feat(config): Implement new config system and resolve refactoring errors Introduced config-manager.js and new utilities (resolveEnvVariable, findProjectRoot). Removed old global CONFIG object from utils.js. Updated .taskmasterconfig, mcp.json, and .env.example. Added generateComplexityAnalysisPrompt to ui.js. Removed unused updateSubtaskById from task-manager.js. Resolved SyntaxError and ReferenceError issues across commands.js, ui.js, task-manager.js, and ai-services.js by replacing CONFIG references with config-manager getters (getDebugFlag, getProjectName, getDefaultSubtasks, isApiKeySet). Refactored 'models' command to use getConfig/writeConfig. Simplified version checking. This stabilizes the codebase after initial Task 61 refactoring, fixing CLI errors and enabling subsequent work on Subtasks 61.34 and 61.35.
This commit is contained in:
Eyal Toledano
191
src/ai-providers/anthropic.js
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191
src/ai-providers/anthropic.js
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/**
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* src/ai-providers/anthropic.js
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*
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* Implementation for interacting with Anthropic models (e.g., Claude)
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* using the Vercel AI SDK.
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*/
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import { createAnthropic } from '@ai-sdk/anthropic';
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import { generateText, streamText, generateObject, streamObject } from 'ai';
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import { log } from '../../scripts/modules/utils.js'; // Assuming utils is accessible
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// TODO: Implement standardized functions for generateText, streamText, generateObject
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// --- Client Instantiation ---
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// Note: API key resolution should ideally happen closer to the call site
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// using the config manager/resolver which checks process.env and session.env.
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// This is a placeholder for basic functionality.
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// Remove the global variable and caching logic
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// let anthropicClient;
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function getClient(apiKey) {
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if (!apiKey) {
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// In a real scenario, this would use the config resolver.
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// Throwing error here if key isn't passed for simplicity.
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// Keep the error check for the passed key
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throw new Error('Anthropic API key is required.');
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}
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// Remove the check for anthropicClient
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// if (!anthropicClient) {
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// TODO: Explore passing options like default headers if needed
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// Create and return a new instance directly
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return createAnthropic({
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apiKey: apiKey
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});
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// }
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// return anthropicClient;
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}
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// --- Standardized Service Function Implementations ---
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/**
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* Generates text using an Anthropic model.
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*
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* @param {object} params - Parameters for the text generation.
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* @param {string} params.apiKey - The Anthropic API key.
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* @param {string} params.modelId - The specific Anthropic model ID to use (e.g., 'claude-3-haiku-20240307').
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* @param {string} params.systemPrompt - The system prompt.
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* @param {string} params.userPrompt - The user prompt.
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* @param {number} [params.maxTokens] - Maximum tokens for the response.
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* @param {number} [params.temperature] - Temperature for generation.
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* @returns {Promise<string>} The generated text content.
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* @throws {Error} If the API call fails.
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*/
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export async function generateAnthropicText({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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maxTokens,
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temperature
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}) {
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log('debug', `Generating Anthropic text with model: ${modelId}`);
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try {
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const client = getClient(apiKey);
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const result = await generateText({
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model: client(modelId), // Pass the model ID to the client instance
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system: systemPrompt,
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prompt: userPrompt,
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maxTokens: maxTokens,
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temperature: temperature
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// TODO: Add other relevant parameters like topP, topK if needed
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});
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log(
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'debug',
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`Anthropic generateText result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
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);
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return result.text;
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} catch (error) {
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log('error', `Anthropic generateText failed: ${error.message}`);
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// Consider more specific error handling or re-throwing a standardized error
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throw error;
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}
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}
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/**
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* Streams text using an Anthropic model.
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*
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* @param {object} params - Parameters for the text streaming.
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* @param {string} params.apiKey - The Anthropic API key.
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* @param {string} params.modelId - The specific Anthropic model ID.
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* @param {string} params.systemPrompt - The system prompt.
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* @param {string} params.userPrompt - The user prompt.
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* @param {number} [params.maxTokens] - Maximum tokens for the response.
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* @param {number} [params.temperature] - Temperature for generation.
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* @returns {Promise<ReadableStream<string>>} A readable stream of text deltas.
