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YAXB-ai / RAG_Chat

Chat application based on Retrieval Augmented Generation RAG, using LangChain, BeatifulSoup and Streamlit libraries on Mistral7B llm
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Refatoring code #2

Open Sekaran-ind opened 3 months ago

Sekaran-ind commented 3 months ago

Refactor code with the below principles

  1. Remove all unwanted imports
  2. make the code aligned properly with comments.
  3. create functions instead of inline coding approach
  4. Do not hard code the values, externalise them as config parameters in a file
  5. give proper file names for programs , e.g do not use Test_1.py etc.
  6. create a proper ReadMe file
  7. remove unwanted codes that are commented
  8. ChromaDB usage needs to be verified, very basic implementation has been used. Need to follow best practices
  9. Conversation memory is not propery used, need to check if the conversation maintains the previous conversation
  10. Sidebar behaviour is not consistent in the Chatbot UI,it appears the first time but not always. Maintain consistency
Sekaran-ind commented 3 months ago

Functionality of the RAG should include all the features mentioned in the below GitHub repository

https://github.com/langchain-ai/rag-from-scratch/blob/main/README.md

Videos in youtube explaind the different chapters

https://www.youtube.com/watch?v=wd7TZ4w1mSw&list=PLfaIDFEXuae2LXbO1_PKyVJiQ23ZztA0x

Sekaran-ind commented 3 months ago

Code Refactoring should follow the best practices outlined in the below 2 articles

a. https://dagster.io/blog/python-packages-primer-1 b. https://dagster.io/blog/python-packages-primer-2