Gemini MCP Server

#!/usr/bin/env python3 """ PrecommitWorkflow Tool Validation Test Tests the precommit tool's capabilities using the new workflow architecture. This validates that the workflow-based pre-commit validation provides step-by-step analysis with proper investigation guidance and expert analysis integration. """ import json from typing import Optional from .conversation_base_test import ConversationBaseTest class PrecommitWorkflowValidationTest(ConversationBaseTest): """Test precommit tool with new workflow architecture""" @property def test_name(self) -> str: return "precommit_validation" @property def test_description(self) -> str: return "PrecommitWorkflow tool validation with new workflow architecture" def run_test(self) -> bool: """Test precommit tool capabilities""" # Set up the test environment self.setUp() try: self.logger.info("Test: PrecommitWorkflow tool validation (new architecture)") # Create test git repository structure with changes self._create_test_git_changes() # Test 1: Single validation session with multiple steps if not self._test_single_validation_session(): return False # Test 2: Validation with backtracking if not self._test_validation_with_backtracking(): return False # Test 3: Complete validation with expert analysis if not self._test_complete_validation_with_analysis(): return False # Test 4: Certain confidence behavior if not self._test_certain_confidence(): return False # Test 5: Context-aware file embedding if not self._test_context_aware_file_embedding(): return False # Test 6: Multi-step file context optimization if not self._test_multi_step_file_context(): return False self.logger.info(" ✅ All precommit validation tests passed") return True except Exception as e: self.logger.error(f"PrecommitWorkflow validation test failed: {e}") return False def _create_test_git_changes(self): """Create test files simulating git changes for pre-commit validation""" # Create a new API endpoint with potential security issues new_api_code = """#!/usr/bin/env python3 from flask import Flask, request, jsonify import sqlite3 import os app = Flask(__name__) @app.route('/api/user/<user_id>', methods=['GET']) def get_user(user_id): \"\"\"Get user information by ID\"\"\" # Potential SQL injection vulnerability conn = sqlite3.connect('users.db') cursor = conn.cursor() # BUG: Direct string interpolation creates SQL injection risk query = f"SELECT * FROM users WHERE id = {user_id}" cursor.execute(query) result = cursor.fetchone() conn.close() if result: return jsonify({ 'id': result[0], 'username': result[1], 'email': result[2], 'password_hash': result[3] # Security issue: exposing password hash }) else: return jsonify({'error': 'User not found'}), 404 @app.route('/api/admin/users', methods=['GET']) def list_all_users(): \"\"\"Admin endpoint to list all users\"\"\" # Missing authentication check conn = sqlite3.connect('users.db') cursor = conn.cursor() cursor.execute("SELECT id, username, email FROM users") users = [] for row in cursor.fetchall(): users.append({ 'id': row[0], 'username': row[1], 'email': row[2] }) conn.close() return jsonify(users) if __name__ == '__main__': # Debug mode in production is a security risk app.run(debug=True, host='0.0.0.0') """ # Create configuration file with issues config_code = """#!/usr/bin/env python3 import os # Database configuration DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///users.db') # Security settings SECRET_KEY = "hardcoded-secret-key-123" # Security issue: hardcoded secret DEBUG_MODE = True # Should be environment-based # API settings API_RATE_LIMIT = 1000 # Very high, no rate limiting effectively MAX_FILE_UPLOAD = 50 * 1024 * 1024 # 50MB - quite large # Missing important security headers configuration CORS_ORIGINS = "*" # Security issue: allows all origins """ # Create test files self.api_file = self.create_additional_test_file("api_endpoints.py", new_api_code) self.config_file = self.create_additional_test_file("config.py", config_code) self.logger.info(f" ✅ Created test files: {self.api_file}, {self.config_file}") # Create change description change_description = """COMMIT DESCRIPTION: Added new user API endpoints and configuration for user management system. CHANGES MADE: - Added GET /api/user/<user_id> endpoint to retrieve user information - Added GET /api/admin/users endpoint for admin user listing - Added configuration file with database and security settings - Set up Flask application with basic routing REQUIREMENTS: - User data should be retrievable by ID - Admin should be able to list all