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from fastapi import FastAPI | |
from transformers import pipeline | |
# Create a new FastAPI app instance | |
app = FastAPI(docs_url="/") | |
# Initialize the text generation pipeline | |
# This function will be able to generate text | |
# given an input. | |
pipe = pipeline("text2text-generation", | |
model="google/flan-t5-small") | |
# 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" | |
def generate(text: str): | |
""" | |
Using the text2text-generation pipeline from `transformers`, generate text | |
from the given input text. The model used is `google/flan-t5-small`, which | |
can be found [here](<https://huggingface.co/google/flan-t5-small>). | |
""" | |
# Use the pipeline to generate text from the given input text | |
output = pipe(text) | |
# Return the generated text in a JSON response | |
return {"output": output[0]["generated_text"]} |