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modeleyes

多厂商多模态图片/视频描述 CLI + OCR 兜底——让纯文本大模型也能"看图"(model eyes)。

简体中文 | English

modeleyes 把图片/视频转成结构化文字描述,供 DeepSeek、GLM 等纯文本大模型理解视觉内容。多厂商视觉 API 自动检测、无 key 时 OCR 兜底,一行命令安装、三平台一致。

基于 vision-skill 改造为独立通用 CLI。

特性

  • 🖼️ 图片描述:结构化 7 段式(场景/背景/主体/文字/色彩/细节/印象),专为纯文本模型设计
  • 🎬 视频描述:关键帧提取 → 逐帧描述 → 汇总总结
  • 🔌 多厂商自动切换:智谱 / OpenAI / Anthropic / Google / 小米 MiMo,按注册顺序检测可用 API
  • 📝 OCR 兜底:无 API key 时降级 easyocr → pytesseract → Pillow 基础信息
  • 📋 多输入:本地文件、远程 URL、stdin 管道、多文件批处理
  • 🔍 魔数识别:无扩展名的 TUI 临时文件也能识别
  • 🌐 跨平台:Windows / macOS / Linux 安装与调用一致

快速开始

# 安装(任选其一)
uv tool install --from 'modeleyes[openai]' --python 3.12
pipx install "modeleyes[openai]"

# 配置 API key
export OPENAI_API_KEY="sk-..."

# 使用
modeleyes photo.jpg

安装

包安装(uv 首选 / pipx)

# 单厂商
uv tool install --from 'modeleyes[openai]' --python 3.12
# 全厂商 API(轻量,无 torch)
uv tool install --from 'modeleyes[all]' --python 3.12
# 全厂商 + OCR(含 torch,体积大)
uv tool install --from 'modeleyes[full]' --python 3.12

# 或用 pipx
pipx install "modeleyes[openai]"

⚠️ OCR 用途需 pin Python 3.12:easyocr 依赖 torch,而 torch 对 Python 3.14 的轮子尚不齐全,故 [ocr]/[full] 在 3.14 上会安装失败。纯 API 用途([openai]/[all])任意版本安全。uv 默认选最新 Python,故安装命令显式 --python 3.12。

可选 extras

extra 厂商/能力 依赖
[zhipu] 智谱 GLM zai-sdk
[openai] OpenAI + 小米 MiMo(复用 SDK) openai
[anthropic] Anthropic Claude anthropic
[google] Google Gemini google-genai
[ocr] easyocr 离线 OCR(含 torch) easyocr
[tesseract] tesseract OCR pytesseract
[all] 上述 4 个 API 厂商(轻量) —
[full] all + ocr + tesseract —

可选系统二进制

  • ffmpeg(视频关键帧提取):Windows winget install ffmpeg / macOS brew install ffmpeg / Linux sudo apt install ffmpeg
  • tesseract(pytesseract OCR):Windows 官方安装器或 choco install tesseract / macOS brew install tesseract / Linux sudo apt install tesseract-ocr tesseract-ocr-chi-sim

用法

modeleyes --list-providers                    # 列出厂商配置状态
modeleyes photo.jpg                           # 图片描述
cat screenshot.png | modeleyes -              # stdin 管道
modeleyes https://example.com/a.jpg           # 远程 URL
modeleyes video.mp4 --max-frames 8            # 视频(需 ffmpeg + key)
modeleyes a.jpg b.jpg                         # 多文件
modeleyes photo.jpg --provider zhipu --model glm-4.6v   # 指定厂商/模型
modeleyes photo.jpg --prompt "重点关注文字"    # 自定义提示词
python -m modeleyes photo.jpg                 # 模块调用(venv 内)

支持的厂商

厂商 环境变量 默认模型
智谱 GLM ZHIPU_API_KEY glm-4.6v
小米 MiMo MIMO_API_KEY mimo-v2.5
OpenAI OPENAI_API_KEY gpt-4o
Anthropic ANTHROPIC_API_KEY claude-sonnet-4-6
Google GOOGLE_API_KEY gemini-2.5-flash

配置 API key

三种方式任选:

# 1. 环境变量(临时)
export OPENAI_API_KEY="your-key"

# 2. 项目级(仅当前项目,推荐用于 Claude Code)
# 编辑 .claude/settings.local.json: { "env": { "OPENAI_API_KEY": "your-key" } }

# 3. 全局
# 编辑 ~/.claude/settings.json 的 env 字段

超时:默认 90s,可用 VISION_TIMEOUT=120 调整。

用环境变量覆盖默认模型

不必每次传 --model,用 VISION_MODEL 设置默认模型(优先级:--model 参数 > VISION_MODEL > 厂商默认值):

export VISION_MODEL="gpt-4o-mini"   # OpenAI 用 gpt-4o-mini 而非默认 gpt-4o
modeleyes photo.jpg

export VISION_MODEL="glm-4.6v"      # 智谱用 glm-4.6v
modeleyes photo.jpg

临时覆盖用 --model(优先级最高):

modeleyes photo.jpg --model gpt-4o   # 本次用 gpt-4o,忽略 VISION_MODEL

平台支持

平台 包安装 视频抽帧 OCR
Windows ✅ winget 装 ffmpeg/tesseract ✅ ✅
macOS ✅ brew 装 ffmpeg/tesseract ✅ ✅
Linux ✅ apt 装 ffmpeg/tesseract ✅ ✅

注意

仅在纯文本主模型下启用本工具。若主模型本身是多模态(如 GPT-4o、Claude Opus),它会冗余调用一次视觉 API,造成无谓开销与延迟。

致谢

基于 LearningByDoingNow/vision-skill 改造,感谢原作者。

许可证

MIT

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