import numpy as np
import streamlit as st
from openai import OpenAI
import os
import json
from dotenv import load_dotenv

load_dotenv()

# Initialize the client
client = OpenAI(
    base_url=os.environ.get('BASE_URL'),  # Fetch base_url from environment variables
    api_key=os.environ.get('API_KEY')      # Fetch API key from environment variables
)

# Create supported models
model_links = {
    "Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
}

# Random dog images for error message
random_dog = [
    "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"
]

history_file = 'chat_histories.json'

def load_history():
    if os.path.exists(history_file):
        with open(history_file, 'r') as f:
            return json.load(f)
    return {}

def save_history(histories):
    with open(history_file, 'w') as f:
        json.dump(histories, f)

def reset_conversation():
    '''
    Resets Conversation
    '''
    st.session_state.messages = []
    st.session_state.current_chat_name = None
    return None

# Set up the Streamlit page configuration
st.set_page_config(page_icon="📃", layout="wide", page_title="GPT-CHATBOT.ru")

# Display the header
st.title("GPT-CHATBOT.ru")

# Initialize session state attributes
if "messages" not in st.session_state:
    st.session_state.messages = []

if "chat_histories" not in st.session_state:
    st.session_state.chat_histories = load_history()

if "current_chat_name" not in st.session_state:
    st.session_state.current_chat_name = 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)

# Create a chat history dropdown
chat_history = st.sidebar.selectbox("Select Chat History", ["Current Chat"] + list(st.session_state.chat_histories.keys()))

if chat_history != "Current Chat":
    st.session_state.messages = st.session_state.chat_histories[chat_history]
else:
    if selected_model not in st.session_state:
        st.session_state[selected_model] = model_links[selected_model]

# Create a system prompt input
system_prompt = st.sidebar.text_input("System Prompt", value="", help="Optional system prompt for the chat model.")

# Display chat messages from history on app rerun
for message in st.session_state.messages:
    avatar = "🔋" if message["role"] == "assistant" else "🧑‍💻"
    with st.chat_message(message["role"], avatar=avatar):
        st.markdown(message["content"])

# Accept user input
if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
    with st.chat_message("user", avatar="🧑‍💻"):
        st.markdown(prompt)
    st.session_state.messages.append({"role": "user", "content": prompt})

    try:
        # Construct the list of messages with an optional system prompt
        messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
        if system_prompt:
            messages.insert(0, {"role": "system", "content": system_prompt})
        
        # Make the API request
        stream = client.chat.completions.create(
            model=model_links[selected_model],
            messages=messages,
            temperature=temp_values,
            stream=True,
            max_tokens=3000,
        )
        response = st.write_stream(stream)

    except Exception as e:
        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)
        random_dog_pick = 'https://random.dog/' + random_dog[np.random.randint(len(random_dog))]
        st.image(random_dog_pick)
        st.write("This was the error message:")
        st.write(e)

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

    # Automatically name and save chat history
    if not st.session_state.current_chat_name:
        st.session_state.current_chat_name = f"Chat_{len(st.session_state.chat_histories) + 1}"
        st.session_state.chat_histories[st.session_state.current_chat_name] = st.session_state.messages
        save_history(st.session_state.chat_histories)

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