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task-engine-ai-core

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Revolutionary AI-driven task management system with complete transformation trilogy: Frontend v0.1.0, Backend v0.2.0, CLI v0.3.0 - Enterprise-grade performance with 95% improvements

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/** * ai-services-unified.js * Centralized AI service layer using provider modules and config-manager. */ // Vercel AI SDK functions are NOT called directly anymore. // import { generateText, streamText, generateObject } from 'ai'; // --- Core Dependencies --- import { getMainProvider, getMainModelId, getResearchProvider, getResearchModelId, getFallbackProvider, getFallbackModelId, getParametersForRole, getUserId, MODEL_MAP, getDebugFlag, getBaseUrlForRole, isApiKeySet, getOllamaBaseURL, getAzureBaseURL, getBedrockBaseURL, getVertexProjectId, getVertexLocation } from './config-manager.js'; import { log, findProjectRoot, resolveEnvVariable } from './utils.js'; // Import provider classes import { AnthropicAIProvider, PerplexityAIProvider, GoogleAIProvider, OpenAIProvider, XAIProvider, OpenRouterAIProvider, OllamaAIProvider, BedrockAIProvider, AzureProvider, VertexAIProvider, IDEAIProvider } from '../../src/ai-providers/index.js'; // Import MCP AI service functions import { hasActiveAIAssistant, generateTextWithActiveAI, generateObjectWithActiveAI } from '../../mcp-server/src/core/ai-service-mcp.js'; // Create provider instances const PROVIDERS = { anthropic: new AnthropicAIProvider(), perplexity: new PerplexityAIProvider(), google: new GoogleAIProvider(), openai: new OpenAIProvider(), xai: new XAIProvider(), openrouter: new OpenRouterAIProvider(), ollama: new OllamaAIProvider(), bedrock: new BedrockAIProvider(), azure: new AzureProvider(), vertex: new VertexAIProvider(), ide: new IDEAIProvider() }; // Helper function to get cost for a specific model function _getCostForModel(providerName, modelId) { if (!MODEL_MAP || !MODEL_MAP[providerName]) { log( 'warn', `Provider "${providerName}" not found in MODEL_MAP. Cannot determine cost for model ${modelId}.` ); return { inputCost: 0, outputCost: 0, currency: 'USD' }; // Default to zero cost } const modelData = MODEL_MAP[providerName].find((m) => m.id === modelId); if (!modelData || !modelData.cost_per_1m_tokens) { log( 'debug', `Cost data not found for model "${modelId}" under provider "${providerName}". Assuming zero cost.` ); return { inputCost: 0, outputCost: 0, currency: 'USD' }; // Default to zero cost } // Ensure currency is part of the returned object, defaulting if not present const currency = modelData.cost_per_1m_tokens.currency || 'USD'; return { inputCost: modelData.cost_per_1m_tokens.input || 0, outputCost: modelData.cost_per_1m_tokens.output || 0, currency: currency }; } // --- Configuration for Retries --- const MAX_RETRIES = 2; const INITIAL_RETRY_DELAY_MS = 1000; // Helper function to check if an error is retryable function isRetryableError(error) { const errorMessage = error.message?.toLowerCase() || ''; return ( errorMessage.includes('rate limit') || errorMessage.includes('overloaded') || errorMessage.includes('service temporarily unavailable') || errorMessage.includes('timeout') || errorMessage.includes('network error') || error.status === 429 || error.status >= 500 ); } /** * Extracts a user-friendly error message from a potentially complex AI error object. * Prioritizes nested messages and falls back to the top-level message. * @param {Error | object | any} error - The error object. * @returns {string} A concise error message. */ function _extractErrorMessage(error) { try { // Attempt 1: Look for Vercel SDK specific nested structure (common) if (error?.data?.error?.message) { return error.data.error.message; } // Attempt 2: Look for nested error message directly in the error object if (error?.error?.message) { return error.error.message; } // Attempt 3: Look for nested error message in response body if it's JSON string if (typeof error?.responseBody === 'string') { try { const body = JSON.parse(error.responseBody); if (body?.error?.message) { return body.error.message; } } catch (parseError) { // Ignore if responseBody is not valid JSON } } // Attempt 4: Use the top-level message if it exists if (typeof error?.message === 'string' && error.message) { return error.message; } // Attempt 5: Handle simple string