feat(R04): add the immutable turn snapshot and typed agent event stream

R04-T01 — `domain/agents/conversation_execution_request.py`: a frozen
snapshot of everything one chat turn needs. Turn inputs previously lived in a
closure plus a 15-key ctx dict inside `ui/chat_panel.py::_start_turn`, and the
worker thread kept reading the widget back while it ran, so every later click
was visible to work already in flight. The request also owns the prompt
composition rules (instruction prefix separator, session notes, model-switch
review note) that were inline in that closure.

R04-T02 — `domain/agents/agent_event.py`: 13 frozen event types replacing the
untyped `{"type": ...}` dicts, whose only specification was the 130-line
if/elif chain in `_on_event`. Each event serialises back to the exact legacy
dict, so the presentation layer is untouched; `agent_event_codec.py` parses the
other way and is a temporary shim, isolated so R08 can delete it in one move.
`assistant_done` is deliberately NOT the end of a turn (it fires once per
provider call), so it maps to AssistantMessageCompletedEvent while the new
TurnCompletedEvent reports the turn itself.

R04-T03 (part) — `domain/agents/agent_result.py`: one named outcome for a
finished turn, replacing the message list / 3-tuple / reconstructed-from-side-
effects trio the three callers each read differently.

Verification: 66 tests. Beyond the unit tests,
`tests/integration/test_agent_event_bridge.py` runs the REAL `run_cowork` loop
offline and asserts every dict it emits is recognised and round-trips
byte-for-byte — a guard against an event type nobody modelled or a key whose
meaning silently drifted.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-23 13:13:56 +09:00
co-authored by Claude Opus 5
parent 176e6aef79
commit 19e6b4deb2
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"""Typed events a turn emits while it runs (R04-T02).
The runtime currently speaks in bare dicts: ``emit({"type": "tool_result", "id":
..., "ok": ...})``. Nothing declares which keys a given type carries, so the
only specification is the 130-line ``if/elif`` chain in
``ui/chat_panel.py::_on_event`` — and a typo in an emitter surfaces as a widget
that silently renders nothing.
This module makes the vocabulary explicit. Each event is a frozen dataclass with
real fields, and each one knows how to serialise itself back to the exact legacy
dict the widget already reads (:meth:`AgentEvent.to_legacy_dict`), with
:func:`from_legacy_dict` parsing the other way. That two-way bridge is what lets
R04 introduce typed events WITHOUT touching the presentation layer — decomposing
``_on_event`` into a renderer is R08-T01's job, and forcing both changes into one
PR is exactly the "rewrite everything at once" the refactor plan forbids.
Scope note: this covers the interactive/scheduled **Cowork turn** vocabulary
(the ``run_cowork`` path R04 unifies). Co4E's own node events (``node_status``,
``stage_text``, ``run_done``) belong to ``Co4EWorkflowService`` in R07-T06 and
are deliberately left as dicts here — :func:`from_legacy_dict` returns ``None``
for them so a bridge can pass them straight through.
Layer rules (``docs/architecture/ADR-001-layered-architecture.md``): domain
layer, standard library only. No PySide6, no ``core/*`` imports.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, ClassVar, Dict, Iterable, Optional, Tuple
# Notice levels. "progress" is special-cased by the UI (it retargets the live
# thinking indicator instead of adding a bubble), so the vocabulary is pinned
# here rather than left to each emitter's string literal.
NOTICE_INFO = "info"
NOTICE_WARNING = "warning"
NOTICE_PROGRESS = "progress"
# --------------------------------------------------------------------------- #
# Value objects shared by several events.
# --------------------------------------------------------------------------- #
@dataclass(frozen=True)
class ToolPreview:
"""The human-readable preview of a proposed tool call.
Mirrors ``core/tools.py::describe_action``'s return shape exactly (three
string keys, nothing else), so wrapping it in a type is lossless. ``kind``
drives which bubble the UI renders: "diff" -> coloured before/after,
"command" -> terminal block, "info" -> plain text.
"""
kind: str = "info"
title: str = ""
text: str = ""
def to_dict(self) -> Dict[str, str]:
return {"kind": self.kind, "title": self.title, "text": self.text}
@classmethod
def from_dict(cls, raw: Any) -> Optional["ToolPreview"]:
"""Parse a legacy preview dict; ``None`` when there was none.
A non-dict value degrades to ``None`` rather than raising: a malformed
preview must cost the user a nicer bubble, never the whole turn.
"""
if not isinstance(raw, dict) or not raw:
return None
return cls(kind=str(raw.get("kind", "info")), title=str(raw.get("title", "")),
text=str(raw.get("text", "")))
@dataclass(frozen=True)
class PlanStep:
"""One entry of the agent's ``update_plan`` checklist.
``status`` is kept a plain string on purpose: ``core/plan.py`` already owns
validation (clamping anything unknown to "pending" against
pending/running/done/error), and duplicating that vocabulary here would give
the app two sources of truth to drift apart.
"""
title: str
status: str = "pending"
def to_dict(self) -> Dict[str, str]:
return {"title": self.title, "status": self.status}
def _as_str_tuple(values: Iterable[Any]) -> Tuple[str, ...]:
"""Freeze an iterable of paths into a tuple of strings.
Emitters hand us live lists (``record["outputs"]``, ``_cleanup``'s result);
copying decouples the event from later mutation of that list.
"""
return tuple(str(v) for v in (values or ()))
# --------------------------------------------------------------------------- #
# Base class.
# --------------------------------------------------------------------------- #
class AgentEvent:
"""Base for every turn event.
Not a dataclass itself (it holds no data) — subclasses are the frozen
dataclasses. ``EVENT_TYPE`` is the legacy wire name, which stays the single
identifier shared between the typed world and the dict world.
"""
EVENT_TYPE: ClassVar[str] = ""
def _payload(self) -> Dict[str, Any]:
"""Type-specific keys of the legacy dict (without ``type``)."""
return {}
def to_legacy_dict(self) -> Dict[str, Any]:
"""The exact dict shape ``ui/chat_panel.py::_on_event`` dispatches on."""
return {"type": self.EVENT_TYPE, **self._payload()}
# --------------------------------------------------------------------------- #
# Streaming events.
# --------------------------------------------------------------------------- #
@dataclass(frozen=True)
class TextChunkEvent(AgentEvent):
"""A fragment of the assistant's visible answer."""
EVENT_TYPE: ClassVar[str] = "text"
delta: str = ""
def _payload(self) -> Dict[str, Any]:
return {"delta": self.delta}
@dataclass(frozen=True)
class ReasoningChunkEvent(AgentEvent):
"""A fragment of a reasoning model's thinking, shown in a collapsed box."""
