edd14100f9
agent/kanban_stop.py now treats kanban_request_review as a terminal board call, but two sibling copies of the same terminal-knowledge were not updated and still steer workers/runs toward kanban_complete only, which deterministically fails after request_review already ended the run: - hermes_cli/kanban_db_dispatch.py: _PROTOCOL_VIOLATION_ERROR (the corrective sentence surfaced to retry workers) now names all three terminal calls and points at kanban_request_review for review-ready work. - agent/turn_iteration_prep.py: the kanban-worker budget-warning tail no longer nudges a near-budget worker exclusively toward kanban_complete. Co-authored-by: ximontk-review <8566250+crazyief@users.noreply.github.com> Tests: tests/agent/test_kanban_stop.py 3 passed (main, without #105645).
520 lines
25 KiB
Python
520 lines
25 KiB
Python
"""Outer-iteration bookkeeping for the conversation turn loop, in call order:
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``begin_iteration`` (pending redirect, interrupt / review-budget / iteration-budget exits),
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``prepare_iteration`` (``agent:step`` callback, skill-nudge counter, pre-API ``/steer`` drain as a
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standalone user row after the newest tool result, run-budget wrap-up notice, tool_call
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argument sanitization, interrupt-scaffold ghost-row drop, role-alternation repair),
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``announce_api_call`` (verbose summary / quiet spinner) and, after the retry loop,
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``apply_retry_restarts`` (consumes the ``TurnRetryState`` restart flags). Nothing here
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imports ``agent.conversation_loop`` at module level (cycle)."""
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from __future__ import annotations
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import logging
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import random
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import sys
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from contextlib import suppress
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from dataclasses import dataclass
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from typing import Any, Dict
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from agent.display import KawaiiSpinner
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from agent.interrupt_control import interrupt_issuer
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from agent.turn_context_compaction import _reanchor
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logger = logging.getLogger("agent.conversation_loop")
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ITERATION_BUDGET_WARNING_TEMPLATE = (
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"[SYSTEM NOTICE — iteration budget checkpoint] You have used {used} of {maximum} "
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"iterations. Checkpoint durable progress now, then continue the task; do not stop "
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"solely because of this warning."
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)
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def _maybe_inject_iteration_budget_warning(agent: Any, messages: Any) -> bool:
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"""Append the opt-in one-shot warning to the newest tool result."""
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import os
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from agent.delegation_context import is_dispatcher_owned_worker_context
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# Cancellation results still need persistence, but must not urge more work.
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if getattr(agent, "_interrupt_requested", False):
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return False
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ratio = getattr(agent, "budget_warning_ratio", None)
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kanban_worker = (
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bool(os.environ.get("HERMES_KANBAN_TASK"))
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and is_dispatcher_owned_worker_context()
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and "kanban_complete" in getattr(agent, "valid_tool_names", ())
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)
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if ratio is None and kanban_worker:
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ratio = 0.9
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budget = getattr(agent, "iteration_budget", None)
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if (
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ratio is None
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or budget is None
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or budget.max_total <= 1
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or budget.max_total >= sys.maxsize
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or getattr(agent, "_iteration_budget_warning_injected", False)
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or budget.used < min(ratio * budget.max_total, budget.max_total - 1)
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):
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return False
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notice = ITERATION_BUDGET_WARNING_TEMPLATE.format(
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used=budget.used, maximum=budget.max_total
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)
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if kanban_worker:
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notice += (
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" While tools are still available, call kanban_complete only if all task "
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"requirements are verified, or kanban_request_review if it is ready for "
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"review; otherwise persist a kanban_comment handoff and "
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"continue. A diff or commit alone is not completion evidence."
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)
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# Only the current tool-result tail is mutable; an older turn may already be cached.
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from agent.context_compressor import _DB_PERSISTED_MARKER
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if (not messages or messages[-1].get("role") != "tool"
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or messages[-1].get(_DB_PERSISTED_MARKER)):
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return False
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message = messages[-1]
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content = message.get("content", "")
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if isinstance(content, str):
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message["content"] = content + f"\n\n{notice}"
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elif isinstance(content, list) or content is None:
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message["content"] = [*(content or []), {"type": "text", "text": notice}]
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else:
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return False
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agent._iteration_budget_warning_injected = True
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return True
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@dataclass
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class IterationPrep:
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"""Always ``action == "fallthrough"``. ``messages`` is the (possibly filtered) transcript
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and ``request_logger`` the per-request logger the caller keeps using."""
