claude-task-master/scripts/modules/config-manager.js

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import fs from 'fs';
import path from 'path';
import chalk from 'chalk';
import { fileURLToPath } from 'url';
import { log, findProjectRoot, resolveEnvVariable } from './utils.js';
// Calculate __dirname in ESM
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
// Load supported models from JSON file using the calculated __dirname
let MODEL_MAP;
try {
const supportedModelsRaw = fs.readFileSync(
path.join(__dirname, 'supported-models.json'),
'utf-8'
);
MODEL_MAP = JSON.parse(supportedModelsRaw);
} catch (error) {
console.error(
chalk.red(
'FATAL ERROR: Could not load supported-models.json. Please ensure the file exists and is valid JSON.'
),
error
);
MODEL_MAP = {}; // Default to empty map on error to avoid crashing, though functionality will be limited
process.exit(1); // Exit if models can't be loaded
}
const CONFIG_FILE_NAME = '.taskmasterconfig';
// Define valid providers dynamically from the loaded MODEL_MAP
const VALID_PROVIDERS = Object.keys(MODEL_MAP || {});
// Default configuration values (used if .taskmasterconfig is missing or incomplete)
const DEFAULTS = {
models: {
main: {
provider: 'anthropic',
modelId: 'claude-3-7-sonnet-20250219',
maxTokens: 64000,
temperature: 0.2
},
research: {
provider: 'perplexity',
modelId: 'sonar-pro',
maxTokens: 8700,
temperature: 0.1
},
fallback: {
// No default fallback provider/model initially
provider: 'anthropic',
modelId: 'claude-3-5-sonnet',
maxTokens: 64000, // Default parameters if fallback IS configured
temperature: 0.2
}
},
global: {
logLevel: 'info',
debug: false,
defaultSubtasks: 5,
defaultPriority: 'medium',
projectName: 'Task Master',
ollamaBaseUrl: 'http://localhost:11434/api'
}
};
// --- Internal Config Loading ---
let loadedConfig = null;
let loadedConfigRoot = null; // Track which root loaded the config
// Custom Error for configuration issues
class ConfigurationError extends Error {
constructor(message) {
super(message);
this.name = 'ConfigurationError';
}
}
function _loadAndValidateConfig(explicitRoot = null) {
const defaults = DEFAULTS; // Use the defined defaults
let rootToUse = explicitRoot;
let configSource = explicitRoot
? `explicit root (${explicitRoot})`
: 'defaults (no root provided yet)';
// ---> If no explicit root, TRY to find it <---
if (!rootToUse) {
rootToUse = findProjectRoot();
if (rootToUse) {
configSource = `found root (${rootToUse})`;
} else {
// No root found, return defaults immediately
return defaults;
}
}
// ---> End find project root logic <---
// --- Proceed with loading from the determined rootToUse ---
const configPath = path.join(rootToUse, CONFIG_FILE_NAME);
let config = { ...defaults }; // Start with a deep copy of defaults
let configExists = false;
if (fs.existsSync(configPath)) {
configExists = true;
try {
const rawData = fs.readFileSync(configPath, 'utf-8');
const parsedConfig = JSON.parse(rawData);
// Deep merge parsed config onto defaults
config = {
models: {
main: { ...defaults.models.main, ...parsedConfig?.models?.main },
research: {
...defaults.models.research,
...parsedConfig?.models?.research
},
fallback:
parsedConfig?.models?.fallback?.provider &&
parsedConfig?.models?.fallback?.modelId
? { ...defaults.models.fallback, ...parsedConfig.models.fallback }
: { ...defaults.models.fallback }
},
global: { ...defaults.global, ...parsedConfig?.global }
};
configSource = `file (${configPath})`; // Update source info
// --- Validation (Warn if file content is invalid) ---
// Use log.warn for consistency
if (!validateProvider(config.models.main.provider)) {
console.warn(
chalk.yellow(
`Warning: Invalid main provider "${config.models.main.provider}" in ${configPath}. Falling back to default.`
)
);
config.models.main = { ...defaults.models.main };
}
if (!validateProvider(config.models.research.provider)) {
console.warn(
chalk.yellow(
`Warning: Invalid research provider "${config.models.research.provider}" in ${configPath}. Falling back to default.`
)
);
config.models.research = { ...defaults.models.research };
}
if (
config.models.fallback?.provider &&
!validateProvider(config.models.fallback.provider)
) {
console.warn(
chalk.yellow(
`Warning: Invalid fallback provider "${config.models.fallback.provider}" in ${configPath}. Fallback model configuration will be ignored.`
)
);
config.models.fallback.provider = undefined;
config.models.fallback.modelId = undefined;
}
} catch (error) {
// Use console.error for actual errors during parsing
console.error(
chalk.red(
`Error reading or parsing ${configPath}: ${error.message}. Using default configuration.`
)
);
config = { ...defaults }; // Reset to defaults on parse error
configSource = `defaults (parse error at ${configPath})`;
}
} else {
// Config file doesn't exist at the determined rootToUse.
