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from fastapi import FastAPI | |
from transformers import pipeline | |
# Create a new FastAPI app instance | |
app = FastAPI(docs_url="/") | |
# Initialize text generation pipeline - to generate text given an input. | |
pipe = pipeline( | |
"text2text-generation", | |
model = "google/flan-t5-small" | |
) | |
# Endpoint route: GET request at `/generate` | |
def generate(text: str) -> dict: | |
""" | |
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>). | |
generates text based on the # input using the pipeline() object | |
returns a JSON response containing the gneerated text under the key 'output' | |
""" | |
# 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"]} | |