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Metadata-Version: 2.1
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Name: zhipuai
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Version: 2.1.5.20250825
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Summary: A SDK library for accessing big model apis from ZhipuAI
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Author: Zhipu AI
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Requires-Python: >=3.8, !=2.7.*, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*, !=3.7.*
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Provides-Extra: cli
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Provides-Extra: extended-testing
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Requires-Dist: cachetools (>=4.2.2)
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Requires-Dist: httpx (>=0.23.0)
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Requires-Dist: pydantic (>=1.9.0,<3.0)
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Requires-Dist: pydantic-core (>=2.14.6)
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Requires-Dist: pyjwt (>=2.8.0,<2.9.0)
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Description-Content-Type: text/markdown
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# ZhipuAI Open Platform Python SDK
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[](https://pypi.org/project/zhipuai/)
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[](https://opensource.org/licenses/MIT)
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[](https://www.python.org/downloads/)
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[中文文档](README_CN.md) | English
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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.
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## ✨ Features
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- **Type Safety**: Complete type annotations for all interfaces
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- **Easy Integration**: Simple initialization and intuitive method calls
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- **High Performance**: Built-in connection pooling and request optimization
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- **Secure**: Automatic token caching and secure API key management
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- **Lightweight**: Minimal dependencies with efficient resource usage
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- **Streaming Support**: Real-time streaming responses for chat completions
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## 📦 Installation
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### Requirements
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- **Python**: 3.9+
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- **Package Manager**: pip
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### Install via pip
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```bash
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pip install zhipuai
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```
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### Core Dependencies
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| Package | Version | Purpose |
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|---------|---------|----------|
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| `httpx` | `>=0.23.0` | HTTP client for API requests |
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| `pydantic` | `>=1.9.0,<3.0.0` | Data validation and serialization |
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| `typing-extensions` | `>=4.0.0` | Enhanced type hints support |
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## 🚀 Quick Start
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### Basic Usage
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```python
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from zhipuai import ZhipuAI
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# Initialize client
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client = ZhipuAI(api_key="your-api-key")
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# Create chat completion
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response = client.chat.completions.create(
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model="glm-4",
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messages=[
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{"role": "user", "content": "Hello, ZhipuAI!"}
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]
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)
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print(response.choices[0].message.content)
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```
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### Client Configuration
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#### Environment Variables
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```bash
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export ZHIPUAI_API_KEY="your-api-key"
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export ZHIPUAI_BASE_URL="https://open.bigmodel.cn/api/paas/v4/" # Optional
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```
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#### Code Configuration
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(
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api_key="your-api-key",
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base_url="https://open.bigmodel.cn/api/paas/v4/" # Optional
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)
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```
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### Advanced Configuration
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Customize client behavior with additional parameters:
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```python
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from zhipuai import ZhipuAI
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import httpx
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client = ZhipuAI(
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api_key="your-api-key",
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timeout=httpx.Timeout(timeout=300.0, connect=8.0), # Request timeout
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max_retries=3, # Retry attempts
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base_url="https://open.bigmodel.cn/api/paas/v4/" # Custom API endpoint
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)
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```
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## 📖 Usage Examples
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### Basic Chat
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="your-api-key") # Uses environment variable ZHIPUAI_API_KEY
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response = client.chat.completions.create(
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model="glm-4",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "What is artificial intelligence?"}
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],
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tools=[
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{
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"type": "web_search",
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"web_search": {
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"search_query": "Search the Zhipu",
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"search_result": True,
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}
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}
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],
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extra_body={"temperature": 0.5, "max_tokens": 50}
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)
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print(response)
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```
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### Streaming Chat
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="your-api-key")
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response = client.chat.completions.create(
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model="glm-4",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Tell me a story about AI."}
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],
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stream=True
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)
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for chunk in response:
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if chunk.choices[0].delta.content:
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print(chunk.choices[0].delta)
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```
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### Multimodal Chat
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```python
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import base64
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from zhipuai import ZhipuAI
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def encode_image(image_path):
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"""Encode image to base64 format"""
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with open(image_path, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode('utf-8')
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client = ZhipuAI(api_key="your-api-key")
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base64_image = encode_image("path/to/your/image.jpg")
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response = client.chat.completions.create(
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model="glm-4v",
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extra_body={"temperature": 0.5, "max_tokens": 50},
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "What's in this image?"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64_image}"
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}
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}
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]
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}
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]
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)
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print(response)
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```
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### Character Role-Playing
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="your-api-key")
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response = client.chat.completions.create(
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model="charglm-3",
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messages=[
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{
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"role": "user",
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"content": "Hello, how are you doing lately?"
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}
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],
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meta={
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"user_info": "I am a film director who specializes in music-themed movies.",
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"bot_info": "You are a popular domestic female singer and actress with outstanding musical talent.",
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"bot_name": "Xiaoya",
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"user_name": "Director"
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}
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)
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print(response)
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```
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### Assistant Conversation
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="your-api-key")
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response = client.assistant.conversation(
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assistant_id="your_assistant_id", # You can use 65940acff94777010aa6b796 for testing
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model="glm-4-assistant",
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messages=[
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{
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"role": "user",
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"content": [{
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"type": "text",
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"text": "Help me search for the latest ZhipuAI product information"
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}]
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}
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],
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stream=True,
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attachments=None,
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metadata=None,
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request_id="request_1790291013237211136",
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user_id="12345678"
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)
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for chunk in response:
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print(chunk)
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```
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### Video Generation
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```python
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from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="your-api-key")
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response = client.videos.generations(
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model="cogvideox-2",
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prompt="A beautiful sunset beach scene",
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quality="quality", # Output mode: use "quality" for higher quality, "speed" for faster generation
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with_audio=True, # Generate video with background audio
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size="1920x1080", # Video resolution (up to 4K, e.g. "3840x2160")
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fps=30, # Frames per second (choose 30 fps or 60 fps)
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user_id="user_12345"
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)
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# Generation may take some time
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result = client.videos.retrieve_videos_result(id=response.id)
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print(result)
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```
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## 🚨 Error Handling
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The SDK provides comprehensive error handling:
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```python
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from zhipuai import ZhipuAI
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import zhipuai
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client = ZhipuAI()
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try:
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response = client.chat.completions.create(
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model="glm-4",
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messages=[
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{"role": "user", "content": "Hello, ZhipuAI!"}
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]
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)
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print(response.choices[0].message.content)
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except zhipuai.APIStatusError as err:
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print(f"API Status Error: {err}")
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except zhipuai.APITimeoutError as err:
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print(f"Request Timeout: {err}")
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except Exception as err:
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print(f"Other Error: {err}")
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```
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### Error Codes
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| Status Code | Error Type | Description |
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|-------------|------------|-------------|
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| 400 | `APIRequestFailedError` | Invalid request parameters |
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| 401 | `APIAuthenticationError` | Authentication failed |
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| 429 | `APIReachLimitError` | Rate limit exceeded |
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| 500 | `APIInternalError` | Internal server error |
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| 503 | `APIServerFlowExceedError` | Server overloaded |
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| N/A | `APIStatusError` | General API error |
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## 📈 Version Updates
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For detailed version history and update information, please see [Release-Note.md](Release-Note.md).
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## 📄 License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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## 🤝 Contributing
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Contributions are welcome! Please feel free to submit a Pull Request.
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## 📞 Support
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For questions and technical support, please visit [ZhipuAI Open Platform](https://open.bigmodel.cn/) or check our documentation.
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