Delete demo.py

demo.py

@@ -1,159 +0,0 @@
-import gradio as gr
-from relative_tester import relative_tester
-# from two_sample_tester import two_sample_tester
-from utils import init_random_seeds
-
-init_random_seeds()
-
-
-def run_test(input_text):
-    if not input_text:
-        return "Now that you've built a demo, you'll probably want to share it with others. Gradio demos can be shared in two ways: using a temporary share link or permanent hosting on Spaces."
-    # return two_sample_tester.test(input_text.strip())
-    return relative_tester.test(input_text.strip())
-    return f"Prediction: Human (Mocked for {input_text})"
-
-# TODO: Add model selection in the future
-# Change mode name
-# def change_mode(mode):
-#    if mode == "Faster Model":
-#        .change_mode("t5-small")
-#    elif mode == "Medium Model":
-#        .change_mode("roberta-base-openai-detector")
-#    elif mode == "Powerful Model":
-#        .change_mode("falcon-rw-1b")
-#    else:
-#        gr.Error(f"Invaild mode selected.")
-#    return mode
-
-
-css = """
-#header { text-align: center; font-size: 3em; margin-bottom: 20px; }
-#output-text { font-weight: bold; font-size: 1.2em; }
-.links {
-    display: flex;
-    justify-content: flex-end;
-    gap: 10px;
-    margin-right: 10px;
-    align-items: center;
-}
-.separator {
-    margin: 0 5px;
-    color: black;
-}
-
-/* Adjusting layout for Input Text and Inference Result */
-.input-row {
-    display: flex;
-    width: 100%;
-}
-
-.input-text {
-    flex: 3;  /* 4 parts of the row */
-    margin-right: 1px;
-}
-
-.output-text {
-    flex: 1;  /* 1 part of the row */
-}
-
-/* Set button widths to match the Select Model width */
-.button {
-    width: 250px;  /* Same as the select box width */
-    height: 100px;  /* Button height */
-}
-
-/* Set height for the Select Model dropdown */
-.select {
-    height: 100px;  /* Set height to 100px */
-}
-
-/* Accordion Styling */
-.accordion {
-    width: 100%;  /* Set the width of the accordion to match the parent */
-    max-height: 200px;  /* Set a max-height for accordion */
-    overflow-y: auto;  /* Allow scrolling if the content exceeds max height */
-    margin-bottom: 10px;  /* Add space below accordion */
-    box-sizing: border-box;  /* Ensure padding is included in width/height */
-}
-
-/* Accordion content max-height */
-.accordion-content {
-    max-height: 200px;  /* Limit the height of the content */
-    overflow-y: auto;  /* Add a scrollbar if content overflows */
-}
-"""
-
-# Gradio App
-with gr.Blocks(css=css) as app:
-    with gr.Row():
-        gr.HTML('<div id="header">R-detect On HuggingFace</div>')
-    with gr.Row():
-        gr.HTML(
-            """
-        <div class="links">
-            <a href="https://openreview.net/forum?id=z9j7wctoGV" target="_blank">Paper</a>
-            <span class="separator">|</span>
-            <a href="https://github.com/xLearn-AU/R-Detect" target="_blank">Code</a>
-            <span class="separator">|</span>
-            <a href="mailto:[email protected]" target="_blank">Contact</a>
-        </div>
-        """
-        )
-    with gr.Row():
-        input_text = gr.Textbox(
-            label="Input Text",
-            placeholder="Enter Text Here",
-            lines=8,
-            elem_classes=["input-text"],  # Applying the CSS class
-        )
-        output = gr.Textbox(
-            label="Inference Result",
-            placeholder="Made by Human or AI",
-            elem_id="output-text",
-            lines=8,
-            elem_classes=["output-text"],
-        )
-    with gr.Row():
-        # TODO: Add model selection in the future
-        # model_name = gr.Dropdown(
-        #     [
-        #         "Faster Model",
-        #         "Medium Model",
-        #         "Powerful Model",
-        #     ],
-        #     label="Select Model",
-        #     value="Medium Model",
-        #     elem_classes=["select"],
-        # )
-        submit_button = gr.Button(
-            "Run Detection", variant="primary", elem_classes=["button"]
-        )
-        clear_button = gr.Button("Clear", variant="secondary", elem_classes=["button"])
-
-    submit_button.click(run_test, inputs=[input_text], outputs=output)
-    clear_button.click(lambda: ("", ""), inputs=[], outputs=[input_text, output])
-
-    with gr.Accordion("Disclaimer", open=False, elem_classes=["accordion"]):
-        gr.Markdown(
-            """
-        - **Disclaimer**: This tool is for demonstration purposes only. It is not a foolproof AI detector.
-        - **Accuracy**: Results may vary based on input length and quality.
-        """
-        )
-
-    with gr.Accordion("Citations", open=False, elem_classes=["accordion"]):
-        gr.Markdown(
-            """
-        ```
-        @inproceedings{zhangs2024MMDMP,
-            title={Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy},
-            author={Zhang, Shuhai and Song, Yiliao and Yang, Jiahao and Li, Yuanqing and Han, Bo and Tan, Mingkui},
-            booktitle = {International Conference on Learning Representations (ICLR)},
-            year={2024}
-        }
-        ```
-        """
-        )
-
-app.launch()