| from fastapi import FastAPI | |
| from pydantic import BaseModel | |
| import joblib | |
| # Load your trained model + vectorizer + encoder | |
| model = joblib.load("bangla_model.pkl") | |
| vectorizer = joblib.load("bangla_vectorizer.pkl") | |
| label_encoder = joblib.load("bangla_label_encoder.pkl") | |
| app = FastAPI() | |
| class TextData(BaseModel): | |
| text: str | |
| def predict(data: TextData): | |
| X = vectorizer.transform([data.text]) | |
| pred = model.predict(X)[0] | |
| label = label_encoder.inverse_transform([pred])[0] | |
| return {"prediction": label} | |