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| import random | |
| import urllib.parse | |
| from http import client | |
| import argilla as rg | |
| import requests | |
| from jinja2 import Template | |
| def generate_html(image_urls, app_url): | |
| """none""" | |
| template_str = """ | |
| <html> | |
| <body> | |
| <iframe src="{{ full_url }}" width="400" height="400" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> | |
| </body> | |
| </html> | |
| """ | |
| base_url = f"{app_url}/?" | |
| encoded_urls = [ | |
| "img{}={}".format(i + 1, urllib.parse.quote(url, safe="")) | |
| for i, url in enumerate(image_urls) | |
| ] | |
| full_url = base_url + "&".join(encoded_urls) | |
| template = Template(template_str) | |
| return template.render(full_url=full_url) | |
| def fetch_data(max_images, name="horse"): | |
| base_url = "https://datasets-server.huggingface.co/rows" | |
| params = { | |
| "dataset": "gigant/horse2zebra", | |
| "config": name, | |
| "split": "train", | |
| "offset": 0, | |
| "length": max_images, | |
| } | |
| response = requests.get(base_url, params=params) | |
| if response.status_code == 200: | |
| data = response.json() | |
| return [row["row"]["image"]["src"] for row in data["rows"]] | |
| else: | |
| print(f"Failed to fetch data. Status code: {response.status_code}") | |
| return None | |
| def log_records(dataset, app_url, max_images=10): | |
| horse_urls = fetch_data(max_images=max_images, name="horse") | |
| zebra_urls = fetch_data(max_images=max_images, name="zebra") | |
| records = [] | |
| for horse_url, zebra_url in zip(horse_urls, zebra_urls): | |
| markdown_str = generate_html(image_urls=[horse_url, zebra_url], app_url=app_url) | |
| record = rg.Record(fields={"gradio_app": markdown_str}) | |
| records.append(record) | |
| dataset.records.log(records) | |
| def create_dataset(api_url="http://localhost:6900", api_key="owner.apikey"): | |
| client = rg.Argilla(api_url=api_url, api_key=api_key) | |
| # Create a dataset | |
| settings = rg.Settings( | |
| fields=[rg.TextField(name="gradio_app")], | |
| questions=[ | |
| rg.LabelQuestion( | |
| name="is_zebra", | |
| description="Is this a zebra?", | |
| labels=["true", "false"], | |
| ) | |
| ], | |
| ) | |
| dataset = rg.Dataset( | |
| name=f"horse2zebra_{random.randint(0,100)}", settings=settings, client=client | |
| ) | |
| dataset.create() | |
| return dataset | |
| if __name__ == "__main__": | |
| dataset = create_dataset(api_url="https://burtenshaw-gradio-field.hf.space") | |
| log_records( | |
| dataset, max_images=10, app_url="https://burtenshaw-gradio-field-app.hf.space" | |
| ) | |