Update app.py

app.py

@@ -1,31 +1,20 @@
 import gradio as gr
-from transformers import AutoProcessor, BarkModel
-import scipy.io.wavfile
-import numpy as np
+from transformers import pipeline
 
-# Model और Processor लोड करें
-processor = AutoProcessor.from_pretrained("suno/bark")
-model = BarkModel.from_pretrained("suno/bark")
-model.to("cuda")  # अगर GPU उपलब्ध है
+# AI मॉडल लोड करें (यहां text-generation के लिए)
+model = pipeline("text-generation", model="gpt2")
 
-def generate_speech(text):
-    inputs = processor(text, voice_preset="v2/hi_speaker_1")  # हिंदी के लिए
-    audio_array = model.generate(**inputs)
-    audio_array = audio_array.cpu().numpy().squeeze()
-    sample_rate = model.generation_config.sample_rate
-    scipy.io.wavfile.write("output.wav", rate=sample_rate, data=audio_array)
-    return "output.wav"
+def respond(message, chat_history):
+    # AI मॉडल से रिस्पॉन्स लें
+    response = model(message, max_length=50)[0]["generated_text"]
+    chat_history.append({"role": "user", "content": message})
+    chat_history.append({"role": "assistant", "content": response})
+    return "", chat_history
 
 with gr.Blocks() as demo:
-    gr.Markdown("## Suno Bark Text-to-Speech")
-    text_input = gr.Textbox(label="टेक्स्ट इनपुट करें")
-    audio_output = gr.Audio(label="ऑडियो आउटपुट")
-    generate_button = gr.Button("Generate Speech")
-    generate_button.click(
-        fn=generate_speech,
-        inputs=text_input,
-        outputs=audio_output
-    )
+    chatbot = gr.Chatbot(type="messages")
+    msg = gr.Textbox(label="Type your message")
+    clear = gr.ClearButton([msg, chatbot])
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
 
 demo.launch()
-