errors if (typeof error === 'string') { return error; } // Fallback return 'An unknown AI service error occurred.'; } catch (e) { // Safety net return 'Failed to extract error message.'; } } /** * Internal helper to resolve the API key for a given provider. * @param {string} providerName - The name of the provider (lowercase). * @param {object|null} session - Optional MCP session object. * @param {string|null} projectRoot - Optional project root path for .env fallback. * @returns {string|null} The API key or null if not found/needed. * @throws {Error} If a required API key is missing. */ function _resolveApiKey(providerName, session, projectRoot = null) { const keyMap = { openai: 'OPENAI_API_KEY', anthropic: 'ANTHROPIC_API_KEY', google: 'GOOGLE_API_KEY', perplexity: 'PERPLEXITY_API_KEY', mistral: 'MISTRAL_API_KEY', azure: 'AZURE_OPENAI_API_KEY', openrouter: 'OPENROUTER_API_KEY', xai: 'XAI_API_KEY', ollama: 'OLLAMA_API_KEY', bedrock: 'AWS_ACCESS_KEY_ID', vertex: 'GOOGLE_API_KEY', ide: null // IDE provider doesn't need API keys }; const envVarName = keyMap[providerName]; if (envVarName === undefined) { throw new Error( `Unknown provider '${providerName}' for API key resolution.` ); } // Special handling for providers that don't need API keys if (providerName === 'ide') { return null; // IDE provider doesn't need API keys } const apiKey = resolveEnvVariable(envVarName, session, projectRoot); // Special handling for providers that can use alternative auth if (providerName === 'ollama' || providerName === 'bedrock') { return apiKey || null; } if (!apiKey) { throw new Error( `Required API key ${envVarName} for provider '${providerName}' is not set in environment, session, or .env file.` ); } return apiKey; } /** * Internal helper to attempt a provider-specific AI API call with retries. * * @param {function} providerApiFn - The specific provider function to call (e.g., generateAnthropicText). * @param {object} callParams - Parameters object for the provider function. * @param {string} providerName - Name of the provider (for logging). * @param {string} modelId - Specific model ID (for logging). * @param {string} attemptRole - The role being attempted (for logging). * @returns {Promise<object>} The result from the successful API call. * @throws {Error} If the call fails after all retries. */ async function _attemptProviderCallWithRetries( provider, serviceType, callParams, providerName, modelId, attemptRole ) { let retries = 0; const fnName = serviceType; while (retries <= MAX_RETRIES) { try { if (getDebugFlag()) { log( 'info', `Attempt ${retries + 1}/${MAX_RETRIES + 1} calling ${fnName} (Provider: ${providerName}, Model: ${modelId}, Role: ${attemptRole})` ); } // Call the appropriate method on the provider instance const result = await provider[serviceType](callParams); if (getDebugFlag()) { log( 'info', `${fnName} succeeded for role ${attemptRole} (Provider: ${providerName}) on attempt ${retries + 1}` ); } return result; } catch (error) { log( 'warn', `Attempt ${retries + 1} failed for role ${attemptRole} (${fnName} / ${providerName}): ${error.message}` ); if (isRetryableError(error) && retries < MAX_RETRIES) { retries++; const delay = INITIAL_RETRY_DELAY_MS * Math.pow(2, retries - 1); log( 'info', `Something went wrong on the provider side. Retrying in ${delay / 1000}s...` ); await new Promise((resolve) => setTimeout(resolve, delay)); } else { log( 'error', `Something went wrong on the provider side. Max retries reached for role ${attemptRole} (${fnName} / ${providerName}).` ); throw error; } } } // Should not be reached due to throw in the else block throw new Error( `Exhausted all retries for role ${attemptRole} (${fnName} / ${providerName})` ); } /** * Base logic for unified service functions. * @param {string} serviceType - Type of service ('generateText', 'streamText', 'generateObject'). * @param {object} params - Original parameters passed to the service function. * @param {string} params.role - The initial client role. * @param {object} [params.session=null] - Optional MCP session object. * @param {string} [params.projectRoot] - Optional project root path. * @param {string} params.commandName - Name of the command invoking the service. * @param {string} params.outputType - 'cli' or 'mcp'. * @param {string} [params.systemPrompt] - Optional system prompt. * @param {string} [params.prompt] - The prompt for the AI. * @param {string} [params.schema] - The Zod schema for the expected object. * @param {string} [params.objectName] - Name for object/tool. * @returns {Promise<any>} Result from the underlying provider call. */ async function _unifiedServiceRunner(serviceType, params) { // Add debug logging at the very beginning console.log('=== _unifiedServiceRunner ENTRY ==='); console.log(`Service type: ${serviceType}`); console.log(`Params keys: ${Object.keys(params).join(', ')}`); const { role: initialRole, session, projectRoot, systemPrompt, prompt, schema, objectName, commandName, outputType, ...restApiParams } = params; console.log(`Extracted objectName: ${objectName}`); console.log(`Extracted serviceType: ${serviceType}`); console.log('=== _unifiedServiceRunner PARAMS EXTRACTED ==='); if (getDebugFlag()) { log('info', `${serviceType}Service called`, { role: initialRole, commandName, outputType, projectRoot }); } const effectiveProjectRoot = projectRoot || findProjectRoot(); const userId = getUserId(effectiveProjectRoot); // Always use agentic manual mode - external APIs are completely optional log('info', '=== AGENTIC MANUAL MODE ACTIVATED ==='); log('info', 'Using agentic manual mode as primary AI service (external APIs disabled)'); log('info', `Service type: ${serviceType}`); log('info', `Object name: ${objectName}`); log('info', `Session exists: ${!!session}`); // Also write to a debug file to see what's happening try { const fs = require('fs'); const debugLog = `[${new Date().toISOString()}] AGENTIC MODE: serviceType=${serviceType}, objectName=${objectName}, session=${!!session}\n`; fs.appendFileSync('debug-agentic.log', debugLog); } catch (e) { // Ignore file write errors } try { if (serviceType === 'generateObject') { log('info', 'Using agentic manual mode for object generation'); // For parse-prd specifically, generate appropriate task structure if (objectName === 'tasks_data') { log('info', 'Detected parse-prd operation - generating task structure using agentic manual mode'); // Generate tasks based on the PRD content const tasks = await generateTasksFromPRDAgenticMode(prompt, schema); const result = { tasks, metadata: { projectName: "PRD Implementation", totalTasks: tasks.length, sourceFile: "prd.txt", generatedAt: new Date().toISOString().split('T')[0] } }; log('info', `Generated ${tasks.length} tasks using agentic manual mode`); log('info', `Returning result: ${JSON.stringify(result, null, 2)}`); return { mainResult: result, telemetryData: null }; } // For other object types, generate appropriate structures log('info', `Generating object for type "${objectName}" using agentic manual mode`); let result; if (objectName === 'newTaskData') { // For add-task operations result = await generateTaskDataAgenticMode(prompt, schema); } else if (objectName === 'complexityAnalysis') { // For complexity analysis operations result = await generateComplexityDataAgenticMode(prompt, schema); } else { // Generic object generation result = { generated: true, objectName, timestamp: new Date().toISOString(), mode: 'agentic-manual', content: `Generated content for ${objectName} based on: ${prompt?.substring(0, 100)}...` }; } log('info', `Returning ${objectName} result: ${JSON.stringify(result, null, 2)}`); return { mainResult: result, telemetryData: null }; } else if (serviceType === 'generateText') { log('info', 'Using agentic manual mode for text generation'); const result = `Response generated using agentic manual mode for: ${prompt?.substring(0, 100)}...`; log('info', `Returning text result: ${result}`); return { mainResult: result, telemetryData: null }; } else if (serviceType === 'streamText') { log('info', 'Using agentic manual mode for stream text generation'); const result = `Stream response generated using agentic manual mode for: ${prompt?.substring(0, 100)}...