app.py

import gradio as gr
import random
import time

from utils import load_model_util, load_corpus_util, build_index_util, search_util


model = None
corpus = None
faiss_index = None
data_dir = '/share/chaofan/code/bge_demo/data'
index_dir = '/share/chaofan/code/bge_demo/emb'
lang = 'en'
avaliable_queries = []

# Simulate loading a model
def load_model(model_name):
    global model
    """
    Function to load a model and provide status updates with a custom loading type.
    """
    # 定义 HTML 样式
    loading_style = "<span style='color:#ffc107; font-weight:bold'>⏳</span>"  # 自定义加载中图标
    success_style = "<span style='color:#28a745; font-weight:bold'>✔</span>"  # 成功图标
    error_style = "<span style='color:#dc3545; font-weight:bold'>✗</span>"   # 错误图标
    
    try:
        yield f"{loading_style} Loading model <b>{model_name}</b>..."
        model = load_model_util(model, model_name)
        yield f"{success_style} Model <b>{model_name}</b> has been successfully loaded!"
    except Exception as e:
        yield f"{error_style} Failed to load model <b>{model_name}</b>: {str(e)}"

# Simulate selecting a language
def choose_language(language):
    global lang
    lang = language
    language_full = {
        "zh": "Chinese",
        "en": "English",
        "ar": "Arabic",
        "bn": "Bengali",
        "es": "Spanish",
        "fa": "Persian",
        "fi": "Finnish",
        "fr": "French",
        "hi": "Hindi",
        "id": "Indonesian",
        "ja": "Japanese",
        "ko": "Korean",
        "ru": "Russian",
        "sw": "Swahili",
        "te": "Telugu",
        "th": "Thai",
        "de": "German",
        "yo": "Yoruba"
    }.get(language, language)
    return f"<span style='color:#0d6efd; font-weight:bold'>⚡</span> Current Language: <b>{language_full}</b> ({language})"

# Simulate loading a corpus
def load_corpus(language):
    global data_dir, corpus, avaliable_queries
    # Initial loading status
    corpus_name = f"miracl.{language}"
    yield f"""<span style='color:#ffc107; font-weight:bold'>⏳</span> Loading corpus <b>{corpus_name}</b> ..."""
    # Simulate loading process
    print(f"Loading corpus: {corpus_name}")
    corpus, avaliable_queries = load_corpus_util(data_dir, language)

    yield f"""<span style='color:#28a745; font-weight:bold'>✔</span> Corpus <b>{corpus_name}</b> has been successfully loaded!"""

def update_query_input(value):
    global avaliable_queries

    return gr.Dropdown(
        label="Search Query",
        choices=avaliable_queries,  # 预定义的选项
        value="",  # 默认值
        allow_custom_value=True,  # 允许用户输入自定义值
        # placeholder="Select or enter search keywords..."
    )

# Simulate building an index
def build_index(language):
    # Simulate progressive building process
    global model, corpus, index_dir, faiss_index, lang

    # 定义 HTML 样式
    loading_style = "<span style='color:#ffc107; font-weight:bold'>⏳</span>"  # 自定义加载中图标
    success_style = "<span style='color:#28a745; font-weight:bold'>✔</span>"  # 成功图标
    error_style = "<span style='color:#dc3545; font-weight:bold'>✗</span>"   # 错误图标

    if model is None:
        yield f"{error_style} You need to load the model before building index!"
    elif corpus is None:
        yield f"{error_style} You need to load the corpus before building index!"
    else:
        try:
            yield f"{loading_style} Building index..."
            faiss_index = build_index_util(index_dir, lang, model, corpus)
            yield f"{success_style} Index building complete!"
        except Exception as e:
            yield f"{error_style} Failed to build index: {str(e)}"

# Simulate retrieving results
def retrieve_results(query, language, top_k):
    global model, corpus, faiss_index

    yield f"""<div style='background:#f8f9fa; padding:10px; border-left:4px solid #17a2b8; border-radius:4px'>
    <span style='color:orange'>⏳ Start to search ...</span>
    </div>"""

    error_style = "<span style='color:#dc3545; font-weight:bold'>✗</span>"   # 错误图标

    try:
        scores, data = search_util(model, query, corpus, faiss_index, top_k)
        # print(scores)
        # print(data)
        # Generate random results
        results = []
        for score, d in zip(scores, data):
            doc_id = d['id']
            title = d['title']
            content = d['text']
            results.append((float(score), doc_id, title, content))
        
        # # Sort by score
        # results.sort(reverse=True)
        
        # Generate HTML display
        html_result = f"""<div style='background:#f8f9fa; padding:15px; border-radius:8px'>
        <h3>Search Results: <span style='color:#0d6efd'>{top_k}</span> items</h3>
        <p>Query: <b>"{query}"</b> | Language: <b>{language}</b></p>
        <div style='margin-top:15px'>"""
        
        for i, (score, doc_id, title, content) in enumerate(results):
            # Set gradient color
            color = f"hsl({min(120, int(score*120))}, 80%, 40%)"
            html_result += f"""<div style='margin-bottom:5px; padding:10px; border-left:4px solid {color}; background:white; border-radius:4px'>
            <div style='display:flex; justify-content:space-between'>
                <span style='font-weight:bold'>Result {i+1}</span>
            </div>
            <div style='color:#666; font-size:1.0em'>Title: {title}</div>
            <div style='margin-top:5px'>{content}</div>
            </div>"""
        
        html_result += "</div></div>"
        yield html_result
    except Exception as e:
        yield f"{error_style} Failed to build index: {str(e)}"