EVENT_TYPE: ClassVar[str] = "reasoning"
delta: str = ""
def _payload(self) -> Dict[str, Any]:
return {"delta": self.delta}
@dataclass(frozen=True)
class AssistantMessageCompletedEvent(AgentEvent):
"""One assistant message finished streaming.
Emitted once per provider call, so a tool-using turn produces SEVERAL of
these — it marks an autosave point, not the end of the turn. The end of the
turn is :class:`TurnCompletedEvent`.
"""
EVENT_TYPE: ClassVar[str] = "assistant_done"
content: str = ""
def _payload(self) -> Dict[str, Any]:
return {"content": self.content}
# --------------------------------------------------------------------------- #
# Tool-call lifecycle.
# --------------------------------------------------------------------------- #
@dataclass(frozen=True)
class ToolCallStartedEvent(AgentEvent):
"""A tool call is about to run (after any security/permission gate).
Field names are the typed ones (``call_id``, ``arguments``); the legacy keys
``id``/``args`` are produced only at the serialisation boundary, so new code
never has to shadow the ``id`` builtin.
"""
EVENT_TYPE: ClassVar[str] = "tool_proposed"
call_id: str = ""
name: str = ""
arguments: Dict[str, Any] = field(default_factory=dict)
preview: Optional[ToolPreview] = None
def _payload(self) -> Dict[str, Any]:
payload: Dict[str, Any] = {"id": self.call_id, "name": self.name,
"args": dict(self.arguments)}
# Omitted rather than sent as None: the widget does
# ``preview = ev.get("preview") or {}`` and an absent key is the shape it
# already handles for tools without a preview.
if self.preview is not None:
payload["preview"] = self.preview.to_dict()
return payload
@dataclass(frozen=True)
class ToolOutputChunkEvent(AgentEvent):
"""Live stdout/stderr from a running command, appended to its step bubble."""
EVENT_TYPE: ClassVar[str] = "tool_output"
call_id: str = ""
name: str = ""
delta: str = ""
def _payload(self) -> Dict[str, Any]:
return {"id": self.call_id, "name": self.name, "delta": self.delta}
@dataclass(frozen=True)
class ToolCallFinishedEvent(AgentEvent):
"""A tool call returned. ``path``/``produced`` name files it created."""
EVENT_TYPE: ClassVar[str] = "tool_result"
call_id: str = ""
name: str = ""
ok: bool = False
output: str = ""
path: str = "" # the single file this call wrote, if any
produced: Tuple[str, ...] = () # extra deliverables a command produced
def __post_init__(self) -> None:
# Callers pass a live list; freeze it so the event cannot change later.
object.__setattr__(self, "produced", _as_str_tuple(self.produced))
def _payload(self) -> Dict[str, Any]:
payload: Dict[str, Any] = {"id": self.call_id, "name": self.name,
"ok": self.ok, "output": self.output}
# Both keys stay ABSENT when empty, matching what chat_agent emits today:
# downstream code tests them with ``ev.get(...)`` truthiness and iterates
# ``ev.get("produced", [])``, so adding empty values would be a change.
if self.path:
payload["path"] = self.path
if self.produced:
payload["produced"] = list(self.produced)
return payload
# --------------------------------------------------------------------------- #
# Side-channel events (plan, notices, output folder).
# --------------------------------------------------------------------------- #
@dataclass(frozen=True)
class PlanUpdatedEvent(AgentEvent):
"""The agent published a new version of its step checklist (full list)."""
EVENT_TYPE: ClassVar[str] = "plan_set"
steps: Tuple[PlanStep, ...] = ()
def __post_init__(self) -> None:
object.__setattr__(self, "steps", tuple(self.steps or ()))
def _payload(self) -> Dict[str, Any]:
return {"steps": [s.to_dict() for s in self.steps]}
@dataclass(frozen=True)
class NoticeEvent(AgentEvent):
"""An aside outside the model's own answer.
Three sources today: context auto-compaction (info), a blocked
security check (warning), and attachment reading progress (progress).
"""
EVENT_TYPE: ClassVar[str] = "notice"
text: str = ""
level: str = NOTICE_INFO
def _payload(self) -> Dict[str, Any]:
return {"level": self.level, "text": self.text}
@dataclass(frozen=True)
class OutputsAddedEvent(AgentEvent):
"""Deliverables appeared in the turn's output folder."""
EVENT_TYPE: ClassVar[str] = "outputs_added"
paths: Tuple[str, ...] = ()
def __post_init__(self) -> None:
object.__setattr__(self, "paths", _as_str_tuple(self.paths))
def _payload(self) -> Dict[str, Any]:
return {"paths": list(self.paths)}
@dataclass(frozen=True)
class OutputsRemovedEvent(AgentEvent):
"""Intermediate/generator files were cleaned up — drop them from Output."""
EVENT_TYPE: ClassVar[str] = "outputs_removed"
paths: Tuple[str, ...] = ()
def __post_init__(self) -> None:
object.__setattr__(self, "paths", _as_str_tuple(self.paths))
def _payload(self) -> Dict[str, Any]:
return {"paths": list(self.paths)}
@dataclass(frozen=True)
class HistoryReadyEvent(AgentEvent):
"""The turn's conversation now exists on disk and can be opened.
Emitted by the unattended (Schedule Task) path so the scheduler refreshes
History only once the session is really there.
"""
EVENT_TYPE: ClassVar[str] = "history_ready"
session_id: str = ""
def _payload(self) -> Dict[str, Any]:
return {"session_id": self.session_id}
# --------------------------------------------------------------------------- #
# Turn-level events introduced by R04 (no legacy consumer yet).
# --------------------------------------------------------------------------- #
@dataclass(frozen=True)
class TurnCompletedEvent(AgentEvent):
"""The whole turn ended — exactly once per turn.
Nothing consumes ``"turn_completed"`` yet: the widget's ``if/elif`` chain
simply has no branch for it, so emitting it is inert until R08 wires a
renderer. It exists now because the state it carries (was the turn
cancelled? did it hit the step ceiling?) is currently reconstructed by the
UI from side effects rather than being told to it.
"""
EVENT_TYPE: ClassVar[str] = "turn_completed"
final_text: str = ""
steps_used: int = 0
cancelled: bool = False
budget_exhausted: bool = False # stopped at effective_max_steps
def _payload(self) -> Dict[str, Any]:
return {"final_text": self.final_text, "steps_used": self.steps_used,
"cancelled": self.cancelled, "budget_exhausted": self.budget_exhausted}
@dataclass(frozen=True)
class ErrorEvent(AgentEvent):
"""The turn hit an error.
