requests are now stored in a private ds repo

constants.py

@@ -7,7 +7,7 @@ import os
 #
 
 TOKEN_HUB = os.environ.get("TOKEN_HUB", None)
-REPO_ID = "brescia-ai/open_ita_asr_leaderboard"
+DATASET_REPO = "brescia-ai/open-ita-asr-requests"
 COLUMN_DTYPES_LIST = ["markdown", "number", "number", "number"]		# in accordance with ./leaderboard.csv
 
 #

requested_models.txt

@@ -1 +0,0 @@
-stabilityai/stable-audio-open-1.0

utils/eval_requests.py

@@ -1,9 +1,11 @@
 import huggingface_hub as hf_hub
-from constants import REPO_ID, TOKEN_HUB
+import uuid
+
+import constants
 
 hf_api = hf_hub.HfApi(
     endpoint="https://huggingface.co", 
-    token=TOKEN_HUB, 
+    token=constants.TOKEN_HUB, 
 )
 
 
@@ -36,17 +38,6 @@ def is_model_on_hub(model_id):
         return "was not found on hub!"
 
 
-def upload_file(local_filepath, repo_filepath, commit_message):
-    hf_api.upload_file(
-            path_or_fileobj=local_filepath,
-            path_in_repo=repo_filepath,
-            repo_id=REPO_ID,
-            token=TOKEN_HUB,
-            repo_type="space",
-            commit_message=commit_message
-    )
-
-
 def request_model(model_id):
 
     def styled_error(error):
@@ -55,26 +46,32 @@ def request_model(model_id):
     def styled_message(message):
         return f"<p style='color: green; font-size: 20px; text-align: center;'>{message}</p>"
     
-    # Check if the model is on the hub
-    error_msg = is_model_on_hub(model_id)
-    if error_msg != None:
-        return styled_error(f"{model_id} {error_msg}")
+    # # Check if the model is on the hub
+    # error_msg = is_model_on_hub(model_id)
+    # if error_msg != None:
+    #     return styled_error(f"{model_id} {error_msg}")
     
-    # Check if the model was already requested
-    with open("requested_models.txt", "r") as f:
-        requested_models_list = f.read().splitlines()
-    if model_id in requested_models_list:
-        return styled_error(f"A request for {model_id} was already made.")
+    # # Check if the model was already requested
+    # with open("requested_models.txt", "r") as f:
+    #     requested_models_list = f.read().splitlines()
+    # if model_id in requested_models_list:
+    #     return styled_error(f"A request for {model_id} was already made.")
     
-    # Add the model to the local evaluation queue
-    with open("requested_models.txt", "a") as f:
-        f.write(model_id + "\n")
+    # # Add the model to the local evaluation queue
+    # with open("requested_models.txt", "a") as f:
+    #     f.write(model_id + "\n")
 
-    # Push the request file to the hub
-    upload_file(
-        local_filepath="requested_models.txt",
-        repo_filepath="requested_models.txt",
-        commit_message=f"{model_id} added to the evaluation queue."
+    # Push the request file to the private dataset repo
+    unique_request_filename = str(uuid.uuid4())
+    with open("unique_request_filename.json", "w") as f:
+        f.write(model_id)
+    hf_api.upload_file(
+            path_or_fileobj=unique_request_filename,     #local_filepath
+            path_in_repo=unique_request_filename,
+            repo_id=constants.DATASET_REPO,
+            token=constants.TOKEN_HUB,
+            repo_type="dataset",
+            commit_message=f"{model_id} added to the evaluation queue.",
     )
 
     return styled_message("🤗 Your request has been submitted and will be evaluated as soon as possible!")