feat: implement baseUrls on all ai providers(#521)

.changeset/forty-plums-stay.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': minor
+---
+
+.taskmasterconfig now supports a baseUrl field per model role (main, research, fallback), allowing endpoint overrides for any provider.

docs/configuration.md

@@ -15,13 +15,15 @@ Taskmaster uses two primary methods for configuration:
       			"provider": "anthropic",
       			"modelId": "claude-3-7-sonnet-20250219",
       			"maxTokens": 64000,
-      			"temperature": 0.2
+      			"temperature": 0.2,
+      			"baseUrl": "https://api.anthropic.com/v1"
       		},
       		"research": {
       			"provider": "perplexity",
       			"modelId": "sonar-pro",
       			"maxTokens": 8700,
-      			"temperature": 0.1
+      			"temperature": 0.1,
+      			"baseUrl": "https://api.perplexity.ai/v1"
       		},
       		"fallback": {
       			"provider": "anthropic",
@@ -56,8 +58,9 @@ Taskmaster uses two primary methods for configuration:
       - `AZURE_OPENAI_API_KEY`: Your Azure OpenAI API key (also requires `AZURE_OPENAI_ENDPOINT`).
       - `OPENROUTER_API_KEY`: Your OpenRouter API key.
       - `XAI_API_KEY`: Your X-AI API key.
-    - **Optional Endpoint Overrides (in .taskmasterconfig):**
+    - **Optional Endpoint Overrides:**
-      - `AZURE_OPENAI_ENDPOINT`: Required if using Azure OpenAI key.
+      - **Per-role `baseUrl` in `.taskmasterconfig`:** You can add a `baseUrl` property to any model role (`main`, `research`, `fallback`) to override the default API endpoint for that provider. If omitted, the provider's standard endpoint is used.
+      - `AZURE_OPENAI_ENDPOINT`: Required if using Azure OpenAI key (can also be set as `baseUrl` for the Azure model role).
       - `OLLAMA_BASE_URL`: Override the default Ollama API URL (Default: `http://localhost:11434/api`).
 
 **Important:** Settings like model ID selections (`main`, `research`, `fallback`), `maxTokens`, `temperature`, `logLevel`, `defaultSubtasks`, `defaultPriority`, and `projectName` are **managed in `.taskmasterconfig`**, not environment variables.

package-lock.json

@@ -1,12 +1,12 @@
 {
 	"name": "task-master-ai",
-	"version": "0.12",
+	"version": "0.13.2",
 	"lockfileVersion": 3,
 	"requires": true,
 	"packages": {
 		"": {
 			"name": "task-master-ai",
-			"version": "0.12",
+			"version": "0.13.2",
 			"license": "MIT WITH Commons-Clause",
 			"dependencies": {
 				"@ai-sdk/anthropic": "^1.2.10",

scripts/modules/ai-services-unified.js

@@ -14,7 +14,8 @@ import {
 	getResearchModelId,
 	getFallbackProvider,
 	getFallbackModelId,
-	getParametersForRole
+	getParametersForRole,
+	getBaseUrlForRole
 } from './config-manager.js';
 import { log, resolveEnvVariable, findProjectRoot } from './utils.js';
 
@@ -284,7 +285,13 @@ async function _unifiedServiceRunner(serviceType, params) {
 		'AI service call failed for all configured roles.';
 
 	for (const currentRole of sequence) {
-		let providerName, modelId, apiKey, roleParams, providerFnSet, providerApiFn;
+		let providerName,
+			modelId,
+			apiKey,
+			roleParams,
+			providerFnSet,
+			providerApiFn,
+			baseUrl;
 
 		try {
 			log('info', `New AI service call with role: ${currentRole}`);
@@ -325,6 +332,7 @@ async function _unifiedServiceRunner(serviceType, params) {
 
 			// Pass effectiveProjectRoot to getParametersForRole
 			roleParams = getParametersForRole(currentRole, effectiveProjectRoot);
+			baseUrl = getBaseUrlForRole(currentRole, effectiveProjectRoot);
 