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action: str
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messages: Any
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request_logger: Any
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current_turn_user_idx: Any
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def prepare_iteration(
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agent: Any, *, messages: Any, api_call_count: Any, user_message: Any = None, current_turn_user_idx: Any = None,
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) -> IterationPrep:
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"""Prepare ``messages`` for this iteration in the original order. Every mutation here is
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cache-safe by construction: steer text is appended as a new (not yet persisted) user row, the ghost-row
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filter only drops hidden scaffold placeholders, and repair runs BEFORE the request build."""
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from agent.conversation_loop import (
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_INTERRUPT_SCAFFOLD_MARKER, _maybe_inject_run_budget_wrapup
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)
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# nous.anthropic_wire=auto: a wire switch decided from the previous response lands here,
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# before this iteration's request is built and with nothing in flight.
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if getattr(agent, "_nous_wire_pending", None):
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from agent.nous_wire import apply_pending_wire_switch
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apply_pending_wire_switch(agent)
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# Fire step_callback for gateway hooks (agent:step event).
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if agent.step_callback is not None:
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try:
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agent.step_callback(api_call_count, _previous_tool_round(messages))
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except Exception as _step_err:
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logger.debug("step_callback error (iteration %s): %s", api_call_count, _step_err)
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# Tool-calling iterations for the skill nudge; resets whenever skill_manage is used.
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if agent._skill_nudge_interval > 0 and "skill_manage" in agent.valid_tool_names:
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agent._iters_since_skill += 1
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# Nous agent keys live ~1 h and a single turn can run for hours: adopt the keepalive's fresh
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# key before the one in hand expires (local JWT exp read; no network unless inside the skew)
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# instead of letting this iteration's request 401. With many agents sharing the hour that
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# 401 was a storm, and the pool benched the sole credential for all of them.
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try:
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agent._adopt_nous_key_before_expiry()
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except Exception:
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logger.debug("Nous key pre-expiry adoption failed", exc_info=True)
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# Drain a /steer sent during the last API call so it lands THIS iteration. Delivered as a
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# standalone user row after the newest tool result (never smeared onto the tool row: that
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# row is already persisted append-only, so replay would diverge from the live request and
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# break the prompt cache — same contract as apply_pending_steer_to_tool_results).
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_pre_api_steer = agent._drain_pending_steer()
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if _pre_api_steer:
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_inject_steer_after_newest_tool_result(agent, messages, _pre_api_steer)
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# One-shot run-budget wrap-up notice at 80% of agent.run_budget_seconds, appended to the
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# newest tool result; off with no budget.
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if getattr(agent, "run_budget_seconds", None):
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_maybe_inject_run_budget_wrapup(agent, messages)
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# Appended to the newest tool result; never a synthetic user/system row.
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_maybe_inject_iteration_budget_warning(agent, messages)
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request_logger = getattr(agent, "logger", None) or logger # same name as the origin module
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# Per-agent validation cursor skips re-parsing tool_call args already validated.
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# Identity-keyed; a rewritten list breaks the prefix match and forces a re-scan.
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_sanitize_cursor = getattr(agent, "_sanitize_args_cursor", None)
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if _sanitize_cursor is None:
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_sanitize_cursor = {}
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with suppress(Exception):
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agent._sanitize_args_cursor = _sanitize_cursor
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repaired_tool_calls = agent._sanitize_tool_call_arguments(
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messages, logger=request_logger, session_id=agent.session_id, cursor=_sanitize_cursor
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)
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if repaired_tool_calls > 0:
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request_logger.info(
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"Sanitized %s corrupted tool_call arguments before request (session=%s)",
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repaired_tool_calls,
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agent.session_id or "-",
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)
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# Drop legacy hidden assistant placeholders carrying the raw interrupt scaffold
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# before repair: replayed, the model echoes/self-replicates.
