Update app.py

app.py

@@ -20,7 +20,7 @@ def upfilepath(local_filename):
     files = {'files': open(local_filename, 'rb')}
 
     try:
-        response = requests.post(upload_url, files=files, timeout=30)  # Set timeout (e.g., 30 seconds)
+        response = requests.post(upload_url, files=files, timeout=30)
         
         if response.status_code == 200:
             result = response.json()
@@ -41,7 +41,6 @@ def transcribe_audio(audio):
     
     recognizer = sr.Recognizer()
 
-    # Check if the file exists
     if not os.path.isfile(audio):
         return "Audio file not found."
 
@@ -91,6 +90,7 @@ def compare_texts(reference_text, transcribed_text):
     reference_words = reference_text.split()
     transcribed_words = transcribed_text.split()
     incorrect_words_audios = []  # Store audio paths for incorrect words
+    word_score_list = []  # To store each word's score
 
     sm = difflib.SequenceMatcher(None, reference_text, transcribed_text)
     similarity_score = round(sm.ratio() * 100, 2)
@@ -108,24 +108,27 @@ def compare_texts(reference_text, transcribed_text):
 
     html_output += f"<strong>Quality Score:</strong> {similarity_score}%<br>"
     html_output += f"<strong>Transcribed Text:</strong> {transcribed_text}<br>"
-    html_output += f"<strong>IPA Transcription:</strong> {ipa_transcription(reference_text)}<br>"  # Display IPA transcription
+    html_output += f"<strong>IPA Transcription:</strong> {ipa_transcription(reference_text)}<br>"
     html_output += "<strong>Word Score List:</strong><br>"
 
     # Generate colored word score list
     for i, word in enumerate(reference_words):
         try:
             if word.lower() == transcribed_words[i].lower():
+                word_score_list.append({"quality_score": 100, "word": word})
                 html_output += f'<span style="color: green;">{word}</span> '  # Correct words in green
             elif difflib.get_close_matches(word, [transcribed_words[i]]):
+                word_score_list.append({"quality_score": 80, "word": word})  # Close matches
                 html_output += f'<span style="color: yellow;">{word}</span> '  # Close matches in yellow
             else:
-                # Incorrect words in red
-                html_output += f'<span style="color: red;">{word}</span> '
+                word_score_list.append({"quality_score": 0, "word": word})
+                html_output += f'<span style="color: red;">{word}</span> '  # Incorrect words in red
                 # Create pronunciation audio for the incorrect word
                 audio_file_path = create_pronunciation_audio(word)
                 incorrect_words_audios.append((word, audio_file_path))
         except IndexError:
             # Word in reference that was not transcribed
+            word_score_list.append({"quality_score": 0, "word": word})
             html_output += f'<span style="color: red;">{word}</span> '
 
     # Provide audio for incorrect words
@@ -139,7 +142,8 @@ def compare_texts(reference_text, transcribed_text):
             html_output += f'{word}: '
             html_output += f'<audio controls><source src="{audio_src}" type="audio/mpeg">Your browser does not support the audio tag.</audio>{suggestion_text}<br>'
 
-    return [html_output]
+    # Return structured data
+    return [html_output, word_score_list]
 
 # Step 4: Text-to-Speech Function
 def text_to_speech(paragraph):