Use Case

Use LangChain to Create Q&A Application on Sravz Financial Data

Session 1

Dataflow Diagram

Topics

• Overview of the architecture
• High-level description of LangChain - Loaders, Tool, Agent, LLM
• Perform sample queries

Video explanation of the code

Source Code

Session 2

Dataflow Diagram

Topics

• 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

Video explanation of the code

Source Code

References

• https://github.com/IvanReznikov/DataVerse/blob/main/Onepagers/pdfs/langchain.pdf
• https://www.kdnuggets.com/wp-content/uploads/LangChain_Cheat_Sheet_KDnuggets.pdf
• https://github.com/ronidas39/LLMtutorial/tree/main
• https://gist.github.com/sravzpublic/e22aeff797aaa110c790b33773908744