if (explicitRoot) {
// Only warn if an explicit root was *expected*.
console.warn(
chalk.yellow(
`Warning: ${CONFIG_FILE_NAME} not found at provided project root (${explicitRoot}). Using default configuration. Run 'task-master models --setup' to configure.`
)
);
} else {
console.warn(
chalk.yellow(
`Warning: ${CONFIG_FILE_NAME} not found at derived root (${rootToUse}). Using defaults.`
)
);
}
// Keep config as defaults
config = { ...defaults };
configSource = `defaults (file not found at ${configPath})`;
}
return config;
}
/**
* Gets the current configuration, loading it if necessary.
* Handles MCP initialization context gracefully.
* @param {string|null} explicitRoot - Optional explicit path to the project root.
* @param {boolean} forceReload - Force reloading the config file.
* @returns {object} The loaded configuration object.
*/
function getConfig(explicitRoot = null, forceReload = false) {
// Determine if a reload is necessary
const needsLoad =
!loadedConfig ||
forceReload ||
(explicitRoot && explicitRoot !== loadedConfigRoot);
if (needsLoad) {
const newConfig = _loadAndValidateConfig(explicitRoot); // _load handles null explicitRoot
// Only update the global cache if loading was forced or if an explicit root
// was provided (meaning we attempted to load a specific project's config).
// We avoid caching the initial default load triggered without an explicitRoot.
if (forceReload || explicitRoot) {
loadedConfig = newConfig;
loadedConfigRoot = explicitRoot; // Store the root used for this loaded config
}
return newConfig; // Return the newly loaded/default config
}
// If no load was needed, return the cached config
return loadedConfig;
}
/**
* Validates if a provider name is in the list of supported providers.
* @param {string} providerName The name of the provider.
* @returns {boolean} True if the provider is valid, false otherwise.
*/
function validateProvider(providerName) {
return VALID_PROVIDERS.includes(providerName);
}
/**
* Optional: Validates if a modelId is known for a given provider based on MODEL_MAP.
* This is a non-strict validation; an unknown model might still be valid.
* @param {string} providerName The name of the provider.
* @param {string} modelId The model ID.
* @returns {boolean} True if the modelId is in the map for the provider, false otherwise.
*/
function validateProviderModelCombination(providerName, modelId) {
// If provider isn't even in our map, we can't validate the model
if (!MODEL_MAP[providerName]) {
return true; // Allow unknown providers or those without specific model lists
}
// If the provider is known, check if the model is in its list OR if the list is empty (meaning accept any)
return (
MODEL_MAP[providerName].length === 0 ||
// Use .some() to check the 'id' property of objects in the array
MODEL_MAP[providerName].some((modelObj) => modelObj.id === modelId)
);
}
// --- Role-Specific Getters ---
function getModelConfigForRole(role, explicitRoot = null) {
const config = getConfig(explicitRoot);
const roleConfig = config?.models?.[role];
if (!roleConfig) {
log(
'warn',
`No model configuration found for role: ${role}. Returning default.`
);
return DEFAULTS.models[role] || {};
}
return roleConfig;
}
function getMainProvider(explicitRoot = null) {
return getModelConfigForRole('main', explicitRoot).provider;
}
function getMainModelId(explicitRoot = null) {
return getModelConfigForRole('main', explicitRoot).modelId;
}
function getMainMaxTokens(explicitRoot = null) {
// Directly return value from config (which includes defaults)
return getModelConfigForRole('main', explicitRoot).maxTokens;
}
function getMainTemperature(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('main', explicitRoot).temperature;
}
function getResearchProvider(explicitRoot = null) {
return getModelConfigForRole('research', explicitRoot).provider;
}
function getResearchModelId(explicitRoot = null) {
return getModelConfigForRole('research', explicitRoot).modelId;
}
function getResearchMaxTokens(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('research', explicitRoot).maxTokens;
}
function getResearchTemperature(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('research', explicitRoot).temperature;
}
function getFallbackProvider(explicitRoot = null) {
// Directly return value from config (will be undefined if not set)
return getModelConfigForRole('fallback', explicitRoot).provider;
