Prompts support (#876)

Add support for the new openai prompts feature.

examples/basic/prompt_template.py

@@ -0,0 +1,79 @@
+import argparse
+import asyncio
+import random
+
+from agents import Agent, GenerateDynamicPromptData, Runner
+
+"""
+NOTE: This example will not work out of the box, because the default prompt ID will not be available
+in your project.
+
+To use it, please:
+1. Go to https://platform.openai.com/playground/prompts
+2. Create a new prompt variable, `poem_style`.
+3. Create a system prompt with the content:
+```
+Write a poem in {{poem_style}}
+```
+4. Run the example with the `--prompt-id` flag.
+"""
+
+DEFAULT_PROMPT_ID = "pmpt_6850729e8ba481939fd439e058c69ee004afaa19c520b78b"
+
+
+class DynamicContext:
+    def __init__(self, prompt_id: str):
+        self.prompt_id = prompt_id
+        self.poem_style = random.choice(["limerick", "haiku", "ballad"])
+        print(f"[debug] DynamicContext initialized with poem_style: {self.poem_style}")
+
+
+async def _get_dynamic_prompt(data: GenerateDynamicPromptData):
+    ctx: DynamicContext = data.context.context
+    return {
+        "id": ctx.prompt_id,
+        "version": "1",
+        "variables": {
+            "poem_style": ctx.poem_style,
+        },
+    }
+
+
+async def dynamic_prompt(prompt_id: str):
+    context = DynamicContext(prompt_id)
+
+    agent = Agent(
+        name="Assistant",
+        prompt=_get_dynamic_prompt,
+    )
+
+    result = await Runner.run(agent, "Tell me about recursion in programming.", context=context)
+    print(result.final_output)
+
+
+async def static_prompt(prompt_id: str):
+    agent = Agent(
+        name="Assistant",
+        prompt={
+            "id": prompt_id,
+            "version": "1",
+            "variables": {
+                "poem_style": "limerick",
+            },
+        },
+    )
+
+    result = await Runner.run(agent, "Tell me about recursion in programming.")
+    print(result.final_output)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dynamic", action="store_true")
+    parser.add_argument("--prompt-id", type=str, default=DEFAULT_PROMPT_ID)
+    args = parser.parse_args()
+
+    if args.dynamic:
+        asyncio.run(dynamic_prompt(args.prompt_id))
+    else:
+        asyncio.run(static_prompt(args.prompt_id))

pyproject.toml

@@ -7,7 +7,7 @@ requires-python = ">=3.9"
 license = "MIT"
 authors = [{ name = "OpenAI", email = "support@openai.com" }]
 dependencies = [
-    "openai>=1.81.0",
+    "openai>=1.87.0",
     "pydantic>=2.10, <3",
     "griffe>=1.5.6, <2",
     "typing-extensions>=4.12.2, <5",

src/agents/__init__.py

@@ -45,6 +45,7 @@ from .models.interface import Model, ModelProvider, ModelTracing
 from .models.openai_chatcompletions import OpenAIChatCompletionsModel
 from .models.openai_provider import OpenAIProvider
 from .models.openai_responses import OpenAIResponsesModel
+from .prompts import DynamicPromptFunction, GenerateDynamicPromptData, Prompt
 from .repl import run_demo_loop
 from .result import RunResult, RunResultStreaming
 from .run import RunConfig, Runner
@@ -178,6 +179,9 @@ __all__ = [
     "AgentsException",
     "InputGuardrailTripwireTriggered",
     "OutputGuardrailTripwireTriggered",
+    "DynamicPromptFunction",
+    "GenerateDynamicPromptData",
+    "Prompt",
     "MaxTurnsExceeded",
     "ModelBehaviorError",
     "UserError",

src/agents/agent.py

@@ -7,6 +7,7 @@ from collections.abc import Awaitable
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, cast
 
