LangGraph Start

Example Use Cases

• 1

  Call local tools or functions from an LLM-driven workflow via a simple MCP server/client integration.

• 2

  Perform retrieval-augmented generation using local FAISS vector stores and embeddings (with a HuggingFace embedding option).

• 3

  An out-of-the-box example demonstrating chatbot flows with function calling, memory, and RAG components.

Description

LangGraph Start is an example project that demonstrates how to build chatbots with function calling, memory, and retrieval-augmented generation (RAG) using LangGraph/LangChain. It includes scripts to create embeddings (with a HuggingFace fallback), build/search a FAISS index, and run a simple local MCP server and client to expose callable tools. The repository is intended as a quickstart to integrate LLMs (via configurable API keys), vector stores, and local tool invocation into agent pipelines.