""" TypeGPT @author: NiansuhAI @email: niansuhtech@gmail.com """ import numpy as np import streamlit as st from openai import OpenAI import os import sys from dotenv import load_dotenv, dotenv_values load_dotenv() # initialize the client client = OpenAI( base_url="https://api-inference.huggingface.co/v1", api_key=os.environ.get('API_KEY') # Replace with your token ) # Create supported models model_links = { "GPT-4o": "mistralai/Mistral-Nemo-Instruct-2407", "GPT-4": "meta-llama/Meta-Llama-3-8B-Instruct", "GPT-3,5": "meta-llama/Meta-Llama-3.1-70B-Instruct", } def reset_conversation(): ''' Resets Conversation ''' st.session_state.conversation = [] st.session_state.messages = [] return None # Define the available models models =[key for key in model_links.keys()] # Create the sidebar with the dropdown for model selection selected_model = st.sidebar.selectbox("Выбрать модель GPT", models) #Add reset button to clear conversation st.sidebar.button('Новый чат', on_click=reset_conversation) #Reset button # Create a temperature slider temp_values = st.sidebar.slider('Температура ChatGPT', 0.0, 1.0, (0.5)) st.sidebar.markdown("Температура в ChatGPT влияет на качество и связность генерируемого текста.") st.sidebar.markdown("**Для оптимального результата рекомендуем выбирать температуру в диапазоне от 0,5 до 0,7**.") # Create model description st.sidebar.markdown("*Созданный контент может быть неточным.*") st.sidebar.markdown("\n Наш сайт: [GPT-ChatBot.ru](https://gpt-chatbot.ru/).") if "prev_option" not in st.session_state: st.session_state.prev_option = selected_model if st.session_state.prev_option != selected_model: st.session_state.messages = [] # st.write(f"Changed to {selected_model}") st.session_state.prev_option = selected_model reset_conversation() #Pull in the model we want to use repo_id = model_links[selected_model] st.subheader(f'[GPT-ChatBot.ru](https://gpt-chatbot.ru/) с моделью {selected_model}') # st.title(f'GPT-ChatBot сейчас использует {selected_model}') # Set a default model if selected_model not in st.session_state: st.session_state[selected_model] = model_links[selected_model] # Initialize chat history if "messages" not in st.session_state: st.session_state.messages = [] # Display chat messages from history on app rerun for message in st.session_state.messages: with st.chat_message(message["role"]): st.markdown(message["content"]) # Accept user input if prompt := st.chat_input(f"Привет. Я {selected_model}. Как я могу вам помочь сегодня?"): # Display user message in chat message container with st.chat_message("user"): st.markdown(prompt) # Add user message to chat history st.session_state.messages.append({"role": "user", "content": prompt}) # Display assistant response in chat message container with st.chat_message("assistant"): try: stream = client.chat.completions.create( model=model_links[selected_model], messages=[ {"role": m["role"], "content": m["content"]} for m in st.session_state.messages ], temperature=temp_values,#0.5, stream=True, max_tokens=3000, ) response = st.write_stream(stream) except Exception as e: # st.empty() response = "Похоже, чат перегружен!\ \n Повторите свой запрос позже:( " st.write(response) st.session_state.messages.append({"role": "assistant", "content": response})