GitHub user chiruu12 added a comment to the discussion: [Discussion] The selection of Agentic/Taskflow frame
I believe for our use case we will have to train to model to also get us the text-to-cypher? As we wont know what kind of input the user is going to give us so for that we will have to fine tune a model for the same as the agent might need to write the cypher query on it's own? > Hey [@imbajin](https://github.com/imbajin) I was working with agentic graph > RAG recently. The project aimed at Document QnA from a story book. It > required Agentic graph-RAG approach as in a story, different characters can > have different relationships with each other. Also different incidents are > linked to each other. So, here agentic graph-RAG worked well if someone asks > deep questions from story. So i made graph where centre node was book --> > first level nodes were chunks (each chapter of that book) --> second level > nodes were atomic_facts from that chunk--> final level nodes were characters. > Same characters from different atomic_facts were connected (so as to know > that character was present in which parts of the story). Also different > characters were connected to each other having some relationships. > > So for finding the answer of user's question, I used LANGGRAPH. It was really > lightweight , Fast and simple to implement it. > > There were agents - > > * character finder (to find all characters, user's question contains) > * atomic fact finder ( worked at finding the relevant atomic facts for each > character, according to user query. Using similarity search) > * information validator (checked if information is enough) > * atomic fact extractor (if information is not enough, then extract the > nearby atomic fact, or nearby events in that story) > * final composer (compose final answer using extracted information and user > query. > > It was a fixed agentic system, worked at graphs of one kind only > > I have a question, regarding what is the requirement ? Do we need to create a > Interface, where user can create his own agentic system for his Graph , just > using drag-drop or prompts (without code) If yes, then using LANGGRAPH or > completely doing it manually would be the best approach, because there will > be transparency , and user would know what is happening. Using CrewAI would > not be a good idea , as there we don't know what is happening under the hood. > > Here is the project :- https://github.com/Aryankb/DOC_QNA GitHub link: https://github.com/apache/incubator-hugegraph-ai/discussions/203#discussioncomment-12666595 ---- This is an automatically sent email for dev@hugegraph.apache.org. To unsubscribe, please send an email to: dev-unsubscr...@hugegraph.apache.org
