Multi-Agent Orchestration for Data Analysis & Simulation Scenarios

A sophisticated data analysis and simulation platform using a multi-agent workflow powered by Chainlit and Mistral AI. This application enables users to perform complex data queries and run what-if scenario simulations through natural language interactions.

Current Status#

Desired Status#

🚀 Features#

• Natural Language Querying: Ask data questions in plain English
• Automatic SQL Generation: AI converts questions to SQL queries
• Scenario Simulation: Run what-if analyses on your data
• Visualization: Automatic chart generation for results
• Multi-Agent Architecture: Specialized agents for different tasks
• Interactive UI: User-friendly Chainlit interface

📋 Table of Contents#

• Installation
• Usage
• Demos
• Architecture
• Roadmap

🛠️ Installation#

Prerequisites#

• Python 3.11+
• UV for package management (recommended)
• Mistral API key

Steps#

1. Clone the repository:

2. Set up environment variables:

   • Copy .env.example to .env
   • Add your Mistral API key to .env

3. Create and activate virtual environment:

   uv venv
   source .venv/bin/activate  # Linux/macOS
   # .\.venv\Scripts\activate  # Windows

   uv venv
   source .venv/bin/activate  # Linux/macOS
   # .\.venv\Scripts\activate  # Windows

4. Install dependencies:

   uv sync

   uv sync

5. Run the application:

   uv run -- chainlit run app.py

   uv run -- chainlit run app.py

🎛️ Usage#

Starting the Application#

1. Run the Chainlit app as shown above
2. Open the provided URL in your browser
3. Use the starter questions or ask your own

Example Queries#

• "Show total estimated revenue across all accounts in January 2025"
• "List the top 5 account names by available balance"
• "What if we raise deposit rates by 0.5%?"

Workflow Visualization#

Type "Show workflow" to see the system architecture diagram.

📊 Demos#

Demo Script

Data Analysis#

Scenario Simulation#

🏛️ Architecture#

The system uses a multi-agent approach:

1. Router Agent: Determines query intent
2. Analysis Agent: Handles data queries
3. Simulation Agent: Runs what-if scenarios
4. Report Agent: Generates visualizations

graph TD;
    A[User] --> B[Router Agent];
    B -->|Data Query| C[Analysis Agent];
    B -->|Simulation| D[Simulation Agent];
    C --> E[Database];
    D --> E;
    C --> F[Report Agent];
    D --> F;
    F --> A;

graph TD;
    A[User] --> B[Router Agent];
    B -->|Data Query| C[Analysis Agent];
    B -->|Simulation| D[Simulation Agent];
    C --> E[Database];
    D --> E;
    C --> F[Report Agent];
    D --> F;
    F --> A;

🗺️ Roadmap#

• Add voice input support
• Implement more advanced simulation models
• Add user authentication
• Support additional data sources