feat(R04): run every Cowork turn through ConversationApplicationService

R04-T03 — the turn lifecycle, extracted from `core/chat_agent.py::run_cowork`
into `application/conversations/`. The 260-line body mixed the lifecycle (step
budget, cancel checks, guard -> preview -> gate -> execute ordering, sandbox
tidy-up) with the machinery doing each step, and reaching any of it meant
standing up a Qt widget and a worker thread. It is now a plain object driven
through two Protocols and six callables (`turn_runtime.py`), with the concrete
`core/*` wiring confined to `core_runtime_adapter.py` — the same shape R03 used
for routing. Faithful port, not an improvement pass: where the original had a
quirk (the step-ceiling note only merges into the answer when the last message
is the assistant's) the quirk is preserved and commented.

R04-T04 — `ui/cowork_tab.py::build_job` no longer calls run_cowork. It captures
the widget's state at submit time, builds the request via the new
`cowork_turn_request.py` and executes it. `execute(..., messages=...)` hands the
widget's own list over because `_reattach_running_turn` replays from it WHILE
the worker appends and `_finalize_turn` slices it afterwards — a private list
would break both silently.

R04-T05 — `core/task_executors.py`'s cowork branch shares the same engine. All
five unattended-run behaviours stay put (plan reminder, history_ready, History
autosave per assistant message, timeout notice, plan_incomplete_reason), and
`_unattended_prompt` now expresses the load-bearing prefix order in one
readable call instead of three successive rebindings.

Verification: 74 new tests (364 passed, 1 skipped overall; check_imports PASS).
The two that matter most:
- `test_conversation_service_parity.py` runs the same scripted turn through
  run_cowork AND the service and compares the event stream, the resulting
  conversation and the advertised tool list across 7 scenarios;
- `test_task_executor_turn.py` was written BEFORE the migration and passed 8/8
  against the old code, then unchanged against the new.

Known: `ui/cowork_tab.py` (416 -> 455) and `core/task_executors.py` (476 -> 524)
stay above the 400-LOC limit. Both were already over it before this change;
bringing them under needs the R08 / R07 decompositions.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-23 13:14:15 +09:00
co-authored by Claude Opus 5
parent 19e6b4deb2
commit 3665135c38
16 changed files with 2452 additions and 48 deletions
@@ -0,0 +1,322 @@
"""The turn lifecycle, once, in pure Python (R04-T03).
Extracted from ``core/chat_agent.py::run_cowork``, whose 260-line body mixed the
lifecycle (compose the prompt, call the model, dispatch tools, respect the step
ceiling, tidy the sandbox) with the concrete machinery that does each of those
things. The lifecycle is the part with rules worth testing — and the part that
was untestable, because reaching it meant standing up a Qt widget and a worker
thread.
Here it is a plain object driven through the seams in :mod:`turn_runtime`, so a
test states a rule ("the guard runs before the model", "a rejected command never
executes") in three lines. ``core/chat_agent.py`` keeps its signature and
delegates, and the presentation layer keeps receiving the same events via the
legacy codec, so nothing downstream had to change with it.
Behavioural contract: this is a faithful port, not an improvement pass. Where
the original had a quirk (the step-ceiling note only merges into the answer when
the last message is the assistant's), the quirk is preserved and commented —
changing what a user sees belongs in its own change, not smuggled into a move.
"""
from __future__ import annotations
import logging
from typing import Any, Dict, List, Optional, Tuple
from ...domain.agents.agent_event import (
AssistantMessageCompletedEvent,
ErrorEvent,
OutputsAddedEvent,
OutputsRemovedEvent,
PlanStep,
PlanUpdatedEvent,
ReasoningChunkEvent,
TextChunkEvent,
ToolCallFinishedEvent,
ToolCallStartedEvent,
ToolOutputChunkEvent,
)
from ...domain.agents.agent_result import AgentResult
from ...domain.agents.conversation_execution_request import ConversationExecutionRequest
from .turn_runtime import (
BUDGET_NOTE_TEMPLATE,
GATED_TOOLS,
PLAN_TOOL,
REASONING_ONLY_NOTE,
REJECTED_OUTPUT,
AttachmentReader,
CancelFn,
CommandGuard,
ContextCompactor,
EventSink,
ModelCallPort,
PermissionRequest,
PromptGuard,
PromptPreparer,
ToolRuntimePort,
)
logger = logging.getLogger("cowork_local.application.conversations")
class ConversationApplicationService:
"""Runs one :class:`ConversationExecutionRequest` to completion."""
def __init__(
self,
model: ModelCallPort,
tools: ToolRuntimePort,
*,
prepare_prompt: Optional[PromptPreparer] = None,
prompt_guard: Optional[PromptGuard] = None,
command_guard: Optional[CommandGuard] = None,
compact: Optional[ContextCompactor] = None,
permission_request: Optional[PermissionRequest] = None,
attachment_reader: Optional[AttachmentReader] = None,
) -> None:
self._model = model
self._tools = tools
# Every hook is optional so the service degrades to a plain chat turn.
# That is not only a test convenience: a headless caller legitimately has
# no guards (``security_config=None`` today) and no permission dialog.
self._prepare_prompt = prepare_prompt
self._prompt_guard = prompt_guard
self._command_guard = command_guard
self._compact = compact
self._permission_request = permission_request
self._attachment_reader = attachment_reader
# -- public API ------------------------------------------------------ #
def execute(self, request: ConversationExecutionRequest, sink: EventSink,
cancel: Optional[CancelFn] = None,
messages: Optional[List[Dict[str, Any]]] = None) -> AgentResult:
"""Run the turn, streaming events to ``sink``, and report the outcome.
``messages``, when given, is a working list the caller already built —
it MUST already end with this turn's user message, and the service
appends into that very object instead of composing its own. The Cowork
widget needs this: it hands out the same list to
``_reattach_running_turn``, which replays the steps done so far while the
worker is still appending, and to ``_finalize_turn``, which slices it by
the pre-turn snapshot length. A private list would break both silently.
Passing ``None`` (every headless caller) lets the service compose the
list from the request, which is the mode the rest of this class assumes.
Raises whatever the runtime raises (a blocked prompt, a dead gateway):
the caller already has a failure path for that — ``AgentWorker.failed``
in the UI, the artifact writer in Schedule Task — and swallowing the
exception here would silently turn a failed turn into an empty answer.
An :class:`ErrorEvent` is emitted first so subscribers see the failure
on the same stream as everything else.
"""
cancel = cancel or (lambda: False)
# -- pre-flight. Runs BEFORE the output snapshot, so a turn refused here
# leaves the output folder completely untouched (tidying is not a
# read-only operation — see ToolRuntimePort.finalize).
try:
# The caller's list is used by reference on purpose (see above); only
# the self-composed path may build a fresh one.
working = messages if messages is not None else self._compose_messages(request)
tools = list(self._tools.specs(request.allowed_tools))
if self._prepare_prompt is not None:
self._prepare_prompt(working, tuple(getattr(t, "name", "") for t in tools))
if request.enforce_rules and self._prompt_guard is not None:
self._prompt_guard(working)
except Exception as exc: # noqa: BLE001 — reported, then re-raised as-is
sink(ErrorEvent(message=str(exc)))
raise
before = self._tools.snapshot()
steps_used = 0
plan_steps: Tuple[PlanStep, ...] = ()
completed_naturally = False
try:
for _ in range(request.effective_max_steps):
if cancel():
break
# Auto-compress when nearing the model's context budget; a no-op
# when off or when the conversation is still short.
if self._compact is not None:
self._compact(working, cancel)
assistant = self._model.call(
working, tools,
on_text=lambda piece: sink(TextChunkEvent(delta=piece)),
on_reasoning=lambda piece: sink(ReasoningChunkEvent(delta=piece)),
cancel=cancel,
)
working.append(assistant)
steps_used += 1
tool_calls = assistant.get("tool_calls") or []
if not tool_calls and not (assistant.get("content") or "").strip():
# Written into the message, not just emitted, so the stored
# conversation never ends on a blank assistant turn.
assistant["content"] = REASONING_ONLY_NOTE
sink(TextChunkEvent(delta=REASONING_ONLY_NOTE))
sink(AssistantMessageCompletedEvent(content=assistant.get("content", "")))
if not tool_calls:
completed_naturally = True
break
for call in tool_calls:
if cancel():
break
tool_message, steps = self._dispatch(request, call, sink, cancel)
working.append(tool_message)
if steps is not None:
plan_steps = steps
if not completed_naturally and not cancel():
self._announce_budget_exhausted(request, working, sink)
except Exception as exc: # noqa: BLE001 — reported, then re-raised as-is
sink(ErrorEvent(message=str(exc)))
raise
finally:
# Always tidy: the sandbox and generator scripts must not survive a
# turn that stopped abruptly. Runs on success, cancel and failure.
self._finalize_outputs(before, sink, cancelled=cancel())
result = AgentResult(
messages=working, steps_used=steps_used, cancelled=cancel(),
budget_exhausted=not completed_naturally and not cancel(),
plan_steps=plan_steps,
)
sink(result.to_turn_completed_event())
return result
# -- internals ------------------------------------------------------- #
def _compose_messages(self, request: ConversationExecutionRequest) -> List[Dict[str, Any]]:
"""History snapshot plus this turn's user message.
The attachment text is read HERE rather than when the request was built,
because extraction is slow enough to freeze the UI thread; the request
deliberately carries paths only.
"""
body = request.prompt
if self._attachment_reader is not None:
body = self._attachment_reader(request.prompt, request.attachments)
messages = [dict(m) for m in request.messages]
messages.append({"role": "user", "content": request.user_content(body)})
return messages
def _dispatch(self, request: ConversationExecutionRequest, call: Dict[str, Any],
sink: EventSink, cancel: CancelFn
) -> Tuple[Dict[str, Any], Optional[Tuple[PlanStep, ...]]]:
"""Run one tool call.
Returns ``(tool_message, plan_steps)`` — the message to append to the
conversation, and the new checklist when this call was the plan tool
(``None`` otherwise, so the caller can tell "no change" from "empty
plan").
"""
call_id = str(call.get("id", ""))
name = str(call.get("name", ""))
args = call.get("arguments") or {}
# The plan tool is invisible in the transcript: it updates the Plan panel
# and nothing else, so it skips preview, guard and gate entirely.
if name == PLAN_TOOL:
outcome = self._tools.execute(name, args, on_output=None, cancel=cancel)
steps = tuple(outcome.get("plan_steps") or ())
sink(PlanUpdatedEvent(steps=steps))
return self._tool_message(call_id, name, outcome.get("output", "")), steps
# Announce first: the user sees the code/command about to run before the
# guard or the approval dialog interrupts them, which is the whole point
# of showing the step CLI-style.
preview = self._tools.preview(name, args)
sink(ToolCallStartedEvent(call_id=call_id, name=name, arguments=dict(args),
preview=preview))
if request.enforce_rules and self._command_guard is not None:
self._command_guard(name, args)
if not self._approved(request, name, args, preview, sink, call_id):
return self._tool_message(call_id, name, REJECTED_OUTPUT), None
outcome = self._tools.execute(
name, args,
on_output=lambda piece: sink(ToolOutputChunkEvent(
call_id=call_id, name=name, delta=piece)),
cancel=cancel,
)
sink(ToolCallFinishedEvent(
call_id=call_id, name=name, ok=bool(outcome.get("ok", False)),
output=str(outcome.get("output", "")), path=str(outcome.get("path", "") or ""),
produced=outcome.get("produced") or (),
))
return self._tool_message(call_id, name, outcome.get("output", "")), None
def _approved(self, request: ConversationExecutionRequest, name: str,
args: Dict[str, Any], preview: Any, sink: EventSink,
call_id: str) -> bool:
"""Whether this call may run.
Only command-shaped tools are gated, and only when the workspace asked
to confirm them: file writes stay inside the turn's own sandbox, so
prompting for those would be noise. A rejection is reported as a failed
tool result — the model needs to read back that it was refused, or it
will simply try the same call again.
"""
if not request.requires_permission_gate or name not in GATED_TOOLS:
return True
if self._permission_request is None:
# Confirm mode with nobody to ask: refusing is the safe direction,
# since auto-running is exactly what confirm mode exists to prevent.
logger.warning("turn: confirm mode without a permission callback — refusing %r", name)
approved = False
else:
approved = bool(self._permission_request({
"name": name, "args": args,
"preview": preview.to_dict() if preview is not None else {},
}))
if not approved:
sink(ToolCallFinishedEvent(call_id=call_id, name=name, ok=False,
output=REJECTED_OUTPUT))
return approved
@staticmethod
def _tool_message(call_id: str, name: str, output: Any) -> Dict[str, Any]:
"""The canonical ``role: tool`` message the model reads back."""
return {"role": "tool", "tool_call_id": call_id, "name": name,
"content": str(output or "")}
@staticmethod
def _announce_budget_exhausted(request: ConversationExecutionRequest,
messages: List[Dict[str, Any]], sink: EventSink) -> None:
"""Report being cut off by the step ceiling.
