Delete st_utils.py

st_utils.py

@@ -1,126 +0,0 @@
-import json
-from huggingface_hub import HfApi, ModelFilter, DatasetFilter, ModelSearchArguments
-from pprint import pprint
-from hf_search import HFSearch
-import streamlit as st
-import itertools
-
-from pbr.version import VersionInfo
-print("hf_search version:", VersionInfo('hf_search').version_string())
-
-hf_search = HFSearch(top_k=200)
-
-@st.cache
-def hf_api(query, limit=5, sort=None, filters={}):
-    print("query", query)
-    print("filters", filters)
-    print("limit", limit)
-    print("sort", sort)
-
-    api = HfApi()
-    filt = ModelFilter(
-        task=filters["task"],
-        library=filters["library"],
-    )
-    models = api.list_models(search=query, filter=filt, limit=limit, sort=sort, full=True)
-    hits = []
-    for model in models:
-        model = model.__dict__
-        hits.append(
-            {
-                "modelId": model.get("modelId"),
-                "tags": model.get("tags"),
-                "downloads": model.get("downloads"),
-                "likes": model.get("likes"),
-            }
-        )
-    count = len(hits)
-    if len(hits) > limit:
-        hits = hits[:limit]
-    return {"hits": hits, "count": count}
-
-
-@st.cache
-def semantic_search(query, limit=5, sort=None, filters={}):
-    print("query", query)
-    print("filters", filters)
-    print("limit", limit)
-    print("sort", sort)
-
-    hits = hf_search.search(query=query, method="retrieve & rerank", limit=limit, sort=sort, filters=filters)
-    hits = [
-        {
-            "modelId": hit["modelId"],
-            "tags": hit["tags"],
-            "downloads": hit["downloads"],
-            "likes": hit["likes"],
-            "readme": hit.get("readme", None),
-        }
-        for hit in hits
-    ]
-    return {"hits": hits, "count": len(hits)}
-
-
-@st.cache
-def bm25_search(query, limit=5, sort=None, filters={}):
-    print("query", query)
-    print("filters", filters)
-    print("limit", limit)
-    print("sort", sort)
-
-    # TODO: filters
-    hits = hf_search.search(query=query, method="bm25", limit=limit, sort=sort, filters=filters)
-    hits = [
-        {
-            "modelId": hit["modelId"],
-            "tags": hit["tags"],
-            "downloads": hit["downloads"],
-            "likes": hit["likes"],
-            "readme": hit.get("readme", None),
-        }
-        for hit in hits
-    ]
-    hits = [
-        hits[i] for i in range(len(hits)) if hits[i]["modelId"] not in [h["modelId"] for h in hits[:i]]
-    ]  # unique hits
-    return {"hits": hits, "count": len(hits)}
-
-
-def paginator(label, articles, articles_per_page=10, on_sidebar=True):
-    # https://gist.github.com/treuille/2ce0acb6697f205e44e3e0f576e810b7
-    """Lets the user paginate a set of article.
-    Parameters
-    ----------
-    label : str
-        The label to display over the pagination widget.
-    article : Iterator[Any]
-        The articles to display in the paginator.
-    articles_per_page: int
-        The number of articles to display per page.
-    on_sidebar: bool
-        Whether to display the paginator widget on the sidebar.
-
-    Returns
-    -------
-    Iterator[Tuple[int, Any]]
-        An iterator over *only the article on that page*, including
-        the item's index.
-    """
-
-    # Figure out where to display the paginator
-    if on_sidebar:
-        location = st.sidebar.empty()
-    else:
-        location = st.empty()
-
-    # Display a pagination selectbox in the specified location.
-    articles = list(articles)
-    n_pages = (len(articles) - 1) // articles_per_page + 1
-    page_format_func = lambda i: f"Results {i*10} to {i*10 +10 -1}"
-    page_number = location.selectbox(label, range(n_pages), format_func=page_format_func)
-
-    # Iterate over the articles in the page to let the user display them.
-    min_index = page_number * articles_per_page
-    max_index = min_index + articles_per_page
-
-    return itertools.islice(enumerate(articles), min_index, max_index)