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| from unittest.mock import Mock, patch | |
| from backend.services.rag_engine import RAGEngine | |
| from backend.services.rag_graph import DocuMindRAGGraph | |
| # Confidence scoring tests | |
| def test_confidence_is_low_when_no_chunks(): | |
| assert RAGEngine._assess_confidence([]) == "LOW" | |
| def test_confidence_is_high_for_strong_similarity(): | |
| chunks = [ | |
| {"similarity": 0.90}, | |
| {"similarity": 0.85}, | |
| ] | |
| assert RAGEngine._assess_confidence(chunks) == "HIGH" | |
| def test_confidence_is_medium_for_moderate_similarity(): | |
| chunks = [ | |
| {"similarity": 0.55}, | |
| {"similarity": 0.50}, | |
| ] | |
| assert RAGEngine._assess_confidence(chunks) == "MEDIUM" | |
| def test_confidence_is_low_for_weak_similarity(): | |
| chunks = [ | |
| {"similarity": 0.20}, | |
| {"similarity": 0.15}, | |
| ] | |
| assert RAGEngine._assess_confidence(chunks) == "LOW" | |
| # RAG engine adapter tests | |
| def test_query_adapts_graph_result(): | |
| fake_graph = Mock() | |
| fake_graph.invoke.return_value = { | |
| "answer": "Python and SQL are listed.", | |
| "chunks": [ | |
| { | |
| "doc_name": "Resume.pdf", | |
| "page_number": 1, | |
| "text": "Technical skills: Python and SQL.", | |
| "similarity": 0.85, | |
| } | |
| ], | |
| "is_grounded": True, | |
| "error": None, | |
| } | |
| with patch( | |
| "backend.services.rag_engine.get_rag_graph", | |
| return_value=fake_graph, | |
| ): | |
| engine = RAGEngine() | |
| result = engine.query("Which skills are listed?") | |
| assert result.answer == "Python and SQL are listed." | |
| assert result.query == "Which skills are listed?" | |
| assert result.chunks_retrieved == 1 | |
| assert result.sources[0].doc_name == "Resume.pdf" | |
| assert result.sources[0].page_number == 1 | |
| assert result.is_grounded is True | |
| assert result.confidence == "HIGH" | |
| fake_graph.invoke.assert_called_once() | |
| def test_query_handles_empty_graph_result(): | |
| fake_graph = Mock() | |
| fake_graph.invoke.return_value = { | |
| "answer": "", | |
| "chunks": [], | |
| "is_grounded": False, | |
| "error": None, | |
| } | |
| with patch( | |
| "backend.services.rag_engine.get_rag_graph", | |
| return_value=fake_graph, | |
| ): | |
| engine = RAGEngine() | |
| result = engine.query("What is in this document?") | |
| assert result.chunks_retrieved == 0 | |
| assert result.is_grounded is False | |
| assert result.confidence == "LOW" | |
| assert "couldn't find relevant information" in result.answer | |
| # LangGraph retrieval-routing tests | |
| def test_retrieval_gate_finishes_when_no_chunks(): | |
| assert DocuMindRAGGraph.route_after_retrieval( | |
| {"chunks": []} | |
| ) == "finish" | |
| def test_retrieval_gate_finishes_for_weak_evidence(): | |
| state = { | |
| "chunks": [ | |
| {"similarity": 0.10}, | |
| {"similarity": 0.15}, | |
| ] | |
| } | |
| assert DocuMindRAGGraph.route_after_retrieval(state) == "finish" | |
| def test_retrieval_gate_generates_for_sufficient_similarity(): | |
| state = { | |
| "chunks": [ | |
| {"similarity": 0.35}, | |
| {"similarity": 0.25}, | |
| ] | |
| } | |
| assert DocuMindRAGGraph.route_after_retrieval(state) == "generate" | |
| def test_refusal_is_never_grounded(): | |
| graph = object.__new__(DocuMindRAGGraph) | |
| result = graph.check_evidence({ | |
| "answer": "The document does not contain that information.", | |
| "chunks": [{"text": "The document contains many important facts."}], | |
| }) | |
| assert result["is_grounded"] is False | |