Update app.py

app.py

@@ -1,32 +1,39 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from gtts import gTTS
+import os
+import tempfile
 
-"""
-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
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+"""IMMY ON device Alpha version with TTS"""
 
+client = InferenceClient("Daemontatox/IMMY_1f")
+
+def text_to_speech(text):
+    """Convert text to speech and return the path to the audio file"""
+    tts = gTTS(text=text, lang='en')
+    with tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') as fp:
+        tts.save(fp.name)
+        return fp.name
 
 def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
+    message, 
+    history: list[tuple[str, str]], 
+    system_message, 
+    max_tokens, 
+    temperature, 
     top_p,
 ):
     messages = [{"role": "system", "content": system_message}]
-
+    
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
-
+    
     messages.append({"role": "user", "content": message})
-
     response = ""
-
+    
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,30 +42,84 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
+    
+    # Generate audio after the complete response is ready
+    audio_path = text_to_speech(response)
+    yield (response, audio_path)
 
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Message")
+    audio_output = gr.Audio(label="Response Audio")
+    
+    system_message = gr.Textbox(
+        value="You are Immy, a magical AI-powered teddy bear who loves chatting with children. You are kind, funny, and full of wonder, always ready to tell stories, answer questions, and offer friendly advice. Speak playfully and patiently, using simple, child-friendly language to encourage curiosity, learning, and imagination.",
+        label="System message"
+    )
+    max_tokens = gr.Slider(
+        minimum=1,
+        maximum=2048,
+        value=512,
+        step=1,
+        label="Max new tokens"
+    )
+    temperature = gr.Slider(
+        minimum=0.1,
+        maximum=4.0,
+        value=0.7,
+        step=0.1,
+        label="Temperature"
+    )
+    top_p = gr.Slider(
+        minimum=0.1,
+        maximum=1.0,
+        value=0.95,
+        step=0.05,
+        label="Top-p (nucleus sampling)"
+    )
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+    def user(user_message, history):
+        return "", history + [[user_message, None]]
+
+    def bot(
+        history,
+        system_message,
+        max_tokens,
+        temperature,
+        top_p
+    ):
+        user_message = history[-1][0]
+        generator = respond(
+            user_message,
+            history[:-1],
+            system_message,
+            max_tokens,
+            temperature,
+            top_p
+        )
+        
+        for response in generator:
+            if isinstance(response, tuple):
+                # This is the final response with audio
+                history[-1][1] = response[0]
+                yield history, response[1]
+            else:
+                # This is a text update
+                history[-1][1] = response
+                yield history, None
 
+    msg.submit(
+        user,
+        [msg, chatbot],
+        [msg, chatbot],
+        queue=False
+    ).then(
+        bot,
+        [chatbot, system_message, max_tokens, temperature, top_p],
+        [chatbot, audio_output]
+    )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()