+from openai.types.responses.response_prompt_param import ResponsePromptParam
 from typing_extensions import NotRequired, TypeAlias, TypedDict
 
 from .agent_output import AgentOutputSchemaBase
@@ -17,6 +18,7 @@ from .logger import logger
 from .mcp import MCPUtil
 from .model_settings import ModelSettings
 from .models.interface import Model
+from .prompts import DynamicPromptFunction, Prompt, PromptUtil
 from .run_context import RunContextWrapper, TContext
 from .tool import FunctionTool, FunctionToolResult, Tool, function_tool
 from .util import _transforms
@@ -95,6 +97,12 @@ class Agent(Generic[TContext]):
     return a string.
     """
 
+    prompt: Prompt | DynamicPromptFunction | None = None
+    """A prompt object (or a function that returns a Prompt). Prompts allow you to dynamically
+    configure the instructions, tools and other config for an agent outside of your code. Only
+    usable with OpenAI models, using the Responses API.
+    """
+
     handoff_description: str | None = None
     """A description of the agent. This is used when the agent is used as a handoff, so that an
     LLM knows what it does and when to invoke it.
@@ -242,6 +250,12 @@ class Agent(Generic[TContext]):
 
         return None
 
+    async def get_prompt(
+        self, run_context: RunContextWrapper[TContext]
+    ) -> ResponsePromptParam | None:
+        """Get the prompt for the agent."""
+        return await PromptUtil.to_model_input(self.prompt, run_context, self)
+
     async def get_mcp_tools(self) -> list[Tool]:
         """Fetches the available tools from the MCP servers."""
         convert_schemas_to_strict = self.mcp_config.get("convert_schemas_to_strict", False)

src/agents/extensions/models/litellm_model.py

@@ -71,6 +71,7 @@ class LitellmModel(Model):
         handoffs: list[Handoff],
         tracing: ModelTracing,
         previous_response_id: str | None,
+        prompt: Any | None = None,
     ) -> ModelResponse:
         with generation_span(
             model=str(self.model),
@@ -88,6 +89,7 @@ class LitellmModel(Model):
                 span_generation,
                 tracing,
                 stream=False,
+                prompt=prompt,
             )
 
             assert isinstance(response.choices[0], litellm.types.utils.Choices)
@@ -153,8 +155,8 @@ class LitellmModel(Model):
         output_schema: AgentOutputSchemaBase | None,
         handoffs: list[Handoff],
         tracing: ModelTracing,
-        *,
         previous_response_id: str | None,
+        prompt: Any | None = None,
     ) -> AsyncIterator[TResponseStreamEvent]:
         with generation_span(
             model=str(self.model),
@@ -172,6 +174,7 @@ class LitellmModel(Model):
                 span_generation,
                 tracing,
                 stream=True,
+                prompt=prompt,
             )
 
             final_response: Response | None = None
@@ -202,6 +205,7 @@ class LitellmModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: Literal[True],
+        prompt: Any | None = None,
     ) -> tuple[Response, AsyncStream[ChatCompletionChunk]]: ...
 
     @overload
@@ -216,6 +220,7 @@ class LitellmModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: Literal[False],
+        prompt: Any | None = None,
     ) -> litellm.types.utils.ModelResponse: ...
 
     async def _fetch_response(
@@ -229,6 +234,7 @@ class LitellmModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: bool = False,
+        prompt: Any | None = None,
     ) -> litellm.types.utils.ModelResponse | tuple[Response, AsyncStream[ChatCompletionChunk]]:
         converted_messages = Converter.items_to_messages(input)
 

src/agents/models/interface.py

@@ -5,6 +5,8 @@ import enum
 from collections.abc import AsyncIterator
 from typing import TYPE_CHECKING
 
+from openai.types.responses.response_prompt_param import ResponsePromptParam
+
 from ..agent_output import AgentOutputSchemaBase
 from ..handoffs import Handoff
 from ..items import ModelResponse, TResponseInputItem, TResponseStreamEvent
@@ -46,6 +48,7 @@ class Model(abc.ABC):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None,
     ) -> ModelResponse:
         """Get a response from the model.
 
