"""
Diabetes Version
@aim: Demo for testing purposes only
@inquiries: Dr M As'ad 
@email: drmohasad@gmail.com
"""

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://p7fw46eiw6xfkxvj.us-east-1.aws.endpoints.huggingface.cloud/v1/",
    # "hf_xxx" # Replace with your token
    api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')
)

# Create supported models
model_links = {
    "HAH v0.1": "drmasad/HAH-2024-v0.11",
    "Mistral": "mistralai/Mistral-7B-Instruct-v0.2",
}

# Pull info about the model to display
model_info = {
    "HAH v0.1":
        {'description': """HAH 0.1 is a fine tuned model based on Mistral 7b instruct.\n \
            \nIt was created by Dr M. As'ad using 250k dB rows sourced from open source 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.\n \
            \nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-7b/) team as has over  **7 billion parameters.** \n""",
         '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))


# Create model description
st.sidebar.button("Reset Chat", on_click=reset_conversation)
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.image("https://www.hmgaihub.com/untitled.png")
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
st.sidebar.markdown("*This is an under development project.*")
st.sidebar.markdown("*Not a replacement for medical advice from a doctor.*")


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})