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ZhipuAI Open Platform Python SDK

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The official Python SDK for ZhipuAI's large model open interface, making it easier for developers to call ZhipuAI's open APIs.

✨ Features

• Type Safety: Complete type annotations for all interfaces
• Easy Integration: Simple initialization and intuitive method calls
• High Performance: Built-in connection pooling and request optimization
• Secure: Automatic token caching and secure API key management
• Lightweight: Minimal dependencies with efficient resource usage
• Streaming Support: Real-time streaming responses for chat completions

📦 Installation

Requirements

• Python: 3.9+
• Package Manager: pip

Install via pip

pip install zhipuai

Core Dependencies

🚀 Quick Start

Basic Usage

from zhipuai import ZhipuAI

Initialize client

client = ZhipuAI(api_key="your-api-key")

Create chat completion

response = client.chat.completions.create( model="glm-4", messages=[ {"role": "user", "content": "Hello, ZhipuAI!"} ] ) print(response.choices[0].message.content)

Client Configuration

Environment Variables

export ZHIPUAI_API_KEY="your-api-key" export ZHIPUAI_BASE_URL="https://open.bigmodel.cn/api/paas/v4/" # Optional

Code Configuration

from zhipuai import ZhipuAI

client = ZhipuAI( api_key="your-api-key", base_url="https://open.bigmodel.cn/api/paas/v4/" # Optional )

Advanced Configuration

Customize client behavior with additional parameters:

from zhipuai import ZhipuAI import httpx

client = ZhipuAI( api_key="your-api-key", timeout=httpx.Timeout(timeout=300.0, connect=8.0), # Request timeout max_retries=3, # Retry attempts base_url="https://open.bigmodel.cn/api/paas/v4/" # Custom API endpoint )

📖 Usage Examples

Basic Chat

from zhipuai import ZhipuAI

client = ZhipuAI(api_key="your-api-key") # Uses environment variable ZHIPUAI_API_KEY response = client.chat.completions.create( model="glm-4", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is artificial intelligence?"} ], tools=[ { "type": "web_search", "web_search": { "search_query": "Search the Zhipu", "search_result": True, } } ], extra_body={"temperature": 0.5, "max_tokens": 50} ) print(response)

Streaming Chat

from zhipuai import ZhipuAI

client = ZhipuAI(api_key="your-api-key") response = client.chat.completions.create( model="glm-4", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Tell me a story about AI."} ], stream=True )

for chunk in response: if chunk.choices[0].delta.content: print(chunk.choices[0].delta)

Multimodal Chat

import base64 from zhipuai import ZhipuAI

def encode_image(image_path): """Encode image to base64 format""" with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode('utf-8')

client = ZhipuAI(api_key="your-api-key") base64_image = encode_image("path/to/your/image.jpg")

response = client.chat.completions.create( model="glm-4v", extra_body={"temperature": 0.5, "max_tokens": 50}, messages=[ { "role": "user", "content": [ { "type": "text", "text": "What's in this image?" }, { "type": "image_url", "image_url": { "url": f"data:image/jpeg;base64,{base64_image}" } } ] } ] ) print(response)

Character Role-Playing

from zhipuai import ZhipuAI

client = ZhipuAI(api_key="your-api-key") response = client.chat.completions.create( model="charglm-3", messages=[ { "role": "user", "content": "Hello, how are you doing lately?" } ], meta={ "user_info": "I am a film director who specializes in music-themed movies.", "bot_info": "You are a popular domestic female singer and actress with outstanding musical talent.", "bot_name": "Xiaoya", "user_name": "Director" } ) print(response)

Assistant Conversation

from zhipuai import ZhipuAI

client = ZhipuAI(api_key="your-api-key") response = client.assistant.conversation( assistant_id="your_assistant_id", # You can use 65940acff94777010aa6b796 for testing model="glm-4-assistant", messages=[ { "role": "user", "content": [{ "type": "text", "text": "Help me search for the latest ZhipuAI product information" }] } ], stream=True, attachments=None, metadata=None, request_id="request_1790291013237211136", user_id="12345678" )

for chunk in response: print(chunk)

Video Generation

from zhipuai import ZhipuAI

client = ZhipuAI(api_key="your-api-key") response = client.videos.generations( model="cogvideox-2", prompt="A beautiful sunset beach scene", quality="quality", # Output mode: use "quality" for higher quality, "speed" for faster generation with_audio=True, # Generate video with background audio size="1920x1080", # Video resolution (up to 4K, e.g. "3840x2160") fps=30, # Frames per second (choose 30 fps or 60 fps) user_id="user_12345" )

Generation may take some time

result = client.videos.retrieve_videos_result(id=response.id) print(result)

🚨 Error Handling

The SDK provides comprehensive error handling:

from zhipuai import ZhipuAI import zhipuai

client = ZhipuAI()

try: response = client.chat.completions.create( model="glm-4", messages=[ {"role": "user", "content": "Hello, ZhipuAI!"} ] ) print(response.choices[0].message.content)

except zhipuai.APIStatusError as err: print(f"API Status Error: {err}") except zhipuai.APITimeoutError as err: print(f"Request Timeout: {err}") except Exception as err: print(f"Other Error: {err}")

Error Codes

📈 Version Updates

For detailed version history and update information, please see <Release-Note.md>.

📄 License

This project is licensed under the MIT License - see the file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📞 Support

For questions and technical support, please visit ZhipuAI Open Platform or check our documentation.