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import spaces
import gradio as gr
from wtpsplit import SaT
import json

# Initialize the SaT model
sat = SaT("sat-12l-sm")
sat.half().to("cuda")

@spaces.GPU(duration=59)
def segment_text(input_text, txt_file):
    results = {}
    
    if input_text:
        # Process single text input
        sentences = sat.split(input_text)
        results["input_text"] = {"segments": sentences}
    elif txt_file is not None:
        # Process txt file
        with open(txt_file.name, 'r', encoding='utf-8') as file:
            for i, line in enumerate(file, 1):
                line = line.strip()
                if line:  # Skip empty lines
                    sentences = sat.split(line)
                    results[f"document_{i}"] = {"segments": sentences}
    
    # Create a JSON object with the results
    json_output = json.dumps(results, indent=2)
    
    return json_output

# Create the Gradio interface
iface = gr.Interface(
    fn=segment_text,
    inputs=[
        gr.Textbox(lines=5, label="Input Text (Optional)"),
        gr.File(label="Upload TXT file (Optional) Row-separated", file_types=[".txt"])
    ],
    outputs=gr.JSON(label="Segmented Text (JSON)"),
    title="Text Segmentation with SaT",
    description="This app uses the SaT (Segment any Text) model to split input text into sentences and return the result as JSON. You can input text directly or upload a TXT file containing multiple documents (one per line). All credits to the respective author(s). Github: https://github.com/segment-any-text/wtpsplit/tree/main",
    examples=[
        ["This is a test This is another test.", None],
        ["Hello this is a test But this is different now Now the next one starts looool", None],
        ["The quick brown fox jumps over the lazy dog It was the best of times, it was the worst of times", None],
    ]
)

# Launch the app
iface.launch()