Update app.py

app.py

@@ -1,31 +1,14 @@
-import os
-os.system("pip install gradio==3.3")
 import gradio as gr
-import numpy as np
-import streamlit as st
-
-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"],
-]
+import os
 
-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 
+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"]
+)
 
-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()
+demo.launch()