hf auth

app.py

@@ -58,6 +58,18 @@ from esm.utils.structure.protein_chain import ProteinChain
 from transformers import AutoTokenizer
 import utils
 
+from huggingface_hub import get_hf_file_metadata
+from huggingface_hub.utils import GatedRepoError
+
+def check_permissions(token: Optional[str] = None) -> None:
+    if token is None:
+        raise gr.Error("Please log in to use this Space")
+    try:
+        get_hf_file_metadata(repo_id="EvolutionaryScale/esm3-sm-open-v1", filename="config.json")
+        return
+    except GatedRepoError:
+        raise gr.Error("You must have access to ... to run this Space. Please go through the gating process and come back.")
+
 def validate_sequence(sequence):
     if not sequence:
         return None
@@ -354,7 +366,8 @@ with dyna1_app:
         outputs=[esm3_inputs, esm2_inputs, results_esm3, results_esm2, examples_esm3]
     )
 
-    def predict_esm3(name, sequence, pdb_id, pdb_file, chain_id, use_pdb_seq):
+    def predict_esm3(oauth_token: gr.OAuthToken | None, name, sequence, pdb_id, pdb_file, chain_id, use_pdb_seq):
+        check_permissions(oauth_token.token)
         csv_output, pdb_output = predict_dynamics(
             sequence=sequence,
             pdb_input=pdb_id if pdb_id else pdb_file,
@@ -378,7 +391,7 @@ with dyna1_app:
 
     submit_btn_esm3.click(
         fn=predict_esm3,
-        inputs=[name_input, sequence_input_esm3, pdb_id, pdb_file, chain_id, use_pdb_seq],
+        inputs=[gr.OAuthToken(), name_input, sequence_input_esm3, pdb_id, pdb_file, chain_id, use_pdb_seq],
         outputs=[csv_output_esm3, pdb_output_esm3]
     )