diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index c7b9913f..24e61b88 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -47,7 +47,7 @@ jobs:
       - name: Build
         run: |
           pip install -U wheel
-          pip install .[all,dev]
+          pip install .[all,dev] fasttext==0.9.2
           python -c "import nltk; nltk.download(['punkt', 'punkt_tab', 'averaged_perceptron_tagger_eng'])"
           python --version
           make data coverage
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 163e6c41..79f065d4 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,13 +1,14 @@
 repos:
   - repo: https://github.com/pycqa/pylint
-    rev: v2.16.2
+    rev: v3.3.1
     hooks:
     - id: pylint
       args:
       - -d import-error
       - -d duplicate-code
+      - -d too-many-positional-arguments
   - repo: https://github.com/ambv/black
-    rev: 23.1.0
+    rev: 24.10.0
     hooks:
     - id: black
       language_version: python3
diff --git a/examples/baseball.py b/examples/baseball.py
index 58f81cb3..80cd7207 100644
--- a/examples/baseball.py
+++ b/examples/baseball.py
@@ -497,7 +497,7 @@ class Application:
 
         st.markdown("Find players with similar statistics.")
 
-        category = self.category("Batting", "searchcategory")
+        stats, category = None, self.category("Batting", "searchcategory")
         with st.form("search"):
             if category == "Batting":
                 stats, columns = self.batting, self.batting.columns[:-6]
diff --git a/src/python/txtai/embeddings/index/__init__.py b/src/python/txtai/embeddings/index/__init__.py
index 013d4191..5b3a1f18 100644
--- a/src/python/txtai/embeddings/index/__init__.py
+++ b/src/python/txtai/embeddings/index/__init__.py
@@ -2,7 +2,6 @@
 Index imports
 """
 
-
 from .action import Action
 from .autoid import AutoId
 from .configuration import Configuration
diff --git a/src/python/txtai/models/models.py b/src/python/txtai/models/models.py
index 3c42da36..ce0cc2a8 100644
--- a/src/python/txtai/models/models.py
+++ b/src/python/txtai/models/models.py
@@ -127,13 +127,11 @@ class Models:
         return (
             deviceid
             if isinstance(deviceid, str)
-            else "cpu"
-            if deviceid < 0
-            else f"cuda:{deviceid}"
-            if torch.cuda.is_available()
-            else "mps"
-            if Models.hasmpsdevice()
-            else Models.finddevice()
+            else (
+                "cpu"
+                if deviceid < 0
+                else f"cuda:{deviceid}" if torch.cuda.is_available() else "mps" if Models.hasmpsdevice() else Models.finddevice()
+            )
         )
 
     @staticmethod
diff --git a/src/python/txtai/models/pooling/__init__.py b/src/python/txtai/models/pooling/__init__.py
index 41aa71a5..f5a8defe 100644
--- a/src/python/txtai/models/pooling/__init__.py
+++ b/src/python/txtai/models/pooling/__init__.py
@@ -2,7 +2,6 @@
 Pooling imports
 """
 
-
 from .base import Pooling
 from .cls import ClsPooling
 from .factory import PoolingFactory
diff --git a/src/python/txtai/scoring/pgtext.py b/src/python/txtai/scoring/pgtext.py
index e3bea03b..4646f05d 100644
--- a/src/python/txtai/scoring/pgtext.py
+++ b/src/python/txtai/scoring/pgtext.py
@@ -127,9 +127,11 @@ class PGText(Scoring):
                 MetaData(),
                 Column("indexid", Integer, primary_key=True, autoincrement=False),
                 Column("text", Text),
-                Column("vector", TSVECTOR, Computed(f"to_tsvector('{self.language}', text)", persisted=True))
-                if self.engine.dialect.name == "postgresql"
-                else Column("vector", Integer),
+                (
+                    Column("vector", TSVECTOR, Computed(f"to_tsvector('{self.language}', text)", persisted=True))
+                    if self.engine.dialect.name == "postgresql"
+                    else Column("vector", Integer)
+                ),
             )
 
             # Create ANN index - inner product is equal to cosine similarity on normalized vectors