📊 AI Data Visualization Agent

A Streamlit application that acts as your personal data visualization expert, powered by local LLMs.
Simply upload your dataset and ask questions in natural language --- the AI agent will analyze your data, generate visualizations, and provide insights through charts, statistics, and explanations.

Output (AI-generated Report):

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✨ Features

Natural Language Data Analysis

• Ask questions about your data in plain English

• Get instant visualizations and statistical analysis

• Receive explanations of findings and insights

• Interactive follow-up questioning

Intelligent Visualization Selection

• Automatic choice of appropriate chart types

• Dynamic visualization generation

• Statistical visualization support

• Custom plot formatting and styling

Multi-Model AI Support (via Ollama)

• Llama 3.1 8B for lightweight, fast analysis

• Llama 3.2 for balanced reasoning

• DeepSeek R1 7B for detailed insights

• Qwen 2.5 7B for quick queries

• Mistral for flexible analysis

⚙️ How to Run

1. Clone the Repository

    `git clone https://github.com/<your-username>/ai-data-visualization-agent.git
    cd ai-data-visualization-agent`

2. Install Dependencies

    `pip install -r requirements.txt`

3. Install Ollama (for local models)

• Download Ollama 👉 https://ollama.com/download
• Pull a model (e.g., Llama 3.2):

        `ollama pull llama3.2:latest`

4. Set up E2B (for safe code execution)

• Get a free API Key: https://e2b.dev/docs/legacy/getting-started/api-key
• Store it in your environment:

        `export E2B_API_KEY=your_api_key_here`

5. Run the Streamlit App

    `streamlit run app.py`

📂 Example Workflow

• Upload a CSV file (e.g., customers.csv)

• Ask: "Show me the number of customers per city"

• The agent normalizes column names (case-insensitive), generates Python code, runs it in a sandbox, and displays the chart.

⚠️ Disclaimer

This project is for educational and experimental purposes only.
It is not a production-ready tool. Please ensure you handle sensitive datasets responsibly.