https://github.com/gsudiro/chatbot-ollama
Simple chatbot with Ollama
https://github.com/gsudiro/chatbot-ollama
Last synced: over 1 year ago
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Simple chatbot with Ollama
- Host: GitHub
- URL: https://github.com/gsudiro/chatbot-ollama
- Owner: gsudiro
- License: mit
- Created: 2024-11-18T00:06:41.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-06T03:29:56.000Z (over 1 year ago)
- Last Synced: 2025-03-06T04:26:23.990Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 35.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AI Chatbot with Ollama Integration
A modern, desktop-based AI chatbot application that integrates with Ollama to provide a user-friendly interface for interacting with LLM models. Built with Python and CustomTkinter for a clean, modern look.
## Features
- 🤖 Integrated with Ollama LLM models
- 🎨 Modern dark-mode GUI using CustomTkinter
- 💬 Real-time chat interface
- 🔄 Automatic Ollama service management
- 📊 Model management and storage information
- 💾 Automatic model downloading
- 🧵 Multi-threaded for responsive UI
- ⌨️ Support for keyboard shortcuts
## Prerequisites
Before running the application, make sure you have:
1. Python 3.8 or higher installed
2. Ollama installed on your system ([Ollama Installation Guide](https://ollama.ai/download))
3. Required Python packages
## Installation
1. Clone the repository:
```bash
git clone https://github.com/gsudiro/Chatbot-Ollama.git
cd ai-chatbot
```
2. Create and activate a virtual environment (recommended):
```bash
python -m venv .venv
# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate
```
3. Install required packages:
```bash
pip install customtkinter requests langchain-core langchain-ollama
# Or
pip install -r requirements.txt
```
## Usage
1. Start the application:
```bash
python main.py
```
2. The application will:
- Automatically start Ollama service if not running
- Check for and download required models
- Initialize the chat interface
3. Features:
- Type messages in the input field and press Enter or click Send
- Click "Show Models" to view installed models and storage usage
- Watch real-time status updates in the status bar
## Model Storage Locations
The models are stored by Ollama in the following locations:
- Linux: `/usr/share/ollama/models`
- macOS: `$HOME/.ollama/models`
- Windows: `C:\Users\%username%\.ollama\models`
## Technical Details
### Components
- **GUI**: Built with CustomTkinter for a modern look
- **LLM Integration**: Uses Langchain and Ollama
- **Threading**: Separate threads for UI and model operations
- **Error Handling**: Comprehensive error catching and user feedback
### Architecture
```
chatbot.py
├── ChatbotGUI (Main Class)
│ ├── UI Components
│ │ ├── Chat Display
│ │ ├── Input Field
│ │ ├── Send Button
│ │ └── Model Info Button
│ ├── Ollama Management
│ │ ├── Service Control
│ │ ├── Model Management
│ │ └── Status Updates
│ └── Chat Processing
├── Message Handling
├── Context Management
└── Response Generation
```
## Key Methods
- `initialize_chatbot()`: Sets up Ollama and model
- `send_message()`: Handles message processing
- `list_installed_models()`: Shows model information
- `pull_model()`: Downloads required models
- `update_status()`: Updates UI status
- `add_message()`: Adds messages to chat display
## Contributing
Feel free to submit issues and pull requests. For major changes, please open an issue first to discuss what you would like to change.
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Acknowledgments
- [Ollama](https://ollama.ai/) for the LLM backend
- [CustomTkinter](https://github.com/TomSchimansky/CustomTkinter) for the modern UI
- [Langchain](https://www.langchain.com/) for the LLM integration framework