``recoverable`` separates "this turn is over" from "something failed but the
loop carried on" — a distinction the current code loses, because both end up
as a bare ``except Exception`` plus a text bubble.
"""
EVENT_TYPE: ClassVar[str] = "error"
message: str = ""
recoverable: bool = False
def _payload(self) -> Dict[str, Any]:
return {"message": self.message, "recoverable": self.recoverable}
__all__ = [
"NOTICE_INFO", "NOTICE_WARNING", "NOTICE_PROGRESS",
"AgentEvent", "ToolPreview", "PlanStep",
"TextChunkEvent", "ReasoningChunkEvent", "AssistantMessageCompletedEvent",
"ToolCallStartedEvent", "ToolOutputChunkEvent", "ToolCallFinishedEvent",
"PlanUpdatedEvent", "NoticeEvent", "OutputsAddedEvent", "OutputsRemovedEvent",
"HistoryReadyEvent", "TurnCompletedEvent", "ErrorEvent",
]
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"""Legacy dict -> typed :mod:`agent_event` translation (R04-T02).
Kept in its own module for two reasons. It is a **temporary compatibility
shim**: once R08-T01 turns ``ui/chat_panel.py::_on_event`` into an event
renderer that consumes typed events directly, nothing needs to parse dicts any
more and this whole file gets deleted — a deletion that stays trivial only while
it is isolated. And it keeps ``agent_event.py`` inside the 400-LOC limit the
architecture rules impose, without diluting either file's single job: one
declares the vocabulary, the other bridges it to the old wire format.
Serialisation the other way lives on the events themselves
(``AgentEvent.to_legacy_dict``), because an event has to be emittable without
anyone importing a codec.
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Tuple
from .agent_event import (
AgentEvent,
AssistantMessageCompletedEvent,
ErrorEvent,
HistoryReadyEvent,
NOTICE_INFO,
NoticeEvent,
OutputsAddedEvent,
OutputsRemovedEvent,
PlanStep,
PlanUpdatedEvent,
ReasoningChunkEvent,
TextChunkEvent,
ToolCallFinishedEvent,
ToolCallStartedEvent,
ToolOutputChunkEvent,
ToolPreview,
TurnCompletedEvent,
)
def _plan_steps_from_legacy(raw: Any) -> Tuple[PlanStep, ...]:
"""Parse the legacy ``steps`` list, dropping anything unusable.
A step with no title cannot be rendered or ticked off, so it is discarded
instead of becoming a blank row in the Plan panel.
"""
if not isinstance(raw, list):
return ()
steps: List[PlanStep] = []
for item in raw:
if not isinstance(item, dict):
continue
title = str(item.get("title", "")).strip()
if not title:
continue
steps.append(PlanStep(title=title, status=str(item.get("status", "pending"))))
return tuple(steps)
def _parse_tool_started(raw: Dict[str, Any]) -> ToolCallStartedEvent:
"""Rebuild a ``tool_proposed`` event, mapping ``id``/``args`` to typed names."""
args = raw.get("args")
return ToolCallStartedEvent(
call_id=str(raw.get("id", "")), name=str(raw.get("name", "")),
arguments=dict(args) if isinstance(args, dict) else {},
preview=ToolPreview.from_dict(raw.get("preview")),
)
def _parse_tool_finished(raw: Dict[str, Any]) -> ToolCallFinishedEvent:
"""Rebuild a ``tool_result`` event; the optional file keys may be absent."""
return ToolCallFinishedEvent(
call_id=str(raw.get("id", "")), name=str(raw.get("name", "")),
ok=bool(raw.get("ok", False)), output=str(raw.get("output", "")),
path=str(raw.get("path", "") or ""), produced=raw.get("produced") or (),
)
# One parser per wire name. A table (rather than an if/elif chain) keeps adding
# an event a single-line change and makes the supported set introspectable.
_PARSERS = {
TextChunkEvent.EVENT_TYPE: lambda raw: TextChunkEvent(delta=str(raw.get("delta", ""))),
ReasoningChunkEvent.EVENT_TYPE: lambda raw: ReasoningChunkEvent(
delta=str(raw.get("delta", ""))),
AssistantMessageCompletedEvent.EVENT_TYPE: lambda raw: AssistantMessageCompletedEvent(
content=str(raw.get("content", ""))),
ToolCallStartedEvent.EVENT_TYPE: _parse_tool_started,
ToolOutputChunkEvent.EVENT_TYPE: lambda raw: ToolOutputChunkEvent(
call_id=str(raw.get("id", "")), name=str(raw.get("name", "")),
delta=str(raw.get("delta", ""))),
ToolCallFinishedEvent.EVENT_TYPE: _parse_tool_finished,
PlanUpdatedEvent.EVENT_TYPE: lambda raw: PlanUpdatedEvent(
steps=_plan_steps_from_legacy(raw.get("steps"))),
NoticeEvent.EVENT_TYPE: lambda raw: NoticeEvent(
text=str(raw.get("text", "")), level=str(raw.get("level", NOTICE_INFO))),
OutputsAddedEvent.EVENT_TYPE: lambda raw: OutputsAddedEvent(paths=raw.get("paths") or ()),
OutputsRemovedEvent.EVENT_TYPE: lambda raw: OutputsRemovedEvent(paths=raw.get("paths") or ()),
HistoryReadyEvent.EVENT_TYPE: lambda raw: HistoryReadyEvent(
session_id=str(raw.get("session_id", ""))),
TurnCompletedEvent.EVENT_TYPE: lambda raw: TurnCompletedEvent(
final_text=str(raw.get("final_text", "")), steps_used=int(raw.get("steps_used", 0) or 0),
cancelled=bool(raw.get("cancelled", False)),
budget_exhausted=bool(raw.get("budget_exhausted", False))),
ErrorEvent.EVENT_TYPE: lambda raw: ErrorEvent(
message=str(raw.get("message", "")), recoverable=bool(raw.get("recoverable", False))),
}
def from_legacy_dict(payload: Any) -> Optional[AgentEvent]:
"""Parse an emitted dict into a typed event, or ``None`` if it isn't ours.
``None`` (rather than an exception) is the contract that makes incremental
adoption possible: a bridge sitting between the runtime and the widget can
type the events it recognises and forward everything else — Co4E's node
events, or anything a future emitter adds — completely untouched.
"""
if not isinstance(payload, dict):
return None
parser = _PARSERS.get(str(payload.get("type", "")))
return parser(payload) if parser is not None else None
__all__ = ["from_legacy_dict"]
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"""What one finished turn produced (R04-T03).
