Merge pull request 'Add executor tool loop (A12/A15) — step 5b' (#12) from executor-loop into main
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This commit was merged in pull request #12.
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commit
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10 files changed
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@@ -59,6 +59,14 @@ class AskHuman:
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question: str
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class MilestoneExecutor(Protocol):
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"""What the orchestrator needs from an executor loop; the concrete one
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lives in nisse_dev.executor (imported there, not here, to keep the
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dependency pointing one way)."""
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def run(self, milestone: int) -> Any: ...
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class PlanningAgent(Protocol):
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def plan(
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self,
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@@ -91,7 +99,9 @@ def _fresh_data() -> dict[str, Any]:
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return {
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"revs": {},
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"gate": None,
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"question": None,
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# What an operator reply in AWAIT_INPUT should resume. Every path into
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# AWAIT_INPUT must set this, or the reply has nowhere to go.
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"pending": None,
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"milestone": 1,
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"task_id": None,
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"roles": None, # A11 mapping, pinned at task start
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@@ -106,11 +116,13 @@ class Orchestrator:
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agent: PlanningAgent,
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operators: Iterable[str],
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roles: RoleMap | None = None,
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executor: "MilestoneExecutor | None" = None,
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) -> None:
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self._store = store
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self._transport = transport
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self._agent = agent
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self._roles = roles
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self._executor = executor
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self._operators = set(operators)
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self._data = _fresh_data()
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self._project: str | None = None
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@@ -128,11 +140,14 @@ class Orchestrator:
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self._store.oplog.task_id = self._data.get("task_id")
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gate = self._data.get("gate")
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if report.action == "await_input":
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self._transition(AWAIT_INPUT, cause="boot: unresolved intents")
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self._transport.ask_question(
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"restart found unresolved work: "
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+ "; ".join(report.notes)
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+ " — how should I proceed?"
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self._await_input(
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cause="boot: unresolved intents",
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prompt=(
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"restart found unresolved work: "
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+ "; ".join(report.notes)
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+ " — how should I proceed?"
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),
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pending={"kind": "boot"},
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)
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elif state.state == IDLE or (
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state.state in (AWAIT_ARCH_SIGNOFF, AWAIT_MILESTONE_SIGNOFF) and gate
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@@ -147,9 +162,10 @@ class Orchestrator:
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else:
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# Interrupted mid-turn (planning, executing, unanswered question):
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# never blind-resume (A3.6).
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self._transition(AWAIT_INPUT, cause=f"boot: restarted in {state.state}")
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self._transport.ask_question(
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f"restarted mid-{state.state}; continue or re-plan?"
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self._await_input(
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cause=f"boot: restarted in {state.state}",
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prompt=f"restarted mid-{state.state}; continue or re-plan?",
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pending={"kind": "boot"},
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)
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def _handle(self, msg: InboundMessage) -> None:
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@@ -207,17 +223,18 @@ class Orchestrator:
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gate_name, self._project, feedback=feedback, answer=answer
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)
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except PlanningError as exc:
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self._transition(AWAIT_INPUT, cause=f"planning failed: {exc}")
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self._transport.ask_question(
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f"planning for {gate_name} failed ({exc}); retry or re-plan?"
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self._await_input(
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cause=f"planning failed: {exc}",
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prompt=f"planning for {gate_name} failed ({exc}); how should I proceed?",
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pending={"kind": "planning_failed", "gate": gate_name},
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)
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return
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if isinstance(action, AskHuman):
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self._data["question"] = {"text": action.question, "gate": gate_name}
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self._transition(
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AWAIT_INPUT, cause=f"agent question during {gate_name} planning"
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self._await_input(
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cause=f"agent question during {gate_name} planning",
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prompt=action.question,
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pending={"kind": "question", "gate": gate_name},
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)
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self._transport.ask_question(action.question)
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return
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rev = self._data["revs"].get(gate_name, 0) + 1
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self._data["revs"][gate_name] = rev
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@@ -259,7 +276,7 @@ class Orchestrator:
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self._transition(
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EXECUTING, cause=f"operator command: start milestone {milestone}"
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)
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self._transport.send_message(f"[stub] executing milestone {milestone}")
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self._execute_milestone(milestone)
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else:
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self._transport.send_message(
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f"plan approved; say 'start milestone {milestone}' to begin"
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@@ -313,18 +330,59 @@ class Orchestrator:
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f"milestone plan approved; say 'start milestone {milestone}' to begin"
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)
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def _execute_milestone(self, milestone: int) -> None:
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if self._executor is None:
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self._transport.send_message(f"[stub] executing milestone {milestone}")
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return
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self._transport.send_message(f"executing milestone {milestone}")
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outcome = self._executor.run(milestone)
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if outcome.status == "completed":
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# PR_OPEN and the review loop arrive with the Gitea layer (B2);
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# until then a finished milestone simply reports and waits.