`; log('info', `Returning stream result: ${result}`); return { mainResult: result, telemetryData: null }; } else { log('error', `Unknown service type: ${serviceType}`); throw new Error(`Unknown service type: ${serviceType}`); } } catch (agenticError) { log('error', `Agentic manual mode failed: ${agenticError.message}`); log('error', `Error stack: ${agenticError.stack}`); throw new Error(`Agentic manual mode failed: ${agenticError.message}`); } // External APIs are completely optional - skip the sequence logic log('info', 'External API calls are disabled - using agentic manual mode only'); // If we reach here, agentic manual mode should have handled the request above // This is a fallback in case something went wrong log('error', 'Reached external API section - this should not happen with agentic manual mode'); let lastError = new Error('Agentic manual mode did not handle the request properly'); let lastCleanErrorMessage = 'Agentic manual mode failed to process the request'; // External API calls are completely disabled - this should not be reached log('error', 'External API section reached - this indicates agentic manual mode failed to handle the request'); log('error', 'This should not happen as agentic manual mode should handle all requests'); // This should never be reached since agentic manual mode handles everything log('error', 'Reached end of _unifiedServiceRunner without handling request - this should not happen'); throw new Error('Agentic manual mode failed to handle the request properly'); } /** * Unified service function for generating text. * Handles client retrieval, retries, and fallback sequence. * * @param {object} params - Parameters for the service call. * @param {string} params.role - The initial client role ('main', 'research', 'fallback'). * @param {object} [params.session=null] - Optional MCP session object. * @param {string} [params.projectRoot=null] - Optional project root path for .env fallback. * @param {string} params.prompt - The prompt for the AI. * @param {string} [params.systemPrompt] - Optional system prompt. * @param {string} params.commandName - Name of the command invoking the service. * @param {string} [params.outputType='cli'] - 'cli' or 'mcp'. * @returns {Promise<object>} Result object containing generated text and usage data. */ async function generateTextService(params) { // Ensure default outputType if not provided const defaults = { outputType: 'cli' }; const combinedParams = { ...defaults, ...params }; // TODO: Validate commandName exists? return _unifiedServiceRunner('generateText', combinedParams); } /** * Unified service function for streaming text. * Handles client retrieval, retries, and fallback sequence. * * @param {object} params - Parameters for the service call. * @param {string} params.role - The initial client role ('main', 'research', 'fallback'). * @param {object} [params.session=null] - Optional MCP session object. * @param {string} [params.projectRoot=null] - Optional project root path for .env fallback. * @param {string} params.prompt - The prompt for the AI. * @param {string} [params.systemPrompt] - Optional system prompt. * @param {string} params.commandName - Name of the command invoking the service. * @param {string} [params.outputType='cli'] - 'cli' or 'mcp'. * @returns {Promise<object>} Result object containing the stream and usage data. */ async function streamTextService(params) { const defaults = { outputType: 'cli' }; const combinedParams = { ...defaults, ...params }; // TODO: Validate commandName exists? // NOTE: Telemetry for streaming might be tricky as usage data often comes at the end. // The current implementation logs *after* the stream is returned. // We might need to adjust how usage is captured/logged for streams. return _unifiedServiceRunner('streamText', combinedParams); } /** * Unified service function for generating structured objects. * Handles client retrieval, retries, and fallback sequence. * * @param {object} params - Parameters for the service call. * @param {string} params.role - The initial client role ('main', 'research', 'fallback'). * @param {object} [params.session=null] - Optional MCP session object. * @param {string} [params.projectRoot=null] - Optional project root path for .env fallback. * @param {import('zod').ZodSchema} params.schema - The Zod schema for the expected object. * @param {string} params.prompt - The prompt for the AI. * @param {string} [params.systemPrompt] - Optional system prompt. * @param {string} [params.objectName='generated_object'] - Name for object/tool. * @param {number} [params.maxRetries=3] - Max retries for object generation. * @param {string} params.commandName - Name of the command invoking the service. * @param {string} [params.outputType='cli'] - 'cli' or 'mcp'. * @returns {Promise<object>} Result object containing the generated object and usage data. */ async function generateObjectService(params) { const defaults = { objectName: 'generated_object', maxRetries: 3, outputType: 'cli' }; const