df_string_output

app.py

@@ -6,82 +6,51 @@ from openai import OpenAI
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 client = OpenAI(api_key=OPENAI_API_KEY)
 
-
-
 def process_file(file):
     # 读取文件
     if file.name.endswith('.csv'):
         df = pd.read_csv(file)
     else:
         df = pd.read_excel(file)
-
     # 将 DataFrame 转换为字符串
-    df_string = df.to_string()
-
-    # 返回 DataFrame 字符串，以用作聊天机器人的系统提示
-    return df_string
-
-def respond(user_message, chat_history):
-    print("=== 變數：user_message ===")
-    print(user_message)
-    print("=== 變數：chat_history ===")
-    print(chat_history)
-
-    sys_content = f"你是一個資料分析師，請用 {df_string_output} 為資料進行對話"
-    messages = [
-        {"role": "system", "content": sys_content},
-        {"role": "user", "content": user_message}
-    ]
-
-    print("=====messages=====")
-    print(messages)
-    print("=====messages=====")
+    return df.to_string()
 
+def respond(user_message, df_string, chat_history):
+    sys_content = f"你是一个资料分析师，以下是数据分析资料:\n{df_string}"
+    messages = chat_history if chat_history is not None else []
+    messages.append({"role": "system", "content": sys_content})
+    messages.append({"role": "user", "content": user_message})
 
     request_payload = {
         "model": "gpt-4-1106-preview",
         "messages": messages,
-        "max_tokens": 2000  # 設定一個較大的值，可根據需要調整
+        "max_tokens": 2000
     }
 
     response = client.chat.completions.create(**request_payload)
-    print(response)
-    
     response_text = response.choices[0].message.content.strip()
 
-    # 更新聊天历史
-    new_chat_history = (user_message, response_text)
-    if chat_history is None:
-        chat_history = [new_chat_history]
-    else:
-        chat_history.append(new_chat_history)
-
-    # 返回聊天历史和空字符串清空输入框
-    return "", chat_history
+    messages.append({"role": "assistant", "content": response_text})
 
+    return "", messages
 
 with gr.Blocks() as demo:
     with gr.Row():
         file_upload = gr.File(label="Upload your file")
-        df_string_output = gr.Textbox(label="DataFrame as String", visible=False)
+        df_string_output = gr.Variable()
 
     with gr.Row():
         chatbot = gr.Chatbot()
-    
+
     with gr.Row():
-        with gr.Column():
-            with gr.Group():
-                # password_input = gr.Textbox(label="Password", type="password")
-                msg = gr.Textbox(label="請输入對話內容")
-                send_button = gr.Button("發送")
+        msg = gr.Textbox(label="请输入对话内容")
+        send_button = gr.Button("发送")
 
-    # 当文件上传时，更新 DataFrame 字符串
     file_upload.change(process_file, inputs=file_upload, outputs=df_string_output)
 
-    # 处理聊天机器人的对话
     send_button.click(
         respond, 
-        inputs=[msg, chatbot], 
+        inputs=[msg, df_string_output, chatbot], 
         outputs=[msg, chatbot]
     )