The note always reaches the transcript. It is merged into the stored
answer only when the last message is the assistant's — which, when the
ceiling is hit, it never is (the turn ends on a tool result). The branch
is kept because it is what the current runtime does, and because it is
the correct behaviour the day a caller ends the loop differently.
"""
note = BUDGET_NOTE_TEMPLATE.format(steps=request.effective_max_steps)
sink(TextChunkEvent(delta=note))
if messages and messages[-1].get("role") == "assistant":
messages[-1]["content"] = (messages[-1].get("content") or "") + note
def _finalize_outputs(self, before: Any, sink: EventSink, cancelled: bool) -> None:
"""Tidy the output folder and report what moved.
Failures are logged, never raised: this runs in a ``finally``, so an
exception here would replace the turn's real error (or its success) with
a housekeeping one.
"""
try:
removed, added = self._tools.finalize(before, cancelled=cancelled)
except Exception: # noqa: BLE001
logger.exception("turn: tidying the output folder failed")
return
if removed:
sink(OutputsRemovedEvent(paths=tuple(removed)))
if added:
sink(OutputsAddedEvent(paths=tuple(added)))
__all__ = ["ConversationApplicationService"]
@@ -0,0 +1,325 @@
"""Wires :class:`ConversationApplicationService` to the existing runtime (R04-T03).
The service is written against the narrow seams in :mod:`turn_runtime` so it can
be tested with plain fakes. This module supplies the real implementations — the
provider call with its recovery pass, the tool/sandbox runtime, the security
guards, context compaction — and is therefore the ONLY file in
``application/conversations/`` that knows ``core/*`` exists. Same shape (and
same reason) as ``application/model_routing/core_routing_adapter.py`` in R03.
Every ``core`` import is deferred into a method body: importing the tool runtime
pulls in ``requests``, ``psutil`` and the sandbox stack, and code that merely
*builds* a service must not pay for that.
Faithfulness notes — two places where this reproduces a quirk of the current
runtime rather than the behaviour one would design fresh. Both are marked
inline: the MS365 system-prompt paragraph keys off the CONFIGURED extra tools
(not the advertised subset), and the ``tool_result`` path falls back to the
call's own ``path`` argument resolved against the workdir.
"""
from __future__ import annotations
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple
from ...domain.agents.agent_event import PlanStep, ToolPreview
from .conversation_application_service import ConversationApplicationService
from .turn_runtime import PLAN_TOOL, EventSink
# Legacy emit: the dict-based callback every current caller already owns.
LegacyEmit = Callable[[Dict[str, Any]], None]
def legacy_event_sink(emit: LegacyEmit) -> EventSink:
"""Adapt a typed :class:`EventSink` onto the legacy dict ``emit``.
This is what lets R04 land without touching the presentation layer: the
service thinks in typed events, ``ui/chat_panel.py::_on_event`` keeps
receiving exactly the dicts it already dispatches on. Deleted in R08 once
the widget consumes events directly.
"""
return lambda event: emit(event.to_legacy_dict())
class CoreModelCall:
""":class:`ModelCallPort` over ``code_agent._call_provider_with_recovery``.
Not ``provider.chat`` directly: the recovery wrapper adds the one bounded
retry that hides a dropped connection or a momentarily unreachable gateway,
and losing it would be a visible regression on flaky corporate networks.
"""
def __init__(self, provider: Any) -> None:
self._provider = provider
def call(self, messages, tools, on_text=None, on_reasoning=None, cancel=None):
from ...core.code_agent import _call_provider_with_recovery
return _call_provider_with_recovery(self._provider, messages, tools, on_text,
cancel, on_reasoning)
class CoreToolRuntime:
""":class:`ToolRuntimePort` over ``core/tools.py`` + Cowork's file tools."""
def __init__(self, output_dir: Path, *, title: str = "",
extra_tools: Optional[Sequence[Any]] = None, extra_executor=None,
security_config: Any = None, agent_role: str = "") -> None:
self._output_dir = Path(output_dir)
self._title = title
self._extra_tools = list(extra_tools or ())
self._extra_names = {getattr(t, "name", "") for t in self._extra_tools}
# The connector executor MCP/REST tools are routed to; None when the
# turn has no connectors enabled.
self._extra_executor = extra_executor
self._security_config = security_config
self._agent_role = agent_role
self._ctx: Any = None # built on first use (see _tool_context)
# -- the configured extra tools, for the system-prompt hints ---------- #
@property
def extra_names(self) -> frozenset:
return frozenset(self._extra_names)
def _tool_context(self):
"""The sandboxed ``ToolContext`` every built-in tool call runs inside.
Built once per turn and cached: it carries the resource limits and the
network policy, so re-deriving it mid-turn could let a Settings change
take effect halfway through work already in flight.
"""
if self._ctx is None:
from ...core import agent_security
from ...core.tools import ToolContext
limits, block_network = agent_security.sandbox_settings(self._security_config)
self._ctx = ToolContext(
self._output_dir, flatten_writes=True, # keep every file in the Output root
resource_limits=limits, block_network=block_network,
allow_url_fetch=agent_security.url_fetch_allowed(self._security_config),
jira=(self._security_config.data.get("jira") if self._security_config else None),
)
return self._ctx
# -- ToolRuntimePort -------------------------------------------------- #
def specs(self, allowed_tools: Optional[Sequence[str]] = None) -> List[Any]:
"""Advertised tools: Cowork's own two, the enabled built-ins, then MCP.
``allowed_tools`` restricts the list so a read-only step literally cannot
write. ``update_plan`` and the connector tools always survive the filter:
the plan tool has no side effects, and connectors are opted into
explicitly rather than governed by the built-in capability scope.
"""
from ...core.chat_agent import SAVE_FILE_SPEC
from ...core.plan import UPDATE_PLAN_SPEC
from ...core.tools import enabled_tool_specs
specs = ([SAVE_FILE_SPEC, UPDATE_PLAN_SPEC]
+ list(enabled_tool_specs(self._security_config))
+ self._extra_tools)
if allowed_tools is None:
return specs
allow = set(allowed_tools) | {PLAN_TOOL} | self._extra_names
return [t for t in specs if getattr(t, "name", "") in allow]
def preview(self, name: str, args: Dict[str, Any]) -> Optional[ToolPreview]:
"""What the user sees before the call runs."""
# A connector call has no local diff to show, so it renders as the plain
# argument dump the runtime already used.
if name in self._extra_names:
return ToolPreview(kind="info", title=name, text=str(args))
if name == "save_file":
return self._save_file_preview(args)
from ...core.tools import describe_action
raw = describe_action(self._tool_context(), name, args)
return ToolPreview.from_dict(raw)
def _save_file_preview(self, args: Dict[str, Any]) -> ToolPreview:
"""A before/after diff for the file the agent is about to write.
A brand-new file renders all-green (before is empty); an overwrite shows
the real change, so saving a file reads like editing one.
"""
import difflib
from ...core.chat_agent import _structure_summary, _titled_filename
fname = _titled_filename(self._title, args.get("filename", "output.txt"))
content = str(args.get("content", ""))
summary = _structure_summary(fname, content)
old = ""
existing = self._output_dir / fname
if existing.exists():
try:
old = existing.read_text(encoding="utf-8", errors="replace")
except OSError:
pass # unreadable existing file: show it as a fresh write
diff = "".join(difflib.unified_diff(
old.splitlines(keepends=True), content.splitlines(keepends=True),
fromfile=f"a/{fname}", tofile=f"b/{fname}",
)) or content[:4000]
return ToolPreview(kind="diff", title=f"Save {fname}",
text=f"{summary}\n\n{diff[:4000]}")
def execute(self, name: str, args: Dict[str, Any], on_output=None,
cancel=None) -> Dict[str, Any]:
"""Run one tool call and return the runtime's result mapping."""
if name == PLAN_TOOL:
return self._execute_plan(args)
if name in self._extra_names and self._extra_executor is not None:
# Connector results carry no local file, so no path/produced keys —
# matching what the runtime reports for an MCP call today.
result = self._extra_executor(name, args) or {}
return {"ok": bool(result.get("ok", False)), "output": result.get("output", "")}
if name == "save_file":
from ...core.chat_agent import _do_save_file
return dict(_do_save_file(self._output_dir, self._title, args))
from ...core.tools import execute_tool
ctx = self._tool_context()
result = dict(execute_tool(ctx, name, args, cancel=cancel, on_output=on_output,
agent_role=self._agent_role))
# Quirk preserved: a tool that wrote the file named in its OWN arguments
# (write_file/edit_file) does not report a path, so the runtime derives
# one from the argument. Dropping this would empty the Output list.
if not result.get("path") and isinstance(args, dict) and args.get("path"):
result["path"] = str(ctx.workdir / str(args["path"]))
return result
def _execute_plan(self, args: Dict[str, Any]) -> Dict[str, Any]:
"""Apply an ``update_plan`` call: validate the steps and audit them.
Produces no file and no chat bubble; the service turns the returned
steps into a single plan event.
"""
from ...core import agent_roles, audit_log
from ...core.plan import normalize_plan_steps
steps = normalize_plan_steps(args.get("steps"))
audit_log.record("tool_call", PLAN_TOOL, True, f"{len(steps)} step(s)",
agent_role=agent_roles.PLANNER)
return {"ok": True, "output": "Plan updated.",
"plan_steps": [PlanStep(title=s["title"], status=s["status"]) for s in steps]}
def snapshot(self) -> Any:
from ...core.tools import _snapshot
return _snapshot(self._output_dir)
def finalize(self, before: Any, cancelled: bool = False
) -> Tuple[List[str], List[str]]:
"""Drop the scratch sandbox and flatten deliverables into the root.
Returns ``(gone, arrived)``: a file that MOVED counts as both, because
the Output list keys entries by path and must drop the old one.
"""
from ...core.chat_agent import _cleanup_cowork_intermediates
removed, moved = _cleanup_cowork_intermediates(self._output_dir, before,
cancelled=cancelled)
gone = list(removed) + [old for old, _new in moved]
arrived = [new for _old, new in moved]
return gone, arrived
def build_cowork_conversation_service(
provider: Any,
output_dir: Path,
emit: LegacyEmit,
*,
title: str = "",
project_context: str = "",
extra_tools: Optional[Sequence[Any]] = None,
extra_executor=None,
security_config: Any = None,
gate: Any = None,
agent_role: str = "",
) -> ConversationApplicationService:
"""A service wired to the real runtime, ready to execute a Cowork turn.
``emit`` is the legacy dict callback: the guards and the compactor publish
their own notices through it directly (exactly as they do now), while the
service's typed events reach it via :func:`legacy_event_sink`.
``gate`` present means the workspace asked to confirm commands; pass the
request with ``gate_mode="confirm"`` so the two agree. A gate of ``None``
keeps the pre-existing auto-run behaviour.
"""
from ...core import agent_roles
tools = CoreToolRuntime(
output_dir, title=title, extra_tools=extra_tools, extra_executor=extra_executor,
security_config=security_config, agent_role=agent_role or agent_roles.COWORK,
)
def prepare_prompt(messages: List[Dict[str, Any]], advertised: Tuple[str, ...]) -> None:
"""Insert the system prompt, then fold in skills, rules and project text.
``advertised`` is unused on purpose: the runtime decides the MS365
paragraph from the CONFIGURED connector tools, not from the subset a
capability scope left advertised. Changing that changes the prompt the
model sees, so it stays as-is here and belongs to R05's tool-policy work.
"""
from ...core.chat_agent import (
COWORK_TOOL_PROMPT,
OPENDATALOADER_PDF_PROMPT,
_apply_project_context,
_apply_security_rules,
_apply_skills,
)
from ...core.deps import _can_pip
from ...core.java_runtime import find_java
from ...core.security_rules import load_rules
from ...core.skills import active_skills_text
if not messages or messages[0].get("role") != "system":
system = COWORK_TOOL_PROMPT
if any(n.startswith("ms365_") for n in tools.extra_names):
system += ("\nThe user has signed in to Microsoft 365 and enabled some ms365__* "
"tools (Outlook / Teams / OneDrive / SharePoint / meeting transcripts, "
"via the built-in MS365 MCP server). Use them whenever the request "
"involves that data — don't say you can't access it.")
if find_java() is not None and _can_pip():
# Only advertise the Java-backed PDF extractor when BOTH the JVM
# and pip are available, so the agent is never steered into a
# command that cannot work on this machine.
system += "\n\n" + OPENDATALOADER_PDF_PROMPT
messages.insert(0, {"role": "system", "content": system})
_apply_skills(messages, active_skills_text())
_apply_security_rules(messages, load_rules())
_apply_project_context(messages, project_context)
def prompt_guard(messages: List[Dict[str, Any]]) -> None:
from ...core import agent_security
agent_security.enforce_prompt(provider, messages, security_config, emit)
def command_guard(name: str, args: Dict[str, Any]) -> None:
from ...core import agent_security
agent_security.enforce_command(provider, name, args, security_config, emit)
def compact(messages: List[Dict[str, Any]], cancel) -> None:
from ...core import context_budget
context_budget.maybe_compact(provider, messages, security_config,
emit=emit, cancel=cancel)
return ConversationApplicationService(
CoreModelCall(provider), tools,
prepare_prompt=prepare_prompt,
prompt_guard=prompt_guard,
command_guard=command_guard,
compact=compact,
permission_request=(gate.request if gate is not None else None),
)
__all__ = [
"LegacyEmit", "legacy_event_sink", "CoreModelCall", "CoreToolRuntime",
"build_cowork_conversation_service",
]
@@ -0,0 +1,77 @@
"""Turn the Cowork widget's captured state into a request (R04-T04).
