Groove-GPT / params.py
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adding stablity patch
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import streamlit as st
def params():
submit_button = st.button("Start Scheming")
# API Key
access_key: str = st.text_input("Enter your gpt key here", type="password")
st.markdown(
"*For more information about how to get an access key, read [this article](https://platform.openai.com/api-keys). Make sure it has money in it ☠️*",
unsafe_allow_html=True,
)
# Chat History
remember_chat_history = st.toggle("Remember This Chat's History")
# Temperature
temperature = st.slider(
label="Creativity of Model", min_value=0.0, max_value=2.0, value=0.8
)
st.markdown("*High creativity will make it go crazy - keep it low*")
# Number of Samples
num_samples = st.slider(
label="Amount of References to Give to Model",
min_value=1,
max_value=20,
value=10,
)
st.markdown(
"*High amount will make it slow and expensive (and may not be relevant) - keep it low*"
)
# GPT Type
gpt_type: str = st.selectbox(
label="Choose GPT Type",
options=[
"gpt-3.5-turbo",
"gpt-3.5-turbo-1106",
"gpt-3.5-turbo-0125",
"gpt-4-32k-0613",
"gpt-4-0125-preview",
"gpt-4-turbo",
],
index=0,
)
st.markdown(
"*For more information about GPT types, read [this article](https://platform.openai.com/docs/models).*",
unsafe_allow_html=True,
)
st.subheader("What is Groovy-GPT?")
st.write(
"Groovy-GPT is a RAG (Retrieval-Augmented Generation) model that uses ChromaDB to retrieve relevant documents and then uses OpenAI's models to generate a response."
)
st.write(
"The model is trained on the MIT Scheme textbook and a handful of Discrete Math and Paradigms related content that Professor Troeger posted"
)
return (
submit_button,
remember_chat_history,
temperature,
num_samples,
access_key,
gpt_type,
)