Delete tests/test_integration.py

tests/test_integration.py

@@ -1,270 +0,0 @@
-import pytest
-
-class TestIntegration:
-    """Integration tests for the complete workflow"""
-    
-    def test_complete_workflow_text_input(self, sample_medical_text):
-        """Test complete workflow from text input to SOAP output"""
-        def mock_complete_workflow(medical_text):
-            # Step 1: Validate input
-            if not medical_text.strip():
-                return "❌ No input provided"
-            
-            # Step 2: Process text (mock preprocessing)
-            processed_text = medical_text.strip()
-            
-            # Step 3: Generate SOAP (mocked)
-            soap_sections = [
-                "SUBJECTIVE:",
-                "Patient reports chest pain for 2 hours.",
-                "",
-                "OBJECTIVE:", 
-                "Vital signs show elevated blood pressure.",
-                "",
-                "ASSESSMENT:",
-                "Acute chest pain, rule out cardiac causes.",
-                "",
-                "PLAN:",
-                "Order EKG and cardiac enzymes."
-            ]
-            
-            # Step 4: Format output
-            result = "\n".join(soap_sections)
-            result += f"\n\n--- Processing Summary ---"
-            result += f"\nProcessed {len(medical_text)} characters of medical text."
-            result += f"\nGenerated SOAP note with {len(soap_sections)} sections."
-            
-            return result
-        
-        result = mock_complete_workflow(sample_medical_text)
-        
-        assert "SUBJECTIVE:" in result
-        assert "OBJECTIVE:" in result
-        assert "ASSESSMENT:" in result
-        assert "PLAN:" in result
-        assert "Processing Summary" in result
-        assert "characters of medical text" in result
-
-    def test_workflow_with_image_and_text(self, sample_medical_text, sample_image):
-        """Test workflow with both image and text input"""
-        def mock_workflow_with_image(text_input, image_input):
-            combined_text = text_input or ""
-            
-            if image_input is not None:
-                # Mock OCR processing
-                ocr_text = "Additional findings: Patient appears anxious, diaphoretic"
-                if combined_text:
-                    combined_text += f"\n\n--- Extracted from image ---\n{ocr_text}"
-                else:
-                    combined_text = ocr_text
-            
-            if not combined_text:
-                return "❌ No input provided"
-            
-            # Mock SOAP generation
-            sections = ["SUBJECTIVE", "OBJECTIVE", "ASSESSMENT", "PLAN"]
-            soap_content = []
-            
-            for section in sections:
-                soap_content.append(f"{section}:")
-                soap_content.append(f"Content for {section.lower()} section")
-                soap_content.append("")
-            
-            result = "\n".join(soap_content)
-            result += f"\n--- Workflow Summary ---"
-            result += f"\nCombined input: {len(combined_text)} characters"
-            result += f"\nImage processing: {'Yes' if image_input else 'No'}"
-            
-            return result
-        
-        result = mock_workflow_with_image(sample_medical_text, sample_image)
-        assert "SUBJECTIVE:" in result
-        assert "OBJECTIVE:" in result
-        assert "ASSESSMENT:" in result
-        assert "PLAN:" in result
-        assert "Workflow Summary" in result
-        assert "Image processing: Yes" in result
-
-    def test_error_recovery_workflow(self):
-        """Test workflow error handling and recovery"""
-        def mock_error_recovery_workflow(input_data, simulate_error=False):
-            try:
-                if simulate_error:
-                    raise Exception("Simulated processing error")
-                
-                if not input_data:
-                    return "❌ No input provided"
-                
-                # Simulate successful processing
-                return "✅ SOAP note generated successfully"
-                
-            except Exception as e:
-                # Error recovery
-                error_msg = f"❌ Error occurred: {str(e)}"
-                recovery_msg = "\n💡 Please try again with different input or check your image quality."
