https://github.com/adelelawady/qwenchat
This project is a React-based chat application powered by Qwen-Coder, designed to assist developers with writing, debugging, and improving code. The application functions like ChatGPT but is tailored specifically for coding needs
https://github.com/adelelawady/qwenchat
Last synced: 3 months ago
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This project is a React-based chat application powered by Qwen-Coder, designed to assist developers with writing, debugging, and improving code. The application functions like ChatGPT but is tailored specifically for coding needs
- Host: GitHub
- URL: https://github.com/adelelawady/qwenchat
- Owner: adelelawady
- License: mit
- Created: 2024-11-29T22:40:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-29T23:07:05.000Z (over 1 year ago)
- Last Synced: 2025-05-07T19:50:27.015Z (about 1 year ago)
- Language: TypeScript
- Size: 462 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Chat with Qwen-Coder
A real-time chat application that allows users to interact with Qwen-Coder AI model, featuring file upload capabilities and chat history. Built with React, FastAPI, and Ollama.
## Features
- Real-time chat with Qwen-Coder
- File upload and analysis
- Chat history persistence
- Code syntax highlighting
- Markdown support
- File content analysis
- Modern UI inspired by ChatGPT
## Prerequisites
- Node.js (v16 or higher)
- Python (3.8 or higher)
- Ollama installed on your system
### Installing Ollama and Qwen-Coder
1. Install Ollama:
**On macOS or Linux:**
```bash
curl -fsSL https://ollama.com/install.sh | sh
```
**On Windows:**
- Download and install from [Ollama Windows](https://ollama.com/download/windows)
- Make sure Windows Subsystem for Linux (WSL) is installed
- Follow the installation wizard instructions
2. Start Ollama service:
```bash
ollama serve
```
3. Pull the Qwen-Coder model (in a new terminal):
```bash
# Pull the smallest version (recommended for most users)
ollama pull qwen2.5-coder:0.5b
```
The download might take a few minutes depending on your internet connection. You'll see a progress bar like this:
```
pulling manifest... done
pulling 6c91e4... done
pulling 4c915e... done
verifying sha256 digest... done
```
4. Test the model installation:
```bash
ollama run qwen2.5-coder:0.5b "Hello, are you ready?"
```
You should get a response from the model.
**Troubleshooting Ollama Installation:**
- If you get permission errors on Linux:
```bash
sudo chmod +x /usr/local/bin/ollama
```
- If Ollama service fails to start:
```bash
# Check if the service is running
ps aux | grep ollama
# Restart the service
killall ollama
ollama serve
```
## Installation
### Backend Setup
1. Create a Python virtual environment:
```
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
2. Install Python dependencies:
```
pip install fastapi uvicorn langchain langchain-community python-multipart
```
3. Create required directories:
```
mkdir uploads
```
### Frontend Setup
1. Install Node.js dependencies:
```
npm install
```
Required dependencies include:
- @tanstack/react-query
- axios
- react-markdown
- react-syntax-highlighter
- lucide-react
- tailwindcss
- @tailwindcss/typography
- shadcn/ui components
## Running the Application
1. Start Ollama (if not already running):
```
ollama start
```
2. Start the backend server (from the project root):
```
uvicorn backend.server:app --reload
```
3. Start the frontend development server (in a new terminal):
```
npm run dev
```
4. Open your browser and navigate to:
```
http://localhost:5173
```
## Project Structure
```
project/
├── backend/
│ ├── init.py
│ ├── server.py # FastAPI server
│ ├── chat_with_qwen.py # Qwen integration
│ └── chat_history.py # Chat history management
├── src/
│ ├── components/ # React components
│ │ ├── Chat.tsx
│ │ ├── ChatInput.tsx
│ │ ├── ChatMessage.tsx
│ │ ├── ChatSidebar.tsx
│ │ └── FileUpload.tsx
│ └── pages/
│ └── Index.tsx
└── uploads/ # Uploaded files directory
```
## Qwen-Coder Models
Available models through Ollama:
| Model | Size | RAM Required | Performance |
|-------|------|--------------|-------------|
| qwen2.5-coder:0.5b | 500MB | 2GB | Fast, good for basic tasks |
| qwen2.5-coder:1.8b | 1.8GB | 4GB | Better comprehension |
| qwen2.5-coder:3b | 3GB | 8GB | Best quality, slower |
To change models, update the model name in `backend/chat_with_qwen.py`:
```
model = Ollama(
model="qwen2.5-coder:0.5b",
base_url="http://localhost:11434",
temperature=0.7, # Add some creativity for analysis
)
```
## Features in Detail
### File Upload
- Supports text files, code files, and other formats
- Automatic content extraction
- File content analysis by Qwen-Coder
### Chat Interface
- Real-time message streaming
- Code syntax highlighting
- Markdown rendering
- File upload indicator
- Typing indicators
### Chat History
- Persistent chat storage
- Multiple chat sessions
- Chat title generation
- Delete chat functionality
## Contributing
1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a new Pull Request
## License
This project is licensed under the MIT License - see the LICENSE file for details.