Replacing deprecated Repository with git

init.py

@@ -1,48 +1,51 @@
-import os 
 from constants import EVAL_REQUESTS_PATH
 from pathlib import Path
-from huggingface_hub import HfApi, Repository
+from huggingface_hub import HfApi
 from dotenv import load_dotenv
+import git
+import os
 
 load_dotenv()
+
+# Hub to access the dataset repo
 TOKEN_HUB = os.environ.get("TOKEN_HUB_V2", None)
+# Name of the repo where the dataset is stored user/repo_name
 QUEUE_REPO = os.environ.get("QUEUE_REPO", None)
+# Local path where the repo is cloned to
 QUEUE_PATH = os.environ.get("QUEUE_PATH", None)
 
 hf_api = HfApi(
-    endpoint="https://huggingface.co", 
-    token=TOKEN_HUB, 
+    endpoint="https://huggingface.co",
+    token=TOKEN_HUB,
 )
 
+
 def load_all_info_from_dataset_hub():
     eval_queue_repo = None
-    results_csv_path = None
+    csv_results = None
     requested_models = None
 
-    passed = True
     if TOKEN_HUB is None:
-        passed = False
+        print(
+            "No HuggingFace token provided. Skipping evaluation requests and results."
+        )
+        return eval_queue_repo, requested_models, csv_results
     else:
         print("Pulling evaluation requests and results.")
 
-        eval_queue_repo = Repository(
-            local_dir=QUEUE_PATH,
-            clone_from=QUEUE_REPO,
-            use_auth_token=TOKEN_HUB,
-            repo_type="dataset",
+        # Pull the dataset repo
+        user_name = QUEUE_REPO.split("/")[0]
+        repo_url = (
+            f"https://{user_name}:{TOKEN_HUB}@huggingface.co/datasets/{QUEUE_REPO}"
         )
-        eval_queue_repo.git_pull()
-        
+        git.Repo.clone_from(repo_url, QUEUE_PATH)
+
         # Local directory where dataset repo is cloned + folder with eval requests
         directory = QUEUE_PATH / EVAL_REQUESTS_PATH
         requested_models = get_all_requested_models(directory)
         requested_models = [p.stem for p in requested_models]
         # Local directory where dataset repo is cloned
         csv_results = get_csv_with_results(QUEUE_PATH)
-        if csv_results is None:
-            passed = False
-    if not passed:
-        print("No HuggingFace token provided. Skipping evaluation requests and results.")
 
     return eval_queue_repo, requested_models, csv_results
 
@@ -51,18 +54,21 @@ def upload_file(requested_model_name, path_or_fileobj):
     dest_repo_file = Path(EVAL_REQUESTS_PATH) / path_or_fileobj.name
     dest_repo_file = str(dest_repo_file)
     hf_api.upload_file(
-            path_or_fileobj=path_or_fileobj,
-            path_in_repo=str(dest_repo_file),
-            repo_id=QUEUE_REPO,
-            token=TOKEN_HUB,
-            repo_type="dataset",
-            commit_message=f"Add {requested_model_name} to eval queue")
+        path_or_fileobj=path_or_fileobj,
+        path_in_repo=str(dest_repo_file),
+        repo_id=QUEUE_REPO,
+        token=TOKEN_HUB,
+        repo_type="dataset",
+        commit_message=f"Add {requested_model_name} to eval queue",
+    )
+
 
 def get_all_requested_models(directory):
     directory = Path(directory)
     all_requested_models = list(directory.glob("*.txt"))
     return all_requested_models
 
+
 def get_csv_with_results(directory):
     directory = Path(directory)
     all_csv_files = list(directory.glob("*.csv"))
@@ -72,16 +78,21 @@ def get_csv_with_results(directory):
     return latest[0]
 
 
-
 def is_model_on_hub(model_name, revision="main") -> bool:
     try:
-        model_name = model_name.replace(" ","")
+        model_name = model_name.replace(" ", "")
         author = model_name.split("/")[0]
         model_id = model_name.split("/")[1]
         if len(author) == 0 or len(model_id) == 0:
-            return False, "is not a valid model name. Please use the format `author/model_name`."
-    except Exception as e:
-        return False, "is not a valid model name. Please use the format `author/model_name`."
+            return (
+                False,
+                "is not a valid model name. Please use the format `author/model_name`.",
+            )
+    except Exception:
+        return (
+            False,
+            "is not a valid model name. Please use the format `author/model_name`.",
+        )
 
     try:
         models = list(hf_api.list_models(author=author, search=model_id))