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docs: make English the default docs language and fix link paths
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zhayujie
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---
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title: vision - 图片理解
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description: 分析图片内容（识别、描述、OCR 等）
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title: vision - Image Understanding
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description: Analyze image content (recognition, description, OCR, etc.)
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---
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使用 Vision API 分析本地图片或图片 URL，支持内容描述、文字提取（OCR）、物体识别等。
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Analyze local images or image URLs using Vision API. Supports content description, text extraction (OCR), object recognition, and more.
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## 模型选择
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## Model Selection
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Vision 工具采用多级自动选择 + 自动兜底策略，无需手动配置即可使用：
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The vision tool uses a multi-level auto-selection strategy with automatic fallback — no manual configuration required:
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1. **主模型** — 优先使用当前配置的主模型进行图像识别（需要是多模态模型）
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2. **其他已配置模型** — 自动发现已配置 API Key 的其他多模态模型作为备选
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1. **Main model** — uses the currently configured main model for image recognition (must be a multimodal model)
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2. **Other configured models** — auto-discovers other multimodal models with configured API keys as alternatives
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如果当前 provider 调用失败，会自动尝试下一个，直到成功或全部失败。
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If the current provider fails, the tool automatically tries the next one until it succeeds or all fail.
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### 支持的模型
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### Supported Models
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| 厂商 | 视觉模型 | 说明 |
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| Provider | Vision Model | Notes |
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| --- | --- | --- |
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| OpenAI / 兼容协议 | 使用主模型 | 支持所有 OpenAI 协议兼容的多模态模型 |
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| 通义千问 (DashScope) | 使用主模型 | 例如 qwen3.6-plus 等 |
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| Claude | 使用主模型 | Anthropic 原生图像格式 |
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| Gemini | 使用主模型 | inlineData 格式 |
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| 豆包 (Doubao) | 使用主模型 | doubao-seed-2-0 系列原生支持 |
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| Kimi (Moonshot) | 使用主模型 | kimi-k2.6、kimi-k2.5 原生支持 |
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| 百度千帆 (Qianfan) | 使用主模型 | 默认使用多模态主模型 (如 ernie-5.1)，主模型不支持时兜底使用 ernie-4.5-turbo-vl |
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| 智谱 AI | glm-5v-turbo | 固定使用视觉专用模型 |
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| MiniMax | MiniMax-Text-01 | 固定使用视觉专用模型 |
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| OpenAI / Compatible | Main model | All OpenAI-protocol-compatible multimodal models |
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| Qwen (DashScope) | Main model | e.g. qwen3.6-plus, etc. |
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| Claude | Main model | Anthropic native image format |
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| Gemini | Main model | inlineData format |
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| Doubao | Main model | doubao-seed-2-0 series natively supported |
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| Kimi (Moonshot) | Main model | kimi-k2.6, kimi-k2.5 natively supported |
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| ERNIE | Main model | Defaults to the multimodal main model (e.g. `ernie-5.1`); falls back to `ernie-4.5-turbo-vl` when the main model is not multimodal |
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| ZhipuAI | glm-5v-turbo | Always uses the dedicated vision model |
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| MiniMax | MiniMax-Text-01 | Always uses the dedicated vision model |
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<Note>
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智谱和 MiniMax 的文本模型不支持图像理解，因此始终使用对应的视觉专用模型，无需手动指定。
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ZhipuAI and MiniMax text models do not support image understanding, so their dedicated vision models are always used automatically.
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</Note>
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> 当 `use_linkai=true` 时，默认使用 LinkAI 的多模态模型进行
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> When `use_linkai=true`, LinkAI's multimodal model is used by default.
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## 自定义配置
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## Custom Configuration
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如果希望指定 Vision 使用的模型，可在 `config.json` 中配置，例如：
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To specify the model used by Vision, configure it in `config.json`, for example:
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```json
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{
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@@ -48,28 +48,28 @@ Vision 工具采用多级自动选择 + 自动兜底策略，无需手动配置
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}
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```
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指定的模型会被**优先使用**，工具会根据模型名自动路由到对应的 provider；若调用失败，会自动 fallback 到其他已配置的 provider。
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The specified model is **used first**, and the tool automatically routes to the corresponding provider based on the model name; on failure, it falls back to other configured providers.
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大多数情况下无需配置，主模型支持多模态或配置任意一个支持视觉的 API Key 即可自动工作。
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In most cases no configuration is needed — the tool works automatically as long as the main model supports multimodal input or any vision-capable API key is configured.
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## 参数
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## Parameters
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| 参数 | 类型 | 必填 | 说明 |
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| Parameter | Type | Required | Description |
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| --- | --- | --- | --- |
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| `image` | string | 是 | 本地文件路径或 HTTP(S) 图片 URL |
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| `question` | string | 是 | 对图片提出的问题 |
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| `image` | string | Yes | Local file path or HTTP(S) image URL |
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| `question` | string | Yes | Question to ask about the image |
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支持的图片格式：jpg、jpeg、png、gif、webp
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Supported image formats: jpg, jpeg, png, gif, webp
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## 使用场景
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## Use Cases
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- 描述图片中的内容
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- 提取图片中的文字（OCR）
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- 识别物体、颜色、场景
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- 分析截图、文档扫描图片等
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- Describe image content
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- Extract text from images (OCR)
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- Identify objects, colors, scenes
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- Analyze screenshots and scanned documents
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<Note>
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超过 1MB 的图片会自动压缩后上传，所有图片（包括远程 URL）会统一转为 base64 传输，确保兼容所有模型后端。
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Images larger than 1MB are automatically compressed before upload. All images (including remote URLs) are converted to base64 for transmission to ensure compatibility with all model backends.
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</Note>
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