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| import streamlit as st | |
| import openai | |
| import os | |
| import base64 | |
| import glob | |
| import json | |
| import mistune | |
| import pytz | |
| import math | |
| from datetime import datetime | |
| from openai import ChatCompletion | |
| from xml.etree import ElementTree as ET | |
| from bs4 import BeautifulSoup | |
| from collections import deque | |
| # Rest of your code goes here... | |
| openai.api_key = os.getenv('OPENAI_KEY') | |
| st.set_page_config( | |
| page_title="GPT Streamlit Document Reasoner", | |
| layout="wide") | |
| # Rest of your code goes here... | |
| def divide_document(document, max_length): | |
| # Split document into sections, each of about 2000 words or 4000 characters | |
| return [document[i:i+max_length] for i in range(0, len(document), max_length)] | |
| def chat_with_model(prompt, document_section): | |
| model = "gpt-3.5-turbo" | |
| 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) | |
| return response['choices'][0]['message']['content'] | |
| def main(): | |
| user_prompt = st.text_area("Your question:", '', height=120) | |
| uploaded_file = st.file_uploader("Choose a file", type=["xml", "json", "html", "htm", "md", "txt"]) | |
| max_length = 4000 | |
| 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: | |
| 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: | |
| 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 | |
| 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("*.txt") + glob.glob("*.htm") + glob.glob("*.md") | |
| for file in all_files: | |
| col1, col2 = st.sidebar.columns([4,1]) # adjust the ratio as needed | |
| with col1: | |
| st.markdown(get_table_download_link(file), unsafe_allow_html=True) | |
| with col2: | |
| if st.button("🗑", key=file): | |
| os.remove(file) | |
| st.experimental_rerun() | |
| if __name__ == "__main__": | |
| main() | |