Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 import requests
-import whisper  # Now using openai-whisper
+import whisper  # Using openai-whisper
 from gtts import gTTS
 from fastapi import FastAPI
 from fastapi.responses import FileResponse
@@ -8,15 +8,15 @@ import os
 
 app = FastAPI()
 
-# Load Whisper model correctly
-model = whisper.load_model("small")  # "small" model is lighter and faster for Hugging Face
+# Load Whisper model
+model = whisper.load_model("small")
 
 # LibreTranslate API (Open Source)
 TRANSLATE_API_URL = "https://libretranslate.com/translate"
 
 OUTPUT_AUDIO = "translated_audio.mp3"
 
-# Transcribe speech using Whisper
+# Function to transcribe speech
 def transcribe_audio(audio):
     audio_file = "input_audio.wav"
     with open(audio_file, "wb") as f:
@@ -25,12 +25,12 @@ def transcribe_audio(audio):
     result = model.transcribe(audio_file)
     return result["text"]
 
-# Translate text
+# Function to translate text
 def translate_text(text, source_lang, target_lang):
     response = requests.post(TRANSLATE_API_URL, data={"q": text, "source": source_lang, "target": target_lang})
     return response.json().get("translatedText", "Translation Error")
 
-# Convert text to speech
+# Function to convert text to speech
 def text_to_speech(text, lang):
     tts = gTTS(text=text, lang=lang)
     tts.save(OUTPUT_AUDIO)
@@ -53,7 +53,7 @@ def process_audio(audio):
 
 with gr.Blocks() as demo:
     gr.Markdown("### 🎙️ Urdu ↔ Pashto Voice Translator")
-    audio_input = gr.Audio(source="microphone", type="file", label="🎤 Record Your Voice")
+    audio_input = gr.Audio(type="file", label="🎤 Record Your Voice")  # 🔹 FIX: Removed `source="microphone"`
     transcribed_text = gr.Textbox(label="Transcribed Text")
     translated_text = gr.Textbox(label="Translated Text")
     audio_output = gr.Audio(label="Translated Audio")