Update app.py

app.py

@@ -1,8 +1,43 @@
+import gradio as gr
 from kittentts import KittenTTS
+
+# Initialize the KittenTTS model
+# This model is lightweight and runs on the CPU
 m = KittenTTS("KittenML/kitten-tts-nano-0.1")
 
-audio = m.generate("This high quality TTS model works without a GPU")
+def text_to_speech(text):
+    """
+    Generates audio from the input text using the KittenTTS model.
+
+    Args:
+        text: The text to be converted to speech.
+
+    Returns:
+        A tuple containing the sample rate and the audio data as a NumPy array.
+    """
+    # The KittenTTS model generates audio at a sample rate of 24000 Hz
+    sampling_rate = 24000
+    audio_numpy = m.generate(text)
+    return (sampling_rate, audio_numpy)
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=text_to_speech,
+    inputs=gr.Textbox(
+        lines=3,
+        label="Text to Synthesize",
+        placeholder="Enter your text here..."
+    ),
+    outputs=gr.Audio(label="Synthesized Speech"),
+    title="KittenTTS: Text-to-Speech",
+    description="A simple Gradio app to demonstrate the capabilities of the KittenTTS model. KittenTTS is a lightweight, high-quality text-to-speech model that can run on a CPU. [2]",
+    examples=[
+        ["This high quality TTS model works without a GPU"],
+        ["Gradio is a great tool for creating machine learning demos."],
+        ["The quick brown fox jumps over the lazy dog."]
+    ],
+    allow_flagging="never"
+)
 
-# Save the audio
-import soundfile as sf
-sf.write('output.wav', audio, 24000)
+# Launch the Gradio app
+iface.launch()