Update app.py

app.py

@@ -1,3 +1,7 @@
+# Step 1: Install Gradio
+!pip install gradio
+
+# Step 2: Import necessary libraries
 import gradio as gr
 import json
 import torch
@@ -11,7 +15,7 @@ model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
 vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
 
 # Load pronunciation dictionary from JSON file
-with open("pronunciation_dict.json", "r") as f:
+with open("/content/pronunciation_dict.json", "r") as f:
     pronunciation_dict = json.load(f)
 
 # Function to preprocess the input text
@@ -41,12 +45,23 @@ def text_to_speech(input_text):
 
     return output_file
 
-# Step 5: Create Gradio interface
-iface = gr.Interface(fn=text_to_speech,
-                     inputs="text",
-                     outputs="audio",
-                     title="Text-to-Speech (TTS) Application",
-                     description="Enter text with technical jargon for TTS conversion.")
+# Step 5: Create Gradio interface with examples
+examples = [
+    "We are using APIs and OAuth for authentication.",
+    "CUDA and TensorFlow work together for deep learning models.",
+    "The database uses NoSQL and supports JSON for data storage.",
+    "Machine learning and artificial intelligence are advancing fast.",
+    "Natural language processing techniques like GPT are widely adopted."
+]
+
+iface = gr.Interface(
+    fn=text_to_speech,
+    inputs="text",
+    outputs="audio",
+    title="Text-to-Speech (TTS) Application",
+    description="Enter text with technical jargon for TTS conversion.",
+    examples=examples  # Adding preset examples for users
+)
 
 # Step 6: Launch the app
 iface.launch(share=True)