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def _is_scaffold_ghost(msg: Dict[str, Any]) -> bool:
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return (
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msg.get("display_kind") == "hidden"
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and msg.get("role") == "assistant"
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and any(
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isinstance(msg.get(k), str) and msg[k].strip() == _INTERRUPT_SCAFFOLD_MARKER
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for k in ("content", "api_content")
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)
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)
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messages = [msg for msg in messages if not _is_scaffold_ghost(msg)]
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# Repair malformed role alternation (tool→user / user→user tails): providers
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# return empty content on them and the empty-retry loop spins. The _with_cursor
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# variant also recomputes the SessionDB flush cursor after compaction.
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from agent.agent_runtime_helpers import repair_message_sequence_with_cursor
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repaired_seq = repair_message_sequence_with_cursor(agent, messages)
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if repaired_seq > 0:
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request_logger.info(
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"Repaired %s message-alternation violations before request (session=%s)",
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repaired_seq,
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agent.session_id or "-",
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)
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# The merge shrank the list, so the index recorded at turn start can point past this
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# turn's user row: prefetch would inject into a historical row and index-settling hosts
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# (hermes-webui) would write the current turn to the FRONT of the context. Re-anchor as
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# the compression-restart path does (last verbatim row wins, never a historical copy);
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# without the text the index cannot be re-derived and is left detectably stale.
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if user_message is not None:
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_reanchored_idx = _reanchor(agent, messages, user_message)
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if _reanchored_idx != current_turn_user_idx:
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request_logger.info(
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"Re-anchored current_turn_user_idx %s -> %s after alternation repair (session=%s)",
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current_turn_user_idx, _reanchored_idx, agent.session_id or "-",
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)
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current_turn_user_idx = _reanchored_idx
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return IterationPrep(
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action="fallthrough", messages=messages, request_logger=request_logger,
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current_turn_user_idx=current_turn_user_idx,
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)
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def _previous_tool_round(messages: Any) -> list:
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"""The newest assistant tool_calls batch with each call's result, for ``agent:step``."""
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for _idx, _m in enumerate(reversed(messages)):
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if _m.get("role") == "assistant" and _m.get("tool_calls"):
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_results_by_id = {}
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for _tm in messages[len(messages) - _idx:]:
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if _tm.get("role") != "tool":
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break
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_tcid = _tm.get("tool_call_id")
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if _tcid:
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_results_by_id[_tcid] = _tm.get("content", "")
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return [
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{
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"name": tc["function"]["name"],
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"result": _results_by_id.get(tc.get("id")),
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"arguments": tc["function"].get("arguments"),
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}
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for tc in _m["tool_calls"]
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if isinstance(tc, dict)
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]
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return []
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def _inject_steer_after_newest_tool_result(agent: Any, messages: Any, steer_text: str) -> None:
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"""Append the steer marker as a standalone user row after the newest tool message; with no
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tool message, put the text back so the post-tool-execution drain delivers it later."""
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for _si in range(len(messages) - 1, -1, -1):
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_sm = messages[_si]
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if isinstance(_sm, dict) and _sm.get("role") == "tool":
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from agent.prompt_builder import steer_user_row
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messages.insert(_si + 1, steer_user_row(steer_text))
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logger.debug("Pre-API-call steer drain: appended user row after tool msg at index %d", _si)
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return
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from agent.agent_runtime_helpers import _requeue_pending_steer
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_requeue_pending_steer(agent, steer_text)
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@dataclass
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class ApiCallAnnouncement:
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"""Always ``action == "fallthrough"``; ``thinking_spinner`` is the started raw spinner or
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None (TUI widget / streaming consumers / verbose mode)."""
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action: str
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thinking_spinner: Any
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def announce_api_call(
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agent: Any, *, messages: Any, api_messages: Any, api_call_count: Any, approx_tokens: Any,
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total_chars: Any,
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) -> ApiCallAnnouncement:
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"""Print the request summary (verbose) or start the quiet-mode thinking indicator."""
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thinking_spinner = None
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if not agent.quiet_mode:
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agent._vprint(f"\n{agent.log_prefix}🔄 Making API call #{api_call_count}/{agent.max_iterations}...")
