kalviumcommunity / kalviumcommunity/InsuranceGuide
Build vector embedding and retrieval pipeline
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data-pipeline
- Dominant language
- Python
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Description
## Why
The RAG application requires semantic search to retrieve relevant insurance policy information. Embeddings must be generated and stored in a vector database for efficient retrieval.
## Done When
- Embeddings are generated.
- Vector database is configured.
- Documents are indexed.
- Semantic similarity search returns relevant chunks.
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