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flan-t5-small-text-gen
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vsmolyakov commited on
Commit
faff143
·
1 Parent(s): cfbb534

html fix

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Files changed (3) hide show
  1. app.py +10 -25
  2. static/index.html +36 -24
  3. static/script.js +12 -8
app.py CHANGED
@@ -1,35 +1,20 @@
1
  from fastapi import FastAPI
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- from transformers import pipeline
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  from fastapi.staticfiles import StaticFiles
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  from fastapi.responses import FileResponse
5
 
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- # Create a new FastAPI app instance
 
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  app = FastAPI()
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-
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- # Initialize the text generation pipeline
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- # This function will be able to generate text
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- # given an input.
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- pipe = pipeline("text2text-generation", model="google/flan-t5-small")
 
 
13
 
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  app.mount("/", StaticFiles(directory="static", html=True), name="static")
15
 
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  @app.get("/")
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  def index() -> FileResponse:
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- return FileResponse(path="/app/static/index.html", media_type="text/html")
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-
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- # Define a function to handle the GET request at `/generate`
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- # The generate() function is defined as a FastAPI route that takes a
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- # string parameter called text. The function generates text based on the # input using the pipeline() object, and returns a JSON response
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- # containing the generated text under the key "output"
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- @app.get("/infer_t5")
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- def t5(text: str):
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- """
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- Using the text2text-generation pipeline from `transformers`, generate text
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- from the given input text. The model used is `google/flan-t5-small`, which
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- can be found [here](<https://huggingface.co/google/flan-t5-small>).
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- """
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- # Use the pipeline to generate text from the given input text
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- output = pipe(text)
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-
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- # Return the generated text in a JSON response
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- return {"output": output[0]["generated_text"]}
 
1
  from fastapi import FastAPI
 
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  from fastapi.staticfiles import StaticFiles
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  from fastapi.responses import FileResponse
4
 
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+ from transformers import pipeline
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+
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  app = FastAPI()
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+
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+ pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
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+
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+ @app.get("/infer_t5")
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+ def t5(input):
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+ output = pipe_flan(input)
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+ return {"output": output[0]["generated_text"]}
15
 
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  app.mount("/", StaticFiles(directory="static", html=True), name="static")
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  @app.get("/")
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  def index() -> FileResponse:
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+ return FileResponse(path="/app/static/index.html", media_type="text/html")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
static/index.html CHANGED
@@ -1,24 +1,36 @@
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- <main>
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- <section id="text-gen">
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- <h2>Text generation using Flan T5</h2>
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- <p>
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- Model:
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- <a
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- href="https://huggingface.co/google/flan-t5-small"
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- rel="noreferrer"
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- target="_blank"
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- >google/flan-t5-small
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- </a>
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- </p>
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- <form class="text-gen-form">
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- <label for="text-gen-input">Text prompt</label>
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- <input
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- id="text-gen-input"
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- type="text"
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- value="German: There are many ducks"
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- />
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- <button id="text-gen-submit">Submit</button>
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- <p class="text-gen-output"></p>
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- </form>
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- </section>
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- </main>
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <!DOCTYPE html>
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+ <html lang="en">
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+ <head>
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+ <meta charset="UTF-8" />
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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+ <title>Fast API 🤗 Space served with Uvicorn</title>
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+ <link rel="stylesheet" href="style.css" />
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+ <script type="module" src="script.js"></script>
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+ </head>
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+ <body>
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+ <main>
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+ <section id="text-gen">
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+ <h1>Text generation using Flan T5</h1>
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+ <p>
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+ Model:
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+ <a
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+ href="https://huggingface.co/google/flan-t5-small"
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+ rel="noreferrer"
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+ target="_blank"
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+ >google/flan-t5-small</a
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+ >
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+ </p>
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+ <form class="text-gen-form">
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+ <label for="text-gen-input">Text prompt</label>
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+ <input
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+ id="text-gen-input"
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+ type="text"
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+ value="English: Translate How are you ?. Russian:"
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+ />
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+ <button id="text-gen-submit">Submit</button>
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+ <p class="text-gen-output"></p>
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+ </form>
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+ </section>
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+ </main>
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+ </body>
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+ </html>
static/script.js CHANGED
@@ -1,17 +1,21 @@
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- const textGenForm = document.querySelector(".text-gen-form");
2
 
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  const translateText = async (text) => {
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- const inferResponse = await fetch(`infer_t5?input=${text}`);
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- const inferJson = await inferResponse.json();
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- return inferJson.output;
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  };
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- textGenForm.addEventListener("submit", async (event) => {
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  event.preventDefault();
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- const textGenInput = document.getElementById("text-gen-input");
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- const textGenParagraph = document.querySelector(".text-gen-output");
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- textGenParagraph.textContent = await translateText(textGenInput.value);
 
 
 
 
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  });
 
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+ const textGenForm = document.querySelector('.text-gen-form');
2
 
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  const translateText = async (text) => {
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+ const inferResponse = await fetch(`infer_t5?input=${text}`);
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+ const inferJson = await inferResponse.json();
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+ return inferJson.output;
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  };
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+ textGenForm.addEventListener('submit', async (event) => {
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  event.preventDefault();
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+ const textGenInput = document.getElementById('text-gen-input');
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+ const textGenParagraph = document.querySelector('.text-gen-output');
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+ try {
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+ textGenParagraph.textContent = await translateText(textGenInput.value);
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+ } catch (err) {
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+ console.error(err);
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+ }
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  });