Upload 18 files

app.py

@@ -1,12 +1,14 @@
 import gradio as gr
+import os
 from cs_ai_kt_transcribe_share.kt_transcript import KnowledgeTranscriber
 
 def process_inputs(api_key, drive_folder_link):
+    os.environ['OPENAI_API_KEY'] = api_key  # Set the API_KEY environment variable
     try:
         # Assuming drive_link is the folder_path and transcribe_flag is derived or fixed
         folder_path = drive_folder_link  # Example adjustment, actual implementation may vary
         transcribe_flag = True  # Example, adjust based on actual use case
-        kt = KnowledgeTranscriber(api_key)  # Create an instance of KnowledgeTranscriber
+        kt = KnowledgeTranscriber(os.environ['OPENAI_API_KEY'])  # Create an instance of KnowledgeTranscriber
         kt.process_folder('scripts/ktTranscript/cs_ai_kt_transcribe_share/Input-Folder', True, drive_folder_link)  # Call the method
         return "Success"
     except ValueError as e:

cs_ai_kt_transcribe_share/kt_transcript.py

@@ -759,6 +759,10 @@ class KnowledgeTranscriber(object):
         try:
             # Ensure the directory where the file will be saved exists
             os.makedirs(os.path.dirname(file_path), exist_ok=True)
+            # Check if the file is an mp4 file before downloading
+            if not file_path.endswith('.mp4'):
+                logging.info(f"Skipping non-mp4 file: {file_path}")
+                return
 
             request = service.files().get_media(fileId=file_id)
             with open(file_path, 'wb') as fh: