app.py

import gradio as gr
from transformers import pipeline

# Available models for zero-shot classification
AVAILABLE_MODELS = [
    "mjwong/multilingual-e5-large-instruct-xnli-anli",
    "mjwong/multilingual-e5-base-xnli-anli",
    "mjwong/multilingual-e5-large-xnli-anli",
    "mjwong/mcontriever-msmarco-xnli",
    "mjwong/mcontriever-xnli"
]

def classify_text(model_name, text, labels):
    classifier = pipeline("zero-shot-classification", model=model_name)
    labels_list = [label.strip() for label in labels.split(",")]
    result = classifier(text, candidate_labels=labels_list)
    return {label: score for label, score in zip(result["labels"], result["scores"])}

# Example Input
examples = [
    [
        "The government announced a new economic policy today aimed at reducing inflation and stabilizing the currency market.", 
        "economy, politics, finance, policy, inflation, government, currency"
    ],
    [
        "中国的科技公司在人工智能领域取得了重大突破，这可能会影响全球市场。", 
        "科技, 经济, 创新, 市场, 人工智能, 全球"
    ],
    [
        "นักวิจัยค้นพบวิธีใหม่ในการรักษาโรคมะเร็ง ซึ่งอาจช่วยชีวิตผู้ป่วยหลายล้านคนทั่วโลก", 
        "การแพทย์, วิทยาศาสตร์, นวัตกรรม, สุขภาพ, โรคมะเร็ง, การรักษา"
    ],
    [
        "La conférence des Nations Unies sur le climat a abouti à un nouvel accord pour réduire les émissions de carbone d'ici 2030.", 
        "environnement, climat, politique, énergie, carbone, écologie, ONU"
    ],
    [
        "सरकार ने आज एक नई आर्थिक नीति की घोषणा की, जिसका उद्देश्य मुद्रास्फीति को कम करना और मुद्रा बाजार को स्थिर करना है।", 
        "अर्थव्यवस्था, राजनीति, वित्त, नीति, मुद्रास्फीति, सरकार, मुद्रा"
    ]
]

# Define the Gradio interface
css = """
footer {display:none !important}
.output-markdown{display:none !important}
.gr-button-primary {
    z-index: 14;
    height: 43px;
    width: 130px;
    left: 0px;
    top: 0px;
    padding: 0px;
    cursor: pointer !important; 
    background: none rgb(17, 20, 45) !important;
    border: none !important;
    text-align: center !important;
    font-family: Poppins !important;
    font-size: 14px !important;
    font-weight: 500 !important;
    color: rgb(255, 255, 255) !important;
    line-height: 1 !important;
    border-radius: 12px !important;
    transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
    box-shadow: none !important;
}
.gr-button-primary:hover{
    background: none rgb(66, 133, 244) !important;
    box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;
}
"""

with gr.Blocks(css=css) as iface:
    gr.Markdown("# Zero-Shot Text Classifier")
    gr.Markdown("Select a model, enter text, and a set of labels to classify it using a zero-shot classification model.")
    
    model_dropdown = gr.Dropdown(AVAILABLE_MODELS, label="Choose Model")
    
    with gr.Row():
        text_input = gr.Textbox(label="Enter Text", placeholder="Type or paste text here...")
        label_input = gr.Textbox(label="Enter Labels (comma-separated)", placeholder="e.g., sports, politics, technology")
    
    output_label = gr.Label(label="Classification Scores")
    
    submit_button = gr.Button("Classify")
    submit_button.click(fn=classify_text, inputs=[model_dropdown, text_input, label_input], outputs=output_label)
    
    gr.Examples(examples, inputs=[text_input, label_input])

# Launch the app
if __name__ == "__main__":
    iface.launch()