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
Normal file
191
src/ai-providers/anthropic.js
Normal file
@@ -0,0 +1,191 @@
|
||||
/**
|
||||
* src/ai-providers/anthropic.js
|
||||
*
|
||||
* Implementation for interacting with Anthropic models (e.g., Claude)
|
||||
* using the Vercel AI SDK.
|
||||
*/
|
||||
import { createAnthropic } from '@ai-sdk/anthropic';
|
||||
import { generateText, streamText, generateObject, streamObject } from 'ai';
|
||||
import { log } from '../../scripts/modules/utils.js'; // Assuming utils is accessible
|
||||
|
||||
// TODO: Implement standardized functions for generateText, streamText, generateObject
|
||||
|
||||
// --- Client Instantiation ---
|
||||
// Note: API key resolution should ideally happen closer to the call site
|
||||
// using the config manager/resolver which checks process.env and session.env.
|
||||
// This is a placeholder for basic functionality.
|
||||
// Remove the global variable and caching logic
|
||||
// let anthropicClient;
|
||||
|
||||
function getClient(apiKey) {
|
||||
if (!apiKey) {
|
||||
// In a real scenario, this would use the config resolver.
|
||||
// Throwing error here if key isn't passed for simplicity.
|
||||
// Keep the error check for the passed key
|
||||
throw new Error('Anthropic API key is required.');
|
||||
}
|
||||
// Remove the check for anthropicClient
|
||||
// if (!anthropicClient) {
|
||||
// TODO: Explore passing options like default headers if needed
|
||||
// Create and return a new instance directly
|
||||
return createAnthropic({
|
||||
apiKey: apiKey
|
||||
});
|
||||
// }
|
||||
// return anthropicClient;
|
||||
}
|
||||
|
||||
// --- Standardized Service Function Implementations ---
|
||||
|
||||
/**
|
||||
* Generates text using an Anthropic model.
|
||||
*
|
||||
* @param {object} params - Parameters for the text generation.
|
||||
* @param {string} params.apiKey - The Anthropic API key.
|
||||
* @param {string} params.modelId - The specific Anthropic model ID to use (e.g., 'claude-3-haiku-20240307').
|
||||
* @param {string} params.systemPrompt - The system prompt.
|
||||
* @param {string} params.userPrompt - The user prompt.
|
||||
* @param {number} [params.maxTokens] - Maximum tokens for the response.
|
||||
* @param {number} [params.temperature] - Temperature for generation.
|
||||
* @returns {Promise<string>} The generated text content.
|
||||
* @throws {Error} If the API call fails.
|
||||
*/
|
||||
export async function generateAnthropicText({
|
||||
apiKey,
|
||||
modelId,
|
||||
systemPrompt,
|
||||
userPrompt,
|
||||
maxTokens,
|
||||
temperature
|
||||
}) {
|
||||
log('debug', `Generating Anthropic text with model: ${modelId}`);
|
||||
try {
|
||||
const client = getClient(apiKey);
|
||||
const result = await generateText({
|
||||
model: client(modelId), // Pass the model ID to the client instance
|
||||
system: systemPrompt,
|
||||
prompt: userPrompt,
|
||||
maxTokens: maxTokens,
|
||||
temperature: temperature
|
||||
// TODO: Add other relevant parameters like topP, topK if needed
|
||||
});
|
||||
log(
|
||||
'debug',
|
||||
`Anthropic generateText result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
|
||||
);
|
||||
return result.text;
|
||||
} catch (error) {
|
||||
log('error', `Anthropic generateText failed: ${error.message}`);
|
||||
// Consider more specific error handling or re-throwing a standardized error
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Streams text using an Anthropic model.
|
||||
*
|
||||
* @param {object} params - Parameters for the text streaming.
|
||||
* @param {string} params.apiKey - The Anthropic API key.
|
||||
* @param {string} params.modelId - The specific Anthropic model ID.
|
||||
* @param {string} params.systemPrompt - The system prompt.
|
||||
* @param {string} params.userPrompt - The user prompt.
|
||||
* @param {number} [params.maxTokens] - Maximum tokens for the response.