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self._transport.send_message(f"milestone {milestone} done: {outcome.note}")
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return
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self._await_input(
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cause=f"milestone {milestone} {outcome.status}",
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prompt=f"milestone {milestone} stopped ({outcome.status}): {outcome.note}",
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pending={"kind": "milestone_stopped", "milestone": milestone},
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)
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def _await_input(self, *, cause: str, prompt: str, pending: dict[str, Any]) -> None:
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self._data["pending"] = pending
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self._transition(AWAIT_INPUT, cause=cause)
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self._transport.ask_question(prompt)
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def _handle_answer(self, text: str) -> None:
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question = self._data.get("question")
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if question is None:
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pending = self._data.get("pending")
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if pending is None:
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# Reached only if state was forced externally; say what works
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# rather than dead-ending the operator.
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self._transport.send_message(
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"awaiting operator resolution; no pending question to answer"
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"waiting for direction, but I have no pending item to resume; "
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"try 'status', or 'use <project>' to start over"
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)
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return
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self._data["question"] = None
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gate_name = question["gate"]
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back = PLANNING_ARCH if gate_name == "arch" else MILESTONE_PLANNING
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self._transition(back, cause="operator answered question")
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self._run_planning_turn(gate_name, answer=text)
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self._data["pending"] = None
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match pending.get("kind"):
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case "question" | "planning_failed":
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gate_name = pending["gate"]
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back = PLANNING_ARCH if gate_name == "arch" else MILESTONE_PLANNING
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self._transition(back, cause="operator answered; resuming planning")
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self._run_planning_turn(gate_name, answer=text)
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case "milestone_stopped":
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milestone = pending["milestone"]
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self._transition(
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AWAIT_MILESTONE_SIGNOFF,
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cause="operator answered; plan still approved",
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)
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self._transport.send_message(
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f"noted. the milestone {milestone} plan is still approved — "
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f"say 'start milestone {milestone}' to run it again"
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)
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case _:
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self._transport.send_message(
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"noted. say 'status' for where things stand"
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)
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def _transition(self, new_state: str, *, cause: str) -> None:
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state = self._store.get_state()
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@@ -0,0 +1,107 @@
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"""Local executor loop (spec A12 escalation triggers, A15 accommodations).
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Runs the approved plan with the executor role — the cheap local model doing
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mechanical work. Every tool call and result is checkpointed to the canonical
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log as it happens (A13), so a crash mid-milestone leaves a resumable record.
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Escalation is decided from outside the model (A12): consecutive command
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failures and hard caps on turns, never the model's own claim that it is stuck
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or finished-enough. Until delegation exists (step 7), an escalation gates to
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the human with the failures attached rather than engaging a frontier model.
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"""
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from dataclasses import dataclass
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from typing import Literal
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from nisse_dev.canonical import ToolCall, ToolResult
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from nisse_dev.llm import LLMClient, LLMError, RoleMap
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from nisse_dev.state import StateStore
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from nisse_dev.tools import EXECUTOR_TOOLS, Workspace
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EXECUTOR_SYSTEM = """You are nisse-dev's executor, doing mechanical work.
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Follow the approved plan above exactly. It was written to be executed
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verbatim; do not redesign it, expand its scope, or skip steps.
