Add types for Responses API (with tests)

Co-authored-by: Cursor <cursoragent@cursor.com>

Author: rushitat

src/gradient/types/responses/__init__.py

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+# Types for the Responses API. See docs/RESPONSES_API_PR_BREAKDOWN.md.
+
+from __future__ import annotations
+
+from .response_create_params import (
+    ResponseTool as ResponseTool,
+    ResponseInputItem as ResponseInputItem,
+    ResponseToolChoice as ResponseToolChoice,
+    ResponseCreateParams as ResponseCreateParams,
+    ResponseToolFunction as ResponseToolFunction,
+    ResponseToolChoiceNamed as ResponseToolChoiceNamed,
+    ResponseInputUserMessage as ResponseInputUserMessage,
+    ResponseInputFunctionCall as ResponseInputFunctionCall,
+    ResponseToolChoiceFunction as ResponseToolChoiceFunction,
+    ResponseInputFunctionCallOutput as ResponseInputFunctionCallOutput,
+)
+from .response_create_response import (
+    ResponseOutputItem as ResponseOutputItem,
+    ResponseOutputMessage as ResponseOutputMessage,
+    ResponseCreateResponse as ResponseCreateResponse,
+    ResponseOutputFunctionCall as ResponseOutputFunctionCall,
+)

src/gradient/types/responses/response_create_params.py

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+# Types for the Responses API (POST /v1/responses). See docs/RESPONSES_API_PR_BREAKDOWN.md.
+
+from __future__ import annotations
+
+from typing import Dict, Union, Iterable, Optional
+from typing_extensions import Literal, Required, TypeAlias, TypedDict
+
+__all__ = [
+    "ResponseCreateParams",
+    "ResponseInputItem",
+    "ResponseInputUserMessage",
+    "ResponseInputFunctionCall",
+    "ResponseInputFunctionCallOutput",
+    "ResponseToolChoice",
+    "ResponseToolChoiceFunction",
+    "ResponseTool",
+    "ResponseToolFunction",
+]
+
+
+class ResponseInputUserMessage(TypedDict, total=False):
+    """User message in the request input list."""
+
+    type: Required[Literal["message"]]
+    role: Required[Literal["user"]]
+    content: Required[str]
+
+
+class ResponseInputFunctionCall(TypedDict, total=False):
+    """Function call (assistant turn) in the request input list."""
+
+    type: Required[Literal["function_call"]]
+    id: Required[str]
+    name: Required[str]
+    arguments: Required[str]
+
+
+class ResponseInputFunctionCallOutput(TypedDict, total=False):
+    """Function call result (tool output) in the request input list."""
+
+    type: Required[Literal["function_call_output"]]
+    call_id: Required[str]
+    output: Required[str]
+
+
+ResponseInputItem: TypeAlias = Union[
+    ResponseInputUserMessage,
+    ResponseInputFunctionCall,
+    ResponseInputFunctionCallOutput,
+]
+
+
+class ResponseToolFunction(TypedDict, total=False):
+    """Function definition for a tool."""
+
+    name: Required[str]
+    description: str
+    parameters: Dict[str, object]
+
+
+class ResponseTool(TypedDict, total=False):
+    """Tool the model may call (e.g. a function)."""
+
+    type: Required[Literal["function"]]
+    function: Required[ResponseToolFunction]
+
+
+class ResponseToolChoiceFunction(TypedDict, total=False):
+    name: Required[str]
+
+
+class ResponseToolChoiceNamed(TypedDict, total=False):
+    type: Required[Literal["function"]]
+    function: Required[ResponseToolChoiceFunction]
+
+
+ResponseToolChoice: TypeAlias = Union[
+    Literal["none", "auto", "required"],
+    ResponseToolChoiceNamed,
+]
+
+
+class ResponseCreateParams(TypedDict, total=False):
+    """Request body for POST /v1/responses."""
+
+    model: Required[str]
+    """Model ID (e.g. openai-gpt-5.2-pro)."""
+
+    input: Required[Iterable[ResponseInputItem]]
+    """List of input items: user messages, function_call, function_call_output."""
+
+    tools: Iterable[ResponseTool]
+    """Optional list of tools the model may call."""
+
+    max_output_tokens: Optional[int]
+    """Maximum tokens to generate."""
+
+    instructions: Optional[str]
+    """System or developer instructions."""
+
+    temperature: Optional[float]
+    """Sampling temperature."""
+
+    tool_choice: ResponseToolChoice
+    """Which tool (if any) the model must or may call."""

