Update app.py

app.py

@@ -1,17 +1,16 @@
 import os
 from collections.abc import Iterator
 from threading import Thread
-import ai_gradio
 import gradio as gr
 import spaces
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
 
 DESCRIPTION = """
-# QwQ Tiny & Kokoro Chatbot
+# QwQ Tiny
 """
 
-css = '''
+css ='''
 h1 {
   text-align: center;
   display: block;
@@ -40,12 +39,6 @@ model = AutoModelForCausalLM.from_pretrained(
 )
 model.eval()
 
-# Load Kokoro chatbot
-kokoro_demo = gr.load(
-    name='onnx-community:kokoro-v1_0',
-    src='ai_gradio.registry',
-)
-kokoro_demo.fn = spaces.GPU()(kokoro_demo.fn)
 
 @spaces.GPU
 def generate(
@@ -57,21 +50,6 @@ def generate(
     top_k: int = 50,
     repetition_penalty: float = 1.2,
 ) -> Iterator[str]:
-    # Check for tags in the message
-    if "@voice" in message:
-        # Remove the tag from the message
-        message = message.replace("@voice", "").strip()
-        # Use Kokoro for voice
-        yield kokoro_demo.fn(message)
-    elif "@text" in message:
-        # Remove the tag from the message
-        message = message.replace("@text", "").strip()
-        # Fall through to text generation
-    else:
-        # Default to text generation if no tag is specified
-        pass
-
-    # Text generation logic (QwQ Tiny)
     conversation = [*chat_history, {"role": "user", "content": message}]
 
     input_ids = tokenizer.apply_chat_template(conversation, add_generation_prompt=True, return_tensors="pt")
@@ -100,6 +78,7 @@ def generate(
         outputs.append(text)
         yield "".join(outputs)
 
+
 demo = gr.ChatInterface(
     fn=generate,
     additional_inputs=[
@@ -145,8 +124,6 @@ demo = gr.ChatInterface(
         ["Write a Python function to check if a number is prime. "],
         ["What causes rainbows to form?"],
         ["Rewrite the following sentence in passive voice: 'The dog chased the cat.'"],
-        ["@voice Hello, how are you today?"],
-        ["@text Explain the theory of relativity."],
     ],
     cache_examples=False,
     type="messages",
@@ -155,5 +132,6 @@ demo = gr.ChatInterface(
     fill_height=True,
 )
 
+
 if __name__ == "__main__":
     demo.queue(max_size=20).launch()