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ISM2023w

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debayan commited on Dec 28, 2023

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11bad2f

1 Parent(s): 80a53ee

Upload folder using huggingface_hub

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Files changed (3) hide show

__pycache__/request_api.cpython-38.pyc +0 -0
gradio_app.py +18 -32
request_api.py +4 -32

__pycache__/request_api.cpython-38.pyc CHANGED Viewed

Binary files a/__pycache__/request_api.cpython-38.pyc and b/__pycache__/request_api.cpython-38.pyc differ

gradio_app.py CHANGED Viewed

@@ -7,8 +7,6 @@ from datetime import datetime, timezone
 from pathlib import Path
 from request_api import make_get_request, make_post_request
 from io import BytesIO, StringIO
-import asyncio
 LEADERBOARD_PATH = "/home/Bhattacharya/ism_leaderboard/files/leaderboard"
 # Directory where request by models are stored
 DIR_OUTPUT_REQUESTS = Path("requested_models")
@@ -18,7 +16,7 @@ EVAL_REQUESTS_PATH = Path("eval_requests")
 # Text definitions       #
 ##########################
-banner_url = "https://huggingface.co/spaces/debayan/ISM2023w/resolve/main/logo_leaderboard.png"
 BANNER = f'<div style="display: flex; justify-content: space-around;"><img src="{banner_url}" alt="Banner" style="width: 40vw; min-width: 300px; max-width: 600px;"> </div>'
 TITLE = "<html> <head> <style> h1 {text-align: center;} </style> </head> <body> <h1> 🤗 Open Automatic Speech Recognition Leaderboard </b> </body> </html>"
@@ -28,9 +26,9 @@ INTRODUCTION_TEXT = "🏆 The ISM2023w Leaderboard ranks and evaluates models \
     \nWe report the Precision, Recall, Accuracy, Weighted [F1 Score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html)\n"
 #CSV_TEXT = "<p>Please make sure that you upload the CSV in the correct format. Click the link to download a sample CSV!</p> <a href=\"https://huggingface.co/spaces/debayan/ism_2023w/raw/main/example.csv\" download=\"example.csv\">Download CSV</a>"
-CSV_TEXT = "<p>Please go to the new url to upload CSV and check leaderboard!</p>  [https://726b6c34825b86770e.gradio.live](https://726b6c34825b86770e.gradio.live)"
 METRICS_TAB_TEXT = """
 Here you will find details about the multi-class classification metrics and datasets reported in our leaderboard.
@@ -41,8 +39,6 @@ below.
 """
 LAST_UPDATED = "Sep 28th 2023"
@@ -62,18 +58,17 @@ def create_html_page(title, content):
     return html_page
-async def fetch_leaderboard(phase=1):
     """
     Fetch the leaderboard from the local disk
     """
     params = {"phase": phase}
-    leaderboard_df = await make_get_request("fetch-leaderboard", params)
     csv_data = leaderboard_df.content.decode('utf-8')
-    #print(csv_data)
     # create dataframe from csv data
     leaderboard_df = pd.read_csv(StringIO(csv_data))
@@ -150,10 +145,6 @@ def formatter(x):
 def format_leaderboard(df,sort_by="F1 Score"):
     # Formats the columns
-    if df is None:
-        return None
-    print(df)
     for col in df.columns:
         if col == "Team Name":
             # do nothing
@@ -169,15 +160,12 @@ def format_leaderboard(df,sort_by="F1 Score"):
     df.sort_values(by=sort_by, inplace=True, ascending=False)
     return df
-# Run the async function in an event loop
-#lb_1 = asyncio.run(fetch_leaderboard(phase=1))
-#lb_2 = asyncio.run(fetch_leaderboard(phase=2))
-#leaderboard_df_1 = format_leaderboard(lb_1)
-#leaderboard_df_2 = format_leaderboard(lb_2)
-#leaderboard_df_1 = None
-#leaderboard_df_2 = None
 COLS = [c.name for c in fields(AutoEvalColumn)]
 TYPES = [c.type for c in fields(AutoEvalColumn)]
@@ -187,8 +175,8 @@ with gr.Blocks() as demo:
     leaderboard_table_2 = None
     def button_clicked_phase_1(inputs):
-        lb_1 = asyncio.run(fetch_leaderboard(phase=1))
-        leaderboard_df_1 = format_leaderboard(lb_1)
         leaderboard_table_1 = gr.components.Dataframe(
@@ -205,8 +193,8 @@ with gr.Blocks() as demo:
     def button_clicked_phase_2():
-        lb_2 = asyncio.run(fetch_leaderboard(phase=2))
-        leaderboard_df_2 = format_leaderboard(lb_2)
         leaderboard_table_2 = gr.components.Dataframe(
@@ -230,8 +218,8 @@ with gr.Blocks() as demo:
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
     gr.HTML(CSV_TEXT, elem_classes="markdown-text")
-    """
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏅 Leaderboard Phase 1", elem_id="od-benchmark-tab-table-1", id=0):
@@ -278,9 +266,9 @@ with gr.Blocks() as demo:
             ],
             outputs=gr.outputs.HTML()
         )
-    """
@@ -288,9 +276,7 @@ with gr.Blocks() as demo:
     gr.Markdown(f"Last updated on **{LAST_UPDATED}**", elem_classes="markdown-text")
-demo.launch( debug=True,share=True)

