Facilitates the development of retrieval agents using LangGraph for question answering.
Sponsored
This starter project provides a foundation for building retrieval-based question answering systems using LangGraph and LangGraph Studio. It includes pre-built graphs for indexing documents and managing chat history to provide personalized responses based on retrieved context. The template supports various vector stores, embedding models, and language models, allowing for extensive customization and experimentation.
Key Features
01Includes an index graph for document processing and indexing.
02Compatible with OpenAI and Cohere embedding models.
