from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from transformers import AutoTokenizer
import onnxruntime as ort
import numpy as np 
from pathlib import Path
import traceback
# import pandas as pd # Dihapus karena tidak dipakai

app = FastAPI()

# === CORS untuk frontend di Vercel ===
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],      
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# === Path setup ===
BASE_DIR = Path(__file__).resolve().parent
MODEL_PATH = BASE_DIR / "models" / "bert_chatbot.onnx"
TOKENIZER_PATH = BASE_DIR / "models" / "bert-base-multilingual-cased" 
# DATASET_PATH tidak diperlukan lagi

# === Global Variables ===
tokenizer = None
session = None

# === Load tokenizer dan model ===
try:
    print("🚀 Loading ONNX model...")
    
    tokenizer = AutoTokenizer.from_pretrained(str(TOKENIZER_PATH))
    session = ort.InferenceSession(str(MODEL_PATH), providers=["CPUExecutionProvider"])
    
    print("✅ ONNX model loaded!")

except Exception as e:
    # Log ini akan muncul jika ada masalah Path/File saat startup
    print("--------------------------------------------------")
    print(f"❌ FATAL ERROR SAAT MEMUAT ONNX/SUMBER DAYA: {e}")
    traceback.print_exc()
    print("--------------------------------------------------")
    pass

# === Default responses ===
responses = {
    # ⭐ PERBAIKAN INI MEMASTIKAN JAWABAN GREETING BENAR ⭐
    "about_me": "I am a passionate developer specializing in AI and web development.",
    "skills": "My main skills are HTML5, CSS3, JavaScript, Laravel, Node.js, Database, TensorFlow, PyTorch, Firebase, and Jupyter Notebook.",
    "projects": "Some of my projects are Mobile Apps Bald Detection and Jupyter Notebook Bald Detection.",
    "experience": "I have worked as IT Support, AI Engineer, and Freelancer on multiple projects.",
    "career_goal": "My career goal is to become a Full Stack Developer and Machine Learning Engineer.",
    "greeting": "Hello! How can I help you regarding this portfolio?", # JAWABAN GREETING YANG BENAR
    "fallback": "I'm sorry, I don't understand. Please ask another question."
}

# === Request schema ===
class ChatRequest(BaseModel):
    text: str

@app.get("/")
async def root():
    return {"message": "🚀 ONNX Chatbot API running on Hugging Face"}

@app.post("/chatbot")
async def chatbot(req: ChatRequest):
    # Deklarasikan intent sebagai fallback untuk mencegah NameError di blok except
    intent = "fallback" 
    
    if session is None:
        return {"reply": responses["fallback"], "intent": "error_loading"}
        
    try:
        # 1. Tokenisasi (return_tensors="np")
        inputs = tokenizer(req.text, return_tensors="np", padding=True, truncation=True, max_length=128)
        
        # 2. Perkuat Tipe Data untuk ONNX
        input_names = [i.name for i in session.get_inputs()]
        ort_inputs = {}

        for name in input_names:
            if name in inputs:
                ort_inputs[name] = inputs[name].astype(np.int64) 

        # 3. Inferensi ONNX
        ort_outputs = session.run(None, ort_inputs)
        
        # 4. Ambil Logit dan Prediksi
        logits = ort_outputs[0]
        pred_id = np.argmax(logits, axis=1)[0]
        
        # === Mapping ID ke label ===
        id2label = {
            0: "greeting", 1: "about_me", 2: "skills", 3: "projects", 
            4: "experience", 5: "career_goal", 6: "fallback",
        }
        
        # Nilai 'intent' yang benar disimpan di sini
        intent = id2label.get(pred_id, "fallback")
        
        # === Ambil jawaban ===
        # Respon diambil dari dictionary responses global
        reply = responses.get(intent, responses["fallback"])
                    
        return {"reply": str(reply), "intent": intent}
        
    except Exception as e:
        import traceback
        print(f"❌ Runtime error in /chatbot: {e}")
        traceback.print_exc()
        return {"reply": "⚠️ Internal server error.", "intent": intent}