``ui/cowork_tab.py::build_job`` reads a dozen values off the widget on the UI
thread and has to translate three of them before a turn can run: which message
is this turn's prompt, which messages are its history, and whether the workspace
wants commands confirmed. Those rules lived inline in the widget, where no test
could reach them — and each fails silently when wrong (a duplicated user message,
or a command that quietly stops asking for approval).
They live here instead, as the mapping step the migration map assigns to the
application layer. The widget keeps only what is genuinely widget-specific:
reading its own state and building the provider.
Layer rules (``docs/architecture/ADR-001-layered-architecture.md``): pure Python.
Everything arrives as a plain value, so this module never sees a widget.
"""
from __future__ import annotations
from typing import Any, Dict, Optional, Sequence
from ...domain.agents.conversation_execution_request import ConversationExecutionRequest
def build_cowork_turn_request(
*,
turn_id: str,
session_id: str,
messages: Sequence[Dict[str, Any]],
surface: str = "cowork",
project_id: str = "",
title: str = "",
provider_id: str = "",
model: str = "",
instructions: str = "",
output_dir: Optional[Any] = None,
home_output_root: Optional[Any] = None,
confirm_commands: bool = False,
agent_role: str = "cowork",
) -> ConversationExecutionRequest:
"""Build one Cowork turn's immutable request.
``messages`` is the widget's working list, which ALREADY ends with this
turn's user message (the chat panel composes it — prefix, attachments,
session notes — before the job starts). So the prompt is that last message
and the history is everything before it. The request records both; the
service is handed the same working list and appends into it.
Keyword-only on purpose: a dozen positional strings in a call site is exactly
how a title ends up in the project-id slot.
"""
history = list(messages or ())
# ``pop`` rather than ``[-1]``/``[:-1]`` so the empty-list case needs no
# special branch: a turn with nothing in it yields an empty prompt instead of
# raising IndexError deep inside a worker thread.
last = history.pop() if history else {}
return ConversationExecutionRequest(
turn_id=turn_id,
session_id=session_id,
surface=surface,
project_id=project_id,
title=title,
prompt=str(last.get("content") or ""),
messages=history,
provider_id=provider_id,
model=model,
project_context=instructions,
output_dir=output_dir,
home_output_root=home_output_root,
# The workspace's Auto-run override (or the global setting) decides
# whether run_command/install_package must be approved first.
gate_mode="confirm" if confirm_commands else "auto",
agent_role=agent_role,
)
__all__ = ["build_cowork_turn_request"]
+177
View File
@@ -0,0 +1,177 @@
"""The seams :mod:`conversation_application_service` runs a turn through (R04-T03).
Two Protocols and six callables — chosen deliberately, not by reflex. The
refactor plan forbids giving every class an interface, so a contract exists here
only where there is both a real ``core/*`` implementation AND a test double:
* :class:`ModelCallPort` — one provider round-trip *including* the app's
existing context-overflow recovery, which is why the raw ``Provider.chat``
signature is not enough.
* :class:`ToolRuntimePort` — the tool + output-folder runtime, kept as one
cohesive object because every method operates on the same sandbox.
Everything else is a single function, so it is expressed as a callable type
rather than a class with one method (the same choice R03 made for
``ConfirmationCallback``). All of them are optional: a service built with none
of them still runs a plain chat turn, which is what keeps the unit tests short.
Layer rules (``docs/architecture/ADR-001-layered-architecture.md``): application
layer — pure Python. Nothing here imports PySide6, ``core.*``, ``providers.*``
or ``ui.*``; the concrete wiring lives in :mod:`core_runtime_adapter`.
"""
from __future__ import annotations
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Protocol,
Sequence,
Tuple,
runtime_checkable,
)
from ...domain.agents.agent_event import AgentEvent, ToolPreview
# The plan tool is special-cased by the loop: it drives the Plan panel and
# produces no chat bubble and no file. Named here so the check is not a bare
# string literal in the middle of the dispatch.
PLAN_TOOL = "update_plan"
# Tools that need approval before they run when the workspace is in confirm
# mode. R05 replaces this tuple with a real ``ToolPolicyGateway`` keyed on
# ToolCapability; until then it mirrors exactly what the runtime gates today.
GATED_TOOLS = ("run_command", "install_package")
# Shown when the user (or the workspace policy) rejects a proposed command. The
# exact string also becomes the tool message the model reads back, so it must
# stay stable.
REJECTED_OUTPUT = "Rejected by user."
# A reasoning model can answer with thinking only. The note is written into the
# assistant message itself, not merely emitted, so an unattended run does not
# read back an empty answer and report "(no output)".
REASONING_ONLY_NOTE = "*(model returned only its reasoning — try rephrasing)*"
# Emitted when the turn is stopped by its own safety ceiling rather than by the
# model finishing. Never silent: being cut off looks exactly like being done.
BUDGET_NOTE_TEMPLATE = (
"\n\n⚠️ Reached the {steps}-step safety limit before the task signalled "
"completion — stopping here. Re-run to continue if more work remains."
)
def combine_instructions(*blocks: Optional[str]) -> str:
"""Join the standing-instruction blocks of a turn, skipping the absent ones.
A turn's instructions arrive as several independent blocks — the project's
shared context, an Admin agent's persona, a skill's rules, the
"this runs unattended" reminder — and each caller was joining them inline
with its own ``f"{a}\\n\\n{b}" if a else b`` expression. Two call sites now
need the same rule (the Cowork widget in R04-T04 and the task runner in
R04-T05), which is the point at which it stops being an expression.
Whitespace-only blocks count as absent: they would otherwise open the system
prompt with a stray blank line.
"""
return "\n\n".join(b.strip() for b in blocks if b and b.strip())
# --------------------------------------------------------------------------- #
# Callables.
# --------------------------------------------------------------------------- #
# Receives every typed event the turn produces. The caller decides what that
# means — render it, forward it as a legacy dict, autosave on it.
EventSink = Callable[[AgentEvent], None]
# True once the user has asked to stop. Polled between steps and between tool
# calls, the same cadence the current runtime uses.
CancelFn = Callable[[], bool]
# ``(prompt, attachment_paths) -> body``. Runs on the worker thread because
# extracting a .docx may pip-install a parser or call LibreOffice.
AttachmentReader = Callable[[str, Tuple[str, ...]], str]
# ``(messages, advertised_tool_names) -> None`` — inserts the system prompt and
# folds in skills, security rules and project instructions, in place. It needs
# the tool names because the system prompt gains an MS365 paragraph only when
# ms365 tools are actually present.
PromptPreparer = Callable[[List[Dict[str, Any]], Tuple[str, ...]], None]
# Reviews the assembled request; raises to refuse the turn outright.
PromptGuard = Callable[[List[Dict[str, Any]]], None]
# Reviews one proposed tool call; raises to refuse it.
CommandGuard = Callable[[str, Dict[str, Any]], None]
# ``(messages, cancel) -> None``. Summarises old turns in place when the
# conversation nears the model's context budget; a no-op when compaction is off
# or the conversation is short. It takes the cancel signal because compacting
# calls the model itself, so Stop has to reach it too.
ContextCompactor = Callable[[List[Dict[str, Any]], "CancelFn"], None]
# ``(action) -> approved``. Blocks the worker thread while a human decides.
PermissionRequest = Callable[[Dict[str, Any]], bool]
# --------------------------------------------------------------------------- #
# Ports.
# --------------------------------------------------------------------------- #
@runtime_checkable
class ModelCallPort(Protocol):
"""One call to the model, with the app's retry/recovery behaviour applied."""
def call(self, messages: List[Dict[str, Any]], tools: Sequence[Any],
on_text: Optional[Callable[[str], None]] = None,
on_reasoning: Optional[Callable[[str], None]] = None,
cancel: Optional[CancelFn] = None) -> Dict[str, Any]:
"""Return the canonical assistant message (content plus tool calls)."""
@runtime_checkable
class ToolRuntimePort(Protocol):
"""The tools a turn may call, and the folder its files land in."""
def specs(self, allowed_tools: Optional[Sequence[str]] = None) -> Sequence[Any]:
"""Tool specs to advertise to the model, already filtered.
Returns opaque objects (the provider layer's ``ToolSpec``); the service
only ever reads ``.name`` off them, which is what keeps this layer free
of a provider import.
"""
def preview(self, name: str, args: Dict[str, Any]) -> Optional[ToolPreview]:
"""Human-readable description of a call that is about to run."""
def execute(self, name: str, args: Dict[str, Any],
on_output: Optional[Callable[[str], None]] = None,
cancel: Optional[CancelFn] = None) -> Dict[str, Any]:
"""Run one tool call.
Returns the runtime's own result mapping: ``ok``, ``output``, optionally
``path``/``produced`` for files it created, and ``plan_steps`` for the
plan tool.
"""
def snapshot(self) -> Any:
"""Opaque record of the output folder before the turn started."""
def finalize(self, before: Any, cancelled: bool = False
) -> Tuple[Sequence[str], Sequence[str]]:
"""Tidy the output folder; return ``(removed_paths, added_paths)``.
Not read-only — it deletes the scratch sandbox and flattens sub-folders —
so the service only calls it for a turn that actually started.
"""
__all__ = [
"PLAN_TOOL", "GATED_TOOLS", "REJECTED_OUTPUT", "REASONING_ONLY_NOTE",
"BUDGET_NOTE_TEMPLATE", "combine_instructions",
"EventSink", "CancelFn", "AttachmentReader", "PromptPreparer", "PromptGuard",
"CommandGuard", "ContextCompactor", "PermissionRequest",
"ModelCallPort", "ToolRuntimePort",
]
+69 -19
View File
@@ -2,7 +2,9 @@
``execute_task`` dispatches by ``task_type`` to the app's existing engines: ``execute_task`` dispatches by ``task_type`` to the app's existing engines:
- ``cowork`` → ``chat_agent.run_cowork`` (documents/answers, real files) - ``cowork`` → ``ConversationApplicationService`` (documents/answers, real
files) — the same turn engine the interactive Cowork chat
runs on since R04-T05
- ``co4e_code`` → ``code_agent.run_code`` (code agent with file/command tools) - ``co4e_code`` → ``code_agent.run_code`` (code agent with file/command tools)
- ``script`` → local subprocess with a timeout - ``script`` → local subprocess with a timeout
- ``flow`` → the task's own simple step list, run sequentially, each - ``flow`` → the task's own simple step list, run sequentially, each
@@ -162,6 +164,30 @@ _TIMEOUT_NOTICE_TMPL = (
) )
_UNATTENDED_PREFIX = (
"This runs unattended (Schedule Task) — no one is watching live. Use "
"update_plan to track your steps and keep it accurate: mark a step "
"'error' (not silently skip it) if it genuinely can't be completed."
)
def _unattended_prompt(prompt: str, *, skill_text: str = "",
agent_instructions: str = "") -> str:
"""Assemble the user message an unattended run sends.
The order is load-bearing and used to be encoded as three successive
rebindings of ``prompt``, each prepending its own block: the plan reminder
must lead (it is the instruction that keeps a run without a human watching
honest), then the chosen skill's rules, then the Admin agent's persona, and
the task's own words last. Routing it through ``combine_instructions`` keeps
that order in one readable expression and drops the absent blocks instead of
leaving blank lines behind.
"""
from ..application.conversations.turn_runtime import combine_instructions
return combine_instructions(_UNATTENDED_PREFIX, skill_text, agent_instructions, prompt)
def _cancel_with_timeout(cancel: CancelFn, timeout_sec: Optional[int]) -> Tuple[CancelFn, Callable[[], bool]]: def _cancel_with_timeout(cancel: CancelFn, timeout_sec: Optional[int]) -> Tuple[CancelFn, Callable[[], bool]]:
"""Wrap ``cancel`` so it also fires once ``timeout_sec`` of wall-clock time """Wrap ``cancel`` so it also fires once ``timeout_sec`` of wall-clock time
elapses. ``timed_out()`` tells the caller whether THAT is why it stopped elapses. ``timed_out()`` tells the caller whether THAT is why it stopped
@@ -218,36 +244,29 @@ def _run_agent(ctx, task_type: str, prompt: str, out_dir: Path,
# default, see state.build_provider_for). A legacy Admin-agent preset # default, see state.build_provider_for). A legacy Admin-agent preset
# (task.admin_agent_id), if still set on an older task, keeps working and # (task.admin_agent_id), if still set on an older task, keeps working and
# takes precedence — it pins the provider/model AND prepends instructions. # takes precedence — it pins the provider/model AND prepends instructions.
agent_instructions = ""
if admin_agent is not None: if admin_agent is not None:
from .admin_agents import build_agent_provider from .admin_agents import build_agent_provider
provider = build_agent_provider(ctx, admin_agent) provider = build_agent_provider(ctx, admin_agent)
agent_instructions = admin_agent.effective_prompt() agent_instructions = admin_agent.effective_prompt()
if agent_instructions:
prompt = f"{agent_instructions}\n\n{prompt}"
elif provider_name or model: elif provider_name or model:
# An explicit per-task provider/model override. # An explicit per-task provider/model override.
provider = ctx.build_provider_for(provider_name or None, model or None) provider = ctx.build_provider_for(provider_name or None, model or None)
else: else:
# Neither overridden → the machine's own Settings default, exactly as before. # Neither overridden → the machine's own Settings default, exactly as before.
provider = ctx.build_active_provider() provider = ctx.build_active_provider()
# A chosen skill's instructions are prepended so this unattended run follows # A chosen skill's instructions are applied so this unattended run follows
# them, mirroring how the interactive chat applies /skill. # them, mirroring how the interactive chat applies /skill.
skill_text = ""
if skill_slug: if skill_slug:
from .skills import skill_prefix_for from .skills import skill_prefix_for
skill_text = skill_prefix_for(skill_slug) skill_text = skill_prefix_for(skill_slug)
if skill_text: # Assemble reminder + skill + persona + the task's own words in one place
prompt = f"{skill_text}\n\n{prompt}" # (see _unattended_prompt for why that order matters).
