GitHub user Kryst4lDem0ni4s added a comment to the discussion: [Discussion] The selection of Agentic/Taskflow frame
Modifying and creating your own implementations of existing frameworks is quite impractical on such a scale, especially when your reasoning is for a small upgrade of performance optimisation. It's better to use existing libraries and the features they offer instead of creating something from scratch, otherwise it's a separate project altogether. As for dependency hell, it is definitely true that we'll have to spend some time initially to figure out compatibility between all the projects, but once the initial investment is cleared, we'll be able to achieve better productivity in the long run as the project scales. I firmly believe in micro-service-based architecture and loose coupling between different services, that's the same rationale here. It's easy to utilise the best of all their facilities (CrewAI, Agno, LlamaIndex and Pydantic) if we define the modularity from the get go. So I'd say that from here on out, it's not much of an issue about "which is the best?" Because we've already figured that part out. Now we need to focus on "which is best for which component?". More specifically, "What goes where?". Let's focus on defining a scalable architecture and not shy away from experimentation when we have such great resources available. And building something from scratch for minimal performance upgrades is not a wise investment unless we can come up with a way to achieve what Agno achieved (thousands of times better in performance). GitHub link: https://github.com/apache/incubator-hugegraph-ai/discussions/203#discussioncomment-12666611 ---- This is an automatically sent email for dev@hugegraph.apache.org. To unsubscribe, please send an email to: dev-unsubscr...@hugegraph.apache.org
