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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. | |
| 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"]} | |