README.md Content

Below is the content tailored to your project. Copy this into a file named README.md in your C:\Users\HP\OneDrive\Desktop\multiagent directory using a text editor (e.g., Notepad, VS Code).

# Multi-Agent Business System

A web-based application that uses multiple AI agents to process business-related queries, powered by FastAPI and Ollama's `mistral` model.

## Overview
This project implements an interactive multi-agent system to handle tasks such as data collection, analysis, visualization, and reporting. Agents collaborate to process user queries and deliver aggregated results via a browser interface.

## Features
- **Planner Agent**: Breaks down queries into manageable subtasks.
- **Data Collector Agent**: Generates or mocks relevant data.
- **Analyzer Agent**: Extracts insights from data.
- **Visualizer Agent**: Creates simple charts (if data supports it).
- **Report Generator Agent**: Compiles final summaries.

## Prerequisites
- **Python 3.8+**
- **Ollama** (for AI model hosting)
- **Windows, macOS, or Linux**

## Installation

### 1. Clone the Repository
```bash
git clone <your-repo-url>  # Replace with your repository URL if applicable
cd multiagent

2. Set Up a Virtual Environment

python -m venv multiagent_venv
multiagent_venv\Scripts\activate  # On Windows
# Or: source multiagent_venv/bin/activate  # On macOS/Linux

3. Install Dependencies

Install the required Python packages:

pip install -r requirements.txt

4. Install and Configure Ollama

• Download and install Ollama from ollama.com.
• Pull the mistral model:

  ollama pull mistral

• Start the Ollama server:

  ollama serve

Usage

1. Start the application:

   python main.py

2. Open your browser and go to http://127.0.0.1:8000/.
3. Enter a query (e.g., "Summarize sales trends for Q1") in the textarea and click "Process Request".
4. View the agent progress and final result on the page.

Example Queries

• Say hello - Tests basic connectivity.
• Summarize the sales data for January - Generates a simple sales summary.
• Analyze customer feedback: 'Great product, poor support' - Performs sentiment analysis.
• Show a pie chart of sales by region: North $5000, South $3000, East $2000 - Creates a pie chart.
• Generate a detailed report on quarterly revenue trends and customer satisfaction for Q1 - Produces a comprehensive report.

Troubleshooting

• Connection Errors: Ensure Ollama is running and listening on 127.0.0.1:11434. Check with curl -X POST http://localhost:11434/api/generate -d '{"model": "mistral", "prompt": "Hello"}'.
• 500 Errors: Increase memory availability (close other apps) or adjust the timeout in main.py (line 40) to 120 seconds.
• Port Conflicts: Use netstat -aon | findstr :11434 to identify conflicts and kill the process with taskkill /PID <PID> /F.

Contributing

Feel free to fork this repository, make improvements, and submit pull requests. Report issues on the GitHub page if applicable.

License

[Specify your license, e.g., MIT] - Add a license file if needed.

Acknowledgments

• Built with FastAPI, Uvicorn, and Ollama.
• Inspired by xAI's multi-agent concepts.

### Step 1: Create the File
1. Open a text editor.
2. Copy the content above.
3. Save it as `README.md` in `C:\Users\HP\OneDrive\Desktop\multiagent`.

### Step 2: Customize (Optional)
- **Repository URL**: If this is a GitHub repo, replace `<your-repo-url>` with the actual URL.
- **License**: Add a license (e.g., MIT) and create a `LICENSE` file if desired.
- **Acknowledgments**: Credit additional tools or inspiration if applicable.

### Step 3: Verify
- Open `README.md` in a text editor or browser (if rendered with Markdown support) to ensure formatting is correct.
- The file uses Markdown syntax (e.g., `#` for headings, `-` for lists), which GitHub and other platforms will render nicely.

### Step 4: Integrate with Project
- This `README.md` complements your `requirements.txt` (from earlier) and project files. It provides setup instructions that align with our troubleshooting steps.
- You can now resume testing the app with the queries I provided earlier once Ollama finishes loading.

### Step 5: Report Back
- After creating the file, let me know if you need adjustments or help with testing the queries (e.g., "Say hello") at 05:00 PM PKT.
- Share any issues with file creation or further logs if testing fails.