users - System should be configurable via environment variables - Security should be properly implemented """ self.changes_file = self.create_additional_test_file("commit_description.txt", change_description) self.logger.info(f" ✅ Created change description: {self.changes_file}") def _test_single_validation_session(self) -> bool: """Test a complete validation session with multiple steps""" try: self.logger.info(" 1.1: Testing single validation session") # Step 1: Start validation self.logger.info(" 1.1.1: Step 1 - Initial validation plan") response1, continuation_id = self.call_mcp_tool( "precommit", { "step": "I need to perform comprehensive pre-commit validation for new API endpoints. Let me start by analyzing the changes and identifying potential issues.", "step_number": 1, "total_steps": 4, "next_step_required": True, "findings": "New user API endpoints and configuration added. Need to examine for security, performance, and best practices.", "files_checked": [self.changes_file], "relevant_files": [self.changes_file], "path": self.test_dir, # Required for step 1 "review_type": "full", "severity_filter": "all", }, ) if not response1 or not continuation_id: self.logger.error("Failed to get initial validation response") return False # Parse and validate JSON response response1_data = self._parse_precommit_response(response1) if not response1_data: return False # Validate step 1 response structure - expect pause_for_validation for next_step_required=True if not self._validate_step_response(response1_data, 1, 4, True, "pause_for_validation"): return False self.logger.info(f" ✅ Step 1 successful, continuation_id: {continuation_id}") # Step 2: Examine the code for issues self.logger.info(" 1.1.2: Step 2 - Code examination") response2, _ = self.call_mcp_tool( "precommit", { "step": "Now examining the API endpoint implementation and configuration for security vulnerabilities and best practices violations.", "step_number": 2, "total_steps": 4, "next_step_required": True, "findings": "Found multiple critical security issues: SQL injection vulnerability in get_user(), hardcoded secrets in config, missing authentication, and password hash exposure.", "files_checked": [self.changes_file, self.api_file, self.config_file], "relevant_files": [self.api_file, self.config_file], "relevant_context": ["get_user", "list_all_users"], "issues_found": [ {"severity": "critical", "description": "SQL injection vulnerability in user lookup"}, {"severity": "high", "description": "Hardcoded secret key in configuration"}, {"severity": "high", "description": "Password hash exposed in API response"}, {"severity": "medium", "description": "Missing authentication on admin endpoint"}, ], # Assessment field removed - using precommit_type instead # Confidence field removed - using precommit_type instead "continuation_id": continuation_id, }, ) if not response2: self.logger.error("Failed to continue validation to step 2") return False response2_data = self._parse_precommit_response(response2) if not self._validate_step_response(response2_data, 2, 4, True, "pause_for_validation"): return False # Check validation status tracking validation_status = response2_data.get("validation_status", {}) if validation_status.get("files_checked", 0) < 3: self.logger.error("Files checked count not properly tracked") return False if validation_status.get("issues_identified", 0) != 4: self.logger.error("Issues found not properly tracked") return False if validation_status.get("precommit_type") != "external": self.logger.error("Precommit type not properly tracked") return False self.logger.info(" ✅ Step 2 successful with proper tracking") # Store continuation_id for next test self.validation_continuation_id = continuation_id return True except Exception as e: self.logger.error(f"Single validation session test failed: {e}") return False def _test_validation_with_backtracking(self) -> bool: """Test validation with backtracking to revise findings""" try: self.logger.info(" 1.2: Testing validation with backtracking") # Start a new validation for testing backtracking self.logger.info(" 1.2.1: Start validation for backtracking test") response1, continuation_id = self.call_mcp_tool( "precommit", { "step": "Validating database connection optimization changes", "step_number": 1, "total_steps": 4, "next_step_required": True, "findings": "Initial analysis shows database connection pooling implementation", "files_checked": ["/db/connection.py"], "relevant_files": ["/db/connection.py"], "path": self.test_dir, }, ) if not response1 or not