Vectara with LangChain
Integrate the full power of end-to-end RAG in your LangChain application, reducing complexity and supporting enterprise scale.
Learn about Vectara + LangChainDetails
As a fully-managed enterprise RAG solution, Vectara provides a full platform for end-to-end RAG development including text extraction and chunking, a state of the art embedding model, a cross-lingual reranker, our own high-performance vector database, and a generative LLM.
Using Vectara in your LangChain application means you can focus on your application logic, and integrate additional features without worrying about security, data privacy, or scaling.
The integration supports:
- Data ingestion in the form of file upload or directly as text.
- You can use the LangChain Vectara integration for a powerful semantic search, recommendation, or as a full RAG pipeline with the convenient as_rag() one-liner.
- Vectara fully supports chat, where session history is stored and managed by Vectara. By calling as_chat() you can convert your LangChain application into a virtual assistant with just one line of code.
- Vectara’s integration fully supports LangChain’s LCEL, parallel execution and streaming.
Take advantage of Vectara’s full set of features from LangChain including our SOTA embeddings model, multi-lingual reranker, hybrid search, and more.
