feat(R04): add the immutable turn snapshot and typed agent event stream
R04-T01 — `domain/agents/conversation_execution_request.py`: a frozen
snapshot of everything one chat turn needs. Turn inputs previously lived in a
closure plus a 15-key ctx dict inside `ui/chat_panel.py::_start_turn`, and the
worker thread kept reading the widget back while it ran, so every later click
was visible to work already in flight. The request also owns the prompt
composition rules (instruction prefix separator, session notes, model-switch
review note) that were inline in that closure.
R04-T02 — `domain/agents/agent_event.py`: 13 frozen event types replacing the
untyped `{"type": ...}` dicts, whose only specification was the 130-line
if/elif chain in `_on_event`. Each event serialises back to the exact legacy
dict, so the presentation layer is untouched; `agent_event_codec.py` parses the
other way and is a temporary shim, isolated so R08 can delete it in one move.
`assistant_done` is deliberately NOT the end of a turn (it fires once per
provider call), so it maps to AssistantMessageCompletedEvent while the new
TurnCompletedEvent reports the turn itself.
R04-T03 (part) — `domain/agents/agent_result.py`: one named outcome for a
finished turn, replacing the message list / 3-tuple / reconstructed-from-side-
effects trio the three callers each read differently.
Verification: 66 tests. Beyond the unit tests,
`tests/integration/test_agent_event_bridge.py` runs the REAL `run_cowork` loop
offline and asserts every dict it emits is recognised and round-trips
byte-for-byte — a guard against an event type nobody modelled or a key whose
meaning silently drifted.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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"""The immutable snapshot of ONE chat turn (R04-T01).
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Today a turn's inputs live in a closure plus a 15-key ``ctx`` dict built inside
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``ui/chat_panel.py::_start_turn``, and the worker thread reads the widget back
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(``self._model``, ``self.title``, ``self.project_id``) while it runs. That is
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the mechanism behind the whole class of "I changed the model mid-answer and the
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running turn behaved oddly" reports: the turn has no snapshot of its own, so
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every later click on the UI is visible to work already in flight.
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:class:`ConversationExecutionRequest` is that missing snapshot. Everything the
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runtime needs for one turn is captured once, on the UI thread, at submit time,
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and then handed to code that runs on a worker thread. Frozen, so no caller —
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widget or service — can retroactively change a decision the turn already acted
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on.
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Layer rules (see ``docs/architecture/ADR-001-layered-architecture.md``): this is
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the domain layer, so standard library only. No PySide6, no ``requests``, no
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filesystem access, and deliberately no import of ``core/*`` — a request only
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*describes* a turn; running it is the application layer's job
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(``application/conversations/``).
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field, replace
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from pathlib import Path
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from typing import Any, Dict, Optional, Tuple
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# Separator between an instruction prefix (a ``/skill`` block, an ``/agent``
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# persona) and the user's own request. Kept as a constant because the prefix is
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# assembled in the presentation layer while the body is only known later on the
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# worker thread — both halves must agree on the exact separator or the model
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# sees a different prompt shape than it did before this refactor.
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PREFIX_SEPARATOR = "\n\n---\n\n"
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@dataclass(frozen=True)
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class ConversationExecutionRequest:
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"""Everything needed to execute one conversation turn.
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Frozen for the reason above; use :meth:`with_model` / :meth:`with_output_dir`
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to derive an adjusted copy rather than mutating one another thread may be
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reading.
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Note on depth: ``messages`` is a *shallow* snapshot (a tuple holding the
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same message dicts the caller passed). That matches the existing
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``snapshot = list(self.messages)`` semantics in ``_start_turn`` exactly —
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the turn is protected from the history list being appended to or replaced,
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which is what actually happens between turns. Making it deep would silently
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change how ``_finalize_turn`` merges the turn's messages back, so the
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stronger guarantee is left to R04-T03 where that merge moves.
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"""
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# -- identity ------------------------------------------------------- #
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turn_id: str # unique within a session ("t1", "t2", ...)
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session_id: str # the conversation this turn belongs to
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surface: str = "cowork" # routing/mode key: "cowork" | "co4e" | "ai_edit"
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project_id: str = "" # workspace the turn is confined to
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title: str = "" # conversation title; also names saved files
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# -- what the user asked -------------------------------------------- #
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# The typed request, already stripped of any ``/skill`` or ``/agent``
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# directive (those become ``instruction_prefix``).
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prompt: str = ""
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instruction_prefix: str = "" # skill rules + agent persona for this turn
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# Prepended when the model/agent was switched mid-conversation, asking the
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# model to re-check the previous step before continuing. Invisible in the
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# chat bubble — it only travels in the payload sent to the provider.
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review_note: str = ""
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# Attachment PATHS, not their text: extracting a .docx can pip-install a
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# parser or shell out to LibreOffice, which must not run on the UI thread.
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# The runtime reads them later and passes the result to :meth:`user_content`.
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attachments: Tuple[str, ...] = ()
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# Conversation history as of submit time; the new user message is NOT part
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# of it (the runtime appends it once the body is composed).
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messages: Tuple[Dict[str, Any], ...] = ()
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# -- which model answers -------------------------------------------- #
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# Already resolved upstream: an Admin-agent pin, the tab's own picker, or a
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# routing override published by ``RoutingApplicationService`` (R03). The
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# runtime does not re-decide, so a switch cannot land mid-turn.
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provider_id: str = ""
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model: str = "" # "" = the provider's configured default
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# -- standing instructions ------------------------------------------ #
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project_context: str = "" # Claude-Projects-style shared instructions
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session_notes: str = "" # e.g. files this conversation already produced
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# -- tool scope and turn limits -------------------------------------- #
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# None = every enabled built-in tool. An explicit (possibly empty) tuple
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# restricts the ADVERTISED tools, which is how a "read-only" step is made
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# literally unable to write.