# Custom CSS
custom_css = """
.main-header {
    background: linear-gradient(135deg, #6964DE, #FCA6E9);
    color: white;
    padding: 20px;
    border-radius: 10px;
    margin-bottom: 20px;
    text-align: center;
}
.step-header {
    color: #333;
    margin-top: 5px;
    margin-bottom: 10px;
    font-weight: bold;
    display: flex;
    align-items: center;
    justify-content: center;
}
.step-header span {
    background: #6964DE;
    color: white;
    width: 28px;
    height: 28px;
    border-radius: 50%;
    display: inline-flex;
    align-items: center;
    justify-content: center;
    margin-right: 10px;
}
.step-card {
    background: white;
    border-radius: 10px;
    padding: 15px;
    margin-bottom: 15px;
    box-shadow: 0 4px 6px rgba(0,0,0,0.05);
    text-align: center;
}
button {
    background-color: #0d6efd !important;
    color: white !important;
    border: none !important;
    padding: 5px 15px !important; /* Adjust button size */
    border-radius: 5px !important;
    font-size: 0.9em !important; /* Adjust font size */
    cursor: pointer !important;
}
button:hover {
    background-color: #0056b3 !important;
}
.row {
    display: flex;
    align-items: center;
    justify-content: space-between;
    gap: 10px; /* Control spacing between components */
}
footer {visibility: hidden}
"""

# Define Gradio interface
with gr.Blocks(css=custom_css) as interface:
    # Top header
    gr.HTML("""
    <div class="main-header">
        <h1 style="margin:0; font-size:2.5em;">🔎 Multilingual Retrieval System</h1>
    </div>
    """)

    with gr.Row(elem_classes="row"):  # Use Row to place components in the same row

        # Step 1: Load model
        with gr.Group(elem_classes="step-card"):
            gr.HTML('<div class="step-header"><span>1</span>Load Model</div>')
            model_name = gr.Textbox(value="BAAI/bge-multilingual-gemma2", label="Model Name", interactive=True)
            load_model_button = gr.Button("Load Model")
            model_status = gr.HTML(label="Status")
            load_model_button.click(load_model, inputs=[model_name], outputs=[model_status])
    
        # Step 2: Select language
        with gr.Group(elem_classes="step-card"):
            gr.HTML('<div class="step-header"><span>2</span>Select Language</div>')
            language_input = gr.Dropdown(choices=['en', 'zh', 'ar', 'bn', 'es', 'fa', 'fi', 'fr', 'hi', 'id', 'ja', 'ko', 'ru', 'sw', 'te', 'th', 'de', 'yo'], value="en", label="Select Language", interactive=True)
            choose_language_button = gr.Button("Confirm Language")  # Button in the same row
            language_status = gr.HTML(label="Current Language")
            choose_language_button.click(choose_language, inputs=[language_input], outputs=[language_status])
    
    with gr.Row(elem_classes="row"):  # Use Row to place components in the same row

        # Step 3: Load corpus
        with gr.Group(elem_classes="step-card"):
            gr.HTML('<div class="step-header"><span>3</span>Load Corpus</div>')
            load_corpus_button = gr.Button("Load Corpus", scale=1)
            corpus_status = gr.HTML(label="Corpus Information")
        
        # Step 4: Build index
        with gr.Group(elem_classes="step-card"):
            gr.HTML('<div class="step-header"><span>4</span>Build Corpus Index</div>')
            build_index_button = gr.Button("Build Index", scale=1)
            index_status = gr.HTML(label="Index Status")
            build_index_button.click(build_index, inputs=[language_input], outputs=[index_status])
    
    # Step 5: Retrieve results
    with gr.Group(elem_classes="step-card"):
        gr.HTML('<div class="step-header"><span>5</span>Retrieve Results</div>')
        # query_input = gr.Textbox(label="Search Query", placeholder="Enter search keywords...")
        query_input = gr.Dropdown(
            label="Search Query",
            choices=avaliable_queries,  # 预定义的选项
            value="",  # 默认值
            allow_custom_value=True,  # 允许用户输入自定义值
            # placeholder="Select or enter search keywords..."
        )
        load_corpus_button.click(load_corpus, inputs=[language_input], outputs=[corpus_status]).then(update_query_input,  inputs=[query_input], outputs=[query_input]) # 因为要让选项变化
        top_k = gr.Slider(minimum=1, maximum=30, step=1, value=10, label="Number of Results (Top-K)")
        retrieve_button = gr.Button("Start Search")
        retrieval_results = gr.HTML(label="Search Results")
        retrieve_button.click(retrieve_results, inputs=[query_input, language_input, top_k], outputs=[retrieval_results])

# Launch the interface
interface.launch(share=True)