import gradio as gr from huggingface_hub import HfApi import duckdb from datasets import load_dataset import pandas as pd custom_css=""" * { animation: gow 3s 1 forwards; } @keyframes gow { from { transform: scale(0.1); } to { transform: scale(1.0); } } """ head_js=""" """ api = HfApi() datasets=api.list_datasets(filter="task_categories:text-generation",language="en",gated=False,limit=100) outf='./output.csv' lst=[] def looky(value): datasets=api.list_datasets(search=f"{value}",language="en",gated=False,limit=100) return gr.CheckboxGroup([d.id for d in datasets], label="Select Datasets") def preview(selected): lst=[] for selecd in selected: datum=load_dataset(selecd, split='train', streaming=True).take(3) lst.extend(datum) fd=pd.DataFrame(lst) return gr.Dataframe(headers=["Dataset", "Sample"], value=fd) def build_dataset(selected_datasets, num_samples): outf='./output.csv' con = duckdb.connect(database=':memory:') combined_data = [] for dataset in selected_datasets: data = load_dataset(dataset, split='train', streaming=True).take(num_samples) combined_data.extend(data) df = pd.DataFrame(combined_data) con.execute("CREATE TABLE dataset AS SELECT * FROM df") result = con.execute("SELECT * FROM dataset").fetchall() con.execute("COPY (SELECT * FROM dataset) TO 'output.csv' (HEADER, DELIMITER ',');") return result,outf with gr.Blocks(head=head_js,css=custom_css) as iface: frst_sample=gr.Dataframe(value=None,label="View 3 Samples per selected dataset") srchbx=gr.Textbox(label="Search datasets",placeholder="Search Datasets on the Hub. Type query..hit Enter.. this will update the dataset list below..") with gr.Accordion("Multi-Select Datasets", open=False,): with gr.Row(): dataset_selector = gr.CheckboxGroup([d.id for d in datasets], label="Multi-Select Datasets") num_samples_input = gr.Number(value=10, label="Number of Samples to retrieve per Dataset") build_button = gr.Button("Build Dataset") out_way = gr.File() output_display = gr.Dataframe(headers=["Dataset", "Sample"]) build_button.click(fn=build_dataset,inputs=[dataset_selector, num_samples_input],outputs=[output_display,out_way]) dataset_selector.change(preview,dataset_selector,frst_sample) srchbx.change(looky,srchbx,dataset_selector) iface.load(None,None,None,js="""() =>{var colr = 'rgba('+Math.floor(Math.random() * 256)+','+Math.floor(Math.random() * 256)+','+Math.floor(Math.random() * 256)+','+(Math.random() * 1)+')'; document.querySelectorAll('*').forEach(item =>{ item.style.backgroundColor=colr; }); var tin = document.getElementById('moish'); var parents=[]; function getAllParentNodes(element) {while (element.parentNode) {element = element.parentNode; element.style.background = bkd; parents.push(element); }; }; getAllParentNodes(tin); document.getElementById('moish').innerHTML += parents; var tiguf=document.getElementById('toish');var javas=document.createElement('canvas');javas.setAttribute('id', 'javas');javas.width = '100%';javas.height = '100%';javas.style.top = '0';javas.style.left = '0';tiguf.appendChild(javas);const ctx = javas.getContext('2d');const svgs = [];const img = new Image();var fish = () => {fetch('https://huggingface.co/front/assets/huggingface_logo-noborder.svg').then(resp => resp.blob()).then(blob => URL.createObjectURL(blob));}; img.src = fish;function createSVG(x, y, size) {return { x, y, size, dx: Math.random() * 4 - 2, dy: Math.random() * 4 - 2 };};for (let i = 0; i < 10; i++) {svgs.push(createSVG(Math.random() * javas.width, Math.random() * javas.height, Math.random() * 30 + 10));};function animate() {ctx.clearRect(0, 0, javas.width, javas.height);svgs.forEach(svg => {svg.x += svg.dx; svg.y += svg.dy;if (svg.x < 0 || svg.x > javas.width - svg.size) svg.dx *= -1;if (svg.y < 0 || svg.y > javas.height - svg.size) svg.dy *= -1;ctx.drawImage(img, svg.x, svg.y, svg.size, svg.size);});requestAnimationFrame(animate);}; let counter = 0;const incrementCounter = () => {while (counter < 100) {animate();counter++;} };incrementCounter();}""",) iface.launch(debug=True)