AI Tooling Kit
Demonstrates an end-to-end workflow for an LLM chat client to interact with a FastAPI server exposing database tools via Server-Sent Events.
Acerca de
This project serves as a comprehensive template demonstrating the integration of a Large Language Model (LLM) chat client with a backend service to perform database operations. It features a FastAPI server that exposes PostgreSQL database tools, leveraging Server-Sent Events (SSE) for efficient client-server communication using JSON-RPC. The accompanying LLM chat client dynamically discovers and invokes these tools—such as listing or adding employees—allowing the conversational AI agent to interact with and retrieve information from a database, making it an ideal starting point for developing intelligent agents capable of complex system interactions.
Características Principales
- Support for multiple LLM providers (OpenAI, OpenRouter)
- LLM chat client capable of dynamic tool discovery and invocation
- 0 GitHub stars
- Robust Server-Sent Events (SSE) communication pattern
- FastAPI server exposing database tools via SSE/JSON-RPC
- Docker Compose setup for PostgreSQL database and server
Casos de Uso
- Developing conversational AI agents that manage database interactions
- Creating LLM-powered assistants for internal business process automation
- Learning and prototyping LLM agent integration with custom APIs via SSE
