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ran ```bash g grep -l "langchain.vectorstores" | xargs -L 1 sed -i '' "s/langchain\.vectorstores/langchain_community.vectorstores/g" g grep -l "langchain.document_loaders" | xargs -L 1 sed -i '' "s/langchain\.document_loaders/langchain_community.document_loaders/g" g grep -l "langchain.chat_loaders" | xargs -L 1 sed -i '' "s/langchain\.chat_loaders/langchain_community.chat_loaders/g" g grep -l "langchain.document_transformers" | xargs -L 1 sed -i '' "s/langchain\.document_transformers/langchain_community.document_transformers/g" g grep -l "langchain\.graphs" | xargs -L 1 sed -i '' "s/langchain\.graphs/langchain_community.graphs/g" g grep -l "langchain\.memory\.chat_message_histories" | xargs -L 1 sed -i '' "s/langchain\.memory\.chat_message_histories/langchain_community.chat_message_histories/g" gco master libs/langchain/tests/unit_tests/*/test_imports.py gco master libs/langchain/tests/unit_tests/**/test_public_api.py ```
24 lines
672 B
Plaintext
24 lines
672 B
Plaintext
# LanceDB
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This page covers how to use [LanceDB](https://github.com/lancedb/lancedb) within LangChain.
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It is broken into two parts: installation and setup, and then references to specific LanceDB wrappers.
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## Installation and Setup
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- Install the Python SDK with `pip install lancedb`
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## Wrappers
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### VectorStore
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There exists a wrapper around LanceDB databases, allowing you to use it as a vectorstore,
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whether for semantic search or example selection.
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To import this vectorstore:
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```python
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from langchain_community.vectorstores import LanceDB
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```
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For a more detailed walkthrough of the LanceDB wrapper, see [this notebook](/docs/integrations/vectorstores/lancedb)
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