Update app.py

app.py

@@ -1,18 +1,140 @@
+import gradio as gr
 import os
-from openai import OpenAI
+import requests
 
-# 设置 API 密钥和 API 地址
-api_key = os.getenv("DASHSCOPE_API_KEY")  # 确保环境变量已设置
-base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+# 从环境变量中读取 API 密钥
+DASHSCOPE_API_KEY = os.getenv("DASHSCOPE_API_KEY")
+DASHSCOPE_API_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 
-# 创建 API 客户端
-client = OpenAI(api_key=api_key, base_url=base_url)
+# 设置 DeepSeek API 客户端
+class DeepSeekClient:
+    def __init__(self, api_key, base_url):
+        self.api_key = api_key
+        self.base_url = base_url
 
-# 测试调用
-response = client.chat.completions.create(
-    model="deepseek-r1",
-    messages=[{"role": "user", "content": "9.9和9.11谁大"}]
-)
+    def chat(self, question):
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
 
-# 输出响应内容
-print(response.choices[0].message["content"])
+        data = {
+            "model": "deepseek-r1",  # 使用 DeepSeek 模型
+            "messages": [{"role": "user", "content": question}],
+        }
+
+        try:
+            response = requests.post(
+                f"{self.base_url}/chat/completions",
+                headers=headers,
+                json=data
+            )
+            response.raise_for_status()
+            result = response.json()
+
+            # 获取思考过程和最终答案
+            reasoning_content = result["choices"][0].get("reasoning_content", "没有思考过程")
+            bot_response = result["choices"][0]["message"]["content"]
+
+            return bot_response, reasoning_content
+
+        except Exception as e:
+            return f"Error: {e}", None
+
+# 创建 DeepSeek 客户端
+client = DeepSeekClient(api_key=DASHSCOPE_API_KEY, base_url=DASHSCOPE_API_URL)
+
+# 定义聊天函数
+def answer(question, history):
+    if history is None:
+        history = []
+
+    # 获取模型响应
+    bot_response, reasoning_content = client.chat(question)
+
+    # 输出思考过程与最终答案（用于调试）
+    print("思考过程：", reasoning_content)
+    print("最终答案：", bot_response)
+
+    # 更新历史记录
+    history.append({"role": "user", "content": question})
+    history.append({"role": "assistant", "content": bot_response})
+
+    return history, history
+
+# 创建 Gradio 界面
+with gr.Blocks(css="""
+    /* 修改布局适应手机端 */
+    .gradio-container {
+        background-color: #f0f0f0;
+        border-radius: 15px;
+        padding: 20px;
+        max-width: 500px;
+        margin: auto;
+        box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
+    }
+    .gr-button {
+        background-color: #4CAF50;
+        color: white;
+        border-radius: 10px;
+        padding: 12px 25px;
+        border: none;
+        font-weight: bold;
+    }
+    .gr-button:hover {
+        background-color: #45a049;
+    }
+    .gr-chatbot {
+        font-family: 'Arial', sans-serif;
+        height: 300px;
+        max-height: 300px;
+        overflow-y: auto;
+        padding: 10px;
+        margin-bottom: 20px;
+        background-color: #ffffff;
+        border-radius: 15px;
+        box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    }
+    .chatbot-message {
+        margin: 10px;
+        padding: 10px;
+        border-radius: 12px;
+        background-color: #e1f5fe;
+    }
+    .user-message {
+        background-color: #a5d6a7;
+        color: #ffffff;
+    }
+    .assistant-message {
+        background-color: #e3f2fd;
+        color: #000000;
+    }
+    input[type="text"] {
+        font-size: 16px;
+        border-radius: 10px;
+        padding: 12px;
+        width: 100%;
+        background-color: #f9f9f9;
+        margin-top: 10px;
+    }
+    /* 手机端优化：输入框宽度和响应式设计 */
+    @media (max-width: 600px) {
+        .gradio-container {
+            padding: 15px;
+            width: 90%;
+        }
+        .gr-button {
+            padding: 10px 20px;
+        }
+    }
+""") as demo:
+
+    chatbot = gr.Chatbot(elem_id="chatbot", type="messages")  # 使用 Gradio 的聊天组件
+    state = gr.State([])
+
+    with gr.Row():
+        txt = gr.Textbox(placeholder="请输入您的问题并按回车发送", lines=1)
+
+    txt.submit(answer, [txt, state], [chatbot, state])
+
+demo.launch()