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Bump version to 0.5.1 #223

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Dec 6, 2024
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Bump version to 0.5.1 #223

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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -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
Expand Down Expand Up @@ -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
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2 changes: 1 addition & 1 deletion chai_lab/__init__.py
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Expand Up @@ -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"
7 changes: 5 additions & 2 deletions chai_lab/data/dataset/msas/colabfold.py
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Expand Up @@ -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__} feedback@chaidiscovery.com"

# 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 -)
Expand 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__} feedback@chaidiscovery.com",
user_agent=user_agent,
)
else:
# If we only have a single protein chain, there are no paired MSAs by definition
Expand All @@ -413,7 +416,7 @@ def generate_colabfold_msas(
mmseqs_dir,
use_pairing=False,
host_url=msa_server_url,
user_agent=f"chai-lab/{__version__} feedback@chaidiscovery.com",
user_agent=user_agent,
)

# Process the MSAs into our internal format
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