feat(ai): Integrate OpenAI provider and enhance model config
- Add OpenAI provider implementation using @ai-sdk/openai.\n- Update `models` command/tool to display API key status for configured providers.\n- Implement model-specific `maxTokens` override logic in `config-manager.js` using `supported-models.json`.\n- Improve AI error message parsing in `ai-services-unified.js` for better clarity.
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Eyal Toledano
@@ -1336,12 +1336,257 @@ When testing the non-streaming `generateTextService` call in `updateSubtaskById`
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### Details:
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## 22. Implement `openai.js` Provider Module using Vercel AI SDK [deferred]
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## 22. Implement `openai.js` Provider Module using Vercel AI SDK [in-progress]
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### Dependencies: None
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### Description: Create and implement the `openai.js` module within `src/ai-providers/`. This module should contain functions to interact with the OpenAI API (streaming and non-streaming) using the **Vercel AI SDK**, adhering to the standardized input/output format defined for `ai-services-unified.js`. (Optional, implement if OpenAI models are needed).
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### Details:
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<info added on 2025-04-27T05:33:49.977Z>
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```javascript
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// Implementation details for openai.js provider module
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import { createOpenAI } from 'ai';
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/**
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* Generates text using OpenAI models via Vercel AI SDK
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*
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* @param {Object} params - Configuration parameters
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* @param {string} params.apiKey - OpenAI API key
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* @param {string} params.modelId - Model ID (e.g., 'gpt-4', 'gpt-3.5-turbo')
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* @param {Array} params.messages - Array of message objects with role and content
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* @param {number} [params.maxTokens] - Maximum tokens to generate
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* @param {number} [params.temperature=0.7] - Sampling temperature (0-1)
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* @returns {Promise<string>} The generated text response
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*/
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export async function generateOpenAIText(params) {
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try {
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const { apiKey, modelId, messages, maxTokens, temperature = 0.7 } = params;
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if (!apiKey) throw new Error('OpenAI API key is required');
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if (!modelId) throw new Error('Model ID is required');
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if (!messages || !Array.isArray(messages)) throw new Error('Messages array is required');
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const openai = createOpenAI({ apiKey });
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const response = await openai.chat.completions.create({
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model: modelId,
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messages,
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max_tokens: maxTokens,
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temperature,
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});
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return response.choices[0].message.content;
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} catch (error) {
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console.error('OpenAI text generation error:', error);
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throw new Error(`OpenAI API error: ${error.message}`);
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}
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}
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/**
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* Streams text using OpenAI models via Vercel AI SDK
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*
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* @param {Object} params - Configuration parameters (same as generateOpenAIText)
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* @returns {ReadableStream} A stream of text chunks
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*/
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export async function streamOpenAIText(params) {
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try {
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const { apiKey, modelId, messages, maxTokens, temperature = 0.7 } = params;
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if (!apiKey) throw new Error('OpenAI API key is required');
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if (!modelId) throw new Error('Model ID is required');
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if (!messages || !Array.isArray(messages)) throw new Error('Messages array is required');
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const openai = createOpenAI({ apiKey });
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const stream = await openai.chat.completions.create({
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model: modelId,
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messages,
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max_tokens: maxTokens,
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temperature,
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stream: true,
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});
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return stream;
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} catch (error) {
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console.error('OpenAI streaming error:', error);
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throw new Error(`OpenAI streaming error: ${error.message}`);
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}
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}
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/**
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* Generates a structured object using OpenAI models via Vercel AI SDK
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*
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* @param {Object} params - Configuration parameters
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* @param {string} params.apiKey - OpenAI API key
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* @param {string} params.modelId - Model ID (e.g., 'gpt-4', 'gpt-3.5-turbo')
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* @param {Array} params.messages - Array of message objects
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* @param {Object} params.schema - JSON schema for the response object
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* @param {string} params.objectName - Name of the object to generate
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* @returns {Promise<Object>} The generated structured object
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*/
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export async function generateOpenAIObject(params) {
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try {
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const { apiKey, modelId, messages, schema, objectName } = params;
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if (!apiKey) throw new Error('OpenAI API key is required');
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if (!modelId) throw new Error('Model ID is required');
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if (!messages || !Array.isArray(messages)) throw new Error('Messages array is required');
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if (!schema) throw new Error('Schema is required');
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if (!objectName) throw new Error('Object name is required');
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const openai = createOpenAI({ apiKey });
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// Using the Vercel AI SDK's function calling capabilities
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const response = await openai.chat.completions.create({
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model: modelId,
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messages,
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functions: [
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{
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name: objectName,
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description: `Generate a ${objectName} object`,
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parameters: schema,
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},
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],
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function_call: { name: objectName },
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});
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const functionCall = response.choices[0].message.function_call;
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return JSON.parse(functionCall.arguments);
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} catch (error) {
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console.error('OpenAI object generation error:', error);
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throw new Error(`OpenAI object generation error: ${error.message}`);
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}
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}
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```
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</info added on 2025-04-27T05:33:49.977Z>
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<info added on 2025-04-27T05:35:03.679Z>
