Spaces:
Running
Running
| import json | |
| import os | |
| from dataclasses import asdict | |
| from glob import glob | |
| import datasets | |
| import streamlit as st | |
| import yaml | |
| st.set_page_config( | |
| page_title="HF Dataset Tagging App", | |
| page_icon="https://huggingface.co/front/assets/huggingface_logo.svg", | |
| layout="wide", | |
| initial_sidebar_state="auto", | |
| ) | |
| task_set = json.load(open("task_set.json")) | |
| license_set = json.load(open("license_set.json")) | |
| language_set_restricted = json.load(open("language_set.json")) | |
| language_set = json.load(open("language_set_full.json")) | |
| multilinguality_set = { | |
| "monolingual": "contains a single language", | |
| "multilingual": "contains multiple languages", | |
| "translation": "contains translated or aligned text", | |
| "other": "other type of language distribution", | |
| } | |
| creator_set = { | |
| "language": [ | |
| "found", | |
| "crowdsourced", | |
| "expert-generated", | |
| "machine-generated", | |
| "other", | |
| ], | |
| "annotations": [ | |
| "found", | |
| "crowdsourced", | |
| "expert-generated", | |
| "machine-generated", | |
| "no-annotation", | |
| "other", | |
| ], | |
| } | |
| ######################## | |
| ## Helper functions | |
| ######################## | |
| def load_existing_tags(): | |
| has_tags = {} | |
| for fname in glob("saved_tags/*/*/tags.json"): | |
| _, did, cid, _ = fname.split(os.sep) | |
| has_tags[did] = has_tags.get(did, {}) | |
| has_tags[did][cid] = fname | |
| return has_tags | |
| def new_pre_loaded(): | |
| return { | |
| "task_categories": [], | |
| "task_ids": [], | |
| "multilinguality": [], | |
| "languages": [], | |
| "language_creators": [], | |
| "annotations_creators": [], | |
| "source_datasets": [], | |
| "size_categories": [], | |
| "licenses": [], | |
| } | |
| pre_loaded = new_pre_loaded() | |
| existing_tag_sets = load_existing_tags() | |
| all_dataset_ids = list(existing_tag_sets.keys()) | |
| ######################## | |
| ## Dataset selection | |
| ######################## | |
| st.sidebar.markdown( | |
| """ | |
| # HuggingFace Dataset Tagger | |
| This app aims to make it easier to add structured tags to the datasets present in the library. | |
| Each configuration requires its own tasks, as these often correspond to distinct sub-tasks. However, we provide the opportunity | |
| to pre-load the tag sets from another dataset or configuration to avoid too much redundancy. | |
| The tag sets are saved in JSON format, but you can print a YAML version in the right-most column to copy-paste to the config README.md | |
| ### Preloading an existing tag set | |
| You can load an existing tag set to get started if you want. | |
| Beware that clicking pre-load will overwrite the current state! | |
| """ | |
| ) | |
| qp = st.experimental_get_query_params() | |
| preload = qp.get("preload_dataset", list()) | |
| did_index = 2 | |
| if len(preload) == 1 and preload[0] in all_dataset_ids: | |
| did_qp, *_ = preload | |
| cid_qp = next(iter(existing_tag_sets[did_qp])) | |
| pre_loaded = json.load(open(existing_tag_sets[did_qp][cid_qp])) | |
| did_index = all_dataset_ids.index(did_qp) | |
| did = st.sidebar.selectbox(label="Choose dataset to load tag set from", options=all_dataset_ids, index=did_index) | |
| if len(existing_tag_sets[did]) > 1: | |
| cid = st.sidebar.selectbox( | |
| label="Choose config to load tag set from", | |
| options=list(existing_tag_sets[did].keys()), | |
| index=0, | |
| ) | |
| else: | |
| cid = next(iter(existing_tag_sets[did].keys())) | |
| if st.sidebar.button("pre-load this tag set"): | |
| pre_loaded = json.load(open(existing_tag_sets[did][cid])) | |
| st.experimental_set_query_params(preload_dataset=did) | |
| if st.sidebar.button("flush state"): | |
| pre_loaded = new_pre_loaded() | |
| st.experimental_set_query_params() | |
| leftcol, _, rightcol = st.beta_columns([12, 1, 12]) | |
| pre_loaded["languages"] = list(set(pre_loaded["languages"])) | |
| leftcol.markdown("### Supported tasks") | |
| task_categories = leftcol.multiselect( | |
| "What categories of task does the dataset support?", | |
| options=list(task_set.keys()), | |
| default=pre_loaded["task_categories"], | |
| format_func=lambda tg: f"{tg} : {task_set[tg]['description']}", | |
| ) | |
| task_specifics = [] | |
| for tg in task_categories: | |
| task_specs = leftcol.multiselect( | |
| f"What specific *{tg}* tasks does the dataset support?", | |
| options=task_set[tg]["options"], | |
| default=[ts for ts in pre_loaded["task_ids"] if ts in task_set[tg]["options"]], | |
