from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from transformers import pipeline
import uvicorn

# Initialize app
app = FastAPI(title="OrcaleSeek API", version="1.0.0")

# CORS for web access
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Change this to your website domain
    allow_methods=["*"],
    allow_headers=["*"],
)

# Load model
classifier = pipeline(
    "text-classification",
    model="your-username/OrcaleSeek",
    tokenizer="your-username/OrcaleSeek"
)

class PredictionRequest(BaseModel):
    text: str
    max_length: int = 128

class PredictionResponse(BaseModel):
    prediction: list
    status: str
    model: str = "OrcaleSeek"

@app.get("/")
def home():
    return {"message": "OrcaleSeek API is running! 🚀"}

@app.get("/health")
def health_check():
    return {"status": "healthy"}

@app.post("/predict", response_model=PredictionResponse)
async def predict(request: PredictionRequest):
    try:
        result = classifier(request.text)
        return PredictionResponse(
            prediction=result,
            status="success"
        )
    except Exception as e:
        return PredictionResponse(
            prediction=[],
            status=f"error: {str(e)}"
        )

# Run with: uvicorn api:app --host 0.0.0.0 --port 8000 --reload
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)