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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 = [["One day I will see the world", "travel, live, die, future"]]

# 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{
    z-index: 14;
    height: 43px;
    width: 130px;
    left: 0px;
    top: 0px;
    padding: 0px;
    cursor: pointer !important;
    background: none rgb(66, 133, 244) !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: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;
}
"""

iface = gr.Interface(
    fn=classify_text,
    inputs=[
        gr.Dropdown(AVAILABLE_MODELS, label="Choose Model"),
        gr.Textbox(label="Enter Text", placeholder="Type or paste text here..."),
        gr.Textbox(label="Enter Labels (comma-separated)", placeholder="e.g., sports, politics, technology")
    ],
    outputs=gr.Label(label="Classification Scores"),
    title="Zero-Shot Text Classifier",
    description="Select a model, enter text, and a set of labels to classify it using a zero-shot classification model.",
    examples=examples,
    css=css
)

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