This project is a FastAPI application paired with a front-end interface that allows users to interact with video frames. It provides the ability to:

• Extract keyframes from a video when paused.
• Automatically generate a description of the frame.
• Ask questions about the frame and receive AI-generated answers.
• Read the generated descriptions and answers aloud using text-to-speech.
• Stop text-to-speech at any time with the Esc key.

1. Keyframe Extraction:

   • When the video is paused, the current frame is captured and analyzed.
   • A textual description of the frame is generated using OpenAI's GPT-4o Mini model.

2. Question Asking:

   • Users can ask a question about the paused frame by pressing the Q key.
   • The application sends the frame and the question to OpenAI and displays the response.

3. Text-to-Speech:

   • Descriptions and answers are read aloud to users.
   • Speech can be stopped at any time by pressing the Esc key.

4. Keyboard-Driven Interaction:

   • Q key: Ask a question about the paused frame.
   • Esc key: Stop any ongoing text-to-speech.

git clone https://github.com/your-username/your-repo.git
cd your-repo


2. Set Up a Virtual Environment
bash
Copy
Edit
python -m venv venv
```markdown
3. Install Dependencies

```bash
pip install -r requirements.txt

4. Create a .env File

In the project root directory, create a file named .env and add your OpenAI API key:

OPENAI_API_KEY=your_openai_api_key

5. Run the Application

Start the FastAPI server:

uvicorn app:app --reload

The application will be accessible at http://127.0.0.1:8000.

Navigate to http://127.0.0.1:8000 in your browser.