 			// 2. Get Provider Function Set
 			providerFnSet = PROVIDER_FUNCTIONS[providerName?.toLowerCase()];
@@ -401,6 +409,7 @@ async function _unifiedServiceRunner(serviceType, params) {
 				maxTokens: roleParams.maxTokens,
 				temperature: roleParams.temperature,
 				messages,
+				baseUrl,
 				...(serviceType === 'generateObject' && { schema, objectName }),
 				...restApiParams
 			};

scripts/modules/config-manager.js

@@ -677,6 +677,13 @@ 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,
@@ -704,6 +711,7 @@ export {
 	getFallbackModelId,
 	getFallbackMaxTokens,
 	getFallbackTemperature,
+	getBaseUrlForRole,
 
 	// Global setting getters (No env var overrides)
 	getLogLevel,

src/ai-providers/anthropic.js

@@ -5,7 +5,7 @@
  * using the Vercel AI SDK.
  */
 import { createAnthropic } from '@ai-sdk/anthropic';
-import { generateText, streamText, generateObject, streamObject } from 'ai';
+import { generateText, streamText, generateObject } from 'ai';
 import { log } from '../../scripts/modules/utils.js'; // Assuming utils is accessible
 
 // TODO: Implement standardized functions for generateText, streamText, generateObject
@@ -17,7 +17,7 @@ import { log } from '../../scripts/modules/utils.js'; // Assuming utils is acces
 // Remove the global variable and caching logic
 // let anthropicClient;
 
-function getClient(apiKey) {
+function getClient(apiKey, baseUrl) {
 	if (!apiKey) {
 		// In a real scenario, this would use the config resolver.
 		// Throwing error here if key isn't passed for simplicity.
@@ -30,14 +30,12 @@ function getClient(apiKey) {
 	// Create and return a new instance directly with standard version header
 	return createAnthropic({
 		apiKey: apiKey,
-		baseURL: 'https://api.anthropic.com/v1',
+		...(baseUrl && { baseURL: baseUrl }),
 		// Use standard version header instead of beta
 		headers: {
 			'anthropic-beta': 'output-128k-2025-02-19'
 		}
 	});
-	// }
-	// return anthropicClient;
 }
 
 // --- Standardized Service Function Implementations ---
@@ -51,6 +49,7 @@ function getClient(apiKey) {
  * @param {Array<object>} params.messages - The messages array (e.g., [{ role: 'user', content: '...' }]).
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - The base URL for the Anthropic API.
  * @returns {Promise<string>} The generated text content.
  * @throws {Error} If the API call fails.
  */
@@ -59,11 +58,12 @@ export async function generateAnthropicText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Generating Anthropic text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const result = await generateText({
 			model: client(modelId),
 			messages: messages,
@@ -93,6 +93,7 @@ export async function generateAnthropicText({
  * @param {Array<object>} params.messages - The messages array.
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - The base URL for the Anthropic API.
  * @returns {Promise<object>} The full stream result object from the Vercel AI SDK.
  * @throws {Error} If the API call fails to initiate the stream.
  */
@@ -101,20 +102,20 @@ export async function streamAnthropicText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Streaming Anthropic text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 
-		// --- DEBUG LOGGING --- >>
 		log(
 			'debug',
 			'[streamAnthropicText] Parameters received by streamText:',
 			JSON.stringify(
 				{
-					modelId: modelId, // Log modelId being used
+					modelId: modelId,
-					messages: messages, // Log the messages array
+					messages: messages,
 					maxTokens: maxTokens,
 					temperature: temperature
 				},
@@ -122,25 +123,19 @@ export async function streamAnthropicText({
 				2
 			)
 		);
-		// --- << DEBUG LOGGING ---
 
 		const stream = await streamText({
 			model: client(modelId),
 			messages: messages,
 			maxTokens: maxTokens,
 			temperature: temperature
-			// Beta header moved to client initialization
 			// TODO: Add other relevant parameters
 		});
 
