Basic RAG method is based on similarity search of vectors and hence most of the times fails to capture the overall syntax of the text presented to it, especially understanding it at higher level. To solve this problem, Knowledge Graph based RAG has been introduced, and Microsoft's GRAPHRAG seems to be a gamechanger, which takes it even further by capturing the entities and their relationship at a very deeperlevel.
This Repository consists of 2 notebooks which compare the results of knowledge graphs generated by GRAPHRAG and simple LLM based model.
Please run the following command to install required dependencies:
pip install -m requirements.txt
NOTE: Open-AI subscription will be required to run GRAPHRAG project. I have used my Azure based subscription.
Some of the commands specific to GRAPHRAG in this repo has to be run in terminal window and has been mentioned explictly.
Explain how others can contribute to the repository. Include guidelines for submitting issues or pull requests.
https://microsoft.github.io/graphrag/posts/get_started/ Prompt Engineering YouTube Channel