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agent._vprint(f"{agent.log_prefix} 📊 Request size: {len(api_messages)} messages, ~{approx_tokens:,} tokens (~{total_chars:,} chars)")
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agent._vprint(f"{agent.log_prefix} 🔧 Available tools: {len(agent.tools) if agent.tools else 0}")
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else:
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# Animated thinking spinner in quiet mode
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face = random.choice(KawaiiSpinner.get_thinking_faces())
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verb = random.choice(KawaiiSpinner.get_thinking_verbs())
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if agent.thinking_callback:
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# CLI TUI mode: use prompt_toolkit widget instead of raw spinner
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# (works in both streaming and non-streaming modes)
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agent.thinking_callback(f"{face} {verb}...")
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elif not agent._has_stream_consumers() and agent._should_start_quiet_spinner():
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# Raw KawaiiSpinner only when no streaming consumers and the
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# spinner output has a safe sink.
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spinner_type = random.choice(['brain', 'sparkle', 'pulse', 'moon', 'star'])
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thinking_spinner = KawaiiSpinner(f"{face} {verb}...", spinner_type=spinner_type, print_fn=agent._print_fn)
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thinking_spinner.start()
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# Log request details if verbose
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if agent.verbose_logging:
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logging.debug(f"API Request - Model: {agent.model}, Messages: {len(messages)}, Tools: {len(agent.tools) if agent.tools else 0}")
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logging.debug(f"Last message role: {messages[-1]['role'] if messages else 'none'}")
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logging.debug(f"Total message size: ~{approx_tokens:,} tokens")
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return ApiCallAnnouncement(action="fallthrough", thinking_spinner=thinking_spinner)
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@dataclass
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class IterationStart:
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"""``action``: ``"fallthrough"`` (run the iteration) or ``"break"`` (turn ends: interrupt,
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review input budget or iteration budget exhausted — ``_turn_exit_reason`` set)."""
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action: str
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original_user_message: Any
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api_call_count: Any
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interrupted: Any
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_turn_exit_reason: Any
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def begin_iteration(
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agent: Any, *, messages: Any, conversation_history: Any, original_user_message: Any,
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api_call_count: Any, interrupted: Any, _turn_exit_reason: Any,
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) -> IterationStart:
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"""Iteration entry in the original order: apply a pending redirect, reset the checkpoint
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dedup, then the interrupt / review-budget / iteration-budget exits. ``api_call_count`` is
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incremented here (the grace call consumes its flag instead of the budget)."""
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from agent.conversation_loop import (
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_apply_active_turn_redirect, _review_input_budget_exhausted
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)
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def _verdict(action: str) -> IterationStart:
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return IterationStart(
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action=action, original_user_message=original_user_message,
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api_call_count=api_call_count, interrupted=interrupted,
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_turn_exit_reason=_turn_exit_reason,
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)
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_redirect_text = agent._drain_pending_redirect()
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if _redirect_text:
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_apply_active_turn_redirect(agent, messages, _redirect_text)
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if isinstance(original_user_message, str):
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original_user_message = (
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f"{original_user_message}\n\n" f"User correction during the turn: {_redirect_text}"
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)
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agent._persist_session(messages, conversation_history)
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# Reset per-turn checkpoint dedup so each iteration can take one snapshot.
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agent._checkpoint_mgr.new_turn()
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if agent._interrupt_requested:
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interrupted = True
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_issuer = interrupt_issuer(agent)
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_turn_exit_reason = f"interrupted_by_system({_issuer})" if _issuer else "interrupted_by_user"
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if not agent.quiet_mode:
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agent._safe_print("\n⚡ Breaking out of tool loop due to interrupt...")
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return _verdict("break")
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# Aggregate input budget for detached auxiliary forks bounds the whole review, not
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# each request; checked between iterations so the crossing request's writes landed.
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if _review_input_budget_exhausted(agent):
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_turn_exit_reason = "review_input_budget_exhausted"
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if not agent.quiet_mode:
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agent._safe_print(
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f"\n⏹️ Review input budget exhausted "
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f"({int(agent.session_input_tokens):,} tokens) — stopping "
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f"the review tool loop before the next provider call.", diagnostic=True,
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)
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return _verdict("break")
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api_call_count += 1
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agent._api_call_count = api_call_count
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agent._touch_activity(f"starting API call #{api_call_count}")
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# Grace call: budget exhausted but the model gets one more call. Consume the
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# flag so the loop exits after this iteration regardless of outcome.
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if agent._budget_grace_call:
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# Exhaustion retains one toolless grace call regardless of whether an opt-in
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# checkpoint was emitted; the warning never extends the hard budget.