The outcome of a turn is currently spread over three shapes: ``run_cowork``
returns the mutated message list, ``task_executors._run_agent`` returns a
``(answer_text, timed_out, incomplete_reason)`` tuple, and the UI reconstructs
the rest (did it get cancelled? did it hit the ceiling?) from side effects. Each
caller therefore knows a slightly different amount about the same turn.
:class:`AgentResult` is the single answer. Frozen, like the request that started
the turn, so a result cannot be edited into disagreeing with what actually
happened.
Layer rules (``docs/architecture/ADR-001-layered-architecture.md``): domain
layer — standard library plus sibling domain types only.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Dict, Tuple
from .agent_event import PlanStep, TurnCompletedEvent
@dataclass(frozen=True)
class AgentResult:
"""The outcome of one conversation turn."""
# The conversation AFTER the turn (system prompt, history, the new user
# message, every assistant reply and tool result).
messages: Tuple[Dict[str, Any], ...] = ()
steps_used: int = 0 # provider calls this turn consumed
cancelled: bool = False # the user pressed Stop
budget_exhausted: bool = False # stopped at effective_max_steps
# The agent's final checklist, so a caller can ask "did it really finish?"
# (``core/plan.py::plan_incomplete_reason``) without replaying the events.
plan_steps: Tuple[PlanStep, ...] = ()
# Non-empty when the turn ended on a failure. A string rather than the
# exception: the domain layer must not depend on where the error came from,
# and the message is what every consumer (bubble, error.txt, audit) shows.
error: str = ""
def __post_init__(self) -> None:
"""Freeze the collections the runtime hands over.
Both arrive as live lists that the caller keeps appending to after the
turn (the UI merges messages back into its own history), so copying here
is what keeps a result a record rather than a moving target.
"""
object.__setattr__(self, "messages", tuple(self.messages or ()))
object.__setattr__(self, "plan_steps", tuple(self.plan_steps or ()))
@property
def final_text(self) -> str:
"""The answer to show the user.
Scans backwards for the last assistant message with real content, which
is not the same as ``messages[-1]``: a turn that was cancelled or that
ran out of steps mid-loop ends on a tool message, and a reasoning-only
reply leaves a blank assistant message behind. Same rule as
``core/task_executors.py::_last_assistant_text``, which this replaces.
"""
for message in reversed(self.messages):
if message.get("role") == "assistant" and (message.get("content") or "").strip():
return str(message["content"])
return ""
@property
def ok(self) -> bool:
"""Whether the turn ran to a normal end.
Hitting the step ceiling still counts as ok: the agent did work and
produced an answer, it just was not allowed to keep going — which the
transcript says in its own note rather than by failing the turn.
"""
return not self.error and not self.cancelled
def to_turn_completed_event(self) -> TurnCompletedEvent:
"""The end-of-turn event carrying this outcome to subscribers."""
return TurnCompletedEvent(
final_text=self.final_text, steps_used=self.steps_used,
cancelled=self.cancelled, budget_exhausted=self.budget_exhausted,
)
__all__ = ["AgentResult"]
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"""The immutable snapshot of ONE chat turn (R04-T01).
Today a turn's inputs live in a closure plus a 15-key ``ctx`` dict built inside
``ui/chat_panel.py::_start_turn``, and the worker thread reads the widget back
(``self._model``, ``self.title``, ``self.project_id``) while it runs. That is
the mechanism behind the whole class of "I changed the model mid-answer and the
running turn behaved oddly" reports: the turn has no snapshot of its own, so
every later click on the UI is visible to work already in flight.
:class:`ConversationExecutionRequest` is that missing snapshot. Everything the
runtime needs for one turn is captured once, on the UI thread, at submit time,
and then handed to code that runs on a worker thread. Frozen, so no caller —
widget or service — can retroactively change a decision the turn already acted
on.
Layer rules (see ``docs/architecture/ADR-001-layered-architecture.md``): this is
the domain layer, so standard library only. No PySide6, no ``requests``, no
filesystem access, and deliberately no import of ``core/*`` — a request only
*describes* a turn; running it is the application layer's job
(``application/conversations/``).
"""
from __future__ import annotations
from dataclasses import dataclass, field, replace
from pathlib import Path
from typing import Any, Dict, Optional, Tuple
# Separator between an instruction prefix (a ``/skill`` block, an ``/agent``
# persona) and the user's own request. Kept as a constant because the prefix is
# assembled in the presentation layer while the body is only known later on the
# worker thread — both halves must agree on the exact separator or the model
# sees a different prompt shape than it did before this refactor.
PREFIX_SEPARATOR = "\n\n---\n\n"
@dataclass(frozen=True)
class ConversationExecutionRequest:
"""Everything needed to execute one conversation turn.
Frozen for the reason above; use :meth:`with_model` / :meth:`with_output_dir`
to derive an adjusted copy rather than mutating one another thread may be
reading.
Note on depth: ``messages`` is a *shallow* snapshot (a tuple holding the
same message dicts the caller passed). That matches the existing
``snapshot = list(self.messages)`` semantics in ``_start_turn`` exactly —
the turn is protected from the history list being appended to or replaced,
which is what actually happens between turns. Making it deep would silently
change how ``_finalize_turn`` merges the turn's messages back, so the
stronger guarantee is left to R04-T03 where that merge moves.
"""
# -- identity ------------------------------------------------------- #
turn_id: str # unique within a session ("t1", "t2", ...)
session_id: str # the conversation this turn belongs to
surface: str = "cowork" # routing/mode key: "cowork" | "co4e" | "ai_edit"
project_id: str = "" # workspace the turn is confined to
title: str = "" # conversation title; also names saved files
# -- what the user asked -------------------------------------------- #
# The typed request, already stripped of any ``/skill`` or ``/agent``
# directive (those become ``instruction_prefix``).
prompt: str = ""
instruction_prefix: str = "" # skill rules + agent persona for this turn
# Prepended when the model/agent was switched mid-conversation, asking the
# model to re-check the previous step before continuing. Invisible in the
# chat bubble — it only travels in the payload sent to the provider.
review_note: str = ""
# Attachment PATHS, not their text: extracting a .docx can pip-install a
# parser or shell out to LibreOffice, which must not run on the UI thread.
# The runtime reads them later and passes the result to :meth:`user_content`.
attachments: Tuple[str, ...] = ()
# Conversation history as of submit time; the new user message is NOT part
# of it (the runtime appends it once the body is composed).
messages: Tuple[Dict[str, Any], ...] = ()
# -- which model answers -------------------------------------------- #
# Already resolved upstream: an Admin-agent pin, the tab's own picker, or a
# routing override published by ``RoutingApplicationService`` (R03). The
# runtime does not re-decide, so a switch cannot land mid-turn.
provider_id: str = ""
model: str = "" # "" = the provider's configured default
# -- standing instructions ------------------------------------------ #
project_context: str = "" # Claude-Projects-style shared instructions
session_notes: str = "" # e.g. files this conversation already produced
# -- tool scope and turn limits -------------------------------------- #
# None = every enabled built-in tool. An explicit (possibly empty) tuple
# restricts the ADVERTISED tools, which is how a "read-only" step is made
# literally unable to write.
allowed_tools: Optional[Tuple[str, ...]] = None
max_steps: int = 30 # interactive cap
completion_max_steps: int = 200 # runaway ceiling for run-to-completion work
run_to_completion: bool = False # Co4E flow steps need the higher ceiling
enforce_rules: bool = True # False for sandboxed Co4E runs
gate_mode: str = "auto" # "confirm" -> ask before run_command/install
agent_role: str = "cowork" # audit-log attribution ("cowork" | "task" | ...)
