Bump version to 0.5.1 (#223)

README.md

@@ -12,7 +12,7 @@ For more information on the model's performance and capabilities, see our [techn
 
 ```shell
 # version on pypi:
-pip install chai_lab==0.5.0
+pip install chai_lab==0.5.1
 
 # newest available version (updates daily to test features that weren't released yet):
 pip install git+https://github.com/chaidiscovery/chai-lab.git
@@ -123,7 +123,7 @@ Devcontainers work on local Linux setup, and on remote machines over an SSH conn
 Since this is an initial release, we expect to make some breaking changes to the API and are not guaranteeing backwards compatibility. We recommend pinning the current version in your requirements, i.e.:
 
 ```
-chai_lab==0.5.0
+chai_lab==0.5.1
 ```
 
 ## Citations

chai_lab/__init__.py

@@ -2,4 +2,4 @@
 # Licensed under the Apache License, Version 2.0.
 # See the LICENSE file for details.
 
-__version__ = "0.5.0"
+__version__ = "0.5.1"

chai_lab/data/dataset/msas/colabfold.py

@@ -390,6 +390,9 @@ def generate_colabfold_msas(
         # Generate MSAs for each protein chain
         logger.info(f"Running MSA generation for {len(protein_seqs)} protein sequences")
 
+        # Identify ourselves to the ColabFold server
+        user_agent = f"chai-lab/{__version__} [email protected]"
+
         # In paired mode, mmseqs2 returns paired a3ms where all a3ms have the same number of rows
         # and each row is already paired to have the same species. As such, we insert pairing key
         # as the i-th index of the sequence so long as it isn't a padding sequence (all -)
@@ -400,7 +403,7 @@ def generate_colabfold_msas(
                 mmseqs_paired_dir,
                 use_pairing=True,
                 host_url=msa_server_url,
-                user_agent=f"chai-lab/{__version__} [email protected]",
+                user_agent=user_agent,
             )
         else:
             # If we only have a single protein chain, there are no paired MSAs by definition
@@ -413,7 +416,7 @@ def generate_colabfold_msas(
             mmseqs_dir,
             use_pairing=False,
             host_url=msa_server_url,
-            user_agent=f"chai-lab/{__version__} [email protected]",
+            user_agent=user_agent,
         )
 
         # Process the MSAs into our internal format