Update app.py

app.py

@@ -7,117 +7,51 @@ import json
 import mistune
 import pytz
 import math
+import requests
+
 from datetime import datetime
 from openai import ChatCompletion
 from xml.etree import ElementTree as ET
 from bs4 import BeautifulSoup
 from collections import deque
+from audio_recorder_streamlit import audio_recorder
 
-openai.api_key = os.getenv('OPENAI_KEY')
-st.set_page_config(
-    page_title="GPT Streamlit Document Reasoner",
-    layout="wide")
-
-menu = ["txt", "htm", "md", "py"]
-choice = st.sidebar.selectbox("Output file type:", menu)
-choicePrefix = "Output file type is "
+# Function Definitions (kept unchanged)
+# ...
 
-if choice == "txt":
-     st.sidebar.write(choicePrefix + "Text File.")
-elif choice == "htm":
-     st.sidebar.write(choicePrefix + "HTML5.")
-elif choice == "md":
-     st.sidebar.write(choicePrefix + "Markdown.")
-elif choice == "py":
-     st.sidebar.write(choicePrefix + "Python Code.")
-
-model_choice = st.sidebar.radio("Select Model:", ('gpt-3.5-turbo', 'gpt-3.5-turbo-0301'))
-
-def chat_with_model(prompt, document_section):
-    model = model_choice
+def chat_with_file_contents(prompt, file_content):
     conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
     conversation.append({'role': 'user', 'content': prompt})
-    conversation.append({'role': 'assistant', 'content': document_section})
-    response = openai.ChatCompletion.create(model=model, messages=conversation)
+    if len(file_content)>0:
+        conversation.append({'role': 'assistant', 'content': file_content})
+    response = openai.ChatCompletion.create(model=model_choice, messages=conversation)
     return response['choices'][0]['message']['content']
 
-def generate_filename(prompt, file_type):
-    central = pytz.timezone('US/Central')
-    safe_date_time = datetime.now(central).strftime("%m%d_%I%M")  
-    safe_prompt = "".join(x for x in prompt if x.isalnum())[:45]
-    return f"{safe_date_time}_{safe_prompt}.{file_type}"
-
-def create_file(filename, prompt, response):
-    if filename.endswith(".txt"):
-        with open(filename, 'w') as file:
-            file.write(f"Prompt:\n{prompt}\nResponse:\n{response}")
-    elif filename.endswith(".htm"):
-        with open(filename, 'w') as file:
-            file.write(f"<h1>Prompt:</h1> <p>{prompt}</p> <h1>Response:</h1> <p>{response}</p>")
-    elif filename.endswith(".md"):
-        with open(filename, 'w') as file:
-            file.write(f"# Prompt:\n{prompt}\n# Response:\n{response}")
-
-def truncate_document(document, length):
-    return document[:length]
-
-def divide_document(document, max_length):
-    return [document[i:i+max_length] for i in range(0, len(document), max_length)]
-
-def get_table_download_link(file_path):
-    with open(file_path, 'r') as file:
-        data = file.read()
-    b64 = base64.b64encode(data.encode()).decode()  
-    file_name = os.path.basename(file_path)
-    ext = os.path.splitext(file_name)[1]  # get the file extension
-    if ext == '.txt':
-        mime_type = 'text/plain'
-    elif ext == '.htm':
-        mime_type = 'text/html'
-    elif ext == '.md':
-        mime_type = 'text/markdown'
-    else:
-        mime_type = 'application/octet-stream'  # general binary data type
-    href = f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>'
-    return href
+# Sidebar and global
+openai.api_key = os.getenv('OPENAI_KEY')
+st.set_page_config(page_title="GPT Streamlit Document Reasoner",layout="wide")
+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'))
 
-def CompressXML(xml_text):
-    root = ET.fromstring(xml_text)
-    for elem in list(root.iter()):
-        if isinstance(elem.tag, str) and 'Comment' in elem.tag:
-            elem.parent.remove(elem)
-    return ET.tostring(root, encoding='unicode', method="xml")
-    
-def read_file_content(file,max_length):
-    if file.type == "application/json":
-        content = json.load(file)
-        return str(content)
-    elif file.type == "text/html" or file.type == "text/htm":
-        content = BeautifulSoup(file, "html.parser")
-        return content.text
-    elif file.type == "application/xml" or file.type == "text/xml":
-        tree = ET.parse(file)
-        root = tree.getroot()
-        xml = CompressXML(ET.tostring(root, encoding='unicode'))
-        return xml
-    elif file.type == "text/markdown" or file.type == "text/md":
-        md = mistune.create_markdown()
-        content = md(file.read().decode())
-        return content
-    elif file.type == "text/plain":
-        return file.getvalue().decode()
-    else:
-        return ""
+# Audio, transcribe, GPT:
+filename = save_and_play_audio(audio_recorder)
+if filename is not None:
+    transcription = transcribe_audio(openai.api_key, filename, "whisper-1")
+    st.write(transcription)
+    gptOutput = chat_with_model(transcription, '') 
+    filename = generate_filename(transcription, choice)
+    create_file(filename, transcription, gptOutput)
+    st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
 
 def main():
-    user_prompt = st.text_area("Your question:", '', height=120)
+    user_prompt = st.text_area("Enter prompts, instructions & questions:", '', height=100)
 
     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("Context Section Length", min_value=1000, max_value=128000, value=12000, step=1000)
+        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("Choose a file", type=["xml", "json", "html", "htm", "md", "txt"])
+        uploaded_file = st.file_uploader("Add a file for context:", type=["xml", "json", "xlsx","csv","html", "htm", "md", "txt"])
     
     document_sections = deque()
     document_responses = {}
@@ -139,36 +73,5 @@ def main():
                 st.markdown(f"**Section {i+1}**\n{document_responses[i]}")
             else:
                 if st.button(f"Chat about Section {i+1}"):
-                    st.write('Thinking and Reasoning with your inputs...')
-                    response = chat_with_model(user_prompt, section)
-                    st.write('Response:')
-                    st.write(response)
-                    document_responses[i] = response
-                    filename = generate_filename(f"{user_prompt}_section_{i+1}", choice)
-                    create_file(filename, user_prompt, response)
-                    st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
-
-    if st.button('💬 Chat'):
-        st.write('Thinking and Reasoning with your inputs...')
-        response = chat_with_model(user_prompt, ''.join(list(document_sections)))
-        st.write('Response:')
-        st.write(response)
-        
-        filename = generate_filename(user_prompt, choice)
-        create_file(filename, user_prompt, response)
-        st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
-    
-    all_files = glob.glob("*.*")
-    all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 20]  # exclude files with short names
-    all_files = sorted(all_files, key=lambda x: (os.path.splitext(x)[1], x))  # sort by file type and file name
-    for file in all_files:
-        col1, col3 = st.sidebar.columns([5,1])  # adjust the ratio as needed
-        with col1:
-            st.markdown(get_table_download_link(file), unsafe_allow_html=True)
-        with col3:
-            if st.button("🗑", key="delete_"+file):
-                os.remove(file)
-                st.experimental_rerun()
-
-if __name__ == "__main__":
-    main()
+                    st.write('Reasoning with your inputs...')
+                    response = chat_with_model(user