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* @throws {Error} If the API call fails to initiate the stream.
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*/
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export async function streamAnthropicText({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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maxTokens,
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temperature
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}) {
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log('debug', `Streaming Anthropic text with model: ${modelId}`);
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try {
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const client = getClient(apiKey);
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const stream = await streamText({
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model: client(modelId),
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system: systemPrompt,
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prompt: userPrompt,
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maxTokens: maxTokens,
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temperature: temperature
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// TODO: Add other relevant parameters
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});
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// We return the stream directly. The consumer will handle reading it.
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// We could potentially wrap it or add logging within the stream pipe if needed.
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return stream.textStream;
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} catch (error) {
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log('error', `Anthropic streamText failed: ${error.message}`);
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throw error;
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}
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}
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/**
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* Generates a structured object using an Anthropic model.
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* NOTE: Anthropic's tool/function calling support might have limitations
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* compared to OpenAI, especially regarding complex schemas or enforcement.
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* The Vercel AI SDK attempts to abstract this.
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*
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* @param {object} params - Parameters for object generation.
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* @param {string} params.apiKey - The Anthropic API key.
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* @param {string} params.modelId - The specific Anthropic model ID.
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* @param {string} params.systemPrompt - The system prompt (optional).
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* @param {string} params.userPrompt - The user prompt describing the desired object.
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* @param {import('zod').ZodSchema} params.schema - The Zod schema for the object.
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* @param {string} params.objectName - A name for the object/tool.
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* @param {number} [params.maxTokens] - Maximum tokens for the response.
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* @param {number} [params.temperature] - Temperature for generation.
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* @param {number} [params.maxRetries] - Max retries for validation/generation.
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* @returns {Promise<object>} The generated object matching the schema.
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* @throws {Error} If generation or validation fails.
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*/
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export async function generateAnthropicObject({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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schema,
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objectName = 'generated_object', // Provide a default name
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maxTokens,
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temperature,
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maxRetries = 3
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}) {
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log(
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'debug',
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`Generating Anthropic object ('${objectName}') with model: ${modelId}`
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);
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try {
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const client = getClient(apiKey);
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const result = await generateObject({
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model: client(modelId),
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mode: 'tool', // Anthropic generally uses 'tool' mode for structured output
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schema: schema,
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system: systemPrompt,
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prompt: userPrompt,
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tool: {
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name: objectName, // Use the provided or default name
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description: `Generate a ${objectName} based on the prompt.` // Simple description
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},
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maxTokens: maxTokens,
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temperature: temperature,
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maxRetries: maxRetries
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});
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log(
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'debug',
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`Anthropic generateObject result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
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);
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return result.object;
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} catch (error) {
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log(
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'error',
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`Anthropic generateObject ('${objectName}') failed: ${error.message}`
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);
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throw error;
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}
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}
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// TODO: Implement streamAnthropicObject if needed and supported well by the SDK for Anthropic.
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// The basic structure would be similar to generateAnthropicObject but using streamObject.
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176
src/ai-providers/perplexity.js
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176
src/ai-providers/perplexity.js
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@@ -0,0 +1,176 @@
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/**
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* src/ai-providers/perplexity.js
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*
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* Implementation for interacting with Perplexity models
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* using the Vercel AI SDK.
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*/
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import { createPerplexity } from '@ai-sdk/perplexity';
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import { generateText, streamText, generateObject, streamObject } from 'ai';
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import { log } from '../../scripts/modules/utils.js';
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// --- Client Instantiation ---
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// Similar to Anthropic, this expects the resolved API key to be passed in.
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function getClient(apiKey) {
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if (!apiKey) {
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throw new Error('Perplexity API key is required.');
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}
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// Create and return a new instance directly
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return createPerplexity({
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apiKey: apiKey
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});
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}
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// --- Standardized Service Function Implementations ---
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/**
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* Generates text using a Perplexity model.
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*
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* @param {object} params - Parameters for text generation.
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* @param {string} params.apiKey - The Perplexity API key.
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* @param {string} params.modelId - The Perplexity model ID (e.g., 'sonar-small-32k-online').
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* @param {string} [params.systemPrompt] - The system prompt (optional for some models).
