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from fastapi import FastAPI
from transformers import pipeline
# Create a new FastAPI app instance
app = FastAPI()
# Initialize the text generation pipeline
# This function will be able to generate text
# given an input.
summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")
# Define a function to handle the GET request at `/generate`
# The generate() function is defined as a FastAPI route that takes a
# string parameter called text. The function generates text based on the # input using the pipeline() object, and returns a JSON response
# containing the generated text under the key "output"
@app.get("/generate")
def generate(text: str):
"""
Using the text summarization pipeline from `transformers`, summerize text
from the given input text. The model used is `philschmid/bart-large-cnn-samsum`, which
can be found [here](<https://huggingface.co/philschmid/bart-large-cnn-samsum>).
"""
# Use the pipeline to generate text from the given input text
output = summarizer(text)
# Return the generated text in a JSON response
return {"output": output[0]["summary_text"]} |