Update app.py

app.py

@@ -8,31 +8,34 @@ import gradio as gr
 from huggingface_hub import HfApi, snapshot_download, ModelInfo, list_models
 from enum import Enum
 
-
 OWNER = "AIEnergyScore"
 COMPUTE_SPACE = f"{OWNER}/launch-computation-example"
-
-
 TOKEN = os.environ.get("DEBUG")
 API = HfApi(token=TOKEN)
 
+task_mappings = {
+    'automatic speech recognition': 'automatic-speech-recognition',
+    'Object Detection': 'object-detection',
+    'Text Classification': 'text-classification',
+    'Image to Text': 'image-to-text',
+    'Question Answering': 'question-answering',
+    'Text Generation': 'text-generation',
+    'Image Classification': 'image-classification',
+    'Sentence Similarity': 'sentence-similarity',
+    'Image Generation': 'image-generation',
+    'Summarization': 'summarization'
+}
 
-
-task_mappings = {'automatic speech recognition':'automatic-speech-recognition', 'Object Detection': 'object-detection', 'Text Classification': 'text-classification',
-                 'Image to Text':'image-to-text', 'Question Answering':'question-answering', 'Text Generation': 'text-generation',
-                 'Image Classification':'image-classification', 'Sentence Similarity': 'sentence-similarity',
-                 'Image Generation':'image-generation', 'Summarization':'summarization'}
 @dataclass
 class ModelDetails:
     name: str
     display_name: str = ""
-    symbol: str = "" # emoji
+    symbol: str = ""  # emoji
 
 def start_compute_space():
     API.restart_space(COMPUTE_SPACE)
     gr.Info(f"Okay! {COMPUTE_SPACE} should be running now!")
 
-
 def get_model_size(model_info: ModelInfo):
     """Gets the model size from the configuration, or the model name if the configuration does not contain the information."""
     try:
@@ -48,16 +51,15 @@ def add_docker_eval(zip_file):
         API.upload_file(
             path_or_fileobj=zip_file,
             repo_id="AIEnergyScore/tested_proprietary_models",
-            path_in_repo='submitted_models/'+new_fid,
+            path_in_repo='submitted_models/' + new_fid,
             repo_type="dataset",
             commit_message="Adding logs via submission Space.",
             token=TOKEN
-            )
+        )
         gr.Info('Uploaded logs to dataset! We will validate their validity and add them to the next version of the leaderboard.')
     else:
         gr.Info('You can only upload .zip files here!')
 
-
 def add_new_eval(repo_id: str, task: str):
     model_owner = repo_id.split("/")[0]
     model_name = repo_id.split("/")[1]
@@ -91,10 +93,8 @@ def add_new_eval(repo_id: str, task: str):
             "task": task_mappings[task],
             "likes": likes,
             "params": model_size,
-            "leaderboard_version": "v0",}
-            #"license": license,
-            #"private": False,
-        #}
+            "leaderboard_version": "v0",
+        }
 
         print("Writing out request file to dataset")
         df_request_dict = pd.DataFrame([request_dict])
@@ -106,11 +106,10 @@ def add_new_eval(repo_id: str, task: str):
         gr.Info("Starting compute space at %s " % COMPUTE_SPACE)
         return start_compute_space()
 
-
 def print_existing_models():
-    requests= load_dataset("AIEnergyScore/requests_debug", split="test", token=TOKEN)
+    requests = load_dataset("AIEnergyScore/requests_debug", split="test", token=TOKEN)
     requests_dset = requests.to_pandas()
-    model_df= requests_dset[['model', 'status']]
+    model_df = requests_dset[['model', 'status']]
     model_df = model_df[model_df['status'] == 'COMPLETED']
     return model_df
 
@@ -132,15 +131,62 @@ def get_leaderboard_models():
     for filename in filenames:
         data.append(pd.read_csv(filename))
     leaderboard_data = pd.concat(data, ignore_index=True)
-    return leaderboard_data[['model','task']]
+    return leaderboard_data[['model', 'task']]
 
