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from transformers import pipeline
from fastapi import FastAPI
from fastapi import FastAPI
from transformers import pipeline
# NOTE - we configure docs_url to serve the interactive Docs at the root path
# of the app. This way, we can use the docs as a landing page for the app on Spaces.
from fastapi import FastAPI
from pydantic import BaseModel
from transformers import pipeline
# You can check any other model in the Hugging Face Hub
pipe = pipeline(model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")
app = FastAPI(docs_url="/")
@app.get("/")
def greet_json():
return {"working..."}
# We define that we expect our input to be a string
class RequestModel(BaseModel):
input: str
# Now we define that we accept post requests
@app.post("/sentiment")
def get_response(request: RequestModel):
prompt = request.input
response = pipe(prompt)
label = response[0]["label"]
score = response[0]["score"]
return f"The '{prompt}' input is {label} with a score of {score}" |