}
function getFallbackModelId(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('fallback', explicitRoot).modelId;
}
function getFallbackMaxTokens(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('fallback', explicitRoot).maxTokens;
}
function getFallbackTemperature(explicitRoot = null) {
// Directly return value from config
return getModelConfigForRole('fallback', explicitRoot).temperature;
}
// --- Global Settings Getters ---
function getGlobalConfig(explicitRoot = null) {
const config = getConfig(explicitRoot);
// Ensure global defaults are applied if global section is missing
return { ...DEFAULTS.global, ...(config?.global || {}) };
}
function getLogLevel(explicitRoot = null) {
// Directly return value from config
return getGlobalConfig(explicitRoot).logLevel.toLowerCase();
}
function getDebugFlag(explicitRoot = null) {
// Directly return value from config, ensure boolean
return getGlobalConfig(explicitRoot).debug === true;
}
function getDefaultSubtasks(explicitRoot = null) {
// Directly return value from config, ensure integer
const val = getGlobalConfig(explicitRoot).defaultSubtasks;
const parsedVal = parseInt(val, 10);
return isNaN(parsedVal) ? DEFAULTS.global.defaultSubtasks : parsedVal;
}
function getDefaultNumTasks(explicitRoot = null) {
const val = getGlobalConfig(explicitRoot).defaultNumTasks;
const parsedVal = parseInt(val, 10);
return isNaN(parsedVal) ? DEFAULTS.global.defaultNumTasks : parsedVal;
}
function getDefaultPriority(explicitRoot = null) {
// Directly return value from config
return getGlobalConfig(explicitRoot).defaultPriority;
}
function getProjectName(explicitRoot = null) {
// Directly return value from config
return getGlobalConfig(explicitRoot).projectName;
}
function getOllamaBaseUrl(explicitRoot = null) {
// Directly return value from config
return getGlobalConfig(explicitRoot).ollamaBaseUrl;
}
/**
* Gets model parameters (maxTokens, temperature) for a specific role,
* considering model-specific overrides from supported-models.json.
* @param {string} role - The role ('main', 'research', 'fallback').
* @param {string|null} explicitRoot - Optional explicit path to the project root.
* @returns {{maxTokens: number, temperature: number}}
*/
function getParametersForRole(role, explicitRoot = null) {
const roleConfig = getModelConfigForRole(role, explicitRoot);
const roleMaxTokens = roleConfig.maxTokens;
const roleTemperature = roleConfig.temperature;
const modelId = roleConfig.modelId;
const providerName = roleConfig.provider;
let effectiveMaxTokens = roleMaxTokens; // Start with the role's default
try {
// Find the model definition in MODEL_MAP
const providerModels = MODEL_MAP[providerName];
if (providerModels && Array.isArray(providerModels)) {
const modelDefinition = providerModels.find((m) => m.id === modelId);
// Check if a model-specific max_tokens is defined and valid
if (
modelDefinition &&
typeof modelDefinition.max_tokens === 'number' &&
modelDefinition.max_tokens > 0
) {
const modelSpecificMaxTokens = modelDefinition.max_tokens;
// Use the minimum of the role default and the model specific limit
effectiveMaxTokens = Math.min(roleMaxTokens, modelSpecificMaxTokens);
log(
'debug',
`Applying model-specific max_tokens (${modelSpecificMaxTokens}) for ${modelId}. Effective limit: ${effectiveMaxTokens}`
);
} else {
log(
'debug',
`No valid model-specific max_tokens override found for ${modelId}. Using role default: ${roleMaxTokens}`
);
}
} else {
log(
'debug',
`No model definitions found for provider ${providerName} in MODEL_MAP. Using role default maxTokens: ${roleMaxTokens}`
);
}
} catch (lookupError) {
log(
'warn',
`Error looking up model-specific max_tokens for ${modelId}: ${lookupError.message}. Using role default: ${roleMaxTokens}`
);
// Fallback to role default on error
effectiveMaxTokens = roleMaxTokens;
}
return {
maxTokens: effectiveMaxTokens,
temperature: roleTemperature
};
}
/**
* Checks if the API key for a given provider is set in the environment.
* Checks process.env first, then session.env if session is provided, then .env file if projectRoot provided.
* @param {string} providerName - The name of the provider (e.g., 'openai', 'anthropic').
* @param {object|null} [session=null] - The MCP session object (optional).
* @param {string|null} [projectRoot=null] - The project root directory (optional, for .env file check).
