Create app.py

app.py

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+import gradio as gr
+from telegram import Bot, Update
+from telegram.ext import CommandHandler, MessageHandler, Filters, Updater, CallbackContext
+
+# Initialize your Telegram bot
+bot = Bot(token="6516533220:AAEoq0ohv4xAraIw7lB7BZVHKyUg85wo3mI")
+
+# Define a Gradio interface for your machine learning model
+def predict_text(text):
+    # Replace this with your model's prediction logic
+    prediction = "Your model's prediction: " + text
+    return prediction
+
+iface = gr.Interface(fn=predict_text, inputs="text", outputs="text")
+
+# Define a command handler for the Telegram bot
+def start(update: Update, context: CallbackContext):
+    update.message.reply_text("Welcome to your bot! Send me text for predictions.")
+
+# Define a message handler for the Telegram bot
+def handle_message(update: Update, context: CallbackContext):
+    user_text = update.message.text
+    prediction = predict_text(user_text)
+    update.message.reply_text(prediction)
+
+# Initialize the Telegram bot updater
+updater = Updater(token="YOUR_TELEGRAM_BOT_TOKEN", use_context=True)
+dispatcher = updater.dispatcher
+
+# Register command and message handlers
+dispatcher.add_handler(CommandHandler("start", start))
+dispatcher.add_handler(MessageHandler(Filters.text & ~Filters.command, handle_message))
+
+# Start both the Gradio interface and the Telegram bot
+iface.launch(share=True)
+updater.start_polling()
+updater.idle()