Support Python 3.14 (#4138)

Co-authored-by: Douwe Maan <douwe@pydantic.dev>
Co-authored-by: David Sanchez <64162682+dsfaccini@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: 4 people

.github/workflows/ci.yml

@@ -102,11 +102,11 @@ jobs:
         && 'depot-ubuntu-24.04-4'
         || 'ubuntu-latest'
       }}
-    timeout-minutes: 20
+    timeout-minutes: 15
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
         install:
           - name: pydantic-ai-slim
             command: "--package pydantic-ai-slim"
@@ -163,11 +163,11 @@ jobs:
         && 'depot-ubuntu-24.04-4'
         || 'ubuntu-latest'
       }}
-    timeout-minutes: 20
+    timeout-minutes: 15
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
     env:
       CI: true
       COVERAGE_PROCESS_START: ./pyproject.toml
@@ -212,7 +212,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
     env:
       CI: true
     steps:

.python-version

@@ -32,6 +32,7 @@ classifiers = [
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
     "Intended Audience :: Developers",
     "Intended Audience :: Information Technology",
     "Intended Audience :: System Administrators",

clai/pyproject.toml

@@ -364,7 +364,7 @@ export VOYAGE_API_KEY='your-api-key'
 
 You can then use the model:
 
-```python {title="voyageai_embeddings.py"}
+```python {title="voyageai_embeddings.py" max_py="3.13"}
 from pydantic_ai import Embedder
 
 embedder = Embedder('voyageai:voyage-3.5')
@@ -384,7 +384,7 @@ See the [VoyageAI Embeddings documentation](https://docs.voyageai.com/docs/embed
 
 VoyageAI models support additional settings via [`VoyageAIEmbeddingSettings`][pydantic_ai.embeddings.voyageai.VoyageAIEmbeddingSettings]:
 
-```python {title="voyageai_settings.py"}
+```python {title="voyageai_settings.py" max_py="3.13"}
 from pydantic_ai import Embedder
 from pydantic_ai.embeddings.voyageai import VoyageAIEmbeddingSettings
 
@@ -590,7 +590,7 @@ pip/uv-add "pydantic-ai-slim[sentence-transformers]"
 
 #### Usage
 
-```python {title="sentence_transformers_embeddings.py"}
+```python {title="sentence_transformers_embeddings.py" max_py="3.13"}
 from pydantic_ai import Embedder
 
 # Model is downloaded from Hugging Face on first use
@@ -611,7 +611,7 @@ See the [Sentence-Transformers pretrained models](https://www.sbert.net/docs/sen
 
 Control which device to use for inference:
 
-```python {title="sentence_transformers_device.py"}
+```python {title="sentence_transformers_device.py" max_py="3.13"}
 from pydantic_ai import Embedder
 from pydantic_ai.embeddings.sentence_transformers import (
     SentenceTransformersEmbeddingSettings,
@@ -630,7 +630,7 @@ embedder = Embedder(
 
 If you need more control over model initialization:
 
-```python {title="sentence_transformers_instance.py"}
+```python {title="sentence_transformers_instance.py" max_py="3.13"}
 from sentence_transformers import SentenceTransformer
 
 from pydantic_ai import Embedder

docs/embeddings.md

@@ -32,6 +32,7 @@ classifiers = [
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
     "Intended Audience :: Developers",
     "Intended Audience :: Information Technology",
     "Intended Audience :: System Administrators",

examples/pyproject.toml

@@ -9,7 +9,7 @@
 from dataclasses import dataclass, field
 from functools import partial
 from inspect import Parameter, signature
-from typing import TYPE_CHECKING, Any, Concatenate, cast, get_origin
+from typing import TYPE_CHECKING, Any, Concatenate, Literal, cast, get_origin
 
 from pydantic import ConfigDict
 from pydantic._internal import _decorators, _generate_schema, _typing_extra
@@ -184,10 +184,8 @@ def function_schema(  # noqa: C901
         raise UserError(f'Error generating schema for {function.__qualname__}:\n  {error_details}')
 
     core_config = config_wrapper.core_config(None)
-    # noinspection PyTypedDict
-    core_config['extra_fields_behavior'] = 'allow' if var_kwargs_schema else 'forbid'
 
