| from typing import List, NewType, Optional, Union |
|
|
| import gradio as gr |
|
|
| from spacerini_utils.index import fetch_index_stats |
| from spacerini_utils.search import _search, init_searcher, SearchResult |
|
|
| HTML = NewType('HTML', str) |
|
|
| searcher = init_searcher(sparse_index_path="sparse_index") |
|
|
| def get_docid_html(docid: Union[int, str]) -> HTML: |
| docid_html = ( |
| f"<a " |
| f'class="underline-on-hover"' |
| 'title="This dataset is licensed apache-2.0"' |
| f'style="color:#2D31FA;"' |
| 'href="https://huggingface.co/datasets/🚀"' |
| 'target="_blank"><b>🔒xsum</b></a><span style="color: #7978FF;">/'+f'{docid}</span>' |
| ) |
|
|
| return docid_html |
|
|
|
|
| def process_results(results: List[SearchResult], language: str, highlight_terms: Optional[List[str]] = None) -> HTML: |
| if len(results) == 0: |
| return """<br><p style='font-family: Arial; color:Silver; text-align: center;'> |
| No results retrieved.</p><br><hr>""" |
|
|
| results_html = "" |
| for result in results: |
| tokens = result["text"].split() |
|
|
| tokens_html = [] |
| if highlight_terms: |
| for token in tokens: |
| if token in highlight_terms: |
| tokens_html.append("<b>{}</b>".format(token)) |
| else: |
| tokens_html.append(token) |
|
|
| tokens_html = " ".join(tokens_html) |
| meta_html = ( |
| """ |
| <p class='underline-on-hover' style='font-size:12px; font-family: Arial; color:#585858; text-align: left;'> |
| """ |
| ) |
| docid_html = get_docid_html(result["docid"]) |
| results_html += """{} |
| <p style='font-size:20px; font-family: Arial; color:#7978FF; text-align: left;'>Document ID: {}</p> |
| <p style='font-size:14px; font-family: Arial; color:#7978FF; text-align: left;'>Score: {}</p> |
| <p style='font-size:12px; font-family: Arial; color:MediumAquaMarine'>Language: {}</p> |
| <p style='font-family: Arial;font-size:15px;'>{}</p> |
| <br> |
| """.format( |
| meta_html, docid_html, result["score"], language, tokens_html |
| ) |
| return results_html + "<hr>" |
|
|
|
|
| def search(query: str, language: str, num_results: int = 10) -> HTML: |
| results_dict = _search(searcher, query, num_results=num_results) |
| return process_results(results_dict, language) |
|
|
|
|
| stats = fetch_index_stats('sparse_index/') |
|
|
| description = f"""# <h2 style="text-align: center;"> 🚀 🔎 None 🔍 🚀 </h2> |
| <p style="text-align: center;font-size:15px;">None</p> |
| <p style="text-align: center;font-size:20px;">Dataset Statistics: Total Number of Documents = <b>{stats["documents"]}</b>, Number of Terms = <b>{stats["total_terms"]}</b> </p>""" |
|
|
| demo = gr.Blocks( |
| css=".underline-on-hover:hover { text-decoration: underline; } .flagging { font-size:12px; color:Silver; }" |
| ) |
|
|
| with demo: |
| with gr.Row(): |
| gr.Markdown(value=description) |
| with gr.Row(): |
| query = gr.Textbox(lines=1, max_lines=1, placeholder="Type your query here...", label="Query") |
| with gr.Row(): |
| lang = gr.Dropdown( |
| choices=[ |
| "en", |
| "detect_language", |
| "all", |
| ], |
| value="en", |
| label="Language", |
| ) |
| with gr.Row(): |
| k = gr.Slider(1, 100, value=10, step=1, label="Max Results") |
| with gr.Row(): |
| submit_btn = gr.Button("Submit") |
| with gr.Row(): |
| results = gr.HTML(label="Results") |
|
|
|
|
| def submit(query: str, lang: str, k: int): |
| query = query.strip() |
| if query is None or query == "": |
| return "", "" |
| return { |
| results: search(query, lang, k), |
| } |
|
|
| query.submit(fn=submit, inputs=[query, lang, k], outputs=[results]) |
| submit_btn.click(submit, inputs=[query, lang, k], outputs=[results]) |
|
|
| demo.launch(enable_queue=True, debug=True) |
|
|
