fix: ensure API key detection properly reads .env in MCP context

Problem: - Task Master model configuration wasn't properly checking for API keys in the project's .env file when running through MCP - The isApiKeySet function was only checking session.env and process.env but not inspecting the .env file directly - This caused incorrect API key status reporting in MCP tools even when keys were properly set in .env Solution: - Modified resolveEnvVariable function in utils.js to properly read from .env file at projectRoot - Updated isApiKeySet to correctly pass projectRoot to resolveEnvVariable - Enhanced the key detection logic to have consistent behavior between CLI and MCP contexts - Maintains the correct precedence: session.env → .env file → process.env Testing: - Verified working correctly with both MCP and CLI tools - API keys properly detected in .env file in both contexts - Deleted .cursor/mcp.json to confirm introspection of .env as fallback works
2025-05-01 13:23:52 -04:00
parent d4a2e34b3b
commit 40df57f969
6 changed files with 105 additions and 46 deletions
--- a/.taskmasterconfig
+++ b/.taskmasterconfig
@@ -1,31 +1,31 @@
 {
-  "models": {
-    "main": {
-      "provider": "anthropic",
-      "modelId": "claude-3-7-sonnet-20250219",
-      "maxTokens": 100000,
-      "temperature": 0.2
-    },
-    "research": {
-      "provider": "xai",
-      "modelId": "grok-3",
-      "maxTokens": 8700,
-      "temperature": 0.1
-    },
-    "fallback": {
-      "provider": "anthropic",
-      "modelId": "claude-3-5-sonnet-20241022",
-      "maxTokens": 120000,
-      "temperature": 0.2
-    }
-  },
-  "global": {
-    "logLevel": "info",
-    "debug": false,
-    "defaultSubtasks": 5,
-    "defaultPriority": "medium",
-    "projectName": "Taskmaster",
-    "ollamaBaseUrl": "http://localhost:11434/api",
-    "azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/"
-  }
+	"models": {
+		"main": {
+			"provider": "anthropic",
+			"modelId": "claude-3-7-sonnet-20250219",
+			"maxTokens": 100000,
+			"temperature": 0.2
+		},
+		"research": {
+			"provider": "perplexity",
+			"modelId": "sonar-pro",
+			"maxTokens": 8700,
+			"temperature": 0.1
+		},
+		"fallback": {
+			"provider": "anthropic",
+			"modelId": "claude-3-5-sonnet-20241022",
+			"maxTokens": 120000,
+			"temperature": 0.2
+		}
+	},
+	"global": {
+		"logLevel": "info",
+		"debug": false,
+		"defaultSubtasks": 5,
+		"defaultPriority": "medium",
+		"projectName": "Taskmaster",
+		"ollamaBaseUrl": "http://localhost:11434/api",
+		"azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/"
+	}
 }
--- a/scripts/modules/config-manager.js
+++ b/scripts/modules/config-manager.js
@@ -424,12 +424,13 @@ function getParametersForRole(role, explicitRoot = null) {

 /**
 * Checks if the API key for a given provider is set in the environment.
- * Checks process.env first, then session.env if session is provided.
+ * Checks process.env first, then session.env if session is provided, then .env file if projectRoot provided.
 * @param {string} providerName - The name of the provider (e.g., 'openai', 'anthropic').
 * @param {object|null} [session=null] - The MCP session object (optional).
+ * @param {string|null} [projectRoot=null] - The project root directory (optional, for .env file check).
 * @returns {boolean} True if the API key is set, false otherwise.
 */
-function isApiKeySet(providerName, session = null) {
+function isApiKeySet(providerName, session = null, projectRoot = null) {
 	// Define the expected environment variable name for each provider
 	if (providerName?.toLowerCase() === 'ollama') {
 		return true; // Indicate key status is effectively "OK"
@@ -454,7 +455,7 @@ function isApiKeySet(providerName, session = null) {
 	}

 	const envVarName = keyMap[providerKey];
-	const apiKeyValue = resolveEnvVariable(envVarName, session);
+	const apiKeyValue = resolveEnvVariable(envVarName, session, projectRoot);

 	// Check if the key exists, is not empty, and is not a placeholder
 	return (
--- a/scripts/modules/task-manager/models.js
+++ b/scripts/modules/task-manager/models.js
@@ -77,7 +77,7 @@ function fetchOpenRouterModels() {
 * @returns {Object} RESTful response with current model configuration
 */
 async function getModelConfiguration(options = {}) {
-	const { mcpLog, projectRoot } = options;
+	const { mcpLog, projectRoot, session } = options;

 	const report = (level, ...args) => {
 		if (mcpLog && typeof mcpLog[level] === 'function') {
@@ -125,12 +125,16 @@ async function getModelConfiguration(options = {}) {
 		const fallbackModelId = getFallbackModelId(projectRoot);

