Create app.py

app.py

@@ -0,0 +1,25 @@
+import os
+import gradio as gr
+import zipfile
+
+# Download and extract the models
+os.system('wget -q https://storage.googleapis.com/vakyansh-open-models/tts/marathi/mr-IN/female_voice_0/glow.zip && unzip -q glow.zip -d ttsv/checkpoints/female')
+os.system('wget -q https://storage.googleapis.com/vakyansh-open-models/tts/marathi/mr-IN/female_voice_0/hifi.zip && unzip -q hifi.zip -d ttsv/checkpoints/female')
+os.system('rm glow.zip && rm hifi.zip')
+os.system('wget -q https://storage.googleapis.com/vakyansh-open-models/translit_models.zip -P ttsv/checkpoints/ && unzip -q ttsv/checkpoints/translit_models.zip -d ttsv/checkpoints/')
+
+# Define the TTS function
+def run_tts(text, language):
+    # Your TTS code here
+    
+    # Replace this placeholder implementation with your actual code
+    audio_data = "Base64-encoded-audio-data"
+    return audio_data
+
+# Define the Gradio interface
+def text_to_speech(text):
+    audio_data = run_tts(text, language="mr")
+    return audio_data
+
+iface = gr.Interface(fn=text_to_speech, inputs="text", outputs="audio")
+iface.launch()