""" TDD Tests for FhirFlame MCP Server Write tests FIRST, then implement to make them pass """ import pytest import asyncio import json import time from unittest.mock import Mock, patch, AsyncMock from typing import Dict, Any # These imports will fail initially - that's expected in TDD RED phase try: from src.fhirflame_mcp_server import FhirFlameMCPServer from src.codellama_processor import CodeLlamaProcessor except ImportError: # Expected during RED phase - we haven't implemented these yet FhirFlameMCPServer = None CodeLlamaProcessor = None class TestFhirFlameMCPServerTDD: """TDD tests for FhirFlame MCP Server - RED phase""" def setup_method(self): """Setup for each test""" self.sample_medical_text = """ DISCHARGE SUMMARY Patient: John Doe DOB: 1980-01-01 MRN: 123456789 DIAGNOSIS: Essential Hypertension VITAL SIGNS: - Blood Pressure: 140/90 mmHg - Heart Rate: 72 bpm - Temperature: 98.6°F MEDICATIONS: - Lisinopril 10mg daily - Metoprolol 25mg twice daily """ self.expected_fhir_bundle = { "resourceType": "Bundle", "type": "document", "entry": [ { "resource": { "resourceType": "Patient", "name": [{"given": ["John"], "family": "Doe"}], "birthDate": "1980-01-01" } } ] } @pytest.mark.mcp @pytest.mark.asyncio async def test_mcp_server_initialization(self): """Test: MCP server initializes correctly""" # Given: MCP server configuration # When: Creating FhirFlame MCP server server = FhirFlameMCPServer() # Then: Should initialize with correct tools assert server is not None assert hasattr(server, 'tools') assert len(server.tools) == 2 # process_medical_document + validate_fhir_bundle assert 'process_medical_document' in server.tools assert 'validate_fhir_bundle' in server.tools @pytest.mark.mcp @pytest.mark.asyncio async def test_process_medical_document_tool_exists(self): """Test: process_medical_document tool is properly registered""" # Given: MCP server server = FhirFlameMCPServer() # When: Getting tool definition tool = server.get_tool('process_medical_document') # Then: Should have correct tool definition assert tool is not None assert tool['name'] == 'process_medical_document' assert 'description' in tool assert 'parameters' in tool assert tool['parameters']['document_content']['required'] is True @pytest.mark.mcp @pytest.mark.asyncio async def test_validate_fhir_bundle_tool_exists(self): """Test: validate_fhir_bundle tool is properly registered""" # Given: MCP server server = FhirFlameMCPServer() # When: Getting tool definition tool = server.get_tool('validate_fhir_bundle') # Then: Should have correct tool definition assert tool is not None assert tool['name'] == 'validate_fhir_bundle' assert 'description' in tool assert 'parameters' in tool assert tool['parameters']['fhir_bundle']['required'] is True @pytest.mark.mcp @pytest.mark.asyncio async def test_process_medical_document_success(self): """Test: process_medical_document returns valid FHIR bundle""" # Given: Valid medical document input server = FhirFlameMCPServer() document_content = "base64_encoded_medical_document" document_type = "discharge_summary" # When: Processing document via MCP tool result = await server.call_tool('process_medical_document', { 'document_content': document_content, 'document_type': document_type }) # Then: Should return success with FHIR bundle assert result['success'] is True assert 'fhir_bundle' in result assert result['fhir_bundle']['resourceType'] == 'Bundle' assert len(result['fhir_bundle']['entry']) > 0 assert result['processing_metadata']['model_used'] == 'codellama:13b-instruct' assert result['processing_metadata']['gpu_used'] == 'RTX_4090' @pytest.mark.mcp @pytest.mark.asyncio async def test_process_medical_document_extracts_entities(self): """Test: Medical entities are correctly extracted""" # Given: Document with known medical entities server = FhirFlameMCPServer() document_content = self.sample_medical_text # When: Processing document result = await server.call_tool('process_medical_document', { 'document_content': document_content, 'document_type': 'discharge_summary' }) # Then: Should extract medical entities assert result['success'] is True assert result['extraction_results']['entities_found'] > 0 assert result['extraction_results']['quality_score'] > 0.6 # Verify specific medical entities are found fhir_bundle = result['fhir_bundle'] patient_found = any( entry['resource']['resourceType'] == 'Patient' for entry in fhir_bundle['entry'] ) assert patient_found is True @pytest.mark.mcp @pytest.mark.asyncio async def test_validate_fhir_bundle_success(self): """Test: FHIR validation with healthcare grade standards""" # Given: Valid FHIR bundle server = FhirFlameMCPServer() fhir_bundle = self.expected_fhir_bundle # When: Validating bundle via MCP tool result = await server.call_tool('validate_fhir_bundle', { 'fhir_bundle': fhir_bundle, 'validation_level': 'healthcare_grade' }) # Then: Should return comprehensive validation assert result['success'] is True assert result['validation_results']['is_valid'] is True assert result['validation_results']['compliance_score'] > 0.9 assert result['compliance_summary']['fhir_r4_compliant'] is True assert result['compliance_summary']['hipaa_ready'] is True @pytest.mark.mcp @pytest.mark.asyncio async def test_mcp_error_handling(self): """Test: MCP server handles errors gracefully""" # Given: Invalid input server = FhirFlameMCPServer() # When: Processing empty document result = await server.call_tool('process_medical_document', { 'document_content': '', 'document_type': 'discharge_summary' }) # Then: Should handle error gracefully assert result['success'] is False assert 'error' in result assert 