| |
| |
| |
| from haystack.evaluation import EvaluationRunResult |
| import pytest |
|
|
|
|
| def test_init_results_evaluator(): |
| data = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [0.805466, 0.410251], "score": 0.58177975}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| _ = EvaluationRunResult("testing_pipeline_1", inputs=data["inputs"], results=data["metrics"]) |
|
|
| with pytest.raises(ValueError, match="No inputs provided"): |
| _ = EvaluationRunResult("testing_pipeline_1", inputs={}, results={}) |
|
|
| with pytest.raises(ValueError, match="Lengths of the inputs should be the same"): |
| _ = EvaluationRunResult( |
| "testing_pipeline_1", |
| inputs={"query_id": ["53c3b3e6", "something else"], "question": ["What is the capital of France?"]}, |
| results={"some": {"score": 0.1, "individual_scores": [0.378064, 0.534964]}}, |
| ) |
|
|
| with pytest.raises(ValueError, match="Aggregate score missing"): |
| _ = EvaluationRunResult( |
| "testing_pipeline_1", |
| inputs={ |
| "query_id": ["53c3b3e6", "something else"], |
| "question": ["What is the capital of France?", "another"], |
| }, |
| results={"some": {"individual_scores": [0.378064, 0.534964]}}, |
| ) |
|
|
| with pytest.raises(ValueError, match="Individual scores missing"): |
| _ = EvaluationRunResult( |
| "testing_pipeline_1", |
| inputs={ |
| "query_id": ["53c3b3e6", "something else"], |
| "question": ["What is the capital of France?", "another"], |
| }, |
| results={"some": {"score": 0.378064}}, |
| ) |
|
|
| with pytest.raises(ValueError, match="Length of individual scores .* should be the same as the inputs"): |
| _ = EvaluationRunResult( |
| "testing_pipeline_1", |
| inputs={ |
| "query_id": ["53c3b3e6", "something else"], |
| "question": ["What is the capital of France?", "another"], |
| }, |
| results={"some": {"score": 0.1, "individual_scores": [0.378064, 0.534964, 0.3]}}, |
| ) |
|
|
|
|
| def test_score_report(): |
| data = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [0.805466, 0.410251], "score": 0.58177975}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| result = EvaluationRunResult("testing_pipeline_1", inputs=data["inputs"], results=data["metrics"]) |
| report = result.score_report().to_json() |
|
|
| assert report == ( |
| '{"metrics":{"0":"reciprocal_rank","1":"single_hit","2":"multi_hit","3":"context_relevance",' |
| '"4":"faithfulness","5":"semantic_answer_similarity"},' |
| '"score":{"0":0.476932,"1":0.75,"2":0.46428375,"3":0.58177975,"4":0.40585375,"5":0.53757075}}' |
| ) |
|
|
|
|
| def test_to_pandas(): |
| data = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7", "53c3b3e6", "225f87f7"], |
| "question": [ |
| "What is the capital of France?", |
| "What is the capital of Spain?", |
| "What is the capital of Luxembourg?", |
| "What is the capital of Portugal?", |
| ], |
| "contexts": ["wiki_France", "wiki_Spain", "wiki_Luxembourg", "wiki_Portugal"], |
| "answer": ["Paris", "Madrid", "Luxembourg", "Lisbon"], |
| "predicted_answer": ["Paris", "Madrid", "Luxembourg", "Lisbon"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"score": 0.1, "individual_scores": [0.378064, 0.534964, 0.216058, 0.778642]}, |
| "single_hit": {"score": 0.1, "individual_scores": [1, 1, 0, 1]}, |
| "multi_hit": {"score": 0.1, "individual_scores": [0.706125, 0.454976, 0.445512, 0.250522]}, |
| "context_relevance": {"score": 0.1, "individual_scores": [0.805466, 0.410251, 0.750070, 0.361332]}, |
| "faithfulness": {"score": 0.1, "individual_scores": [0.135581, 0.695974, 0.749861, 0.041999]}, |
| "semantic_answer_similarity": {"score": 0.1, "individual_scores": [0.971241, 0.159320, 0.019722, 1]}, |
| }, |
| } |
|
|
| result = EvaluationRunResult("testing_pipeline_1", inputs=data["inputs"], results=data["metrics"]) |
| assert result.to_pandas().to_json() == ( |
| '{"query_id":{"0":"53c3b3e6","1":"225f87f7","2":"53c3b3e6","3":"225f87f7"},' |
| '"question":{"0":"What is the capital of France?","1":"What is the capital of Spain?",' |
| '"2":"What is the capital of Luxembourg?","3":"What is the capital of Portugal?"},' |
| '"contexts":{"0":"wiki_France","1":"wiki_Spain","2":"wiki_Luxembourg","3":"wiki_Portugal"},' |
| '"answer":{"0":"Paris","1":"Madrid","2":"Luxembourg","3":"Lisbon"},' |
| '"predicted_answer":{"0":"Paris","1":"Madrid","2":"Luxembourg","3":"Lisbon"},' |