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Work by calling tools. Verify your work by running the project's tests.
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When every step of the plan is done and the tests pass, reply with a short
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plain-text summary and no tool call — that ends the milestone."""
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DEFAULT_MAX_TURNS = 24
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DEFAULT_FAILURE_LIMIT = 2
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@dataclass(frozen=True)
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class ExecutorOutcome:
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status: Literal["completed", "capped", "escalate"]
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note: str
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class LLMExecutor:
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def __init__(
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self,
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client: LLMClient,
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store: StateStore,
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roles: RoleMap,
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workspace: Workspace,
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*,
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max_turns: int = DEFAULT_MAX_TURNS,
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failure_limit: int = DEFAULT_FAILURE_LIMIT,
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) -> None:
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self._client = client
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self._store = store
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self._roles = roles
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self._workspace = workspace
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self._max_turns = max_turns
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self._failure_limit = failure_limit
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def run(self, milestone: int) -> ExecutorOutcome:
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model = self._roles.resolve("executor")
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system = f"{EXECUTOR_SYSTEM}\n\nYou are executing milestone {milestone}."
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consecutive_failures = 0
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for _turn in range(self._max_turns):
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try:
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produced = self._client.complete(
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self._store.read_events(),
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tools=EXECUTOR_TOOLS,
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model=model,
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system=system,
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)
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except LLMError as exc:
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return ExecutorOutcome("escalate", f"executor call failed: {exc}")
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calls: list[ToolCall] = []
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for event in produced:
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self._store.append_event(event)
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if isinstance(event, ToolCall):
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calls.append(event)
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if not calls:
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return ExecutorOutcome("completed", "executor reported the plan done")
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for call in calls:
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outcome = self._workspace.dispatch(call.tool, call.arguments)
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self._store.append_event(
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ToolResult(
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call_id=call.call_id,
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result=outcome.result,
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success=outcome.success,
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)
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)
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# Only commands count toward escalation: a failed read is the
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# model looking around, a failed command is work not working.
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if call.tool == "run_command":
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consecutive_failures = (
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0 if outcome.success else consecutive_failures + 1
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)
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if consecutive_failures >= self._failure_limit:
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return ExecutorOutcome(
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"escalate",
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f"{consecutive_failures} consecutive command failures; "
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f"last: {outcome.result[:500]}",
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)
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return ExecutorOutcome(
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"capped", f"hit the {self._max_turns}-turn cap for milestone {milestone}"
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)
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@@ -11,7 +11,7 @@ crash mid-planning leaves a truthful transcript.
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from typing import Any
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from nisse_dev.canonical import AssistantText, ToolCall
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from nisse_dev.canonical import AssistantText, ToolCall, ToolResult
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from nisse_dev.control import AskHuman, PlanningError, SubmitPlan
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from nisse_dev.llm import LLMClient, LLMError, RoleMap
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from nisse_dev.state import StateStore
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@@ -142,6 +142,21 @@ class LLMPlanningAgent:
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continue
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if isinstance(event, ToolCall):
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action = self._interpret(event)
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if action is not None:
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# The gate is this call's outcome. Recording it keeps the
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# transcript renderable: providers reject a tool call with
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# no result, and the next planning turn replays this log.
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self._store.append_event(
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ToolResult(
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call_id=event.call_id,
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result=(
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"plan posted for approval; turn ended"
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if isinstance(action, SubmitPlan)
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else "question posted; awaiting the operator"
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),
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success=True,
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)
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)
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return action
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def _interpret(self, call: ToolCall) -> SubmitPlan | AskHuman | None:
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@@ -57,8 +57,24 @@ class OpenAIChatRenderer:
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messages: list[dict[str, Any]] = []
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if system is not None:
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messages.append({"role": "system", "content": system})
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for stored in effective_events(events):
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kept = effective_events(events)
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answered = {e.event.call_id for e in kept if isinstance(e.event, ToolResult)}
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for stored in kept:
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messages.append(self._message_for(stored.event))
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# Providers reject a tool call with no result following it. One
|
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# can legitimately be missing: a crash between the call and its
|
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# result (A3), or a turn-ending gate tool. Render a placeholder so
|
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# the transcript stays replayable rather than poisoned.
