import os
import logging
import re
import io
from PIL import Image
import gradio as gr

# ✅ تعطيل SSR قبل استيراد Gradio
os.environ["GRADIO_SSR_MODE"] = "False"
os.environ["GRADIO_NODE_DISABLED"] = "True"

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

logger.info("بدء تشغيل DermaScan AI...")

try:
    from rag import build_default_vectorstore
    from agent import (
        build_agent,
        set_session_storage,
        set_current_thread_id,
        set_api_client,
    )
    from api_client import DermaScanAPIClient
    logger.info("✅ تم استيراد جميع الوحدات بنجاح")
except Exception as e:
    logger.error(f"❌ فشل استيراد الوحدات: {e}", exc_info=True)
    raise

MODEL_NAME = "llama-3.1-8b-instant"
TEMPERATURE = 0.25
TOP_K = 3
EXTERNAL_API_URL = "https://omarelrayes-api.hf.space"
SESSIONS = {}
agent = None
api_client = None

def get_session(thread_id: str) -> dict:
    if thread_id not in SESSIONS:
        SESSIONS[thread_id] = {
            "role": "patient", "last_analysis": None, "current_image": None,
            "_image_blobs": {}, "_session_image_names": [], "_turn_count": 0
        }
    return SESSIONS[thread_id]

def initialize_system():
    global agent, api_client
    try:
        logger.info("بدء تهيئة النظام...")
        groq_key = os.environ.get("GROQ_API_KEY")
        if not groq_key:
            logger.warning("GROQ_API_KEY not set")
        else:
            logger.info("GROQ_API_KEY found")
        
        api_client = DermaScanAPIClient(EXTERNAL_API_URL)
        set_api_client(api_client)
        
        if api_client.health_check():
            logger.info("External API is healthy")
        
        vectorstore = build_default_vectorstore()
        retriever = vectorstore.as_retriever(search_kwargs={"k": TOP_K}) if vectorstore else None
        
        if retriever is None:
            logger.warning("Vectorstore not available")
        
        agent = build_agent(retriever, model_name=MODEL_NAME, temperature=TEMPERATURE)
        logger.info("✅ Agent built successfully")
        logger.info("تم تهيئة النظام بنجاح!")
    except Exception as e:
        logger.error(f"فشل التهيئة: {e}", exc_info=True)
        raise

initialize_system()

def chat_with_agent(message: str, history: list) -> str:
    if agent is None:
        return "System not initialized yet."
    
    session = get_session("default")
    set_session_storage(SESSIONS)
    set_current_thread_id("default")
    
    try:
        last_analysis = session.get("last_analysis")
        analysis_ctx = f"\n\n[Analysis: {last_analysis.get('label', 'N/A')}]" if last_analysis else ""
        full_prompt = message + analysis_ctx
        config = {"configurable": {"thread_id": "default"}, "recursion_limit": 14}
        
        final_text = ""
        for event in agent.stream(
            {"messages": [("user", full_prompt)]},
            config=config,
            stream_mode="values"
        ):
            last_msg = event["messages"][-1]
            if last_msg.type == "ai" and last_msg.content:
                final_text = last_msg.content
        
        cleaned_text = re.sub(r'\[ANALYSIS_RESULT:\{.*?\}\]', '', final_text).strip()
        session["_turn_count"] = session.get("_turn_count", 0) + 1
        return cleaned_text if cleaned_text else "No response."
    except Exception as e:
        logger.error(f"Chat error: {e}")
        return f"Error: {str(e)}"

def analyze_image(image, thread_id: str = "default") -> str:
    if api_client is None:
        return "API client not initialized"
    
    try:
        api_client.set_role(thread_id, "patient")
        session = get_session(thread_id)
        session["current_image"] = image
        
        result = api_client.upload_and_analyze_image(image, thread_id)
        if not result.get('ok'):
            return f"Error: {result.get('error', 'Unknown error')}"
        
        session["last_analysis"] = {
            "label": result.get("label"),
            "confidence_pct": result.get("confidence_pct"),
            "infection_pct": result.get("infection_pct")
        }
        
        return (
            f"تم التحليل بنجاح!\n\n"
            f"التصنيف: {result.get('label')}\n"
            f"نسبة الثقة: {result.get('confidence_pct')}%\n"
            f"المساحة المصابة: {result.get('infection_pct')}%"
        )
    except Exception as e:
        logger.error(f"Image analysis error: {e}")
        return f"Error: {str(e)}"

logger.info("جاري بناء واجهة Gradio...")

with gr.Blocks(title="DermaScan AI") as demo:
    gr.Markdown("# 🏥 DermaScan AI - مساعد أمراض الجلدية")
    
    with gr.Tab("📤 رفع الصورة"):
        image_input = gr.Image(type="pil", label="ارفع صورة الجلد")
        analyze_btn = gr.Button("🔍 تحليل الصورة", variant="primary")
        analysis_output = gr.Textbox(label="نتيجة التحليل", lines=6)
        analyze_btn.click(fn=analyze_image, inputs=[image_input], outputs=[analysis_output])
    
    with gr.Tab("💬 الدردشة"):
        chatbot = gr.Chatbot(label="المحادثة", height=400)
        msg_input = gr.Textbox(label="رسالتك", placeholder="اسأل عن حالتك الجلدية...", lines=2)
        send_btn = gr.Button("🚀 إرسال", variant="primary")
        clear_btn = gr.Button("🗑️ مسح")
        
        def user_message(user_msg, history):
            return "", history + [[user_msg, None]]
        
        def bot_response(history):
            if not history:
                return history
            user_msg = history[-1][0]
            response = chat_with_agent(user_msg, history[:-1])
            history[-1][1] = response
            return history
        
        send_btn.click(user_message, [msg_input, chatbot], [msg_input, chatbot]).then(
            bot_response, chatbot, chatbot
        )
        msg_input.submit(user_message, [msg_input, chatbot], [msg_input, chatbot]).then(
            bot_response, chatbot, chatbot
        )
        clear_btn.click(lambda: None, None, chatbot)
    
    with gr.Tab("📚 API Info"):
        gr.Markdown("## API شغالة! استخدم Gradio Client للاتصال.")

logger.info("✅ تم بناء واجهة Gradio")
logger.info("🎉 DermaScan AI جاهز!")

# ✅ الحل الحقيقي: ssr_mode=False في launch()
demo.launch(
    server_name="0.0.0.0",
    server_port=7860,
    ssr_mode=False,  # ← ده اللي هيمنع Node.js SSR
    share=False
)