Facebook AI Similarity Search (FAISS) is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in ...

Construct FAISS wrapper from raw documents asynchronously. This is intended to be a quick way to get started.

Facebook AI Similarity Search (Faiss) is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in ...

Construct FAISS wrapper from raw documents asynchronously. This is intended to be a quick way to get started.

Create a way to dynamically look up deprecated imports. Used to consolidate logic for raising deprecation warnings and handling optional imports.

Faiss is a library for efficient similarity search and clustering of dense vectors. Langchainjs supports using Faiss as a vectorstore that can be saved to ...

3 февр. 2024 г. · FAISS is an library stands for Facebook AI similarity search which is used to create embedding for documents and to perform similarity search ...

Build context-aware reasoning applications. Contribute to langchain-ai/langchain development by creating an account on GitHub.

9 авг. 2023 г. · FAISS, or Facebook AI Similarity Search is a library that unlocks the power of similarity search algorithms, enabling swift and efficient ...

25 янв. 2024 г. · The solution was for me to importing the FAISS class directly from the langchain.vectorstores.faiss module and then using the from_documents ...