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Implement Retrieval module (Read Path) for KM-RAG Architecture #48

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opened 2026-05-20 18:22:41 +00:00 by Antigravity · 0 comments
Antigravity commented 2026-05-20 18:22:41 +00:00
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We need to implement the KM-RAG Retrieval Engine (Read Path) to allow users to ask complex questions, retrieve relevant semantic contexts from Qdrant, expand context via Neo4j conceptual relationships, and synthesize a grounded response with proper citations using Google Gemini (via Microsoft.Extensions.AI).

Scope of Work

  • Define query schema and DTOs (GroundedResponseDto, CitationDto).
  • Implement AskQuestionAsync method on IKnowledgeService/KnowledgeService using Qdrant, Neo4j, PostgreSQL, and Google Gemini.
  • Expose MediatR handlers and endpoints (/api/knowledge/ask, /api/knowledge/search).
  • Build a dedicated Blazor UI page (/intelligence) for testing and global Q&A with rich, premium aesthetics and micro-animations.
  • Write robust unit tests.
We need to implement the KM-RAG Retrieval Engine (Read Path) to allow users to ask complex questions, retrieve relevant semantic contexts from Qdrant, expand context via Neo4j conceptual relationships, and synthesize a grounded response with proper citations using Google Gemini (via Microsoft.Extensions.AI). ### Scope of Work - Define query schema and DTOs (GroundedResponseDto, CitationDto). - Implement AskQuestionAsync method on IKnowledgeService/KnowledgeService using Qdrant, Neo4j, PostgreSQL, and Google Gemini. - Expose MediatR handlers and endpoints (/api/knowledge/ask, /api/knowledge/search). - Build a dedicated Blazor UI page (/intelligence) for testing and global Q&A with rich, premium aesthetics and micro-animations. - Write robust unit tests.
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Antigravity M.Wojtaszek mjasin (Marek Jaisński)
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Reference: mjasin/Nexus.Reader#48
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