# This is an UNATTENDED run (no human watching to catch a half-finished prompt = _unattended_prompt(prompt, skill_text=skill_text,
# job) — push the agent to actually use the Plan checklist so completion agent_instructions=agent_instructions)
# can be verified afterward, instead of just trusting "no exception".
prompt = (
"This runs unattended (Schedule Task) — no one is watching live. Use "
"update_plan to track your steps and keep it accurate: mark a step "
"'error' (not silently skip it) if it genuinely can't be completed.\n\n"
f"{prompt}"
)
messages = [{"role": "user", "content": prompt}] messages = [{"role": "user", "content": prompt}]
session_id = new_session_id() session_id = new_session_id()
project_id = project.project_id if project is not None else "" project_id = project.project_id if project is not None else ""
@@ -273,10 +292,41 @@ def _run_agent(ctx, task_type: str, prompt: str, out_dir: Path,
watched_cancel, timed_out = _cancel_with_timeout(cancel, timeout_sec) watched_cancel, timed_out = _cancel_with_timeout(cancel, timeout_sec)
try: try:
if task_type == "cowork": if task_type == "cowork":
from .chat_agent import run_cowork # R04-T05: the unattended run shares the interactive turn engine
run_cowork(provider, messages, out_dir, emit_and_autosave, watched_cancel, # instead of calling run_cowork itself, so there is exactly one place
security_config=ctx.config, agent_role=agent_roles.TASK, # where a turn's lifecycle is defined. Everything unattended-specific
project_context=project_context) # stays here (the plan reminder above, the History autosave in
# emit_and_autosave, the timeout notice below).
from ..application.conversations.core_runtime_adapter import (
build_cowork_conversation_service,
legacy_event_sink,
)
from ..domain.agents.conversation_execution_request import (
ConversationExecutionRequest,
)
# No extra_tools/extra_executor and no permission gate: a scheduled
# run gets no MCP connectors and nobody is there to approve a
# command, which is exactly what run_cowork was called with.
service = build_cowork_conversation_service(
provider, out_dir, emit_and_autosave, title=title,
project_context=project_context, security_config=ctx.config,
agent_role=agent_roles.TASK,
)
request = ConversationExecutionRequest(
# The artifact folder is named by the run id, which identifies
# this attempt in the audit log.
turn_id=out_dir.name or session_id, session_id=session_id,
surface="task", title=title, project_id=project_id,
prompt=prompt, output_dir=out_dir,
agent_role=agent_roles.TASK, unattended=True,
timeout_sec=timeout_sec,
)
# ``messages`` is handed over so the History autosave in
# emit_and_autosave (and the final save in the finally block below)
# keep reading the live conversation as it grows.
service.execute(request, legacy_event_sink(emit_and_autosave),
cancel=watched_cancel, messages=messages)
else: else:
from .code_agent import run_code from .code_agent import run_code
limits, block_network = agent_security.sandbox_settings(ctx.config) limits, block_network = agent_security.sandbox_settings(ctx.config)
+16 -10
View File
@@ -135,16 +135,22 @@
* **Team chịu trách nhiệm**: 🔵 **Team Duy** (Chủ trì) * **Team chịu trách nhiệm**: 🔵 **Team Duy** (Chủ trì)
* **Mục tiêu**: Đóng gói input turn chat thành `ConversationExecutionRequest` bất biến, điều phối vòng đời qua `ConversationApplicationService` và phát sinh sự kiện `AgentEvent` có định kiểu. * **Mục tiêu**: Đóng gói input turn chat thành `ConversationExecutionRequest` bất biến, điều phối vòng đời qua `ConversationApplicationService` và phát sinh sự kiện `AgentEvent` có định kiểu.
- [ ] **R04-T01 (Team Duy)**: Định nghĩa immutable dataclass `ConversationExecutionRequest` ➔ `domain/agents/conversation_execution_request.py` - [x] **R04-T01 (Team Duy)**: Định nghĩa immutable dataclass `ConversationExecutionRequest` ➔ `domain/agents/conversation_execution_request.py`
*Start: `____-__-__ __:__` | End: `____-__-__ __:__`* *Start: `2026-08-23 00:56` | End: `2026-08-23 01:00`*
- [ ] **R04-T02 (Team Duy)**: Chuẩn hóa các sự kiện `AgentEvent` (TextChunk, ToolCallStarted, ToolCallResult, Error) ➔ `domain/agents/agent_event.py` - [x] **R04-T02 (Team Duy)**: Chuẩn hóa các sự kiện `AgentEvent` (TextChunk, ToolCallStarted, ToolCallResult, Error) ➔ `domain/agents/agent_event.py` (+ `domain/agents/agent_event_codec.py` — shim dịch legacy dict, tách riêng để giữ LOC < 400 và để xoá gọn sau R08)
*Start: `____-__-__ __:__` | End: `____-__-__ __:__`* *Start: `2026-08-23 01:00` | End: `2026-08-23 01:08`*
- [ ] **R04-T03 (Team Duy)**: Xây dựng `ConversationApplicationService` điều phối thực thi từ `core/chat_agent.py` ➔ `application/conversations/conversation_application_service.py` - [x] **R04-T03 (Team Duy)**: Xây dựng `ConversationApplicationService` điều phối thực thi từ `core/chat_agent.py` ➔ `application/conversations/conversation_application_service.py` (+ `turn_runtime.py` định nghĩa 2 port/6 callable, `core_runtime_adapter.py` cầu nối sang `core/*`, `domain/agents/agent_result.py`)
*Start: `____-__-__ __:__` | End: `____-__-__ __:__`* *Start: `2026-08-23 01:08` | End: `2026-08-23 07:10`*
- [ ] **R04-T04 (Team Duy)**: Di chuyển `ui/cowork_tab.py::build_job` sang sử dụng `ConversationExecutionRequest` Chưa đổi call site nào — `run_cowork` giữ nguyên (Co4E vẫn dùng); việc chuyển call site là T04/T05. Bằng chứng tương đương: `tests/integration/test_conversation_service_parity.py` chạy cùng 1 script provider qua 2 đường và so khớp từng event/message/tool list trên 7 kịch bản.
*Start: `____-__-__ __:__` | End: `____-__-__ __:__`* - [x] **R04-T04 (Team Duy)**: Di chuyển `ui/cowork_tab.py::build_job` sang sử dụng `ConversationExecutionRequest`
- [ ] **R04-T05 (Team Duy)**: Di chuyển `core/task_executors.py` sang dùng chung `ConversationApplicationService` *Start: `2026-08-23 07:10` | End: `2026-08-23 07:23`*
*Start: `____-__-__ __:__` | End: `____-__-__ __:__`* `build_job` không còn gọi `run_cowork`: nó chụp state widget tại submit time ➔ `build_cowork_turn_request()` (mới, `application/conversations/cowork_turn_request.py`) ➔ `ConversationApplicationService`. Thêm `combine_instructions()` vào `turn_runtime.py` (project context + admin agent, T05 dùng lại) và tham số `messages=` cho `execute()` để service append vào **đúng list của widget** — `_reattach_running_turn` đọc list đó trong lúc turn đang chạy và `_finalize_turn` slice nó sau đó. Kiểm chứng: `tests/integration/test_cowork_tab_turn.py` gọi thẳng `CoworkTab.build_job` (widget stub, không cần Qt) và chạy turn thật với `FakeProvider`.
⚠️ `ui/cowork_tab.py` 416 ➔ 455 LOC — file này **vốn đã vượt 400 trước khi sửa**; phân rã thuộc EPIC R08.
- [x] **R04-T05 (Team Duy)**: Di chuyển `core/task_executors.py` sang dùng chung `ConversationApplicationService`
*Start: `2026-08-23 07:23` | End: `2026-08-23 07:31`*
Nhánh `task_type == "cowork"` của `_run_agent` gọi service thay vì `run_cowork`; 5 hành vi riêng của unattended run giữ nguyên (plan reminder, `history_ready`, autosave History mỗi `assistant_done`, timeout notice, `plan_incomplete_reason`). Tách `_unattended_prompt()` dùng `combine_instructions` để thứ tự reminder → skill → persona → prompt nằm ở 1 chỗ đọc được. Lưới an toàn: `tests/integration/test_task_executor_turn.py` viết **trước** khi migrate và pass 8/8 trên code cũ, vẫn pass sau khi migrate.
⚠️ `core/task_executors.py` 476 ➔ 524 LOC — file này **vốn đã vượt 400 trước khi sửa**; phân rã thuộc EPIC R07 (`application/scheduling/`).
Còn lại gọi `run_cowork`: `core/co4e_runner.py` (×2) và `ui/co4e_tab.py` — phân hệ Co4E của 🟣 Team Nam, R04 không chạm theo luật 1 file 1 team.
--- ---
+141
View File
@@ -0,0 +1,141 @@
"""Offline test doubles for the R04 turn runtime seams.
Sits beside ``fake_provider.py``/``fake_tool_executor.py`` (R01-T02) and plays
the same role one level up: those fake a *provider*, these fake the ports
``ConversationApplicationService`` is driven through
(``application/conversations/turn_runtime.py``).
Deliberately dumb — they record what they were asked and return canned answers.
A failing test then points at the service under test rather than at a mock
framework's configuration.
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Tuple
from cowork_local.domain.agents.agent_event import ToolPreview
from cowork_local.domain.agents.conversation_execution_request import (
ConversationExecutionRequest,
)
class FakeSpec:
"""An advertised tool. The service only ever reads ``.name`` off a spec."""
def __init__(self, name: str) -> None:
self.name = name
class FakeReply:
"""One programmed provider answer."""
def __init__(self, content: str = "", tool_calls=None, chunks=None, reasoning: str = ""):
self.content = content
self.tool_calls = tool_calls or []
# Default to streaming the whole content as a single chunk, which is what
# a non-streaming gateway effectively does.
self.chunks = chunks if chunks is not None else ([content] if content else [])
self.reasoning = reasoning
class FakeModelCall:
""":class:`ModelCallPort` returning programmed replies in order.
A programmed entry may be an exception instead of a reply, which is how a
test simulates the gateway dying mid-turn.
