import streamlit as st import openai import os import base64 import glob import json import mistune import pytz from datetime import datetime from openai import ChatCompletion from xml.etree import ElementTree as ET from bs4 import BeautifulSoup openai.api_key = os.getenv('OPENAI_KEY') def chat_with_model(prompts): model = "gpt-3.5-turbo" #model = "gpt-4-32k" # 32k tokens between prompt and inference tokens 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_old(prompt): #safe_date_time = datetime.now().strftime("%m%d_%H%M") safe_date_time = datetime.now().strftime("%m%d_%I_%M_%p") safe_prompt = "".join(x for x in prompt if x.isalnum())[:30] return f"{safe_date_time}_{safe_prompt}.txt" def generate_filename(prompt): central = pytz.timezone('US/Central') safe_date_time = datetime.now(central).strftime("%m%d_%I_%M_%p") 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"

Prompt:

{prompt}

Response:

{response}

") 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'{os.path.basename(file_path)}' 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'{file_name}' 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")[:4000] # hack - top N characters to keep context document under token max def read_file_content(file): 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() #return ET.tostring(root, encoding='unicode') return CompressXML(ET.tostring(root, encoding='unicode')) 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 "" def main(): st.title("Chat with AI") prompts = [''] file_content = "" user_prompt = st.text_area("Your question:", '', height=120) uploaded_file = st.file_uploader("Choose a file", type=["xml", "json", "html", "htm", "md", "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('๐Ÿ’ฌ 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) if len(file_content) > 0: st.markdown(f"**Content Added to Prompt:**\n{file_content}") 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"๐Ÿ—‘Delete {file}"): #if st.sidebar.button("๐Ÿ—‘ Delete"): os.remove(file) st.experimental_rerun() if __name__ == "__main__": main()