| '"reciprocal_rank":{"0":0.378064,"1":0.534964,"2":0.216058,"3":0.778642},' |
| '"single_hit":{"0":1,"1":1,"2":0,"3":1},' |
| '"multi_hit":{"0":0.706125,"1":0.454976,"2":0.445512,"3":0.250522},' |
| '"context_relevance":{"0":0.805466,"1":0.410251,"2":0.75007,"3":0.361332},' |
| '"faithfulness":{"0":0.135581,"1":0.695974,"2":0.749861,"3":0.041999},' |
| '"semantic_answer_similarity":{"0":0.971241,"1":0.15932,"2":0.019722,"3":1.0}}' |
| ) |
|
|
|
|
| def test_comparative_individual_scores_report(): |
| data_1 = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [1, 1], "score": 1}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| data_2 = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [1, 1], "score": 1}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| result1 = EvaluationRunResult("testing_pipeline_1", inputs=data_1["inputs"], results=data_1["metrics"]) |
| result2 = EvaluationRunResult("testing_pipeline_2", inputs=data_2["inputs"], results=data_2["metrics"]) |
| results = result1.comparative_individual_scores_report(result2) |
|
|
| expected = { |
| "query_id": {0: "53c3b3e6", 1: "225f87f7"}, |
| "question": {0: "What is the capital of France?", 1: "What is the capital of Spain?"}, |
| "contexts": {0: "wiki_France", 1: "wiki_Spain"}, |
| "answer": {0: "Paris", 1: "Madrid"}, |
| "predicted_answer": {0: "Paris", 1: "Madrid"}, |
| "testing_pipeline_1_reciprocal_rank": {0: 0.378064, 1: 0.534964}, |
| "testing_pipeline_1_single_hit": {0: 1, 1: 1}, |
| "testing_pipeline_1_multi_hit": {0: 0.706125, 1: 0.454976}, |
| "testing_pipeline_1_context_relevance": {0: 1, 1: 1}, |
| "testing_pipeline_1_faithfulness": {0: 0.135581, 1: 0.695974}, |
| "testing_pipeline_1_semantic_answer_similarity": {0: 0.971241, 1: 0.15932}, |
| "testing_pipeline_2_reciprocal_rank": {0: 0.378064, 1: 0.534964}, |
| "testing_pipeline_2_single_hit": {0: 1, 1: 1}, |
| "testing_pipeline_2_multi_hit": {0: 0.706125, 1: 0.454976}, |
| "testing_pipeline_2_context_relevance": {0: 1, 1: 1}, |
| "testing_pipeline_2_faithfulness": {0: 0.135581, 1: 0.695974}, |
| "testing_pipeline_2_semantic_answer_similarity": {0: 0.971241, 1: 0.15932}, |
| } |
|
|
| assert expected == results.to_dict() |
|
|
|
|
| def test_comparative_individual_scores_report_keep_truth_answer_in_df(): |
| data_1 = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [1, 1], "score": 1}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| data_2 = { |
| "inputs": { |
| "query_id": ["53c3b3e6", "225f87f7"], |
| "question": ["What is the capital of France?", "What is the capital of Spain?"], |
| "contexts": ["wiki_France", "wiki_Spain"], |
| "answer": ["Paris", "Madrid"], |
| "predicted_answer": ["Paris", "Madrid"], |
| }, |
| "metrics": { |
| "reciprocal_rank": {"individual_scores": [0.378064, 0.534964], "score": 0.476932}, |
| "single_hit": {"individual_scores": [1, 1], "score": 0.75}, |
| "multi_hit": {"individual_scores": [0.706125, 0.454976], "score": 0.46428375}, |
| "context_relevance": {"individual_scores": [1, 1], "score": 1}, |
| "faithfulness": {"individual_scores": [0.135581, 0.695974], "score": 0.40585375}, |
| "semantic_answer_similarity": {"individual_scores": [0.971241, 0.159320], "score": 0.53757075}, |
| }, |
| } |
|
|
| result1 = EvaluationRunResult("testing_pipeline_1", inputs=data_1["inputs"], results=data_1["metrics"]) |
| result2 = EvaluationRunResult("testing_pipeline_2", inputs=data_2["inputs"], results=data_2["metrics"]) |
| results = result1.comparative_individual_scores_report(result2, keep_columns=["predicted_answer"]) |
|
|
| assert list(results.columns) == [ |
| "query_id", |
| "question", |
| "contexts", |
| "answer", |
| "testing_pipeline_1_predicted_answer", |
| "testing_pipeline_1_reciprocal_rank", |
| "testing_pipeline_1_single_hit", |
| "testing_pipeline_1_multi_hit", |
| "testing_pipeline_1_context_relevance", |
| "testing_pipeline_1_faithfulness", |
| "testing_pipeline_1_semantic_answer_similarity", |
| "testing_pipeline_2_predicted_answer", |
| "testing_pipeline_2_reciprocal_rank", |
| "testing_pipeline_2_single_hit", |
| "testing_pipeline_2_multi_hit", |
| "testing_pipeline_2_context_relevance", |
| "testing_pipeline_2_faithfulness", |
| "testing_pipeline_2_semantic_answer_similarity", |
| ] |
|
|