continuation_id: self.logger.error("Failed to start backtracking test validation") return False # Step 2: Wrong direction self.logger.info(" 1.2.2: Step 2 - Wrong validation focus") response2, _ = self.call_mcp_tool( "precommit", { "step": "Focusing on connection pool size optimization", "step_number": 2, "total_steps": 4, "next_step_required": True, "findings": "Connection pool configuration seems reasonable, might be looking in wrong place", "files_checked": ["/db/connection.py", "/config/database.py"], "relevant_files": [], # Assessment fields removed - using precommit_type instead "continuation_id": continuation_id, }, ) if not response2: self.logger.error("Failed to continue to step 2") return False # Step 3: Backtrack from step 2 self.logger.info(" 1.2.3: Step 3 - Backtrack and revise approach") response3, _ = self.call_mcp_tool( "precommit", { "step": "Backtracking - the issue might not be database configuration. Let me examine the actual SQL queries and data access patterns instead.", "step_number": 3, "total_steps": 4, "next_step_required": True, "findings": "Found inefficient N+1 query pattern in user data loading causing performance issues", "files_checked": ["/models/user.py"], "relevant_files": ["/models/user.py"], "relevant_context": ["User.load_profile"], "issues_found": [ {"severity": "medium", "description": "N+1 query pattern in user profile loading"} ], # Assessment fields removed - using precommit_type instead "backtrack_from_step": 2, # Backtrack from step 2 "continuation_id": continuation_id, }, ) if not response3: self.logger.error("Failed to backtrack") return False response3_data = self._parse_precommit_response(response3) if not self._validate_step_response(response3_data, 3, 4, True, "pause_for_validation"): return False self.logger.info(" ✅ Backtracking working correctly") return True except Exception as e: self.logger.error(f"Backtracking test failed: {e}") return False def _test_complete_validation_with_analysis(self) -> bool: """Test complete validation ending with expert analysis""" try: self.logger.info(" 1.3: Testing complete validation with expert analysis") # Use the continuation from first test continuation_id = getattr(self, "validation_continuation_id", None) if not continuation_id: # Start fresh if no continuation available self.logger.info(" 1.3.0: Starting fresh validation") response0, continuation_id = self.call_mcp_tool( "precommit", { "step": "Validating the security fixes for API endpoints", "step_number": 1, "total_steps": 2, "next_step_required": True, "findings": "Found critical security vulnerabilities in API implementation", "files_checked": [self.api_file], "relevant_files": [self.api_file], "relevant_context": ["get_user", "list_all_users"], "issues_found": [{"severity": "critical", "description": "SQL injection vulnerability"}], "path": self.test_dir, }, ) if not response0 or not continuation_id: self.logger.error("Failed to start fresh validation") return False # Final step - trigger expert analysis self.logger.info(" 1.3.1: Final step - complete validation") response_final, _ = self.call_mcp_tool( "precommit", { "step": "Validation complete. I have identified all critical security issues and missing safeguards in the new API endpoints.", "step_number": 2, "total_steps": 2, "next_step_required": False, # Final step - triggers expert analysis "findings": "Comprehensive analysis complete: SQL injection, hardcoded secrets, missing authentication, password exposure, and insecure defaults all identified with specific fixes needed.", "files_checked": [self.api_file, self.config_file], "relevant_files": [self.api_file, self.config_file], "relevant_context": ["get_user", "list_all_users", "SECRET_KEY", "DEBUG_MODE"], "issues_found": [ {"severity": "critical", "description": "SQL injection vulnerability in user lookup query"}, {"severity": "high", "description": "Hardcoded secret key exposes application security"}, {"severity": "high", "description": "Password hash exposed in API response"}, {"severity": "medium", "description": "Missing authentication on admin endpoint"}, {"severity": "medium", "description": "Debug mode enabled in production configuration"}, ], # Confidence field removed - using precommit_type instead "continuation_id": continuation_id, "model": "flash", # Use flash for expert analysis }, ) if not response_final: self.logger.error("Failed to complete validation") return False response_final_data = self._parse_precommit_response(response_final) if not response_final_data: return False # Validate final response