jupyterlab-ai-assistant 1.1.1

A JupyterLab extension that integrates Ollama-powered AI assistance directly into notebooks

JupyterLab AI Assistant

A comprehensive JupyterLab extension that integrates Ollama-powered AI assistance directly into notebooks with cell-specific context awareness and responsive design.

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✨ Features

• Chat with Ollama Models: Interact with locally-running Ollama AI models directly within JupyterLab
• Cell-Contextual AI Assistance: Ask questions about specific notebook cells with a simple click
• Smart Responses: Get syntax-highlighted, markdown-formatted responses
• Responsive Design: Clean, modern interface that adapts to your JupyterLab theme
• Theme-Aware UI: Seamless integration with JupyterLab's light/dark themes
• Multi-Model Support: Use any Ollama model installed on your system
• Code Analysis: Explain, optimize, or debug code directly from your notebooks

🔍 How It Works

The extension connects to your local Ollama service and provides two main interaction modes:

1. Chat Interface: A standalone chat widget where you can ask general questions
2. Cell Context Actions: Toolbar buttons that appear on notebook cells for code-specific questions

Chat Widget

The chat interface features:

• Full markdown support including code blocks
• Syntax highlighting for code
• Model selection dropdown
• Responsive design for all screen sizes

Cell Context Analysis

Cell toolbar buttons provide quick access to:

• 🔍 Explain code in the current cell
• 🔧 Optimize performance
• 🐞 Debug issues
• 📊 Analyze data processing logic
• 💬 Ask custom questions about the cell content

📋 Prerequisites

• JupyterLab 4.x (compatible with 4.0.0 and above)
• Ollama installed and running locally
• Python 3.8+

Detailed Dependencies

This extension has the following specific dependencies:

jupyterlab >= 4.0.0, < 5.0.0
jupyter_server >= 2.0.0
jupyter-client >= 8.0.0
aiohttp
requests >= 2.25.0

Frontend Dependencies

react >= 18.2.0
react-dom >= 18.2.0
react-markdown >= 8.0.0
bootstrap >= 5.3.3

🚀 Installation

Method 1: Install from Source

Use the provided installation script which handles all dependencies and setup:

# Clone the repository
git clone https://github.com/bhumukul-raj/ollama-ai-assistant-project.git
cd ollama-ai-assistant-project/jupyterlab-ai-assistant

# Run the installation script (creates a virtual environment)
bash install-fixed.sh

Method 2: Manual Installation

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate

# Install JupyterLab 4.x and dependencies
pip install "jupyterlab>=4.0.0,<5.0.0" "jupyter_server>=2.0.0,<3.0.0" "jupyter-client>=8.0.0"
pip install aiohttp "requests>=2.25.0"

# Install the extension in development mode
pip install -e .

# Build and link the extension
jupyter labextension develop . --overwrite
jupyter lab build

Verify Installation

To verify the extension is properly installed:

jupyter labextension list

You should see jupyterlab-ai-assistant listed in the output.

Ollama Setup

1. Install Ollama from ollama.ai
2. Start the Ollama service:

   ollama serve
   

3. Pull at least one model to use with the extension:

   ollama pull llama2
   

📖 Usage Guide

Chat Interface

1. Launch JupyterLab
2. Click on the "AI Assistant" icon in the sidebar or open it from the menu (AI Assistant > Open AI Assistant)
3. Select a model from the dropdown
4. Type your question and press Enter

Cell-Specific Questions

1. Open a notebook in JupyterLab
2. Hover over any code or markdown cell
3. Click on one of the AI assistant buttons in the cell toolbar:
   • 🔍 Explain - Understand what the code does
   • 🔧 Optimize - Get suggestions for performance improvement
   • 🐞 Debug - Find and fix issues in your code
   • 💬 Chat - Ask a custom question about this cell
4. View the AI's response in the popup dialog

Common Use Cases

• Code Explanation: "What does this pandas transformation do?"
• Debugging Help: "Why am I getting this ValueError in my function?"
• Performance Optimization: "How can I make this loop faster?"
• Documentation: "Generate docstrings for this class"
• Learning: "Explain this algorithm step by step"

⚙️ Configuration

You can configure the extension in JupyterLab's Settings menu:

1. Go to Settings > Advanced Settings Editor
2. Select "AI Assistant" from the dropdown
3. Modify the settings as needed

Available settings:

{
  "defaultModel": "llama2",
  "baseUrl": "http://localhost:11434",
  "enabled": true,
  "maxTokens": 4096,
  "defaultTemperature": 0.7,
  "requestTimeout": 60,
  "debugMode": false
}

💻 System Requirements

For the best experience, we recommend:

• A system with at least 8GB RAM
• Sufficient disk space for Ollama models (models range from 1GB to 10GB+ each)
• A modern web browser (Chrome, Firefox, Safari, Edge)
• Python 3.8 or newer

🔧 Troubleshooting

Common Issues

• Extension visible in jupyter labextension list but not in JupyterLab UI:

  • Clear JupyterLab caches with jupyter lab clean
  • Remove any conflicting configurations in ~/.jupyter/jupyter_server_config.json
  • Run jupyter server extension enable jupyterlab_ai_assistant
  • Restart JupyterLab completely

• "Module not found" error for jupyterlab_ai_assistant:

  • Ensure you're running JupyterLab from the same virtual environment where you installed the extension
  • Try reinstalling: pip install -e . from the extension directory
  • Check that the module is in your Python path with python -c "import sys; print(sys.path)"

• No models available:

  • Ensure Ollama is running (ollama serve)
  • Verify you've pulled at least one model (ollama list)
  • Check connection to the Ollama API: curl http://localhost:11434/api/tags

• Connection errors:

  • Verify the Ollama API is accessible at http://localhost:11434
  • Check your network configuration if running on a remote system
  • Ensure there are no firewall rules blocking the connection

• TypeScript build errors:

  • Make sure you have Node.js installed (version 14 or higher recommended)
  • Run a clean build: npm run clean && npm run build:prod

Testing the Connection

The extension includes a test tool to verify connectivity:

1. From the JupyterLab menu, select: AI Assistant > Test Ollama Connection
2. A panel will open showing all available models if the connection is successful

Checking Server Logs

If experiencing issues, check the JupyterLab server logs for error messages:

jupyter lab --debug

🛠️ Development

For developers who want to contribute to the project:

# Clone the repository
git clone https://github.com/bhumukul-raj/ollama-ai-assistant-project.git
cd ollama-ai-assistant-project/jupyterlab-ai-assistant

# Install dependencies
pip install -e .
jupyter labextension develop . --overwrite

# Watch for changes during development
npm run watch

In a separate terminal, run JupyterLab in watch mode:

jupyter lab --watch

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

• Bhumukul Raj - GitHub - Email

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

📸 Screenshots