imbajin commented on issue #183: URL: https://github.com/apache/incubator-hugegraph-ai/issues/183#issuecomment-2690348133
> Also [@imbajin](https://github.com/imbajin?rgh-link-date=2025-02-28T07%3A26%3A17.000Z) sir just wanted to know , what is the actual requirement. > > * Is it direct prompt -->information > (where user just write a prompt, subtasks will be divided and agents gets created based on the knowledge graph structure) > * or user will have capability to create and orchestrate his own agents ( to extract specific information from graph) > > And also where we are currently ? Good question in fact, we need to provide both of these abilities at the same time, but with a **focus on the second point**. We can understand that the first one is mainly aimed at **novice users**(novice here means: people who are not completely unfamiliar with **property graphs**, and they don't expect a way where simply throwing a `text/PDF` can make everything go OK (similar to simple but casual extraction of RDF/triplets), and we need to simply support this case, but it is not the key (similarly, including visualization/UI/compatibility with different vector-DBs, etc., are not our focus) Our core focus is on devs with basic vector-db(vector-rag/naive/basic-rag) or Agent systems. Assuming they already have Vector-RAG, how can we better integrate GraphRAG to provide more operability and ease of orchestration? This is also why we provide separate `HTTP-API` layer encapsulation, which facilitates developers to call our core query functions directly. For example, suppose the user is already using `AutoGen` to orchestrate their Agent system, and now assuming that the data in the graph has been extracted (skipping the extraction step), how can they better and faster integrate it into their original system, while maintaining high performance and simplicity as much as possible They(Devs) can directly modify our pipeline/workflow code, instead of requiring us to provide a fixed "local/global" mode like Microsoft GraphRAG that is not easy to adjust -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
