Update app.py

app.py

@@ -1,12 +1,41 @@
-import gradio as gr
+import gradio as gr 
+import numpy as np 
+from elevenlabs import voices, generate, set_api_key, UnauthenticatedRateLimitError
+
+def pad_buffer(audio):
+    buffer_size = len(audio)
+    element_size = np.dtype(np.int16).itemsize
+    if buffer_size % element_size != 0:
+        audio = audio + b'\0' * (element_size - (buffer_size % element_size))
+    return audio 
+
+def generate_voice(text, voice_name):
+    model_name = "eleven_multilingual_v1"
+    try:
+        audio = generate(
+            text[:250],
+            voice=voice_name, 
+            model=model_name
+        )
+        return (44100, np.frombuffer(pad_buffer(audio), dtype=np.int16))
+    except UnauthenticatedRateLimitError as e:
+        raise gr.Error("Thanks for trying out ElevenLabs TTS! You've reached the free tier limit. Please provide an API key to continue.") 
+    except Exception as e:
+        raise gr.Error(str(e))
+
+all_voices = voices()
+desired_voices = ["Antonio"]
+filtered_voices = [voice.name for voice in all_voices if voice.name in desired_voices]
+
+input_text = gr.Textbox(label="Input Text", lines=2)
+input_voice = gr.Dropdown(choices=filtered_voices, default="Antonio", label="Voice")
+out_audio = gr.Audio(label="Generated Voice", type="numpy")
 
 iface = gr.Interface(
-    title="Image recognition",
-    description="Upload an image you want to categorize.",
-    theme="Monochrome",
-    live=True,
-    capture_session=True,
+    fn=generate_voice,
+    inputs=[input_text, input_voice],
+    outputs=out_audio,
+    live=True
 )
-gr.load("models/google/vit-base-patch16-224").launch()
 
 iface.launch()