* @returns {boolean} True if the API key is set, false otherwise.
*/
function isApiKeySet(providerName, session = null, projectRoot = null) {
// Define the expected environment variable name for each provider
if (providerName?.toLowerCase() === 'ollama') {
return true; // Indicate key status is effectively "OK"
}
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'
// Add other providers as needed
};
const providerKey = providerName?.toLowerCase();
if (!providerKey || !keyMap[providerKey]) {
log('warn', `Unknown provider name: ${providerName} in isApiKeySet check.`);
return false;
}
const envVarName = keyMap[providerKey];
const apiKeyValue = resolveEnvVariable(envVarName, session, projectRoot);
// Check if the key exists, is not empty, and is not a placeholder
return (
apiKeyValue &&
apiKeyValue.trim() !== '' &&
!/YOUR_.*_API_KEY_HERE/.test(apiKeyValue) && // General placeholder check
!apiKeyValue.includes('KEY_HERE')
); // Another common placeholder pattern
}
/**
* Checks the API key status within .cursor/mcp.json for a given provider.
* Reads the mcp.json file, finds the taskmaster-ai server config, and checks the relevant env var.
* @param {string} providerName The name of the provider.
* @param {string|null} projectRoot - Optional explicit path to the project root.
* @returns {boolean} True if the key exists and is not a placeholder, false otherwise.
*/
function getMcpApiKeyStatus(providerName, projectRoot = null) {
const rootDir = projectRoot || findProjectRoot(); // Use existing root finding
if (!rootDir) {
console.warn(
chalk.yellow('Warning: Could not find project root to check mcp.json.')
);
return false; // Cannot check without root
}
const mcpConfigPath = path.join(rootDir, '.cursor', 'mcp.json');
if (!fs.existsSync(mcpConfigPath)) {
// console.warn(chalk.yellow('Warning: .cursor/mcp.json not found.'));
return false; // File doesn't exist
}
try {
const mcpConfigRaw = fs.readFileSync(mcpConfigPath, 'utf-8');
const mcpConfig = JSON.parse(mcpConfigRaw);
const mcpEnv = mcpConfig?.mcpServers?.['taskmaster-ai']?.env;
if (!mcpEnv) {
// console.warn(chalk.yellow('Warning: Could not find taskmaster-ai env in mcp.json.'));
return false; // Structure missing
}
let apiKeyToCheck = null;
let placeholderValue = null;
switch (providerName) {
case 'anthropic':
apiKeyToCheck = mcpEnv.ANTHROPIC_API_KEY;
placeholderValue = 'YOUR_ANTHROPIC_API_KEY_HERE';
break;
case 'openai':
apiKeyToCheck = mcpEnv.OPENAI_API_KEY;
placeholderValue = 'YOUR_OPENAI_API_KEY_HERE'; // Assuming placeholder matches OPENAI
break;
docs: Update documentation for new AI/config architecture and finalize cleanup This commit updates all relevant documentation (READMEs, docs/*, .cursor/rules) to accurately reflect the finalized unified AI service architecture and the new configuration system (.taskmasterconfig + .env/mcp.json). It also includes the final code cleanup steps related to the refactoring. Key Changes: 1. **Documentation Updates:** * Revised `README.md`, `README-task-master.md`, `assets/scripts_README.md`, `docs/configuration.md`, and `docs/tutorial.md` to explain the new configuration split (.taskmasterconfig vs .env/mcp.json). * Updated MCP configuration examples in READMEs and tutorials to only include API keys in the `env` block. * Added/updated examples for using the `--research` flag in `docs/command-reference.md`, `docs/examples.md`, and `docs/tutorial.md`. * Updated `.cursor/rules/ai_services.mdc`, `.cursor/rules/architecture.mdc`, `.cursor/rules/dev_workflow.mdc`, `.cursor/rules/mcp.mdc`, `.cursor/rules/taskmaster.mdc`, `.cursor/rules/utilities.mdc`, and `.cursor/rules/new_features.mdc` to align with the new architecture, removing references to old patterns/files. * Removed internal rule links from user-facing rules (`taskmaster.mdc`, `dev_workflow.mdc`, `self_improve.mdc`). * Deleted outdated example file `docs/ai-client-utils-example.md`. 2. **Final Code Refactor & Cleanup:** * Corrected `update-task-by-id.js` by removing the last import from the old `ai-services.js`. * Refactored `update-subtask-by-id.js` to correctly use the unified service and logger patterns. * Removed the obsolete export block from `mcp-server/src/core/task-master-core.js`. * Corrected logger implementation in `update-tasks.js` for CLI context. * Updated API key mapping in `config-manager.js` and `ai-services-unified.js`. 3. **Configuration Files:** * Updated API keys in `.cursor/mcp.json`, replacing `GROK_API_KEY` with `XAI_API_KEY`. * Updated `.env.example` with current API key names. * Added `azureOpenaiBaseUrl` to `.taskmasterconfig` example. 4. **Task Management:** * Marked documentation subtask 61.10 as 'done'. * Includes various other task content/status updates from the diff summary. 5. **Changeset:** * Added `.changeset/cuddly-zebras-matter.md` for user-facing `expand`/`expand-all` improvements. This commit concludes the major architectural refactoring (Task 61) and ensures the documentation accurately reflects the current system.
