AI Video Search Engine

Objectives

• Index videos by transcribing audio and extracting keyframe descriptions
• Generate semantic embeddings for text and visual content segments
• Store embeddings in a vector database for similarity search
• Support natural language search queries with ranked results
• Return results with timestamp-linked video previews

Hints

• Use OpenAI embeddings for both text transcripts and image descriptions
• Pinecone, Weaviate, or pgvector can serve as the vector store
• Chunk transcripts into overlapping segments for better retrieval

Resources

• platform.openai.com/docs/guides/embeddings
• docs.pinecone.io

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