reorg front end

about.py

@@ -5,6 +5,6 @@ PROBLEM_TYPES = ["unconditional", "conditional"]
 TOKEN = os.environ.get("HF_TOKEN")
 CACHE_PATH=os.getenv("HF_HOME", ".")
 API = HfApi(token=TOKEN)
-organization="cgeorgiaw"
-submissions_repo = f'{organization}/lemat-bench-submissions'
-results_repo = f'{organization}/lemat-bench-results'
+organization="LeMaterial"
+submissions_repo = f'{organization}/lemat-gen-bench-submissions'
+results_repo = f'{organization}/lemat-gen-bench-results'

app.py

@@ -9,52 +9,47 @@ from datetime import datetime
 import os
 
 from about import PROBLEM_TYPES, TOKEN, CACHE_PATH, API, submissions_repo, results_repo
-from utils import make_user_clickable, make_boundary_clickable
-
 
 def get_leaderboard():
     ds = load_dataset(results_repo, split='train', download_mode="force_redownload")
     full_df = pd.DataFrame(ds)
-    full_df['full results'] = full_df['result_filename'].apply(lambda x: make_boundary_clickable(x)).astype(str)
-
-    full_df.rename(columns={'submission_time': 'submission time', 'problem_type': 'problem type'}, inplace=True)
-    to_show = full_df.copy(deep=True)
-    to_show = to_show[to_show['user'] != 'test']
-    to_show = to_show[['submission time', 'problem type', 'user', 'score', 'full results']]
-    to_show['user'] = to_show['user'].apply(lambda x: make_user_clickable(x)).astype(str)
+    if len(full_df) == 0:
+        return pd.DataFrame({'date':[], 'model':[], 'score':[], 'verified':[]})
 
-    return to_show
+    return full_df
 
 def show_output_box(message):
     return gr.update(value=message, visible=True)
 
+def submit_cif_files(problem_type, cif_files, profile: gr.OAuthProfile | None):
+    return 
+
 def gradio_interface() -> gr.Blocks:
     with gr.Blocks() as demo:
-        gr.Markdown("## Welcome to the ConStellaration Boundary Leaderboard!")
+        gr.Markdown("## Welcome to the LeMaterial Generative Benchmark Leaderboard!")
         with gr.Tabs(elem_classes="tab-buttons"):
             with gr.TabItem("🚀 Leaderboard", elem_id="boundary-benchmark-tab-table"):                
-                gr.Markdown("# Boundary Design Leaderboard")
+                gr.Markdown("# LeMat-Gen-Bench")
 
                 try: 
                     Leaderboard(
                         value=get_leaderboard(),
-                        datatype=['date', 'str', 'html', 'number', 'html'],
-                        select_columns=["submission time", "problem type", "user", "score", "full results"],
-                        search_columns=["submission time", "score", "user"],
-                        # hide_columns=["result_filename", "submission_filename", "objective", "minimize_objective", "boundary_json", "evaluated"],
-                        filter_columns=["problem type"],
+                        datatype=['date', 'model', 'score', 'verified'],
+                        select_columns=["model"],
+                        search_columns=["model"],
+                        filter_columns=["verified"],
                         every=60,
                         render=True
                     )
                 except:
                     gr.Markdown("Leaderboard is empty.")
 
-                gr.Markdown("For the `geometrical` and `simple_to_build`, the scores are bounded between 0.0 and 1.0, where 1.0 is the best possible score. For the `mhd_stable` multi-objective problem, the score is unbounded with a undefined maximum score.")
+                gr.Markdown("Verified submissions mean the results came from a model submission rather than a CIF submission.")
 
             with gr.TabItem("❔About", elem_id="boundary-benchmark-tab-table"):
                 gr.Markdown(
                     """
-                    ## About LeMat-Bench
+                    ## About LeMat-Gen-Bench
 
                     **Welcome to the LeMat-Bench Leaderboard**, There are unconditional generation and conditional generation components of this leaderboard.
 
@@ -69,27 +64,14 @@ def gradio_interface() -> gr.Blocks:
                 """
                 )
                 filename = gr.State(value=None) 
-                eval_state = gr.State(value=None) 
-                user_state = gr.State(value=None)
 
-                # gr.LoginButton()
+                gr.LoginButton()
 
                 with gr.Row():
                     with gr.Column():
                         problem_type = gr.Dropdown(PROBLEM_TYPES, label="Problem Type")
-                        username_input = gr.Textbox(
-                            label="Username", 
-                            placeholder="Enter your Hugging Face username",
-                            info="This will be displayed on the leaderboard."
-                        )
                     with gr.Column():
-                        boundary_file = gr.File(label="Upload a CSV, a pkl, or a ZIP of CIF files.")
-
-                username_input.change(
-                    fn=lambda x: x if x.strip() else None,
-                    inputs=username_input,
-                    outputs=user_state
-                )                       
+                        cif_file = gr.File(label="Upload a CSV, a pkl, or a ZIP of CIF files.")                 
 
                 submit_btn = gr.Button("Submission")
                 message = gr.Textbox(label="Status", lines=1, visible=False)
@@ -97,8 +79,8 @@ def gradio_interface() -> gr.Blocks:
                 gr.Markdown("If you have issues with submission or using the leaderboard, please start a discussion in the Community tab of this Space.")
                 
                 submit_btn.click(
-                    submit_boundary,
-                    inputs=[problem_type, boundary_file, user_state],
+                    submit_cif_files,
+                    inputs=[problem_type, cif_file],
                     outputs=[message, filename],
                 ).then(
                     fn=show_output_box,

requirements.txt

@@ -1,5 +1,4 @@
 gradio
 datasets
 huggingface_hub
-gradio-leaderboard
-git+https://github.com/LeMaterial/lemat-genbench.git
+gradio-leaderboard