src/gradient/types/responses/response_create_response.py

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+# Response type for the Responses API (POST /v1/responses). See docs/RESPONSES_API_PR_BREAKDOWN.md.
+
+from __future__ import annotations
+
+from typing import List, Union, Optional
+from typing_extensions import Literal, Annotated, TypeAlias
+
+from ..._utils import PropertyInfo
+from ..._models import BaseModel
+from ..shared.completion_usage import CompletionUsage
+
+__all__ = [
+    "ResponseCreateResponse",
+    "ResponseOutputItem",
+    "ResponseOutputMessage",
+    "ResponseOutputFunctionCall",
+]
+
+
+class ResponseOutputMessage(BaseModel):
+    """Message item in the response output list."""
+
+    type: Literal["message"] = "message"
+    role: Literal["assistant"] = "assistant"
+    content: Optional[str] = None
+    """Text content of the message."""
+    output_text: Optional[str] = None
+    """Aggregated or final text for this item (when present)."""
+
+
+class ResponseOutputFunctionCall(BaseModel):
+    """Function call item in the response output list."""
+
+    type: Literal["function_call"] = "function_call"
+    id: str
+    name: str
+    arguments: str
+
+
+# Discriminated union so Pydantic parses each output item by "type".
+ResponseOutputItem: TypeAlias = Annotated[
+    Union[ResponseOutputMessage, ResponseOutputFunctionCall],
+    PropertyInfo(discriminator="type"),
+]
+
+
+class ResponseCreateResponse(BaseModel):
+    """
+    Response from POST /v1/responses.
+    Use the `output_text` property to get aggregated text from message items in `output`.
+    """
+
+    id: str
+    """Unique identifier for the response."""
+
+    output: List[ResponseOutputItem]
+    """List of output items (messages, function calls)."""
+
+    status: str
+    """Status of the response (e.g. completed, failed)."""
+
+    error: Optional[str] = None
+    """Error message if status indicates failure."""
+
+    model: Optional[str] = None
+    """Model used for the response."""
+
+    usage: Optional[CompletionUsage] = None
+    """Token usage statistics."""
+
+    @property
+    def output_text(self) -> str:
+        """
+        Aggregate text from all message items in `output`.
+        For each item with type "message", uses `output_text` if present, else `content`.
+        """
+        parts: List[str] = []
+        for item in self.output:
+            if isinstance(item, ResponseOutputMessage):
+                text: Optional[str] = item.output_text if item.output_text is not None else item.content
+                if text:
+                    parts.append(text)
+        return "".join(parts)

tests/types/__init__.py

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+# Tests for Responses API response types. No network; static payloads only.
+
+from __future__ import annotations
+
+from gradient.types.responses import (
+    ResponseOutputMessage,
+    ResponseCreateResponse,
+    ResponseOutputFunctionCall,
+)
+
+# Minimal valid response payload (static, no network).
+MINIMAL_RESPONSE = {
+    "id": "resp_123",
+    "output": [],
+    "status": "completed",
+    "model": "openai-gpt-5.2-pro",
+}
+
+
+class TestResponseCreateResponseParse:
+    """Test that ResponseCreateResponse parses minimal and extended JSON."""
+
+    def test_parse_minimal_response(self) -> None:
+        parsed = ResponseCreateResponse.model_validate(MINIMAL_RESPONSE)
+        assert parsed.id == "resp_123"
+        assert parsed.output == []
+        assert parsed.status == "completed"
+        assert parsed.model == "openai-gpt-5.2-pro"
+        assert parsed.output_text == ""
+
+    def test_parse_response_with_usage(self) -> None:
+        payload = {
+            **MINIMAL_RESPONSE,
+            "usage": {
+                "prompt_tokens": 10,
+                "completion_tokens": 5,
+                "total_tokens": 15,
+            },
+        }
+        parsed = ResponseCreateResponse.model_validate(payload)
+        assert parsed.usage is not None
+        assert parsed.usage.prompt_tokens == 10
+        assert parsed.usage.completion_tokens == 5
+        assert parsed.usage.total_tokens == 15
+
+
+class TestResponseCreateResponseOutputText:
+    """Test that output_text aggregates text from message items in output."""
+
+    def test_output_text_aggregates_content(self) -> None:
+        payload = {
+            **MINIMAL_RESPONSE,
+            "output": [
+                {"type": "message", "role": "assistant", "content": "Hello "},
+                {"type": "message", "role": "assistant", "content": "world."},
+            ],
+        }
+        parsed = ResponseCreateResponse.model_validate(payload)
+        assert parsed.output_text == "Hello world."
+
+    def test_output_text_prefers_output_text_field(self) -> None:
+        payload = {
+            **MINIMAL_RESPONSE,
+            "output": [
+                {
+                    "type": "message",
+                    "role": "assistant",
+                    "content": "raw",
+                    "output_text": "aggregated",
+                },
+            ],
+        }
+        parsed = ResponseCreateResponse.model_validate(payload)
+        assert parsed.output_text == "aggregated"
+
+    def test_output_text_skips_function_call_items(self) -> None:
+        payload = {
+            **MINIMAL_RESPONSE,
+            "output": [
+                {"type": "message", "role": "assistant", "content": "Here is "},
+                {
+                    "type": "function_call",
+                    "id": "call_1",
+                    "name": "get_weather",
+                    "arguments": "{}",
+                },
+                {"type": "message", "role": "assistant", "content": "the result."},
+            ],
+        }
+        parsed = ResponseCreateResponse.model_validate(payload)
+        assert parsed.output_text == "Here is the result."
+
+    def test_output_text_empty_message_content_treated_as_empty(self) -> None:
+        payload = {
+            **MINIMAL_RESPONSE,
+            "output": [
+                {"type": "message", "role": "assistant", "content": None},
+                {"type": "message", "role": "assistant", "output_text": "only this"},
+            ],
+        }
+        parsed = ResponseCreateResponse.model_validate(payload)
+        assert parsed.output_text == "only this"
+
+
+class TestResponseOutputItemTypes:
+    """Test that output item types parse correctly."""
+
+    def test_message_item_parses(self) -> None:
+        msg = ResponseOutputMessage.model_validate({"type": "message", "role": "assistant", "content": "Hi"})
+        assert msg.type == "message"
+        assert msg.role == "assistant"
+        assert msg.content == "Hi"
+
+    def test_function_call_item_parses(self) -> None:
+        fc = ResponseOutputFunctionCall.model_validate(
+            {
+                "type": "function_call",
+                "id": "call_1",
+                "name": "foo",
+                "arguments": '{"x": 1}',
+            }
+        )
+        assert fc.type == "function_call"
+        assert fc.id == "call_1"
+        assert fc.name == "foo"
+        assert fc.arguments == '{"x": 1}'