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/ macOSbrew install ffmpeg/ Linuxsudo apt install ffmpeg - tesseract(pytesseract OCR):Windows 官方安装器或
choco install tesseract/ macOSbrew install tesseract/ Linuxsudo 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_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
Metadata
Release files for modeleyes 0.1.0
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| modeleyes-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.0 kB
Release files / modeleyes-0.1.0.tar.gz
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