app. py

import gradio as gr

def greet(name):
    return "Hello " + name + "!!"

demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()
import gradio as gr
from transformers import pipeline

def generate_speech(text, language):
    # Check for empty text
    if not text.strip():
        return None, "Please enter some text"
    
    # Load appropriate model based on language
    if language == "Hindi":
        model_name = "facebook/mms-tts-hin"
    elif language == "Bengali":
        model_name = "facebook/mms-tts-ben"
    
    try:
        # Create text-to-speech pipeline
        synthesizer = pipeline("text-to-speech", model=model_name)
        # Generate speech
        output = synthesizer(text)
        return output["audio"], None
    except Exception as e:
        return None, f"Error: {str(e)}"

# Create Gradio interface
interface = gr.Interface(
    fn=generate_speech,
    inputs=[
        gr.Textbox(label="Enter Text", placeholder="Type your text here..."),
        gr.Dropdown(choices=["Hindi", "Bengali"], label="Select Language")
    ],
    outputs=[
        gr.Audio(label="Generated Speech"),
        gr.Textbox(label="Error Message", visible=False)
    ],
    title="Hindi & Bengali Text-to-Speech",
    description="Convert text to speech for Hindi and Bengali languages using Facebook's MMS-TTS models",
    examples=[
        ["नमस्ते, यह हिंदी में पाठ से वाक् उदाहरण है", "Hindi"],
        ["হ্যালো, এটি বাংলায় একটি টেক্সট-টু-স্পিচ উদাহরণ", "Bengali"]
    ]
)

interface.launch()