Basic Chat
```python
from zai import ZaiClient
client = ZaiClient(api_key="YOUR_KEY")
response = client.chat.completions.create(
model="glm-4.7",
messages=[
{"role": "system", "content": "You are helpful."},
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
```
OpenAI SDK Compatibility
```python
from openai import OpenAI
client = OpenAI(
api_key="YOUR_ZAI_KEY",
base_url="https://api.z.ai/api/paas/v4/"
)
# Use exactly like OpenAI SDK
```
Streaming
```python
response = client.chat.completions.create(
model="glm-4.7",
messages=[...],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content, end="")
```
Function Calling
```python
tools = [{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather for a city",
"parameters": {
"type": "object",
"properties": {
"city": {"type": "string"}
},
"required": ["city"]
}
}
}]
response = client.chat.completions.create(
model="glm-4.7",
messages=[{"role": "user", "content": "Weather in Tokyo?"}],
tools=tools,
tool_choice="auto"
)
# Handle tool_calls in response.choices[0].message.tool_calls
```
Vision (Images/Video/Files)
```python
response = client.chat.completions.create(
model="glm-4.6v",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://..."}},
{"type": "text", "text": "Describe this image"}
]
}]
)
```
Image Generation
```python
response = client.images.generate(
model="glm-image",
prompt="A serene mountain at sunset",
size="1280x1280",
quality="hd"
)
print(response.data[0].url) # Expires in 30 days
```
Video Generation (Async)
```python
# Submit
response = client.videos.generate(
model="cogvideox-3",
prompt="A cat playing with yarn",
size="1920x1080",
duration=5
)
task_id = response.id
# Poll for result
import time
while True:
result = client.async_result.get(task_id)
if result.task_status == "SUCCESS":
print(result.video_result[0].url)
break
time.sleep(5)
```
Web Search Integration
```python
response = client.chat.completions.create(
model="glm-4.7",
messages=[{"role": "user", "content": "Latest AI news?"}],
tools=[{
"type": "web_search",
"web_search": {
"enable": True,
"search_result": True
}
}]
)
# Access response.web_search for sources
```
Thinking Mode (Chain-of-Thought)
```python
response = client.chat.completions.create(
model="glm-4.7",
messages=[...],
thinking={"type": "enabled"},
stream=True # Recommended with thinking
)
# Access reasoning_content in response
```
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