Update app.py

app.py

@@ -1,5 +1,4 @@
 import os
-import requests
 import speech_recognition as sr
 import difflib
 import gradio as gr
@@ -46,44 +45,15 @@ def transcribe_audio(audio):
     except sr.RequestError as e:
         return f"Error with Google Speech Recognition service: {e}"
 
-
-# Step 2: Create pronunciation audio for incorrect words
-def upfilepath(local_filename):
-    upload_url = "https://mr2along-speech-recognize.hf.space/gradio_api/upload?upload_id=yw08d344te"
-    files = {'files': open(local_filename, 'rb')}
-
+# Step 2: Create pronunciation audio for incorrect words (locally)
+def create_pronunciation_audio(word):
     try:
-        response = requests.post(upload_url, files=files, timeout=30)  # Set timeout (e.g., 30 seconds)
-        
-        if response.status_code == 200:
-            result = response.json()
-            extracted_path = result[0]
-            return extracted_path
-        else:
-            return None
-
-    except requests.exceptions.Timeout:
-        return "Request timed out. Please try again."
+        tts = gTTS(word)
+        audio_file_path = f"audio/{word}.mp3"
+        tts.save(audio_file_path)
+        return audio_file_path  # Return the local path instead of uploading
     except Exception as e:
-        return f"An error occurred: {e}"
-
-        
-def create_pronunciation_audio(word):
-    retries = 3  # Retry up to 3 times
-    for attempt in range(retries):
-        try:
-            tts = gTTS(word)
-            audio_file_path = f"audio/{word}.mp3"
-            tts.save(audio_file_path)
-            word_audio = upfilepath(audio_file_path)
-            if word_audio:
-                return f"https://mr2along-speech-recognize.hf.space/gradio_api/file={word_audio}"
-        except Exception as e:
-            if attempt < retries - 1:
-                time.sleep(2 ** attempt)  # Exponential backoff
-            else:
-                return f"Failed to create pronunciation audio: {e}"
-
+        return f"Failed to create pronunciation audio: {e}"
 
 # Step 3: Compare the transcribed text with the input paragraph
 def compare_texts(reference_text, transcribed_text):
@@ -133,7 +103,7 @@ def compare_texts(reference_text, transcribed_text):
             suggestion = difflib.get_close_matches(word, reference_words, n=1)
             suggestion_text = f" (Did you mean: <em>{suggestion[0]}</em>?)" if suggestion else ""
             html_output += f'{word}: '
-            html_output += f'<audio controls><source src="{audio}" type="audio/wav">Your browser does not support the audio tag.</audio>{suggestion_text}<br>'
+            html_output += f'<audio controls><source src="{audio}" type="audio/mpeg">Your browser does not support the audio tag.</audio>{suggestion_text}<br>'
 
     return [html_output, [audio for _, audio in incorrect_words_audios]]
 
@@ -145,7 +115,7 @@ def text_to_speech(paragraph):
     tts = gTTS(paragraph)
     audio_file_path = "audio/paragraph.mp3"  # Save the audio to a file
     tts.save(audio_file_path)
-    return audio_file_path  # Return the file path instead of None
+    return audio_file_path  # Return the file path
 
 # Gradio Interface Function
 def gradio_function(paragraph, audio):