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title: MCP Video Analysis with Llama 3 | |
emoji: π₯ | |
colorFrom: purple | |
colorTo: blue | |
sdk: gradio | |
sdk_version: 5.33.1 | |
app_file: app.py | |
pinned: false | |
license: mit | |
short_description: AI-powered video analysis with Llama 3 and Modal | |
# π₯ MCP Video Analysis with Llama 3 | |
This application provides comprehensive video analysis using the Model Context Protocol (MCP) to integrate multiple AI technologies: | |
## π§ Technology Stack | |
- **Modal Backend**: Scalable cloud compute for video processing | |
- **Whisper**: Speech-to-text transcription | |
- **Computer Vision Models**: Object detection, action recognition, and captioning | |
- **Meta Llama 3**: Advanced AI for intelligent content analysis, hosted on Modal | |
- **MCP Protocol**: Model Context Protocol for seamless integration | |
## π― Features | |
- **Transcription**: Extract spoken content from videos | |
- **Visual Analysis**: Identify objects, actions, and scenes | |
- **Content Understanding**: AI-powered insights and summaries | |
- **Custom Queries**: Ask specific questions about video content | |
## π Usage | |
1. Enter a video URL (YouTube or direct link) | |
2. Optionally ask a specific question | |
3. Click "Analyze Video" to get comprehensive insights | |
4. Review both Llama 3's intelligent analysis and raw data | |
## π Environment Variables Required | |
- `MODAL_LLAMA3_ENDPOINT_URL`: The URL for the deployed Llama 3 Modal service. | |
- `MODAL_VIDEO_ANALYSIS_ENDPOINT_URL`: The URL for the video processing Modal service (optional, has a default value). | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |