main.py

from fastapi import FastAPI
from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware
from transformers import pipeline
from pythainlp.util import normalize

# โหลดสมอง AI (ภาษาไทย)
print("Downloading Model...")
classifier = pipeline("text-classification", model="SandboxBhh/sentiment-thai-text-model", tokenizer="SandboxBhh/sentiment-thai-text-model")

app = FastAPI()

# เปิดอนุญาตให้เว็บข้างนอกเข้ามาใช้ได้
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

class Item(BaseModel):
    text: str

# ฟังก์ชันแปลผล (Positive/Negative)
label_map = {
    "pos": "Positive (บวก)",
    "neg": "Negative (ลบ)",
    "neu": "Neutral (ทั่วไป)",
    "q": "Question (สอบถาม)"
}

@app.get("/")
def home():
    return {"status": "AI Ready"}

@app.post("/analyze-sentiment")
def analyze(item: Item):
    text = normalize(item.text)
    prediction = classifier(text)[0]
    return {
        "label": label_map.get(prediction['label'], "Unknown"),
        "score": round(prediction['score'] * 100, 2)
    }