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- **Description:** Azure Cognitive Search vector DB store performs slow embedding as it does not utilize the batch embedding functionality. This PR provide a fix to improve the performance of Azure Search class when adding documents to the vector search, - **Issue:** #11313 , - **Dependencies:** any dependencies required for this change, - **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` from the root of the package you've modified 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/docs/integrations` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> |
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| .. | ||
| adapters | ||
| agent_toolkits | ||
| callbacks | ||
| chat_loaders | ||
| chat_message_histories | ||
| chat_models | ||
| docstore | ||
| document_loaders | ||
| document_transformers | ||
| embeddings | ||
| graphs | ||
| indexes | ||
| llms | ||
| retrievers | ||
| storage | ||
| tools | ||
| utilities | ||
| utils | ||
| vectorstores | ||
| __init__.py | ||
| cache.py | ||
| py.typed | ||