Generate mock LLM response for testing
(self, prompt: str)
| 466 | return f"Error in LLM analysis: {error_msg}" |
| 467 | |
| 468 | def _generate_mock_response(self, prompt: str) -> str: |
| 469 | """Generate mock LLM response for testing""" |
| 470 | if "JSON format" in prompt and "file_type" in prompt: |
| 471 | # File analysis mock |
| 472 | return """ |
| 473 | { |
| 474 | "file_type": "Python module", |
| 475 | "main_functions": ["main_function", "helper_function"], |
| 476 | "key_concepts": ["data_processing", "algorithm"], |
| 477 | "dependencies": ["numpy", "pandas"], |
| 478 | "summary": "Mock analysis of code file functionality." |
| 479 | } |
| 480 | """ |
| 481 | elif "relationships" in prompt: |
| 482 | # Relationship analysis mock |
| 483 | return """ |
| 484 | { |
| 485 | "relationships": [ |
| 486 | { |
| 487 | "target_file_path": "src/core/mock.py", |
| 488 | "relationship_type": "partial_match", |
| 489 | "confidence_score": 0.8, |
| 490 | "helpful_aspects": ["algorithm implementation", "data structures"], |
| 491 | "potential_contributions": ["core functionality", "utility methods"], |
| 492 | "usage_suggestions": "Mock relationship suggestion for testing." |
| 493 | } |
| 494 | ] |
| 495 | } |
| 496 | """ |
| 497 | elif "relevant_files" in prompt: |
| 498 | # File filtering mock |
| 499 | return """ |
| 500 | { |
| 501 | "relevant_files": [ |
| 502 | { |
| 503 | "file_path": "mock_file.py", |
| 504 | "relevance_reason": "Mock relevance reason", |
| 505 | "confidence": 0.9, |
| 506 | "expected_contribution": "Mock contribution" |
| 507 | } |
| 508 | ], |
| 509 | "summary": { |
| 510 | "total_files_analyzed": "10", |
| 511 | "relevant_files_count": "1", |
| 512 | "filtering_strategy": "Mock filtering strategy" |
| 513 | } |
| 514 | } |
| 515 | """ |
| 516 | else: |
| 517 | return "Mock LLM response for testing purposes." |
| 518 | |
| 519 | def _save_debug_response(self, provider: str, prompt: str, response: str): |
| 520 | """Save LLM response for debugging""" |