Add OpenAI Responses API (#1256)

Co-authored-by: David Montague <[email protected]>

Author: Kludex

docs/models.md

@@ -128,6 +128,29 @@ agent = Agent(model)
 ...
 ```
 
+### OpenAI Responses API
+
+PydanticAI also supports OpenAI's [Responses API](https://platform.openai.com/docs/api-reference/responses) through the [`OpenAIResponsesModel`][pydantic_ai.models.openai.OpenAIResponsesModel] class.
+
+The Responses API has built-in tools that you can use instead of building your own:
+- [Web search](https://platform.openai.com/docs/guides/tools-web-search)
+- [File search](https://platform.openai.com/docs/guides/tools-file-search)
+- [Computer use](https://platform.openai.com/docs/guides/tools-computer-use)
+
+!!! warning "Work in progress"
+    We currently don't support the native OpenAI tools listed above in the `OpenAIResponsesModel` class.
+
+You can learn more about the differences between the Responses API and Chat Completions API in the [OpenAI API docs](https://platform.openai.com/docs/guides/responses-vs-chat-completions).
+
+```python {title="openai_responses_model.py"}
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIResponsesModel
+
+model = OpenAIResponsesModel('gpt-4o')
+agent = Agent(model)
+...
+```
+
 ## Anthropic
 
 ### Install

pydantic_ai_slim/pydantic_ai/_result.py

@@ -13,7 +13,7 @@
 from . import _utils, messages as _messages
 from .exceptions import ModelRetry
 from .result import ResultDataT, ResultDataT_inv, ResultValidatorFunc
-from .tools import AgentDepsT, RunContext, ToolDefinition
+from .tools import AgentDepsT, GenerateToolJsonSchema, RunContext, ToolDefinition
 
 T = TypeVar('T')
 """An invariant TypeVar."""
@@ -159,7 +159,9 @@ def __init__(self, response_type: type[ResultDataT], name: str, description: str
             self.type_adapter = TypeAdapter(response_type)
             outer_typed_dict_key: str | None = None
             # noinspection PyArgumentList
-            parameters_json_schema = _utils.check_object_json_schema(self.type_adapter.json_schema())
+            parameters_json_schema = _utils.check_object_json_schema(
+                self.type_adapter.json_schema(schema_generator=GenerateToolJsonSchema)
+            )
         else:
             response_data_typed_dict = TypedDict(  # noqa: UP013
                 'response_data_typed_dict',
@@ -168,7 +170,9 @@ def __init__(self, response_type: type[ResultDataT], name: str, description: str
             self.type_adapter = TypeAdapter(response_data_typed_dict)
             outer_typed_dict_key = 'response'
             # noinspection PyArgumentList
-            parameters_json_schema = _utils.check_object_json_schema(self.type_adapter.json_schema())
+            parameters_json_schema = _utils.check_object_json_schema(
+                self.type_adapter.json_schema(schema_generator=GenerateToolJsonSchema)
+            )
             # including `response_data_typed_dict` as a title here doesn't add anything and could confuse the LLM
             parameters_json_schema.pop('title')