from sentence_transformers import SentenceTransformer
from fastapi import FastAPI
from pydantic import BaseModel
import torch

app = FastAPI()
model_name = "meedan/paraphrase-filipino-mpnet-base-v2"
model = SentenceTransformer(model_name)


class TextInput(BaseModel):
    text: str


@app.post("/embed")
def embed_text(input: TextInput):
    with torch.no_grad():
        embedding = model.encode([input.text])[0].tolist()
    return {"embedding": embedding}


@app.get("/")
def read_root():
    return f"Encode text to numerical vectors using sentence transformer: {model_name}"