Update app.py

app.py

@@ -1,104 +1,96 @@
-import gradio as gr
 import openai
+import gradio as gr
 
-# Initialize the OpenAI client with your proxy API
+# 初始化 OpenAI API 客户端
 client = openai.OpenAI(
     api_key="sk-hm35RR1E0dfB26C8873BT3BlBKFJE681B3d87a6c4B3e8C44",
     base_url="https://aigptx.top/"
 )
 
-# Function to handle predictions
-def predict(inputs, top_p, temperature, system_prompt, chat_counter, chatbot=[], history=[]):  
-    # Build the system prompt if provided
-    messages = []
-    if system_prompt:
-        messages.append({"role": "system", "content": system_prompt})
-    
-    # Add previous conversation history
-    if chat_counter != 0:
-        for data in chatbot:
-            messages.append({"role": "user", "content": data[0]})
-            messages.append({"role": "assistant", "content": data[1]})
-    
-    # Add the current user input to the messages
-    messages.append({"role": "user", "content": inputs})
-    
-    payload = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages,
-        "temperature": temperature,
-        "top_p": top_p,
-        "n": 1,
-        "stream": True,
-        "presence_penalty": 0,
-        "frequency_penalty": 0,
-    }
+# 默认系统消息（可以通过UI定制）
+system_prompt = "您好！欢迎来到聊天机器人。请随时提出您的问题或想法。"
+
+# 添加用户消息到聊天记录
+def add_text(history, text, custom_prompt):
+    if not custom_prompt:
+        custom_prompt = system_prompt  # 使用默认系统提示
+    if text:
+        if not history:
+            history = [("System Message", custom_prompt)]
+        history.append((text, None))
+    else:
+        history.append(("System Message", "您发送了一个空消息，请输入您的问题或想法。"))
+    return history, ""
+
+# 调用 OpenAI GPT 生成回复
+def predict(history, custom_prompt):
+    if not custom_prompt:
+        custom_prompt = system_prompt  # 使用默认系统提示
+    if not history or (len(history) == 1 and history[0][0] == "System Message"):
+        history = [("System Message", custom_prompt)]
+        yield history
+        return history, ""
 
-    # Set the chat counter
-    chat_counter += 1
-    history.append(inputs)
+    history_ = history[1:] if history[0][0] == "System Message" else history
 
-    # Using the proxy API to get the response
-    response = client.ChatCompletion.create(
-        model=payload["model"],
-        messages=payload["messages"],
-        temperature=payload["temperature"],
-        top_p=payload["top_p"],
-        stream=payload["stream"],
-        presence_penalty=payload["presence_penalty"],
-        frequency_penalty=payload["frequency_penalty"]
+    history_openai_format = [{"role": "user", "content": human} for human, assistant in history_ if human]
+
+    if not history_openai_format:
+        yield history
+        return history
+
+    response = client.chat.completions.create(
+        model='gpt-4-1106-preview',
+        messages=[{"role": "system", "content": custom_prompt}] + history_openai_format,
+        temperature=0.9,
     )
 
-    token_counter = 0
-    partial_words = ""
-    
-    for chunk in response:
-        if 'choices' in chunk:
-            delta = chunk['choices'][0]['delta']
-            if 'content' in delta:
-                partial_words += delta['content']
-                if token_counter == 0:
-                    history.append(" " + partial_words)
-                else:
-                    history[-1] = partial_words
-                chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2)]
-                token_counter += 1
-                yield chat, history, chat_counter
+    history[-1][1] = response.choices[0].message.content
+    yield history
+
+# 构建 Gradio 界面
+with gr.Blocks() as demo:
+    gr.Markdown("<h1><center>聊天机器人</center></h1>")
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(
+                value=[("System Message", system_prompt)],
+            )
+            with gr.Row():
+                textbox = gr.Textbox(placeholder="请输入您的问题或想法", show_label=False, scale=2)
+                submit = gr.Button("💬 发送", scale=1)
 
-# Function to reset the textbox
-def reset_textbox():
-    return gr.update(value='')
+                # 自定义系统消息输入框
+                custom_system_prompt = gr.Textbox(
+                    value=system_prompt,
+                    placeholder="自定义系统消息，例如：'我是一个乐于助人的助手，请告诉我如何帮您'",
+                    label="自定义系统提示",
+                    lines=2
+                )
 
-# UI Components
-title = """<h1 align="center">Customizable Chatbot with OpenAI API</h1>"""
-description = """
-Explore the outputs of a GPT-3.5 model, with the ability to customize system prompts and interact with a history of conversation logs.
-"""
+                # 在用户输入消息时，传递自定义系统提示给 GPT 模型
+                textbox_msg = textbox.submit(
+                    add_text, 
+                    [chatbot, textbox, custom_system_prompt], 
+                    [chatbot, textbox], 
+                    queue=False
+                ).then(
+                    predict, 
+                    [chatbot, custom_system_prompt], 
+                    chatbot
+                )
 
-with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
-                      #chatbot {height: 520px; overflow: auto;}""") as demo:
-    
-    gr.HTML(title)
-    with gr.Column(elem_id="col_container"):
-        # Removed the API key input field
-        # openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here")
-        system_prompt = gr.Textbox(placeholder="Enter system prompt (optional)", label="System Prompt", lines=2)
-        chatbot = gr.Chatbot(elem_id='chatbot')
-        inputs = gr.Textbox(placeholder="Type your message here!", label="Input", lines=1)
-        send_btn = gr.Button("Send")
-        state = gr.State([])
-        chat_counter = gr.Number(value=0, visible=False, precision=0)
-        reset_btn = gr.Button("Reset Chat")
-        
-        # Input parameters for OpenAI API
-        with gr.Accordion("Model Parameters", open=False):
-            top_p = gr.Slider(minimum=0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (Nucleus Sampling)")
-            temperature = gr.Slider(minimum=0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature")
-        
-        # Submit input for model prediction with the send button
-        send_btn.click(predict, [inputs, top_p, temperature, system_prompt, chat_counter, chatbot, state], 
-                      [chatbot, state, chat_counter])
-        reset_btn.click(reset_textbox, [], [inputs])
-        inputs.submit(reset_textbox, [], [inputs])
+                submit.click(
+                    add_text, 
+                    inputs=[chatbot, textbox, custom_system_prompt], 
+                    outputs=[chatbot, textbox], 
+                    queue=False
+                ).then(
+                    predict, 
+                    [chatbot, custom_system_prompt], 
+                    chatbot
+                )
 
-    demo.queue().launch(debug=True)
+demo.queue()
+demo.launch()