|
||||
* @param {number} [params.temperature] - Temperature for generation.
|
||||
* @returns {Promise<ReadableStream<string>>} A readable stream of text deltas.
|
||||
* @throws {Error} If the API call fails to initiate the stream.
|
||||
*/
|
||||
export async function streamAnthropicText({
|
||||
apiKey,
|
||||
modelId,
|
||||
systemPrompt,
|
||||
userPrompt,
|
||||
maxTokens,
|
||||
temperature
|
||||
}) {
|
||||
log('debug', `Streaming Anthropic text with model: ${modelId}`);
|
||||
try {
|
||||
const client = getClient(apiKey);
|
||||
const stream = await streamText({
|
||||
model: client(modelId),
|
||||
system: systemPrompt,
|
||||
prompt: userPrompt,
|
||||
maxTokens: maxTokens,
|
||||
temperature: temperature
|
||||
// TODO: Add other relevant parameters
|
||||
});
|
||||
|
||||
// We return the stream directly. The consumer will handle reading it.
|
||||
// We could potentially wrap it or add logging within the stream pipe if needed.
|
||||
return stream.textStream;
|
||||
} catch (error) {
|
||||
log('error', `Anthropic streamText failed: ${error.message}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates a structured object using an Anthropic model.
|
||||
* NOTE: Anthropic's tool/function calling support might have limitations
|
||||
* compared to OpenAI, especially regarding complex schemas or enforcement.
|
||||
* The Vercel AI SDK attempts to abstract this.
|
||||
*
|
||||
* @param {object} params - Parameters for object generation.
|
||||
* @param {string} params.apiKey - The Anthropic API key.
|
||||
* @param {string} params.modelId - The specific Anthropic model ID.
|
||||
* @param {string} params.systemPrompt - The system prompt (optional).
|
||||
* @param {string} params.userPrompt - The user prompt describing the desired object.
|
||||
* @param {import('zod').ZodSchema} params.schema - The Zod schema for the object.
|
||||
* @param {string} params.objectName - A name for the object/tool.
|
||||
* @param {number} [params.maxTokens] - Maximum tokens for the response.
|
||||
* @param {number} [params.temperature] - Temperature for generation.
|
||||
* @param {number} [params.maxRetries] - Max retries for validation/generation.
|
||||
* @returns {Promise<object>} The generated object matching the schema.
|
||||
* @throws {Error} If generation or validation fails.
|
||||
*/
|
||||
export async function generateAnthropicObject({
|
||||
apiKey,
|
||||
modelId,
|
||||
systemPrompt,
|
||||
userPrompt,
|
||||
schema,
|
||||
objectName = 'generated_object', // Provide a default name
|
||||
maxTokens,
|
||||
temperature,
|
||||
maxRetries = 3
|
||||
}) {
|
||||
log(
|
||||
'debug',
|
||||
`Generating Anthropic object ('${objectName}') with model: ${modelId}`
|
||||
);
|
||||
try {
|
||||
const client = getClient(apiKey);
|
||||
const result = await generateObject({
|
||||
model: client(modelId),
|
||||
mode: 'tool', // Anthropic generally uses 'tool' mode for structured output
|
||||
schema: schema,
|
||||
system: systemPrompt,
|
||||
prompt: userPrompt,
|
||||
tool: {
|
||||
name: objectName, // Use the provided or default name
|
||||
description: `Generate a ${objectName} based on the prompt.` // Simple description
|
||||
},
|
||||
maxTokens: maxTokens,
|
||||
temperature: temperature,
|
||||
maxRetries: maxRetries
|
||||
});
|
||||
log(
|
||||
'debug',
|
||||
`Anthropic generateObject result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
|
||||
);
|
||||
return result.object;
|
||||
} catch (error) {
|
||||
log(
|
||||
'error',
|
||||
`Anthropic generateObject ('${objectName}') failed: ${error.message}`
|
||||
);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
// TODO: Implement streamAnthropicObject if needed and supported well by the SDK for Anthropic.
|
||||
// The basic structure would be similar to generateAnthropicObject but using streamObject.
|
||||
Reference in New Issue
Block a user