Multi Agent Ai Azure Neon Openai

Multi-Agent AI Example with LangChain, AutoGen, Azure OpenAI, and Neon Serverless Postgres

This repository demonstrates how to build a **multi-agent AI solution** using:

• LangChain for natural language to SQL translation.
• AutoGen for coordinating AI agents in collaborative workflows.
• Azure OpenAI GPT-4o for intelligent language understanding and generation of SQL queries in Neon PostgreSQL.
• Neon Serverless Postgres for scalable database branching and dynamic data management.

The application showcases a shipping company where AI agents manage shipments, customers, and product information. The main goal is to demonstrate how AI agents can not only **query data** but also **act on it**, extending the "Chat With Your Data" concept to "Chat and Act on Your Data."


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Features

• 🌐 Gradio UI: User-friendly interface for natural language interactions.
• 🤖 AutoGen Multi-Agent: AI agents collaborate for specific tasks:
  • SchemaAgent: Manages database schema retrieval and sharing.
  • ShipmentAgent: Handles shipment-related queries and updates. Uses the send_shipment stored procedure.
  • CRMAgent: Manages customer and product-related data. Uses the add_customer stored procedure.

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Getting Started

1. Prerequisites

• Python 3.9+ (Recommended: 3.10 or 3.11)
• A Neon account (Sign up for Neon)
• Azure OpenAI API Endpoint, Model Deployment Name and API Key (For GPT-4)

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**2. Setup Instructions**

**Clone the Repository**

git clone https://github.com/your-username/multi-agent-ai-azure-neon-openai.git
cd mu