 		// *** RETURN THE FULL STREAM OBJECT, NOT JUST stream.textStream ***
 		return stream;
 	} catch (error) {
-		log(
+		log('error', `Anthropic streamText failed: ${error.message}`, error.stack);
-			'error',
-			`Anthropic streamText failed: ${error.message}`,
-			error.stack // Log stack trace for more details
-		);
 		throw error;
 	}
 }
@@ -160,6 +155,7 @@ export async function streamAnthropicText({
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
  * @param {number} [params.maxRetries] - Max retries for validation/generation.
+ * @param {string} [params.baseUrl] - The base URL for the Anthropic API.
  * @returns {Promise<object>} The generated object matching the schema.
  * @throws {Error} If generation or validation fails.
  */
@@ -171,24 +167,22 @@ export async function generateAnthropicObject({
 	objectName = 'generated_object',
 	maxTokens,
 	temperature,
-	maxRetries = 3
+	maxRetries = 3,
+	baseUrl
 }) {
 	log(
 		'debug',
 		`Generating Anthropic object ('${objectName}') with model: ${modelId}`
 	);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
-
-		// Log basic debug info
 		log(
 			'debug',
 			`Using maxTokens: ${maxTokens}, temperature: ${temperature}, model: ${modelId}`
 		);
-
 		const result = await generateObject({
 			model: client(modelId),
-			mode: 'tool', // Anthropic generally uses 'tool' mode for structured output
+			mode: 'tool',
 			schema: schema,
 			messages: messages,
 			tool: {
@@ -199,14 +193,12 @@ export async function generateAnthropicObject({
 			temperature: temperature,
 			maxRetries: maxRetries
 		});
-
 		log(
 			'debug',
 			`Anthropic generateObject result received. Tokens: ${result.usage.completionTokens}/${result.usage.promptTokens}`
 		);
 		return result.object;
 	} catch (error) {
-		// Simple error logging
 		log(
 			'error',
 			`Anthropic generateObject ('${objectName}') failed: ${error.message}`

src/ai-providers/google.js

@@ -12,6 +12,16 @@ import { log } from '../../scripts/modules/utils.js'; // Import logging utility
 const DEFAULT_MODEL = 'gemini-2.0-pro'; // Or a suitable default
 const DEFAULT_TEMPERATURE = 0.2; // Or a suitable default
 
+function getClient(apiKey, baseUrl) {
+	if (!apiKey) {
+		throw new Error('Google API key is required.');
+	}
+	return createGoogleGenerativeAI({
+		apiKey: apiKey,
+		...(baseUrl && { baseURL: baseUrl })
+	});
+}
+
 /**
  * Generates text using a Google AI model.
  *
@@ -29,7 +39,8 @@ async function generateGoogleText({
 	modelId = DEFAULT_MODEL,
 	temperature = DEFAULT_TEMPERATURE,
 	messages,
-	maxTokens // Note: Vercel SDK might handle this differently, needs verification
+	maxTokens,
+	baseUrl
 }) {
 	if (!apiKey) {
 		throw new Error('Google API key is required.');
@@ -37,28 +48,21 @@ async function generateGoogleText({
 	log('info', `Generating text with Google model: ${modelId}`);
 
