Update app.py

app.py

@@ -395,6 +395,66 @@ def get_zip_download_link(zip_file):
     href = f'<a href="data:application/zip;base64,{b64}" download="{zip_file}">Download All</a>'
     return href
 
+def whisper(filename):
+    with open(filename, "rb") as f:
+        data = f.read
+    #try:
+    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).')
+    return response.json()
+
+def whisper_generate_filename(prompt, file_type):
+    central = pytz.timezone('US/Central')
+    safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
+    replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
+    safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90]
+    return f"{safe_date_time}_{safe_prompt}.{file_type}"
+
+def whisper_save_and_play_audio(audio_recorder):
+    audio_bytes = audio_recorder()
+    if audio_bytes:
+        filename = whisper_generate_filename("Recording", "wav")
+        with open(filename, 'wb') as f:
+            f.write(audio_bytes)
+        st.audio(audio_bytes, format="audio/wav")
+        return filename
+
+def whisper_transcribe_audio(filename):
+    output = whisper(filename)
+    return output
+
+def whisper_save_transcription(transcription):
+    with open(file_path, 'a') as f:
+        f.write(f"{transcription}\n")
+
+def whisper_load_previous_transcriptions():
+    if os.path.exists(file_path):
+        with open(file_path, 'r') as f:
+            return f.read()
+    return ""
+
+def whisper_main():
+    st.title("Speech to Text 🎤📝")
+    st.write("Record your speech and get the text. 🗨️")
+
+    previous_transcriptions = whisper_load_previous_transcriptions()
+    text_area = st.text_area("Transcriptions:", previous_transcriptions, height=400)
+
+    filename = whisper_save_and_play_audio(audio_recorder)
+    if filename is not None:
+        try:
+            transcription = whisper_transcribe_audio(filename)
+        
+            # Update the text area with new transcription
+            updated_transcriptions = f"{previous_transcriptions}\n{transcription}"
+            st.text_area("Transcriptions:", updated_transcriptions, height=400)
+        
+            # Save the new transcription to file
+            whisper_save_transcription(transcription)
+        except:
+            st.write('Whisperer loading..')
+
 def main():
 
     st.title("DromeLlama7B")
@@ -410,7 +470,6 @@ def main():
         except:
             st.write('DromeLlama is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
 
-    
     openai.api_key = os.getenv('OPENAI_KEY')
     menu = ["txt", "htm", "xlsx", "csv", "md", "py"]
     choice = st.sidebar.selectbox("Output File Type:", menu)
@@ -511,7 +570,6 @@ def main():
             create_file(filename, user_prompt, response, should_save)
             st.experimental_rerun()
 
-
     # Feedback
     # Step: Give User a Way to Upvote or Downvote
     feedback = st.radio("Step 8: Give your feedback", ("👍 Upvote", "👎 Downvote"))
@@ -520,89 +578,28 @@ def main():
     else:
         st.write("You downvoted 👎. Thank you for your feedback!")
         
-
-load_dotenv()
-st.write(css, unsafe_allow_html=True)
-st.header("Chat with documents :books:")
-user_question = st.text_input("Ask a question about your documents:")
-if user_question:
-    process_user_input(user_question)
-with st.sidebar:
-    st.subheader("Your documents")
-    docs = st.file_uploader("import documents", accept_multiple_files=True)
-    with st.spinner("Processing"):
-        raw = pdf2txt(docs)
-        if len(raw) > 0:
-            length = str(len(raw))
-            text_chunks = txt2chunks(raw)
-            vectorstore = vector_store(text_chunks)
-            st.session_state.conversation = get_chain(vectorstore)
-            st.markdown('# AI Search Index of Length:' + length + ' Created.')  # add timing
-            filename = generate_filename(raw, 'txt')
-            create_file(filename, raw, '', should_save)
+    load_dotenv()
+    st.write(css, unsafe_allow_html=True)
+    st.header("Chat with documents :books:")
+    user_question = st.text_input("Ask a question about your documents:")
+    if user_question:
+        process_user_input(user_question)
+    with st.sidebar:
+        st.subheader("Your documents")
+        docs = st.file_uploader("import documents", accept_multiple_files=True)
+        with st.spinner("Processing"):
+            raw = pdf2txt(docs)
+            if len(raw) > 0:
+                length = str(len(raw))
+                text_chunks = txt2chunks(raw)
+                vectorstore = vector_store(text_chunks)
+                st.session_state.conversation = get_chain(vectorstore)
+                st.markdown('# AI Search Index of Length:' + length + ' Created.')  # add timing
+                filename = generate_filename(raw, 'txt')
+                create_file(filename, raw, '', should_save)
 
 if __name__ == "__main__":
+    whisper_main()
     main()
 
 
-
-def whisper(filename):
-    with open(filename, "rb") as f:
-        data = f.read
-    #try:
-    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).')
-    return response.json()
-
-def whisper_generate_filename(prompt, file_type):
-    central = pytz.timezone('US/Central')
-    safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
-    replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
-    safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90]
-    return f"{safe_date_time}_{safe_prompt}.{file_type}"
-
-def whisper_save_and_play_audio(audio_recorder):
-    audio_bytes = audio_recorder()
-    if audio_bytes:
-        filename = whisper_generate_filename("Recording", "wav")
-        with open(filename, 'wb') as f:
-            f.write(audio_bytes)
-        st.audio(audio_bytes, format="audio/wav")
-        return filename
-
-def whisper_transcribe_audio(filename):
-    output = whisper(filename)
-    return output
-
-def whisper_save_transcription(transcription):
-    with open(file_path, 'a') as f:
-        f.write(f"{transcription}\n")
-
-def whisper_load_previous_transcriptions():
-    if os.path.exists(file_path):
-        with open(file_path, 'r') as f:
-            return f.read()
-    return ""
-
-def whisper_main():
-    st.title("Speech to Text 🎤📝")
-    st.write("Record your speech and get the text. 🗨️")
-
-    previous_transcriptions = whisper_load_previous_transcriptions()
-    text_area = st.text_area("Transcriptions:", previous_transcriptions, height=400)
-
-    filename = whisper_save_and_play_audio(audio_recorder)
-    if filename is not None:
-        try:
-            transcription = whisper_transcribe_audio(filename)
-        
-            # Update the text area with new transcription
-            updated_transcriptions = f"{previous_transcriptions}\n{transcription}"
-            st.text_area("Transcriptions:", updated_transcriptions, height=400)
-        
-            # Save the new transcription to file
-            whisper_save_transcription(transcription)
-        except:
-            st.write('Whisperer loading..')
-