'Empty document' in result['error'] @pytest.mark.mcp @pytest.mark.integration @pytest.mark.asyncio async def test_complete_mcp_workflow(self): """Test: Complete MCP workflow from document to validated FHIR""" # Given: Medical document server = FhirFlameMCPServer() test_document = self.sample_medical_text # When: Complete workflow via MCP # Step 1: Process document process_result = await server.call_tool('process_medical_document', { 'document_content': test_document, 'document_type': 'discharge_summary' }) assert process_result['success'] is True # Step 2: Validate resulting FHIR bundle validate_result = await server.call_tool('validate_fhir_bundle', { 'fhir_bundle': process_result['fhir_bundle'], 'validation_level': 'healthcare_grade' }) assert validate_result['success'] is True # Then: Complete workflow should produce valid healthcare data assert validate_result['validation_results']['is_valid'] is True assert validate_result['compliance_summary']['hipaa_ready'] is True class TestCodeLlamaProcessorTDD: """TDD tests for CodeLlama processor - RED phase""" def setup_method(self): """Setup for each test""" self.sample_text = "Patient: John Doe, DOB: 1980-01-01, Diagnosis: Hypertension" @pytest.mark.codellama @pytest.mark.gpu def test_codellama_processor_initialization(self): """Test: CodeLlama processor initializes correctly""" # Given: RTX 4090 GPU available # When: Creating CodeLlama processor processor = CodeLlamaProcessor() # Then: Should initialize with correct configuration assert processor is not None assert processor.model_name == 'codellama:13b-instruct' assert processor.gpu_available is True assert processor.vram_allocated == '12GB' @pytest.mark.codellama @pytest.mark.gpu @pytest.mark.asyncio async def test_codellama_medical_text_processing(self): """Test: CodeLlama processes medical text correctly""" # Given: Medical text and processor processor = CodeLlamaProcessor() medical_text = self.sample_text # When: Processing medical text result = await processor.process_medical_text_codellama(medical_text) # Then: Should return structured medical data assert result['success'] is True assert result['model_used'] == 'codellama:13b-instruct' assert result['gpu_used'] == 'RTX_4090' assert result['vram_used'] == '12GB' assert 'extracted_data' in result assert result['processing_time'] < 5.0 # Under 5 seconds @pytest.mark.codellama @pytest.mark.gpu @pytest.mark.asyncio async def test_codellama_json_output_format(self): """Test: CodeLlama returns proper JSON format for FHIR""" # Given: Medical text processor = CodeLlamaProcessor() medical_text = self.sample_text # When: Processing text result = await processor.process_medical_text_codellama(medical_text) # Then: Should return valid JSON structure assert result['success'] is True extracted_data = result['extracted_data'] # Should be parseable JSON try: parsed_data = json.loads(extracted_data) assert 'patient' in parsed_data assert 'conditions' in parsed_data assert 'confidence_score' in parsed_data except json.JSONDecodeError: pytest.fail("CodeLlama did not return valid JSON") @pytest.mark.codellama @pytest.mark.gpu def test_codellama_gpu_memory_efficiency(self): """Test: CodeLlama uses GPU memory efficiently""" # Given: CodeLlama processor processor = CodeLlamaProcessor() # When: Checking memory configuration memory_info = processor.get_memory_info() # Then: Should use memory efficiently assert memory_info['total_vram'] == '24GB' assert memory_info['allocated_vram'] == '12GB' assert memory_info['available_vram'] == '12GB' assert memory_info['memory_efficient'] is True class TestPerformanceBenchmarksTDD: """TDD performance tests for RTX 4090 optimization""" @pytest.mark.benchmark @pytest.mark.gpu @pytest.mark.slow def test_document_processing_speed_benchmark(self): """Benchmark: Document processing speed on RTX 4090""" try: import pytest_benchmark except ImportError: pytest.skip("pytest-benchmark not available") # Given: Standard medical document processor = CodeLlamaProcessor() sample_doc = "Patient: Jane Smith, DOB: 1975-05-15, Chief Complaint: Chest pain" # When: Processing document with timing start_time = time.time() result = asyncio.run(processor.process_medical_text_codellama(sample_doc)) processing_time = time.time() - start_time # Then: Should meet performance targets assert result['success'] is True assert processing_time < 10.0 # Reasonable target for mock processing print(f"🕒 Processing completed in {processing_time:.2f} seconds") assert result['gpu_used'] == 'RTX_4090' @pytest.mark.benchmark @pytest.mark.gpu def test_concurrent_processing_capability(self): """Test: RTX 4090 can handle concurrent medical document processing""" # Given: Multiple documents processor = CodeLlamaProcessor() documents = [ "Patient A: Hypertension diagnosis", "Patient B: Diabetes management", "Patient C: Pneumonia treatment" ] # When: Processing concurrently async def process_concurrent(): tasks = [ processor.process_medical_text_codellama(doc) for doc in documents ] return await asyncio.gather(*tasks) results = asyncio.run(process_concurrent()) # Then: All should succeed without memory issues assert len(results) == 3 for result in results: assert result['success'] is True assert result['gpu_used'] == 'RTX_4090' @pytest.mark.skip(reason="Will fail until implementation - TDD RED phase") class TestTDDRedPhaseRunner: """This class ensures tests fail initially as expected in TDD""" def test_all_tests_should_fail_initially(self): """Meta-test: Confirms we're in TDD RED phase""" # This test documents that we expect failures initially # Remove @pytest.mark.skip once implementation begins pass