"""
def __init__(self, replies: List[Any]) -> None:
self.replies = list(replies)
self.calls: List[Dict[str, Any]] = []
def call(self, messages, tools, on_text=None, on_reasoning=None, cancel=None):
# Snapshot the messages: the service keeps mutating its own list, so
# storing it by reference would make every recorded call look identical.
self.calls.append({"messages": [dict(m) for m in messages],
"tool_names": [getattr(t, "name", "") for t in tools]})
reply = self.replies.pop(0) if self.replies else FakeReply(content="(default)")
if isinstance(reply, BaseException):
raise reply
if reply.reasoning and on_reasoning:
on_reasoning(reply.reasoning)
for chunk in reply.chunks:
if on_text and chunk:
on_text(chunk)
assistant: Dict[str, Any] = {"role": "assistant", "content": reply.content}
if reply.tool_calls:
assistant["tool_calls"] = reply.tool_calls
return assistant
class FakeToolRuntime:
""":class:`ToolRuntimePort` over an imaginary output folder."""
def __init__(self, specs=("save_file", "run_command", "update_plan"),
results: Optional[Dict[str, Dict[str, Any]]] = None,
removed: Tuple[str, ...] = (), added: Tuple[str, ...] = ()) -> None:
self._specs = [FakeSpec(n) for n in specs]
self._results = results or {}
self._removed, self._added = removed, added
self.executed: List[Tuple[str, Dict[str, Any]]] = []
self.finalize_calls: List[Dict[str, Any]] = []
# When set, every executed tool streams this string through ``on_output``.
self.emit_output: Optional[str] = None
def specs(self, allowed_tools=None):
if allowed_tools is None:
return list(self._specs)
return [s for s in self._specs if s.name in allowed_tools]
def preview(self, name, args):
return ToolPreview(kind="info", title=name, text=str(args))
def execute(self, name, args, on_output=None, cancel=None):
self.executed.append((name, dict(args)))
if self.emit_output and on_output:
on_output(self.emit_output)
return dict(self._results.get(name, {"ok": True, "output": f"{name} ok"}))
def snapshot(self):
return "before"
def finalize(self, before, cancelled=False):
self.finalize_calls.append({"before": before, "cancelled": cancelled})
return list(self._removed), list(self._added)
# --------------------------------------------------------------------------- #
# Small helpers shared by the turn tests.
# --------------------------------------------------------------------------- #
def make_request(**overrides) -> ConversationExecutionRequest:
"""A minimal valid request; each test overrides only what it exercises."""
base: Dict[str, Any] = {"turn_id": "t1", "session_id": "s1", "prompt": "do it"}
base.update(overrides)
return ConversationExecutionRequest(**base)
def run_turn(service, request=None, cancel=None):
"""Execute a turn and return ``(result, events)``."""
events: List[Any] = []
result = service.execute(request or make_request(), events.append, cancel=cancel)
return result, events
def events_of_type(events, cls):
"""Every emitted event of one type, in order."""
return [e for e in events if isinstance(e, cls)]
def tool_turn(tool_name: str = "save_file", args=None, **tool_kwargs):
"""A turn that calls one tool and then answers — ``(model, tools)``."""
calls = [{"id": "c1", "name": tool_name, "arguments": args or {"filename": "a.md"}}]
model = FakeModelCall([FakeReply(content="working", tool_calls=calls),
FakeReply(content="done")])
return model, FakeToolRuntime(**tool_kwargs)
__all__ = [
"FakeSpec", "FakeReply", "FakeModelCall", "FakeToolRuntime",
"make_request", "run_turn", "events_of_type", "tool_turn",
]
@@ -0,0 +1,207 @@
"""R04-T03 (c) — the service must behave exactly like ``run_cowork``.
The unit tests prove the loop follows the rules I wrote down. They cannot prove
those rules are the ones the shipped runtime actually follows. This file does:
each test scripts one provider, runs the SAME turn twice — once through
``core/chat_agent.py::run_cowork``, once through
``ConversationApplicationService`` wired by ``core_runtime_adapter`` — and
compares the emitted event stream, the resulting conversation and the tool list
the model was shown.
Anything the port got wrong (a missing event, a reordered guard, a different
tool set, a changed message) fails here rather than in front of a user. The only
allowed difference is the extra ``turn_completed`` event R04 introduces, which
has no legacy consumer.
"""
from __future__ import annotations
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from cowork_local.application.conversations.core_runtime_adapter import (
build_cowork_conversation_service,
legacy_event_sink,
)
from cowork_local.core import chat_agent
from cowork_local.domain.agents.conversation_execution_request import (
ConversationExecutionRequest,
)
from cowork_local.tests.fakes.fake_provider import FakeProvider
_USER_TURN = [{"role": "user", "content": "make me a report"}]
class _FakeGate:
"""Stands in for ``core/permissions.py::PermissionGate``."""
def __init__(self, approve: bool) -> None:
self.approve = approve
self.requests: List[Dict[str, Any]] = []
def request(self, action: Dict[str, Any]) -> bool:
self.requests.append(action)
return self.approve
def _normalise(events: List[Dict[str, Any]], out_dir: Path) -> List[Dict[str, Any]]:
"""Replace the run's own output path with a placeholder.
The two runs write into different temp folders, so absolute paths in
``tool_result``/``outputs_*`` events differ by construction. Everything else
must match verbatim.
"""
marker, raw = "<OUT>", str(out_dir)
def scrub(value: Any) -> Any:
if isinstance(value, str):
return value.replace(raw, marker).replace(raw.replace("\\", "/"), marker)
if isinstance(value, list):
return [scrub(v) for v in value]
if isinstance(value, dict):
return {k: scrub(v) for k, v in value.items()}
return value
return [scrub(e) for e in events]
def _run_legacy(tmp_path: Path, provider: FakeProvider, *, allowed_tools=None,
gate: Optional[_FakeGate] = None, max_steps: int = 30
) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]], List[str]]:
"""Run the turn through the existing ``run_cowork``."""
out_dir = tmp_path / "legacy"
out_dir.mkdir(parents=True, exist_ok=True)
events: List[Dict[str, Any]] = []
messages = [dict(m) for m in _USER_TURN]
chat_agent.run_cowork(
provider, messages, out_dir, events.append, title="Report",
security_config=None, allowed_tools=allowed_tools, gate=gate, max_steps=max_steps,
)
tool_names = [t.name for t in (provider.last_tools or [])]
return _normalise(events, out_dir), messages, tool_names
def _run_service(tmp_path: Path, provider: FakeProvider, *, allowed_tools=None,
gate: Optional[_FakeGate] = None, max_steps: int = 30
) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]], List[str]]:
"""Run the same turn through the application service."""
out_dir = tmp_path / "service"
out_dir.mkdir(parents=True, exist_ok=True)
events: List[Dict[str, Any]] = []
service = build_cowork_conversation_service(
provider, out_dir, events.append, title="Report", security_config=None, gate=gate)
request = ConversationExecutionRequest(
turn_id="t1", session_id="s1",
# run_cowork receives the user message already appended; the request
# carries the history and this turn's prompt separately.
messages=_USER_TURN[:-1], prompt=_USER_TURN[-1]["content"],
output_dir=out_dir, allowed_tools=allowed_tools, max_steps=max_steps,
gate_mode="confirm" if gate is not None else "auto",
)
result = service.execute(request, legacy_event_sink(events.append))
# The end-of-turn event is new in R04 and has no legacy counterpart.
kept = [e for e in events if e.get("type") != "turn_completed"]
tool_names = [t.name for t in (provider.last_tools or [])]
return _normalise(kept, out_dir), list(result.messages), tool_names
def _assert_parity(tmp_path: Path, script, *, approve: Optional[bool] = None, **kwargs) -> None:
"""Script two identical providers, run both paths, compare everything."""
legacy_provider, service_provider = FakeProvider(), FakeProvider()
script(legacy_provider)
script(service_provider)
legacy_gate = _FakeGate(approve) if approve is not None else None
service_gate = _FakeGate(approve) if approve is not None else None
legacy_events, legacy_messages, legacy_tools = _run_legacy(
tmp_path, legacy_provider, gate=legacy_gate, **kwargs)
service_events, service_messages, service_tools = _run_service(
tmp_path, service_provider, gate=service_gate, **kwargs)
assert service_events == legacy_events
assert service_messages == legacy_messages
assert service_tools == legacy_tools
if legacy_gate is not None and service_gate is not None:
assert [r["name"] for r in service_gate.requests] == \
[r["name"] for r in legacy_gate.requests]
# --------------------------------------------------------------------------- #
# Scenarios.
# --------------------------------------------------------------------------- #
def test_a_plain_answer_turn_behaves_identically(tmp_path: Path) -> None:
def script(provider: FakeProvider) -> None:
provider.queue_response(content="Here you go.", chunks=["Here ", "you go."])
_assert_parity(tmp_path, script)
def test_a_save_file_turn_behaves_identically(tmp_path: Path) -> None:
def script(provider: FakeProvider) -> None:
provider.queue_response(
content="Writing it.",
tool_calls=[{"id": "c1", "name": "save_file",
"arguments": {"filename": "report.md", "content": "# Report\n"}}],
)
provider.queue_response(content="Saved.")
_assert_parity(tmp_path, script)
def test_an_update_plan_turn_behaves_identically(tmp_path: Path) -> None:
def script(provider: FakeProvider) -> None:
provider.queue_response(
content="Planning.",
tool_calls=[{"id": "c1", "name": "update_plan",
"arguments": {"steps": [{"title": "Draft", "status": "running"},
{"title": "Ship", "status": "pending"}]}}],
)
provider.queue_response(content="Done.")
_assert_parity(tmp_path, script)
def test_a_reasoning_only_reply_behaves_identically(tmp_path: Path) -> None:
def script(provider: FakeProvider) -> None:
provider.queue_response(content="", reasoning="thinking hard")
_assert_parity(tmp_path, script)
def test_restricting_the_tool_scope_advertises_the_same_tools(tmp_path: Path) -> None:
def script(provider: FakeProvider) -> None:
provider.queue_response(content="ok")
_assert_parity(tmp_path, script, allowed_tools=["save_file"])
def test_a_rejected_command_behaves_identically(tmp_path: Path) -> None:
# The security-critical path: the gate says no, so the command must never
# run and the model must read back the same refusal in both designs.
def script(provider: FakeProvider) -> None:
provider.queue_response(
content="Running it.",
tool_calls=[{"id": "c1", "name": "run_command",
"arguments": {"command": "echo hi"}}],
)
provider.queue_response(content="Understood.")
_assert_parity(tmp_path, script, approve=False)
def test_hitting_the_step_ceiling_behaves_identically(tmp_path: Path) -> None:
# The model never stops calling tools, so both paths must stop at the same
# place and say so the same way.
def script(provider: FakeProvider) -> None:
for i in range(4):
provider.queue_response(
content=f"step {i}",
tool_calls=[{"id": f"c{i}", "name": "save_file",
"arguments": {"filename": f"f{i}.md", "content": "x"}}],
)
_assert_parity(tmp_path, script, max_steps=2)
+220
View File
@@ -0,0 +1,220 @@
"""R04-T04 — the migrated Cowork call site, exercised end to end without Qt.
``CoworkTab.build_job`` only ever *reads attributes* off its widget, so the real
production method can be invoked against a stand-in that supplies those
attributes. That is what happens here: the actual ``build_job`` body runs, builds
a request, wires the service through ``core_runtime_adapter``, and drives a real
turn (real tool execution, real output-folder cleanup) against ``FakeProvider``.
Why it matters: this is the only automated check that the widget's contract with
the service still holds — that the worker's list is appended to in place (the
transcript re-render and history merge both read it), that events still arrive as
legacy dicts, and that a produced file really lands in the turn's folder. None of
it needs a display server, so it runs in CI like every other test.
"""
from __future__ import annotations
import copy
from pathlib import Path
from typing import Any, Dict, List, Optional
import pytest
from cowork_local.config import DEFAULT_CONFIG, AppConfig
from cowork_local.tests.fakes.fake_provider import FakeProvider
class _FakeWorker:
"""The parts of ``core/worker.py::AgentWorker`` a job actually touches."""
def __init__(self, approve_commands: bool = True) -> None:
self.events: List[Dict[str, Any]] = []
self.gate: Optional[Any] = None
self._approve = approve_commands
self.cancelled = False
def emit_event(self, event: Dict[str, Any]) -> None:
self.events.append(event)
def is_cancelled(self) -> bool:
return self.cancelled
def new_gate(self, mode: str, agent_role: str = "") -> Any:
# Mirrors AgentWorker.new_gate: the gate is stored on the worker so the
# UI thread can resolve it, and answers request() from the worker thread.
worker = self
class _Gate:
requests: List[Dict[str, Any]] = []
def request(self, action: Dict[str, Any]) -> bool:
self.requests.append(action)
return worker._approve
self.gate = _Gate()
return self.gate
class _FakeCtx:
"""The ``AppContext`` surface ``build_job`` uses."""
def __init__(self, config: AppConfig, confirm_commands: bool = False) -> None:
self.config = config
self._confirm = confirm_commands
def project_confirm_commands(self) -> bool:
return self._confirm
def build_mcp_tools(self):
return [], None
class _WidgetStub:
"""Stands in for the CoworkTab instance ``build_job`` reads its state from."""
kind = "cowork"
def __init__(self, out_root: Path, ctx: _FakeCtx, provider: FakeProvider) -> None:
self._out_root = out_root
self.ctx = ctx
self._provider = provider
self.title = "Report"
self.session_id = "s1"
self.project_id = "" # the auto-seeded default workspace
self._model = ""
self._routed_provider = None
self._routed_model = None
def _session_output_dir(self) -> Path:
return self._out_root
def workspace_dir(self) -> Path:
return self._out_root
def admin_agent_prompt(self) -> str:
return ""
def build_provider(self) -> FakeProvider:
return self._provider
def _config() -> AppConfig:
"""A real AppConfig that never touches ``~/.cowork_local``.
The AI security guardrails are switched off: they would call the model to
review the prompt, which is a separate feature with its own tests and would
make this one depend on what the fake answers.
