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| from fastapi import FastAPI | |
| from fastapi.responses import HTMLResponse | |
| from transformers import pipeline | |
| from fastapi.middleware.cors import CORSMiddleware | |
| app = FastAPI() | |
| app.add_middleware(CORSMiddleware, | |
| allow_origins=["*"], | |
| allow_credentials=True, | |
| allow_methods=["*"], | |
| allow_headers=["*"]) | |
| pipe = pipeline(task="text-generation", model="gpt2-large", framework="pt") | |
| def get_ui(): | |
| """ | |
| Returns the HTML page for the UI. | |
| """ | |
| 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 Generator</title> | |
| <style> | |
| body { | |
| font-family: Arial, sans-serif; | |
| display: flex; | |
| justify-content: center; | |
| align-items: center; | |
| min-height: 100vh; | |
| margin: 0; | |
| padding: 20px; | |
| background-color: #f5f5f5; | |
| } | |
| #container { | |
| width: 100%; | |
| max-width: 600px; | |
| background: white; | |
| padding: 20px; | |
| border-radius: 8px; | |
| box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1); | |
| box-sizing: border-box; | |
| } | |
| #prompt, #output { | |
| width: 100%; | |
| padding: 10px; | |
| margin-bottom: 20px; | |
| border: 1px solid #ddd; | |
| border-radius: 4px; | |
| box-sizing: border-box; | |
| } | |
| #output { | |
| min-height: 100px; | |
| white-space: pre-wrap; | |
| background-color: #f9f9f9; | |
| padding: 15px; | |
| border-radius: 4px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <div id="container"> | |
| <h1>Text Generator</h1> | |
| <textarea id="prompt" rows="4" placeholder="Enter your prompt here..."></textarea> | |
| <div id="output"></div> | |
| </div> | |
| <script> | |
| document.getElementById("prompt").addEventListener("keydown", async function(event) { | |
| if (event.key === "Enter" && !event.shiftKey) { | |
| event.preventDefault(); | |
| const prompt = this.value.trim(); | |
| if (!prompt) return; | |
| const outputDiv = document.getElementById("output"); | |
| outputDiv.innerHTML = "Loading..."; | |
| this.disabled = true; | |
| const response = await fetch(`/generate?text=${encodeURIComponent(prompt)}`); | |
| const data = await response.json(); | |
| const text = data.output; | |
| outputDiv.innerHTML = ""; | |
| let i = 0; | |
| function printText() { | |
| if (i < text.length) { | |
| outputDiv.innerHTML += text.charAt(i); | |
| i++; | |
| setTimeout(printText, 50); | |
| } else { | |
| document.getElementById("prompt").disabled = false; | |
| } | |
| } | |
| printText(); | |
| } | |
| }); | |
| </script> | |
| </body> | |
| </html> | |
| """ | |
| return html_content | |
| def generate(text: str): | |
| """ | |
| Using the text-generation pipeline from `transformers`, generate text | |
| from the given input text. The model used is `openai-community/gpt2-large`, which | |
| can be found [here](<https://huggingface.co/openai-community/gpt2-large>). | |
| """ | |
| output = pipe(text) | |
| return {"output": output[0]["generated_text"]} | |