Update app.py

app.py

@@ -229,6 +229,8 @@ def main():
     # Sidebar and global
     openai.api_key = os.getenv('OPENAI_API_KEY')
     st.set_page_config(page_title="GPT Streamlit Document Reasoner",layout="wide")
+
+    # File type for output, model choice
     menu = ["htm", "txt", "xlsx", "csv", "md", "py"]  #619
     choice = st.sidebar.selectbox("Output File Type:", menu)
     model_choice = st.sidebar.radio("Select Model:", ('gpt-3.5-turbo', 'gpt-3.5-turbo-0301'))
@@ -237,35 +239,29 @@ def main():
     filename = save_and_play_audio(audio_recorder)
     if filename is not None:
         transcription = transcribe_audio(openai.api_key, filename, "whisper-1")
-        #gptOutput = chat_with_model(transcription, '', model_choice) # *************************************
-        #filename = generate_filename(transcription, choice)
-        #create_file(filename, transcription, gptOutput)
         st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
 
-
+    # prompt interfaces
     user_prompt = st.text_area("Enter prompts, instructions & questions:", '', height=100)
 
+    # file section interface for prompts against large documents as context
     collength, colupload = st.columns([2,3])  # adjust the ratio as needed
     with collength:
-        #max_length = 12000 - optimal for gpt35 turbo. 2x=24000 for gpt4.  8x=96000 for gpt4-32k.
         max_length = st.slider("File section length for large files", min_value=1000, max_value=128000, value=12000, step=1000)
     with colupload:
         uploaded_file = st.file_uploader("Add a file for context:", type=["xml", "json", "xlsx","csv","html", "htm", "md", "txt"])
-    
+
+    # Document section chat
     document_sections = deque()
     document_responses = {}
-
     if uploaded_file is not None:
         file_content = read_file_content(uploaded_file, max_length)
         document_sections.extend(divide_document(file_content, max_length))
-
     if len(document_sections) > 0:
-        
         if st.button("👁️ View Upload"):
             st.markdown("**Sections of the uploaded file:**")
             for i, section in enumerate(list(document_sections)):
                 st.markdown(f"**Section {i+1}**\n{section}")
-        
         st.markdown("**Chat with the model:**")
         for i, section in enumerate(list(document_sections)):
             if i in document_responses:
@@ -330,13 +326,9 @@ def main():
         if next_action=='search':
             file_content_area = st.text_area("File Contents:", file_contents, height=500)
             st.write('Reasoning with your inputs...')
-            #response = chat_with_file_contents(user_prompt, file_contents)
             response = chat_with_model(user_prompt, file_contents, model_choice)
-            #st.write('Response:')
-            #st.write(response)
-            
-            filename = generate_filename(file_content_area, choice)
-            create_file(filename, file_content_area, response)
+            filename = generate_filename(file_contents, choice)
+            create_file(filename, file_contents, response)
             st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
                 
 if __name__ == "__main__":