- name
- glmv-caption
- description
- metadata
- openclaw
- requires
- env
- primaryEnv
- ZHIPU_API_KEY
- emoji
- 🖼️
- homepage
- https://github.com/zai-org/GLM-V/tree/main/skills/glmv-caption
GLM-V Caption Skill
Generate captions for images, videos, and documents using the ZhiPu GLM-V multimodal model.
When to Use
- Describe, caption, summarize, or interpret image/video/document content
- User mentions "describe this image", "caption", "summarize this video", "图片描述", "视频摘要", "文档解读", "看图说话"
- Extract visual or textual information from media files
- Compare multiple images
- User provides an image/video/file and asks what's in it
Supported Input Types
| Type | Formats | Max Size | Max Count | Base64 |
|---|---|---|---|---|
| Image | jpg, png, jpeg | 5MB / 6000×6000px | 50 | ✅ |
| Video | mp4, mkv, mov | 200MB | — | ❌ |
| File | pdf, docx, txt, xlsx, pptx, jsonl | — | 50 | ❌ |
⚠️ file_url cannot mix with image_url or video_url in the same request. ⚠️ Videos and files only support URLs — local paths and base64 are NOT supported (images only).
Resource Links
| Resource | Link |
|---|---|
| Get API Key | https://bigmodel.cn/usercenter/proj-mgmt/apikeys |
| API Docs | Chat Completions / 对话补全 |
Prerequisites
API Key Setup / API Key 配置（Required / 必需）
This script reads the key from the ZHIPU_API_KEY environment variable and shares it with other Zhipu skills. 脚本通过 ZHIPU_API_KEY 环境变量获取密钥，与其他智谱技能共用同一个 key。
Get Key / 获取 Key： Visit Zhipu Open Platform API Keys / 智谱开放平台 API Keys to create or copy your key.
Setup options / 配置方式（任选一种）：
- OpenClaw config (recommended) / OpenClaw 配置（推荐）： Set in
openclaw.jsonunderskills.entries.glmv-caption.env:
"glmv-caption": { "enabled": true, "env": { "ZHIPU_API_KEY": "你的密钥" } }- Shell environment variable / Shell 环境变量： Add to
~/.zshrc:
export ZHIPU_API_KEY="你的密钥"- .env file / .env 文件： Create
.envin this skill directory:
ZHIPU_API_KEY=你的密钥⛔ MANDATORY RESTRICTIONS - DO NOT VIOLATE ⛔
- ONLY use GLM-V API — Execute the script
python scripts/glmv_caption.py - NEVER caption media yourself — Do NOT try to describe content using built-in vision or any other method
- NEVER offer alternatives — Do NOT suggest "I can try to describe it" or similar
- IF API fails — Display the error message and STOP immediately
- NO fallback methods — Do NOT attempt captioning any other way
📋 Output Display Rules (MANDATORY)
After running the script, you must show the full raw output to the user exactly as returned. Do not summarize, truncate, or only say "generated". Users need the original model output to evaluate quality.
- Image captioning: show the full caption text
- Multiple images: show each image result
- Video/files: show the full understanding result
- If token usage is included, you may optionally display it
How to Use
Caption an Image
python scripts/glmv_caption.py --images "https://example.com/photo.jpg"
python scripts/glmv_caption.py --images /path/to/photo.pngCaption Multiple Images
python scripts/glmv_caption.py --images img1.jpg img2.png "https://example.com/img3.jpg"Caption a Video
python scripts/glmv_caption.py --videos "https://example.com/clip.mp4"Caption a Document
python scripts/glmv_caption.py --files "https://example.com/report.pdf"
python scripts/glmv_caption.py --files "https://example.com/doc1.docx" "https://example.com/doc2.txt"Custom Prompt
python scripts/glmv_caption.py --images photo.jpg --prompt "Describe the architecture style in detail"Save Result
python scripts/glmv_caption.py --images photo.jpg --output result.jsonThinking Mode
python scripts/glmv_caption.py --images photo.jpg --thinkingCLI Reference
python {baseDir}/scripts/glmv_caption.py (--images IMG [IMG...] | --videos VID [VID...] | --files FILE [FILE...]) [OPTIONS]| Parameter | Required | Description |
|---|---|---|
--images, -i | One of | Image paths or URLs (supports multiple, base64 OK) |
--videos, -v | One of | Video paths or URLs (supports multiple, mp4/mkv/mov) |
--files, -f | One of | Document paths or URLs (supports multiple, pdf/docx/txt/xlsx/pptx/jsonl) |
--prompt, -p | No | Custom prompt (default: "请详细描述这张图片的内容" / "Please describe this image in detail") |
--model, -m | No | Model name (default: glm-4.6v) |
--temperature, -t | No | Sampling temperature 0-1 (default: 0.8) |
--top-p | No | Nucleus sampling 0.01-1.0 (default: 0.6) |
--max-tokens | No | Max output tokens (default: 1024, max 32768) |
--thinking | No | Enable thinking/reasoning mode |
--output, -o | No | Save result JSON to file |
--pretty | No | Pretty-print JSON output |
--stream | No | Enable streaming output |
Note: --images, --videos, and --files are mutually exclusive per API limits.
Response Format
{
"success": true,
"caption": "A landscape photo showing a mountain range at sunset...",
"usage": {
"prompt_tokens": 128,
"completion_tokens": 256,
"total_tokens": 384
}
}Key fields:
success— whether the request succeededcaption— the generated caption textusage— token usage statisticswarning— present when content was blocked by safety reviewerror— error details on failure
Error Handling
API key not configured:
ZHIPU_API_KEY not configured. Get your API key at: https://bigmodel.cn/usercenter/proj-mgmt/apikeys→ Show exact error to user, guide them to configure
Authentication failed (401/403): API key invalid/expired → reconfigure
Rate limit (429): Quota exhausted → inform user to wait
File not found: Local file missing → check path
Content filtered: warning field present → content blocked by safety review