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allowed_tools: Optional[Tuple[str, ...]] = None
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max_steps: int = 30 # interactive cap
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completion_max_steps: int = 200 # runaway ceiling for run-to-completion work
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run_to_completion: bool = False # Co4E flow steps need the higher ceiling
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enforce_rules: bool = True # False for sandboxed Co4E runs
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gate_mode: str = "auto" # "confirm" -> ask before run_command/install
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agent_role: str = "cowork" # audit-log attribution ("cowork" | "task" | ...)
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# -- where its files go ---------------------------------------------- #
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output_dir: Optional[Path] = None # this turn's isolated sandbox
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home_output_root: Optional[Path] = None # conversation Output root to promote into
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# -- unattended execution (Schedule Task) ----------------------------- #
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unattended: bool = False # no human watching; plan tracking is enforced
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timeout_sec: Optional[int] = None # None = no wall-clock limit
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# Escape hatch for surface-specific data a future task needs to thread
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# through without another schema change (same role as
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# ``ProviderDescriptor.extras``).
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extras: Dict[str, Any] = field(default_factory=dict)
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# -- validation / normalisation --------------------------------------- #
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def __post_init__(self) -> None:
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"""Reject unusable requests and freeze the mutable inputs.
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Validation lives here (not at the call site) so a request that exists is
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always safe to key by: the audit log, the History autosave and the
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per-turn output folder are all named from ``session_id``/``turn_id``.
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Normalisation matters just as much: the caller hands us the composer's
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own attachment LIST and the live history LIST, and both get cleared or
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appended to for the next turn. Copying them into tuples here is what
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actually makes the snapshot a snapshot. ``object.__setattr__`` is the
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standard way to do this in a frozen dataclass.
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"""
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if not (self.turn_id or "").strip():
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raise ValueError("ConversationExecutionRequest.turn_id must not be empty")
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if not (self.session_id or "").strip():
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raise ValueError("ConversationExecutionRequest.session_id must not be empty")
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object.__setattr__(self, "attachments", tuple(self.attachments or ()))
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object.__setattr__(self, "messages", tuple(self.messages or ()))
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# None must survive: it means "no restriction", while an empty tuple
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# means "deny every built-in tool" — two very different turns.
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if self.allowed_tools is not None:
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object.__setattr__(self, "allowed_tools", tuple(self.allowed_tools))
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# Accept str paths so a call site holding a config value does not have to
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# wrap it; everything downstream can then assume Path.
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for name in ("output_dir", "home_output_root"):
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value = getattr(self, name)
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if value is not None and not isinstance(value, Path):
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object.__setattr__(self, name, Path(value))
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# -- derived turn policy ---------------------------------------------- #
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@property
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def has_prompt(self) -> bool:
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"""Whether the user actually typed something (an attachment-only turn
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legitimately has none). Mirrors ``RoutingRequest.has_prompt`` so both
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DTOs answer the "is there anything to work with?" question the same way.
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"""
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return bool((self.prompt or "").strip())
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@property
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def effective_max_steps(self) -> int:
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"""The tool-use budget for this turn.
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Run-to-completion work (a Co4E flow step whose single instruction may
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need many tool calls) gets the higher ceiling; interactive chat keeps the
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tight cap. Either way the turn still ends the moment the model stops
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calling tools — this is only the runaway limit.
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"""
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return self.completion_max_steps if self.run_to_completion else self.max_steps
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@property
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def requires_permission_gate(self) -> bool:
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"""Whether ``run_command``/``install_package`` must be approved first.
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Resolved by the caller (per-workspace Auto-run override, else the global
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"confirm before running commands" setting) and frozen here, so toggling
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the setting mid-turn cannot change the rules the turn started under.
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"""
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return self.gate_mode == "confirm"
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# -- prompt composition ------------------------------------------------ #
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def user_content(self, body: str = "") -> str:
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"""The exact ``content`` to send as this turn's user message.
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``body`` is the request text AFTER attachment extraction, which happens
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on the worker thread — hence a method taking it as an argument rather
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than a stored field. The assembly order reproduces the closure in
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``_start_turn`` byte for byte, because changing what a model receives is
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a behaviour change, not a refactor:
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1. session notes are appended after the body;
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2. the instruction prefix goes in front, behind a fixed separator;
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3. the model-switch review note goes ahead of everything.
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"""
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content = body or ""
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notes = self.session_notes or ""
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if notes:
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# Guard the empty-body case (attachment-only turn) so the payload
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# never opens with a stray blank line.
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content = f"{content}\n\n{notes}" if content else notes
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prefix = self.instruction_prefix or ""
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if prefix:
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content = f"{prefix}{PREFIX_SEPARATOR}{content}"
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review = self.review_note or ""
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if review:
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content = f"{review}\n\n{content}"
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return content
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# -- derivation --------------------------------------------------------- #
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def with_model(self, provider_id: str = "", model: str = "") -> "ConversationExecutionRequest":
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"""A copy pinned to another provider/model.
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Needed when a decision lands between building the request and running it
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(a routing override, an Admin-agent pin). Deriving a new request keeps
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the "one turn, one immutable snapshot" rule intact instead of patching a
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request another thread may already hold.
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"""
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return replace(self, provider_id=provider_id or self.provider_id,
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model=model or self.model)
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def with_output_dir(self, output_dir) -> "ConversationExecutionRequest":
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"""A copy writing into a different sandbox — used when the caller only
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learns the per-turn folder after the request is assembled."""
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return replace(self, output_dir=output_dir)
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__all__ = ["PREFIX_SEPARATOR", "ConversationExecutionRequest"]
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