 		// Check API keys
-		const mainCliKeyOk = isApiKeySet(mainProvider);
+		const mainCliKeyOk = isApiKeySet(mainProvider, session, projectRoot);
 		const mainMcpKeyOk = getMcpApiKeyStatus(mainProvider, projectRoot);
-		const researchCliKeyOk = isApiKeySet(researchProvider);
+		const researchCliKeyOk = isApiKeySet(
+			researchProvider,
+			session,
+			projectRoot
+		);
 		const researchMcpKeyOk = getMcpApiKeyStatus(researchProvider, projectRoot);
 		const fallbackCliKeyOk = fallbackProvider
-			? isApiKeySet(fallbackProvider)
+			? isApiKeySet(fallbackProvider, session, projectRoot)
 			: true;
 		const fallbackMcpKeyOk = fallbackProvider
 			? getMcpApiKeyStatus(fallbackProvider, projectRoot)
@@ -523,7 +527,7 @@ async function getApiKeyStatusReport(options = {}) {
 		); // Ollama is not a provider, it's a service, doesn't need an api key usually
 		const statusReport = providersToCheck.map((provider) => {
 			// Use provided projectRoot for MCP status check
-			const cliOk = isApiKeySet(provider, session); // Pass session for CLI check too
+			const cliOk = isApiKeySet(provider, session, projectRoot); // Pass session and projectRoot for CLI check
 			const mcpOk = getMcpApiKeyStatus(provider, projectRoot);
 			return {
 				provider,
--- a/scripts/modules/utils.js
+++ b/scripts/modules/utils.js
@@ -6,6 +6,7 @@
 import fs from 'fs';
 import path from 'path';
 import chalk from 'chalk';
+import dotenv from 'dotenv';
 // Import specific config getters needed here
 import { getLogLevel, getDebugFlag } from './config-manager.js';

@@ -14,16 +15,47 @@ let silentMode = false;

 // --- Environment Variable Resolution Utility ---
 /**
- * Resolves an environment variable by checking process.env first, then session.env.
- * @param {string} varName - The name of the environment variable.
- * @param {string|null} session - The MCP session object (optional).
+ * Resolves an environment variable's value.
+ * Precedence:
+ * 1. session.env (if session provided)
+ * 2. process.env
+ * 3. .env file at projectRoot (if projectRoot provided)
+ * @param {string} key - The environment variable key.
+ * @param {object|null} [session=null] - The MCP session object.
+ * @param {string|null} [projectRoot=null] - The project root directory (for .env fallback).
 * @returns {string|undefined} The value of the environment variable or undefined if not found.
 */
-function resolveEnvVariable(varName, session) {
-	// Ensure session and session.env exist before attempting access
-	const sessionValue =
-		session && session.env ? session.env[varName] : undefined;
-	return process.env[varName] ?? sessionValue;
+function resolveEnvVariable(key, session = null, projectRoot = null) {
+	// 1. Check session.env
+	if (session?.env?.[key]) {
+		return session.env[key];
+	}
+
+	// 2. Read .env file at projectRoot
+	if (projectRoot) {
+		const envPath = path.join(projectRoot, '.env');
+		if (fs.existsSync(envPath)) {
+			try {
+				const envFileContent = fs.readFileSync(envPath, 'utf-8');
+				const parsedEnv = dotenv.parse(envFileContent); // Use dotenv to parse
+				if (parsedEnv && parsedEnv[key]) {
+					// console.log(`DEBUG: Found key ${key} in ${envPath}`); // Optional debug log
+					return parsedEnv[key];
+				}
+			} catch (error) {
+				// Log error but don't crash, just proceed as if key wasn't found in file
+				log('warn', `Could not read or parse ${envPath}: ${error.message}`);
+			}
+		}
+	}
+
+	// 3. Fallback: Check process.env
+	if (process.env[key]) {
+		return process.env[key];
+	}
+
+	// Not found anywhere
+	return undefined;
 }