"""
data = copy.deepcopy(DEFAULT_CONFIG)
data["agent_security"]["enabled"] = False
return AppConfig(data)
def _run_turn(tmp_path: Path, provider: FakeProvider, messages: List[Dict[str, Any]],
*, confirm_commands: bool = False, approve: bool = True):
"""Invoke the real ``CoworkTab.build_job`` against the stub and run its job."""
from cowork_local.ui.cowork_tab import CoworkTab
out_dir = tmp_path / ".turns" / "t1"
out_dir.mkdir(parents=True, exist_ok=True)
widget = _WidgetStub(tmp_path, _FakeCtx(_config(), confirm_commands), provider)
worker = _FakeWorker(approve_commands=approve)
job = CoworkTab.build_job(widget, "make me a report", messages, out_dir)
result = job(worker)
return result, worker
def test_the_turn_runs_and_reports_its_folder(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(content="Here you go.", chunks=["Here ", "you go."])
messages = [{"role": "user", "content": "make me a report"}]
result, worker = _run_turn(tmp_path, provider, messages)
assert result["turn_dir"] == str(tmp_path / ".turns" / "t1")
assert [e["type"] for e in worker.events] == [
"text", "text", "assistant_done", "turn_completed"]
def test_the_worker_list_is_appended_to_in_place(tmp_path: Path) -> None:
# _reattach_running_turn replays from this very list while the turn runs, and
# _finalize_turn slices it by the pre-turn length afterwards.
provider = FakeProvider()
provider.queue_response(content="Done.")
user = {"role": "user", "content": "make me a report"}
messages = [user]
result, _ = _run_turn(tmp_path, provider, messages)
assert result["messages"] is messages
# Identity, not just equality: _reattach_running_turn locates the turn's user
# message with ``m is ctx["user_msg"]`` to replay the steps after it.
assert any(m is user for m in messages)
# Several system blocks are expected — the tool prompt plus the tagged
# skills/security-rules blocks the runtime refreshes on every turn.
assert [m["role"] for m in messages if m["role"] != "system"] == ["user", "assistant"]
assert messages[-1]["content"] == "Done."
def test_a_saved_file_lands_in_the_turn_folder(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(
content="Writing it.",
tool_calls=[{"id": "c1", "name": "save_file",
"arguments": {"filename": "report.md", "content": "# Report\n"}}],
)
provider.queue_response(content="Saved.")
messages = [{"role": "user", "content": "make me a report"}]
_, worker = _run_turn(tmp_path, provider, messages)
produced = list((tmp_path / ".turns" / "t1").glob("*.md"))
assert len(produced) == 1
assert produced[0].read_text(encoding="utf-8") == "# Report\n"
results = [e for e in worker.events if e["type"] == "tool_result"]
assert results and results[0]["ok"] is True
def test_auto_run_mode_never_creates_a_permission_gate(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(content="ok")
_, worker = _run_turn(tmp_path, provider, [{"role": "user", "content": "hi"}],
confirm_commands=False)
assert worker.gate is None
def test_confirm_mode_creates_the_gate_and_a_refusal_stops_the_command(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(
content="Running it.",
tool_calls=[{"id": "c1", "name": "run_command",
"arguments": {"command": "echo hi"}}],
)
provider.queue_response(content="Understood.")
_, worker = _run_turn(tmp_path, provider, [{"role": "user", "content": "run it"}],
confirm_commands=True, approve=False)
assert worker.gate is not None
refusals = [e for e in worker.events
if e["type"] == "tool_result" and e["output"] == "Rejected by user."]
assert len(refusals) == 1
def test_cancelling_before_the_turn_starts_calls_no_model(tmp_path: Path) -> None:
from cowork_local.ui.cowork_tab import CoworkTab
provider = FakeProvider()
provider.queue_response(content="never")
out_dir = tmp_path / ".turns" / "t1"
out_dir.mkdir(parents=True)
widget = _WidgetStub(tmp_path, _FakeCtx(_config()), provider)
worker = _FakeWorker()
worker.cancelled = True
CoworkTab.build_job(widget, "x", [{"role": "user", "content": "x"}], out_dir)(worker)
assert provider.call_count == 0
@@ -0,0 +1,191 @@
"""R04-T05 — the Schedule Task runner's cowork branch, pinned before and after.
Written against the CURRENT ``_run_agent`` first, as the safety net for moving it
onto ``ConversationApplicationService``: an unattended run has five behaviours the
interactive path does not have (the plan reminder prefixed to the prompt, the
session registered in History before the model starts, a re-save after every
assistant message, the timeout notice, and the "did the agent's own checklist
finish?" report), and none of them was covered by a test.
Everything is isolated from the user's real config: history goes to ``tmp_path``
via ``history.custom_dir`` and the AI guardrails are off, so no run touches
``~/.cowork_local`` or calls a model to review a prompt.
"""
from __future__ import annotations
import copy
import json
from pathlib import Path
from typing import Any, Dict, List, Optional
from cowork_local.config import DEFAULT_CONFIG, AppConfig
from cowork_local.core import task_executors
from cowork_local.tests.fakes.fake_provider import FakeProvider
class _FakeCtx:
"""The ``AppContext`` surface ``_run_agent`` touches."""
def __init__(self, config: AppConfig, provider: FakeProvider) -> None:
self.config = config
self._provider = provider
def build_active_provider(self) -> FakeProvider:
return self._provider
def build_provider_for(self, name=None, model=None) -> FakeProvider:
return self._provider
def _config(tmp_path: Path) -> AppConfig:
data = copy.deepcopy(DEFAULT_CONFIG)
# Keep the run entirely offline and off the real config dir.
data["agent_security"]["enabled"] = False
data["history"]["custom_dir"] = str(tmp_path / "history")
return AppConfig(data)
def _run(tmp_path: Path, provider: FakeProvider, *, prompt: str = "write the report",
timeout_sec: Optional[int] = None, admin_agent: Any = None):
"""Run one cowork task and return ``(result_tuple, events, config)``."""
out_dir = tmp_path / "run"
out_dir.mkdir(parents=True, exist_ok=True)
config = _config(tmp_path)
events: List[Dict[str, Any]] = []
result = task_executors._run_agent(
_FakeCtx(config, provider), "cowork", prompt, out_dir,
events.append, lambda: False, title="Weekly report",
timeout_sec=timeout_sec, admin_agent=admin_agent,
)
return result, events, config
def _saved_conversation(config: AppConfig) -> Dict[str, Any]:
"""The single conversation the run wrote into the isolated history folder."""
files = list(Path(config.history_dir()).rglob("*.json"))
assert len(files) == 1, f"expected one saved conversation, found {files}"
return json.loads(files[0].read_text(encoding="utf-8"))
# --------------------------------------------------------------------------- #
def test_a_cowork_task_returns_the_final_answer(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(content="Report is ready.")
(answer, timed_out, incomplete), _events, _config = _run(tmp_path, provider)
assert answer == "Report is ready."
assert timed_out is False
assert incomplete == ""
def test_the_plan_reminder_is_prefixed_to_the_prompt(tmp_path: Path) -> None:
# An unattended run has nobody watching, so the agent is pushed to keep its
# own checklist honest. The reminder must lead the message.
provider = FakeProvider()
provider.queue_response(content="ok")
_run(tmp_path, provider, prompt="write the report")
sent = provider.call_history[0][-1]["content"]
assert sent.startswith("This runs unattended (Schedule Task)")
assert sent.endswith("write the report")
def test_an_admin_agent_persona_sits_between_the_reminder_and_the_prompt(
tmp_path: Path) -> None:
class _Agent:
# An admin agent may pin its own provider/model; blank means "use the
# machine's Settings default", which is what build_agent_provider reads.
provider = ""
model = ""
def effective_prompt(self) -> str:
return "You are the reporting agent."
provider = FakeProvider()
provider.queue_response(content="ok")
_run(tmp_path, provider, prompt="write the report", admin_agent=_Agent())
sent = provider.call_history[0][-1]["content"]
assert sent.index("This runs unattended") < sent.index("You are the reporting agent.")
assert sent.index("You are the reporting agent.") < sent.index("write the report")
def test_the_session_is_announced_once_it_exists_on_disk(tmp_path: Path) -> None:
# The scheduler refreshes History on this event, so it must not fire before
# the conversation is really there.
provider = FakeProvider()
provider.queue_response(content="ok")
_result, events, config = _run(tmp_path, provider)
ready = [e for e in events if e["type"] == "history_ready"]
assert len(ready) == 1
assert ready[0]["session_id"]
assert _saved_conversation(config)["session_id"] == ready[0]["session_id"]
def test_the_saved_conversation_carries_the_answer_and_the_task_title(
tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(content="Report is ready.")
_result, _events, config = _run(tmp_path, provider)
saved = _saved_conversation(config)
assert saved["title"] == "[Task] Weekly report"
assert saved["messages"][-1] == {"role": "assistant", "content": "Report is ready."}
def test_an_unfinished_checklist_is_reported_back_to_the_scheduler(
tmp_path: Path) -> None:
# The agent ticked no step to done, so the task must not be called finished
# just because no exception was raised.
provider = FakeProvider()
provider.queue_response(
content="Working on it.",
tool_calls=[{"id": "c1", "name": "update_plan",
"arguments": {"steps": [{"title": "Draft", "status": "running"}]}}],
)
provider.queue_response(content="Stopping here.")
(_answer, _timed_out, incomplete), _events, _config = _run(tmp_path, provider)
assert incomplete
assert "Draft" in incomplete
def test_a_finished_checklist_reports_nothing_outstanding(tmp_path: Path) -> None:
provider = FakeProvider()
provider.queue_response(
content="Done.",
tool_calls=[{"id": "c1", "name": "update_plan",
"arguments": {"steps": [{"title": "Draft", "status": "done"}]}}],
)
provider.queue_response(content="All done.")
(_answer, _timed_out, incomplete), _events, _config = _run(tmp_path, provider)
assert incomplete == ""
def test_running_out_of_time_appends_the_timeout_notice_to_the_conversation(
tmp_path: Path) -> None:
# A negative timeout puts the deadline in the past, which is the only
# deterministic way to exercise a wall-clock branch in a unit test.
provider = FakeProvider()
provider.queue_response(content="never gets there")
(answer, timed_out, incomplete), events, config = _run(
tmp_path, provider, timeout_sec=-1)
assert timed_out is True
assert incomplete == "" # a timeout is not an unfinished checklist
assert "quá thời gian chờ" in answer
assert any(e["type"] == "assistant_done" and "quá thời gian chờ" in e["content"]
for e in events)
assert "quá thời gian chờ" in _saved_conversation(config)["messages"][-1]["content"]
@@ -0,0 +1,293 @@
"""R04-T03 (b) — the turn loop: composition, tool dispatch, budget, cancel.
Behaviour that used to be reachable only by running the real widget. Every
dependency is a fake from ``tests/fakes/turn_runtime_fakes.py``, so the file
runs in milliseconds and each test states one rule of the loop.
"""
from __future__ import annotations
from typing import Any, Dict, List, Tuple
from cowork_local.application.conversations.conversation_application_service import (
ConversationApplicationService,
)
from cowork_local.domain.agents.agent_event import (
AssistantMessageCompletedEvent,
PlanStep,
PlanUpdatedEvent,
TextChunkEvent,
ToolCallFinishedEvent,
ToolCallStartedEvent,
ToolOutputChunkEvent,
ToolPreview,
TurnCompletedEvent,
)
from cowork_local.tests.fakes.turn_runtime_fakes import (
FakeModelCall,
FakeReply,
FakeToolRuntime,
events_of_type,
make_request,
run_turn,
tool_turn,
)
def _service(model, tools, **overrides) -> ConversationApplicationService:
return ConversationApplicationService(model, tools, **overrides)
# --------------------------------------------------------------------------- #
# The happy path.
# --------------------------------------------------------------------------- #
def test_a_plain_answer_streams_text_then_reports_the_message_and_the_turn() -> None:
model = FakeModelCall([FakeReply(content="Hello there", chunks=["Hello ", "there"])])
result, events = run_turn(_service(model, FakeToolRuntime()))
assert [e.delta for e in events_of_type(events, TextChunkEvent)] == ["Hello ", "there"]
assert events_of_type(events, AssistantMessageCompletedEvent) == [
AssistantMessageCompletedEvent(content="Hello there")]
assert events_of_type(events, TurnCompletedEvent) == [
TurnCompletedEvent(final_text="Hello there", steps_used=1)]
assert result.final_text == "Hello there"
assert result.ok is True
def test_the_composed_user_message_is_appended_before_the_first_call() -> None:
model = FakeModelCall([FakeReply(content="ok")])
request = make_request(prompt="ship it", instruction_prefix="RULES",
session_notes="earlier: a.md",
messages=[{"role": "user", "content": "previous"}])
run_turn(_service(model, FakeToolRuntime()), request)
sent = model.calls[0]["messages"]
assert sent[-1] == {"role": "user",
"content": "RULES\n\n---\n\nship it\n\nearlier: a.md"}
assert sent[-2] == {"role": "user", "content": "previous"}
def test_attachments_are_read_when_the_turn_runs_not_when_it_was_built() -> None:
# Extraction can pip-install a parser or shell out to LibreOffice, so it must
# happen here (worker thread), not while the UI was assembling the request.
seen: List[Tuple[str, Tuple[str, ...]]] = []
def reader(prompt: str, attachments: Tuple[str, ...]) -> str:
seen.append((prompt, attachments))
return f"{prompt}\n\n<contents of {len(attachments)} file(s)>"
model = FakeModelCall([FakeReply(content="ok")])
request = make_request(prompt="summarise", attachments=["a.docx", "b.pdf"])
run_turn(_service(model, FakeToolRuntime(), attachment_reader=reader), request)
assert seen == [("summarise", ("a.docx", "b.pdf"))]
assert "contents of 2 file(s)" in model.calls[0]["messages"][-1]["content"]
def test_the_prompt_preparer_is_told_which_tools_the_turn_advertises() -> None:
# The system prompt gains an MS365 paragraph only when ms365__* tools are
# present, so the preparer has to see the real list.
seen: List[Tuple[str, ...]] = []
model = FakeModelCall([FakeReply(content="ok")])
tools = FakeToolRuntime(specs=("save_file", "ms365__send_mail"))
run_turn(_service(model, tools,
prepare_prompt=lambda messages, names: seen.append(names)))
assert seen == [("save_file", "ms365__send_mail")]
def test_only_the_allowed_tools_are_advertised() -> None:
model = FakeModelCall([FakeReply(content="ok")])
tools = FakeToolRuntime(specs=("save_file", "run_command", "update_plan"))
run_turn(_service(model, tools), make_request(allowed_tools=("save_file", "update_plan")))
assert model.calls[0]["tool_names"] == ["save_file", "update_plan"]
# --------------------------------------------------------------------------- #
# Tool dispatch.
# --------------------------------------------------------------------------- #
def tool_turn(tool_name: str = "save_file", args=None, **tool_kwargs):
"""A turn that calls one tool, then answers."""
