[Question]: Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

[lhxxrds]

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RAGFlow workspace code commit ID

2345678

RAGFlow image version

v0.22.0

Other environment information

Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

Actual behavior

Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

Expected behavior

Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

Steps to reproduce

Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

Additional information

Does RAGFlow (v0.22.0) support accessing the global index and using the recall-enhanced RAPTOR strategy in RAGFlow applications via HTTP requests, i.e., using RAGFlow solely as a knowledge base and accessing it from Dify?

[dosubot[bot]]

Yes, RAGFlow v0.22.0 supports accessing the global index and using the recall-enhanced RAPTOR strategy via HTTP requests, making it possible to use RAGFlow solely as a knowledge base and access it from Dify.

You can manage datasets, enable RAPTOR (including recall enhancements) in the parser_config, and construct or trace RAPTOR indexes using endpoints like /api/v1/datasets, /api/v1/datasets/{dataset_id}/run_raptor, and /api/v1/datasets/{dataset_id}/trace_raptor (API reference).

For retrieval, RAGFlow exposes both a general retrieval endpoint (/api/v1/retrieval) and a Dify-compatible endpoint (/dify/retrieval). The Dify endpoint accepts parameters like knowledge_id, query, use_kg, retrieval_setting, and metadata_condition, returning results in a format suitable for Dify integration (API code). All retrieval strategies and enhancements configured in RAGFlow (including RAPTOR) are respected when accessed via these APIs.

To use RAGFlow as a knowledge base for Dify, deploy a self-hosted RAGFlow instance, connect Dify to the /dify/retrieval endpoint, and provide the appropriate API token and knowledge base ID. Note that some features (like tag referencing) may not be fully supported in Dify integration (integration discussion).

Let me know if you need example API calls or more details on configuring RAPTOR or Dify integration.

To reply, just mention @dosu.

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[KevinHuSh]

Yes, it does support.

[lhxxrds]

After I uninstalled my previous version of ragflow and upgraded to the latest ragflow version v0.22.1, I kept reporting this error 502. Then:：DB is not ready yet: (1146, "Table 'rag_flow.sync_logs' doesn't exist")mention @dosu. @KevinHuSh

[KevinHuSh]

It's warning message which is not important.

[Magicbook1108]

Since there has been no further activity for over three weeks, we will proceed to close this issue. If the problem persists or you have additional questions, please feel free to reopen the issue or create a new one. We’re happy to assist anytime.