NexQuant

mirror of https://github.com/NicolasBohn/NexQuant.git synced 2026-08-09 13:00:56 +00:00

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T

Xu Yang 4ae7e6db19 feat: Initial version if Graph RAG in KAGGLE scenario (#301 )

* Initial version if Graph RAG in KAGGLE scenario

* fix CI

* fix a small bug

* fix CI

* fix CI

* fix CI

2024-09-23 19:32:01 +08:00

extract_knowledge.py

feat: Added support for loading and storing RAG in Kaggle scenarios. (#269 )

2024-09-19 11:33:33 +08:00

graph.py

feat: Initial version if Graph RAG in KAGGLE scenario (#301 )

2024-09-23 19:32:01 +08:00

prompts.yaml

feat: Initial version if Graph RAG in KAGGLE scenario (#301 )

2024-09-23 19:32:01 +08:00

README.md

feat: Added support for loading and storing RAG in Kaggle scenarios. (#269 )

2024-09-19 11:33:33 +08:00

vector_base.py

feat: Initial version if Graph RAG in KAGGLE scenario (#301 )

2024-09-23 19:32:01 +08:00

README.md

Usage

This folder implements a knowledge base using RAG based on Kaggle competitions. It allows you to store Kaggle competition experiences into the knowledge base, as well as store experimental experiences from RD-Agent.

First, generate a knowledge base (in JSON format) by running the main function in extract_knowledge.py.
Then, create a vector base in vector_base.py and save it.
Finally, add the field KG_RAG_PATH="xxx.pkl" (the path to the saved vector base) in your .env file.