Python-LLM - Session 2 - LangChain - Cost Improvement - Vector embeddings - ChromaDB
ฝัง
- เผยแพร่เมื่อ 25 ส.ค. 2024
- Use Case
Use LangChain to Create Q&A Application on Sravz Financial Data
Session 2
- Query cost improvements by using vector embeddings and similarity search
- RecursiveJsonSplitter to split large JSON file
- Use HuggingFace all-MiniLM-L6-v2 to create vector embeddings
- Use ChromaDB to store and query vector embeddings
- Extend JSONToolKit used by JSON Agent
- Perform sample queries and analyze cost
Documentation Link: docs.sravz.com...
Code: gist.github.co...
Video Explanation: • Python-LLM - Session 2...
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