 	try {
-		// const google = new GoogleGenerativeAI({ apiKey }); // Incorrect instantiation
+		const googleProvider = getClient(apiKey, baseUrl);
-		const googleProvider = createGoogleGenerativeAI({ apiKey }); // Correct instantiation
+		const model = googleProvider(modelId);
-		// const model = google.getGenerativeModel({ model: modelId }); // Incorrect model retrieval
-		const model = googleProvider(modelId); // Correct model retrieval
-
-		// Construct payload suitable for Vercel SDK's generateText
-		// Note: The exact structure might depend on how messages are passed
 		const result = await generateText({
-			model, // Pass the model instance
+			model,
-			messages, // Pass the messages array directly
+			messages,
 			temperature,
-			maxOutputTokens: maxTokens // Map to correct Vercel SDK param if available
+			maxOutputTokens: maxTokens
 		});
-
+		return result.text;
-		// Assuming result structure provides text directly or within a property
-		return result.text; // Adjust based on actual SDK response
 	} catch (error) {
 		log(
 			'error',
 			`Error generating text with Google (${modelId}): ${error.message}`
 		);
-		throw error; // Re-throw for unified service handler
+		throw error;
 	}
 }
 
@@ -79,7 +83,8 @@ async function streamGoogleText({
 	modelId = DEFAULT_MODEL,
 	temperature = DEFAULT_TEMPERATURE,
 	messages,
-	maxTokens
+	maxTokens,
+	baseUrl
 }) {
 	if (!apiKey) {
 		throw new Error('Google API key is required.');
@@ -87,19 +92,15 @@ async function streamGoogleText({
 	log('info', `Streaming text with Google model: ${modelId}`);
 
 	try {
-		// const google = new GoogleGenerativeAI({ apiKey }); // Incorrect instantiation
+		const googleProvider = getClient(apiKey, baseUrl);
-		const googleProvider = createGoogleGenerativeAI({ apiKey }); // Correct instantiation
+		const model = googleProvider(modelId);
-		// const model = google.getGenerativeModel({ model: modelId }); // Incorrect model retrieval
-		const model = googleProvider(modelId); // Correct model retrieval
-
 		const stream = await streamText({
-			model, // Pass the model instance
+			model,
 			messages,
 			temperature,
 			maxOutputTokens: maxTokens
 		});
-
+		return stream;
-		return stream; // Return the stream directly
 	} catch (error) {
 		log(
 			'error',
@@ -130,7 +131,8 @@ async function generateGoogleObject({
 	messages,
 	schema,
 	objectName, // Note: Vercel SDK might use this differently or not at all
-	maxTokens
+	maxTokens,
+	baseUrl
 }) {
 	if (!apiKey) {
 		throw new Error('Google API key is required.');
@@ -138,23 +140,16 @@ async function generateGoogleObject({
 	log('info', `Generating object with Google model: ${modelId}`);
 
 	try {
-		// const google = new GoogleGenerativeAI({ apiKey }); // Incorrect instantiation
+		const googleProvider = getClient(apiKey, baseUrl);
-		const googleProvider = createGoogleGenerativeAI({ apiKey }); // Correct instantiation
+		const model = googleProvider(modelId);
-		// const model = google.getGenerativeModel({ model: modelId }); // Incorrect model retrieval
-		const model = googleProvider(modelId); // Correct model retrieval
-
 		const { object } = await generateObject({
-			model, // Pass the model instance
+			model,
 			schema,
 			messages,
 			temperature,
 			maxOutputTokens: maxTokens
-			// Note: 'objectName' or 'mode' might not be directly applicable here
-			// depending on how `@ai-sdk/google` handles `generateObject`.
-			// Check SDK docs if specific tool calling/JSON mode needs explicit setup.
 		});
-
+		return object;
-		return object; // Return the parsed object
 	} catch (error) {
 		log(
 			'error',

src/ai-providers/openai.js

@@ -1,16 +1,26 @@
-import { createOpenAI, openai } from '@ai-sdk/openai'; // Using openai provider from Vercel AI SDK
+import { createOpenAI } from '@ai-sdk/openai'; // Using openai provider from Vercel AI SDK
-import { generateText, streamText, generateObject } from 'ai'; // Import necessary functions from 'ai'
+import { generateObject } from 'ai'; // Import necessary functions from 'ai'
 import { log } from '../../scripts/modules/utils.js';
 
