fhirflame / tests /test_mcp_server_tdd.py
leksval
initial commit
a963d65
"""
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