Thanks @Goran Cvijanovic I did see some interesting case studies on the website. Right now what we have quite a bit of documentation on related to AI is Documents->Vector Embeddings-> Vector Space and how they are retrieved and integrated into the LLM retrieval process for automated prompting. I am looking for some similar information on Documents -> ? -> Knowledge Base and how how the knowledge base relates to the retrieval process in LLM

Hey Draco, Sorry I was busy doing things not checking slack for some time. Regarding KG + LLM + Vector, we already shared some approaches with LlamaIndex on creating KG from unstructured data with LLM/models like Rebel ref: • https://docs.llamaindex.ai/en/stable/examples/index_structs/knowledge_graph/NebulaGraphKGIndexDemo.html#using-knowledge-graph-with-nebulagraphstore • https://bit.ly/graph-rag-workshop Also, we have some work that's not yet being published, called NebulaLLM(lib to help easily access KG during LLM agent/RAG pipeline), if you are interested we could book a time to talk about it 😄

that looks great. I will read up on it and follow up. Thanks