手把手教你Python如何调用API做个聊天机器人

pip install requests

import requests

# 你的API密钥（记得替换成自己的）
API_KEY = "your_api_key_here"
API_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"  # 智谱AI的接口

# 准备要发送的数据
headers = {
    "Authorization": f"Bearer {API_KEY}",  # 这行是证明你的身份
    "Content-Type": "application/json"     # 告诉服务器我发的是JSON格式
}

data = {
    "model": "glm-4",           # 选择模型版本
    "messages": [               # 你的对话内容
        {"role": "user", "content": "你好，介绍一下自己"}
    ]
}

# 发送请求（就像按下寄快递的按钮）
response = requests.post(API_URL, headers=headers, json=data)
print(response.json())  # 打印原始返回结果

response = requests.post(API_URL, headers=headers, json=data)
result = response.json()

# 从返回结果里挖出AI的回答
ai_message = result['choices'][0]['message']['content']
print(f"AI：{ai_message}")

import requests

API_KEY = "your_api_key_here"
API_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

# 用列表记录对话历史
messages = []

print("聊天机器人已启动！输入'退出'结束对话\n")

while True:
    user_input = input("你：")
    
    if user_input == "退出":
        print("再见！")
        break
    
    # 把用户的话加到历史记录
    messages.append({"role": "user", "content": user_input})
    
    data = {
        "model": "glm-4",
        "messages": messages  # 发送整个对话历史
    }
    
    response = requests.post(API_URL, headers=headers, json=data)
    ai_message = response.json()['choices'][0]['message']['content']
    
    # 把AI的回答也记录下来
    messages.append({"role": "assistant", "content": ai_message})
    
    print(f"AI：{ai_message}\n")

import requests

API_KEY = "your_api_key_here"
API_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

messages = []

print("聊天机器人已启动！输入'退出'结束对话\n")

while True:
    user_input = input("你：")
    
    if user_input == "退出":
        print("再见！")
        break
    
    messages.append({"role": "user", "content": user_input})
    
    data = {
        "model": "glm-4",
        "messages": messages
    }
    
    try:
        response = requests.post(API_URL, headers=headers, json=data, timeout=30)
        
        # 检查请求是否成功
        if response.status_code != 200:
            print(f"请求失败，错误码：{response.status_code}")
            messages.pop()  # 移除刚才添加的用户消息
            continue
        
        ai_message = response.json()['choices'][0]['message']['content']
        messages.append({"role": "assistant", "content": ai_message})
        print(f"AI：{ai_message}\n")
        
    except requests.exceptions.RequestException as e:
        print(f"网络错误：{e}")
        messages.pop()  # 出错了就撤回这条消息

import requests

# ========== 配置区 ==========
API_KEY = "your_api_key_here"  # 替换成你的密钥
API_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

messages = []  # 对话历史

# ========== 主程序 ==========
print("聊天机器人已启动！输入'退出'结束对话\n")

while True:
    user_input = input("你：")
    if user_input == "退出":
        break
    
    messages.append({"role": "user", "content": user_input})
    
    try:
        response = requests.post(
            API_URL, 
            headers=headers, 
            json={"model": "glm-4", "messages": messages},
            timeout=30
        )
        
        if response.status_code == 200:
            ai_message = response.json()['choices'][0]['message']['content']
            messages.append({"role": "assistant", "content": ai_message})
            print(f"AI：{ai_message}\n")
        else:
            print(f"请求失败：{response.status_code}")
            messages.pop()
    
    except Exception as e:
        print(f"出错了：{e}")
        messages.pop()

print("再见！")