chore: run npm run format
This commit is contained in:
Ralph Khreish
@@ -6,57 +6,55 @@ This document provides examples of how to use the new AI client utilities with A
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```javascript
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// In your direct function implementation:
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import {
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getAnthropicClientForMCP,
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getModelConfig,
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handleClaudeError
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import {
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getAnthropicClientForMCP,
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getModelConfig,
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handleClaudeError
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} from '../utils/ai-client-utils.js';
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export async function someAiOperationDirect(args, log, context) {
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try {
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// Initialize Anthropic client with session from context
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const client = getAnthropicClientForMCP(context.session, log);
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// Get model configuration with defaults or session overrides
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const modelConfig = getModelConfig(context.session);
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// Make API call with proper error handling
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try {
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const response = await client.messages.create({
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model: modelConfig.model,
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max_tokens: modelConfig.maxTokens,
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temperature: modelConfig.temperature,
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messages: [
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{ role: 'user', content: 'Your prompt here' }
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]
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});
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return {
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success: true,
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data: response
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};
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} catch (apiError) {
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// Use helper to get user-friendly error message
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const friendlyMessage = handleClaudeError(apiError);
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return {
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success: false,
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error: {
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code: 'AI_API_ERROR',
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message: friendlyMessage
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}
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};
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}
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} catch (error) {
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// Handle client initialization errors
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return {
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success: false,
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error: {
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code: 'AI_CLIENT_ERROR',
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message: error.message
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}
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};
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}
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try {
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// Initialize Anthropic client with session from context
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const client = getAnthropicClientForMCP(context.session, log);
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// Get model configuration with defaults or session overrides
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const modelConfig = getModelConfig(context.session);
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// Make API call with proper error handling
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try {
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const response = await client.messages.create({
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model: modelConfig.model,
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max_tokens: modelConfig.maxTokens,
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temperature: modelConfig.temperature,
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messages: [{ role: 'user', content: 'Your prompt here' }]
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});
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return {
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success: true,
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data: response
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};
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} catch (apiError) {
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// Use helper to get user-friendly error message
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const friendlyMessage = handleClaudeError(apiError);
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return {
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success: false,
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error: {
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code: 'AI_API_ERROR',
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message: friendlyMessage
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}
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};
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}
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} catch (error) {
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// Handle client initialization errors
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return {
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success: false,
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error: {
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code: 'AI_CLIENT_ERROR',
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message: error.message
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}
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};
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}
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}
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```
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@@ -64,86 +62,85 @@ export async function someAiOperationDirect(args, log, context) {
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```javascript
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// In your MCP tool implementation:
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import { AsyncOperationManager, StatusCodes } from '../../utils/async-operation-manager.js';
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import {
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AsyncOperationManager,
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StatusCodes
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} from '../../utils/async-operation-manager.js';
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import { someAiOperationDirect } from '../../core/direct-functions/some-ai-operation.js';
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export async function someAiOperation(args, context) {
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const { session, mcpLog } = context;
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const log = mcpLog || console;
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try {
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// Create operation description
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const operationDescription = `AI operation: ${args.someParam}`;
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// Start async operation
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const operation = AsyncOperationManager.createOperation(
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operationDescription,
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async (reportProgress) => {
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try {
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// Initial progress report
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reportProgress({
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progress: 0,
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status: 'Starting AI operation...'
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});
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// Call direct function with session and progress reporting
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const result = await someAiOperationDirect(
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args,
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log,
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{
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reportProgress,
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mcpLog: log,
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session
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}
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);
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// Final progress update
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reportProgress({
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progress: 100,
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status: result.success ? 'Operation completed' : 'Operation failed',
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result: result.data,
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error: result.error
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});
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return result;
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} catch (error) {
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// Handle errors in the operation
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reportProgress({
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progress: 100,
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status: 'Operation failed',
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error: {
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message: error.message,
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code: error.code || 'OPERATION_FAILED'
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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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);
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// Return immediate response with operation ID
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return {
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status: StatusCodes.ACCEPTED,
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body: {
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success: true,
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message: 'Operation started',
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operationId: operation.id
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}
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};
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} catch (error) {
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// Handle errors in the MCP tool
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log.error(`Error in someAiOperation: ${error.message}`);
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return {
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status: StatusCodes.INTERNAL_SERVER_ERROR,
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body: {
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success: false,
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error: {
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code: 'OPERATION_FAILED',
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message: error.message
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}
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}
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};
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}
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const { session, mcpLog } = context;
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const log = mcpLog || console;
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try {
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// Create operation description
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const operationDescription = `AI operation: ${args.someParam}`;
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// Start async operation
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const operation = AsyncOperationManager.createOperation(
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operationDescription,
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async (reportProgress) => {
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try {
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// Initial progress report
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reportProgress({
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progress: 0,
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status: 'Starting AI operation...'
