import gradio as gr
import requests
import os
import json
from datetime import datetime
import re
from pathlib import Path
import uuid

# === CONFIG ===
STORAGE_DIR = Path("journal_data")
STORAGE_DIR.mkdir(exist_ok=True)
HISTORY_FILE = STORAGE_DIR / "history.json"
API_KEY = os.getenv("GROQ_API_KEY")
API_URL = "https://api.groq.com/openai/v1/chat/completions"
MODEL = "gemma2-9b-it"

# === MEMORY: Load history ===
def load_history():
    if HISTORY_FILE.exists():
        try:
            with open(HISTORY_FILE, 'r', encoding='utf-8') as f:
                return json.load(f)
        except: pass
    return []

def save_history(history):
    with open(HISTORY_FILE, 'w', encoding='utf-8') as f:
        json.dump(history[-100:], f, indent=2, ensure_ascii=False)  # Simpen 100 terakhir

chat_history = load_history()
current_session = str(uuid.uuid4())

# === Smart Summary Generator ===
def generate_summary(messages):
    if not messages:
        return "User baru mulai ngobrol."
    
    user_msgs = [m for m in messages if m['role'] == 'user']
    topics = [m['topic'] for m in user_msgs[-5:]]
    main_topic = max(set(topics), key=topics.count) if topics else "general"
    
    # Emosi kasar
    pos = sum(1 for m in user_msgs[-3:] if any(w in m['content'].lower() for w in ['senang', 'semangat', 'baik']))
    neg = sum(1 for m in user_msgs[-3:] if any(w in m['content'].lower() for w in ['capek', 'sedih', 'gagal']))
    mood = "positif" if pos > neg else "negatif" if neg > pos else "netral"
    
    # Gaya bicara
    style = "kasual" if any('gue' in m['content'].lower() or 'anjir' in m['content'].lower() for m in user_msgs[-2:]) else "formal"
    
    return f"""
Topik utama: {main_topic}
Mood: {mood}
Gaya: {style}
Catatan: Validasi emosi dulu, hindari klise, akhiri dengan pertanyaan terbuka.
    """.strip()

# === Deteksi Gaya Khusus (Tom Schreiter, dll) ===
def detect_style_instruction(content):
    content = content.lower()
    if "gaya schreiter" in content: return "Tom Schreiter: pendek, ngena, Mini-Stories, empati, efektif."
    if "gaya henneke" in content: return "Henneke Duistermaat: hangat, relatable, humor halus."
    if "gaya ogilvy" in content: return "David Ogilvy: elegan, persuasive, storytelling memikat."
    if "gaya halbert" in content: return "Gary Halbert: bold, direct, seperti surat penjualan."
    if "gaya rohn" in content: return "Jim Rohn: inspiratif, penuh wisdom."
    if "gaya lao tzu" in content: return "Lao Tzu: filosofis, minimalis, tenang."
    return "santai, cerdas, kayak ngobrol sama world-class mentor."

# === Kirim ke Groq + Context Ringan ===
def groq_respond(message, topic):
    if not message.strip(): return "❌ Isi pesannya dulu.", ""
    if not API_KEY: return "❌ GROQ_API_KEY belum diset.", ""
    
    global chat_history, current_session
    
    # Simpan user message
    user_msg = {
        "role": "user",
        "content": message.strip(),
        "topic": topic,
        "timestamp": datetime.now().isoformat(),
        "session_id": current_session
    }
    chat_history.append(user_msg)
    
    # Buat context: system + summary + 2 terakhir
    summary = generate_summary(chat_history)
    style_instruction = detect_style_instruction(message)
    
    recent = chat_history[-2:]  # Cuma 2 terakhir
    messages = [
        {
            "role": "system",
            "content": f"""Kamu adalah Deepseek-Mentor.
Prinsip:
1. Validasi emosi dulu sebelum solusi.
2. Hindari jawaban generik — tanya balik yang mendalam.
3. Sesuaikan gaya: {style_instruction}
4. Akhiri dengan pertanyaan terbuka yang mengajak bertindak.
5. Jangan jadi motivator klise. Jadi teman yang kompeten.

[MEMORY]
{summary}
""".strip()
        }
    ] + [{"role": m["role"], "content": m["content"]} for m in recent]
    
    try:
        resp = requests.post(
            API_URL,
            headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
            json={
                "model": MODEL,
                "messages": messages,
                "max_tokens": 1024,
                "temperature": 0.9,
                "top_p": 0.95,
                "presence_penalty": 0.8,
                "frequency_penalty": 0.7
            },
            timeout=30
        )
        resp.raise_for_status()
        ai_msg = resp.json()["choices"][0]["message"]["content"]
        
        # Simpan response
        chat_history.append({
            "role": "assistant",
            "content": ai_msg,
            "topic": topic,
            "timestamp": datetime.now().isoformat(),
            "session_id": current_session
        })
        save_history(chat_history)
        return ai_msg, ""
    except Exception as e:
        return f"❌ Error: {str(e)}", ""

# === Gradio UI ===
with gr.Blocks(title="🧠 AI Journal Paling Keren Sedunia", theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🧠 AI Journal Paling Keren Sedunia")
    gr.Markdown("Minimalis. Pintar. Nyambung. Input token < 300, tapi tetap kayak ngobrol beneran.")

    with gr.Tab("💬 Chat"):
        response = gr.Textbox(label="🤖 AI", lines=10, interactive=False, show_copy_button=True)
        user_input = gr.Textbox(label="✍️ Kamu", placeholder="Apa yang kamu rasakan sekarang?", lines=3)
        topic_input = gr.Textbox(label="🏷️ Topik", value="journal", placeholder="e.g., produktivitas, hubungan")
        send_btn = gr.Button("🚀 Kirim")
    
    with gr.Tab("📚 Riwayat"):
        history_display = gr.Textbox(label="Riwayat", lines=15, interactive=False, show_copy_button=True)
        refresh_btn = gr.Button("🔄 Muat Ulang")
    
    with gr.Tab("📊 Ringkasan"):
        summary_display = gr.Textbox(label="Insight", lines=10, interactive=False)
        gen_summary_btn = gr.Button("🔮 Buat Ringkasan")

    # Actions
    send_btn.click(groq_respond, [user_input, topic_input], [response, user_input])
    refresh_btn.click(lambda: "\n\n".join(f"[{m['timestamp'][:10]}] {m['role']}: {m['content']}" for m in chat_history[-20:]), None, history_display)
    gen_summary_btn.click(lambda: generate_summary(chat_history), None, summary_display)

# Jalanin
if __name__ == "__main__":
    demo.launch()