Update app.py

app.py

@@ -108,6 +108,13 @@ def init_leaderboard(dataframe):
     )
 
 
+# =================test
+if os.path.exists("./text.txt"):
+    print(open("./text.txt").read())
+else:
+    print("not exists")
+
+
 demo = gr.Blocks(css=custom_css)
 with demo:
     gr.HTML(TITLE)
@@ -125,88 +132,134 @@ with demo:
             with gr.Column():
                 with gr.Row():
                     gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
+            with gr.Column():  
+                with gr.Row():  
+                    score_input = gr.Textbox(label="Score (float)", placeholder="请输入分数")  
+                    name_input = gr.Textbox(label="Name (str)", placeholder="请输入名称")  
+                    base_model_input = gr.Textbox(label="BaseModel (str)", placeholder="请输入基模型名称")  
+                  
+                with gr.Row():  
+                    env_dropdown = gr.Dropdown(  
+                        choices=["Sokoban", "Football", "WebUI"],  
+                        label="Env.",  
+                        value="Sokoban"  
+                    )  
+                    target_research_dropdown = gr.Dropdown(  
+                        choices=["Model-Eval-Online", "Model-Eval-Global"],  
+                        label="Target-research",  
+                        value="Model-Eval-Online"  
+                    )  
+                    subset_dropdown = gr.Dropdown(  
+                        choices=["mini", "all"],  
+                        label="Subset",  
+                        value="mini"  
+                    )  
+                  
+                link_input = gr.Textbox(label="Link (str)", placeholder="请输入链接")  
+                  
+                submit_button = gr.Button("Submit Eval")  
+                submission_result = gr.Markdown()  
+                  
+                def submit_eval(score, name, base_model, env, target_research, subset, link):  
+                    # 在这里处理提交逻辑，可以将信息保存到数据库或进行其他处理  
+                    result = (  
+                        f"Score: {score}\n"  
+                        f"Name: {name}\n"  
+                        f"BaseModel: {base_model}\n"  
+                        f"Env: {env}\n"  
+                        f"Target-research: {target_research}\n"  
+                        f"Subset: {subset}\n"  
+                        f"Link: {link}"  
+                    ) 
+                    open("./text.txt", "w").write(result)
+                    return result  
+                  
+                submit_button.click(  
+                    submit_eval,   
+                    [score_input, name_input, base_model_input, env_dropdown, target_research_dropdown, subset_dropdown, link_input],  
+                    submission_result  
+                )  
+            #     with gr.Column():
+            #         with gr.Accordion(
+            #             f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
+            #             open=False,
+            #         ):
+            #             with gr.Row():
+            #                 finished_eval_table = gr.components.Dataframe(
+            #                     value=finished_eval_queue_df,
+            #                     headers=EVAL_COLS,
+            #                     datatype=EVAL_TYPES,
+            #                     row_count=5,
+            #                 )
+            #         with gr.Accordion(
+            #             f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
+            #             open=False,
+            #         ):
+            #             with gr.Row():
+            #                 running_eval_table = gr.components.Dataframe(
+            #                     value=running_eval_queue_df,
+            #                     headers=EVAL_COLS,
+            #                     datatype=EVAL_TYPES,
+            #                     row_count=5,
+            #                 )
 
-                with gr.Column():
-                    with gr.Accordion(
-                        f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
-                        open=False,
-                    ):
-                        with gr.Row():
-                            finished_eval_table = gr.components.Dataframe(
-                                value=finished_eval_queue_df,
-                                headers=EVAL_COLS,
-                                datatype=EVAL_TYPES,
-                                row_count=5,
-                            )
-                    with gr.Accordion(
-                        f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
-                        open=False,
-                    ):
-                        with gr.Row():
-                            running_eval_table = gr.components.Dataframe(
-                                value=running_eval_queue_df,
-                                headers=EVAL_COLS,
-                                datatype=EVAL_TYPES,
-                                row_count=5,
-                            )
-
-                    with gr.Accordion(
-                        f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
-                        open=False,
-                    ):
-                        with gr.Row():
-                            pending_eval_table = gr.components.Dataframe(
-                                value=pending_eval_queue_df,
-                                headers=EVAL_COLS,
-                                datatype=EVAL_TYPES,
-                                row_count=5,
-                            )
-            with gr.Row():
-                gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
-
-            with gr.Row():
-                with gr.Column():
-                    model_name_textbox = gr.Textbox(label="Model name")
-                    revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-                    model_type = gr.Dropdown(
-                        choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-                        label="Model type",
-                        multiselect=False,
-                        value=None,
-                        interactive=True,
-                    )
-
-                with gr.Column():
-                    precision = gr.Dropdown(
-                        choices=[i.value.name for i in Precision if i != Precision.Unknown],
-                        label="Precision",
-                        multiselect=False,
-                        value="float16",
-                        interactive=True,
-                    )
-                    weight_type = gr.Dropdown(
-                        choices=[i.value.name for i in WeightType],
-                        label="Weights type",
-                        multiselect=False,
-                        value="Original",
-                        interactive=True,
-                    )
-                    base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
-            submit_button = gr.Button("Submit Eval")
-            submission_result = gr.Markdown()
-            submit_button.click(
-                add_new_eval,
-                [
-                    model_name_textbox,
-                    base_model_name_textbox,
-                    revision_name_textbox,
-                    precision,
-                    weight_type,
-                    model_type,
-                ],
-                submission_result,
-            )
+            #         with gr.Accordion(
+            #             f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
+            #             open=False,
+            #         ):
+            #             with gr.Row():
+            #                 pending_eval_table = gr.components.Dataframe(
+            #                     value=pending_eval_queue_df,
+            #                     headers=EVAL_COLS,
+            #                     datatype=EVAL_TYPES,
+            #                     row_count=5,
+            #                 )
+            # with gr.Row():
+            #     gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
+
+            # with gr.Row():
+            #     with gr.Column():
+            #         model_name_textbox = gr.Textbox(label="Model name")
+            #         revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
+            #         model_type = gr.Dropdown(
+            #             choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
+            #             label="Model type",
+            #             multiselect=False,
+            #             value=None,
+            #             interactive=True,
+            #         )
+
+            #     with gr.Column():
+            #         precision = gr.Dropdown(
+            #             choices=[i.value.name for i in Precision if i != Precision.Unknown],
+            #             label="Precision",
+            #             multiselect=False,
+            #             value="float16",
+            #             interactive=True,
+            #         )
+            #         weight_type = gr.Dropdown(
+            #             choices=[i.value.name for i in WeightType],
+            #             label="Weights type",
+            #             multiselect=False,
+            #             value="Original",
+            #             interactive=True,
+            #         )
+            #         base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
+
+            # submit_button = gr.Button("Submit Eval")
+            # submission_result = gr.Markdown()
+            # submit_button.click(
+            #     add_new_eval,
+            #     [
+            #         model_name_textbox,
+            #         base_model_name_textbox,
+            #         revision_name_textbox,
+            #         precision,
+            #         weight_type,
+            #         model_type,
+            #     ],
+            #     submission_result,
+            # )
 
     with gr.Row():
         with gr.Accordion("📙 Citation", open=False):