2025-04-25 14:43:12 -04:00
case 'openrouter':
apiKeyToCheck = mcpEnv.OPENROUTER_API_KEY;
placeholderValue = 'YOUR_OPENROUTER_API_KEY_HERE';
break;
case 'google':
apiKeyToCheck = mcpEnv.GOOGLE_API_KEY;
placeholderValue = 'YOUR_GOOGLE_API_KEY_HERE';
break;
case 'perplexity':
apiKeyToCheck = mcpEnv.PERPLEXITY_API_KEY;
placeholderValue = 'YOUR_PERPLEXITY_API_KEY_HERE';
break;
case 'xai':
docs: Update documentation for new AI/config architecture and finalize cleanup This commit updates all relevant documentation (READMEs, docs/*, .cursor/rules) to accurately reflect the finalized unified AI service architecture and the new configuration system (.taskmasterconfig + .env/mcp.json). It also includes the final code cleanup steps related to the refactoring. Key Changes: 1. **Documentation Updates:** * Revised `README.md`, `README-task-master.md`, `assets/scripts_README.md`, `docs/configuration.md`, and `docs/tutorial.md` to explain the new configuration split (.taskmasterconfig vs .env/mcp.json). * Updated MCP configuration examples in READMEs and tutorials to only include API keys in the `env` block. * Added/updated examples for using the `--research` flag in `docs/command-reference.md`, `docs/examples.md`, and `docs/tutorial.md`. * Updated `.cursor/rules/ai_services.mdc`, `.cursor/rules/architecture.mdc`, `.cursor/rules/dev_workflow.mdc`, `.cursor/rules/mcp.mdc`, `.cursor/rules/taskmaster.mdc`, `.cursor/rules/utilities.mdc`, and `.cursor/rules/new_features.mdc` to align with the new architecture, removing references to old patterns/files. * Removed internal rule links from user-facing rules (`taskmaster.mdc`, `dev_workflow.mdc`, `self_improve.mdc`). * Deleted outdated example file `docs/ai-client-utils-example.md`. 2. **Final Code Refactor & Cleanup:** * Corrected `update-task-by-id.js` by removing the last import from the old `ai-services.js`. * Refactored `update-subtask-by-id.js` to correctly use the unified service and logger patterns. * Removed the obsolete export block from `mcp-server/src/core/task-master-core.js`. * Corrected logger implementation in `update-tasks.js` for CLI context. * Updated API key mapping in `config-manager.js` and `ai-services-unified.js`. 3. **Configuration Files:** * Updated API keys in `.cursor/mcp.json`, replacing `GROK_API_KEY` with `XAI_API_KEY`. * Updated `.env.example` with current API key names. * Added `azureOpenaiBaseUrl` to `.taskmasterconfig` example. 4. **Task Management:** * Marked documentation subtask 61.10 as 'done'. * Includes various other task content/status updates from the diff summary. 5. **Changeset:** * Added `.changeset/cuddly-zebras-matter.md` for user-facing `expand`/`expand-all` improvements. This commit concludes the major architectural refactoring (Task 61) and ensures the documentation accurately reflects the current system.
