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""" TypeGPT
@author: NiansuhAI
@email: [email protected]
"""
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": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8",
"GPT-4": "meta-llama/Meta-Llama-3.1-405B-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('New Chat', on_click=reset_conversation) #Reset button
# Create a temperature slider
temp_values = st.sidebar.slider('ChatGPT Temperature', 0.0, 1.0, (0.5))
st.sidebar.markdown("Temperature in ChatGPT affects the quality and coherence of the generated text.")
st.sidebar.markdown("**For optimum results, we recommend selecting a temperature between 0.5 and 0.7**")
# Create model description
st.sidebar.markdown("*The content created may not be accurate.*")
st.sidebar.markdown("\n Our website: [Chat-GPT-Free.com](https://chat-gpt-free.com/).")
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'[Chat-GPT-Free.com](https://chat-gpt-free.com/) with AI model {selected_model}')
# st.title(f'Chat-GPT-Free is now using {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"Hi. I'm {selected_model}. How can I help you today?"):
# 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 = "The GPT is overloaded!\
\n Repeat your request later :( "
st.write(response)
st.session_state.messages.append({"role": "assistant", "content": response})
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