import streamlit as st
import openai
import os
import base64
import glob

from datetime import datetime
from openai import ChatCompletion
from xml.etree import ElementTree as ET
from bs4 import BeautifulSoup

import json

# from dotenv import load_dotenv
# load_dotenv()

openai.api_key = os.getenv('OPENAI_KEY')

def chat_with_model(prompts):
    model = "gpt-3.5-turbo"
    #model = "gpt-4-32k"
    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())[:30]
    return f"{safe_date_time}_{safe_prompt}.txt"

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_old(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 get_table_download_link(file_path):
    import os
    import base64
    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

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")
    return ET.tostring(root, encoding='unicode', method="xml")[:16000]


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":
        tree = ET.parse(file)
        root = tree.getroot()
        #return ET.tostring(root, encoding='unicode')
        return CompressXML(ET.tostring(root, encoding='unicode'))
        
    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)
        st.markdown(f"**Content Added to Prompt:**\n{file_content}")
        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("*.txt")
    for file in htm_files:
        st.sidebar.markdown(get_table_download_link(file), unsafe_allow_html=True)
        # if st.sidebar.button(f"Delete {file}"):
        if st.sidebar.button("🗑 Delete"):
            os.remove(file)
            st.experimental_rerun()

if __name__ == "__main__":
    main()