2464 Quickstartpython A18edb06

Documentation Index

Fetch the complete documentation index at: https://docs.z.ai/llms.txt Use this file to discover all available pages before exploring further.

OpenAI Python SDK

Z.AI provides interfaces compatible with OpenAI API, which means you can use existing OpenAI SDK code and seamlessly switch to Z.AI's model services by simply modifying the API key and base URL. This compatibility allows you to:

• Quickly migrate existing OpenAI applications
• Use familiar development patterns and tools
• Enjoy the powerful capabilities of Z.AI models
• Maintain code consistency and maintainability

Core Advantages

Environment Requirements

Install OpenAI Python SDK

Install using pip

# Install or upgrade to latest version
pip install --upgrade 'openai>=1.0'

# Verify installation
python -c "import openai; print(openai.__version__)"

Install using poetry

poetry add "openai>=1.0"

Quick Start

Get API Key

1. Access Z.AI Open Platform, Register or Login.
2. Create an API Key in the API Keys management page.
3. Copy your API Key for use.

Create Client

# Create Z.AI client
client = OpenAI(
    api_key="your-Z.AI-api-key",
    base_url="https://api.z.ai/api/paas/v4/"
)
```

# Use environment variables
client = OpenAI(
    api_key=os.getenv("ZAI_API_KEY"),
    base_url="https://api.z.ai/api/paas/v4/"
)
```

@dataclass
class Z.AIConfig:
    api_key: str
    base_url: str = "https://api.z.ai/api/paas/v4/"
    timeout: int = 30
    max_retries: int = 3

config = Z.AIConfig(api_key="your-api-key")
client = OpenAI(
    api_key=config.api_key,
    base_url=config.base_url,
    timeout=config.timeout,
    max_retries=config.max_retries
)
```

Quick Start Examples

Basic Chat

from openai import OpenAI

client = OpenAI(
    api_key="your-Z.AI-api-key",
    base_url="https://api.z.ai/api/paas/v4/"
)

completion = client.chat.completions.create(
    model="glm-5",
    messages=[
        {"role": "system", "content": "You are a smart and creative novelist"},
        {"role": "user", "content": "Please write a short fairy tale story as a fairy tale master"}
    ]
)

print(completion.choices[0].message.content)

Streaming Response

from openai import OpenAI

client = OpenAI(
    api_key="your-Z.AI-api-key",
    base_url="https://api.z.ai/api/paas/v4/"
)

stream = client.chat.completions.create(
    model="glm-5",
    messages=[
        {"role": "user", "content": "Write a poem about artificial intelligence"}
    ],
    stream=True,
    temperature=1.0
)

for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="", flush=True)

print()  # New line

Multi-turn Conversation

from openai import OpenAI

class ChatBot:
    def __init__(self, api_key: str):
        self.client = OpenAI(
            api_key=api_key,
            base_url="https://api.z.ai/api/paas/v4/"
        )
        self.conversation = [
            {"role": "system", "content": "You are a helpful AI assistant"}
        ]

    def chat(self, user_input: str) -> str:
        # Add user message
        self.conversation.append({"role": "user", "content": user_input})

        # Call API
        response = self.client.chat.completions.create(
            model="glm-5",
            messages=self.conversation,
            temperature=1.0
        )

        # Get AI response
        ai_response = response.choices[0].message.content

        # Add to conversation history
        self.conversation.append({"role": "assistant", "content": ai_response})

        return ai_response

    def clear_history(self):
        """Clear conversation history, keep system prompt"""
        self.conversation = self.conversation[:1]

# Usage example
bot = ChatBot("your-api-key")
print(bot.chat("Hello, please introduce yourself"))
print(bot.chat("Can you help me write code?"))
print(bot.chat("Write a Python quicksort algorithm"))

Advanced Features

Thinking Mode

In thinking mode, GLM-4.6, GLM-4.5 and GLM-4.5-Air can solve complex reasoning problems, including mathematics, science, and logic problems.

The param thinking.type can be either enabled or disabled.

import os
from openai import OpenAI

client = OpenAI(api_key='your-api-key', base_url='https://api.z.ai/api/paas/v4/')
response = client.chat.completions.create(
        model='glm-4.7',
        messages=[
            {"role": "system", "content": "you are a helpful assistant"},
            {"role": "user", "content": "what is the revolution of llm?"}
        ],
        stream=True,
        extra_body={
            "thinking": {
                "type": "enabled",
            },
        }
    )
for chunk in response:
    if chunk.choices[0].delta.reasoning_content:
        print(chunk.choices[0].delta.reasoning_content, end='')
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end='')

Function Calling

import json
from openai import OpenAI

client = OpenAI(
    api_key="your-Z.AI-api-key",
    base_url="https://api.z.ai/api/paas/v4/"
)

def get_weather(location: str) -> str:
    """Get weather information for specified location"""
    # This should call a real weather API
    return f"Weather in {location}: Sunny, 25°C"

# Define function description
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather information for specified location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "Location name, e.g.: Beijing, Shanghai"
                    }
                },
                "required": ["location"]
            }
        }
    }
]

# Call conversation with functions
response = client.chat.completions.create(
    model="glm-5",
    messages=[
        {"role": "user", "content": "How's the weather in Beijing today?"}
    ],
    tools=tools,
    tool_choice="auto"
)

# Handle function calls
message = response.choices[0].message
if message.tool_calls:
    for tool_call in message.tool_calls:
        if tool_call.function.name == "get_weather":
            args = json.loads(tool_call.function.arguments)
            result = get_weather(args["location"])
            print(f"Function call result: {result}")

Parameter Configuration

Common Parameters

Best Practices

Migration Guide

Migrating from OpenAI

If you're already using OpenAI API, migrating to Z.AI is very simple:

# Original OpenAI code
from openai import OpenAI

client = OpenAI(
    api_key="sk-...",  # OpenAI API Key
    # base_url uses default value
)

# Migrate to Z.AI, only need to modify two places
client = OpenAI(
    api_key="your-Z.AI-api-key",  # Replace with Z.AI API Key
    base_url="https://api.z.ai/api/paas/v4/"  # Add Z.AI base_url
)

# Other code remains unchanged
response = client.chat.completions.create(
    model="glm-5",  # Use Z.AI model
    messages=[{"role": "user", "content": "Hello!"}]
)

Getting Help