| ) | |
| if "other" in task_specs: | |
| other_task = st.text_input( | |
| "You selected 'other' task. Please enter a short hyphen-separated description for the task:", | |
| value="my-task-description", | |
| ) | |
| st.write(f"Registering {tg}-other-{other_task} task") | |
| task_specs[task_specs.index("other")] = f"{tg}-other-{other_task}" | |
| task_specifics += task_specs | |
| leftcol.markdown("### Languages") | |
| multilinguality = leftcol.multiselect( | |
| "Does the dataset contain more than one language?", | |
| options=list(multilinguality_set.keys()), | |
| default=pre_loaded["multilinguality"], | |
| format_func=lambda m: f"{m} : {multilinguality_set[m]}", | |
| ) | |
| if "other" in multilinguality: | |
| other_multilinguality = st.text_input( | |
| "You selected 'other' type of multilinguality. Please enter a short hyphen-separated description:", | |
| value="my-multilinguality", | |
| ) | |
| st.write(f"Registering other-{other_multilinguality} multilinguality") | |
| multilinguality[multilinguality.index("other")] = f"other-{other_multilinguality}" | |
| languages = leftcol.multiselect( | |
| "What languages are represented in the dataset?", | |
| options=list(language_set.keys()), | |
| default=pre_loaded["languages"], | |
| format_func=lambda m: f"{m} : {language_set[m]}", | |
| ) | |
| leftcol.markdown("### Dataset creators") | |
| language_creators = leftcol.multiselect( | |
| "Where does the text in the dataset come from?", | |
| options=creator_set["language"], | |
| default=pre_loaded["language_creators"], | |
| ) | |
| annotations_creators = leftcol.multiselect( | |
| "Where do the annotations in the dataset come from?", | |
| options=creator_set["annotations"], | |
| default=pre_loaded["annotations_creators"], | |
| ) | |
| licenses = leftcol.multiselect( | |
| "What licenses is the dataset under?", | |
| options=list(license_set.keys()), | |
| default=pre_loaded["licenses"], | |
| format_func=lambda l: f"{l} : {license_set[l]}", | |
| ) | |
| if "other" in licenses: | |
| other_license = st.text_input( | |
| "You selected 'other' type of license. Please enter a short hyphen-separated description:", | |
| value="my-license", | |
| ) | |
| st.write(f"Registering other-{other_license} license") | |
| licenses[licenses.index("other")] = f"other-{other_license}" | |
| # link ro supported datasets | |
| pre_select_ext_a = [] | |
| if "original" in pre_loaded["source_datasets"]: | |
| pre_select_ext_a += ["original"] | |
| if any([p.startswith("extended") for p in pre_loaded["source_datasets"]]): | |
| pre_select_ext_a += ["extended"] | |
| extended = leftcol.multiselect( | |
| "Does the dataset contain original data and/or was it extended from other datasets?", | |
| options=["original", "extended"], | |
| default=pre_select_ext_a, | |
| ) | |
| source_datasets = ["original"] if "original" in extended else [] | |
| if "extended" in extended: | |
| pre_select_ext_b = [p.split("|")[1] for p in pre_loaded["source_datasets"] if p.startswith("extended")] | |
| extended_sources = leftcol.multiselect( | |
| "Which other datasets does this one use data from?", | |
| options=all_dataset_ids + ["other"], | |
| default=pre_select_ext_b, | |
| ) | |
| if "other" in extended_sources: | |
| other_extended_sources = st.text_input( | |
| "You selected 'other' dataset. Please enter a short hyphen-separated description:", | |
| value="my-dataset", | |
| ) | |
| st.write(f"Registering other-{other_extended_sources} dataset") | |
| extended_sources[extended_sources.index("other")] = f"other-{other_extended_sources}" | |
| source_datasets += [f"extended|{src}" for src in extended_sources] | |
| size_category = leftcol.selectbox( | |
| "What is the size category of the dataset?", | |
| options=["unknown", "n<1K", "1K<n<10K", "10K<n<100K", "100K<n<1M", "n>1M"], | |
| index=["unknown", "n<1K", "1K<n<10K", "10K<n<100K", "100K<n<1M", "n>1M"].index( | |
| (pre_loaded.get("size_categories") or ["unknown"])[0] | |
| ), | |
| ) | |
| ######################## | |
| ## Show results | |
| ######################## | |
| rightcol.markdown( | |
| f""" | |
| ### Finalized tag set | |
| ```yaml | |
| {yaml.dump({ | |
| "task_categories": task_categories, | |
| "task_ids": task_specifics, | |
| "multilinguality": multilinguality, | |
| "languages": languages, | |
| "language_creators": language_creators, | |
| "annotations_creators": annotations_creators, | |
| "source_datasets": source_datasets, | |
| "size_categories": size_category, | |
| "licenses": licenses, | |
| })} | |
| ``` | |
| """ | |
| ) | |