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<img width="1536" height="1024" alt="Atlas_Hero" src="https://github.com/user-attachments/assets/faf34217-83f1-4028-a4b3-daea5422470e" />
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---
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<details>
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<summary>🌐 Recognition & ecosystem integration</summary>
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<br>
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> As of 2026-03, the **WFGY RAG 16 Problem Map** line has been adopted or referenced by
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> **20+ frameworks, academic labs, and curated lists** in the RAG and agent ecosystem.
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> Most external references use the WFGY ProblemMap as a diagnostic layer for RAG / agent pipelines,
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> not the full WFGY product stack.
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> A smaller but growing set also uses **WFGY 3.0 · Singularity Demo** as a long-horizon TXT stress test.
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Some representative integrations:
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| Project | Stars | Segment | How it uses WFGY ProblemMap | Proof (PR / doc) |
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| --- | --- | --- | --- | --- |
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| [LlamaIndex](https://github.com/run-llama/llama_index) | [](https://github.com/run-llama/llama_index) | Mainstream RAG infra | Integrates the WFGY 16-problem RAG failure checklist into its official RAG troubleshooting docs as a structured failure mode reference. | [PR #20760](https://github.com/run-llama/llama_index/pull/20760) |
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| [RAGFlow](https://github.com/infiniflow/ragflow) | [](https://github.com/infiniflow/ragflow) | Mainstream RAG engine | Introduced a RAG failure modes checklist guide to the RAGFlow documentation via PR, adapted from the WFGY 16-problem failure map for step-by-step RAG pipeline diagnostics. | [PR #13204](https://github.com/infiniflow/ragflow/pull/13204) |
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| [FlashRAG (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/FlashRAG) | [](https://github.com/RUC-NLPIR/FlashRAG) | Academic lab / RAG research toolkit | Adapts the **WFGY ProblemMap** as a structured RAG failure checklist in its documentation. The 16-mode taxonomy is cited to support reproducible debugging and systematic failure-mode reasoning for RAG experiments. | [PR #224](https://github.com/RUC-NLPIR/FlashRAG/pull/224) |
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| [DeepAgent (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/DeepAgent) | [](https://github.com/RUC-NLPIR/DeepAgent) | Academic lab / agent research | Adds a **multi-tool agent failure modes troubleshooting note** inspired by WFGY-style debugging concepts for diagnosing tool selection loops, tool misuse, and multi-tool workflow failures in agent pipelines. | [PR #15](https://github.com/RUC-NLPIR/DeepAgent/pull/15#issuecomment-4020600680) |
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| [ToolUniverse (Harvard MIMS Lab)](https://github.com/mims-harvard/ToolUniverse) | [](https://github.com/mims-harvard/ToolUniverse) | Academic lab / tools | Provides a `WFGY_triage_llm_rag_failure` tool that wraps the 16 mode map for incident triage. | [PR #75](https://github.com/mims-harvard/ToolUniverse/pull/75) |
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| [Rankify (University of Innsbruck)](https://github.com/DataScienceUIBK/Rankify) | [](https://github.com/DataScienceUIBK/Rankify) | Academic lab / system | Uses the 16 failure patterns in RAG and re-ranking troubleshooting docs. | [PR #76](https://github.com/DataScienceUIBK/Rankify/pull/76) |
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| [Multimodal RAG Survey (QCRI LLM Lab)](https://github.com/llm-lab-org/Multimodal-RAG-Survey) | [](https://github.com/llm-lab-org/Multimodal-RAG-Survey) | Academic lab / survey | Cites WFGY as a practical diagnostic resource for multimodal RAG. | [PR #4](https://github.com/llm-lab-org/Multimodal-RAG-Survey/pull/4) |
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| [LightAgent](https://github.com/wanxingai/LightAgent) | [](https://github.com/wanxingai/LightAgent) | Agent framework | Incorporates WFGY ProblemMap concepts into its documentation via a **Multi-agent troubleshooting (failure map)** section, providing a structured symptom → failure-mode → debugging checklist for diagnosing role drift, cross-agent memory issues, and coordination failures in multi-agent systems. | [PR #24](https://github.com/wanxingai/LightAgent/pull/24#event-23265428525) |
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For the complete 20+ project list (frameworks, benchmarks, curated lists), see the 👉 **[WFGY Recognition Map](https://github.com/onestardao/WFGY/blob/main/recognition/README.md)**
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> If your project uses the WFGY ProblemMap and you would like to be listed,
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> feel free to open an issue or pull request in this repository.
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---
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</details>
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Modern AI systems rarely fail in one clean way.
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