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agent._budget_grace_call = False
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elif not agent.iteration_budget.consume():
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_turn_exit_reason = "budget_exhausted"
|
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if not agent.quiet_mode:
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agent._safe_print(f"\n⚠️ Iteration budget exhausted ({agent.iteration_budget.used}/{agent.iteration_budget.max_total} iterations used)", diagnostic=True)
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return _verdict("break")
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return _verdict("fallthrough")
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|
||
@dataclass
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class RetryRestartVerdict:
|
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"""``action``: ``"fallthrough"`` (a response is ready — process it), ``"continue"``
|
||
(a restart flag re-issues the iteration: redirect / compressed / rebuilt-for-fallback /
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length continuation) or ``"break"`` (turn ends: interrupted, non-actionable compaction
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||
handoff, or every retry exhausted without a response)."""
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||
|
||
action: str
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||
current_turn_user_idx: Any
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||
final_response: Any
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||
retry_count: Any
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||
restart_count: Any
|
||
api_call_count: Any
|
||
_preflight_compression_blocked: Any
|
||
_turn_exit_reason: Any
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||
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||
|
||
def apply_retry_restarts(
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agent: Any, *, _retry: Any, response: Any, interrupted: Any, messages: Any,
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conversation_history: Any, user_message: Any, api_kwargs: Any, current_turn_user_idx: Any,
|
||
final_response: Any, retry_count: Any, max_retries: Any, api_call_count: Any,
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||
restart_count: Any, length_continue_retries: Any,
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||
_preflight_compression_blocked: Any, _turn_exit_reason: Any,
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||
) -> RetryRestartVerdict:
|
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"""Consume the ``TurnRetryState`` restart flags after the retry loop, in the original
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priority order. Refunds the iteration budget/count for restarts that produced no valid
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assistant item; ``restart_with_rebuilt_messages`` is the single consumer that clears
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``_preflight_compression_blocked`` so the fallback gets a fresh preflight (#84733).
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|
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The two refunding restart paths (redirect and rebuilt-for-fallback) are bounded by
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``max_retries`` via ``restart_count`` (a per-turn accumulator) so a runaway
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interrupt/redirect that keeps re-arming a restart flag cannot refund the budget
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forever and hold the turn lease indefinitely."""
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|
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from agent.conversation_loop import (
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_HANDOFF_SKIP_FINAL_RESPONSE, _should_skip_model_call_for_reference_handoff
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||
)
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|
||
def _verdict(action: str) -> RetryRestartVerdict:
|
||
return RetryRestartVerdict(
|
||
action=action, current_turn_user_idx=current_turn_user_idx,
|
||
final_response=final_response, retry_count=retry_count, restart_count=restart_count,
|
||
api_call_count=api_call_count,
|
||
_preflight_compression_blocked=_preflight_compression_blocked,
|
||
_turn_exit_reason=_turn_exit_reason,
|
||
)
|
||
|
||
if _retry.restart_with_redirected_messages:
|
||
restart_count += 1
|
||
if restart_count > max_retries:
|
||
# A redirect/interrupt keeps re-arming this flag: stop refunding the iteration
|
||
# budget and re-issuing the same logical iteration, or a runaway turn holds the
|
||
# turn lease indefinitely (redirect restarts previously had no bound).
|
||
_turn_exit_reason = "redirect_restart_limit_exceeded"
|
||
logger.warning(
|
||
"Redirected-message restart limit (%s) exceeded; ending turn instead of "
|
||
"refunding the iteration budget indefinitely.",
|
||
max_retries,
|
||
)
|
||
# The correction that tripped the cap was never applied; hand it back as the
|
||
# next user turn (result["pending_steer"]) instead of losing it to clear_interrupt().
|
||
_unapplied = agent._drain_pending_redirect()
|
||
if _unapplied:
|
||
agent.steer(_unapplied)
|
||
return _verdict("break")
