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- **Description:** VertexAIEmbeddings performance improvements - **Twitter handle:** @vladkol ## Improvements - Dynamic batch size, starting from 250, lowering down to 5. Batch size varies across regions. Some regions support larger batches, and it significantly improves performance. When running large batches of texts in `us-central1`, performance gain can be up to 3.5x. The dynamic batching also makes sure every batch is below 20K token limit. - New model parameter `embeddings_type` that translates to `task_type` parameter of the API. Newer model versions support [different embeddings task types](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings#api_changes_to_models_released_on_or_after_august_2023).
🦜️🧑🤝🧑 LangChain Community
Quick Install
pip install langchain-community
What is it?
LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.
For full documentation see the API reference.
📕 Releases & Versioning
langchain-community is currently on version 0.0.x
All changes will be accompanied by a patch version increase.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.