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* @param {string} params.userPrompt - The user prompt.
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* @param {number} [params.maxTokens] - Maximum tokens.
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* @param {number} [params.temperature] - Temperature.
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* @returns {Promise<string>} Generated text.
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*/
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export async function generatePerplexityText({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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maxTokens,
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temperature
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}) {
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log('debug', `Generating Perplexity text with model: ${modelId}`);
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try {
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const client = getClient(apiKey);
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const result = await generateText({
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model: client(modelId),
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system: systemPrompt, // Pass system prompt if provided
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prompt: userPrompt,
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maxTokens: maxTokens,
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temperature: temperature
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});
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log(
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'debug',
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`Perplexity generateText result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
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);
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return result.text;
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} catch (error) {
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log('error', `Perplexity generateText failed: ${error.message}`);
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throw error;
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}
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}
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/**
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* Streams text using a Perplexity model.
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*
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* @param {object} params - Parameters for text streaming.
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* @param {string} params.apiKey - The Perplexity API key.
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* @param {string} params.modelId - The Perplexity model ID.
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* @param {string} [params.systemPrompt] - The system prompt.
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* @param {string} params.userPrompt - The user prompt.
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* @param {number} [params.maxTokens] - Maximum tokens.
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* @param {number} [params.temperature] - Temperature.
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* @returns {Promise<ReadableStream<string>>} Stream of text deltas.
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*/
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export async function streamPerplexityText({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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maxTokens,
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temperature
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}) {
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log('debug', `Streaming Perplexity text with model: ${modelId}`);
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try {
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const client = getClient(apiKey);
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const stream = await streamText({
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model: client(modelId),
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system: systemPrompt,
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prompt: userPrompt,
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maxTokens: maxTokens,
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temperature: temperature
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});
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return stream.textStream;
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} catch (error) {
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log('error', `Perplexity streamText failed: ${error.message}`);
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throw error;
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}
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}
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/**
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* Generates a structured object using a Perplexity model.
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* Note: Perplexity's support for structured output/tool use might vary.
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* We assume it follows OpenAI's function/tool calling conventions if supported by the SDK.
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*
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* @param {object} params - Parameters for object generation.
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* @param {string} params.apiKey - The Perplexity API key.
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* @param {string} params.modelId - The Perplexity model ID.
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* @param {string} [params.systemPrompt] - System prompt.
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* @param {string} params.userPrompt - User prompt.
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* @param {import('zod').ZodSchema} params.schema - Zod schema.
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* @param {string} params.objectName - Name for the object/tool.
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* @param {number} [params.maxTokens] - Maximum tokens.
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* @param {number} [params.temperature] - Temperature.
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* @param {number} [params.maxRetries] - Max retries.
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* @returns {Promise<object>} Generated object.
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*/
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export async function generatePerplexityObject({
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apiKey,
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modelId,
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systemPrompt,
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userPrompt,
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schema,
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objectName = 'generated_object',
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maxTokens,
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temperature,
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maxRetries = 3
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}) {
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log(
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'debug',
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`Generating Perplexity object ('${objectName}') with model: ${modelId}`
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);
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try {
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const client = getClient(apiKey);
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// Assuming Perplexity follows OpenAI-like tool mode if supported by SDK
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const result = await generateObject({
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model: client(modelId),
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mode: 'tool',
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schema: schema,
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system: systemPrompt,
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prompt: userPrompt,
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tool: {
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name: objectName,
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description: `Generate a ${objectName} based on the prompt.`
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},
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maxTokens: maxTokens,
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temperature: temperature,
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maxRetries: maxRetries
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});
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log(
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'debug',
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`Perplexity generateObject result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
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);
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return result.object;
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} catch (error) {
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log(
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'error',
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`Perplexity generateObject ('${objectName}') failed: ${error.message}`
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);
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// Check if the error indicates lack of tool support
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if (
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error.message.includes('tool use') ||
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error.message.includes('structured output')
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) {
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log(
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'warn',
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`Model ${modelId} might not support structured output via tools.`
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);
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}
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throw error;
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}
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}
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// TODO: Implement streamPerplexityObject if needed and supported.
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