Update app.py

app.py

@@ -88,116 +88,11 @@ def main():
 
         st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
 
-    htm_files = glob.glob("*.htm")
-    for file in htm_files:
-        st.sidebar.mark
-
-
-
-
-User
-show full code listing
-ChatGPT
-Here is the full Python script:
-
-python
-Copy code
-import streamlit as st
-import openai
-import os
-import base64
-import glob
-import json
-from xml.etree import ElementTree as ET
-from datetime import datetime
-from dotenv import load_dotenv
-from openai import ChatCompletion
-
-load_dotenv()
-
-openai.api_key = os.getenv('OPENAI_KEY')
-
-def chat_with_model(prompts):
-    model = "gpt-3.5-turbo"
-
-    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
-    conversation.extend([{'role': 'user', 'content': prompt} for prompt in prompts])
-
-    response = openai.ChatCompletion.create(model=model, messages=conversation)
-    return response['choices'][0]['message']['content']
-
-def generate_filename(prompt):
-    safe_date_time = datetime.now().strftime("%m_%d_%H_%M")
-    safe_prompt = "".join(x for x in prompt if x.isalnum())[:50]
-    return f"{safe_date_time}_{safe_prompt}.htm"
-
-def create_file(filename, prompt, response):
-    with open(filename, 'w') as file:
-        file.write(f"<h1>Prompt:</h1> <p>{prompt}</p> <h1>Response:</h1> <p>{response}</p>")
-
-def get_table_download_link(file_path):
-    with open(file_path, 'r') as file:
-        data = file.read()
-    b64 = base64.b64encode(data.encode()).decode()
-    href = f'<a href="data:file/htm;base64,{b64}" target="_blank" download="{os.path.basename(file_path)}">{os.path.basename(file_path)}</a>'
-    return href
-
-def CompressXML(xml_text):
-    tree = ET.ElementTree(ET.fromstring(xml_text))
-    for elem in tree.iter():
-        if isinstance(elem.tag, ET.Comment):
-            elem.getparent().remove(elem)
-    return ET.tostring(tree.getroot(), encoding='unicode')
-
-def read_file_content(file):
-    if file.type == "application/json":
-        content = json.load(file)
-        return str(content)
-    elif file.type == "text/html":
-        content = BeautifulSoup(file, "html.parser")
-        return content.text
-    elif file.type == "application/xml" or file.type == "text/xml":
-        xml_text = file.getvalue().decode()
-        compressed_text = CompressXML(xml_text)
-        return compressed_text
-    elif file.type == "text/plain":
-        return file.getvalue().decode()
-    else:
-        return ""
-
-
-def main():
-    st.title("Chat with AI")
-
-    prompts = ['']
-
-    user_prompt = st.text_area("Your question:", '', height=120)
-    uploaded_file = st.file_uploader("Choose a file", type=["xml", "json", "htm", "txt"])
-
-    if user_prompt:
-        prompts.append(user_prompt)
-
-    if uploaded_file is not None:
-        file_content = read_file_content(uploaded_file)
-        prompts.append(file_content)
-
-    if st.button('Chat'):
-        st.write('Chatting with GPT-3...')
-        response = chat_with_model(prompts)
-        st.write('Response:')
-        st.write(response)
-
-        filename = generate_filename(user_prompt)
-        create_file(filename, user_prompt, response)
-
-        st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
-
     htm_files = glob.glob("*.htm")
     for file in htm_files:
         st.sidebar.markdown(get_table_download_link(file), unsafe_allow_html=True)
         if st.sidebar.button(f"Delete {file}"):
             os.remove(file)
-            st.experimental_rerun()
 
 if __name__ == "__main__":
     main()