auto_analyze_image
Analyze images to extract and interpret code, architecture diagrams, errors, or documentation using AI-powered visual recognition. Supports file paths, URLs, or clipboard input.
Instructions
自动获取并分析图片（支持文件路径、网络URL或剪贴板）
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| imagePath | No | 图片文件路径或网络URL（可选，不提供则使用剪贴板） | |
| focusArea | No | 分析重点区域 | code |
Implementation Reference
- src/services/auto-image-service.ts:25-82 (handler)Core handler function that automatically acquires image from file path, network URL, or clipboard, processes it with sharp, analyzes using GLMService, and returns structured result including source.async autoGetAndAnalyzeImage( imagePath?: string, focusArea: 'code' | 'architecture' | 'error' | 'documentation' = 'code' ): Promise<ImageAnalysisResult & { source: string }> { try { logger.info('开始自动获取图片', { imagePath, focusArea }); let source: string; let finalImagePath: string; if (imagePath) { // 检查是否为网络URL if (this.isUrl(imagePath)) { source = 'url'; finalImagePath = await this.downloadImageFromUrl(imagePath); logger.info('从网络URL下载图片', { url: imagePath, path: finalImagePath }); } else { // 如果提供了文件路径，直接使用 source = 'file'; finalImagePath = imagePath; // 验证文件是否存在 if (!(await this.fileExists(finalImagePath))) { throw new Error(`文件不存在: ${imagePath}`); } logger.info('使用提供的文件路径', { path: finalImagePath }); } } else { // 如果没有提供文件路径，尝试从剪贴板获取 source = 'clipboard'; const clipboardImage = await this.getImageFromClipboard(); if (!clipboardImage) { throw new Error('无法获取图片：没有提供文件路径且剪贴板中没有图片'); } finalImagePath = clipboardImage; logger.info('从剪贴板获取图片', { path: finalImagePath }); } // 分析图片 const result = await this.analyzeImageFile(finalImagePath, focusArea); // 如果是剪贴板或URL下载的图片，清理临时文件 if (source === 'clipboard' || source === 'url') { await this.cleanupTempFile(finalImagePath); } return { ...result, source, }; } catch (error) { logger.error('自动获取并分析图片失败', { error }); throw new Error(`自动处理图片失败: ${error instanceof Error ? error.message : '未知错误'}`); } }
- src/index.ts:40-65 (registration)Registration of the tool in the ListToolsRequestSchema handler, including name, description, and input schema.this.server.setRequestHandler(ListToolsRequestSchema, async () => { return { tools: [ { name: 'auto_analyze_image', description: '自动获取并分析图片（支持文件路径、网络URL或剪贴板）', inputSchema: { type: 'object', properties: { imagePath: { type: 'string', description: '图片文件路径或网络URL（可选，不提供则使用剪贴板）', }, focusArea: { type: 'string', enum: ['code', 'architecture', 'error', 'documentation'], description: '分析重点区域', default: 'code', }, }, required: [], }, }, ], }; });
- src/index.ts:76-81 (registration)Dispatch logic in CallToolRequestSchema handler that invokes the auto_analyze_image handler when the tool name matches.if (name === 'auto_analyze_image') { result = await this.autoImageService.autoGetAndAnalyzeImage( typedArgs.imagePath, typedArgs.focusArea || 'code' ); } else {
- src/types/index.ts:1-16 (schema)TypeScript interface defining the structure of the image analysis result returned by the tool.export interface ImageAnalysisResult { description?: string; content?: string; type?: string; layout?: string; issues?: string[]; details?: string; summary: string; confidence: number; metadata?: { format?: string; width?: number; height?: number; fileSize?: string; }; }
- Helper method that processes the image file (resize, jpeg, base64), extracts metadata, calls GLMService for analysis, and structures the result.private async analyzeImageFile( imagePath: string, focusArea: 'code' | 'architecture' | 'error' | 'documentation' = 'code' ): Promise<ImageAnalysisResult> { try { // 读取图片文件 const imageBuffer = await fs.readFile(imagePath); // 使用 sharp 处理图片 const sharp = require('sharp'); const processedImage = await sharp(imageBuffer) .jpeg({ quality: 90 }) .resize(2048, 2048, { fit: 'inside', withoutEnlargement: true }) .toBuffer(); const base64 = processedImage.toString('base64'); // 获取基本信息 const metadata = await sharp(imageBuffer).metadata(); const fileSize = (imageBuffer.length / 1024).toFixed(2) + ' KB'; // 使用 GLM 服务分析图片 const analysisResult = await this.glmService.analyzeCode(base64, focusArea); // 解析结果 let result: ImageAnalysisResult; try { // 尝试解析JSON响应 const parsed = JSON.parse(analysisResult); result = { description: parsed.description || parsed.content, type: parsed.type, layout: parsed.layout, issues: parsed.issues, details: parsed.details, summary: parsed.summary || analysisResult.substring(0, 500), confidence: 0.9, metadata: { format: metadata.format, width: metadata.width, height: metadata.height, fileSize, }, }; } catch { // 如果不是JSON格式，直接使用文本响应 result = { summary: analysisResult, confidence: 0.8, metadata: { format: metadata.format, width: metadata.width, height: metadata.height, fileSize, }, }; } return result; } catch (error) { logger.error('分析图片文件失败', { path: imagePath, error }); throw new Error(`分析图片失败: ${error instanceof Error ? error.message : '未知错误'}`); } }