|
||||
if isinstance(stored.event, ToolCall) and (
|
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stored.event.call_id not in answered
|
||||
):
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messages.append(
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{
|
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"role": "tool",
|
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"tool_call_id": stored.event.call_id,
|
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"content": "[no result recorded]",
|
||||
}
|
||||
)
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body: dict[str, Any] = {"model": model, "messages": messages}
|
||||
if tools:
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||||
body["tools"] = tools
|
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|
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@@ -0,0 +1,204 @@
|
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"""Executor tools (spec A15: reduced schema, flat arguments).
|
||||
|
||||
Deliberately unsandboxed. The VM is the trust boundary (B3) and tool use is
|
||||
auto-approved inside an approved unit of work (A4), so per-command
|
||||
confinement would add failure modes without adding safety. The workspace is
|
||||
where work happens — the default for relative paths and the command cwd — not
|
||||
a wall. Protecting agent state from the agent is a mount-layout concern
|
||||
(A2/B3), not this module's job.
|
||||
|
||||
What *is* enforced here is operational: commands cannot hang the loop, cannot
|
||||
consume the context window with megabytes of build log, and do not inherit
|
||||
the agent's own credentials.
|
||||
"""
|
||||
|
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import os
|
||||
import shutil
|
||||
import signal
|
||||
import subprocess
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
DEFAULT_TIMEOUT_S = 120
|
||||
MAX_OUTPUT_CHARS = 4000
|
||||
|
||||
EXECUTOR_TOOLS: list[dict[str, Any]] = [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "read_file",
|
||||
"description": "Read a UTF-8 text file.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {"path": {"type": "string"}},
|
||||
"required": ["path"],
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "write_file",
|
||||
"description": "Write a UTF-8 text file, creating parent directories.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"path": {"type": "string"},
|
||||
"content": {"type": "string"},
|
||||
},
|
||||
"required": ["path", "content"],
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "list_dir",
|
||||
"description": "List the entries of a directory.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {"path": {"type": "string"}},
|
||||
"required": ["path"],
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "run_command",
|
||||
"description": (
|
||||
"Run a shell command in the workspace. Returns its exit code "
|
||||
"and output; a non-zero exit is a result, not an error."
|
||||
),
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {"command": {"type": "string"}},
|
||||
"required": ["command"],
|
||||
},
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
def _truncate(text: str) -> str:
|
||||
if len(text) <= MAX_OUTPUT_CHARS:
|
||||
return text
|
||||
dropped = len(text) - MAX_OUTPUT_CHARS
|
||||
return f"{text[:MAX_OUTPUT_CHARS]}\n[... {dropped} characters truncated]"
|
||||
|
||||
|
||||
def _child_env() -> dict[str, str]:
|
||||
"""The project's build and test code is arbitrary; it has no business
|
||||
reading the agent's LiteLLM, Matrix, or Gitea credentials."""
|
||||
return {k: v for k, v in os.environ.items() if not k.startswith("NISSE_")}
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class ToolOutcome:
|
||||
result: str
|
||||
success: bool
|
||||
|
||||
|
||||
class Workspace:
|
||||
def __init__(self, root: Path, *, timeout_s: int = DEFAULT_TIMEOUT_S) -> None:
|
||||
self.root = Path(root)
|
||||
self.root.mkdir(parents=True, exist_ok=True)
|
||||
self._timeout_s = timeout_s
|
||||
|
||||
def _resolve(self, path: str) -> Path:
|
||||
candidate = Path(path)
|
||||
return candidate if candidate.is_absolute() else self.root / candidate
|
||||
|
||||
def dispatch(self, tool: str, arguments: dict[str, Any]) -> ToolOutcome:
|
||||
try:
|
||||
match tool:
|
||||
case "read_file":
|
||||
return self.read_file(str(arguments["path"]))
|
||||
case "write_file":
|
||||
return self.write_file(
|
||||
str(arguments["path"]), str(arguments["content"])
|
||||
)
|
||||
case "list_dir":
|
||||
return self.list_dir(str(arguments.get("path", ".")))