structure - expect calling_expert_analysis for next_step_required=False if response_final_data.get("status") != "calling_expert_analysis": self.logger.error( f"Expected status 'calling_expert_analysis', got '{response_final_data.get('status')}'" ) return False if not response_final_data.get("validation_complete"): self.logger.error("Expected validation_complete=true for final step") return False # Check for expert analysis if "expert_analysis" not in response_final_data: self.logger.error("Missing expert_analysis in final response") return False expert_analysis = response_final_data.get("expert_analysis", {}) # Check for expected analysis content (checking common patterns) analysis_text = json.dumps(expert_analysis, ensure_ascii=False).lower() # Look for security issue identification security_indicators = ["sql", "injection", "security", "hardcoded", "secret", "authentication"] found_indicators = sum(1 for indicator in security_indicators if indicator in analysis_text) if found_indicators >= 3: self.logger.info(" ✅ Expert analysis identified security issues correctly") else: self.logger.warning( f" ⚠️ Expert analysis may not have fully identified security issues (found {found_indicators}/6 indicators)" ) # Check complete validation summary if "complete_validation" not in response_final_data: self.logger.error("Missing complete_validation in final response") return False complete_validation = response_final_data["complete_validation"] if not complete_validation.get("relevant_context"): self.logger.error("Missing relevant context in complete validation") return False if "get_user" not in complete_validation["relevant_context"]: self.logger.error("Expected function not found in validation summary") return False self.logger.info(" ✅ Complete validation with expert analysis successful") return True except Exception as e: self.logger.error(f"Complete validation test failed: {e}") return False def _test_certain_confidence(self) -> bool: """Test certain confidence behavior - should skip expert analysis""" try: self.logger.info(" 1.4: Testing certain confidence behavior") # Test certain confidence - should skip expert analysis self.logger.info(" 1.4.1: Certain confidence validation") response_certain, _ = self.call_mcp_tool( "precommit", { "step": "I have confirmed all security issues with 100% certainty: SQL injection, hardcoded secrets, and missing authentication.", "step_number": 1, "total_steps": 1, "next_step_required": False, # Final step "findings": "All critical issues identified: parameterized queries needed, environment variables for secrets, authentication middleware required, and debug mode must be disabled for production.", "files_checked": [self.api_file, self.config_file], "relevant_files": [self.api_file, self.config_file], "relevant_context": ["get_user", "list_all_users"], "issues_found": [ { "severity": "critical", "description": "SQL injection vulnerability - fix with parameterized queries", }, {"severity": "high", "description": "Hardcoded secret - use environment variables"}, {"severity": "medium", "description": "Missing authentication - add middleware"}, ], "precommit_type": "internal", # This should skip expert analysis "path": self.test_dir, "model": "flash", }, ) if not response_certain: self.logger.error("Failed to test certain confidence") return False response_certain_data = self._parse_precommit_response(response_certain) if not response_certain_data: return False # Validate certain confidence response - should skip expert analysis if response_certain_data.get("status") != "validation_complete_ready_for_commit": self.logger.error( f"Expected status 'validation_complete_ready_for_commit', got '{response_certain_data.get('status')}'" ) return False if not response_certain_data.get("skip_expert_analysis"): self.logger.error("Expected skip_expert_analysis=true for certain confidence") return False expert_analysis = response_certain_data.get("expert_analysis", {}) if expert_analysis.get("status") != "skipped_due_to_internal_analysis_type": self.logger.error("Expert analysis should be skipped for certain confidence") return False self.logger.info(" ✅ Certain confidence behavior working correctly") return True except Exception as e: self.logger.error(f"Certain confidence test failed: {e}") return False def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]: """Call an MCP tool in-process - override for precommit-specific response handling""" # Use in-process implementation to maintain conversation memory response_text, _ = self.call_mcp_tool_direct(tool_name, params) if