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});
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// Call direct function with session and progress reporting
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const result = await someAiOperationDirect(args, log, {
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reportProgress,
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mcpLog: log,
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session
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});
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// Final progress update
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reportProgress({
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progress: 100,
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status: result.success ? 'Operation completed' : 'Operation failed',
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result: result.data,
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error: result.error
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});
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return result;
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} catch (error) {
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// Handle errors in the operation
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reportProgress({
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progress: 100,
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status: 'Operation failed',
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error: {
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message: error.message,
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code: error.code || 'OPERATION_FAILED'
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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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);
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// Return immediate response with operation ID
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return {
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status: StatusCodes.ACCEPTED,
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body: {
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success: true,
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message: 'Operation started',
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operationId: operation.id
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}
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};
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} catch (error) {
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// Handle errors in the MCP tool
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log.error(`Error in someAiOperation: ${error.message}`);
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return {
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status: StatusCodes.INTERNAL_SERVER_ERROR,
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body: {
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success: false,
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error: {
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code: 'OPERATION_FAILED',
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message: error.message
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}
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}
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};
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}
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}
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```
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@@ -151,58 +148,56 @@ export async function someAiOperation(args, context) {
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```javascript
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// In your direct function:
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import {
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getPerplexityClientForMCP,
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getBestAvailableAIModel
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import {
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getPerplexityClientForMCP,
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getBestAvailableAIModel
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} from '../utils/ai-client-utils.js';
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export async function researchOperationDirect(args, log, context) {
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try {
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// Get the best AI model for this operation based on needs
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const { type, client } = await getBestAvailableAIModel(
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context.session,
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{ requiresResearch: true },
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log
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);
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// Report which model we're using
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if (context.reportProgress) {
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await context.reportProgress({
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progress: 10,
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status: `Using ${type} model for research...`
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});
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}
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// Make API call based on the model type
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if (type === 'perplexity') {
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// Call Perplexity
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const response = await client.chat.completions.create({
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model: context.session?.env?.PERPLEXITY_MODEL || 'sonar-medium-online',
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messages: [
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{ role: 'user', content: args.researchQuery }
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],
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temperature: 0.1
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});
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return {
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success: true,
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data: response.choices[0].message.content
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};
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} else {
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// Call Claude as fallback
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// (Implementation depends on specific needs)
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// ...
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}
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} catch (error) {
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// Handle errors
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return {
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success: false,
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error: {
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code: 'RESEARCH_ERROR',
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message: error.message
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}
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};
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}
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try {
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// Get the best AI model for this operation based on needs
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const { type, client } = await getBestAvailableAIModel(
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context.session,
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{ requiresResearch: true },
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log
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);
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// Report which model we're using
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if (context.reportProgress) {
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await context.reportProgress({
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progress: 10,
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status: `Using ${type} model for research...`
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});
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}
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// Make API call based on the model type
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if (type === 'perplexity') {
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// Call Perplexity
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const response = await client.chat.completions.create({
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model: context.session?.env?.PERPLEXITY_MODEL || 'sonar-medium-online',
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messages: [{ role: 'user', content: args.researchQuery }],
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temperature: 0.1
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});
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return {
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success: true,
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data: response.choices[0].message.content
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};
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} else {
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// Call Claude as fallback
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// (Implementation depends on specific needs)
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// ...
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}
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} catch (error) {
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// Handle errors
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return {
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success: false,
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error: {
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code: 'RESEARCH_ERROR',
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message: error.message
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}
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};
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}
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}
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```
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@@ -214,9 +209,9 @@ import { getModelConfig } from '../utils/ai-client-utils.js';
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// Using custom defaults for a specific operation
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const operationDefaults = {
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model: 'claude-3-haiku-20240307', // Faster, smaller model
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maxTokens: 1000, // Lower token limit
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temperature: 0.2 // Lower temperature for more deterministic output
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model: 'claude-3-haiku-20240307', // Faster, smaller model
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maxTokens: 1000, // Lower token limit
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temperature: 0.2 // Lower temperature for more deterministic output
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};
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// Get model config with operation-specific defaults
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@@ -224,30 +219,34 @@ const modelConfig = getModelConfig(context.session, operationDefaults);
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// Now use modelConfig in your API calls
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const response = await client.messages.create({
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model: modelConfig.model,
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max_tokens: modelConfig.maxTokens,
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temperature: modelConfig.temperature,
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// Other parameters...
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model: modelConfig.model,
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max_tokens: modelConfig.maxTokens,
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temperature: modelConfig.temperature
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// Other parameters...
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});
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```
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## Best Practices
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1. **Error Handling**:
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- Always use try/catch blocks around both client initialization and API calls
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- Use `handleClaudeError` to provide user-friendly error messages
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- Return standardized error objects with code and message
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2. **Progress Reporting**:
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- Report progress at key points (starting, processing, completing)
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- Include meaningful status messages
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- Include error details in progress reports when failures occur
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3. **Session Handling**:
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- Always pass the session from the context to the AI client getters
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- Use `getModelConfig` to respect user settings from session
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4. **Model Selection**:
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- Use `getBestAvailableAIModel` when you need to select between different models
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- Set `requiresResearch: true` when you need Perplexity capabilities
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@@ -255,4 +254,4 @@ const response = await client.messages.create({
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- Create descriptive operation names
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- Handle all errors within the operation function
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- Return standardized results from direct functions
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- Return immediate responses with operation IDs
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- Return immediate responses with operation IDs
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@@ -14,22 +14,22 @@ MCP (Model Control Protocol) provides the easiest way to get started with Task M
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```json
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{
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"mcpServers": {
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"taskmaster-ai": {
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"command": "npx",
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"args": ["-y", "task-master-ai", "mcp-server"],
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"env": {
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"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
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"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
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"MODEL": "claude-3-7-sonnet-20250219",
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"PERPLEXITY_MODEL": "sonar-pro",
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"MAX_TOKENS": 128000,
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"TEMPERATURE": 0.2,
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"DEFAULT_SUBTASKS": 5,
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"DEFAULT_PRIORITY": "medium"
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}
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}
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}
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"mcpServers": {
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"taskmaster-ai": {
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"command": "npx",
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"args": ["-y", "task-master-ai", "mcp-server"],
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"env": {
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"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
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"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
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"MODEL": "claude-3-7-sonnet-20250219",
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"PERPLEXITY_MODEL": "sonar-pro",
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"MAX_TOKENS": 128000,
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"TEMPERATURE": 0.2,
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"DEFAULT_SUBTASKS": 5,
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"DEFAULT_PRIORITY": "medium"
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}
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}
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}
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}
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```
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Reference in New Issue
Block a user