|
||
# Cancelled request produced no valid assistant item: reuse the same logical
|
||
# iteration after the outer loop appends partial context + correction.
|
||
api_call_count -= 1
|
||
agent.iteration_budget.refund()
|
||
_retry.restart_with_redirected_messages = False
|
||
return _verdict("continue")
|
||
|
||
if interrupted:
|
||
_issuer = interrupt_issuer(agent)
|
||
_turn_exit_reason = (
|
||
f"interrupted_during_api_call({_issuer})" if _issuer else "interrupted_during_api_call"
|
||
)
|
||
return _verdict("break")
|
||
|
||
if _retry.restart_with_compressed_messages:
|
||
api_call_count -= 1
|
||
agent.iteration_budget.refund()
|
||
# Compression restarts count toward the retry limit so a compression that
|
||
# shrinks messages but not enough can't loop forever.
|
||
retry_count += 1
|
||
_retry.restart_with_compressed_messages = False
|
||
if _should_skip_model_call_for_reference_handoff(
|
||
# Compression rebuilt the list (tail messages are fresh compaction copies), so the
|
||
# pre-compression index of this turn's user message is stale. Re-anchor both index trackers: the
|
||
# api_content stamp below, the loop's injection site, and the flush's persist-override row
|
||
# (#48677) must all target the surviving dict, not a stale position. Exact-content match first
|
||
# so a todo-snapshot user message appended after the tail can't steal the anchor.
|
||
messages, user_message
|
||
):
|
||
logger.info(
|
||
"Skipping compressed-restart model call: reference-only "
|
||
"handoff would be the sole active user turn (#80622)"
|
||
)
|
||
if not final_response:
|
||
final_response = _HANDOFF_SKIP_FINAL_RESPONSE
|
||
_turn_exit_reason = "compaction_handoff_not_actionable"
|
||
return _verdict("break")
|
||
# In-loop compression rebuilt `messages`; re-anchor the current-turn index
|
||
# like the prologue, AFTER the handoff guard (it may re-append this turn's
|
||
# ask). A stale anchor injects prefetch into a historical row.
|
||
current_turn_user_idx = _reanchor(agent, messages, user_message)
|
||
return _verdict("continue")
|
||
|
||
if _retry.restart_with_rebuilt_messages:
|
||
restart_count += 1
|
||
if restart_count > max_retries:
|
||
# A stall/failure keeps re-escalating to the fallback chain: stop refunding the
|
||
# iteration budget and re-issuing, or a runaway turn holds the turn lease
|
||
# indefinitely (rebuilt restarts previously had no bound).
|
||
_turn_exit_reason = "rebuilt_restart_limit_exceeded"
|
||
logger.warning(
|
||
"Rebuilt-message restart limit (%s) exceeded; ending turn instead of "
|
||
"refunding the iteration budget indefinitely.",
|
||
max_retries,
|
||
)
|
||
return _verdict("break")
|
||
# A stall/failure escalated to the fallback chain: re-issue against the
|
||
# active fallback provider, refunding budget/count for the stalled attempt.
|
||
api_call_count -= 1
|
||
agent.iteration_budget.refund()
|
||
_retry.restart_with_rebuilt_messages = False
|
||
# Failover shrank the compressor window: clear the preflight block so
|
||
# preflight re-runs before the first fallback call (single consumer).
|
||
_preflight_compression_blocked = False
|
||
return _verdict("continue")
|
||
|
||
if _retry.restart_with_length_continuation:
|
||
# Boost output budget per retry: 2×, 4×, 8×, 16× base, capped at 32 768, via
|
||
# _ephemeral_max_output_tokens. Keep a larger original provider/model
|
||
# default as the floor so retries never downshift.
|
||
_boost = (agent.max_tokens or 4096) * (2 ** length_continue_retries)
|
||
_requested_cap = agent._requested_output_cap_from_api_kwargs(api_kwargs)
|
||
if _requested_cap is not None:
|
||
_boost = max(_boost, _requested_cap)
|
||
_boost_cap = max(32768, _requested_cap or 0)
|
||
agent._ephemeral_max_output_tokens = min(_boost, _boost_cap)
|
||
return _verdict("continue")
|
||
|
||
# All retries may exhaust with `response` still None; break out cleanly.
|
||
if response is None:
|
||
_turn_exit_reason = "all_retries_exhausted_no_response"
|
||
agent._emit_diagnostic_status("❌ The model provider didn't answer after all retries. Send /retry, or switch models with /model.")
|
||
agent._persist_session(messages, conversation_history)
|
||
return _verdict("break")
|
||
return _verdict("fallthrough")
|