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| import logging | |
| import requests | |
| import streamlit as st | |
| from core.constants import OAUTH_CLIENT_ID | |
| from core.past_projects import save_current_project | |
| from core.path import get_resource_path | |
| from core.query_params import set_project | |
| from core.state import CurrentProject | |
| from core.state import Metadata | |
| import mlcroissant as mlc | |
| from views.load import render_load | |
| from views.previous_files import render_previous_files | |
| _DATASETS = { | |
| "Titanic": ["data/embarkation_ports.csv", "data/genders.csv"], | |
| "FLORES-200": [], | |
| "GPT-3": [], | |
| "COCO2014": [], | |
| "PASS": [], | |
| "MovieLens": [], | |
| "Bigcode-The-Stack": [], | |
| } | |
| def render_splash(): | |
| if OAUTH_CLIENT_ID: | |
| st.info( | |
| "**Disclaimer**: Do not put sensitive information or datasets here. The" | |
| " storage on Hugging Face Spaces is ephemeral. If you want to host your own" | |
| " version locally, build the app from [the GitHub" | |
| " repository](https://github.com/mlcommons/croissant/tree/main/editor)." | |
| ) | |
| col1, col2 = st.columns([1, 1], gap="large") | |
| with col1: | |
| with st.expander("**Load an existing Croissant JSON-LD file**", expanded=True): | |
| render_load() | |
| with st.expander("**Create from scratch**", expanded=True): | |
| def create_new_croissant(): | |
| st.session_state[Metadata] = Metadata() | |
| save_current_project() | |
| st.button( | |
| "Create", | |
| on_click=create_new_croissant, | |
| type="primary", | |
| ) | |
| with st.expander("**Try out an example!**", expanded=True): | |
| def create_example(dataset: str): | |
| base = f"https://raw.githubusercontent.com/mlcommons/croissant/main/datasets/{dataset.lower()}" | |
| url = f"{base}/metadata.json" | |
| try: | |
| json = requests.get(url).json() | |
| metadata = mlc.Metadata.from_json(mlc.Issues(), json, None) | |
| st.session_state[Metadata] = Metadata.from_canonical(metadata) | |
| save_current_project() | |
| # Write supplementary files. | |
| files = _DATASETS.get(dataset, []) | |
| for file in files: | |
| path = get_resource_path(file) | |
| json = requests.get(f"{base}/{file}") | |
| path.write_bytes(json.content) | |
| except Exception as exception: | |
| logging.error(exception) | |
| st.error( | |
| "Sorry, it seems that the example is broken... Can you please" | |
| " [open an issue on" | |
| " GitHub](https://github.com/mlcommons/croissant/issues/new)?" | |
| ) | |
| dataset = st.selectbox( | |
| label="Dataset", | |
| options=_DATASETS.keys(), | |
| ) | |
| st.button( | |
| f"{dataset} dataset", | |
| on_click=create_example, | |
| type="primary", | |
| args=(dataset,), | |
| ) | |
| with col2: | |
| with st.expander("**Past projects**", expanded=True): | |
| render_previous_files() | |