# app.py  ─  Streamlit + LangChain + Groq
import os, asyncio, streamlit as st
from dotenv import load_dotenv
from langchain.schema import SystemMessage, HumanMessage, AIMessage
from langchain_groq import ChatGroq

# ─────────────────────────  bootstrap event‑loop  ─────────────────────
try:
    asyncio.get_running_loop()
except RuntimeError:
    asyncio.set_event_loop(asyncio.new_event_loop())
if os.name == "nt":
    import asyncio as _asyncio
    asyncio.set_event_loop_policy(_asyncio.WindowsSelectorEventLoopPolicy())

# ───────────────────────────  UI  /  SETTINGS  ────────────────────────
st.set_page_config("Groq Chatbot", "🤖")
st.title("🤖  Groq‑powered Advanced Chatbot")
st.caption("DeepSeek‑R1‑Distill‑Llama‑70B • LangChain • Streamlit")

with st.sidebar:
    st.header("🔑  Groq API Key")
    groq_key = st.text_input("Paste your key here", type="password")
    st.divider()
    temperature = st.slider("Temperature", 0.0, 1.2, 0.7, 0.1)
    top_p       = st.slider("Top‑p",       0.0, 1.0, 1.0, 0.05)
    st.markdown("*All values remain local to your browser.*")

user_q = st.chat_input("Type your message…")

# ──────────────────────────  LLM (lazy init)  ─────────────────────────
MODEL_NAME = "deepseek-r1-distill-llama-70b"

def get_llm():
    if "llm" not in st.session_state:
        key = groq_key or os.getenv("GROQ_API_KEY")
        if not key:
            raise ValueError("Add your Groq key in the sidebar.")
        os.environ["GROQ_API_KEY"] = key                  # for the client
        st.session_state.llm = ChatGroq(
            model        = MODEL_NAME,
            groq_api_key = key,
            temperature  = temperature,
            top_p        = top_p,
        )
    # refresh sampling params if the sliders changed
    llm = st.session_state.llm
    llm.temperature = temperature
    llm.top_p       = top_p
    return llm

# ─────────────────────────  conversation memory  ──────────────────────
if "history" not in st.session_state:
    st.session_state.history = [
        SystemMessage(content="You are an advanced, helpful assistant.")
    ]

# ────────────────────────────  main loop  ─────────────────────────────
if user_q:
    st.session_state.history.append(HumanMessage(content=user_q))

    try:
        with st.chat_message("assistant", avatar="🤖"):
            with st.spinner("Thinking…"):
                answer = get_llm().invoke(st.session_state.history).content
            st.markdown(answer)

        st.session_state.history.append(AIMessage(content=answer))

    except Exception as err:
        st.error(f"**Error:** {err}")

# ────────────────────────  display chat history  ──────────────────────
for msg in st.session_state.history[1:]:              # skip system message
    role = "user" if isinstance(msg, HumanMessage) else "assistant"
    with st.chat_message(role):
        st.markdown(msg.content)