Update app.py

app.py

@@ -1,5 +1,160 @@
-from demo import app
+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()
 
-if __name__ == "__main__":
-    # Launch the Gradio interface
-    app.launch(show_api=False, debug=True, share=True)