z-ai-api

Original：🇺🇸 English
Translated

Z.ai API integration for building applications with GLM models. Use when working with Z.ai/ZhipuAI APIs for: (1) Chat completions with GLM-4.7/4.6/4.5 models, (2) Vision/multimodal tasks with GLM-4.6V, (3) Image generation with GLM-Image or CogView-4, (4) Video generation with CogVideoX-3 or Vidu models, (5) Audio transcription with GLM-ASR-2512, (6) Function calling and tool use, (7) Web search integration, (8) Translation, slide/poster generation agents. Triggers: Z.ai, ZhipuAI, GLM, BigModel, Zhipu, CogVideoX, CogView, Vidu.

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Sourcejrajasekera/claude-skills
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NPX Install

npx skill4agent add jrajasekera/claude-skills z-ai-api

Tags

Translated version includes tags in frontmatter
zhipuai-apiglm-modelsmultimodal-aimedia-generationfunction-calling

SKILL.md Content

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Z.ai API Skill

Quick Reference

Base URL: 
https://api.z.ai/api/paas/v4
Coding Plan URL: 
https://api.z.ai/api/coding/paas/v4
Auth: 
Authorization: Bearer YOUR_API_KEY

Core Endpoints

EndpointPurpose
/chat/completions
Text/vision chat
/images/generations
Image generation
/videos/generations
Video generation (async)
/audio/transcriptions
Speech-to-text
/web_search
Web search
/async-result/{id}
Poll async tasks
/v1/agents
Translation, slides, effects

Model Selection

Chat (pick by need):
  • glm-4.7
    — Latest flagship, best quality, agentic coding
  • glm-4.7-flash
    — Fast, high quality
  • glm-4.6
    — Reliable general use
  • glm-4.5-flash
    — Fastest, lower cost
Vision:
  • glm-4.6v
    — Best multimodal (images, video, files)
  • glm-4.6v-flash
    — Fast vision
Media:
  • glm-image
    — High-quality images (HD, ~20s)
  • cogview-4-250304
    — Fast images (~5-10s)
  • cogvideox-3
    — Video, up to 4K, 5-10s
  • viduq1-text/image
    — Vidu video generation

Implementation Patterns

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

Key Parameters

ParameterValuesNotes
temperature
0.0-1.0GLM-4.7: 1.0, GLM-4.5: 0.6 default
top_p
0.01-1.0Default ~0.95
max_tokens
variesGLM-4.7: 128K, GLM-4.5: 96K max
stream
boolEnable SSE streaming
response_format
{"type": "json_object"}
Force JSON output

Error Handling

  • 429: Rate limited — implement exponential backoff
  • 401: Bad API key — verify credentials
  • sensitive: Content filtered — modify input
python
if response.choices[0].finish_reason == "tool_calls":
    # Execute function and continue conversation
elif response.choices[0].finish_reason == "length":
    # Increase max_tokens or truncate
elif response.choices[0].finish_reason == "sensitive":
    # Content was filtered

Reference Files

For detailed API specifications, consult:
  • references/chat-completions.md
    — Full chat API, parameters, models
  • references/tools-and-functions.md
    — Function calling, web search, retrieval
  • references/media-generation.md
    — Image, video, audio APIs
  • references/agents.md
    — Translation, slides, effects agents
  • references/error-codes.md
    — Error handling, rate limits