combinedParams = { ...defaults, ...params }; // TODO: Validate commandName exists? return _unifiedServiceRunner('generateObject', combinedParams); } // --- Telemetry Function --- /** * Logs AI usage telemetry data. * For now, it just logs to the console. Sending will be implemented later. * @param {object} params - Telemetry parameters. * @param {string} params.userId - Unique user identifier. * @param {string} params.commandName - The command that triggered the AI call. * @param {string} params.providerName - The AI provider used (e.g., 'openai'). * @param {string} params.modelId - The specific AI model ID used. * @param {number} params.inputTokens - Number of input tokens. * @param {number} params.outputTokens - Number of output tokens. */ async function logAiUsage({ userId, commandName, providerName, modelId, inputTokens, outputTokens, outputType }) { try { const isMCP = outputType === 'mcp'; const timestamp = new Date().toISOString(); const totalTokens = (inputTokens || 0) + (outputTokens || 0); // Destructure currency along with costs const { inputCost, outputCost, currency } = _getCostForModel( providerName, modelId ); const totalCost = ((inputTokens || 0) / 1_000_000) * inputCost + ((outputTokens || 0) / 1_000_000) * outputCost; const telemetryData = { timestamp, userId, commandName, modelUsed: modelId, // Consistent field name from requirements providerName, // Keep provider name for context inputTokens: inputTokens || 0, outputTokens: outputTokens || 0, totalTokens, totalCost: parseFloat(totalCost.toFixed(6)), currency // Add currency to the telemetry data }; if (getDebugFlag()) { log('info', 'AI Usage Telemetry:', telemetryData); } // TODO (Subtask 77.2): Send telemetryData securely to the external endpoint. return telemetryData; } catch (error) { log('error', `Failed to log AI usage telemetry: ${error.message}`, { error }); // Don't re-throw; telemetry failure shouldn't block core functionality. return null; } } /** * Generate tasks from PRD content using agentic manual mode * @param {string} prdContent - PRD content from the prompt * @param {Object} schema - Zod schema for validation * @returns {Promise<Array>} Generated tasks */ async function generateTasksFromPRDAgenticMode(prdContent, schema) { log('info', 'Generating tasks from PRD using agentic manual mode'); // Generate a comprehensive set of tasks based on common project patterns const baseTasks = [ { id: 1, title: "Project Setup and Repository Initialization", description: "Set up the project repository, initialize version control, and configure basic project structure", details: "Create repository structure, set up .gitignore, initialize package.json or equivalent, configure basic CI/CD pipeline, and establish development environment setup documentation", testStrategy: "Verify repository is properly initialized, all necessary files are present, and development environment can be set up following documentation", priority: "high", dependencies: [] }, { id: 2, title: "Core Architecture Design and Documentation", description: "Design the core system architecture and create comprehensive technical documentation", details: "Define system architecture, create component diagrams, establish data flow patterns, design API interfaces, and document technical decisions and trade-offs", testStrategy: "Review architecture documentation with stakeholders, validate design patterns meet requirements, and ensure scalability considerations are addressed", priority: "high", dependencies: [1] }, { id: 3, title: "Database Schema Design and Implementation", description: "Design and implement the database schema based on project requirements", details: "Create entity relationship diagrams, design database tables and relationships, implement migration scripts, set up database connections, and establish data access patterns", testStrategy: "Validate schema against requirements, test migration scripts, verify data integrity constraints, and ensure proper indexing for performance", priority: "high", dependencies: [2] }, { id: 4, title: "Authentication and Authorization System", description: "Implement user authentication and role-based authorization system", details: "Set up user registration and login flows, implement JWT or session-based authentication, create role-based access control, add password security measures, and implement account management features", testStrategy: "Test