@@ -59,6 +62,7 @@ class Model(abc.ABC):
             tracing: Tracing configuration.
             previous_response_id: the ID of the previous response. Generally not used by the model,
                 except for the OpenAI Responses API.
+            prompt: The prompt config to use for the model.
 
         Returns:
             The full model response.
@@ -77,6 +81,7 @@ class Model(abc.ABC):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None,
     ) -> AsyncIterator[TResponseStreamEvent]:
         """Stream a response from the model.
 
@@ -90,6 +95,7 @@ class Model(abc.ABC):
             tracing: Tracing configuration.
             previous_response_id: the ID of the previous response. Generally not used by the model,
                 except for the OpenAI Responses API.
+            prompt: The prompt config to use for the model.
 
         Returns:
             An iterator of response stream events, in OpenAI Responses format.

src/agents/models/openai_chatcompletions.py

@@ -9,6 +9,7 @@ from openai import NOT_GIVEN, AsyncOpenAI, AsyncStream
 from openai.types import ChatModel
 from openai.types.chat import ChatCompletion, ChatCompletionChunk
 from openai.types.responses import Response
+from openai.types.responses.response_prompt_param import ResponsePromptParam
 from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
 
 from .. import _debug
@@ -53,6 +54,7 @@ class OpenAIChatCompletionsModel(Model):
         handoffs: list[Handoff],
         tracing: ModelTracing,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None = None,
     ) -> ModelResponse:
         with generation_span(
             model=str(self.model),
@@ -69,6 +71,7 @@ class OpenAIChatCompletionsModel(Model):
                 span_generation,
                 tracing,
                 stream=False,
+                prompt=prompt,
             )
 
             first_choice = response.choices[0]
@@ -136,8 +139,8 @@ class OpenAIChatCompletionsModel(Model):
         output_schema: AgentOutputSchemaBase | None,
         handoffs: list[Handoff],
         tracing: ModelTracing,
-        *,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None = None,
     ) -> AsyncIterator[TResponseStreamEvent]:
         """
         Yields a partial message as it is generated, as well as the usage information.
@@ -157,6 +160,7 @@ class OpenAIChatCompletionsModel(Model):
                 span_generation,
                 tracing,
                 stream=True,
+                prompt=prompt,
             )
 
             final_response: Response | None = None
@@ -187,6 +191,7 @@ class OpenAIChatCompletionsModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: Literal[True],
+        prompt: ResponsePromptParam | None = None,
     ) -> tuple[Response, AsyncStream[ChatCompletionChunk]]: ...
 
     @overload
@@ -201,6 +206,7 @@ class OpenAIChatCompletionsModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: Literal[False],
+        prompt: ResponsePromptParam | None = None,
     ) -> ChatCompletion: ...
 
     async def _fetch_response(
@@ -214,6 +220,7 @@ class OpenAIChatCompletionsModel(Model):
         span: Span[GenerationSpanData],
         tracing: ModelTracing,
         stream: bool = False,
+        prompt: ResponsePromptParam | None = None,
     ) -> ChatCompletion | tuple[Response, AsyncStream[ChatCompletionChunk]]:
         converted_messages = Converter.items_to_messages(input)
 

src/agents/models/openai_responses.py

@@ -17,6 +17,7 @@ from openai.types.responses import (
     WebSearchToolParam,
     response_create_params,
 )
+from openai.types.responses.response_prompt_param import ResponsePromptParam
 
 from .. import _debug
 from ..agent_output import AgentOutputSchemaBase
@@ -74,6 +75,7 @@ class OpenAIResponsesModel(Model):
         handoffs: list[Handoff],
         tracing: ModelTracing,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None = None,
     ) -> ModelResponse:
         with response_span(disabled=tracing.is_disabled()) as span_response:
             try:
@@ -86,6 +88,7 @@ class OpenAIResponsesModel(Model):
                     handoffs,
                     previous_response_id,
                     stream=False,
+                    prompt=prompt,
                 )
 
