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FastApi example
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import uvicorn | |
from fastapi import FastAPI | |
from model import SentimentModel, SentimentQueryModel | |
app = FastAPI() | |
model = SentimentModel() | |
@app.post('/predict') | |
def predict(data: SentimentQueryModel): | |
data = data.dict() | |
polarity, subjectivity = model.get_sentiment(data['text']) | |
return { | |
'polarity': polarity, | |
'subjectivity': subjectivity | |
} | |
if __name__ == '__main__': | |
uvicorn.run(app, host='127.0.0.1', port=8000) |
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import spacy | |
from spacytextblob import SpacyTextBlob | |
from pydantic import BaseModel | |
class SentimentQueryModel(BaseModel): | |
text : str | |
class SentimentModel: | |
@Language.spacytextblob | |
def get_sentiment(self, text): | |
nlp = spacy.load('en_core_web_sm') | |
spacy_text_blob = SpacyTextBlob() | |
nlp.add_pipe(spacy_text_blob) | |
doc = nlp(text) | |
polarity = doc._.sentiment.polarity | |
subjectivity = doc._.sentiment.subjectivity | |
return polarity, subjectivity |
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