-    schema, single_arg_name = _build_schema(fields, var_kwargs_schema, gen_schema, core_config)
+    schema, single_arg_name = _build_schema(fields, var_kwargs_schema, core_config)
     schema = gen_schema.clean_schema(schema)
     # noinspection PyUnresolvedReferences
     schema_validator = create_schema_validator(
@@ -269,15 +267,13 @@ def _takes_ctx(callable_obj: TargetCallable[P, R]) -> TypeIs[WithCtx[P, R]]:  #
 def _build_schema(
     fields: dict[str, core_schema.TypedDictField],
     var_kwargs_schema: core_schema.CoreSchema | None,
-    gen_schema: _generate_schema.GenerateSchema,
     core_config: core_schema.CoreConfig,
 ) -> tuple[core_schema.CoreSchema, str | None]:
     """Generate a typed dict schema for function parameters.
 
     Args:
         fields: The fields to generate a typed dict schema for.
         var_kwargs_schema: The variable keyword arguments schema.
-        gen_schema: The `GenerateSchema` instance.
         core_config: The core configuration.
 
     Returns:
@@ -289,10 +285,12 @@ def _build_schema(
         if td_field['metadata']['is_model_like']:  # type: ignore
             return td_field['schema'], name
 
+    extra_behavior: Literal['allow', 'forbid'] = 'allow' if var_kwargs_schema else 'forbid'
     td_schema = core_schema.typed_dict_schema(
         fields,
         config=core_config,
-        extras_schema=gen_schema.generate_schema(var_kwargs_schema) if var_kwargs_schema else None,
+        extra_behavior=extra_behavior,
+        extras_schema=var_kwargs_schema,
     )
     return td_schema, None
 

pydantic_ai_slim/pydantic_ai/_function_schema.py

@@ -66,7 +66,7 @@ class SentenceTransformerEmbeddingModel(EmbeddingModel):
     for available models.
 
     Example:
-    ```python
+    ```python {max_py="3.13"}
     from sentence_transformers import SentenceTransformer
 
     from pydantic_ai.embeddings.sentence_transformers import (

pydantic_ai_slim/pydantic_ai/embeddings/sentence_transformers.py

@@ -90,7 +90,7 @@ class VoyageAIEmbeddingModel(EmbeddingModel):
     retrieval, with specialized models for code, finance, and legal domains.
 
     Example:
-    ```python
+    ```python {max_py="3.13"}
     from pydantic_ai.embeddings.voyageai import VoyageAIEmbeddingModel
 
     model = VoyageAIEmbeddingModel('voyage-3.5')

pydantic_ai_slim/pydantic_ai/embeddings/voyageai.py

@@ -137,7 +137,7 @@ def _set_scalar_text(self, element: ElementTree.Element, value: Any) -> bool:
         if value is None:
             element.text = self.none_str
         elif isinstance(value, str):
-            element.text = value
+            element.text = value.value if isinstance(value, Enum) else value
         elif isinstance(value, bytes | bytearray):
             element.text = value.decode(errors='ignore')
         elif isinstance(value, bool | int | float | Enum):

pydantic_ai_slim/pydantic_ai/format_prompt.py

@@ -236,21 +236,6 @@ class DeferredToolResults:
 
 
 class GenerateToolJsonSchema(GenerateJsonSchema):
-    def typed_dict_schema(self, schema: core_schema.TypedDictSchema) -> JsonSchemaValue:
-        json_schema = super().typed_dict_schema(schema)
-        # Workaround for https://github.com/pydantic/pydantic/issues/12123
-        if 'additionalProperties' not in json_schema:  # pragma: no branch
-            extra = schema.get('extra_behavior') or schema.get('config', {}).get('extra_fields_behavior')
-            if extra == 'allow':
-                extras_schema = schema.get('extras_schema', None)
-                if extras_schema is not None:
-                    json_schema['additionalProperties'] = self.generate_inner(extras_schema) or True
-                else:
-                    json_schema['additionalProperties'] = True  # pragma: no cover
-            elif extra == 'forbid':
-                json_schema['additionalProperties'] = False
-        return json_schema
-
     def _named_required_fields_schema(self, named_required_fields: Sequence[tuple[str, bool, Any]]) -> JsonSchemaValue:
         # Remove largely-useless property titles
         s = super()._named_required_fields_schema(named_required_fields)