calls = [{"id": "c1", "name": tool_name, "arguments": args or {"filename": "a.md"}}]
model = FakeModelCall([FakeReply(content="working", tool_calls=calls),
FakeReply(content="done")])
return model, FakeToolRuntime(**tool_kwargs)
def test_a_tool_call_is_announced_executed_and_answered_in_the_message_list() -> None:
model, tools = tool_turn(results={"save_file": {"ok": True, "output": "saved",
"path": "out/a.md"}})
result, events = run_turn(_service(model, tools))
assert events_of_type(events, ToolCallStartedEvent) == [ToolCallStartedEvent(
call_id="c1", name="save_file", arguments={"filename": "a.md"},
preview=ToolPreview(kind="info", title="save_file", text="{'filename': 'a.md'}"))]
assert events_of_type(events, ToolCallFinishedEvent) == [ToolCallFinishedEvent(
call_id="c1", name="save_file", ok=True, output="saved", path="out/a.md")]
assert tools.executed == [("save_file", {"filename": "a.md"})]
assert result.messages[-2] == {"role": "tool", "tool_call_id": "c1",
"name": "save_file", "content": "saved"}
def test_live_tool_output_is_streamed_while_the_tool_runs() -> None:
model, tools = tool_turn("run_command", {"command": "ls"})
tools.emit_output = "file-a\n"
_, events = run_turn(_service(model, tools))
assert events_of_type(events, ToolOutputChunkEvent) == [ToolOutputChunkEvent(
call_id="c1", name="run_command", delta="file-a\n")]
def test_the_loop_ends_as_soon_as_the_model_stops_calling_tools() -> None:
model, tools = tool_turn()
result, _ = run_turn(_service(model, tools))
assert result.steps_used == 2
assert result.budget_exhausted is False
def test_the_plan_tool_reports_a_plan_update_and_no_tool_bubble() -> None:
calls = [{"id": "c1", "name": "update_plan",
"arguments": {"steps": [{"title": "Draft", "status": "running"}]}}]
model = FakeModelCall([FakeReply(content="planning", tool_calls=calls), FakeReply(content="done")])
tools = FakeToolRuntime(results={"update_plan": {
"ok": True, "output": "Plan updated.",
"plan_steps": [PlanStep(title="Draft", status="running")]}})
result, events = run_turn(_service(model, tools))
assert events_of_type(events, PlanUpdatedEvent) == [
PlanUpdatedEvent(steps=(PlanStep(title="Draft", status="running"),))]
assert events_of_type(events, ToolCallStartedEvent) == []
assert events_of_type(events, ToolCallFinishedEvent) == []
assert result.plan_steps == (PlanStep(title="Draft", status="running"),)
# --------------------------------------------------------------------------- #
# Budget, cancellation.
# --------------------------------------------------------------------------- #
def test_running_out_of_steps_is_flagged_and_announced() -> None:
# The model keeps calling tools forever; the ceiling must stop it visibly.
forever = [FakeReply(content=f"step {i}",
tool_calls=[{"id": f"c{i}", "name": "save_file", "arguments": {}}])
for i in range(5)]
model = FakeModelCall(forever)
result, events = run_turn(_service(model, FakeToolRuntime()), make_request(max_steps=2))
assert result.steps_used == 2
assert result.budget_exhausted is True
assert "2-step safety limit" in events_of_type(events, TextChunkEvent)[-1].delta
# The note reaches the transcript but NOT the stored answer: a turn that hits
# the ceiling always ends on a tool message, and the existing runtime only
# merges the note when the last message is the assistant's. Pinned here so a
# future change to that rule is a deliberate decision, not a silent drift.
assert result.final_text == "step 1"
def test_run_to_completion_uses_the_higher_ceiling() -> None:
forever = [FakeReply(content="x", tool_calls=[{"id": "c", "name": "save_file", "arguments": {}}])
for _ in range(6)]
model = FakeModelCall(forever)
result, _ = run_turn(_service(model, FakeToolRuntime()),
make_request(max_steps=2, completion_max_steps=5, run_to_completion=True))
assert result.steps_used == 5
def test_a_turn_cancelled_before_it_starts_never_calls_the_model() -> None:
model = FakeModelCall([FakeReply(content="never")])
result, events = run_turn(_service(model, FakeToolRuntime()), cancel=lambda: True)
assert model.calls == []
assert result.cancelled is True
assert result.budget_exhausted is False
assert events_of_type(events, TurnCompletedEvent) == [TurnCompletedEvent(cancelled=True)]
def test_cancelling_during_a_turn_stops_dispatching_the_remaining_tool_calls() -> None:
calls = [{"id": "c1", "name": "save_file", "arguments": {}},
{"id": "c2", "name": "save_file", "arguments": {}}]
model = FakeModelCall([FakeReply(content="two tools", tool_calls=calls)])
tools = FakeToolRuntime()
stop = {"now": False}
def cancel() -> bool:
return stop["now"]
original_execute = tools.execute
def execute(name, args, on_output=None, cancel=None):
stop["now"] = True # cancel raised while the first tool runs
return original_execute(name, args, on_output=on_output, cancel=cancel)
tools.execute = execute
result, _ = run_turn(_service(model, tools), cancel=cancel)
assert len(tools.executed) == 1
assert result.cancelled is True
# --------------------------------------------------------------------------- #
# Bring-your-own working list.
#
# ``ui/chat_panel.py`` holds the turn's message list in its own turn context and
# reads it WHILE the worker appends (``_reattach_running_turn`` replays the steps
# done so far when the user reopens a running conversation; ``_finalize_turn``
# slices it by ``snapshot_len``). A service that built its own private list would
# silently break both, so a caller can hand its list over instead.
# --------------------------------------------------------------------------- #
def test_a_caller_supplied_list_is_appended_to_in_place() -> None:
model, tools = tool_turn()
live: List[Dict[str, Any]] = [{"role": "user", "content": "already composed"}]
result = ConversationApplicationService(model, tools).execute(
make_request(), lambda event: None, messages=live)
roles = [m["role"] for m in live]
assert roles == ["user", "assistant", "tool", "assistant"]
assert result.messages == tuple(live)
def test_a_caller_supplied_list_is_used_as_is_without_recomposing_the_prompt() -> None:
# The widget already applied the skill prefix and the session notes when it
# built its message; composing again would duplicate them.
model = FakeModelCall([FakeReply(content="ok")])
user = {"role": "user", "content": "already composed"}
live = [user]
ConversationApplicationService(model, FakeToolRuntime()).execute(
make_request(prompt="typed text", instruction_prefix="RULES",
session_notes="notes"),
lambda event: None, messages=live)
assert live[0] is user
assert live[0]["content"] == "already composed"
assert [m["role"] for m in live].count("user") == 1
def test_a_caller_supplied_list_skips_the_attachment_reader() -> None:
# Reading the attachments is what produced the caller's message in the first
# place; doing it again would re-parse every file.
model = FakeModelCall([FakeReply(content="ok")])
calls: List[Any] = []
ConversationApplicationService(
model, FakeToolRuntime(),
attachment_reader=lambda prompt, attachments: calls.append(prompt) or prompt,
).execute(make_request(attachments=["a.docx"]), lambda event: None,
messages=[{"role": "user", "content": "composed"}])
assert calls == []
+210
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@@ -0,0 +1,210 @@
"""R04-T03 (b) — the turn loop: guards, permission gate, compaction, cleanup.
Split out of ``test_conversation_application_service.py`` to keep each file
inside the 400-LOC limit. Same fakes, same service; this half pins the ORDER of
the safety steps (guard before model, guard before execute, gate before execute)
and the promise that the output sandbox is tidied on the way out.
"""
from __future__ import annotations
from typing import Any, Dict, List
import pytest
from cowork_local.application.conversations.conversation_application_service import (
ConversationApplicationService,
)
from cowork_local.domain.agents.agent_event import (
ErrorEvent,
OutputsAddedEvent,
ReasoningChunkEvent,
TextChunkEvent,
ToolCallFinishedEvent,
)
from cowork_local.tests.fakes.turn_runtime_fakes import (
FakeModelCall,
FakeReply,
FakeToolRuntime,
events_of_type,
make_request,
run_turn,
tool_turn,
)
def _service(model, tools, **overrides) -> ConversationApplicationService:
return ConversationApplicationService(model, tools, **overrides)
# --------------------------------------------------------------------------- #
# Guards and the permission gate.
# --------------------------------------------------------------------------- #
def test_the_prompt_guard_runs_before_the_model_is_ever_called() -> None:
order: List[str] = []
model = FakeModelCall([FakeReply(content="ok")])
model_call = model.call
def call(*a, **kw):
order.append("model")
return model_call(*a, **kw)
model.call = call
run_turn(_service(model, FakeToolRuntime(), prompt_guard=lambda messages: order.append("guard")))
assert order == ["guard", "model"]
def test_a_blocked_prompt_propagates_before_the_output_folder_is_touched() -> None:
model = FakeModelCall([FakeReply(content="never")])
tools = FakeToolRuntime()
events: List[Any] = []
def guard(messages) -> None:
raise RuntimeError("SecurityBlocked: nope")
service = _service(model, tools, prompt_guard=guard)
with pytest.raises(RuntimeError, match="SecurityBlocked"):
service.execute(make_request(), events.append)
assert model.calls == []
assert events_of_type(events, ErrorEvent) == [ErrorEvent(message="SecurityBlocked: nope")]
# Cleanup is NOT a read-only operation (it deletes a stale .scratch and every
# empty sub-folder), so a turn rejected before it started must not run it.
assert tools.finalize_calls == []
def test_output_cleanup_still_runs_when_the_turn_fails_mid_loop() -> None:
# Once the turn has started producing files, the sandbox must be tidied on
# the way out no matter how the turn ends.
model = FakeModelCall([RuntimeError("gateway exploded")])
tools = FakeToolRuntime()
events: List[Any] = []
with pytest.raises(RuntimeError, match="gateway exploded"):
_service(model, tools).execute(make_request(), events.append)
assert tools.finalize_calls == [{"before": "before", "cancelled": False}]
assert events_of_type(events, ErrorEvent) == [ErrorEvent(message="gateway exploded")]
def test_the_command_guard_runs_before_the_tool_executes() -> None:
order: List[str] = []
model, tools = tool_turn("run_command", {"command": "ls"})
original = tools.execute
def execute(name, args, on_output=None, cancel=None):
order.append("execute")
return original(name, args, on_output=on_output, cancel=cancel)
tools.execute = execute
run_turn(_service(model, tools,
command_guard=lambda name, args: order.append(f"guard:{name}")))
assert order == ["guard:run_command", "execute"]
def test_disabling_rule_enforcement_skips_both_guards() -> None:
# Co4E flow steps run inside the workspace sandbox and opt out on purpose.
calls: List[str] = []
model, tools = tool_turn("run_command", {"command": "ls"})
run_turn(_service(model, tools,
prompt_guard=lambda messages: calls.append("prompt"),
command_guard=lambda name, args: calls.append("command")),
make_request(enforce_rules=False))
assert calls == []
def test_the_permission_gate_is_asked_only_for_command_tools() -> None:
asked: List[str] = []
model, tools = tool_turn("save_file", {"filename": "a.md"})
run_turn(_service(model, tools,
permission_request=lambda action: asked.append(action["name"]) or True),
make_request(gate_mode="confirm"))
assert asked == [] # save_file writes into the sandbox: never gated
def test_a_command_tool_in_confirm_mode_asks_before_running() -> None:
asked: List[Dict[str, Any]] = []
model, tools = tool_turn("run_command", {"command": "ls"})
def approve(action: Dict[str, Any]) -> bool:
asked.append(action)
return True
run_turn(_service(model, tools, permission_request=approve), make_request(gate_mode="confirm"))
assert [a["name"] for a in asked] == ["run_command"]
assert tools.executed == [("run_command", {"command": "ls"})]
def test_a_rejected_command_is_reported_as_a_failed_tool_and_never_runs() -> None:
model, tools = tool_turn("run_command", {"command": "rm -rf /"})
result, events = run_turn(_service(model, tools, permission_request=lambda action: False),
make_request(gate_mode="confirm"))
assert tools.executed == []
assert events_of_type(events, ToolCallFinishedEvent) == [ToolCallFinishedEvent(
call_id="c1", name="run_command", ok=False, output="Rejected by user.")]
assert result.messages[-2]["content"] == "Rejected by user."
def test_auto_mode_never_asks_even_for_a_command() -> None:
model, tools = tool_turn("run_command", {"command": "ls"})
def refuse(action): # would block the turn if it were consulted
raise AssertionError("the gate must not be consulted in auto mode")
run_turn(_service(model, tools, permission_request=refuse), make_request(gate_mode="auto"))
assert tools.executed == [("run_command", {"command": "ls"})]
# --------------------------------------------------------------------------- #
# Context compaction, reasoning, output cleanup.
# --------------------------------------------------------------------------- #
def test_the_conversation_is_offered_for_compaction_before_every_call() -> None:
compactions: List[int] = []
model, tools = tool_turn()
run_turn(_service(model, tools,
compact=lambda messages, cancel: compactions.append(len(messages))))
assert len(compactions) == 2 # once per provider call
def test_reasoning_is_streamed_as_its_own_event() -> None:
model = FakeModelCall([FakeReply(content="42", reasoning="thinking...")])