# -- where its files go ---------------------------------------------- #
output_dir: Optional[Path] = None # this turn's isolated sandbox
home_output_root: Optional[Path] = None # conversation Output root to promote into
# -- unattended execution (Schedule Task) ----------------------------- #
unattended: bool = False # no human watching; plan tracking is enforced
timeout_sec: Optional[int] = None # None = no wall-clock limit
# Escape hatch for surface-specific data a future task needs to thread
# through without another schema change (same role as
# ``ProviderDescriptor.extras``).
extras: Dict[str, Any] = field(default_factory=dict)
# -- validation / normalisation --------------------------------------- #
def __post_init__(self) -> None:
"""Reject unusable requests and freeze the mutable inputs.
Validation lives here (not at the call site) so a request that exists is
always safe to key by: the audit log, the History autosave and the
per-turn output folder are all named from ``session_id``/``turn_id``.
Normalisation matters just as much: the caller hands us the composer's
own attachment LIST and the live history LIST, and both get cleared or
appended to for the next turn. Copying them into tuples here is what
actually makes the snapshot a snapshot. ``object.__setattr__`` is the
standard way to do this in a frozen dataclass.
"""
if not (self.turn_id or "").strip():
raise ValueError("ConversationExecutionRequest.turn_id must not be empty")
if not (self.session_id or "").strip():
raise ValueError("ConversationExecutionRequest.session_id must not be empty")
object.__setattr__(self, "attachments", tuple(self.attachments or ()))
object.__setattr__(self, "messages", tuple(self.messages or ()))
# None must survive: it means "no restriction", while an empty tuple
# means "deny every built-in tool" — two very different turns.
if self.allowed_tools is not None:
object.__setattr__(self, "allowed_tools", tuple(self.allowed_tools))
# Accept str paths so a call site holding a config value does not have to
# wrap it; everything downstream can then assume Path.
for name in ("output_dir", "home_output_root"):
value = getattr(self, name)
if value is not None and not isinstance(value, Path):
object.__setattr__(self, name, Path(value))
# -- derived turn policy ---------------------------------------------- #
@property
def has_prompt(self) -> bool:
"""Whether the user actually typed something (an attachment-only turn
legitimately has none). Mirrors ``RoutingRequest.has_prompt`` so both
DTOs answer the "is there anything to work with?" question the same way.
"""
return bool((self.prompt or "").strip())
@property
def effective_max_steps(self) -> int:
"""The tool-use budget for this turn.
Run-to-completion work (a Co4E flow step whose single instruction may
need many tool calls) gets the higher ceiling; interactive chat keeps the
tight cap. Either way the turn still ends the moment the model stops
calling tools — this is only the runaway limit.
"""
return self.completion_max_steps if self.run_to_completion else self.max_steps
@property
def requires_permission_gate(self) -> bool:
"""Whether ``run_command``/``install_package`` must be approved first.
Resolved by the caller (per-workspace Auto-run override, else the global
"confirm before running commands" setting) and frozen here, so toggling
the setting mid-turn cannot change the rules the turn started under.
"""
return self.gate_mode == "confirm"
# -- prompt composition ------------------------------------------------ #
def user_content(self, body: str = "") -> str:
"""The exact ``content`` to send as this turn's user message.
``body`` is the request text AFTER attachment extraction, which happens
on the worker thread — hence a method taking it as an argument rather
than a stored field. The assembly order reproduces the closure in
``_start_turn`` byte for byte, because changing what a model receives is
a behaviour change, not a refactor:
1. session notes are appended after the body;
2. the instruction prefix goes in front, behind a fixed separator;
3. the model-switch review note goes ahead of everything.
"""
content = body or ""
notes = self.session_notes or ""
if notes:
# Guard the empty-body case (attachment-only turn) so the payload
# never opens with a stray blank line.
content = f"{content}\n\n{notes}" if content else notes
prefix = self.instruction_prefix or ""
if prefix:
content = f"{prefix}{PREFIX_SEPARATOR}{content}"
review = self.review_note or ""
if review:
content = f"{review}\n\n{content}"
return content
# -- derivation --------------------------------------------------------- #
def with_model(self, provider_id: str = "", model: str = "") -> "ConversationExecutionRequest":
"""A copy pinned to another provider/model.
Needed when a decision lands between building the request and running it
(a routing override, an Admin-agent pin). Deriving a new request keeps
the "one turn, one immutable snapshot" rule intact instead of patching a
request another thread may already hold.
"""
return replace(self, provider_id=provider_id or self.provider_id,
model=model or self.model)
def with_output_dir(self, output_dir) -> "ConversationExecutionRequest":
"""A copy writing into a different sandbox — used when the caller only
learns the per-turn folder after the request is assembled."""
return replace(self, output_dir=output_dir)
__all__ = ["PREFIX_SEPARATOR", "ConversationExecutionRequest"]
@@ -0,0 +1,113 @@
"""R04-T02 — the typed event vocabulary vs. what the real runtime emits.
The unit tests pin each event against the shape I *read* out of
``core/chat_agent.py``. This one removes the reading: it runs the actual
``run_cowork`` loop offline (FakeProvider, real tool execution, real cleanup)
and asserts every dict it emits is recognised by :func:`from_legacy_dict` and
survives a round trip byte-for-byte.
That makes it a guard against the two failure modes a hand-written vocabulary
has: an event type nobody modelled, and a key that silently changes meaning.
Either one would surface here as a failure instead of as a blank chat bubble
after R04-T03 starts routing events through the typed layer.
