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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 | |
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 " | |
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.") | |
max_length = st.sidebar.slider("Max document length", min_value=1000, max_value=32000, value=2000, step=1000) | |
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 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'] | |
#... Rest of your code... | |
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('π¬ 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("π", key=file): | |
os.remove(file) | |
st.experimental_rerun() | |
if __name__ == "__main__": | |
main() | |