Implement document chunk embedding and Chroma DB vector indexing for EpsteinFiles dataset
Browse filesThis commit introduces the vector embedding pipeline for the
EpsteinFiles dataset and integrates Chroma DB for persistent
vector storage.
Key updates:
- Processed and chunked cleaned dataset
- Generated embeddings using configured embedding model
- Indexed document chunks into Chroma DB
- Enabled persistent local vector storage
- Prepared dataset for retrieval-based querying
Note: This commit includes only the embedding and vector
database components.
- .gitattributes +1 -0
- chroma_db/94df74a4-1c32-402c-8823-5c6358144b66/data_level0.bin +3 -0
- chroma_db/94df74a4-1c32-402c-8823-5c6358144b66/header.bin +3 -0
- chroma_db/94df74a4-1c32-402c-8823-5c6358144b66/index_metadata.pickle +3 -0
- chroma_db/94df74a4-1c32-402c-8823-5c6358144b66/length.bin +3 -0
- chroma_db/94df74a4-1c32-402c-8823-5c6358144b66/link_lists.bin +3 -0
- chroma_db/chroma.sqlite3 +3 -0
.gitattributes
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# Video files - compressed
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chroma_db/chroma.sqlite3 filter=lfs diff=lfs merge=lfs -text
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