-                return error_msg + recovery_msg
-        
-        # Test normal operation
-        result = mock_error_recovery_workflow("Valid input")
-        assert "✅ SOAP note generated successfully" in result
-        
-        # Test error handling
-        result = mock_error_recovery_workflow("Input", simulate_error=True)
-        assert "❌ Error occurred:" in result
-        assert "💡 Please try again" in result
-        
-        # Test empty input
-        result = mock_error_recovery_workflow("")
-        assert "❌ No input provided" in result
-
-    def test_performance_workflow(self, sample_medical_text):
-        """Test workflow performance characteristics"""
-        def mock_performance_workflow(input_text):
-            import time
-            
-            start_time = time.time()
-            
-            # Simulate processing steps
-            steps = [
-                "Validating input",
-                "Preprocessing text", 
-                "Extracting medical entities",
-                "Generating SOAP structure",
-                "Formatting output"
-            ]
-            
-            processing_log = []
-            for i, step in enumerate(steps):
-                step_time = time.time()
-                processing_log.append(f"Step {i+1}: {step} - {step_time - start_time:.3f}s")
-                time.sleep(0.01)  # Simulate processing time
-            
-            total_time = time.time() - start_time
-            
-            result = "Generated SOAP Note\n\n"
-            result += "--- Performance Log ---\n"
-            result += "\n".join(processing_log)
-            result += f"\nTotal processing time: {total_time:.3f}s"
-            
-            return result, total_time
-        
-        result, processing_time = mock_performance_workflow(sample_medical_text)
-        
-        assert "Generated SOAP Note" in result
-        assert "Performance Log" in result
-        assert "Total processing time:" in result
-        assert processing_time > 0
-        assert processing_time < 1.0  # Should be fast for mocked version
-
-    def test_batch_processing_workflow(self):
-        """Test batch processing of multiple medical notes"""
-        def mock_batch_workflow(medical_notes_list):
-            if not medical_notes_list:
-                return "❌ No notes provided for batch processing"
-            
-            results = []
-            
-            for i, notes in enumerate(medical_notes_list):
-                if not notes.strip():
-                    results.append(f"Note {i+1}: ❌ Empty input")
-                    continue
-                
-                # Mock SOAP generation for each note
-                soap_result = f"""Note {i+1} - SOAP Generated:
-SUBJECTIVE: Patient presentation from note {i+1}
-OBJECTIVE: Clinical findings 
-ASSESSMENT: Medical diagnosis
-PLAN: Treatment approach
-"""
-                results.append(soap_result)
-            
-            summary = f"\n--- Batch Summary ---"
-            summary += f"\nTotal notes processed: {len(medical_notes_list)}"
-            summary += f"\nSuccessful: {len([r for r in results if '❌' not in r])}"
-            summary += f"\nFailed: {len([r for r in results if '❌' in r])}"
-            
-            return "\n".join(results) + summary
-        
-        # Test batch processing
-        notes_batch = [
-            "Patient 1: Chest pain complaint",
-            "Patient 2: Diabetes follow-up", 
-            "",  # Empty note
-            "Patient 3: Pediatric fever case"
-        ]
-        
-        result = mock_batch_workflow(notes_batch)
-        
-        assert "Note 1 - SOAP Generated:" in result
-        assert "Note 2 - SOAP Generated:" in result
-        assert "Note 3: ❌ Empty input" in result
-        assert "Note 4 - SOAP Generated:" in result
-        assert "Batch Summary" in result
-        assert "Total notes processed: 4" in result
-        assert "Successful: 3" in result
-        assert "Failed: 1" in result
-
-    def test_gradio_integration(self, sample_medical_text, sample_image):
-        """Test Gradio interface integration"""
-        def mock_gradio_integration(text_input, image_input, example_selection=None):
-            # Simulate Gradio interface behavior
-            if example_selection:
-                # Load example
-                examples = {
-                    "chest_pain": "Example chest pain case",
-                    "diabetes": "Example diabetes case", 
-                    "pediatric": "Example pediatric case"
-                }
-                text_input = examples.get(example_selection, text_input)
-            
-            # Process inputs (same as gradio_generate_soap)
-            final_text = text_input or ""
-            
-            if image_input is not None:
-                ocr_result = "OCR extracted: Patient vital signs documented"
-                if final_text:
-                    final_text += f"\n\n--- From Image ---\n{ocr_result}"
-                else:
-                    final_text = ocr_result
-            
-            if not final_text:
-                return "❌ Please provide input"
-            
-            # Generate SOAP
-            soap_output = f"""📋 SOAP NOTE GENERATED
-
-SUBJECTIVE:
-{final_text[:100]}...
-
-OBJECTIVE:
-Clinical examination findings documented.
-
-ASSESSMENT:  
-Medical evaluation completed.
-
-PLAN:
-Treatment recommendations provided.
-
---- Generated via Gradio Interface ---
-Input sources: {'Text + Image' if text_input and image_input else 'Text' if text_input else 'Image'}
-Processing timestamp: 2025-01-15 10:30:00
-"""
-            return soap_output
-        
-        # Test text only
-        result = mock_gradio_integration(sample_medical_text, None)
-        assert "📋 SOAP NOTE GENERATED" in result
-        assert "Input sources: Text" in result
-        
-        # Test image only  
-        result = mock_gradio_integration("", sample_image)
-        assert "📋 SOAP NOTE GENERATED" in result
-        assert "From Image" in result
-        
-        # Test text + image
-        result = mock_gradio_integration(sample_medical_text, sample_image)
-        assert "Input sources: Text + Image" in result
-        
-        # Test example selection
-        result = mock_gradio_integration("", None, "chest_pain")
-        assert "Example chest pain case" in result