2025-04-25 14:43:12 -04:00
apiKeyToCheck = mcpEnv.XAI_API_KEY;
placeholderValue = 'YOUR_XAI_API_KEY_HERE';
break;
case 'ollama':
return true; // No key needed
docs: Update documentation for new AI/config architecture and finalize cleanup This commit updates all relevant documentation (READMEs, docs/*, .cursor/rules) to accurately reflect the finalized unified AI service architecture and the new configuration system (.taskmasterconfig + .env/mcp.json). It also includes the final code cleanup steps related to the refactoring. Key Changes: 1. **Documentation Updates:** * Revised `README.md`, `README-task-master.md`, `assets/scripts_README.md`, `docs/configuration.md`, and `docs/tutorial.md` to explain the new configuration split (.taskmasterconfig vs .env/mcp.json). * Updated MCP configuration examples in READMEs and tutorials to only include API keys in the `env` block. * Added/updated examples for using the `--research` flag in `docs/command-reference.md`, `docs/examples.md`, and `docs/tutorial.md`. * Updated `.cursor/rules/ai_services.mdc`, `.cursor/rules/architecture.mdc`, `.cursor/rules/dev_workflow.mdc`, `.cursor/rules/mcp.mdc`, `.cursor/rules/taskmaster.mdc`, `.cursor/rules/utilities.mdc`, and `.cursor/rules/new_features.mdc` to align with the new architecture, removing references to old patterns/files. * Removed internal rule links from user-facing rules (`taskmaster.mdc`, `dev_workflow.mdc`, `self_improve.mdc`). * Deleted outdated example file `docs/ai-client-utils-example.md`. 2. **Final Code Refactor & Cleanup:** * Corrected `update-task-by-id.js` by removing the last import from the old `ai-services.js`. * Refactored `update-subtask-by-id.js` to correctly use the unified service and logger patterns. * Removed the obsolete export block from `mcp-server/src/core/task-master-core.js`. * Corrected logger implementation in `update-tasks.js` for CLI context. * Updated API key mapping in `config-manager.js` and `ai-services-unified.js`. 3. **Configuration Files:** * Updated API keys in `.cursor/mcp.json`, replacing `GROK_API_KEY` with `XAI_API_KEY`. * Updated `.env.example` with current API key names. * Added `azureOpenaiBaseUrl` to `.taskmasterconfig` example. 4. **Task Management:** * Marked documentation subtask 61.10 as 'done'. * Includes various other task content/status updates from the diff summary. 5. **Changeset:** * Added `.changeset/cuddly-zebras-matter.md` for user-facing `expand`/`expand-all` improvements. This commit concludes the major architectural refactoring (Task 61) and ensures the documentation accurately reflects the current system.
2025-04-25 14:43:12 -04:00
case 'mistral':
apiKeyToCheck = mcpEnv.MISTRAL_API_KEY;
placeholderValue = 'YOUR_MISTRAL_API_KEY_HERE';
break;
case 'azure':
apiKeyToCheck = mcpEnv.AZURE_OPENAI_API_KEY;
placeholderValue = 'YOUR_AZURE_OPENAI_API_KEY_HERE';
break;
default:
return false; // Unknown provider
}
return !!apiKeyToCheck && !/KEY_HERE$/.test(apiKeyToCheck);
} catch (error) {
console.error(
chalk.red(`Error reading or parsing .cursor/mcp.json: ${error.message}`)
);
return false;
}
}
/**
* Gets a list of available models based on the MODEL_MAP.
* @returns {Array<{id: string, name: string, provider: string, swe_score: number|null, cost_per_1m_tokens: {input: number|null, output: number|null}|null, allowed_roles: string[]}>}
*/
function getAvailableModels() {
const available = [];
for (const [provider, models] of Object.entries(MODEL_MAP)) {
if (models.length > 0) {
models.forEach((modelObj) => {
// Basic name generation - can be improved
const modelId = modelObj.id;
const sweScore = modelObj.swe_score;
const cost = modelObj.cost_per_1m_tokens;
const allowedRoles = modelObj.allowed_roles || ['main', 'fallback'];
const nameParts = modelId
.split('-')
.map((p) => p.charAt(0).toUpperCase() + p.slice(1));
// Handle specific known names better if needed
let name = nameParts.join(' ');
if (modelId === 'claude-3.5-sonnet-20240620')
name = 'Claude 3.5 Sonnet';
if (modelId === 'claude-3-7-sonnet-20250219')
name = 'Claude 3.7 Sonnet';
if (modelId === 'gpt-4o') name = 'GPT-4o';
if (modelId === 'gpt-4-turbo') name = 'GPT-4 Turbo';
if (modelId === 'sonar-pro') name = 'Perplexity Sonar Pro';
if (modelId === 'sonar-mini') name = 'Perplexity Sonar Mini';
available.push({
id: modelId,
name: name,
provider: provider,
swe_score: sweScore,
cost_per_1m_tokens: cost,
allowed_roles: allowedRoles
});
});
} else {
// For providers with empty lists (like ollama), maybe add a placeholder or skip
available.push({
id: `[${provider}-any]`,
name: `Any (${provider})`,
provider: provider
});
}
}
return available;
}
/**
* Writes the configuration object to the file.
