Merge branch 'release-1.0' into 'main'

Bump release to 1.0

See merge request olenyi/vespa-cli!11

Author: Tobias Olenyi

pyproject.toml

@@ -1,8 +1,27 @@
 [tool.poetry]
-name = "vespa"
-version = "0.9.0-beta"
-description = ""
+name = "vespa-effect"
+version = "1.0.0"
+description = "Predictor for single-amino acid variant effects in protein sequences (https://doi.org/10.1007/s00439-021-02411-y)"
 authors = ["Tobias O <tobias.olenyi@tum.de>", "Duc Anh Le <ducanh.le@tum.de>"]
+license = 'AGPL-3.0-or-later'
+readme = "README.md"
+homepage = ""
+repository = "https://github.com/Rostlab/VESPA"
+keywords = [
+    "Embeddings",
+    "Protein-Sequences",
+    "Machine-Learning",
+    "Mutation-Effect"
+]
+
+include = [
+    "LICENSE",
+    "CODE_OF_CONDUCT.md",
+     "models/*"
+]
+packages = [
+    {include = "vespa"}
+]
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
@@ -29,14 +48,3 @@ vespa = 'vespa.scripts.meta:main'
 vespa_conspred = 'vespa.scripts.conspred:main'
 vespa_run = 'vespa.scripts.vespa_run:main'
 vespa_emb = 'vespa.scripts.embedding:main'
-
-[tool.poetry2conda]
-name = "vespa-env"
-
-[tool.poetry2conda.dependencies]
-poetry2conda = { channel = "conda-forge" }
-sentencepiece = { channel = "conda-forge" }
-transformers = { channel = "conda-forge" }
-torch = { channel = "conda-forge" }
-sklearn = { channel = "conda-forge" }
-

vespa/__init__.py

@@ -1,7 +1,7 @@
 __author__ = "Tobias O, Michael H., Celine M., Duc Anh L."
 __copyright__ = "Copyright 2022, Rostlab"
 __license__ = "AGPL-3.0-or-later"
-__version__ = "0.9.0b"
+__version__ = "1.0.0"
 __maintainer__ = ["Duc Anh L.", "Tobias O."]
 __email__ = ""
 __status__ = "Production"

vespa/scripts/embedding.py

@@ -1,6 +1,6 @@
 import argparse
 from vespa.predict.embedding import *
-from vespa.predict.config import VERBOSE
+from vespa.predict.config import VERBOSE, CACHE_DIR
 
 
 def setup_argparse():
@@ -29,7 +29,7 @@ def setup_argparse():
     )
 
     parser.add_argument(
-        "--language_model_cache",
+        "--prott5_weights_cache",
         required=False,
         type=Path,
         default=Path(CACHE_DIR),
@@ -55,7 +55,7 @@ def main():
     arguments = {
         'seq_path': args.input,
         'out_path': args.output,
-        'cache_dir': args.language_model_cache
+        'cache_dir': args.prott5_weights_cache
     }
     run_embedding(**arguments)
 

vespa/scripts/logodds.py

@@ -16,7 +16,7 @@
 """
 import argparse
 
-from vespa.predict.config import VERBOSE
+from vespa.predict.config import VERBOSE, CACHE_DIR
 from vespa.predict.logodds import *
 from vespa.predict import utils
 
@@ -101,7 +101,7 @@ def create_arg_parser():
     )
 
     parser.add_argument(
-        "--language_model_cache",
+        "--prott5_weights_cache",
         required=False,
         type=Path,
         default=Path(CACHE_DIR),
@@ -169,7 +169,7 @@ def main():
         'reconstruction_output': args.reconstruction_output,
         'single_csv': args.single_csv,
         'csv_dir': args.csv_dir,
-        'cache_dir': args.language_model_cache
+        'cache_dir': args.prott5_weights_cache
     }
     run_logodds(**arguments)