                 if _debug.DONT_LOG_MODEL_DATA:
@@ -141,6 +144,7 @@ class OpenAIResponsesModel(Model):
         handoffs: list[Handoff],
         tracing: ModelTracing,
         previous_response_id: str | None,
+        prompt: ResponsePromptParam | None = None,
     ) -> AsyncIterator[ResponseStreamEvent]:
         """
         Yields a partial message as it is generated, as well as the usage information.
@@ -156,6 +160,7 @@ class OpenAIResponsesModel(Model):
                     handoffs,
                     previous_response_id,
                     stream=True,
+                    prompt=prompt,
                 )
 
                 final_response: Response | None = None
@@ -192,6 +197,7 @@ class OpenAIResponsesModel(Model):
         handoffs: list[Handoff],
         previous_response_id: str | None,
         stream: Literal[True],
+        prompt: ResponsePromptParam | None = None,
     ) -> AsyncStream[ResponseStreamEvent]: ...
 
     @overload
@@ -205,6 +211,7 @@ class OpenAIResponsesModel(Model):
         handoffs: list[Handoff],
         previous_response_id: str | None,
         stream: Literal[False],
+        prompt: ResponsePromptParam | None = None,
     ) -> Response: ...
 
     async def _fetch_response(
@@ -217,6 +224,7 @@ class OpenAIResponsesModel(Model):
         handoffs: list[Handoff],
         previous_response_id: str | None,
         stream: Literal[True] | Literal[False] = False,
+        prompt: ResponsePromptParam | None = None,
     ) -> Response | AsyncStream[ResponseStreamEvent]:
         list_input = ItemHelpers.input_to_new_input_list(input)
 
@@ -252,6 +260,7 @@ class OpenAIResponsesModel(Model):
             input=list_input,
             include=converted_tools.includes,
             tools=converted_tools.tools,
+            prompt=self._non_null_or_not_given(prompt),
             temperature=self._non_null_or_not_given(model_settings.temperature),
             top_p=self._non_null_or_not_given(model_settings.top_p),
             truncation=self._non_null_or_not_given(model_settings.truncation),

src/agents/prompts.py

@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import inspect
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Callable
+
+from openai.types.responses.response_prompt_param import (
+    ResponsePromptParam,
+    Variables as ResponsesPromptVariables,
+)
+from typing_extensions import NotRequired, TypedDict
+
+from agents.util._types import MaybeAwaitable
+
+from .exceptions import UserError
+from .run_context import RunContextWrapper
+
+if TYPE_CHECKING:
+    from .agent import Agent
+
+
+class Prompt(TypedDict):
+    """Prompt configuration to use for interacting with an OpenAI model."""
+
+    id: str
+    """The unique ID of the prompt."""
+
+    version: NotRequired[str]
+    """Optional version of the prompt."""
+
+    variables: NotRequired[dict[str, ResponsesPromptVariables]]
+    """Optional variables to substitute into the prompt."""
+
+
+@dataclass
+class GenerateDynamicPromptData:
+    """Inputs to a function that allows you to dynamically generate a prompt."""
+
+    context: RunContextWrapper[Any]
+    """The run context."""
+
+    agent: Agent[Any]
+    """The agent for which the prompt is being generated."""
+
+
+DynamicPromptFunction = Callable[[GenerateDynamicPromptData], MaybeAwaitable[Prompt]]
+"""A function that dynamically generates a prompt."""
+
+
+class PromptUtil:
+    @staticmethod
+    async def to_model_input(
+        prompt: Prompt | DynamicPromptFunction | None,
+        context: RunContextWrapper[Any],
+        agent: Agent[Any],
+    ) -> ResponsePromptParam | None:
+        if prompt is None:
+            return None
+
+        resolved_prompt: Prompt
+        if isinstance(prompt, dict):
+            resolved_prompt = prompt
+        else:
+            func_result = prompt(GenerateDynamicPromptData(context=context, agent=agent))
+            if inspect.isawaitable(func_result):
+                resolved_prompt = await func_result
+            else:
+                resolved_prompt = func_result
+            if not isinstance(resolved_prompt, dict):
+                raise UserError("Dynamic prompt function must return a Prompt")
+
+        return {
+            "id": resolved_prompt["id"],
+            "version": resolved_prompt.get("version"),
+            "variables": resolved_prompt.get("variables"),
+        }

src/agents/run.py

@@ -6,6 +6,9 @@ from dataclasses import dataclass, field
 from typing import Any, cast
 
 from openai.types.responses import ResponseCompletedEvent
+from openai.types.responses.response_prompt_param import (
+    ResponsePromptParam,
+)
 
 from ._run_impl import (
     AgentToolUseTracker,
@@ -682,7 +685,10 @@ class Runner:
         streamed_result.current_agent = agent
         streamed_result._current_agent_output_schema = output_schema
 