* @param {Object} config The configuration object to write.
* @param {string|null} explicitRoot - Optional explicit path to the project root.
* @returns {boolean} True if successful, false otherwise.
*/
function writeConfig(config, explicitRoot = null) {
// ---> Determine root path reliably <---
let rootPath = explicitRoot;
if (explicitRoot === null || explicitRoot === undefined) {
// Logic matching _loadAndValidateConfig
const foundRoot = findProjectRoot(); // *** Explicitly call findProjectRoot ***
if (!foundRoot) {
console.error(
chalk.red(
'Error: Could not determine project root. Configuration not saved.'
)
);
return false;
}
rootPath = foundRoot;
}
// ---> End determine root path logic <---
const configPath =
path.basename(rootPath) === CONFIG_FILE_NAME
? rootPath
: path.join(rootPath, CONFIG_FILE_NAME);
try {
fs.writeFileSync(configPath, JSON.stringify(config, null, 2));
loadedConfig = config; // Update the cache after successful write
return true;
} catch (error) {
console.error(
chalk.red(
`Error writing configuration to ${configPath}: ${error.message}`
)
);
return false;
}
}
/**
* Checks if the .taskmasterconfig file exists at the project root
* @param {string|null} explicitRoot - Optional explicit path to the project root
* @returns {boolean} True if the file exists, false otherwise
*/
function isConfigFilePresent(explicitRoot = null) {
// ---> Determine root path reliably <---
let rootPath = explicitRoot;
if (explicitRoot === null || explicitRoot === undefined) {
// Logic matching _loadAndValidateConfig
const foundRoot = findProjectRoot(); // *** Explicitly call findProjectRoot ***
if (!foundRoot) {
return false; // Cannot check if root doesn't exist
}
rootPath = foundRoot;
}
// ---> End determine root path logic <---
const configPath = path.join(rootPath, CONFIG_FILE_NAME);
return fs.existsSync(configPath);
}
feat(telemetry): Implement AI usage telemetry pattern and apply to add-task This commit introduces a standardized pattern for capturing and propagating AI usage telemetry (cost, tokens, model used) across the Task Master stack and applies it to the 'add-task' functionality. Key changes include: - **Telemetry Pattern Definition:** - Added defining the integration pattern for core logic, direct functions, MCP tools, and CLI commands. - Updated related rules (, , Usage: mcp [OPTIONS] COMMAND [ARGS]... MCP development tools ╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ --help Show this message and exit. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭─ Commands ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ version Show the MCP version. │ │ dev Run a MCP server with the MCP Inspector. │ │ run Run a MCP server. │ │ install Install a MCP server in the Claude desktop app. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯, , ) to reference the new telemetry rule. - **Core Telemetry Implementation ():** - Refactored the unified AI service to generate and return a object alongside the main AI result. - Fixed an MCP server startup crash by removing redundant local loading of and instead using the imported from for cost calculations. - Added to the object. - ** Integration:** - Modified (core) to receive from the AI service, return it, and call the new UI display function for CLI output. - Updated to receive from the core function and include it in the payload of its response. - Ensured (MCP tool) correctly passes the through via . - Updated to correctly pass context (, ) to the core function and rely on it for CLI telemetry display. - **UI Enhancement:** - Added function to to show telemetry details in the CLI. - **Project Management:** - Added subtasks 77.6 through 77.12 to track the rollout of this telemetry pattern to other AI-powered commands (, , , , , , ). This establishes the foundation for tracking AI usage across the application.
2025-05-07 13:41:25 -04:00
/**
* Gets the user ID from the configuration.
* @param {string|null} explicitRoot - Optional explicit path to the project root.
* @returns {string|null} The user ID or null if not found.
*/
function getUserId(explicitRoot = null) {
const config = getConfig(explicitRoot);
if (!config.global) {
config.global = {}; // Ensure global object exists
}
if (!config.global.userId) {
config.global.userId = '1234567890';
// Attempt to write the updated config.
// It's important that writeConfig correctly resolves the path
// using explicitRoot, similar to how getConfig does.
const success = writeConfig(config, explicitRoot);
if (!success) {
// Log an error or handle the failure to write,
// though for now, we'll proceed with the in-memory default.
log(
'warning',
'Failed to write updated configuration with new userId. Please let the developers know.'