not response_text: return None, None # Extract continuation_id from precommit response specifically continuation_id = self._extract_precommit_continuation_id(response_text) return response_text, continuation_id def _extract_precommit_continuation_id(self, response_text: str) -> Optional[str]: """Extract continuation_id from precommit response""" try: # Parse the response response_data = json.loads(response_text) return response_data.get("continuation_id") except json.JSONDecodeError as e: self.logger.debug(f"Failed to parse response for precommit continuation_id: {e}") return None def _parse_precommit_response(self, response_text: str) -> dict: """Parse precommit tool JSON response""" try: # Parse the response - it should be direct JSON return json.loads(response_text) except json.JSONDecodeError as e: self.logger.error(f"Failed to parse precommit response as JSON: {e}") self.logger.error(f"Response text: {response_text[:500]}...") return {} def _validate_step_response( self, response_data: dict, expected_step: int, expected_total: int, expected_next_required: bool, expected_status: str, ) -> bool: """Validate a precommit validation step response structure""" try: # Check status if response_data.get("status") != expected_status: self.logger.error(f"Expected status '{expected_status}', got '{response_data.get('status')}'") return False # Check step number if response_data.get("step_number") != expected_step: self.logger.error(f"Expected step_number {expected_step}, got {response_data.get('step_number')}") return False # Check total steps if response_data.get("total_steps") != expected_total: self.logger.error(f"Expected total_steps {expected_total}, got {response_data.get('total_steps')}") return False # Check next_step_required if response_data.get("next_step_required") != expected_next_required: self.logger.error( f"Expected next_step_required {expected_next_required}, got {response_data.get('next_step_required')}" ) return False # Check validation_status exists if "validation_status" not in response_data: self.logger.error("Missing validation_status in response") return False # Check next_steps guidance if not response_data.get("next_steps"): self.logger.error("Missing next_steps guidance in response") return False return True except Exception as e: self.logger.error(f"Error validating step response: {e}") return False def _test_context_aware_file_embedding(self) -> bool: """Test context-aware file embedding optimization""" try: self.logger.info(" 1.5: Testing context-aware file embedding") # Create multiple test files for context testing auth_file_content = """#!/usr/bin/env python3 from functools import wraps from flask import request, jsonify def require_auth(f): \"\"\"Authentication decorator\"\"\" @wraps(f) def decorated_function(*args, **kwargs): token = request.headers.get('Authorization') if not token: return jsonify({'error': 'No token provided'}), 401 # Validate token here if not validate_token(token): return jsonify({'error': 'Invalid token'}), 401 return f(*args, **kwargs) return decorated_function def validate_token(token): \"\"\"Validate authentication token\"\"\" # Token validation logic return token.startswith('Bearer ') """ middleware_file_content = """#!/usr/bin/env python3 from flask import Flask, request, g import time def add_security_headers(app): \"\"\"Add security headers to all responses\"\"\" @app.after_request def security_headers(response): response.headers['X-Content-Type-Options'] = 'nosniff' response.headers['X-Frame-Options'] = 'DENY' response.headers['X-XSS-Protection'] = '1; mode=block' return response def rate_limiting_middleware(app): \"\"\"Basic rate limiting\"\"\" @app.before_request def limit_remote_addr(): # Simple rate limiting logic pass """ # Create test files auth_file = self.create_additional_test_file("auth.py", auth_file_content) middleware_file = self.create_additional_test_file("middleware.py", middleware_file_content) # Test 1: New conversation, intermediate step - should only reference files self.logger.info(" 1.5.1: New conversation intermediate step (should reference only)") response1, continuation_id = self.call_mcp_tool( "precommit", { "step": "Starting validation of new authentication and security middleware", "step_number": 1, "total_steps": 3, "next_step_required": True, # Intermediate step "findings": "Initial analysis of authentication and middleware components", "files_checked": [auth_file, middleware_file], "relevant_files": [auth_file], # This should be referenced, not embedded "relevant_context": ["require_auth"], # Assessment fields removed - using precommit_type instead "path": self.test_dir, "model": "flash", }, ) if not response1 or not continuation_id: self.logger.error("Failed to start context-aware file embedding test") return False response1_data = self._parse_precommit_response(response1) if not response1_data: return False # Check file context - should be reference_only for intermediate step file_context = response1_data.get("file_context", {}) if file_context.get("type") != "reference_only": self.logger.error(f"Expected reference_only file context, got: {file_context.get('type')}") return False if "Files referenced but not embedded" not in file_context.get("context_optimization", ""): self.logger.error("Expected context optimization message for reference_only") return False self.logger.info(" ✅ Intermediate step correctly uses reference_only file context") # Test 2: Intermediate step with continuation - should still only reference self.logger.info(" 1.5.2: Intermediate step with continuation (should reference only)") response2, _ = self.call_mcp_tool( "precommit", { "step": "Continuing validation with detailed security analysis", "step_number": 2, "total_steps": 3, "next_step_required": True, # Still intermediate "continuation_id": continuation_id, "findings": "Found potential issues in token validation and missing security headers", "files_checked": [auth_file, middleware_file], "relevant_files": [auth_file, middleware_file], # Both files referenced "relevant_context": ["require_auth", "validate_token", "add_security_headers"], "issues_found": [ {"severity": "medium", "description": "Basic token validation might be insufficient"} ], # Assessment fields removed - using precommit_type instead "model": "flash", }, ) if not response2: self.logger.error("Failed to continue to step 2") return False response2_data = self._parse_precommit_response(response2) if not response2_data: return False # Check file context - should still be reference_only file_context2 = response2_data.get("file_context", {}) if file_context2.get("type") != "reference_only": self.logger.error(f"Expected reference_only file context for step 2, got: {file_context2.get('type')}") return False # Should include reference note if not file_context2.get("note"): self.logger.error("Expected file reference note for intermediate step") return False reference_note = file_context2.get("note", "") if "auth.py" not in reference_note or "middleware.py" not in reference_note: self.logger.error("File reference note should mention both files") return False self.logger.info(" ✅ Intermediate step with continuation correctly uses reference_only") # Test 3: Final step - should embed files for expert analysis self.logger.info(" 1.5.3: Final step (should embed files)") response3, _ = self.call_mcp_tool( "precommit", { "step": "Validation complete - identified security gaps and improvement areas", "step_number": 3, "total_steps": 3, "next_step_required": False, # Final step - should embed files "continuation_id": continuation_id, "findings": "Security implementation has several gaps: token validation is basic, missing CSRF protection, and rate limiting is not implemented", "files_checked": [auth_file, middleware_file], "relevant_files": [auth_file, middleware_file], # Should be fully embedded "relevant_context": ["require_auth", "validate_token", "add_security_headers"], "issues_found": [ {"severity": "medium", "description": "Token validation needs strengthening"}, {"severity": "low", "description": "Missing CSRF protection"}, {"severity": "low", "description": "Rate limiting not implemented"}, ], # Assessment field removed - using precommit_type instead # Confidence field removed - using precommit_type instead "model": "flash", }, ) if not response3: self.logger.error("Failed to complete to final step") return False response3_data = self._parse_precommit_response(response3) if not response3_data: return False # Check file context - should be fully_embedded for final step file_context3 = response3_data.get("file_context", {}) if file_context3.get("type") != "fully_embedded": self.logger.error( f"Expected fully_embedded file context for final step, got: {file_context3.get('type')}" ) return False if "Full file content embedded for expert analysis" not in file_context3.get("context_optimization", ""): self.logger.error("Expected expert analysis optimization message for fully_embedded") return False # Should show files embedded count files_embedded = file_context3.get("files_embedded", 0) if files_embedded == 0: # This is OK - files might already be in conversation history self.logger.info( " ℹ️ Files embedded count is 0 - files already in conversation history (smart deduplication)" ) else: self.logger.info(f" ✅ Files embedded count: {files_embedded}") self.logger.info(" ✅ Final step correctly uses fully_embedded file context") # Verify expert analysis was called for final step if response3_data.get("status") != "calling_expert_analysis": self.logger.error("Final step should trigger expert analysis") return False if "expert_analysis" not in response3_data: self.logger.error("Expert analysis should be present in final step") return False self.logger.info(" ✅ Context-aware file embedding test completed successfully") return True except Exception as e: self.logger.error(f"Context-aware file embedding test failed: {e}") return False def _test_multi_step_file_context(self) -> bool: """Test multi-step workflow with proper file context transitions""" try: self.logger.info(" 1.6: Testing multi-step file context optimization") # Create a complex scenario with multiple files for pre-commit validation database_content = """#!/usr/bin/env python3 import sqlite3 import os from contextlib import contextmanager class DatabaseManager: def __init__(self): self.db_path = os.getenv('DATABASE_PATH', 'app.db') @contextmanager def get_connection(self): \"\"\"Get database connection with proper cleanup\"\"\" conn = None try: conn = sqlite3.connect(self.db_path) yield conn finally: if conn: conn.close() def create_user(self, username, email, password_hash): \"\"\"Create a new user\"\"\" with self.get_connection() as conn: cursor = conn.cursor() # Proper parameterized query cursor.execute( "INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)", (username, email, password_hash) ) conn.commit() return cursor.lastrowid """ tests_content = """#!/usr/bin/env python3 import unittest from unittest.mock import patch, MagicMock from database_manager import DatabaseManager class TestDatabaseManager(unittest.TestCase): def setUp(self): self.db_manager = DatabaseManager() @patch('sqlite3.connect') def test_create_user(self, mock_connect): \"\"\"Test user creation\"\"\" mock_conn = MagicMock() mock_cursor = MagicMock() mock_cursor.lastrowid = 123 mock_conn.cursor.return_value = mock_cursor mock_connect.return_value = mock_conn user_id = self.db_manager.create_user('testuser', 'test@example.com', 'hashed_password') self.assertEqual(user_id, 123) mock_cursor.execute.assert_called_once_with( "INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)", ('testuser', 'test@example.com', 'hashed_password') ) if __name__ == '__main__': unittest.main() """ # Create test files db_file = self.create_additional_test_file("database_manager.py", database_content) test_file = self.create_additional_test_file("test_database.py", tests_content) # Step 1: Start validation (new conversation) self.logger.info(" 1.6.1: Step 1 - Start validation") response1, continuation_id = self.call_mcp_tool( "precommit", { "step": "Validating new database manager implementation and corresponding tests", "step_number": 1, "total_steps": 4, "next_step_required": True, "findings": "New database manager with connection handling and user creation functionality", "files_checked": [db_file], "relevant_files": [db_file], "relevant_context": [], # Assessment fields removed - using precommit_type instead "path": self.test_dir, "model": "flash", }, ) if not response1 or not continuation_id: self.logger.error("Failed to start multi-step file context test") return False response1_data = self._parse_precommit_response(response1) # Validate step 1 - should use reference_only file_context1 = response1_data.get("file_context", {}) if file_context1.get("type") != "reference_only": self.logger.error("Step 1 should use reference_only file context") return False self.logger.info(" ✅ Step 1: reference_only file context") # Step 2: Expand validation self.logger.info(" 1.6.2: Step 2 - Expand validation") response2, _ = self.call_mcp_tool( "precommit", { "step": "Found good database implementation - now examining test coverage", "step_number": 2, "total_steps": 4, "next_step_required": True, "continuation_id": continuation_id, "findings": "Database manager uses proper parameterized queries and context managers. Test file provides good coverage with mocking.", "files_checked": [db_file, test_file], "relevant_files": [db_file, test_file], "relevant_context": ["DatabaseManager.create_user", "TestDatabaseManager.test_create_user"], # Assessment fields removed - using