gradio app

README.md

@@ -5,5 +5,5 @@ colorFrom: indigo
 colorTo: gray
 sdk: docker
 pinned: false
-app_port: 8501
+app_port: 7860
 ---

app.py

@@ -0,0 +1,158 @@
+import uuid
+from datetime import datetime
+from functools import partial
+
+import gradio as gr
+import numpy as np
+import pandas as pd
+from huggingface_hub import HfApi
+from huggingface_hub.utils._errors import EntryNotFoundError
+
+import config
+import utils
+
+SUBMISSION_TEXT = f"""You can make upto {config.competition_info.submission_limit} submissions per day.
+The test data has been divided into public and private splits.
+Your score on the public split will be shown on the leaderboard.
+Your final score will be based on your private split performance.
+The final rankings will be based on the private split performance.
+"""
+
+SUBMISSION_ERROR = """Submission is not in a proper format.
+Please check evaluation instructions for more details."""
+
+SUBMISSION_LIMIT_TEXT = f"""You can select upto {config.competition_info.selection_limit}
+ submissions for private leaderboard."""
+
+
+def get_subs(user_info, private=False):
+    # get user submissions
+    user_id = user_info["id"]
+    try:
+        user_submissions = utils.fetch_submissions(user_id)
+    except EntryNotFoundError:
+        gr.Markdown("No submissions found")
+        return
+    submissions_df = pd.DataFrame(user_submissions)
+    if not private:
+        submissions_df = submissions_df.drop(columns=["private_score"])
+        submissions_df = submissions_df[
+            ["date", "submission_id", "public_score", "submission_comment", "selected", "status"]
+        ]
+    else:
+        submissions_df = submissions_df[
+            ["date", "submission_id", "public_score", "private_score", "submission_comment", "selected", "status"]
+        ]
+    gr.Markdown(submissions_df.to_markdown())
+
+
+def my_submissions(user_token):
+    if user_token != "":
+        user_info = utils.user_authentication(token=user_token)
+        if "error" in user_info:
+            gr.Markdown("Invalid token")
+            return
+
+        if user_info["emailVerified"] is False:
+            gr.Markdown("Please verify your email on Hugging Face Hub")
+            return
+
+        current_date_time = datetime.now()
+        private = False
+        if current_date_time >= config.competition_info.end_date:
+            private = True
+        get_subs(user_info, private=private)
+
+
+def new_submission(user_token):
+    gr.Markdown(SUBMISSION_TEXT)
+    uploaded_file = st.file_uploader("Choose a file")
+    submit_button = st.button("Submit")
+    if uploaded_file is not None and user_token != "" and submit_button:
+        # verify token
+        user_info = utils.user_authentication(token=user_token)
+        if "error" in user_info:
+            gr.Markdown("Invalid token")
+            return
+
+        if user_info["emailVerified"] is False:
+            gr.Markdown("Please verify your email on Hugging Face Hub")
+            return
+
+        # check if user can submit to the competition
+        if utils.check_user_submission_limit(user_info) is False:
+            gr.Markdown("You have reached your submission limit for today")
+            return
+
+        bytes_data = uploaded_file.getvalue()
+        # verify file is valid
+        if not utils.verify_submission(bytes_data):
+            gr.Markdown("Invalid submission")
+            gr.Markdown(SUBMISSION_ERROR)
+            # write a horizontal html line
+            gr.Markdown("<hr/>", unsafe_allow_html=True)
+        else:
+            # TODO: add spinner here
+            user_id = user_info["id"]
+            submission_id = str(uuid.uuid4())
+            file_extension = uploaded_file.name.split(".")[-1]
+            # upload file to hf hub
+            api = HfApi()
+            api.upload_file(
+                path_or_fileobj=bytes_data,
+                path_in_repo=f"submissions/{user_id}-{submission_id}.{file_extension}",
+                repo_id=config.COMPETITION_ID,
+                repo_type="dataset",
+                token=config.AUTOTRAIN_TOKEN,
+            )
+            # update submission limit
+            submissions_made = utils.increment_submissions(
+                user_id=user_id,
+                submission_id=submission_id,
+                submission_comment="",
+            )
+            # schedule submission for evaluation
+            utils.create_project(
+                project_id=f"{submission_id}",
+                dataset=f"{config.COMPETITION_ID}",
+                submission_dataset=user_id,
+                model="generic_competition",
+            )
+        gr.Markdown("Submission scheduled for evaluation")
+        gr.Markdown(
+            f"You have {config.competition_info.submission_limit - submissions_made} submissions left for today."
+        )
+
+
+with gr.Blocks() as demo:
+    with gr.Tab("Overview"):
+        gr.Markdown(f"# Welcome to {config.competition_info.competition_name}! 👋")
+
+        gr.Markdown(f"{config.competition_info.competition_description}")
+
+        gr.Markdown("## Dataset")
+        gr.Markdown(f"{config.competition_info.dataset_description}")
+
+    with gr.Tab("Public Leaderboard"):
+        lb = utils.fetch_leaderboard(private=False)
+        gr.Markdown(lb.to_markdown())
+    with gr.Tab("Private Leaderboard"):
+        current_date_time = datetime.now()
+        if current_date_time >= config.competition_info.end_date:
+            lb = utils.fetch_leaderboard(private=True)
+            gr.Markdown(lb.to_markdown())
+        else:
+            gr.Markdown("Private Leaderboard will be available after the competition ends")
+    with gr.Tab("New Submission"):
+        text_input = gr.Textbox()
+        text_output = gr.Textbox()
+        text_button = gr.Button("Flip")
+    with gr.Tab("My Submissions"):
+        gr.Markdown(SUBMISSION_LIMIT_TEXT)
+        user_token = gr.Textbox(max_lines=1)
+        my_subs_button = gr.Button("Fetch Submissions")
+        mysubs = partial(my_submissions, user_token=user_token)
+        my_subs_button.click(mysubs)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -1,4 +1,4 @@
+gradio==3.9.1
 pandas==1.5.0
 python-dotenv==0.20.0
-streamlit==1.14.0
 huggingface_hub==0.10.1