Update app.py

app.py

@@ -1,14 +1,31 @@
-import gradio as gr
 import os
-
+os.system("pip install gradio==3.3")
+import gradio as gr
+import numpy as np
 import streamlit as st
 
-demo = gr.Interface.load(
-    "huggingface/facebook/xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022",
-    title="Speech-to-Speech",
-    inputs="mic",
-    description="Let me translate what you're saying!",
-    api_key=st.secrets["api_key"]
-)
+title = "Fairseq S2S"
+
+description = "Gradio Demo for fairseq S2S: speech-to-speech translation models. To use it, simply add your audio, or click one of the examples to load them. Read more at the links below."
+
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.05604' target='_blank'>Direct speech-to-speech translation with discrete units</a> | <a href='https://github.com/facebookresearch/fairseq/tree/main/examples/speech_to_speech' target='_blank'>Github Repo</a></p>"
+
+examples = [
+  ["enhanced_direct_s2st_units_audios_es-en_set2_source_12478_cv.flac","xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022"],
+]
+
+io1 = gr.Interface.load("huggingface/facebook/xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022", api_key=st.secrets["api_key"])
+   
+def inference(text,model):
+   outtext = io1(text)   
+   return outtext 
+
 
-demo.launch()
+gr.Interface(
+    inference, 
+    [gr.inputs.Audio(label="Input",type="filepath"),gr.inputs.Dropdown(choices=["xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022"], type="value", label="model")
+],
+    gr.outputs.Audio(label="Output"),
+    article=article,
+    title=title,
+    description=description).queue().launch()