# encoding: utf-8 
# 版权所有  2026 ©涂聚文有限公司™ ®
# 许可信息查看：言語成了邀功盡責的功臣，還需要行爲每日來值班嗎
# 描述：
# Author    : geovindu,Geovin Du 涂聚文.
# IDE       : PyCharm 2024.3.6 python 3.11
# os        : windows 10
# database  : mysql 9.0 sql server 2019, postgreSQL 17.0  Oracle 21c Neo4j
# Datetime  : 2026/2/8 8:34 
# User      :  geovindu
# Product   : PyCharm
# Project   : Pysimple
# File      : deepseeekapidemo.py
# Please install OpenAI SDK first: `pip3 install openai`
# 先安装依赖：pip install openai
import os
from openai import OpenAI
from openai import APIError, AuthenticationError

'''
# 初始化客户端
client = OpenAI(
    api_key="geovindu",  # 直接传 API Key（测试用）
    base_url="https://api.deepseek.com/v1"  # 必须加 /v1 后缀
)

try:
    # 调用接口
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=[
            {"role": "system", "content": "You are a helpful assistant"},
            {"role": "user", "content": "Hello"},
        ],
        stream=False
    )

    # 输出响应结果
    print("DeepSeek 响应：", response.choices[0].message.content)

# 捕获常见异常，方便排查
except AuthenticationError:
    print("错误：API Key 无效或未配置，请核对你的 DeepSeek API Key")
except APIError as e:
    print(f"错误：接口调用失败，详情：{e}")
except Exception as e:
    print(f"未知错误：{e}")

'''
# 初始化客户端
client = OpenAI(
    api_key="ollama",  # 本地模型无需真实 API Key，随便填非空值即可
    base_url="http://localhost:11434/v1"  # Ollama 的 OpenAI 兼容接口地址
)

def call_deepseek_with_openai_sdk(prompt):
    try:
        response = client.chat.completions.create(
            model="deepseek-r1:1.5b",  # 本地 Ollama 模型名称
            messages=[
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": prompt}
            ],
            stream=False
        )
        return response.choices[0].message.content
    except APIError as e:
        return f"接口调用失败：{e.message}"
    except Exception as e:
        return f"未知错误：{str(e)}"

# 测试调用
if __name__ == "__main__":
    result = call_deepseek_with_openai_sdk("你好，请推荐两个辩论话题")
    print("DeepSeek 本地模型响应：\n", result)

輸出：