+function getClient(apiKey, baseUrl) {
+	if (!apiKey) {
+		throw new Error('OpenAI API key is required.');
+	}
+	return createOpenAI({
+		apiKey: apiKey,
+		...(baseUrl && { baseURL: baseUrl })
+	});
+}
+
 /**
  * Generates text using OpenAI models via Vercel AI SDK.
  *
- * @param {object} params - Parameters including apiKey, modelId, messages, maxTokens, temperature.
+ * @param {object} params - Parameters including apiKey, modelId, messages, maxTokens, temperature, baseUrl.
  * @returns {Promise<string>} The generated text content.
  * @throws {Error} If API call fails.
  */
 export async function generateOpenAIText(params) {
-	const { apiKey, modelId, messages, maxTokens, temperature } = params;
+	const { apiKey, modelId, messages, maxTokens, temperature, baseUrl } = params;
 	log('debug', `generateOpenAIText called with model: ${modelId}`);
 
 	if (!apiKey) {
@@ -23,18 +33,15 @@ export async function generateOpenAIText(params) {
 		throw new Error('Invalid or empty messages array provided for OpenAI.');
 	}
 
-	const openaiClient = createOpenAI({ apiKey });
+	const openaiClient = getClient(apiKey, baseUrl);
 
 	try {
 		const result = await openaiClient.chat(messages, {
-			// Updated: Use openaiClient.chat directly
 			model: modelId,
 			max_tokens: maxTokens,
 			temperature
 		});
 
-		// Adjust based on actual Vercel SDK response structure for openaiClient.chat
-		// This might need refinement based on testing the SDK's output.
 		const textContent = result?.choices?.[0]?.message?.content?.trim();
 
 		if (!textContent) {
@@ -65,12 +72,12 @@ export async function generateOpenAIText(params) {
 /**
  * Streams text using OpenAI models via Vercel AI SDK.
  *
- * @param {object} params - Parameters including apiKey, modelId, messages, maxTokens, temperature.
+ * @param {object} params - Parameters including apiKey, modelId, messages, maxTokens, temperature, baseUrl.
  * @returns {Promise<ReadableStream>} A readable stream of text deltas.
  * @throws {Error} If API call fails.
  */
 export async function streamOpenAIText(params) {
-	const { apiKey, modelId, messages, maxTokens, temperature } = params;
+	const { apiKey, modelId, messages, maxTokens, temperature, baseUrl } = params;
 	log('debug', `streamOpenAIText called with model: ${modelId}`);
 
 	if (!apiKey) {
@@ -85,12 +92,10 @@ export async function streamOpenAIText(params) {
 		);
 	}
 
-	const openaiClient = createOpenAI({ apiKey });
+	const openaiClient = getClient(apiKey, baseUrl);
 
 	try {
-		// Use the streamText function from Vercel AI SDK core
 		const stream = await openaiClient.chat.stream(messages, {
-			// Updated: Use openaiClient.chat.stream
 			model: modelId,
 			max_tokens: maxTokens,
 			temperature
@@ -100,7 +105,6 @@ export async function streamOpenAIText(params) {
 			'debug',
 			`OpenAI streamText initiated successfully for model: ${modelId}`
 		);
-		// The Vercel SDK's streamText should directly return the stream object
 		return stream;
 	} catch (error) {
 		log(
@@ -117,7 +121,7 @@ export async function streamOpenAIText(params) {
 /**
  * Generates structured objects using OpenAI models via Vercel AI SDK.
  *
- * @param {object} params - Parameters including apiKey, modelId, messages, schema, objectName, maxTokens, temperature.
+ * @param {object} params - Parameters including apiKey, modelId, messages, schema, objectName, maxTokens, temperature, baseUrl.
  * @returns {Promise<object>} The generated object matching the schema.
  * @throws {Error} If API call fails or object generation fails.
  */
@@ -129,7 +133,8 @@ export async function generateOpenAIObject(params) {
 		schema,
 		objectName,
 		maxTokens,
-		temperature
+		temperature,
+		baseUrl
 	} = params;
 	log(
 		'debug',
@@ -145,10 +150,9 @@ export async function generateOpenAIObject(params) {
 	if (!objectName)
 		throw new Error('Object name is required for OpenAI object generation.');
 