"""
from __future__ import annotations
from pathlib import Path
from typing import Any, Dict, List
import pytest
from cowork_local.core import chat_agent
from cowork_local.domain.agents.agent_event_codec import from_legacy_dict
from cowork_local.tests.fakes.fake_provider import FakeProvider
def _run_turn_and_collect(tmp_path: Path, provider: FakeProvider) -> List[Dict[str, Any]]:
"""Run one real ``run_cowork`` turn offline and return every emitted dict."""
output_dir = tmp_path / "output"
output_dir.mkdir(parents=True, exist_ok=True)
emitted: List[Dict[str, Any]] = []
chat_agent.run_cowork(
provider=provider,
messages=[{"role": "user", "content": "make me a report"}],
output_dir=output_dir,
emit=emitted.append,
# security_config=None disables the AI guardrail layers, which is the
# documented behaviour for headless callers and keeps this test offline.
security_config=None,
title="Report",
)
return emitted
def _reporting_turn(tmp_path: Path) -> List[Dict[str, Any]]:
"""A turn that streams text, calls save_file, then answers — the common path."""
provider = FakeProvider()
provider.queue_response(
content="Writing it now.",
chunks=["Writing ", "it now."],
tool_calls=[{"id": "call_1", "name": "save_file",
"arguments": {"filename": "report.md", "content": "# Report\n"}}],
)
provider.queue_response(content="Saved to report.md.", chunks=["Saved to report.md."])
return _run_turn_and_collect(tmp_path, provider)
def test_the_runtime_emits_only_event_types_the_domain_layer_models(tmp_path: Path) -> None:
emitted = _reporting_turn(tmp_path)
unmodelled = sorted({e["type"] for e in emitted if from_legacy_dict(e) is None})
assert unmodelled == [], f"run_cowork emits event types R04-T02 does not model: {unmodelled}"
def test_every_emitted_event_round_trips_without_losing_a_key(tmp_path: Path) -> None:
emitted = _reporting_turn(tmp_path)
assert emitted, "the turn produced no events at all — the fixture is wrong"
for raw in emitted:
event = from_legacy_dict(raw)
assert event is not None, raw
assert event.to_legacy_dict() == raw, f"round trip changed the {raw['type']} event"
def test_a_tool_using_turn_really_exercises_the_tool_events(tmp_path: Path) -> None:
# Guards the test above from passing trivially: if the fixture ever stopped
# calling a tool, the round-trip check would only cover text events.
types = {e["type"] for e in _reporting_turn(tmp_path)}
assert {"text", "assistant_done", "tool_proposed", "tool_result"} <= types
def test_reasoning_events_from_a_thinking_model_round_trip(tmp_path: Path) -> None:
# A separate fixture because only reasoning models emit these, and the
# common-path turn above would otherwise never cover the event.
provider = FakeProvider()
provider.queue_response(content="42", chunks=["42"], reasoning="Let me think...")
emitted = _run_turn_and_collect(tmp_path, provider)
reasoning_events = [e for e in emitted if e["type"] == "reasoning"]
assert reasoning_events, "a reasoning model produced no reasoning event"
for raw in reasoning_events:
assert from_legacy_dict(raw).to_legacy_dict() == raw
def test_plan_events_from_the_real_update_plan_tool_round_trip(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(
content="Planning.",
tool_calls=[{"id": "call_1", "name": "update_plan",
"arguments": {"steps": [{"title": "Draft", "status": "running"},
{"title": "Review", "status": "pending"}]}}],
)
provider.queue_response(content="Done.")
emitted = _run_turn_and_collect(tmp_path, provider)
plan_events = [e for e in emitted if e["type"] == "plan_set"]
assert plan_events, "update_plan did not produce a plan_set event"
for raw in plan_events:
assert from_legacy_dict(raw).to_legacy_dict() == raw
+209
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@@ -0,0 +1,209 @@
"""R04-T02 — unit tests for the typed agent event stream.
The events replace the untyped ``{"type": ...}`` dicts the runtime emits today,
but ``ui/chat_panel.py::_on_event`` still dispatches on those dicts until R08.
So the contract under test is two-sided: each event must be a real typed value
AND must serialise back to the exact legacy shape the widget already reads —
same wire name, same keys, same optional-key behaviour.
"""
from __future__ import annotations
from dataclasses import FrozenInstanceError
import pytest
from cowork_local.domain.agents.agent_event import (
AssistantMessageCompletedEvent,
ErrorEvent,
HistoryReadyEvent,
NoticeEvent,
OutputsAddedEvent,
OutputsRemovedEvent,
PlanStep,
PlanUpdatedEvent,
ReasoningChunkEvent,
TextChunkEvent,
ToolCallFinishedEvent,
ToolCallStartedEvent,
ToolOutputChunkEvent,
ToolPreview,
TurnCompletedEvent,
)
from cowork_local.domain.agents.agent_event_codec import from_legacy_dict
# -- base contract --------------------------------------------------------- #
def test_events_reject_mutation() -> None:
event = TextChunkEvent(delta="hello")
with pytest.raises(FrozenInstanceError):
event.delta = "goodbye"
# -- legacy wire compatibility --------------------------------------------- #
def test_text_chunk_serialises_as_the_legacy_text_event() -> None:
assert TextChunkEvent(delta="hi").to_legacy_dict() == {"type": "text", "delta": "hi"}
def test_reasoning_chunk_serialises_as_the_legacy_reasoning_event() -> None:
assert ReasoningChunkEvent(delta="hmm").to_legacy_dict() == {
"type": "reasoning", "delta": "hmm"}
def test_assistant_message_completed_serialises_as_assistant_done() -> None:
# Fires once per provider call, so several times in a tool-using turn — it
# is NOT the end of the turn (that is TurnCompletedEvent).
assert AssistantMessageCompletedEvent(content="done").to_legacy_dict() == {
"type": "assistant_done", "content": "done"}
def test_tool_call_started_serialises_with_the_legacy_id_and_args_keys() -> None:
event = ToolCallStartedEvent(
call_id="call_1", name="write_file", arguments={"path": "a.md"},
preview=ToolPreview(kind="diff", title="Create file: a.md", text="+ hi"),
)
assert event.to_legacy_dict() == {
"type": "tool_proposed",
"id": "call_1",
"name": "write_file",
"args": {"path": "a.md"},
"preview": {"kind": "diff", "title": "Create file: a.md", "text": "+ hi"},
}
def test_tool_call_started_omits_the_preview_when_there_is_none() -> None:
event = ToolCallStartedEvent(call_id="call_1", name="read_file")
assert "preview" not in event.to_legacy_dict()
def test_tool_output_chunk_serialises_as_the_legacy_tool_output_event() -> None:
event = ToolOutputChunkEvent(call_id="call_1", name="run_command", delta="line\n")
assert event.to_legacy_dict() == {
"type": "tool_output", "id": "call_1", "name": "run_command", "delta": "line\n"}
def test_tool_call_finished_serialises_as_the_legacy_tool_result_event() -> None:
event = ToolCallFinishedEvent(
call_id="call_1", name="save_file", ok=True, output="saved",
path="C:/out/a.md", produced=["C:/out/b.pptx"],
)
assert event.to_legacy_dict() == {
"type": "tool_result",
"id": "call_1",
"name": "save_file",
"ok": True,
"output": "saved",
"path": "C:/out/a.md",
"produced": ["C:/out/b.pptx"],
}
def test_tool_call_finished_omits_path_and_produced_when_empty() -> None:
