Hybrid search pipeline with OpenAI embeddings and Cohere reranking#15
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Chaithra-S-Nayak-2 wants to merge 2 commits intomainfrom
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Hybrid search pipeline with OpenAI embeddings and Cohere reranking#15Chaithra-S-Nayak-2 wants to merge 2 commits intomainfrom
Chaithra-S-Nayak-2 wants to merge 2 commits intomainfrom
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- Introduced `embed_corpus.py` for generating document embeddings using OpenAI's text-embedding-3-large model. - Added `hybrid_search.py` for implementing a hybrid search pipeline combining BM25 and dense embeddings. - Updated `.gitignore` to exclude additional cache and binary files. - Included new dependencies in `requirements.txt` for rank-bm25 and cohere integration.
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hey @Chaithra-S-Nayak-2 can you please share your linkedIn profile we're going to post about winners soon! |
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sure, here is my linkedIn profile : https://www.linkedin.com/in/chaithra-s-nayak/ |
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hey @Chaithra-S-Nayak-2 can you please share your linkedIn profile we're going to post about winners soon! |
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Overview
Hybrid retrieval pipeline for the DevRev Search challenge.
Pipeline
Dense (OpenAI text-embedding-3-large, 3072-dim) + BM25 + HyDE + Multi-Query → Weighted RRF (BM25 2x weight) → Article-sibling expansion → Cohere Rerank v3.5 (top-200 candidates)
System Details
Work item: https://app.devrev.ai/devrev/works/ISS-269621/