app.py

import streamlit as st
from st_utils import bm25_search, semantic_search, hf_api, paginator
from huggingface_hub import ModelSearchArguments
import webbrowser
from numerize.numerize import numerize
import math

st.set_page_config(
    page_title="HF Search Engine",
    page_icon="🔎",
    layout="wide",
    initial_sidebar_state="auto",
)

### SIDEBAR
search_backend = st.sidebar.selectbox(
    "Search method",
    ["semantic", "bm25", "hfapi"],
    format_func=lambda x: {"hfapi": "Keyword search", "bm25": "BM25 search", "semantic": "Semantic Search"}[x],
)
limit_results = int(st.sidebar.number_input("Limit results", min_value=0, value=10))

st.sidebar.markdown("# Filters")
args = ModelSearchArguments()
library = st.sidebar.multiselect(
    "Library", args.library.values(), format_func=lambda x: {v: k for k, v in args.library.items()}[x]
)
task = st.sidebar.multiselect(
    "Task", args.pipeline_tag.values(), format_func=lambda x: {v: k for k, v in args.pipeline_tag.items()}[x]
)

### MAIN PAGE
st.markdown(
    "<h1 style='text-align: center; '>🔎🤗 HF Search Engine</h1>",
    unsafe_allow_html=True,
)

# Search bar
search_query = st.text_input("Search for a model in HuggingFace", value="", max_chars=None, key=None, type="default")

if search_query != "":
    filters = {
        "library": library,
        "task": task,
    }
    if search_backend == "hfapi":
        res = hf_api(search_query, limit_results, filters)
    elif search_backend == "semantic":
        res = semantic_search(search_query, limit_results, filters)
    elif search_backend == "bm25":
        res = bm25_search(search_query, limit_results, filters)
    hit_list, hits_count = res["hits"], res["count"]
    hit_list = [
        {
            "modelId": hit["modelId"],
            "tags": hit["tags"],
            "downloads": hit["downloads"],
            "likes": hit["likes"],
            "readme": hit.get("readme", None),
        }
        for hit in hit_list
    ]

    if hit_list:
        st.write(f"Search results ({hits_count}):")

        if hits_count > 100:
            shown_results = 100
        else:
            shown_results = hits_count

        for i, hit in paginator(
            f"Select results (showing {shown_results} of {hits_count} results)",
            hit_list,
        ):
            col1, col2, col3 = st.columns([5, 1, 1])
            col1.metric("Model", hit["modelId"])
            col2.metric("N° downloads", numerize(hit["downloads"]) if not math.isnan(hit["downloads"]) else "N/A")
            col3.metric("N° likes", numerize(hit["likes"]) if not math.isnan(hit["likes"]) else "N/A")
            st.button(
                f"View model on 🤗",
                on_click=lambda hit=hit: webbrowser.open(f"https://huggingface.co/{hit['modelId']}"),
                key=f"{i}-{hit['modelId']}",
            )
            st.write(f"**Tags:** {'&nbsp;&nbsp;•&nbsp;&nbsp;'.join(hit['tags'])}")

            if hit["readme"]:
                with st.expander("See README"):
                    st.write(hit["readme"])

            # TODO: embed huggingface spaces
            #                 import streamlit.components.v1 as components
            #                 components.html(
            #     f"""
            #     <link rel="stylesheet" href="https://gradio.s3-us-west-2.amazonaws.com/2.6.2/static/bundle.css">
            # <div id="target"></div>
            # <script src="https://gradio.s3-us-west-2.amazonaws.com/2.6.2/static/bundle.js"></script>
            # <script>
            # launchGradioFromSpaces("abidlabs/question-answering", "#target")
            # </script>
            #     """,
            #     height=400,
            # )

            st.markdown("---")

    else:
        st.write(f"No Search results, please try again with different keywords")

st.markdown(
    "<h6 style='text-align: center; color: #808080;'>Made with ❤️ By <a href='https://github.com/NouamaneTazi'>Nouamane</a> - Checkout complete project <a href='https://github.com/NouamaneTazi/hf_search'>here</a></h6>",
    unsafe_allow_html=True,
)