first commit

app.py

@@ -1,7 +1,41 @@
 import gradio as gr
+import pandas as pd
 
-def greet(name):
-    return "Hello " + name + "!!"
+# theme = gr.themes.Monochrome(spacing_size=gr.themes.sizes.spacing_md,
+#                              radius_size=gr.themes.sizes.radius_sm,
+#                              text_size=gr.themes.sizes.text_lg).set(
+#     loader_color="#FF0000",
+#     slider_color="#FF0000"
+# )
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+
+def click_button(model, abstract):
+    labels = {"Classificação 1": 0.75, "Classificação 2": 0.8, "Classificação 3": 0.2}
+    return labels
+
+
+# with gr.Blocks(theme=theme) as startup_genome_demo:
+with gr.Blocks() as startup_genome_demo:
+    state_lotto = gr.State()
+    selected_x_labels = gr.State()
+
+    with gr.Tab("Patent Discovery"):
+        with gr.Row():
+            dropdown_model = gr.Dropdown(label="Model", choices=['model_1', 'model_2', 'model_3'], interactive=True)
+        with gr.Row(equal_height=True):
+            abstract_description = gr.Textbox(label="Abstract description", lines=10, max_lines=10000, interactive=True, value="A holographic optical accessing system includes a light source for emitting a light beam; an optical assembly module for receiving the light beam and generating a signal beam and a reference beam that are parallel to each other rather than overlap with each other, and have the same first polarization state; a lens module for focusing the signal beam and the reference beam on a focal point at the same time; and a storage medium for recording the focal point. The optical assembly module includes at least a data plane for displaying image information so that the signal beam contains the image information.")
+        with gr.Row():
+            btn_get_result = gr.Button("Show classification")
+        with gr.Row():
+            label_result = gr.Label(num_top_classes=None)
+        with gr.Row():
+            reasoning = gr.Textbox(label="Reasoning", lines=5)
+    with gr.Tab("Classification data"):
+        pass
+
+    btn_get_result.click(fn=click_button, inputs=[dropdown_model, abstract_description], outputs=[label_result])
+
+
+if __name__ == "__main__":
+    startup_genome_demo.queue()
+    startup_genome_demo.launch()

requirements.txt

@@ -1 +1,2 @@
-gradio
+gradio
+plotly