Integrate Mixpeek Video Embedding Service

[esteininger]

Description

We should integrate the Mixpeek video embedding service into the multi-modal starter kit to enhance the video processing capabilities. This will allows us to generate embeddings for video chunks, which can be used for more advanced video analysis and search functionality.

Proposed Implementation

1. Add Mixpeek as a dependency to the project.

2. Create a new utility function in src/utils/ to handle video embedding:

   • Initialize the Mixpeek client with an API key (to be stored in .env).
   • Process video chunks using mixpeek.tools.video.process().
   • Generate embeddings for each chunk using mixpeek.embed.video().
   • Store the embeddings along with their corresponding time ranges.

3. Update the video processing pipeline to include the embedding step.

4. Modify the Tigris storage implementation to store the embeddings alongside the video data.

5. Update the .env.example file to include the Mixpeek API key.

6. Add documentation in the README about the new video embedding feature.

Tasks

• Add Mixpeek dependency
• Create video embedding utility function
• Integrate embedding into video processing pipeline
• Update Tigris storage to handle embeddings
• Update environment variable setup
• Update documentation

Additional Considerations

• We need to decide on the optimal chunk interval and resolution for our use case.
• Consider adding a configuration option to enable/disable video embedding.
• Evaluate the impact on processing time and storage requirements.
• Explore potential use cases for the embeddings (e.g., semantic search, scene detection).

Resources

• Mixpeek Documentation
• Sample Mixpeek Integration Code

Please comment on this issue if you have any questions or suggestions regarding the integration of Mixpeek video embedding.