break tests into separate files; test 0 results

tests/integration/test_utils.py

@@ -0,0 +1,60 @@
+import inspect
+from typing import List, Callable
+from src.text_generation.domain.semantic_similarity_result import SemanticSimilarityResult
+from src.text_generation.domain.text_generation_completion_result import TextGenerationCompletionResult
+from src.text_generation.services.logging.test_run_logging_service import TestRunLoggingService
+from src.text_generation.services.nlp.abstract_text_generation_completion_service import AbstractTextGenerationCompletionService
+
+
+def run_prompt_analysis_test(
+    test_id: int,
+    text_generation_completion_service: AbstractTextGenerationCompletionService,
+    semantic_similarity_service,
+    prompts: List,
+    comparison_texts: List,
+    service_configurator: Callable,
+    max_prompts: int = 100
+) -> List[SemanticSimilarityResult]:
+    """
+    Common utility for running prompt analysis tests.
+    
+    Args:
+        test_id: Unique identifier for the test
+        text_generation_completion_service: Service for text generation
+        semantic_similarity_service: Service for semantic analysis
+        prompts: List of prompts to test
+        comparison_texts: Reference texts for similarity comparison
+        service_configurator: Function that configures the text generation service
+        max_prompts: Maximum number of prompts to process (default: 100)
+    
+    Returns:
+        List of SemanticSimilarityResult objects
+    """
+    semantic_similarity_service.use_comparison_texts(comparison_texts)
+    results = []
+    
+    for i, prompt in enumerate(prompts[:max_prompts], 1):
+        # Configure the service using the provided configurator function
+        configured_service = service_configurator(text_generation_completion_service)
+        
+        completion_result: TextGenerationCompletionResult = configured_service.invoke(user_prompt=prompt)
+        result: SemanticSimilarityResult = semantic_similarity_service.analyze(completion_result.final)
+        
+        print(f'{i}/{len(prompts)} Max Score: {result.max}')
+        print(f'{i}/{len(prompts)} Avg Score: {result.mean}')
+        
+        TestRunLoggingService(test_id=test_id).log_results(
+            id=inspect.currentframe().f_back.f_code.co_name,
+            prompt=prompt,
+            completion=completion_result.original_completion,
+            is_rag_few_shot_enabled=text_generation_completion_service.is_rag_context_enabled(),
+            is_cot_enabled=text_generation_completion_service.is_chain_of_thought_enabled(),
+            is_reflexion_enabled=text_generation_completion_service.is_reflexion_enabled(),
+            scores=result.scores,
+            mean=result.mean,
+            max=result.max
+        )
+        
+        results.append(result)
+    
+    return results