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from fastapi import FastAPI | |
from fastapi.responses import HTMLResponse | |
from transformers import pipeline | |
# Create a new FastAPI app instance | |
app = FastAPI() | |
# Initialize the text generation pipeline | |
pipe = pipeline("text2text-generation", model="google/flan-t5-small") | |
def home(): | |
html_content = """ | |
<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="UTF-8"> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<title>Text to Text Generation</title> | |
</head> | |
<body> | |
<h1>Welcome to Text to Text Generation</h1> | |
<iframe | |
src="https://rohitjakkam-text2text-using-docker.hf.space" | |
frameborder="0" | |
width="850" | |
height="450" | |
></iframe> | |
</body> | |
</html> | |
""" | |
return HTMLResponse(content=html_content) | |
def generate(text: str): | |
# Use pipeline to generate text from given text as input parameter | |
output = pipe(text) | |
# Return the generated text in JSON response | |
return {"output": output[0]['generated_text']} | |