precommit_type instead "model": "flash", }, ) if not response2: self.logger.error("Failed to continue to step 2") return False response2_data = self._parse_precommit_response(response2) # Validate step 2 - should still use reference_only file_context2 = response2_data.get("file_context", {}) if file_context2.get("type") != "reference_only": self.logger.error("Step 2 should use reference_only file context") return False # Should reference both files reference_note = file_context2.get("note", "") if "database_manager.py" not in reference_note or "test_database.py" not in reference_note: self.logger.error("Step 2 should reference both files in note") return False self.logger.info(" ✅ Step 2: reference_only file context with multiple files") # Step 3: Deep analysis self.logger.info(" 1.6.3: Step 3 - Deep analysis") response3, _ = self.call_mcp_tool( "precommit", { "step": "Performing comprehensive security and best practices analysis", "step_number": 3, "total_steps": 4, "next_step_required": True, "continuation_id": continuation_id, "findings": "Code follows security best practices: parameterized queries prevent SQL injection, proper resource cleanup with context managers, environment-based configuration.", "files_checked": [db_file, test_file], "relevant_files": [db_file, test_file], "relevant_context": ["DatabaseManager.get_connection", "DatabaseManager.create_user"], "issues_found": [], # No issues found # Assessment field removed - using precommit_type instead # Confidence field removed - using precommit_type instead "model": "flash", }, ) if not response3: self.logger.error("Failed to continue to step 3") return False response3_data = self._parse_precommit_response(response3) # Validate step 3 - should still use reference_only file_context3 = response3_data.get("file_context", {}) if file_context3.get("type") != "reference_only": self.logger.error("Step 3 should use reference_only file context") return False self.logger.info(" ✅ Step 3: reference_only file context") # Step 4: Final validation with expert consultation self.logger.info(" 1.6.4: Step 4 - Final step with expert analysis") response4, _ = self.call_mcp_tool( "precommit", { "step": "Validation complete - code is ready for commit", "step_number": 4, "total_steps": 4, "next_step_required": False, # Final step - should embed files "continuation_id": continuation_id, "findings": "Comprehensive validation complete: secure implementation with parameterized queries, proper resource management, good test coverage, and no security vulnerabilities identified.", "files_checked": [db_file, test_file], "relevant_files": [db_file, test_file], "relevant_context": ["DatabaseManager", "TestDatabaseManager"], "issues_found": [], # Assessment field removed - using precommit_type instead # Confidence field removed - using precommit_type instead "model": "flash", }, ) if not response4: self.logger.error("Failed to complete to final step") return False response4_data = self._parse_precommit_response(response4) # Validate step 4 - should use fully_embedded for expert analysis file_context4 = response4_data.get("file_context", {}) if file_context4.get("type") != "fully_embedded": self.logger.error("Step 4 (final) should use fully_embedded file context") return False if "expert analysis" not in file_context4.get("context_optimization", "").lower(): self.logger.error("Final step should mention expert analysis in context optimization") return False # Verify expert analysis was triggered if response4_data.get("status") != "calling_expert_analysis": self.logger.error("Final step should trigger expert analysis") return False # Check that expert analysis has file context expert_analysis = response4_data.get("expert_analysis", {}) if not expert_analysis: self.logger.error("Expert analysis should be present in final step") return False self.logger.info(" ✅ Step 4: fully_embedded file context with expert analysis") # Validate the complete workflow progression progression_summary = { "step_1": "reference_only (new conversation, intermediate)", "step_2": "reference_only (continuation, intermediate)", "step_3": "reference_only (continuation, intermediate)", "step_4": "fully_embedded (continuation, final)", } self.logger.info(" 📋 File context progression:") for step, context_type in progression_summary.items(): self.logger.info(f" {step}: {context_type}") self.logger.info(" ✅ Multi-step file context optimization test completed successfully") return True except Exception as e: self.logger.error(f"Multi-step file context test failed: {e}") return False