-        system_prompt = await agent.get_system_prompt(context_wrapper)
+        system_prompt, prompt_config = await asyncio.gather(
+            agent.get_system_prompt(context_wrapper),
+            agent.get_prompt(context_wrapper),
+        )
 
         handoffs = cls._get_handoffs(agent)
         model = cls._get_model(agent, run_config)
@@ -706,6 +712,7 @@ class Runner:
                 run_config.tracing_disabled, run_config.trace_include_sensitive_data
             ),
             previous_response_id=previous_response_id,
+            prompt=prompt_config,
         ):
             if isinstance(event, ResponseCompletedEvent):
                 usage = (
@@ -777,7 +784,10 @@ class Runner:
                 ),
             )
 
-        system_prompt = await agent.get_system_prompt(context_wrapper)
+        system_prompt, prompt_config = await asyncio.gather(
+            agent.get_system_prompt(context_wrapper),
+            agent.get_prompt(context_wrapper),
+        )
 
         output_schema = cls._get_output_schema(agent)
         handoffs = cls._get_handoffs(agent)
@@ -795,6 +805,7 @@ class Runner:
             run_config,
             tool_use_tracker,
             previous_response_id,
+            prompt_config,
         )
 
         return await cls._get_single_step_result_from_response(
@@ -938,6 +949,7 @@ class Runner:
         run_config: RunConfig,
         tool_use_tracker: AgentToolUseTracker,
         previous_response_id: str | None,
+        prompt_config: ResponsePromptParam | None,
     ) -> ModelResponse:
         model = cls._get_model(agent, run_config)
         model_settings = agent.model_settings.resolve(run_config.model_settings)
@@ -954,6 +966,7 @@ class Runner:
                 run_config.tracing_disabled, run_config.trace_include_sensitive_data
             ),
             previous_response_id=previous_response_id,
+            prompt=prompt_config,
         )
 
         context_wrapper.usage.add(new_response.usage)

src/agents/tool_context.py

@@ -7,6 +7,7 @@ from .run_context import RunContextWrapper, TContext
 def _assert_must_pass_tool_call_id() -> str:
     raise ValueError("tool_call_id must be passed to ToolContext")
 
+
 @dataclass
 class ToolContext(RunContextWrapper[TContext]):
     """The context of a tool call."""

tests/fake_model.py

@@ -61,6 +61,7 @@ class FakeModel(Model):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: Any | None,
     ) -> ModelResponse:
         self.last_turn_args = {
             "system_instructions": system_instructions,
@@ -103,6 +104,7 @@ class FakeModel(Model):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: Any | None,
     ) -> AsyncIterator[TResponseStreamEvent]:
         self.last_turn_args = {
             "system_instructions": system_instructions,

tests/models/test_litellm_chatcompletions_stream.py

@@ -90,6 +90,7 @@ async def test_stream_response_yields_events_for_text_content(monkeypatch) -> No
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # We expect a response.created, then a response.output_item.added, content part added,
@@ -182,6 +183,7 @@ async def test_stream_response_yields_events_for_refusal_content(monkeypatch) ->
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # Expect sequence similar to text: created, output_item.added, content part added,
@@ -270,6 +272,7 @@ async def test_stream_response_yields_events_for_tool_call(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # Sequence should be: response.created, then after loop we expect function call-related events:

