File size: 563 Bytes
356aab4
 
 
 
 
0a51239
356aab4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fa4e059
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
from fastapi import FastAPI, Request
from transformers import pipeline
from pydantic import BaseModel

class TextQuery(BaseModel):
    inputs: str


def predict(text: str):
    model_name = "blanchefort/rubert-base-cased-sentiment-rurewiews"
    pipe = pipeline("text-classification", model=model_name, return_all_scores=True)
    scores = pipe(text)[0]
    sorted_scores = sorted(scores, key=lambda x: x['score'], reverse=True)
    return sorted_scores


app = FastAPI()

@app.post("/", )
def home(request: Request, q: TextQuery):


    return predict(q.inputs)