+# A placeholder for get_zip_data_link() -- replace with your actual implementation if available.
+def get_zip_data_link():
+    return (
+        '<a href="https://example.com/download.zip" '
+        'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+        'color: black; font-family: \'Inter\', sans-serif;">Download Logs</a>'
+    )
 
 with gr.Blocks() as demo:
-    gr.Markdown("# AI Energy Score | Submission Portal")
-    gr.Markdown("### The goal of the AI Energy Score project is to develop an energy-based rating system for AI model deployment that will guide members of the community in choosing models for different tasks based on energy efficiency.", elem_classes="markdown-text")
+    # --- Header Links (at the very top) ---
+    with gr.Row():
+        leaderboard_link = gr.HTML(
+            '<a href="https://huggingface.co/spaces/AIEnergyScore/Leaderboard" '
+            'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+            'color: black; font-family: \'Inter\', sans-serif;">Leaderboard</a>'
+        )
+        label_link = gr.HTML(
+            '<a href="https://huggingface.co/spaces/AIEnergyScore/Label" '
+            'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+            'color: black; font-family: \'Inter\', sans-serif;">Label Generator</a>'
+        )
+        faq_link = gr.HTML(
+            '<a href="https://huggingface.github.io/AIEnergyScore/#faq" '
+            'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+            'color: black; font-family: \'Inter\', sans-serif;">FAQ</a>'
+        )
+        documentation_link = gr.HTML(
+            '<a href="https://huggingface.github.io/AIEnergyScore/#documentation" '
+            'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+            'color: black; font-family: \'Inter\', sans-serif;">Documentation</a>'
+        )
+        download_link = gr.HTML(get_zip_data_link())
+        community_link = gr.HTML(
+            '<a href="https://huggingface.co/spaces/AIEnergyScore/README/discussions" '
+            'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
+            'color: black; font-family: \'Inter\', sans-serif;">Community</a>'
+        )
+    
+    # --- Logo (centered) ---
+    gr.HTML('''
+    <div style="margin-top: 0px;">
+        <img src="https://huggingface.co/spaces/AIEnergyScore/Leaderboard/resolve/main/logo.png" 
+             alt="Logo" 
+             style="display: block; margin: 0 auto; max-width: 500px; height: auto;">
+    </div>
+    ''')
+
+    # --- Main UI ---
+    gr.Markdown("# Submission Portal")
+    gr.Markdown("### The goal of the AI Energy Score project is to develop an energy-based rating system for AI model deployment that will guide members of the community in choosing models for different tasks based on energy efficiency.")
     gr.Markdown("### If you want us to evaluate a model hosted on the 🤗 Hub, enter the model ID and choose the corresponding task from the dropdown list below, then click **Run Analysis** to launch the benchmarking process.")
     gr.Markdown("### If you've used the [Docker file](https://github.com/huggingface/AIEnergyScore/) to run your own evaluation, please submit the resulting log files at the bottom of the page.")
-    gr.Markdown("### The [Project Leaderboard](https://huggingface.co/spaces/AIEnergyScore/Leaderboard) will be updated twice a year.")
+    gr.Markdown("### The [Project Leaderboard](https://huggingface.co/spaces/AIEnergyScore/Leaderboard) will be updated on a biannual basis (last updated in February 2025).")
+    
     with gr.Row():
         with gr.Column():
             task = gr.Dropdown(
@@ -152,19 +198,17 @@ with gr.Blocks() as demo:
             )
         with gr.Column():
             model_name_textbox = gr.Textbox(label="Model name (user_name/model_name)")
-
+    
     with gr.Row():
         with gr.Column():
             submit_button = gr.Button("Submit for Analysis")
             submission_result = gr.Markdown()
             submit_button.click(
                 fn=add_new_eval,
-                inputs=[
-                    model_name_textbox,
-                    task,
-                ],
+                inputs=[model_name_textbox, task],
                 outputs=submission_result,
             )
+    
     with gr.Row():
         with gr.Column():
             with gr.Accordion("Submit log files from a Docker run:", open=False):
@@ -176,19 +220,21 @@ with gr.Blocks() as demo:
                 file_output = gr.File(visible=False)
                 u = gr.UploadButton("Upload a zip file with logs", file_count="single", interactive=False)
                 u.upload(add_docker_eval, u, file_output)
-
+    
                 def update_upload_button_interactive(checkbox_value):
                     return gr.UploadButton.update(interactive=checkbox_value)
-
+    
                 agreement_checkbox.change(
                     fn=update_upload_button_interactive,
                     inputs=[agreement_checkbox],
                     outputs=[u]
                 )
+    
     with gr.Row():
         with gr.Column():
-                with gr.Accordion("Models that are in the latest leaderboard version:", open=False, visible=False):
-                   gr.Dataframe(get_leaderboard_models())
-                with gr.Accordion("Models that have been benchmarked recently:", open=False, visible=False):
-                    gr.Dataframe(formatted_df)
+            with gr.Accordion("Models that are in the latest leaderboard version:", open=False, visible=False):
+                gr.Dataframe(get_leaderboard_models())
+            with gr.Accordion("Models that have been benchmarked recently:", open=False, visible=False):
+                gr.Dataframe(formatted_df)
+
 demo.launch()