Oracle AI Vector Search Integration with LangChain
LangChain is a powerful and flexible open source orchestration framework that helps developers build applications that leverage the advanced capabilities of large language models (LLMs).
LangChain provides essential tools for managing workflows, maintaining context, and integrating with external systems. For example, the LangChain framework allows you to create Chatbots and agent applications. LangChain primarily supports Python but also has support for JavaScript and TypeScript.
Oracle AI Vector Search integrates with LangChain at various levels:
- Document Loaders
- Text Splitter
- Embeddings
- Summary
- Vector Store
For more information about each of these components, see LangChain Oracle AI Vector Search documentation.
See Also:
- LangChain documentation for an introduction to the LangChain framwork
- LangChain component documentation for a list of LangChain components
- LangChain installation documentation to learn how to install LangChain packages in Python
- Oracle AI Vector Search integration demo for an end-to-end tutorial that demonstrates how Oracle AI Vector Search can be used with LangChain to serve as an end-to-end RAG pipeline
Parent topic: Use Retrieval Augmented Generation to Complement LLMs