fastapi_app.py

from fastapi import FastAPI, HTTPException
import os
from starlette.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import uvicorn
import torch
from simpletransformers.classification import ClassificationModel
app = FastAPI()

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

class Query(BaseModel):
    query :str

rob_chem_model = ClassificationModel('roberta', 'seyonec/SMILES_tokenized_PubChem_shard00_160k',use_cuda=False ,args={'evaluate_each_epoch':True , 'evaluate_during_training_verbose':True, 'seed':4})

@app.post("/ToxicityPrediction")
async def c(query:Query):
    try:
        predictions, raw_outputs = rob_chem_model.predict([str(query.query)])
        print(predictions)

        return {"prediction":predictions[0]}

    except Exception as e:
        raise HTTPException(detail = str(e) , status_code = 500)
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=5566)