-	const openaiClient = createOpenAI({ apiKey });
+	const openaiClient = getClient(apiKey, baseUrl);
 
 	try {
-		// Use the imported generateObject function from 'ai' package
 		const result = await generateObject({
 			model: openaiClient(modelId),
 			schema: schema,

src/ai-providers/openrouter.js

@@ -2,6 +2,14 @@ import { createOpenRouter } from '@openrouter/ai-sdk-provider';
 import { generateText, streamText, generateObject } from 'ai';
 import { log } from '../../scripts/modules/utils.js'; // Assuming utils.js is in scripts/modules
 
+function getClient(apiKey, baseUrl) {
+	if (!apiKey) throw new Error('OpenRouter API key is required.');
+	return createOpenRouter({
+		apiKey,
+		...(baseUrl && { baseURL: baseUrl })
+	});
+}
+
 /**
  * Generates text using an OpenRouter chat model.
  *
@@ -11,6 +19,7 @@ import { log } from '../../scripts/modules/utils.js'; // Assuming utils.js is in
  * @param {Array<object>} params.messages - Array of message objects (system, user, assistant).
  * @param {number} [params.maxTokens] - Maximum tokens to generate.
  * @param {number} [params.temperature] - Sampling temperature.
+ * @param {string} [params.baseUrl] - Base URL for the OpenRouter API.
  * @returns {Promise<string>} The generated text content.
  * @throws {Error} If the API call fails.
  */
@@ -20,6 +29,7 @@ async function generateOpenRouterText({
 	messages,
 	maxTokens,
 	temperature,
+	baseUrl,
 	...rest // Capture any other Vercel AI SDK compatible parameters
 }) {
 	if (!apiKey) throw new Error('OpenRouter API key is required.');
@@ -28,7 +38,7 @@ async function generateOpenRouterText({
 		throw new Error('Messages array cannot be empty.');
 
 	try {
-		const openrouter = createOpenRouter({ apiKey });
+		const openrouter = getClient(apiKey, baseUrl);
 		const model = openrouter.chat(modelId); // Assuming chat model
 
 		const { text } = await generateText({
@@ -58,6 +68,7 @@ async function generateOpenRouterText({
  * @param {Array<object>} params.messages - Array of message objects (system, user, assistant).
  * @param {number} [params.maxTokens] - Maximum tokens to generate.
  * @param {number} [params.temperature] - Sampling temperature.
+ * @param {string} [params.baseUrl] - Base URL for the OpenRouter API.
  * @returns {Promise<ReadableStream<string>>} A readable stream of text deltas.
  * @throws {Error} If the API call fails.
  */
@@ -67,6 +78,7 @@ async function streamOpenRouterText({
 	messages,
 	maxTokens,
 	temperature,
+	baseUrl,
 	...rest
 }) {
 	if (!apiKey) throw new Error('OpenRouter API key is required.');
@@ -75,7 +87,7 @@ async function streamOpenRouterText({
 		throw new Error('Messages array cannot be empty.');
 
 	try {
-		const openrouter = createOpenRouter({ apiKey });
+		const openrouter = getClient(apiKey, baseUrl);
 		const model = openrouter.chat(modelId);
 
