Update app.py

app.py

@@ -2,17 +2,14 @@ import gradio as gr
 import numpy as np
 from huggingface_hub import InferenceClient
 import os
-print(os.getenv('hf_token'))
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# 获取 HuggingFace 的 API Token
 client = InferenceClient(
     "microsoft/Phi-3-mini-4k-instruct",
     token=os.getenv('hf_token'),
 )
 
-
+# 定义 respond 函数，用于生成聊天回复
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -45,24 +42,6 @@ def respond(
         response += token
         yield response
 
-def reverse_audio(audio):
-    sr, data = audio
-    return (sr, np.flipud(data))
-
-input_audio = gr.Audio(
-    sources=["microphone"],
-    waveform_options=gr.WaveformOptions(
-        waveform_color="#01C6FF",
-        waveform_progress_color="#0066B4",
-        skip_length=2,
-        show_controls=False,
-    ),
-)
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-
 # 定义音频处理函数
 def process_audio(audio):
     if audio is None:
@@ -74,22 +53,38 @@ def process_audio(audio):
 
     return 'True'
 
+# 定义聊天逻辑，更新聊天历史记录
+def chat_with_model(user_message, history):
+    system_message = "You are chatting with a helpful assistant."
+    max_tokens = 200
+    temperature = 0.7
+    top_p = 0.9
+
+    # 调用 respond 函数，生成回复
+    bot_response = next(respond(user_message, history, system_message, max_tokens, temperature, top_p))
+
+    # 将用户消息和模型回复添加到历史记录中
+    history.append((user_message, bot_response))
+    return history, history
+
 # 创建 Gradio 接口
 def create_interface():
     with gr.Blocks() as demo:
         # 标题
         gr.Markdown("# 语音识别与生成系统")
-        
+
         # 输入部分：音频上传
         with gr.Row():
-            audio_input = gr.Audio(    
+            audio_input = gr.Audio(
                 sources=["microphone"],
                 waveform_options=gr.WaveformOptions(
                     waveform_color="#01C6FF",
                     waveform_progress_color="#0066B4",
                     skip_length=2,
                     show_controls=False,
-                ),label="音频生成")
+                ), 
+                label="音频生成"
+            )
         
         # 输出部分：文本识别结果和音频播放
         with gr.Row():
@@ -98,14 +93,25 @@ def create_interface():
 
         # 处理按钮
         process_button = gr.Button("处理音频")
-        
+
         # 绑定处理逻辑
         process_button.click(process_audio, inputs=[audio_input], outputs=[recognized_text])
-    
-    return demo
 
+        # 添加聊天框
+        with gr.Row():
+            chatbot = gr.Chatbot(label="Chatbot")  # 显示聊天记录的区域
+            user_input = gr.Textbox(placeholder="Type a message...", label="输入消息")  # 用户输入区域
+            send_button = gr.Button("发送")  # 发送消息的按钮
+
+        # 聊天历史记录
+        chat_history = gr.State([])  # 用于存储聊天历史
+
+        # 点击发送按钮时，调用 chat_with_model 函数并更新聊天记录
+        send_button.click(chat_with_model, inputs=[user_input, chat_history], outputs=[chatbot, chat_history])
+
+    return demo
 
 
 if __name__ == "__main__":
     demo = create_interface()
-    demo.launch()
+    demo.launch()