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Build HybridOrchestrator

Objective: Implement the main orchestration logic for hybrid retrieval.

Description: Create query routing, result fusion, and ranking logic for the HybridOrchestrator.

Dependencies: Complete VectorStore Implementation, Implement GraphStore with Neo4j

Details:

  • Develop query routing logic to select appropriate retrieval strategies.
  • Implement result fusion and ranking algorithms.
  • Ensure modular and extensible orchestration code.

Status: Done

Test Strategy:

pytest tests/unit/test_hybrid_orchestrator.py

Verify all tests pass and orchestration logic works as expected.

HybridOrchestrator Architecture​

flowchart TD
  Q[Query Input] --> QR[Query Routing]
  QR --> VS[VectorStore]
  QR --> GS[GraphStore]
  VS --> RF[Result Fusion]
  GS --> RF
  RF --> RK[Ranking]
  RK --> O[Orchestrator Output]

Explanatory Notes​

  • Orchestration Logic: Coordinates multiple retrieval strategies for optimal results.
  • Result Fusion: Combines outputs from vector and graph stores for comprehensive answers.
  • Ranking: Orders results by relevance, improving user experience.
  • Best Practices:
    • Modularize orchestration code for easy extension.
    • Log intermediate results for debugging.
    • Test with diverse queries and data.
  • Debugging:
    • Use unit and integration tests to validate logic.
    • Analyze logs for unexpected routing or ranking behavior.