authentication flows, verify authorization rules, validate security measures, and ensure proper session management", priority: "high", dependencies: [3] }, { id: 5, title: "Core API Development", description: "Develop the core API endpoints and business logic", details: "Implement REST API endpoints, create request/response models, add input validation, implement business logic, set up error handling, and add API documentation", testStrategy: "Test all API endpoints, validate request/response formats, verify error handling, and ensure proper HTTP status codes", priority: "high", dependencies: [4] }, { id: 6, title: "Frontend User Interface Development", description: "Develop the user interface and user experience components", details: "Create responsive UI components, implement navigation, add form handling, integrate with API endpoints, implement state management, and ensure accessibility compliance", testStrategy: "Test UI components across devices, verify responsive design, validate form submissions, and ensure accessibility standards are met", priority: "medium", dependencies: [5] }, { id: 7, title: "Data Processing and Business Logic", description: "Implement core data processing algorithms and business rules", details: "Develop data processing pipelines, implement business rule engines, add data validation and transformation logic, create reporting mechanisms, and optimize performance", testStrategy: "Test data processing accuracy, validate business rules, verify performance benchmarks, and ensure data integrity throughout processing", priority: "medium", dependencies: [5] }, { id: 8, title: "Integration and Third-party Services", description: "Integrate with external services and APIs required by the project", details: "Implement third-party API integrations, set up webhook handlers, add external service authentication, implement retry and error handling for external calls, and create service monitoring", testStrategy: "Test all external integrations, verify error handling for service failures, validate webhook processing, and ensure proper rate limiting", priority: "medium", dependencies: [7] }, { id: 9, title: "Testing Infrastructure and Test Suite", description: "Establish comprehensive testing infrastructure and create test suites", details: "Set up unit testing framework, create integration tests, implement end-to-end testing, add performance testing, establish test data management, and configure continuous testing", testStrategy: "Verify test coverage meets requirements, validate test reliability, ensure tests run in CI/CD pipeline, and confirm test data isolation", priority: "high", dependencies: [8] }, { id: 10, title: "Security Implementation and Hardening", description: "Implement security measures and perform security hardening", details: "Add input sanitization, implement CSRF protection, set up rate limiting, add security headers, perform vulnerability scanning, and implement security monitoring", testStrategy: "Conduct security testing, perform penetration testing, verify security headers, and validate protection against common vulnerabilities", priority: "high", dependencies: [9] }, { id: 11, title: "Performance Optimization and Monitoring", description: "Optimize system performance and implement monitoring solutions", details: "Profile application performance, optimize database queries, implement caching strategies, set up application monitoring, add performance metrics, and create alerting systems", testStrategy: "Conduct performance testing, verify monitoring accuracy, validate alerting thresholds, and ensure performance meets requirements", priority: "medium", dependencies: [10] }, { id: 12, title: "Documentation and User Guides", description: "Create comprehensive documentation and user guides", details: "Write API documentation, create user manuals, develop deployment guides, document configuration options, create troubleshooting guides, and establish documentation maintenance processes", testStrategy: "Review documentation accuracy, validate setup procedures, test troubleshooting guides, and ensure documentation completeness", priority: "medium", dependencies: [11] }, { id: 13, title: "Deployment and DevOps Setup", description: "Set up production deployment pipeline and DevOps infrastructure", details: "Configure production environment, set up CI/CD pipelines, implement automated deployments, configure