|
||||
case "run_command":
|
||||
return self.run_command(str(arguments["command"]))
|
||||
case _:
|
||||
return ToolOutcome(f"no such tool: {tool}", success=False)
|
||||
except KeyError as exc:
|
||||
return ToolOutcome(f"missing argument {exc} for {tool}", success=False)
|
||||
|
||||
def read_file(self, path: str) -> ToolOutcome:
|
||||
target = self._resolve(path)
|
||||
try:
|
||||
return ToolOutcome(_truncate(target.read_text()), success=True)
|
||||
except (OSError, UnicodeDecodeError) as exc:
|
||||
return ToolOutcome(f"could not read {path}: {exc}", success=False)
|
||||
|
||||
def write_file(self, path: str, content: str) -> ToolOutcome:
|
||||
target = self._resolve(path)
|
||||
try:
|
||||
target.parent.mkdir(parents=True, exist_ok=True)
|
||||
target.write_text(content)
|
||||
except OSError as exc:
|
||||
return ToolOutcome(f"could not write {path}: {exc}", success=False)
|
||||
return ToolOutcome(f"wrote {len(content)} characters to {path}", success=True)
|
||||
|
||||
def list_dir(self, path: str) -> ToolOutcome:
|
||||
target = self._resolve(path)
|
||||
try:
|
||||
entries = sorted(
|
||||
f"{p.name}/" if p.is_dir() else p.name for p in target.iterdir()
|
||||
)
|
||||
except OSError as exc:
|
||||
return ToolOutcome(f"could not list {path}: {exc}", success=False)
|
||||
return ToolOutcome(_truncate("\n".join(entries) or "(empty)"), success=True)
|
||||
|
||||
def run_command(self, command: str) -> ToolOutcome:
|
||||
try:
|
||||
# Popen rather than run(): on timeout, run() kills only the direct
|
||||
# child, and TimeoutExpired carries no pid, so a backgrounded
|
||||
# grandchild (a dev server, say) would survive. Holding the pid
|
||||
# lets us kill the whole session.
|
||||
process = subprocess.Popen(
|
||||
command,
|
||||
shell=True,
|
||||
cwd=self.root,
|
||||
env=_child_env(),
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.PIPE,
|
||||
stdin=subprocess.DEVNULL,
|
||||
text=True,
|
||||
start_new_session=True,
|
||||
)
|
||||
except OSError as exc:
|
||||
return ToolOutcome(f"could not run command: {exc}", success=False)
|
||||
try:
|
||||
stdout, stderr = process.communicate(timeout=self._timeout_s)
|
||||
except subprocess.TimeoutExpired:
|
||||
self._kill_group(process)
|
||||
return ToolOutcome(
|
||||
f"command timed out after {self._timeout_s}s: {command}",
|
||||
success=False,
|
||||
)
|
||||
body = _truncate(
|
||||
f"exit code: {process.returncode}\nstdout:\n{stdout}\nstderr:\n{stderr}"
|
||||
)
|
||||
return ToolOutcome(body, success=process.returncode == 0)
|
||||
|
||||
@staticmethod
|
||||
def _kill_group(process: "subprocess.Popen[str]") -> None:
|
||||
try:
|
||||
os.killpg(os.getpgid(process.pid), signal.SIGKILL)
|
||||
except (ProcessLookupError, PermissionError):
|
||||
process.kill()
|
||||
# Drain the pipes of the now-dead group so no zombie is left behind.
|
||||
try:
|
||||
process.communicate(timeout=5)
|
||||
except subprocess.TimeoutExpired:
|
||||
pass
|
||||
|
||||
def reset(self) -> None:
|
||||
"""Discard workspace contents; used by tests, not by the agent."""
|
||||
shutil.rmtree(self.root, ignore_errors=True)
|
||||
self.root.mkdir(parents=True, exist_ok=True)
|
||||
Reference in new issue
Block a user