edited seamless_client name

app.py

@@ -13,7 +13,7 @@ import PIL
 from openai import OpenAI
 dotenv.load_dotenv()
 
-client = Client("facebook/seamless_m4t")
+seamless_client = Client("facebook/seamless_m4t")
 
 
 
@@ -27,7 +27,7 @@ def process_speech(audio):
     sr, data = audio
     write(audio_name, sr, data.astype(np.int16))
 
-    out = client.predict(
+    out = seamless_client.predict(
         "S2TT",
         "file",
         None,

test.py

@@ -1,36 +1,7 @@
-import dotenv
-import base64
-import os
-import requests
 import gradio as gr
-import PIL
-import numpy as np
-from scipy.io.wavfile import write
-import gradio_client as grc
-dotenv.load_dotenv()
 
-client = grc.Client("facebook/seamless_m4t")
 def process_image(audio):  
-    # audio_name = f"{np.random.randint(0, 100)}.jpg"
-    audio_name = f"{1}.wav"
-    sr, data = audio
-    write(audio_name, sr, data.astype(np.int16))
+    return str(len(audio))
 
-    out = client.predict(
-        "S2TT",
-        "file",
-        None,
-        audio_name,
-        "",
-        "French",# source language
-        "English",# target language
-        api_name="/run",
-    )
-    out = out[1] # get the text
-    try :
-        return f"{out}"
-    except Exception as e :
-        return f"{e}"
-
-iface = gr.Interface(fn=process_image, inputs="audio", outputs="text")
+iface = gr.Interface(fn=process_image, inputs=["textbox","audio"], outputs="text")
 iface.launch()