# import requests
# import json
#
#
# def deepseek_generation(prompt, api_key):
#     """
#     调用DeepSeek模型的生成接口
#     参数:
#         prompt: 用户输入的提示文本
#         api_key: 用户的API密钥
#     返回:
#         str: 模型生成的文本
#     """
#     url = "https://api.deepseek.com/v1/chat/completions"
#
#     headers = {
#         "Content-Type": "application/json",
#         "Authorization": f"Bearer {api_key}",
#         "Accept": "application/json"
#     }
#
#     # payload = {
#     #     "model": "deepseek-reasoner",
#     #     "messages": [
#     #         {"role": "user", "content": prompt}
#     #     ],
#     #     "temperature": 0.3,
#     #     "max_tokens": 2048
#     # }
#     payload = {
#         "model": "deepseek-chat",  # 确认模型名称
#         "messages": [
#             {"role": "system", "content": "你是一个有帮助的助手"},
#             {"role": "user", "content": prompt}
#         ],
#         "temperature": 0.7,  # 调整为官网默认值
#         "max_tokens": 2048,
#         "top_p": 1,
#         "frequency_penalty": 0
#     }
#     try:
#         response = requests.post(url, headers=headers, data=json.dumps(payload))
#         response.raise_for_status()
#
#         result = response.json()
#         return result['choices'][0]['message']['content']
#     except requests.exceptions.RequestException as e:
#         print(f"API请求错误: {e}")
#         return None
#     except KeyError:
#         print("响应格式解析失败")
#         return None
#
#
# if __name__ == "__main__":
#     # 使用示例
#     api_key = "sk-055784b1d4904ce6a34b5733a091c130"  # 替换为你的实际API密钥
#     user_input = input("请输入您的问题：")
#
#     response = deepseek_generation(user_input, api_key)
#
#     if response:
#         print("\nDeepSeek回答：")
#         print(response)
#     else:
#         print("生成内容时出现错误")


import os
from openai import OpenAI

client = OpenAI(
    api_key = os.environ.get("5017c24f-581f-48fb-abef-8ac4654e9018"),
    base_url = "https://ark.cn-beijing.volces.com/api/v3",
)

# Non-streaming:
print("----- standard request -----")
completion = client.chat.completions.create(
    model = "deepseek-r1-250120",  # your model endpoint ID
    messages = [
        {"role": "system", "content": "你是人工智能助手"},
        {"role": "user", "content": "帮我生成无忧渡电视剧中的实景拍摄地和行程安排？"},
    ],
)
print(completion.choices[0].message.content)

# Streaming:
print("----- streaming request -----")
stream = client.chat.completions.create(
    model = "deepseek-r1-250120",  # your model endpoint ID
    messages = [
        {"role": "system", "content": "你是人工智能助手"},
        {"role": "user", "content": "帮我生成无忧渡电视剧中的实景拍摄地和行程安排？"},
    ],
    stream=True
)

for chunk in stream:
    if not chunk.choices:
        continue
    print(chunk.choices[0].delta.content, end="")
print()