ||
| callbacks | ||
| chat_message_histories | ||
| chat_models | ||
| document_loaders | ||
| embeddings | ||
| examples | ||
| graphs | ||
| llms | ||
| retrievers | ||
| storage | ||
| tools | ||
| utilities | ||
| vectorstores | ||
| __init__.py | ||
| test_compile.py | ||