Created
April 4, 2021 17:26
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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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