# chat_agent only sets these keys when they exist; emitting them as None
# would make ``ev.get("path")`` truthy checks read differently downstream.
legacy = ToolCallFinishedEvent(call_id="c", name="read_file", ok=True).to_legacy_dict()
assert "path" not in legacy
assert "produced" not in legacy
def test_plan_updated_serialises_steps_back_to_title_status_dicts() -> None:
event = PlanUpdatedEvent(steps=(PlanStep(title="Read config", status="done"),
PlanStep(title="Patch it", status="running")))
assert event.to_legacy_dict() == {
"type": "plan_set",
"steps": [{"title": "Read config", "status": "done"},
{"title": "Patch it", "status": "running"}],
}
def test_notice_serialises_with_its_level() -> None:
assert NoticeEvent(text="reading page 2/9", level="progress").to_legacy_dict() == {
"type": "notice", "level": "progress", "text": "reading page 2/9"}
def test_notice_defaults_to_the_info_level() -> None:
assert NoticeEvent(text="compacted").to_legacy_dict()["level"] == "info"
def test_outputs_added_and_removed_serialise_their_path_lists() -> None:
assert OutputsAddedEvent(paths=("a.md",)).to_legacy_dict() == {
"type": "outputs_added", "paths": ["a.md"]}
assert OutputsRemovedEvent(paths=("tmp.py",)).to_legacy_dict() == {
"type": "outputs_removed", "paths": ["tmp.py"]}
def test_history_ready_serialises_its_session_id() -> None:
assert HistoryReadyEvent(session_id="s7").to_legacy_dict() == {
"type": "history_ready", "session_id": "s7"}
# -- events introduced by R04 (no legacy consumer) ------------------------- #
def test_turn_completed_carries_the_final_answer_and_step_count() -> None:
event = TurnCompletedEvent(final_text="all done", steps_used=3)
assert event.to_legacy_dict() == {
"type": "turn_completed", "final_text": "all done", "steps_used": 3,
"cancelled": False, "budget_exhausted": False}
def test_error_event_is_fatal_unless_marked_recoverable() -> None:
assert ErrorEvent(message="boom").recoverable is False
assert ErrorEvent(message="rate limited", recoverable=True).recoverable is True
# -- parsing legacy dicts back into events --------------------------------- #
_ROUND_TRIP_CASES = [
TextChunkEvent(delta="hi"),
ReasoningChunkEvent(delta="hmm"),
AssistantMessageCompletedEvent(content="done"),
ToolCallStartedEvent(call_id="c", name="run_command", arguments={"command": "ls"},
preview=ToolPreview(kind="command", title="Run", text="ls")),
ToolCallStartedEvent(call_id="c", name="read_file"),
ToolOutputChunkEvent(call_id="c", name="run_command", delta="out"),
ToolCallFinishedEvent(call_id="c", name="save_file", ok=True, output="ok",
path="a.md", produced=["b.md"]),
ToolCallFinishedEvent(call_id="c", name="read_file", ok=False, output="missing"),
PlanUpdatedEvent(steps=(PlanStep(title="Step", status="pending"),)),
NoticeEvent(text="warned", level="warning"),
OutputsAddedEvent(paths=("a.md",)),
OutputsRemovedEvent(paths=("tmp.py",)),
HistoryReadyEvent(session_id="s7"),
TurnCompletedEvent(final_text="done", steps_used=2, cancelled=True),
ErrorEvent(message="boom", recoverable=True),
]
@pytest.mark.parametrize("event", _ROUND_TRIP_CASES, ids=lambda e: type(e).__name__)
def test_every_event_survives_a_round_trip_through_the_legacy_dict(event) -> None:
assert from_legacy_dict(event.to_legacy_dict()) == event
def test_unknown_event_types_parse_to_none_instead_of_raising() -> None:
# Co4E emits its own vocabulary (node_status, stage_text, run_done) which R04
# deliberately leaves alone; a bridge must be able to pass those through
# untouched rather than crash on them.
assert from_legacy_dict({"type": "node_status", "node_id": "n1"}) is None
assert from_legacy_dict({"type": ""}) is None
assert from_legacy_dict("not a dict") is None
def test_missing_payload_keys_parse_to_empty_values() -> None:
# Defensive: a truncated event from an older emitter must not kill the turn.
assert from_legacy_dict({"type": "text"}) == TextChunkEvent(delta="")
assert from_legacy_dict({"type": "tool_result", "id": "c", "name": "x"}) == (
ToolCallFinishedEvent(call_id="c", name="x", ok=False, output=""))
def test_plan_steps_from_legacy_drop_entries_without_a_title() -> None:
# normalize_plan_steps already clamps upstream; this only guards the parse
# path so a hand-written dict cannot produce a titleless step.
event = from_legacy_dict({"type": "plan_set",
"steps": [{"title": "Real", "status": "done"}, {"status": "done"}]})
assert event == PlanUpdatedEvent(steps=(PlanStep(title="Real", status="done"),))
+101
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@@ -0,0 +1,101 @@
"""R04-T03 (a) — unit tests for the value a finished turn returns.
Two callers need different things out of one turn today:
``ui/chat_panel.py::_finalize_turn`` wants the message list, while
``core/task_executors.py::_run_agent`` returns a
``(answer_text, timed_out, incomplete_reason)`` tuple assembled by hand. This
type is what both read instead, so "what happened in that turn?" has one answer
with names on it.
