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)

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

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
)

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)

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)

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)

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)

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)

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)

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}")