);
}
}
return config.global.userId;
feat(telemetry): Implement AI usage telemetry pattern and apply to add-task This commit introduces a standardized pattern for capturing and propagating AI usage telemetry (cost, tokens, model used) across the Task Master stack and applies it to the 'add-task' functionality. Key changes include: - **Telemetry Pattern Definition:** - Added defining the integration pattern for core logic, direct functions, MCP tools, and CLI commands. - Updated related rules (, , Usage: mcp [OPTIONS] COMMAND [ARGS]... MCP development tools ╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ --help Show this message and exit. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭─ Commands ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ version Show the MCP version. │ │ dev Run a MCP server with the MCP Inspector. │ │ run Run a MCP server. │ │ install Install a MCP server in the Claude desktop app. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯, , ) to reference the new telemetry rule. - **Core Telemetry Implementation ():** - Refactored the unified AI service to generate and return a object alongside the main AI result. - Fixed an MCP server startup crash by removing redundant local loading of and instead using the imported from for cost calculations. - Added to the object. - ** Integration:** - Modified (core) to receive from the AI service, return it, and call the new UI display function for CLI output. - Updated to receive from the core function and include it in the payload of its response. - Ensured (MCP tool) correctly passes the through via . - Updated to correctly pass context (, ) to the core function and rely on it for CLI telemetry display. - **UI Enhancement:** - Added function to to show telemetry details in the CLI. - **Project Management:** - Added subtasks 77.6 through 77.12 to track the rollout of this telemetry pattern to other AI-powered commands (, , , , , , ). This establishes the foundation for tracking AI usage across the application.
2025-05-07 13:41:25 -04:00
}
/**
* Gets a list of all provider names defined in the MODEL_MAP.
* @returns {string[]} An array of provider names.
*/
function getAllProviders() {
return Object.keys(MODEL_MAP || {});
}
function getBaseUrlForRole(role, explicitRoot = null) {
const roleConfig = getModelConfigForRole(role, explicitRoot);
return roleConfig && typeof roleConfig.baseUrl === 'string'
? roleConfig.baseUrl
: undefined;
}
export {
// Core config access
getConfig,
writeConfig,
ConfigurationError,
isConfigFilePresent,
// Validation
validateProvider,
validateProviderModelCombination,
VALID_PROVIDERS,
MODEL_MAP,
getAvailableModels,
// Role-specific getters (No env var overrides)
getMainProvider,
getMainModelId,
getMainMaxTokens,
getMainTemperature,
getResearchProvider,
getResearchModelId,
getResearchMaxTokens,
getResearchTemperature,
getFallbackProvider,
getFallbackModelId,
getFallbackMaxTokens,
getFallbackTemperature,
getBaseUrlForRole,
// Global setting getters (No env var overrides)
getLogLevel,
getDebugFlag,
getDefaultNumTasks,
getDefaultSubtasks,
getDefaultPriority,
getProjectName,
getOllamaBaseUrl,
getParametersForRole,
feat(telemetry): Implement AI usage telemetry pattern and apply to add-task This commit introduces a standardized pattern for capturing and propagating AI usage telemetry (cost, tokens, model used) across the Task Master stack and applies it to the 'add-task' functionality. Key changes include: - **Telemetry Pattern Definition:** - Added defining the integration pattern for core logic, direct functions, MCP tools, and CLI commands. - Updated related rules (, , Usage: mcp [OPTIONS] COMMAND [ARGS]... MCP development tools ╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ --help Show this message and exit. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭─ Commands ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ version Show the MCP version. │ │ dev Run a MCP server with the MCP Inspector. │ │ run Run a MCP server. │ │ install Install a MCP server in the Claude desktop app. │ ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯, , ) to reference the new telemetry rule. - **Core Telemetry Implementation ():** - Refactored the unified AI service to generate and return a object alongside the main AI result. - Fixed an MCP server startup crash by removing redundant local loading of and instead using the imported from for cost calculations. - Added to the object. - ** Integration:** - Modified (core) to receive from the AI service, return it, and call the new UI display function for CLI output. - Updated to receive from the core function and include it in the payload of its response. - Ensured (MCP tool) correctly passes the through via . - Updated to correctly pass context (, ) to the core function and rely on it for CLI telemetry display. - **UI Enhancement:** - Added function to to show telemetry details in the CLI. - **Project Management:** - Added subtasks 77.6 through 77.12 to track the rollout of this telemetry pattern to other AI-powered commands (, , , , , , ). This establishes the foundation for tracking AI usage across the application.
2025-05-07 13:41:25 -04:00
getUserId,
// API Key Checkers (still relevant)
isApiKeySet,
getMcpApiKeyStatus,
// ADD: Function to get all provider names
getAllProviders
};