"""
from __future__ import annotations
from dataclasses import FrozenInstanceError
import pytest
from cowork_local.domain.agents.agent_event import PlanStep, TurnCompletedEvent
from cowork_local.domain.agents.agent_result import AgentResult
def test_result_rejects_mutation() -> None:
result = AgentResult(steps_used=1)
with pytest.raises(FrozenInstanceError):
result.steps_used = 2
def test_messages_are_frozen_into_a_tuple() -> None:
live = [{"role": "user", "content": "hi"}]
result = AgentResult(messages=live)
live.append({"role": "assistant", "content": "later"})
assert result.messages == ({"role": "user", "content": "hi"},)
def test_final_text_is_the_last_non_empty_assistant_message() -> None:
# A turn ends on a tool message often enough (cancelled mid-loop) that the
# answer cannot simply be messages[-1].
result = AgentResult(messages=[
{"role": "assistant", "content": "first pass"},
{"role": "assistant", "content": "the answer"},
{"role": "tool", "tool_call_id": "c", "name": "read_file", "content": "..."},
])
assert result.final_text == "the answer"
def test_final_text_skips_a_blank_assistant_message() -> None:
result = AgentResult(messages=[
{"role": "assistant", "content": "the answer"},
{"role": "assistant", "content": " "},
])
assert result.final_text == "the answer"
def test_final_text_is_empty_when_the_model_never_answered() -> None:
assert AgentResult(messages=[{"role": "user", "content": "hi"}]).final_text == ""
def test_a_plain_finished_turn_is_ok() -> None:
assert AgentResult(messages=[{"role": "assistant", "content": "done"}]).ok is True
def test_a_cancelled_turn_is_not_ok() -> None:
assert AgentResult(cancelled=True).ok is False
def test_a_failed_turn_is_not_ok_and_keeps_its_message() -> None:
result = AgentResult(error="SecurityBlocked: nope")
assert result.ok is False
assert result.error == "SecurityBlocked: nope"
def test_hitting_the_step_ceiling_is_reported_separately_from_cancelling() -> None:
# "Stopped because the safety limit was reached" and "the user pressed Stop"
# need different wording in the transcript, so they stay separate flags.
result = AgentResult(budget_exhausted=True, steps_used=30)
assert result.budget_exhausted is True
assert result.cancelled is False
def test_result_converts_to_the_turn_completed_event() -> None:
result = AgentResult(
messages=[{"role": "assistant", "content": "done"}],
steps_used=3, cancelled=False, budget_exhausted=True,
)
assert result.to_turn_completed_event() == TurnCompletedEvent(
final_text="done", steps_used=3, cancelled=False, budget_exhausted=True)
def test_plan_steps_are_frozen_into_a_tuple() -> None:
steps = [PlanStep(title="Draft", status="done")]
result = AgentResult(plan_steps=steps)
steps.append(PlanStep(title="Review"))
assert result.plan_steps == (PlanStep(title="Draft", status="done"),)
@@ -0,0 +1,132 @@
"""R04-T01 — unit tests for the immutable turn snapshot.
The snapshot exists so a turn already running cannot be altered by the UI the
user keeps clicking on. These tests pin exactly that: the object refuses
mutation, it copies the mutable collections handed to it at submit time, and it
owns the prompt-composition rules that were inline in
``ui/chat_panel.py::_start_turn``'s worker closure (prefix separator, session
notes, model-switch review note).
"""
from __future__ import annotations
from dataclasses import FrozenInstanceError
from pathlib import Path
import pytest
from cowork_local.domain.agents.conversation_execution_request import (
ConversationExecutionRequest,
)
def _request(**overrides) -> ConversationExecutionRequest:
"""A minimal valid request; each test overrides only what it exercises."""
base = {"turn_id": "t1", "session_id": "s1"}
base.update(overrides)
return ConversationExecutionRequest(**base)
# -- immutability ---------------------------------------------------------- #
def test_request_rejects_mutation_after_construction() -> None:
request = _request(model="gpt-4o-mini")
with pytest.raises(FrozenInstanceError):
request.model = "claude-sonnet-4-6"
def test_turn_id_is_required() -> None:
with pytest.raises(ValueError):
ConversationExecutionRequest(turn_id="", session_id="s1")
def test_session_id_is_required() -> None:
with pytest.raises(ValueError):
ConversationExecutionRequest(turn_id="t1", session_id="")
# -- snapshotting mutable UI state ---------------------------------------- #
def test_attachments_are_snapshotted_away_from_the_caller_list() -> None:
picked = ["a.docx"]
request = _request(attachments=picked)
picked.append("b.pdf") # the composer clears/refills its own list next turn
assert request.attachments == ("a.docx",)
def test_messages_are_snapshotted_away_from_the_live_history_list() -> None:
history = [{"role": "user", "content": "earlier"}]
request = _request(messages=history)
history.append({"role": "assistant", "content": "later"})
assert len(request.messages) == 1
assert isinstance(request.messages, tuple)
def test_allowed_tools_none_means_every_tool_stays_available() -> None:
# None and () must stay distinguishable: None = no restriction, () = deny
# every built-in tool. Coercing None to () would silently disarm the agent.
assert _request().allowed_tools is None
assert _request(allowed_tools=[]).allowed_tools == ()
def test_output_paths_accept_strings_and_normalise_to_path() -> None:
request = _request(output_dir="out/t1", home_output_root="out")
assert request.output_dir == Path("out/t1")
assert request.home_output_root == Path("out")
# -- derived turn policy --------------------------------------------------- #
def test_effective_max_steps_uses_the_interactive_cap_by_default() -> None:
assert _request(max_steps=30, completion_max_steps=200).effective_max_steps == 30
def test_effective_max_steps_lifts_the_cap_when_running_to_completion() -> None:
request = _request(max_steps=30, completion_max_steps=200, run_to_completion=True)
assert request.effective_max_steps == 200
def test_permission_gate_is_required_only_in_confirm_mode() -> None:
assert _request(gate_mode="confirm").requires_permission_gate is True
assert _request(gate_mode="auto").requires_permission_gate is False
def test_has_prompt_ignores_whitespace_only_input() -> None:
assert _request(prompt=" \n ").has_prompt is False
assert _request(prompt="do it").has_prompt is True
# -- prompt composition (moved out of the widget's worker closure) --------- #
def test_user_content_returns_the_body_unchanged_without_prefix_or_notes() -> None:
assert _request().user_content("the body") == "the body"
def test_user_content_separates_the_instruction_prefix_from_the_body() -> None:
request = _request(instruction_prefix="SKILL RULES")
assert request.user_content("the body") == "SKILL RULES\n\n---\n\nthe body"
def test_user_content_appends_session_notes_after_the_body() -> None:
request = _request(session_notes="Files produced earlier: a.md")
assert request.user_content("the body") == "the body\n\nFiles produced earlier: a.md"
def test_user_content_falls_back_to_session_notes_when_the_body_is_empty() -> None:
# An attachment-only turn has no typed text, so the notes must not be
# prefixed with a stray blank line.
request = _request(session_notes="Files produced earlier: a.md")
assert request.user_content("") == "Files produced earlier: a.md"
def test_user_content_puts_the_review_note_ahead_of_everything_else() -> None:
request = _request(instruction_prefix="SKILL RULES", review_note="[Note: switched]")
content = request.user_content("the body")
assert content == "[Note: switched]\n\nSKILL RULES\n\n---\n\nthe body"