Fix issue 371 in AiDotNet

[ooples]

This commit addresses issue #371 by implementing comprehensive unit tests for all RAG retrieval strategies in src/RetrievalAugmentedGeneration/Retrievers/.

Test Coverage Includes:

• RetrieverBase (via VectorRetriever tests)
• DenseRetriever: Constructor validation, basic retrieval, semantic search
• VectorRetriever: Full coverage including query/topK validation, metadata filtering
• BM25Retriever: Keyword matching, BM25 scoring, parameter validation
• TFIDFRetriever: TF-IDF scoring, caching behavior, term frequency analysis
• HybridRetriever: Score fusion, weight balancing, dual strategy combination
• MultiQueryRetriever: Query expansion, score aggregation, multi-query logic
• MultiVectorRetriever: Vector aggregation methods (max/mean/weighted)
• ParentDocumentRetriever: Chunk/parent relationship, hierarchical retrieval
• ColBERTRetriever: Token-level interaction, parameter validation
• GraphRetriever: Entity extraction, relationship scoring, graph-based retrieval

Test Infrastructure:

• Created InMemoryDocumentStore for isolated testing
• Created StubEmbeddingModel for deterministic embeddings
• Test helpers for creating sample documents and data

All tests follow xUnit patterns and include:

• Constructor validation with null/invalid parameters
• Basic retrieval functionality
• TopK parameter enforcement
• Metadata filtering integration
• Empty query/document store handling
• Relevance score assignment and sorting
• Strategy-specific scoring behavior
• Edge cases and error conditions

Target: 80%+ code coverage for all retriever implementations

User Story / Context

• Reference: [US-XXX] (if applicable)
• Base branch: merge-dev2-to-master

Summary

• What changed and why (scoped strictly to the user story / PR intent)

Verification

• [ ] Builds succeed (scoped to changed projects)
• [ ] Unit tests pass locally
• [ ] Code coverage >= 90% for touched code
• [ ] Codecov upload succeeded (if token configured)
• [ ] TFM verification (net46, net6.0, net8.0) passes (if packaging)
• [ ] No unresolved Copilot comments on HEAD

Copilot Review Loop (Outcome-Based)

Record counts before/after your last push:

• Comments on HEAD BEFORE: [N]
• Comments on HEAD AFTER (60s): [M]
• Final HEAD SHA: [sha]

Files Modified

• [ ] List files changed (must align with scope)

Notes

• Any follow-ups, caveats, or migration details

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📥 Commits

Reviewing files that changed from the base of the PR and between f0a6a964020f5b2e571f158c26afd62225031674 and 32e9a86a48ca7d9a761f89b5f0bf166bac683496.

📒 Files selected for processing (9)

• commitlint.config.js (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/AdvancedRetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/BM25RetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/DenseRetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/HybridRetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/MultiQueryRetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/TFIDFRetrieverTests.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/TestHelpers.cs (1 hunks)
• tests/AiDotNet.Tests/UnitTests/RetrievalAugmentedGeneration/Retrievers/VectorRetrieverTests.cs (1 hunks)

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Summary by CodeRabbit

• Tests
  • Added extensive unit test coverage for retriever components in the Retrieval-Augmented Generation system.
  • Tests validate constructor validation, retrieval accuracy, relevance scoring, metadata filtering, and error handling across multiple retriever implementations.
  • Includes comprehensive edge-case coverage to ensure robust system behavior.

_{✏️ Tip: You can customize this high-level summary in your review settings.}

Walkthrough

This PR adds comprehensive unit test suites for seven retriever implementations in Retrieval-Augmented Generation, including Vector, Dense, Hybrid, BM25, TF-IDF, MultiQuery, and Advanced retrievers. Tests validate constructor preconditions, retrieval input handling, metadata filtering, relevance scoring, and edge cases. Supporting test infrastructure includes an in-memory document store and stub embedding model.

Changes

Cohort / File(s)	Summary
Vector-based Retriever Tests VectorRetrieverTests.cs, DenseRetrieverTests.cs, HybridRetrieverTests.cs	Tests for vector/embedding-based retrievers covering constructor validation, basic retrieval with empty/populated stores, topK limiting, relevance score sorting, metadata filtering, and semantic search capabilities.
Keyword-based Retriever Tests BM25RetrieverTests.cs, TFIDFRetrieverTests.cs	Tests for sparse/keyword retrievers validating constructor behavior, keyword matching, BM25/TF-IDF parameter variations, scoring dynamics, caching mechanisms, case-insensitive handling, and relevance sorting.
Advanced Retriever Tests AdvancedRetrieverTests.cs, MultiQueryRetrieverTests.cs	Tests for advanced retriever patterns including MultiVectorRetriever, ParentDocumentRetriever, ColBERTRetriever, GraphRetriever, and MultiQueryRetriever, covering score aggregation, entity extraction, query expansion, and cross-retriever composition.
Test Infrastructure TestHelpers.cs	Provides reusable test utilities: InMemoryDocumentStore<T> with similarity search and metadata filtering, StubEmbeddingModel<T> for deterministic embeddings, and helper methods to create sample documents and test fixtures.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~25 minutes

• TestHelpers.cs implementation: Review InMemoryDocumentStore cosine similarity calculations, filter matching logic, and embedding determinism
• Test pattern consistency: Verify similar test structure and assertions are applied consistently across all seven retriever test files
• Test data population: Ensure helper methods correctly seed document stores and embeddings for all test scenarios
• Float-type coverage: Verify cross-type tests (float vs. double) are properly implemented across retriever suites

Suggested labels

feature

Poem

🐰 Through vectors dense and keywords sparse, Tests now hop with measured grace, Each retriever gets its due, Hybrid paths, old and new. Eight new files, all trimmed and bright— Here's to coverage, clean and right! 🎯

Pre-merge checks and finishing touches

❌ Failed checks (1 warning, 1 inconclusive)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 1.61% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.
Title check	❓ Inconclusive	The title is vague and generic. It references 'issue 371' and 'AiDotNet' but does not describe the actual changes made, which are comprehensive unit tests for RAG retrieval strategies.	Replace with a more descriptive title that captures the main change, such as 'Add comprehensive unit tests for RAG retriever implementations' or 'Implement test coverage for all retriever strategies (issue #371)'.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Description check	✅ Passed	The description is well-structured and clearly related to the changeset, detailing comprehensive unit tests for RAG retrieval strategies with specific coverage areas, test infrastructure, and verification checkpoints.

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