_, events = run_turn(_service(model, FakeToolRuntime()))
assert events_of_type(events, ReasoningChunkEvent) == [ReasoningChunkEvent(delta="thinking...")]
def test_a_reasoning_only_reply_gets_a_visible_note_in_the_transcript() -> None:
# Otherwise a Schedule Task run reads back an empty answer and writes
# "(no output)" into its report.
model = FakeModelCall([FakeReply(content="", reasoning="thought hard")])
result, events = run_turn(_service(model, FakeToolRuntime()))
assert "only its reasoning" in events_of_type(events, TextChunkEvent)[-1].delta
assert "only its reasoning" in result.final_text
def test_promoted_and_discarded_output_files_are_reported_at_the_end() -> None:
model = FakeModelCall([FakeReply(content="ok")])
tools = FakeToolRuntime(added=("out/report.pptx",))
_, events = run_turn(_service(model, tools))
assert events_of_type(events, OutputsAddedEvent) == [
OutputsAddedEvent(paths=("out/report.pptx",))]
assert tools.finalize_calls == [{"before": "before", "cancelled": False}]
+76
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@@ -0,0 +1,76 @@
"""R04-T04 — unit tests for the UI-state -> request mapping.
Three small rules used to sit inline in ``ui/cowork_tab.py::build_job``, where no
test could reach them: the turn's prompt is the last message in the working list,
the history is everything before it, and the confirm-commands flag becomes a gate
mode. Getting any of them wrong is silent (a duplicated user message, a command
that stops asking for approval), so they are pinned here.
"""
from __future__ import annotations
from pathlib import Path
from cowork_local.application.conversations.cowork_turn_request import (
build_cowork_turn_request,
)
def _build(**overrides):
base = {
"turn_id": "t3",
"session_id": "s1",
"messages": [{"role": "user", "content": "make me a report"}],
}
base.update(overrides)
return build_cowork_turn_request(**base)
def test_the_last_message_becomes_the_prompt_and_the_rest_the_history() -> None:
request = _build(messages=[
{"role": "user", "content": "earlier"},
{"role": "assistant", "content": "sure"},
{"role": "user", "content": "now this"},
])
assert request.prompt == "now this"
assert request.messages == ({"role": "user", "content": "earlier"},
{"role": "assistant", "content": "sure"})
def test_an_empty_working_list_yields_an_empty_prompt() -> None:
# Defensive: a turn with no message at all must not raise on messages[-1].
request = _build(messages=[])
assert request.prompt == ""
assert request.messages == ()
def test_confirming_commands_puts_the_turn_in_confirm_gate_mode() -> None:
assert _build(confirm_commands=True).gate_mode == "confirm"
assert _build(confirm_commands=False).gate_mode == "auto"
assert _build().gate_mode == "auto" # auto-run is the default
def test_the_captured_widget_state_is_carried_into_the_request() -> None:
request = _build(
surface="cowork", project_id="p7", title="Weekly report",
provider_id="anthropic", model="claude-sonnet-4-6",
instructions="PROJECT RULES", output_dir="out/.turns/t3",
home_output_root="out", agent_role="cowork",
)
assert (request.turn_id, request.session_id) == ("t3", "s1")
assert (request.surface, request.project_id, request.title) == \
("cowork", "p7", "Weekly report")
assert (request.provider_id, request.model) == ("anthropic", "claude-sonnet-4-6")
assert request.project_context == "PROJECT RULES"
assert request.output_dir == Path("out/.turns/t3")
assert request.home_output_root == Path("out")
assert request.agent_role == "cowork"
def test_the_prompt_survives_a_message_whose_content_is_missing() -> None:
request = _build(messages=[{"role": "user"}])
assert request.prompt == ""
+34
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@@ -0,0 +1,34 @@
"""R04-T05 — unit tests for the unattended-run prompt assembly.
``_run_agent`` used to build this by rebinding ``prompt`` three times, each with
its own ``f"{block}\n\n{prompt}"``. The ORDER that produced is load-bearing (the
plan reminder has to lead, the task's own words have to trail) and it was
readable only by replaying the rebindings in your head.
"""
from __future__ import annotations
from cowork_local.core.task_executors import _unattended_prompt
def test_the_plan_reminder_leads_and_the_task_prompt_trails() -> None:
built = _unattended_prompt("write the report")
assert built.startswith("This runs unattended (Schedule Task)")
assert built.endswith("write the report")
def test_a_skill_block_sits_between_the_reminder_and_the_agent_persona() -> None:
built = _unattended_prompt("write the report", skill_text="SKILL",
agent_instructions="PERSONA")
assert built.index("This runs unattended") < built.index("SKILL")
assert built.index("SKILL") < built.index("PERSONA")
assert built.index("PERSONA") < built.index("write the report")
def test_absent_blocks_leave_no_extra_blank_lines() -> None:
built = _unattended_prompt("do it", skill_text="", agent_instructions=None)
assert "\n\n\n" not in built
assert built.count("do it") == 1
+36
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@@ -0,0 +1,36 @@
"""R04-T04 — unit tests for the shared turn-runtime helpers.
``combine_instructions`` is the small rule the UI applied inline: a turn's
standing instructions are several independent blocks (project context, an Admin
agent's persona, a skill's rules, an unattended-run reminder) that must be joined
with one blank line, skipping whatever is absent. Two call sites need it (T04's
widget and T05's task runner), which is exactly when a rule stops being an inline
expression.
"""
from __future__ import annotations
from cowork_local.application.conversations.turn_runtime import combine_instructions
def test_two_blocks_are_joined_by_a_blank_line() -> None:
assert combine_instructions("PROJECT", "AGENT") == "PROJECT\n\nAGENT"
def test_an_absent_block_leaves_no_blank_line_behind() -> None:
assert combine_instructions("", "AGENT") == "AGENT"
assert combine_instructions("PROJECT", "") == "PROJECT"
assert combine_instructions("PROJECT", None) == "PROJECT"
def test_whitespace_only_blocks_do_not_count_as_instructions() -> None:
assert combine_instructions(" \n ", "AGENT") == "AGENT"
def test_nothing_to_say_produces_an_empty_string() -> None:
assert combine_instructions() == ""
assert combine_instructions("", None, " ") == ""
def test_more_than_two_blocks_keep_their_order() -> None:
assert combine_instructions("A", "B", "C") == "A\n\nB\n\nC"
+58 -19
View File
@@ -346,19 +346,45 @@ class CoworkTab(ChatPanel):
self._apply_output_folder_label() # picks up edits made via Settings too self._apply_output_folder_label() # picks up edits made via Settings too
def build_job(self, text: str, messages, out_dir): def build_job(self, text: str, messages, out_dir):
# Each turn writes into its OWN isolated folder (out_dir) and works on its """This turn's job: a frozen request run through the conversation service.
# OWN message list, so several turns can run in parallel without clobbering
# each other's files or history. Deliverables are moved up to the session Since R04-T04 the widget no longer drives the turn loop. Every value a
# Output root when the turn finishes (see _cleanup_turn). turn depends on is read HERE, on the UI thread at submit time, and packed
into an immutable ``ConversationExecutionRequest`` — so clicking a
different model or switching workspace mid-answer cannot reach work
already in flight.
"""
output_dir = out_dir or self._session_output_dir() output_dir = out_dir or self._session_output_dir()
# The sandbox folder is named by the turn id ('.turns/t3'); with no
# sandbox the session id identifies the turn well enough for the audit log.
turn_id = out_dir.name if out_dir is not None else self.session_id
session_id = self.session_id
title = self.title title = self.title
project_id = self.project_id project_id = self.project_id
home_output_root = self.workspace_dir()
# Captured at submit time (UI thread): the Admin-defined agent # Captured at submit time (UI thread): the Admin-defined agent
# preset's instructions, if one is selected in the Agent picker. # preset's instructions, if one is selected in the Agent picker.
agent_prompt = self.admin_agent_prompt() agent_prompt = self.admin_agent_prompt()
# Per-workspace Auto-run override wins, else the global "confirm before
# running commands" setting. Frozen now, so a Settings change mid-turn
# cannot flip the rules this turn started under.
confirm_commands = self.ctx.project_confirm_commands()
# What the turn is recorded as running on. A routing override (R03) wins
# over the tab's own picker; '' means the provider's configured default.
# Informational only — an Admin-agent preset builds its own provider
# below, so treat these as the record, not the decision.
provider_id = self._routed_provider or self.ctx.config.active_provider
model = self._routed_model or self._model or ""
def job(worker: AgentWorker): def job(worker: AgentWorker):
from ..core.chat_agent import run_cowork from ..application.conversations.core_runtime_adapter import (
build_cowork_conversation_service,
legacy_event_sink,
)
from ..application.conversations.cowork_turn_request import (
build_cowork_turn_request,
)
from ..application.conversations.turn_runtime import combine_instructions
from ..core.projects import load_project, project_context_text from ..core.projects import load_project, project_context_text
provider = self.build_provider() # this tab's selected agent/model provider = self.build_provider() # this tab's selected agent/model
@@ -367,23 +393,36 @@ class CoworkTab(ChatPanel):
# built-in MCP server auto-registered while signed in, see # built-in MCP server auto-registered while signed in, see
# AppContext._ms365_builtin_connection / mcp_servers/ms365_server.py). # AppContext._ms365_builtin_connection / mcp_servers/ms365_server.py).
extra_tools, extra_exec = self.ctx.build_mcp_tools() extra_tools, extra_exec = self.ctx.build_mcp_tools()
# Shared project instructions (Claude-Projects style) — refreshed # Shared project instructions (Claude-Projects style) plus the Admin
# each turn so edits in the Workspace screen apply immediately. # agent's persona, refreshed each turn so edits in the Workspace
proj_ctx = project_context_text(load_project(project_id)) # screen apply immediately.
if agent_prompt: instructions = combine_instructions(
proj_ctx = f"{proj_ctx}\n\n{agent_prompt}" if proj_ctx else agent_prompt project_context_text(load_project(project_id)), agent_prompt)
# Permission Management (Sandbox Security Layer): off by default — # Permission Management (Sandbox Security Layer): off by default —
# matches the pre-existing auto-run behavior. Now resolved PER # matches the pre-existing auto-run behavior. The gate lives on the
# WORKSPACE: this project's Auto-run override wins, else the global # worker because the UI resolves it from the main thread.
# "confirm before running commands" setting (project_confirm_commands).
gate = None gate = None
if self.ctx.project_confirm_commands(): if confirm_commands:
gate = worker.new_gate("confirm", agent_role=agent_roles.COWORK) gate = worker.new_gate("confirm", agent_role=agent_roles.COWORK)
run_cowork(provider, messages, output_dir, worker.emit_event,
worker.is_cancelled, title=title, service = build_cowork_conversation_service(
extra_tools=extra_tools, extra_executor=extra_exec, provider, output_dir, worker.emit_event, title=title,
project_context=proj_ctx, security_config=self.ctx.config, project_context=instructions, extra_tools=extra_tools,
gate=gate) extra_executor=extra_exec, security_config=self.ctx.config,
gate=gate, agent_role=agent_roles.COWORK,
)
request = build_cowork_turn_request(
turn_id=turn_id, session_id=session_id, surface=self.kind,
project_id=project_id, title=title, messages=messages,
provider_id=provider_id, model=model, instructions=instructions,
output_dir=output_dir, home_output_root=home_output_root,
confirm_commands=gate is not None, agent_role=agent_roles.COWORK,
)
# Hand the widget's own list over: _reattach_running_turn replays
# from it while the turn is still running, and _finalize_turn slices
# it afterwards, so the service must append into that very object.
service.execute(request, legacy_event_sink(worker.emit_event),
cancel=worker.is_cancelled, messages=messages)
return {"messages": messages, "turn_dir": str(output_dir)} return {"messages": messages, "turn_dir": str(output_dir)}
return job return job