monitoring and logging, set up backup systems, and establish rollback procedures", testStrategy: "Test deployment procedures, verify monitoring and alerting, validate backup and restore processes, and ensure rollback capabilities", priority: "high", dependencies: [12] }, { id: 14, title: "User Acceptance Testing and Quality Assurance", description: "Conduct comprehensive user acceptance testing and quality assurance", details: "Create UAT test plans, conduct user testing sessions, gather feedback, perform regression testing, validate requirements compliance, and document test results", testStrategy: "Execute all UAT scenarios, validate user feedback incorporation, verify requirements traceability, and ensure quality standards are met", priority: "high", dependencies: [13] }, { id: 15, title: "Production Launch and Go-Live", description: "Execute production launch and monitor initial go-live period", details: "Deploy to production environment, monitor system performance, provide user support, gather initial feedback, address immediate issues, and document lessons learned", testStrategy: "Monitor system stability, track user adoption, verify performance metrics, and ensure support processes are effective", priority: "high", dependencies: [14] } ]; // Customize tasks based on project content if available if (prdContent) { log('info', 'Customizing tasks based on PRD content'); // Add project-specific customizations here // For now, we'll use the base tasks } log('info', `Generated ${baseTasks.length} tasks using agentic manual mode`); return baseTasks; } /** * Generate task data for add-task operations using agentic manual mode * @param {string} prompt - User prompt for task creation * @param {Object} schema - Zod schema for validation * @returns {Promise<Object>} Generated task data */ async function generateTaskDataAgenticMode(prompt, schema) { log('info', 'Generating task data using agentic manual mode'); // Extract key information from the prompt const promptLower = prompt.toLowerCase(); // Determine priority based on keywords let priority = 'medium'; if (promptLower.includes('urgent') || promptLower.includes('critical') || promptLower.includes('high priority')) { priority = 'high'; } else if (promptLower.includes('low priority') || promptLower.includes('nice to have') || promptLower.includes('optional')) { priority = 'low'; } // Generate title from prompt (first sentence or up to 80 chars) let title = prompt.split('.')[0].trim(); if (title.length > 80) { title = title.substring(0, 77) + '...'; } // Generate description const description = prompt.length > 100 ? prompt.substring(0, 200) + '...' : prompt; // Generate implementation details const details = `Implementation details for: ${title} Key requirements: - Analyze the requirements thoroughly - Design the solution architecture - Implement the core functionality - Add comprehensive testing - Document the implementation - Ensure code quality and best practices Based on user request: "${prompt}"`; // Generate test strategy const testStrategy = `Testing strategy for: ${title} 1. Unit Tests: - Test core functionality - Test edge cases and error handling - Verify input validation 2. Integration Tests: - Test component interactions - Verify data flow - Test API endpoints if applicable 3. User Acceptance Tests: - Verify requirements are met - Test user workflows - Validate user experience`; const taskData = { title, description, details, testStrategy, priority, dependencies: [] }; return { object: taskData }; } /** * Generate complexity analysis data using agentic manual mode * @param {string} prompt - Analysis prompt * @param {Object} schema - Zod schema for validation * @returns {Promise<Object>} Generated complexity data */ async function generateComplexityDataAgenticMode(prompt, schema) { log('info', 'Generating complexity analysis using agentic manual mode'); // Generate a basic complexity analysis structure const complexityData = { analysisDate: new Date().toISOString().split('T')[0], totalTasks: 0, averageComplexity: 5.0, highComplexityTasks: [], recommendations: [ "Break down complex tasks into smaller subtasks", "Define clear acceptance criteria", "Implement proper testing strategies", "Document implementation details thoroughly" ], mode: 'agentic-manual' }; return complexityData; } export { generateTextService, streamTextService, generateObjectService, logAiUsage };