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<html> | |
<head> | |
<meta charset="UTF-8"/> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"/> | |
<script src="https://cdn.tailwindcss.com"></script> | |
<!-- polyfill for firefox + import maps --> | |
<script src="https://unpkg.com/es-module-shims@1.7.0/dist/es-module-shims.js"></script> | |
<script type="importmap"> | |
{ | |
"imports": { | |
"@huggingface/inference": "./index.mjs" | |
} | |
} | |
</script> | |
</head> | |
<body> | |
<form class="w-[90%] mx-auto pt-8" onsubmit="launch(); return false;"> | |
<h1 class="text-3xl font-bold"> | |
<span | |
class="bg-clip-text text-transparent bg-gradient-to-r from-pink-500 to-violet-500" | |
> | |
Document & visual question answering demo with | |
<a href="https://github.com/huggingface/huggingface.js"> | |
<kbd>@huggingface/inference</kbd> | |
</a> | |
</span> | |
</h1> | |
<p class="mt-8"> | |
First, input your token if you have one! Otherwise, you may encounter | |
rate limiting. You can create a token for free at | |
<a | |
target="_blank" | |
href="https://huggingface.co/settings/tokens" | |
class="underline text-blue-500" | |
>hf.co/settings/tokens</a | |
> | |
</p> | |
<input | |
type="text" | |
id="token" | |
class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6" | |
placeholder="token (optional)" | |
/> | |
<p class="mt-8"> | |
Pick the model type and the model you want to run. Check out models for | |
<a | |
href="https://huggingface.co/tasks/document-question-answering" | |
class="underline text-blue-500" | |
target="_blank" | |
> | |
document</a | |
> and | |
<a | |
href="https://huggingface.co/tasks/visual-question-answering" | |
class="underline text-blue-500" | |
target="_blank" | |
>image</a> question answering. | |
</p> | |
<div class="space-x-2 flex text-sm mt-8"> | |
<label> | |
<input class="sr-only peer" name="type" type="radio" value="document" onclick="update_model(this.value)" checked /> | |
<div class="px-3 py-3 rounded-lg shadow-md flex items-center justify-center text-slate-700 bg-gradient-to-r peer-checked:font-semibold peer-checked:from-pink-500 peer-checked:to-violet-500 peer-checked:text-white"> | |
Document | |
</div> | |
</label> | |
<label> | |
<input class="sr-only peer" name="type" type="radio" value="image" onclick="update_model(this.value)" /> | |
<div class="px-3 py-3 rounded-lg shadow-md flex items-center justify-center text-slate-700 bg-gradient-to-r peer-checked:font-semibold peer-checked:from-pink-500 peer-checked:to-violet-500 peer-checked:text-white"> | |
Image | |
</div> | |
</label> | |
</div> | |
<input | |
id="model" | |
class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6" | |
value="impira/layoutlm-document-qa" | |
required | |
/> | |
<p class="mt-8">The input image</p> | |
<input type="file" required accept="image/*" | |
class="rounded border-blue-500 shadow-md px-3 py-2 w-96 mt-6 block" | |
rows="5" | |
id="image" | |
/> | |
<p class="mt-8">The question</p> | |
<input | |
type="text" | |
id="question" | |
class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6" | |
required | |
/> | |
<button | |
id="submit" | |
class="my-8 bg-green-500 rounded py-3 px-5 text-white shadow-md disabled:bg-slate-300" | |
> | |
Run | |
</button> | |
<p class="text-gray-400 text-sm">Output logs</p> | |
<div id="logs" class="bg-gray-100 rounded p-3 mb-8 text-sm"> | |
Output will be here | |
</div> | |
<p>Check out the <a class="underline text-blue-500" | |
href="#" | |
target="_blank">source code</a></p> | |
</form> | |
<script type="module"> | |
import {HfInference} from "@huggingface/inference"; | |
const default_models = { | |
"document": "impira/layoutlm-document-qa", | |
"image": "dandelin/vilt-b32-finetuned-vqa", | |
}; | |
let running = false; | |
async function launch() { | |
if (running) { | |
return; | |
} | |
running = true; | |
try { | |
const hf = new HfInference( | |
document.getElementById("token").value.trim() || undefined | |
); | |
const model = document.getElementById("model").value.trim(); | |
const model_type = document.querySelector("[name=type]:checked").value; | |
const image = document.getElementById("image").files[0]; | |
const question = document.getElementById("question").value.trim(); | |
document.getElementById("logs").textContent = ""; | |
const method = model_type === "document" ? hf.documentQuestionAnswering : hf.visualQuestionAnswering; | |
const {answer, score} = await method({model, inputs: { | |
image, question | |
}}); | |
document.getElementById("logs").textContent = answer + ": " + score; | |
} catch (err) { | |
alert("Error: " + err.message); | |
} finally { | |
running = false; | |
} | |
} | |
window.launch = launch; | |
window.update_model = (model_type) => { | |
const model_input = document.getElementById("model"); | |
const cur_model = model_input.value.trim(); | |
let new_model = ""; | |
if ( | |
model_type === "document" && cur_model === default_models["image"] | |
|| model_type === "image" && cur_model === default_models["document"] | |
|| cur_model === "" | |
) { | |
new_model = default_models[model_type]; | |
} | |
model_input.value = new_model; | |
}; | |
</script> | |
</body> | |
</html> | |