Aryankb commented on issue #183:
URL:
https://github.com/apache/incubator-hugegraph-ai/issues/183#issuecomment-2689857543
Hey @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.
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