refactor: Async batch processing, limits, and configuration #80
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…figuring batching
|
Ideal |
danny-avila
reviewed
Oct 18, 2024
process_docs.py
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| start_time = time.perf_counter() | ||
| for i in range(0, len(docs), BATCH_SIZE): | ||
| batch = docs[i : min(i + BATCH_SIZE, len(docs))] | ||
| #logger.info(f"Sending batch {i} to {i+len(batch)} / {len(docs)}") |
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Added async api calls to embed (process) and add chunks (documents) to vector storage.
Added env variables:
MAX_CHUNKS,EMBEDDING_TIMEOUT,BATCH_SIZE, andCONCURRENT_LIMITto configure/limit batching api class. Description in Readme.Tested with PGVector with bedrock and
amazon.titan-embed-text-v2:0. Also rebuilt in docker successfully.BATCH_SIZEandCONCURRENT_LIMITaffecting process calls to embed correctlyMAX_CHUNKSworks as limit and throws exception if over. Correct default behavior of ignoringEMBEDDING_TIMEOUTworks within limit and throws exception if over