import streamlit as st
import datetime
import requests
from streamlit_extras.add_vertical_space import add_vertical_space
from streamlit_lottie import st_lottie
import streamlit.components.v1 as components

# Senin lokal servislerini doğrudan içeri aktarıyoruz (FastAPI veya Render'a gerek yok!)
from app.services.nlp_triplet import extract_triplets_from_text
from app.services.memory_engine import group_by_author, count_predicates, most_common_subjects
from app.services.graph_builder import build_graph_from_triplets
from app.services.graph_visualizer import visualize_graph

st.set_page_config(page_title="AI Memory Graph", layout="wide", page_icon="🧠")

# Lottie Animasyonu Yükleme
def load_lottieurl(url: str):
    r = requests.get(url)
    if r.status_code != 200: return None
    return r.json()

lottie_ai = load_lottieurl("https://assets9.lottiefiles.com/packages/lf20_touohxv0.json")

col1, col2 = st.columns([4, 1])
with col1:
    st.title("🧠 AI Memory Graph")
    st.markdown("A visual way to extract and understand multi-user chat memories using NLP + Graphs.")
with col2:
    if lottie_ai:
        st_lottie(lottie_ai, height=100, key="ai")

add_vertical_space(1)

# Session State Tanımlamaları
if "messages" not in st.session_state:
    st.session_state["messages"] = []
if "triplets" not in st.session_state:
    st.session_state["triplets"] = []

# --- SOHBET GİRİŞ ALANI ---
st.subheader("💬 Add Chat Messages")
with st.form("message_form", clear_on_submit=True):
    col_sender, col_msg = st.columns([1, 3])
    with col_sender:
        sender = st.text_input("Sender", placeholder="e.g. Erdem")
    with col_msg:
        text = st.text_input("Message", placeholder="e.g. I recommend using FastAPI for the backend.")
    
    submitted = st.form_submit_button("➕ Add Message")
    if submitted and sender and text:
        st.session_state["messages"].append({
            "sender": sender,
            "text": text,
            "timestamp": datetime.datetime.utcnow().isoformat()
        })
        st.success(f"Message added for {sender}!")

# Eklenen mesajları göster
if st.session_state["messages"]:
    with st.expander("📑 View Current Messages", expanded=False):
        st.json(st.session_state["messages"])

    add_vertical_space(1)
    
    # --- İŞLEM BUTONLARI ---
    c1, c2, c3 = st.columns(3)

    # 1. Triplet Çıkarma İşlemi
    with c1:
        if st.button("🔍 Extract Triplets", use_container_width=True):
            with st.spinner("Analyzing text with SpaCy Transformer..."):
                all_triplets = []
                for msg in st.session_state["messages"]:
                    extracted = extract_triplets_from_text(msg["text"])
                    for triplet in extracted:
                        triplet["timestamp"] = msg["timestamp"]
                        triplet["author"] = msg["sender"]
                        all_triplets.append(triplet)
                
                st.session_state["triplets"] = all_triplets
                st.success(f"Extracted {len(all_triplets)} triplets!")
                st.json(all_triplets)

    # 2. Hafıza Özeti İşlemi
    with c2:
        if st.button("📝 Memory Summary", use_container_width=True):
            if not st.session_state["triplets"]:
                st.warning("Please extract triplets first!")
            else:
                summary = {
                    "total_triplets": len(st.session_state["triplets"]),
                    "by_user": group_by_author(st.session_state["triplets"]),
                    "predicate_counts": count_predicates(st.session_state["triplets"]),
                    "common_subjects": most_common_subjects(st.session_state["triplets"])
                }
                st.write("### 📊 Stats")
                st.json(summary)

    # 3. Grafik Çizdirme İşlemi
    with c3:
        if st.button("🌐 Show Knowledge Graph", use_container_width=True):
            if not st.session_state["triplets"]:
                st.warning("Please extract triplets first!")
            else:
                with st.spinner("Building and rendering graph..."):
                    # Grafiği oluştur
                    G = build_graph_from_triplets(st.session_state["triplets"])
                    
                    # HTML olarak kaydet (webbrowser.open KESİNLİKLE KAPALI OLMALI)
                    visualize_graph(G, output_path="memory_graph.html")
                    
                    # Kaydedilen HTML'i Streamlit içine göm
                    try:
                        with open("memory_graph.html", "r", encoding="utf-8") as f:
                            html_content = f.read()
                        st.write("### 🕸️ Graph Visualization")
                        components.html(html_content, height=600, scrolling=True)
                    except FileNotFoundError:
                        st.error("Graph HTML file could not be generated.")

# Footer
add_vertical_space(3)
st.markdown("---")
st.caption("Developed by Erdem Yavuz Hacisoftaoglu | Powered by SpaCy, NetworkX & Streamlit")