Full Stack LangGraph Example

This is an example app that uses LangGraph to create an AI agent. It will be a simpler application that uses React/Python/FastAPI/ Postgres and LLMs to perform analysis on customer feedback for products for a fictional company called 'Acme'.

Todo:

Backend

• Seed DB with products
• Decide on vector DB and add to docker compose file. (Between Milvus or PGVector)
• Add a tool to get user information at login and insert it into the graph start so the agent knows the user.
• Add a tool to search DB with products using text to SQL.
• Add a tool to provide feedback about a product
• Finish integrating Alembic for migrations

Frontend

• Initialize the frontend repo with CRA + Bulma for easy CSS
• Create Register Component
• Create Login Component
• Create provider to save user info
• Create Dashboard to chat with agent + streaming support
• Add to dashboard graphs to show customer sentiment about all products/specific products

Prereqs

1. Have poetry installed
2. Have docker installed

How to run

To start the backend

1. cd backend/
2. poetry install --no-root
3. docker-compose up --build --remove-orphans