GitHub user imbajin added a comment to the discussion: [Discussion] The selection of Agentic/Taskflow frame
> So summing it up here is the proposed architecture, kept simple: > > > Base Layer (Agno) > > Handle high-frequency L1 queries through optimized parallel execution > > Implement Gremlin-Cypher transpiler for hybrid query support > > Orchestration Layer (CrewAI) > > Manage complex workflows using dynamic intent classification > > Integrate with HugeGraph's priority queue system > > Validation Layer (Pydantic-AI) > > Enforce schema consistency across all graph operations > > Provide developer-friendly type hints > > Retrieval Enhancement (LlamaIndex) > > Implement recursive retrieval with tiered caching > > Integrate with HugeGraph's OLAP engine > > My rationale and research summarized: Agno delivers performance gains for > core operations while maintaining lower memory usage CrewAI's workflow engine > reduces development time for complex agent interactions compared to manual > implementations Hybrid model achieves a much higher fault recovery through > layered fallback mechanisms > > This proposed architecture is based off of what I saw on the apache's jira, > where the required architecture was provided for the upcoming months of > development. > > I also emailed you additional insights for the architecture, please do check > ( > [@imbajin](https://github.com/imbajin?rgh-link-date=2025-03-01T06%3A01%3A39.000Z) > ) @Kryst4lDem0ni4s Thanks for ur graph, and I have fixed the mermaid UI: <img width="512" alt="Image" src="https://github.com/user-attachments/assets/d487762d-3aa1-457d-869a-46561d7ef38e"; /> And some comment about the graph: <img width="552" alt="Image" src="https://github.com/user-attachments/assets/ae555a2c-32b2-4a2d-b322-282565877f99"; /> As I mentioned above, it is entirely feasible to mix the strengths of multiple frameworks, but we are unlikely to directly introduce the entire framework (such as `pip install xxx`). Instead, we should choose the source code that can be extracted separately and integrate it directly into our tool (of course, we need to follow ASF's reference specifications). If that feature is bundled with multiple frameworks and difficult to separate separately, we may need to evaluate its importance. We are likely to first introduce a relatively balanced framework and integrate the good aspects of other designs for transformation. This is currently my thought GitHub link: https://github.com/apache/incubator-hugegraph-ai/discussions/203#discussioncomment-12666617 ---- This is an automatically sent email for dev@hugegraph.apache.org. To unsubscribe, please send an email to: dev-unsubscr...@hugegraph.apache.org
