OpenAI SDK 兼容

# 安装或升级到最新版本
pip install --upgrade 'openai>=1.0'

# 验证安装
python -c "import openai; print(openai.__version__)"

poetry add "openai>=1.0"

from openai import OpenAI

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

completion = client.chat.completions.create(
    model="glm-4.5",
    messages=[
        {"role": "system", "content": "你是一个聪明且富有创造力的小说作家"},
        {"role": "user", "content": "请你作为童话故事大王，写一篇短篇童话故事"}
    ],
    top_p=0.7,
    temperature=0.9
)

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

stream = client.chat.completions.create(
    model="glm-4.5",
    messages=[
        {"role": "user", "content": "写一首关于人工智能的诗"}
    ],
    stream=True,
    temperature=0.8
)

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

print()  # 换行

class ChatBot:
    def __init__(self, api_key: str):
        self.client = OpenAI(
            api_key=api_key,
            base_url="https://open.bigmodel.cn/api/paas/v4/"
        )
        self.conversation = [
            {"role": "system", "content": "你是一个有用的AI助手"}
        ]
    
    def chat(self, user_input: str) -> str:
        # 添加用户消息
        self.conversation.append({"role": "user", "content": user_input})
        
        # 调用API
        response = self.client.chat.completions.create(
            model="glm-4-air-250414",
            messages=self.conversation,
            temperature=0.7
        )
        
        # 获取AI回复
        ai_response = response.choices[0].message.content
        
        # 添加到对话历史
        self.conversation.append({"role": "assistant", "content": ai_response})
        
        return ai_response
    
    def clear_history(self):
        """清除对话历史，保留系统提示"""
        self.conversation = self.conversation[:1]

# 使用示例
bot = ChatBot("your-api-key")
print(bot.chat("你好，请介绍一下自己"))
print(bot.chat("你能帮我写代码吗？"))
print(bot.chat("写一个Python的快速排序算法"))

import json

def get_weather(location: str) -> str:
    """获取指定地点的天气信息"""
    # 这里应该调用真实的天气API
    return f"{location}的天气：晴天，温度25°C"

# 定义函数描述
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取指定地点的天气信息",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "地点名称，例如：北京、上海"
                    }
                },
                "required": ["location"]
            }
        }
    }
]

# 调用带函数的对话
response = client.chat.completions.create(
    model="glm-4-air-250414",
    messages=[
        {"role": "user", "content": "北京今天天气怎么样？"}
    ],
    tools=tools,
    tool_choice="auto"
)

# 处理函数调用
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"函数调用结果: {result}")

import base64
from PIL import Image
import io

def encode_image(image_path: str) -> str:
    """将图像编码为base64字符串"""
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# 图像理解示例
image_base64 = encode_image("path/to/your/image.jpg")

response = client.chat.completions.create(
    model="glm-4v",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "请描述这张图片的内容"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{image_base64}"
                    }
                }
            ]
        }
    ],
    temperature=0.7
)

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

# 原来的 OpenAI 代码
from openai import OpenAI

client = OpenAI(
    api_key="sk-...",  # OpenAI API Key
    # base_url 使用默认值
)

# 迁移到智谱AI，只需要修改两个地方
client = OpenAI(
    api_key="your-zhipuai-api-key",  # 替换为智谱AI API Key
    base_url="https://open.bigmodel.cn/api/paas/v4/"  # 添加智谱AI base_url
)

# 其他代码保持不变
response = client.chat.completions.create(
    model="glm-4.5",  # 使用智谱AI模型
    messages=[{"role": "user", "content": "Hello!"}]
)