feat(rag): implement KM-RAG retrieval read-path, API endpoints, global Q&A UI, and unit tests #49

2026-05-20T18:22:44Z

Antigravity commented

2026-05-20 18:22:44 +00:00

This Pull Request implements the complete Retrieval module (Read Path) for the Knowledge-Map RAG (KM-RAG) architecture within the NexusReader platform. It resolves all requirements for vector-based semantic search, Neo4j graph context expansion, structured grounding with Google Gemini, API/Wasm integration, and an interactive front-end global Q&A panel.

Resolves #48

🚀 Key Implementations

Grounded DTOs & Schema Definition
- Added GroundedResponseDto and CitationDto for strict JSON Schema matching with Gemini.
Core Service & Read Path Logic
- Implemented the robust 5-step pipeline in KnowledgeService.AskQuestionAsync:
  1. Embedding: Query vectorization using IEmbeddingGenerator.
  2. Semantic Search: Multi-tenant vector search with Qdrant, supporting scoping to a specific book or global search.
  3. Graph Expansion: Fetching connected concepts and parent relationships using Neo4j Cypher.
  4. Citation Hydration: Cross-referencing results with PostgreSQL to fetch book titles and accurate chapter citations.
  5. Grounded Generation: Strict structured generation via IChatClient (Gemini) preventing hallucinations and using citations.
CQRS & Endpoints
- Added AskLibraryQuestionQuery and its handler.
- Mapped /api/knowledge/ask and /api/knowledge/search endpoints inside Program.cs.
- Updated WasmKnowledgeService to support proxying retrieval requests.
Premium Blazor UI Panel
- Implemented /intelligence (Global AI Q&A) with a curated HSL palette, dark theme, smooth micro-animations, loading shimmers, and side-by-side citation cards.
- Registered the panel within the MainHubLayout sidebar.
Test Coverage
- Wrote comprehensive xUnit tests in QueryTests.cs using Moq and FluentAssertions to assert that handlers correctly validate input and interact with services.

🧪 Verification

Verified compilation and build gate successfully (dotnet build: 0 errors).
All 7 tests passed perfectly (dotnet test).

This Pull Request implements the complete **Retrieval module (Read Path)** for the Knowledge-Map RAG (KM-RAG) architecture within the NexusReader platform. It resolves all requirements for vector-based semantic search, Neo4j graph context expansion, structured grounding with Google Gemini, API/Wasm integration, and an interactive front-end global Q&A panel. Resolves #48 ### 🚀 Key Implementations 1. **Grounded DTOs & Schema Definition** - Added `GroundedResponseDto` and `CitationDto` for strict JSON Schema matching with Gemini. 2. **Core Service & Read Path Logic** - Implemented the robust **5-step pipeline** in `KnowledgeService.AskQuestionAsync`: 1. *Embedding*: Query vectorization using `IEmbeddingGenerator`. 2. *Semantic Search*: Multi-tenant vector search with Qdrant, supporting scoping to a specific book or global search. 3. *Graph Expansion*: Fetching connected concepts and parent relationships using Neo4j Cypher. 4. *Citation Hydration*: Cross-referencing results with PostgreSQL to fetch book titles and accurate chapter citations. 5. *Grounded Generation*: Strict structured generation via `IChatClient` (Gemini) preventing hallucinations and using citations. 3. **CQRS & Endpoints** - Added `AskLibraryQuestionQuery` and its handler. - Mapped `/api/knowledge/ask` and `/api/knowledge/search` endpoints inside `Program.cs`. - Updated `WasmKnowledgeService` to support proxying retrieval requests. 4. **Premium Blazor UI Panel** - Implemented `/intelligence` (Global AI Q&A) with a curated HSL palette, dark theme, smooth micro-animations, loading shimmers, and side-by-side citation cards. - Registered the panel within the `MainHubLayout` sidebar. 5. **Test Coverage** - Wrote comprehensive xUnit tests in `QueryTests.cs` using Moq and FluentAssertions to assert that handlers correctly validate input and interact with services. ### 🧪 Verification - Verified compilation and build gate successfully (`dotnet build`: 0 errors). - All 7 tests passed perfectly (`dotnet test`).

Antigravity added 3 commits 2026-05-20 18:22:44 +00:00

feat: complete KM-RAG polyglot ingestion pipeline migration 03bc649335

Merge remote-tracking branch 'origin/develop' into feature/km-rag-retrieval 0473103286

feat(rag): implement KM-RAG retrieval read-path, endpoints, query handlers, global Q&A panel, and unit tests c5102c1d14

mjasin approved these changes 2026-05-20 18:29:08 +00:00

mjasin merged commit cb4b7d0052 into develop

2026-05-20 18:29:16 +00:00

mjasin deleted branch feature/km-rag-retrieval

2026-05-20 18:29:16 +00:00

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