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""" HAH 2024 v0.1 Chatbot
@author: Dr M As'ad
@email: [email protected]
"""
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('HUGGINGFACEHUB_API_TOKEN')
)
#Create supported models
model_links ={
"HAH-2024-v0.1":"drmasad/HAH-2024-v0.11",
"Mistral":"mistralai/Mistral-7B-Instruct-v0.2",
}
model_info ={
"HAH-2024-v0.1":
{'description':"""The HAH-2024-v0.1 model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
\nIt was created by fine tuning Mistra 7b instruct usin 3000 review articles on diabetes** \n""",
'logo':'https://www.hmgaihub.com/untitled.png'},
"Mistral":
{'description':
"""The Mistral model is a **Large Language Model (LLM)** that's able to have question and answer interactions...""",
'logo':
'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'},
}
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("Select Model", models)
#Create a temperature slider
temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
#Add reset button to clear conversation
st.sidebar.button('Reset Chat', on_click=reset_conversation) #Reset button
# Create model description
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.markdown(model_info[selected_model]['description'])
st.sidebar.image(model_info[selected_model]['logo'])
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
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'AI - {selected_model}')
# st.title(f'ChatBot 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}, ask me a question"):
# 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"):
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)
st.session_state.messages.append({"role": "assistant", "content": response}) |