test sentiment analysis

.huggingface.yml

@@ -0,0 +1,2 @@
+streamlit:
+  app: main.py

audio_predictions.py

@@ -25,21 +25,21 @@ class AudioTranslation:
         converted_file_path = self.convert_to_mp3(file_path)
         with open(converted_file_path, 'rb') as file:
             files = {'file': (file_path, file, 'audio/mpeg')}
+            print('transcribing audio')
             try:
                 response = requests.post(url, files=files)
                 response.raise_for_status()
                 transcription = response.json()
-
                 # Remove punctuation
                 translator = str.maketrans('', '', string.punctuation)
                 cleaned_text = transcription['text'].translate(translator)
+                print('cleaned text')
                 print(cleaned_text)
                 return cleaned_text
             except requests.exceptions.HTTPError as err:
                 print(f"HTTP error occurred: {err}")
             except Exception as err:
                 print(f"An error occurred: {err}")
-
         return None
 
     def get_translation(self, src, tgt, text):
@@ -72,6 +72,7 @@ class AudioTranslation:
         try:
             response = requests.post(url, headers=headers, data=json.dumps(data))
             response.raise_for_status()
+            print('translation sentence')
             return response.json()
         except requests.exceptions.HTTPError as err:
             print(f"HTTP error occurred: {err}")
@@ -96,10 +97,10 @@ class AudioTranslation:
         return None
 
 # Example usage
-audio_translator = AudioTranslation()
-transcription = audio_translator.transcribe_audio("voice_test_1.mp3")
-translation_result = audio_translator.translate_sentence("rw", "en","MULTI-rw-en","", transcription)
-print(translation_result)
+# audio_translator = AudioTranslation()
+# transcription = audio_translator.transcribe_audio("voice_test_1.mp3")
+# translation_result = audio_translator.translate_sentence("rw", "en","MULTI-rw-en","", transcription)
+# print(translation_result)
 '''
 alternative models:
     https://huggingface.co/facebook/nllb-200-3.3B

evaluation.py

@@ -17,4 +17,4 @@ def evaluate_predictions(filename):
     print("Classification Report:\n", class_report)
 
 # Call the function with the path to your CSV file
-evaluate_predictions('predictions.csv')
+# evaluate_predictions('predictions.csv')

main.py

@@ -37,6 +37,9 @@ def process_audio_files(directories):
         audio_files = list_audio_files(f"{directory}/")
         for file_path in audio_files:
             transc = audio_translator.transcribe_audio(file_path)
+            print(file_path)
+            print('transcription')
+            print(transc)
             translation_result = audio_translator.translate_sentence("rw", "en", "MULTI-rw-en", "", transc)
             translation_text = translation_result #.get('translatedText') if translation_result else "Translation Failed"