 // --- Project Root Finding Utility ---
--- a/tasks/task_075.txt
+++ b/tasks/task_075.txt
@@ -0,0 +1,11 @@
+# Task ID: 75
+# Title: Integrate Google Search Grounding for Research Role
+# Status: pending
+# Dependencies: None
+# Priority: medium
+# Description: Update the AI service layer to enable Google Search Grounding specifically when a Google model is used in the 'research' role.
+# Details:
+**Goal:** Conditionally enable Google Search Grounding based on the AI role.\n\n**Implementation Plan:**\n\n1.  **Modify `ai-services-unified.js`:** Update `generateTextService`, `streamTextService`, and `generateObjectService`.\n2.  **Conditional Logic:** Inside these functions, check if `providerName === 'google'` AND `role === 'research'`.\n3.  **Construct `providerOptions`:** If the condition is met, create an options object:\n    ```javascript\n    let providerSpecificOptions = {};\n    if (providerName === 'google' && role === 'research') {\n        log('info', 'Enabling Google Search Grounding for research role.');\n        providerSpecificOptions = {\n            google: {\n                useSearchGrounding: true,\n                // Optional: Add dynamic retrieval for compatible models\n                // dynamicRetrievalConfig: { mode: 'MODE_DYNAMIC' } \n            }\n        };\n    }\n    ```\n4.  **Pass Options to SDK:** Pass `providerSpecificOptions` to the Vercel AI SDK functions (`generateText`, `streamText`, `generateObject`) via the `providerOptions` parameter:\n    ```javascript\n    const { text, ... } = await generateText({\n        // ... other params\n        providerOptions: providerSpecificOptions \n    });\n    ```\n5.  **Update `supported-models.json`:** Ensure Google models intended for research (e.g., `gemini-1.5-pro-latest`, `gemini-1.5-flash-latest`) include `'research'` in their `allowed_roles` array.\n\n**Rationale:** This approach maintains the clear separation between 'main' and 'research' roles, ensuring grounding is only activated when explicitly requested via the `--research` flag or when the research model is invoked.
+
+# Test Strategy:
+1. Configure a Google model (e.g., gemini-1.5-flash-latest) as the 'research' model in `.taskmasterconfig`.\n2. Run a command with the `--research` flag (e.g., `task-master add-task --prompt='Latest news on AI SDK 4.2' --research`).\n3. Verify logs show 'Enabling Google Search Grounding'.\n4. Check if the task output incorporates recent information.\n5. Configure the same Google model as the 'main' model.\n6. Run a command *without* the `--research` flag.\n7. Verify logs *do not* show grounding being enabled.\n8. Add unit tests to `ai-services-unified.test.js` to verify the conditional logic for adding `providerOptions`. Ensure mocks correctly simulate different roles and providers.
--- a/tasks/tasks.json
+++ b/tasks/tasks.json
@@ -3937,6 +3937,17 @@
          "parentTaskId": 74
        }
      ]
+    },
+    {
+      "id": 75,
+      "title": "Integrate Google Search Grounding for Research Role",
+      "description": "Update the AI service layer to enable Google Search Grounding specifically when a Google model is used in the 'research' role.",
+      "details": "**Goal:** Conditionally enable Google Search Grounding based on the AI role.\\n\\n**Implementation Plan:**\\n\\n1.  **Modify `ai-services-unified.js`:** Update `generateTextService`, `streamTextService`, and `generateObjectService`.\\n2.  **Conditional Logic:** Inside these functions, check if `providerName === 'google'` AND `role === 'research'`.\\n3.  **Construct `providerOptions`:** If the condition is met, create an options object:\\n    ```javascript\\n    let providerSpecificOptions = {};\\n    if (providerName === 'google' && role === 'research') {\\n        log('info', 'Enabling Google Search Grounding for research role.');\\n        providerSpecificOptions = {\\n            google: {\\n                useSearchGrounding: true,\\n                // Optional: Add dynamic retrieval for compatible models\\n                // dynamicRetrievalConfig: { mode: 'MODE_DYNAMIC' } \\n            }\\n        };\\n    }\\n    ```\\n4.  **Pass Options to SDK:** Pass `providerSpecificOptions` to the Vercel AI SDK functions (`generateText`, `streamText`, `generateObject`) via the `providerOptions` parameter:\\n    ```javascript\\n    const { text, ... } = await generateText({\\n        // ... other params\\n        providerOptions: providerSpecificOptions \\n    });\\n    ```\\n5.  **Update `supported-models.json`:** Ensure Google models intended for research (e.g., `gemini-1.5-pro-latest`, `gemini-1.5-flash-latest`) include `'research'` in their `allowed_roles` array.\\n\\n**Rationale:** This approach maintains the clear separation between 'main' and 'research' roles, ensuring grounding is only activated when explicitly requested via the `--research` flag or when the research model is invoked.",
+      "testStrategy": "1. Configure a Google model (e.g., gemini-1.5-flash-latest) as the 'research' model in `.taskmasterconfig`.\\n2. Run a command with the `--research` flag (e.g., `task-master add-task --prompt='Latest news on AI SDK 4.2' --research`).\\n3. Verify logs show 'Enabling Google Search Grounding'.\\n4. Check if the task output incorporates recent information.\\n5. Configure the same Google model as the 'main' model.\\n6. Run a command *without* the `--research` flag.\\n7. Verify logs *do not* show grounding being enabled.\\n8. Add unit tests to `ai-services-unified.test.js` to verify the conditional logic for adding `providerOptions`. Ensure mocks correctly simulate different roles and providers.",
+      "status": "pending",
+      "dependencies": [],
+      "priority": "medium",
+      "subtasks": []
    }
  ]
 }