app.py

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch
import warnings
import uvicorn

# Tắt warning lặt vặt
warnings.filterwarnings("ignore")

# Load model
MODEL_NAME = "tarudesu/ViHateT5-base-HSD"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)

# Khởi tạo FastAPI
app = FastAPI(title="Vietnamese Toxic Comment Detection API")

# Bật CORS cho tất cả domain
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],   # Cho phép tất cả domain
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Schema cho input
class CommentInput(BaseModel):
    text: str
    prefix: str = "hate-speech-detection"

# Hàm dự đoán
def predict_vihatet5(comment: str, prefix: str = "hate-speech-detection"):
    input_text = prefix + ": " + comment
    inputs = tokenizer(
        input_text,
        return_tensors="pt",
        truncation=True,
        padding=True,
        max_length=128
    )
    output_ids = model.generate(**inputs, max_length=50)
    output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
    return output
@app.get("/")
async def root():
    """Health check endpoint with comprehensive API documentation"""
    return {
        "endpoints": {
            "POSR https://haiss123-check-comment.hf.space/predict": {
                "Resquest body": {
                    "input": "string",
                    "prefix": "hate-speech-detection or toxic-speech-detection"
                },
                "Response": {
                    "input": "string",
                    "prefix": "hate-speech-detection or toxic-speech-detection",
                    "prediction": "offensive,hate,..."
                    
                }
            }
        }
    }
# API route
@app.post("/predict")
def predict(input_data: CommentInput):
    result = predict_vihatet5(input_data.text, prefix=input_data.prefix)
    return {
        "input": input_data.text,
        "prefix": input_data.prefix,
        "prediction": result
    }

# Chạy app
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)