feat(iit-manager): Integrate Dify knowledge base for hybrid retrieval
Completed features: - Created Dify dataset (Dify_test0102) with 2 processed documents - Linked test0102 project with Dify dataset ID - Extended intent detection to recognize query_protocol intent - Implemented queryDifyKnowledge method (semantic search Top 5) - Integrated hybrid retrieval (REDCap data + Dify documents) - Fixed AI hallucination bugs (intent detection + API field path) - Developed debugging scripts - Completed end-to-end testing (5 scenarios passed) - Generated comprehensive documentation (600+ lines) - Updated development plans and module status Technical highlights: - Single project single knowledge base architecture - Smart routing based on user intent - Prevent AI hallucination by injecting real data/documents - Session memory for multi-turn conversations - Reused LLMFactory for DeepSeek-V3 integration Bug fixes: - Fixed intent detection missing keywords - Fixed Dify API response field path error Testing: All scenarios verified in WeChat production environment Status: Fully tested and deployed
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@@ -391,5 +391,6 @@ curl http://你的SAE地址:3001/health
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@@ -723,5 +723,6 @@ const job = await queue.getJob(jobId);
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@@ -490,5 +490,6 @@ processLiteraturesInBackground(task.id, projectId, testLiteratures);
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@@ -967,5 +967,6 @@ ROI = (¥22,556 - ¥144) / ¥144 × 100% = 15,564%
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