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from model.layer import Bi_LSTM_CRF
from flair.data import Sentence
from schema import WordSchema
from settings import app
from fastapi import APIRouter
from starlette import status
from starlette.responses import JSONResponse
import uvicorn
api_router = APIRouter()
# Variables for Interactive selections
tagger = Bi_LSTM_CRF.load("checkpoints/best-model.pt")
@api_router.get("/")
def health():
return JSONResponse(
status_code=status.HTTP_201_CREATED,
content={
"code": 200,
"version": "1.0.0"
},
)
@api_router.get("/api/model", response_model=WordSchema)
def model(
*,
word: str,
file_name: str
):
"""
An api for serving the model for the PHI classification.
:param word: list of word tokens in a paragraph.
:param file_name: name of the wile.
:returns: json response that contains labeled
tags their respective classification.
"""
txt = Sentence(word)
tagger.predict(txt)
labels, tags = [], []
for entity in txt.get_spans('ner'):
labels.append(entity.text)
tags.append(entity.get_label("ner").value)
return JSONResponse(
status_code=status.HTTP_201_CREATED,
content={
"code": 200,
"data": {
"labels": labels,
"tags": tags
}
},
)
app.include_router(api_router)
if __name__ == "__main__":
uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True, debug=True)
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