Updated counters to use use info

main_backend_lighteval.py

@@ -88,23 +88,21 @@ def run_auto_eval():
 
     # next, check to see who made the last commit to this repo - keep track of that. One person shouldn't commit more 
     # than 4 models in one month. 
-    commits = API.list_repo_commits(eval_request.model, revision=eval_request.revision)
-    users = commits[0].authors
-    for user in users:
-        if user in requests_seen and len(requests_seen[user]) >= 4:
-            set_eval_request(
-                api=API,
-                eval_request=eval_request,
-                set_to_status=FAILED_STATUS,
-                hf_repo=QUEUE_REPO,
-                local_dir=EVAL_REQUESTS_PATH_BACKEND,
-            )
-            pp.pprint(dict(message="Reached maximum cap for requests for this user this month", counter=counter_key, user=user))
-            return
-        if not user in requests_seen:
-            requests_seen[user] = []
-        requests_seen[user].append(dict(model_id=eval_request.model, revision=eval_request.revision))
+    user = eval_request.user_info['name']
+    if user in requests_seen and len(requests_seen[user]) >= 4:
+        set_eval_request(
+            api=API,
+            eval_request=eval_request,
+            set_to_status=FAILED_STATUS,
+            hf_repo=QUEUE_REPO,
+            local_dir=EVAL_REQUESTS_PATH_BACKEND,
+        )
+        pp.pprint(dict(message="Reached maximum cap for requests for this user this month", counter=counter_key, user=user))
+        return
+    if not user in requests_seen:
+        requests_seen[user] = []
         
+    requests_seen[user].append(dict(model_id=eval_request.model, revision=eval_request.revision))
     requests_seen[counter_key] += 1
     set_requests_seen(
         api=API,

src/backend/manage_requests.py

@@ -24,6 +24,7 @@ class EvalRequest:
     likes: Optional[int] = 0
     params: Optional[int] = None
     license: Optional[str] = ""
+    user_info: Optional[dict] = None
     
     def get_model_args(self):
         model_args = f"pretrained={self.model},revision={self.revision}"