import numpy as np
import streamlit as st
from transformers import Autookenizer, AutoModelorCausalLM
import os
import sys
from dotenv import loaddotenv, dotenvvalues
loaddotenv()

# initialize the client
# client = OpenAI(
#   baseurl="https://api-inference.huggingface.co/v1",
#   apikey=os.environ.get('APIY')  # Replace with your token
# )

# Create supported models
modellinks = {
    "Meta-Llama-3-8B-Instruct": "meta-llama/Meta-Llama-3-8B-Instruct"
}

#andom dog images for error message
randomdog = ["0f476473-2d8b-415e-b944-483768418a95.jpg",
              "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg",
              "526590d2-8817-4ff0-8c62-fdcba5306d02.jpg",
              "1326984c-39b0-492c-a773-f120d747a7e2.jpg",
              "42a98d03-5ed7-4b3b-af89-7c4876cb14c3.jpg",
              "8b3317ed-2083-42ac-a575-7ae45f9fdc0d.jpg",
              "ee17f54a-83ac-44a3-8a35-e89ff7153fb4.jpg",
              "027eef85-ccc1-4a66-8967-5d74f34c8bb4.jpg",
              "08f5398d-7f89-47da-a5cd-1ed74967dc1f.jpg",
              "0fd781ff-ec46-4bdc-a4e8-24f18bf07def.jpg",
              "0fb4aeee-f949-4c7b-a6d8-05bf0736bdd1.jpg",
              "6edac66e-c0de-4e69-a9d6-b2e6f6f9001b.jpg",
              "bfb9e165-c643-4993-9b3a-7e73571672a6.jpg"]



def resetconversation():
    '''
    Resets Conversation
    '''
    st.sessionstate.conversation = []
    st.sessionstate.messages = []
    return None
    



# Define the available models
models =[key for key in modellinks.keys()]

# Create the sidebar with the dropdown for model selection
selectedmodel = st.sidebar.selectbox("Select Model", models)

# Create a temperature slider
tempvalues = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))


#Add reset button to clear conversation
st.sidebar.button('eset Chat', onclick=resetconversation) #eset button


# Create model description
st.sidebar.write(f"You're now chatting with **{selectedmodel}**")
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
st.sidebar.markdown("\n[ypeGP](https://typegpt.net).")


if "prevoption" not in st.sessionstate:
    st.sessionstate.prevoption = selectedmodel

if st.sessionstate.prevoption != selectedmodel:
    st.sessionstate.messages = []
    # st.write(f"Changed to {selectedmodel}")
    st.sessionstate.prevoption = selectedmodel
    resetconversation()



#Pull in the model we want to use
repoid = modellinks[selectedmodel]


st.subheader(f'ypeGP.net - {selectedmodel}')
# st.title(f'ChatBot Using {selectedmodel}')

# Set a default model
if selectedmodel not in st.sessionstate:
    st.sessionstate[selectedmodel] = modellinks[selectedmodel] 

# Initialize chat history
if "messages" not in st.sessionstate:
    st.sessionstate.messages = []


# Display chat messages from history on app rerun
for message in st.sessionstate.messages:
    with st.chatmessage(message["role"]):
        st.markdown(message["content"])




if prompt := st.chatinput(f"Hi I'm {selectedmodel}, ask me a question"):
    # Display user message in chat message container
    with st.chatmessage("user"):
        st.markdown(prompt)
    # Add user message to chat history
    st.sessionstate.messages.append({"role": "user", "content": prompt})
    

    # Display assistant response in chat message container
    with st.chatmessage("assistant"):
        try:
            # stream = client.chat.completions.create(
            #     model=modellinks[selectedmodel],
            #     messages=[
            #         {"role": m["role"], "content": m["content"]}
            #         for m in st.sessionstate.messages
            #     ],
            #     temperature=tempvalues,#0.5,
            #     stream=rue,
            #     maxtokens=3000,
            # )

            # 수정 전 코드 (penAI)
            # response = st.writestream(stream)

            # 수정 후 코드 (Hugging Face)
            tokenizer = Autookenizer.frompretrained(repoid)
            model = AutoModelorCausalLM.frompretrained(repoid)

            inputids = tokenizer(prompt, returntensors="pt").inputids
            output = model.generate(inputids, maxlength=1000, temperature=tempvalues)
            response = tokenizer.decode(output[0], skipspecialtokens=rue)

        except Exception as e:
            # st.empty()
            response = "😵‍💫 Looks like someone unplugged something!\
                    \n Either the model space is being updated or something is down.\
                    \n\
                    \n Try again later. \
                    \n\
                    \n Here's a random pic of a 🐶:"
            st.write(response)
            randomdogpick = 'https://random.dog/'+ randomdog[np.random.randint(len(randomdog))]
            st.image(randomdogpick)
            st.write("his was the error message:")
            st.write(e)





    st.sessionstate.messages.append({"role": "assistant", "content": response})