import os
import streamlit as st
from huggingface_hub import InferenceClient
from dotenv import load_dotenv

# Load .env (if you’re using one)
load_dotenv()

# Instantiate once
client = InferenceClient(
    provider="auto",
    api_key=os.environ["HUGGINGFACEHUB_API_TOKEN"]
)

# Page config
st.set_page_config(page_title="Educational Chatbot", layout="wide")
st.title("🎓 Educational Chatbot")

# Initialize history
if "history" not in st.session_state:
    st.session_state.history = []

# Render existing messages
for sender, message in st.session_state.history:
    if sender == "You":
        st.chat_message("user").write(message)
    else:
        st.chat_message("assistant").write(message)

# Input box
user_input = st.chat_input("Ask me anything…")

if user_input:
    # Display user message immediately
    st.chat_message("user").write(user_input)
    st.session_state.history.append(("You", user_input))

    # Bot placeholder
    placeholder = st.chat_message("assistant")
    placeholder.write("⏳ Thinking...")

    try:
        # Call HF Inference API
        completion = client.chat.completions.create(
            model="deepseek-ai/DeepSeek-R1",
            messages=[{"role": "user", "content": user_input}],
        )
        reply = completion.choices[0].message["content"]
    except Exception as e:
        reply = f"❌ API Error: {e}"

    # Update placeholder with real response
    placeholder.write(reply)
    st.session_state.history.append(("Bot", reply))