Update app.py

app.py

@@ -31,14 +31,6 @@ from PyPDF2 import PdfReader
 from templates import bot_template, css, user_template
 from xml.etree import ElementTree as ET
 
-# Whisper Constants
-file_path = 'text_output.txt'
-WHISPER_API_URL = 'https://tonpixzfvq3791u9.us-east-1.aws.endpoints.huggingface.cloud'
-WHISPER_headers = {
-    "Authorization": "Bearer XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
-    "Content-Type": "audio/wav"
-}
-
 # Llama Constants
 API_URL = 'https://qe55p8afio98s0u3.us-east-1.aws.endpoints.huggingface.cloud'  # Dr Llama
 API_KEY = os.getenv('API_KEY')
@@ -403,6 +395,11 @@ def whisper(filename):
     except:
         st.write(f'Could not open or read {filename}')
     #try:
+    WHISPER_API_URL = 'https://tonpixzfvq3791u9.us-east-1.aws.endpoints.huggingface.cloud'
+    WHISPER_headers = {
+    "Authorization": "Bearer XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
+    "Content-Type": "audio/wav"
+    }
     response = requests.post(WHISPER_API_URL, headers=WHISPER_headers, data=data)
     #except:
     #    st.write('Whisper Voice Speech to Text Model is asleep. Starting up now on T4 - please give 3 minutes then retry as KEDA scales up from zero to activate running container(s).')
@@ -429,6 +426,7 @@ def whisper_transcribe_audio(filename):
     return output
 
 def whisper_save_transcription(transcription):
+    file_path = 'text_output.txt'
     with open(file_path, 'a') as f:
         f.write(f"{transcription}\n")