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<info added on 2025-04-28T10:15:22.123Z>
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```javascript
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// Additional implementation notes for openai.js
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/**
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* Export a provider info object for OpenAI
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*/
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export const providerInfo = {
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id: 'openai',
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name: 'OpenAI',
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description: 'OpenAI API integration using Vercel AI SDK',
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models: {
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'gpt-4': {
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id: 'gpt-4',
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name: 'GPT-4',
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contextWindow: 8192,
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supportsFunctions: true,
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},
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'gpt-4-turbo': {
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id: 'gpt-4-turbo',
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name: 'GPT-4 Turbo',
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contextWindow: 128000,
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supportsFunctions: true,
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},
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'gpt-3.5-turbo': {
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id: 'gpt-3.5-turbo',
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name: 'GPT-3.5 Turbo',
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contextWindow: 16385,
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supportsFunctions: true,
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}
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}
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};
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/**
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* Helper function to format error responses consistently
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*
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* @param {Error} error - The caught error
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* @param {string} operation - The operation being performed
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* @returns {Error} A formatted error
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*/
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function formatError(error, operation) {
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// Extract OpenAI specific error details if available
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const statusCode = error.status || error.statusCode;
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const errorType = error.type || error.code || 'unknown_error';
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// Create a more detailed error message
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const message = `OpenAI ${operation} error (${errorType}): ${error.message}`;
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// Create a new error with the formatted message
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const formattedError = new Error(message);
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// Add additional properties for debugging
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formattedError.originalError = error;
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formattedError.provider = 'openai';
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formattedError.statusCode = statusCode;
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formattedError.errorType = errorType;
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return formattedError;
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}
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/**
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* Example usage with the unified AI services interface:
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*
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* // In ai-services-unified.js
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* import * as openaiProvider from './ai-providers/openai.js';
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*
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* export async function generateText(params) {
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* switch(params.provider) {
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* case 'openai':
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* return openaiProvider.generateOpenAIText(params);
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* // other providers...
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* }
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* }
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*/
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// Note: For proper error handling with the Vercel AI SDK, you may need to:
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// 1. Check for rate limiting errors (429)
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// 2. Handle token context window exceeded errors
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// 3. Implement exponential backoff for retries on 5xx errors
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// 4. Parse streaming errors properly from the ReadableStream
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```
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</info added on 2025-04-28T10:15:22.123Z>
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</info added on 2025-04-27T05:35:03.679Z>
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<info added on 2025-04-27T05:39:31.942Z>
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```javascript
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// Correction for openai.js provider module
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// IMPORTANT: Use the correct import from Vercel AI SDK
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import { createOpenAI, openai } from '@ai-sdk/openai';
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// Note: Before using this module, install the required dependency:
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// npm install @ai-sdk/openai
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// The rest of the implementation remains the same, but uses the correct imports.
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// When implementing this module, ensure your package.json includes this dependency.
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// For streaming implementations with the Vercel AI SDK, you can also use the
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// streamText and experimental streamUI methods:
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/**
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* Example of using streamText for simpler streaming implementation
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*/
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export async function streamOpenAITextSimplified(params) {
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try {
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const { apiKey, modelId, messages, maxTokens, temperature = 0.7 } = params;
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if (!apiKey) throw new Error('OpenAI API key is required');
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const openaiClient = createOpenAI({ apiKey });
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return openaiClient.streamText({
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model: modelId,
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messages,
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temperature,
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maxTokens,
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});
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} catch (error) {
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console.error('OpenAI streaming error:', error);
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throw new Error(`OpenAI streaming error: ${error.message}`);
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}
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}
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```
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</info added on 2025-04-27T05:39:31.942Z>
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## 23. Implement Conditional Provider Logic in `ai-services-unified.js` [done]
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### Dependencies: 61.20,61.21,61.22,61.24,61.25,61.26,61.27,61.28,61.29,61.30,61.34
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### Description: Implement logic within the functions of `ai-services-unified.js` (e.g., `generateTextService`, `generateObjectService`, `streamChatService`) to dynamically select and call the appropriate provider module (`anthropic.js`, `perplexity.js`, etc.) based on configuration (e.g., environment variables like `AI_PROVIDER` and `AI_MODEL` from `process.env` or `session.env`).
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@@ -1425,7 +1670,7 @@ function checkProviderCapability(provider, capability) {
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```
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</info added on 2025-04-20T03:52:13.065Z>
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## 24. Implement `google.js` Provider Module using Vercel AI SDK [pending]
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## 24. Implement `google.js` Provider Module using Vercel AI SDK [done]
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### Dependencies: None
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### Description: Create and implement the `google.js` module within `src/ai-providers/`. This module should contain functions to interact with Google AI models (e.g., Gemini) using the **Vercel AI SDK (`@ai-sdk/google`)**, adhering to the standardized input/output format defined for `ai-services-unified.js`.
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### Details:
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