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# GPT-4o Media Stream Capture and Analysis
## Project Overview
This project provides a web application that captures media streams from various sources such as a webcam, desktop, or specific applications. It captures frames at intervals and uses AI to analyze and summarize the frames, providing insights using GPT-4.
![GPT-4o Media Stream Capture and Analysis](https://github.com/ruvnet/ai-video/blob/main/assets/preview.png?raw=true)
### Key Features
- **Media Stream Capture**: Capture video streams from a webcam, screen, or specific applications.
- **Frame Analysis**: Use OpenAI's GPT-4 to analyze captured frames for text, objects, context, and other details.
- **Customizable Prompts**: Customize the prompt used for frame analysis.
- **API Integration**: Integrate with OpenAI's API for frame analysis.
## Project Structure
- `app.py`: The main server-side application code using Quart.
- `templates/index.html`: The HTML template for the web application.
- `static/script.js`: The client-side JavaScript for handling media streams and interaction with the backend.
## API Endpoints
- **`GET /`**: Serves the main web application.
- **`POST /process_frame`**: Processes a captured frame and returns the analysis result.
### `POST /process_frame`
- **Request Body**:
```json
{
"image": "data:image/jpeg;base64,<base64-encoded-image>",
"prompt": "Analyze this frame",
"api_key": "<OpenAI API Key>"
}
```
- **Response**:
```json
{
"response": "<Analysis result in markdown format>"
}
```
## Potential Uses
- **Remote Monitoring**: Capture and analyze video streams for remote monitoring applications.
- **Educational Purposes**: Use AI to analyze and summarize educational video content.
- **Content Creation**: Automate the analysis and summarization of video content for creators.
## Customization
- **Prompts**: Customize the analysis prompt via the settings panel in the web application.
- **Refresh Rate**: Adjust the frame capture interval through the settings panel.
- **API Key**: Configure the OpenAI API key via the settings panel.
## Deployment
1. **Clone the Repository**:
```bash
git clone https://github.com/ruvnet/ai-video.git
cd ai-video
```
2. **Install Dependencies**:
```bash
pip install -r requirements.txt
```
3. **Set Environment Variables**:
```bash
export OPENAI_API_KEY=<your_openai_api_key>
```
4. **Run the Application**:
```bash
python app.py
```
5. **Access the Application**:
Open your web browser and navigate to `http://localhost:5000`.
## `requirements.txt`
```plaintext
quart
opencv-python-headless
httpx
numpy
```
### API Endpoints
- **`GET /`**: Serves the main web application.
- **`POST /process_frame`**: Processes a captured frame and returns the analysis result.
### Customization
- Customize prompts and refresh rates via the settings panel in the web application.
- Configure the OpenAI API key via the settings panel.
## Contributing
Feel free to fork the repository and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.
## License
[MIT](LICENSE)