 		// Directly return the stream from the Vercel AI SDK function
@@ -108,6 +120,7 @@ async function streamOpenRouterText({
  * @param {number} [params.maxRetries=3] - Max retries for object generation.
  * @param {number} [params.maxTokens] - Maximum tokens.
  * @param {number} [params.temperature] - Temperature.
+ * @param {string} [params.baseUrl] - Base URL for the OpenRouter API.
  * @returns {Promise<object>} The generated object matching the schema.
  * @throws {Error} If the API call fails or validation fails.
  */
@@ -120,6 +133,7 @@ async function generateOpenRouterObject({
 	maxRetries = 3,
 	maxTokens,
 	temperature,
+	baseUrl,
 	...rest
 }) {
 	if (!apiKey) throw new Error('OpenRouter API key is required.');
@@ -129,7 +143,7 @@ async function generateOpenRouterObject({
 		throw new Error('Messages array cannot be empty.');
 
 	try {
-		const openrouter = createOpenRouter({ apiKey });
+		const openrouter = getClient(apiKey, baseUrl);
 		const model = openrouter.chat(modelId);
 
 		const { object } = await generateObject({

src/ai-providers/perplexity.js

@@ -10,13 +10,13 @@ import { log } from '../../scripts/modules/utils.js';
 
 // --- Client Instantiation ---
 // Similar to Anthropic, this expects the resolved API key to be passed in.
-function getClient(apiKey) {
+function getClient(apiKey, baseUrl) {
 	if (!apiKey) {
 		throw new Error('Perplexity API key is required.');
 	}
-	// Create and return a new instance directly
 	return createPerplexity({
-		apiKey: apiKey
+		apiKey: apiKey,
+		...(baseUrl && { baseURL: baseUrl })
 	});
 }
 
@@ -31,6 +31,7 @@ function getClient(apiKey) {
  * @param {Array<object>} params.messages - The messages array.
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - Base URL for the Perplexity API.
  * @returns {Promise<string>} The generated text content.
  * @throws {Error} If the API call fails.
  */
@@ -39,11 +40,12 @@ export async function generatePerplexityText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Generating Perplexity text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const result = await generateText({
 			model: client(modelId),
 			messages: messages,
@@ -70,6 +72,7 @@ export async function generatePerplexityText({
  * @param {Array<object>} params.messages - The messages array.
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - Base URL for the Perplexity API.
  * @returns {Promise<object>} The full stream result object from the Vercel AI SDK.
  * @throws {Error} If the API call fails to initiate the stream.
  */
@@ -78,11 +81,12 @@ export async function streamPerplexityText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Streaming Perplexity text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const stream = await streamText({
 			model: client(modelId),
 			messages: messages,
@@ -112,6 +116,7 @@ export async function streamPerplexityText({
  * @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.
+ * @param {string} [params.baseUrl] - Base URL for the Perplexity API.
  * @returns {Promise<object>} The generated object matching the schema.
  * @throws {Error} If generation or validation fails or is unsupported.
  */
@@ -123,7 +128,8 @@ export async function generatePerplexityObject({
 	objectName = 'generated_object',
 	maxTokens,
 	temperature,
-	maxRetries = 1 // Lower retries as support might be limited
+	maxRetries = 1,
+	baseUrl
 }) {
 	log(
 		'debug',
@@ -134,8 +140,7 @@ export async function generatePerplexityObject({
 		'generateObject support for Perplexity might be limited or experimental.'
 	);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
-		// Attempt using generateObject, but be prepared for potential issues
 		const result = await generateObject({
 			model: client(modelId),
 			schema: schema,

src/ai-providers/xai.js

@@ -9,14 +9,13 @@ import { generateText, streamText, generateObject } from 'ai'; // Only import wh
 import { log } from '../../scripts/modules/utils.js'; // Assuming utils is accessible
 
 // --- Client Instantiation ---
-function getClient(apiKey) {
+function getClient(apiKey, baseUrl) {
 	if (!apiKey) {
 		throw new Error('xAI API key is required.');
 	}
-	// Create and return a new instance directly
 	return createXai({
-		apiKey: apiKey
+		apiKey: apiKey,
-		// Add baseURL or other options if needed later
+		...(baseUrl && { baseURL: baseUrl })
 	});
 }
 
