Task Router Skill
Task Router
智谱 GLM-4V/4.6V 视觉模型调用技能。用于图像/视频理解、多模态对话、图表分析等任务。 当用户提到:图片理解、图像识别、视觉模型、GLM-4V、GLM-4.6V、多模态分析、看图说话、图表分析、视频理解时使用此技能。
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install baokui/glm-v-model打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
本技能提供调用智谱 AI 的 GLM-4V 和 GLM-4.6V 视觉模型的能力,支持图像理解、视频分析、图表解读等功能。
| 模型 | 说明 | 特点 |
|---|---|---|
| glm-4v | GLM-4 视觉模型 | 基础视觉理解 |
| glm-4.6v | GLM-4.6V 视觉模型 | 更强的视觉理解能力,支持更长上下文 |
from zai import ZhipuAiClient
import base64
client = ZhipuAiClient(api_key="YOUR_API_KEY")
# 读取本地图片并转为 base64
with open("image.jpg", "rb") as f:
img_base = base64.b64encode(f.read()).decode("utf-8")
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img_base}"}},
{"type": "text", "content": "描述这张图片"}
]
}],
thinking={"type": "enabled"}
)
print(response.choices[0].message.content)
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}},
{"type": "text", "content": "这张图片里有什么?"}
]
}]
)
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "图片1 base64 或 URL"}},
{"type": "image_url", "image_url": {"url": "图片2 base64 或 URL"}},
{"type": "text", "content": "比较这两张图片的异同"}
]
}]
)
# 支持理解视频内容
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "video_url", "video_url": {"url": "视频URL"}},
{"type": "text", "content": "描述这个视频的内容"}
]
}]
)
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# GLM 视觉模型调用
本技能提供调用智谱 AI 的 GLM-4V 和 GLM-4.6V 视觉模型的能力,支持图像理解、视频分析、图表解读等功能。
## 支持的模型
| 模型 | 说明 | 特点 |
|------|------|------|
| glm-4v | GLM-4 视觉模型 | 基础视觉理解 |
| glm-4.6v | GLM-4.6V 视觉模型 | 更强的视觉理解能力,支持更长上下文 |
## 快速使用
### 基本图像理解
```python
from zai import ZhipuAiClient
import base64
client = ZhipuAiClient(api_key="YOUR_API_KEY")
# 读取本地图片并转为 base64
with open("image.jpg", "rb") as f:
img_base = base64.b64encode(f.read()).decode("utf-8")
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img_base}"}},
{"type": "text", "content": "描述这张图片"}
]
}],
thinking={"type": "enabled"}
)
print(response.choices[0].message.content)
```
### 使用图片URL
```python
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}},
{"type": "text", "content": "这张图片里有什么?"}
]
}]
)
```
### 多图理解
```python
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "图片1 base64 或 URL"}},
{"type": "image_url", "image_url": {"url": "图片2 base64 或 URL"}},
{"type": "text", "content": "比较这两张图片的异同"}
]
}]
)
```
### 视频理解(GLM-4.6V)
```python
# 支持理解视频内容
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "video_url", "video_url": {"url": "视频URL"}},
{"type": "text", "content": "描述这个视频的内容"}
]
}]
)
```
## 使用...Task Router
Register, communicate, and earn on the x402hub AI agent marketplace. Use when an agent needs to register on x402hub, browse or claim bounties, submit deliverables, send messages to other agents via x402 Relay,...
Real-time event bus for AI agents. Publish, subscribe, and share live signals across a network of agents with Unix-style simplicity.
OpenClaw integration guidance for CAPTCHAS Agent API, including OpenResponses tool schemas and plugin tool registration.