tests/test_agent_prompt.py

@@ -0,0 +1,97 @@
+import pytest
+
+from agents import Agent, Prompt, RunContextWrapper, Runner
+
+from .fake_model import FakeModel
+from .test_responses import get_text_message
+
+
+class PromptCaptureFakeModel(FakeModel):
+    """Subclass of FakeModel that records the prompt passed to the model."""
+
+    def __init__(self):
+        super().__init__()
+        self.last_prompt = None
+
+    async def get_response(
+        self,
+        system_instructions,
+        input,
+        model_settings,
+        tools,
+        output_schema,
+        handoffs,
+        tracing,
+        *,
+        previous_response_id,
+        prompt,
+    ):
+        # Record the prompt that the agent resolved and passed in.
+        self.last_prompt = prompt
+        return await super().get_response(
+            system_instructions,
+            input,
+            model_settings,
+            tools,
+            output_schema,
+            handoffs,
+            tracing,
+            previous_response_id=previous_response_id,
+            prompt=prompt,
+        )
+
+
+@pytest.mark.asyncio
+async def test_static_prompt_is_resolved_correctly():
+    static_prompt: Prompt = {
+        "id": "my_prompt",
+        "version": "1",
+        "variables": {"some_var": "some_value"},
+    }
+
+    agent = Agent(name="test", prompt=static_prompt)
+    context_wrapper = RunContextWrapper(context=None)
+
+    resolved = await agent.get_prompt(context_wrapper)
+
+    assert resolved == {
+        "id": "my_prompt",
+        "version": "1",
+        "variables": {"some_var": "some_value"},
+    }
+
+
+@pytest.mark.asyncio
+async def test_dynamic_prompt_is_resolved_correctly():
+    dynamic_prompt_value: Prompt = {"id": "dyn_prompt", "version": "2"}
+
+    def dynamic_prompt_fn(_data):
+        return dynamic_prompt_value
+
+    agent = Agent(name="test", prompt=dynamic_prompt_fn)
+    context_wrapper = RunContextWrapper(context=None)
+
+    resolved = await agent.get_prompt(context_wrapper)
+
+    assert resolved == {"id": "dyn_prompt", "version": "2", "variables": None}
+
+
+@pytest.mark.asyncio
+async def test_prompt_is_passed_to_model():
+    static_prompt: Prompt = {"id": "model_prompt"}
+
+    model = PromptCaptureFakeModel()
+    agent = Agent(name="test", model=model, prompt=static_prompt)
+
+    # Ensure the model returns a simple message so the run completes in one turn.
+    model.set_next_output([get_text_message("done")])
+
+    await Runner.run(agent, input="hello")
+
+    # The model should have received the prompt resolved by the agent.
+    expected_prompt = {
+        "id": "model_prompt",
+        "version": None,
+        "variables": None,
+    }
+    assert model.last_prompt == expected_prompt

tests/test_openai_chatcompletions.py

@@ -77,6 +77,7 @@ async def test_get_response_with_text_message(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     )
     # Should have produced exactly one output message with one text part
     assert isinstance(resp, ModelResponse)
@@ -128,6 +129,7 @@ async def test_get_response_with_refusal(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     )
     assert len(resp.output) == 1
     assert isinstance(resp.output[0], ResponseOutputMessage)
@@ -180,6 +182,7 @@ async def test_get_response_with_tool_call(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     )
     # Expect a message item followed by a function tool call item.
     assert len(resp.output) == 2
@@ -221,6 +224,7 @@ async def test_get_response_with_no_message(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     )
     assert resp.output == []
 

tests/test_openai_chatcompletions_stream.py

@@ -90,6 +90,7 @@ async def test_stream_response_yields_events_for_text_content(monkeypatch) -> No
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # We expect a response.created, then a response.output_item.added, content part added,
@@ -182,6 +183,7 @@ async def test_stream_response_yields_events_for_refusal_content(monkeypatch) ->
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # Expect sequence similar to text: created, output_item.added, content part added,
@@ -270,6 +272,7 @@ async def test_stream_response_yields_events_for_tool_call(monkeypatch) -> None:
         handoffs=[],
         tracing=ModelTracing.DISABLED,
         previous_response_id=None,
+        prompt=None,
     ):
         output_events.append(event)
     # Sequence should be: response.created, then after loop we expect function call-related events:

tests/test_responses_tracing.py

@@ -71,6 +71,7 @@ async def test_get_response_creates_trace(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             return DummyResponse()
 
