2025.10.24

02 LLM基础与调用/1. llm基础调用.py

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+import os # 导入环境变量
+from dotenv import load_dotenv
+
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+
+
+from openai import OpenAI
+
+client = OpenAI(
+    api_key=api_key,
+    base_url="https://api.deepseek.com")
+
+response = client.chat.completions.create(
+    model="deepseek-chat",
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant"}, # 提示词角色
+        {"role": "user", "content": "Hello"}, # 用户输入的对话
+    ],
+    stream=False # 非流式输出，只会等语句全部生成才返回
+)
+
+print(response.choices[0].message.content)

02 LLM基础与调用/2. 问答agent--多轮对话.py

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+import os # 导入环境变量
+from dotenv import load_dotenv
+from openai import OpenAI
+
+load_dotenv()
+
+def create_client():
+    api_key = os.getenv("OPENAI_API_KEY")
+    return OpenAI(api_key=api_key,base_url="https://api.deepseek.com")
+
+def chat_loop(agent_client):
+    messages = [
+                {"role":"system","content":"你是一个历史老师，你会耐心的教导我有关的事情。同时你的回答会相对精简，在五十字内。"},
+                {"role":"user","content":"汉朝存在了多久，其中哪个皇帝你认为最厉害？"}
+            ]
+    while 1:
+        response = agent_client.chat.completions.create(
+            model="deepseek-chat",
+            messages=messages
+        )
+        answer = response.choices[0].message.content
+        print(f'回答:{answer}')
+
+        # 询问是否还有其他问题
+        user_input =input('您还有其他想继续问的吗 | (exit退出)\n')
+        if user_input == "exit":
+            break
+
+        # 继续记录对话(涵盖用户追问 + ai上句回答)
+        messages.append({"role":"user","content":user_input})
+        messages.append({"role":"assistant","content":answer})
+
+
+if __name__ == '__main__':
+    client = create_client()
+    chat_loop(client)