@@ -31,6 +30,7 @@ function getClient(apiKey) {
  * @param {Array<object>} params.messages - The messages array (e.g., [{ role: 'user', content: '...' }]).
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - The base URL for the xAI API.
  * @returns {Promise<string>} The generated text content.
  * @throws {Error} If the API call fails.
  */
@@ -39,13 +39,14 @@ export async function generateXaiText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Generating xAI text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const result = await generateText({
-			model: client(modelId), // Correct model invocation
+			model: client(modelId),
 			messages: messages,
 			maxTokens: maxTokens,
 			temperature: temperature
@@ -70,6 +71,7 @@ export async function generateXaiText({
  * @param {Array<object>} params.messages - The messages array.
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
+ * @param {string} [params.baseUrl] - The base URL for the xAI API.
  * @returns {Promise<object>} The full stream result object from the Vercel AI SDK.
  * @throws {Error} If the API call fails to initiate the stream.
  */
@@ -78,18 +80,19 @@ export async function streamXaiText({
 	modelId,
 	messages,
 	maxTokens,
-	temperature
+	temperature,
+	baseUrl
 }) {
 	log('debug', `Streaming xAI text with model: ${modelId}`);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const stream = await streamText({
-			model: client(modelId), // Correct model invocation
+			model: client(modelId),
 			messages: messages,
 			maxTokens: maxTokens,
 			temperature: temperature
 		});
-		return stream; // Return the full stream object
+		return stream;
 	} catch (error) {
 		log('error', `xAI streamText failed: ${error.message}`, error.stack);
 		throw error;
@@ -110,6 +113,7 @@ export async function streamXaiText({
  * @param {number} [params.maxTokens] - Maximum tokens for the response.
  * @param {number} [params.temperature] - Temperature for generation.
  * @param {number} [params.maxRetries] - Max retries for validation/generation.
+ * @param {string} [params.baseUrl] - The base URL for the xAI API.
  * @returns {Promise<object>} The generated object matching the schema.
  * @throws {Error} If generation or validation fails.
  */
@@ -121,16 +125,17 @@ export async function generateXaiObject({
 	objectName = 'generated_xai_object',
 	maxTokens,
 	temperature,
-	maxRetries = 3
+	maxRetries = 3,
+	baseUrl
 }) {
 	log(
-		'warn', // Log warning as this is likely unsupported
+		'warn',
 		`Attempting to generate xAI object ('${objectName}') with model: ${modelId}. This may not be supported by the provider.`
 	);
 	try {
-		const client = getClient(apiKey);
+		const client = getClient(apiKey, baseUrl);
 		const result = await generateObject({
-			model: client(modelId), // Correct model invocation
+			model: client(modelId),
 			// Note: mode might need adjustment if xAI ever supports object generation differently
 			mode: 'tool',
 			schema: schema,
@@ -153,6 +158,6 @@ export async function generateXaiObject({
 			'error',
 			`xAI generateObject ('${objectName}') failed: ${error.message}. (Likely unsupported by provider)`
 		);
-		throw error; // Re-throw the error
+		throw error;
 	}
 }

tests/unit/ai-services-unified.test.js

@@ -8,6 +8,7 @@ const mockGetResearchModelId = jest.fn();
 const mockGetFallbackProvider = jest.fn();
 const mockGetFallbackModelId = jest.fn();
 const mockGetParametersForRole = jest.fn();
+const mockGetBaseUrlForRole = jest.fn();
 
 jest.unstable_mockModule('../../scripts/modules/config-manager.js', () => ({
 	getMainProvider: mockGetMainProvider,
@@ -16,7 +17,8 @@ jest.unstable_mockModule('../../scripts/modules/config-manager.js', () => ({
 	getResearchModelId: mockGetResearchModelId,
 	getFallbackProvider: mockGetFallbackProvider,
 	getFallbackModelId: mockGetFallbackModelId,
-	getParametersForRole: mockGetParametersForRole
+	getParametersForRole: mockGetParametersForRole,
+	getBaseUrlForRole: mockGetBaseUrlForRole
 }));
 
 // Mock AI Provider Modules