Files
codex/sdk/python/src/openai_codex/_inputs.py
Ahmed Ibrahim 1a4096e273 Add untrusted external messages to the Python SDK (#44086)
## Why

Applications need to deliver content from other agents, tools, or services with tool-level authority, without treating it as user input or granting authorization.

## What changed

- Export `ExternalMessage` for sync and async `run(...)` and `turn(...)`, accepting text or structured content with a tool name and optional namespace. Send it through `toolOutput` and require CLI 0.151.0 or newer.
- Support starting a turn or joining an active regular turn while preserving external content as function output in history. Keep external messages separate from user-input lists and `steer(...)`.
- Give turn handles independent subscriptions, replaying completed items and latest usage to joining handles. Release consumed transient events and clean up subscriptions on closure, failure, or cancellation.
- Document the authority boundary and add sync and async examples.

## Testing

Add coverage for wire representations, input validation, runtime compatibility, tool authority across resume, active-turn joins, and tool-output truncation. Add subscription tests for replay, concurrent consumers, early completion, cancellation, and cleanup.

GitOrigin-RevId: 6106327085fd9c4bd11b71e20b3d8e74738b8bb5
2026-09-09 06:54:18 +00:00

104 lines
3.0 KiB
Python

from __future__ import annotations
from collections.abc import Sequence
from dataclasses import dataclass
from .generated.v2_all import FunctionCallOutputContentItem, TurnToolOutput
from .models import JsonObject
@dataclass(slots=True)
class TextInput:
"""Text supplied to a turn or steering request."""
text: str
@dataclass(slots=True)
class ImageInput:
"""Image data URL supplied as turn input."""
url: str
@dataclass(slots=True)
class LocalImageInput:
"""Local image path supplied as turn input."""
path: str
@dataclass(slots=True)
class SkillInput:
"""Named skill reference supplied as turn input."""
name: str
path: str
@dataclass(slots=True)
class MentionInput:
"""Named resource mention supplied as turn input."""
name: str
path: str
@dataclass(slots=True)
class ExternalMessage:
"""Untrusted content supplied by another agent, tool, or application.
Content has tool-level authority, below user and developer instructions. It
does not establish user authorization or approval. Pass this as the whole
input to ``thread.run()`` or ``thread.turn()`` to start a turn or join an
active regular turn. ``tool_name`` identifies the tool delivering it.
``content`` accepts text or Responses-compatible function-output content
items. Structured items can be dictionaries; no generated wrapper is needed.
"""
tool_name: str
content: str | Sequence[JsonObject | FunctionCallOutputContentItem]
namespace: str | None = None
InputItem = TextInput | ImageInput | LocalImageInput | SkillInput | MentionInput
Input = list[InputItem] | InputItem
RunInput = Input | str | ExternalMessage
def _to_wire_item(item: InputItem) -> JsonObject:
if isinstance(item, TextInput):
return {"type": "text", "text": item.text}
if isinstance(item, ImageInput):
return {"type": "image", "url": item.url}
if isinstance(item, LocalImageInput):
return {"type": "localImage", "path": item.path}
if isinstance(item, SkillInput):
return {"type": "skill", "name": item.name, "path": item.path}
if isinstance(item, MentionInput):
return {"type": "mention", "name": item.name, "path": item.path}
raise TypeError(f"unsupported input item: {type(item)!r}")
def _to_wire_input(input: Input) -> list[JsonObject]:
if isinstance(input, list):
return [_to_wire_item(i) for i in input]
return [_to_wire_item(input)]
def _normalize_run_input(input: Input | str) -> Input:
if isinstance(input, str):
return TextInput(input)
return input
def _to_wire_turn_input(input: RunInput) -> tuple[list[JsonObject], TurnToolOutput | None]:
if isinstance(input, ExternalMessage):
if not isinstance(input.tool_name, str) or not input.tool_name.strip():
raise ValueError("ExternalMessage.tool_name must be a nonempty string")
return [], TurnToolOutput.model_validate(
{"name": input.tool_name, "namespace": input.namespace, "output": input.content}
)
return _to_wire_input(_normalize_run_input(input)), None