 from pathlib import Path
 from request_api import make_get_request, make_post_request
 from io import BytesIO, StringIO
 LEADERBOARD_PATH = "/home/Bhattacharya/ism_leaderboard/files/leaderboard"
 # Directory where request by models are stored
 DIR_OUTPUT_REQUESTS = Path("requested_models")
 # Text definitions       #
 ##########################
+banner_url = "https://huggingface.co/spaces/debayan/ism_2023w/resolve/main/logo_leaderboard.png"
 BANNER = f'<div style="display: flex; justify-content: space-around;"><img src="{banner_url}" alt="Banner" style="width: 40vw; min-width: 300px; max-width: 600px;"> </div>'
 TITLE = "<html> <head> <style> h1 {text-align: center;} </style> </head> <body> <h1> 🤗 Open Automatic Speech Recognition Leaderboard </b> </body> </html>"
     \nWe report the Precision, Recall, Accuracy, Weighted [F1 Score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html)\n"
 #CSV_TEXT = "<p>Please make sure that you upload the CSV in the correct format. Click the link to download a sample CSV!</p> <a href=\"https://huggingface.co/spaces/debayan/ism_2023w/raw/main/example.csv\" download=\"example.csv\">Download CSV</a>"
+CSV_TEXT = "<p>Please use this link to upload your csvs and check leaderboards!</p> <a href=\"https://96a0375bee72bd00d0.gradio.live\" >https://96a0375bee72bd00d0.gradio.live</a>"
 METRICS_TAB_TEXT = """
 Here you will find details about the multi-class classification metrics and datasets reported in our leaderboard.
 """
 LAST_UPDATED = "Sep 28th 2023"
     return html_page
+def fetch_leaderboard(phase=1):
     """
     Fetch the leaderboard from the local disk
     """
     params = {"phase": phase}
+    leaderboard_df = make_get_request("fetch-leaderboard", params)
     csv_data = leaderboard_df.content.decode('utf-8')
+    print(csv_data)
     # create dataframe from csv data
     leaderboard_df = pd.read_csv(StringIO(csv_data))
 def format_leaderboard(df,sort_by="F1 Score"):
     # Formats the columns
     for col in df.columns:
         if col == "Team Name":
             # do nothing
     df.sort_values(by=sort_by, inplace=True, ascending=False)
     return df
+#leaderboard_df_1 = format_leaderboard(fetch_leaderboard(phase=1))
+#leaderboard_df_2 = format_leaderboard(fetch_leaderboard(phase=2))
 COLS = [c.name for c in fields(AutoEvalColumn)]
 TYPES = [c.type for c in fields(AutoEvalColumn)]
     leaderboard_table_2 = None
     def button_clicked_phase_1(inputs):
+        leaderboard_df_1 = format_leaderboard(fetch_leaderboard(phase=1))
         leaderboard_table_1 = gr.components.Dataframe(
     def button_clicked_phase_2():
+        leaderboard_df_2 = format_leaderboard(fetch_leaderboard(phase=2))
         leaderboard_table_2 = gr.components.Dataframe(
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
     gr.HTML(CSV_TEXT, elem_classes="markdown-text")
+    """
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏅 Leaderboard Phase 1", elem_id="od-benchmark-tab-table-1", id=0):
             ],
             outputs=gr.outputs.HTML()
         )
+    """
     gr.Markdown(f"Last updated on **{LAST_UPDATED}**", elem_classes="markdown-text")
+demo.launch(debug=True,share=True)

request_api.py CHANGED Viewed

@@ -4,43 +4,15 @@
 import requests
-from urllib.parse import urljoin, urlencode
-# Define the base URL
-#BASE_URL = 'http://127.0.0.1:5000/'
-import httpx
 BASE_URL = 'https://d9c5-134-28-45-21.ngrok-free.app/'
-async def make_get_request(endpoint, params):
-    async with httpx.AsyncClient() as client:
-        try:
-            response = await client.get(urljoin(BASE_URL, endpoint), params=params)
-            print(response.url)
-            response.raise_for_status()  # Check if the response is successful
-        except httpx.HTTPError as e:
-            print(f"Request failed: {e}")
-            return None
-    print(response)
-    return response
-async def make_post_request(endpoint, params, data=None):
-    if data is None:
-        return None
-    async with httpx.AsyncClient() as client:
-        try:
-            response = await client.post(urljoin(BASE_URL, endpoint), params=params, data=data)
-            response.raise_for_status()  # Check if the response is successful
-        except httpx.HTTPError as e:
-            print(f"Request failed: {e}")
-            return None
-    return response
-"""
 def make_get_request(endpoint,params):
     try:
@@ -78,5 +50,5 @@ def make_post_request(endpoint,params,data=None):
     # Return the error
     return response
-"""

 import requests
+from urllib.parse import urljoin, urlencode, urlparse, urlunparse
+# Define the base URL
 BASE_URL = 'https://d9c5-134-28-45-21.ngrok-free.app/'
+#BASE_URL = 'http://127.0.0.1:5000/'
 def make_get_request(endpoint,params):
     try:
     # Return the error
     return response