@@ -115,6 +116,7 @@ async def test_non_data_tracing_doesnt_set_response_id(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             return DummyResponse()
 
@@ -157,6 +159,7 @@ async def test_disable_tracing_does_not_create_span(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             return DummyResponse()
 
@@ -196,6 +199,7 @@ async def test_stream_response_creates_trace(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             class DummyStream:
                 async def __aiter__(self):
@@ -249,6 +253,7 @@ async def test_stream_non_data_tracing_doesnt_set_response_id(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             class DummyStream:
                 async def __aiter__(self):
@@ -301,6 +306,7 @@ async def test_stream_disabled_tracing_doesnt_create_span(monkeypatch):
             handoffs,
             prev_response_id,
             stream,
+            prompt,
         ):
             class DummyStream:
                 async def __aiter__(self):

tests/voice/test_workflow.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import json
 from collections.abc import AsyncIterator
+from typing import Any
 
 import pytest
 from inline_snapshot import snapshot
@@ -53,6 +54,7 @@ class FakeStreamingModel(Model):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: Any | None,
     ) -> ModelResponse:
         raise NotImplementedError("Not implemented")
 
@@ -67,6 +69,7 @@ class FakeStreamingModel(Model):
         tracing: ModelTracing,
         *,
         previous_response_id: str | None,
+        prompt: Any | None,
     ) -> AsyncIterator[TResponseStreamEvent]:
         output = self.get_next_output()
         for item in output:

uv.lock

@@ -1461,7 +1461,7 @@ wheels = [
 
 [[package]]
 name = "openai"
-version = "1.81.0"
+version = "1.87.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
@@ -1473,9 +1473,9 @@ dependencies = [
     { name = "tqdm" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/1c/89/a1e4f3fa7ca4f7fec90dbf47d93b7cd5ff65924926733af15044e302a192/openai-1.81.0.tar.gz", hash = "sha256:349567a8607e0bcffd28e02f96b5c2397d0d25d06732d90ab3ecbf97abf030f9", size = 456861 }
+sdist = { url = "https://files.pythonhosted.org/packages/47/ed/2b3f6c7e950784e9442115ab8ebeff514d543fb33da10607b39364645a75/openai-1.87.0.tar.gz", hash = "sha256:5c69764171e0db9ef993e7a4d8a01fd8ff1026b66f8bdd005b9461782b6e7dfc", size = 470880 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/02/66/bcc7f9bf48e8610a33e3b5c96a5a644dad032d92404ea2a5e8b43ba067e8/openai-1.81.0-py3-none-any.whl", hash = "sha256:1c71572e22b43876c5d7d65ade0b7b516bb527c3d44ae94111267a09125f7bae", size = 717529 },
+    { url = "https://files.pythonhosted.org/packages/36/ac/313ded47ce1d5bc2ec02ed5dd5506bf5718678a4655ac20f337231d9aae3/openai-1.87.0-py3-none-any.whl", hash = "sha256:f9bcae02ac4fff6522276eee85d33047335cfb692b863bd8261353ce4ada5692", size = 734368 },
 ]
 
 [[package]]
@@ -1536,7 +1536,7 @@ requires-dist = [
     { name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.67.4.post1,<2" },
     { name = "mcp", marker = "python_full_version >= '3.10'", specifier = ">=1.9.4,<2" },
     { name = "numpy", marker = "python_full_version >= '3.10' and extra == 'voice'", specifier = ">=2.2.0,<3" },
-    { name = "openai", specifier = ">=1.81.0" },
+    { name = "openai", specifier = ">=1.87.0" },
     { name = "pydantic", specifier = ">=2.10,<3" },
     { name = "requests", specifier = ">=2.0,<3" },
     { name = "types-requests", specifier = ">=2.0,<3" },