Merge branch 'main' into fix/tool-call-result-order-2943
This commit is contained in:
layla
+149
-2
@@ -4,6 +4,7 @@ from __future__ import annotations
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import asyncio
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from dataclasses import dataclass, field
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import inspect
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from pathlib import Path
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from typing import Any
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@@ -34,6 +35,8 @@ _DEFAULT_ERROR_MESSAGE = "Sorry, I encountered an error calling the AI model."
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_PERSISTED_MODEL_ERROR_PLACEHOLDER = "[Assistant reply unavailable due to model error.]"
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_MAX_EMPTY_RETRIES = 2
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_MAX_LENGTH_RECOVERIES = 3
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_MAX_INJECTIONS_PER_TURN = 3
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_MAX_INJECTION_CYCLES = 5
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_SNIP_SAFETY_BUFFER = 1024
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_MICROCOMPACT_KEEP_RECENT = 10
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_MICROCOMPACT_MIN_CHARS = 500
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@@ -42,6 +45,9 @@ _COMPACTABLE_TOOLS = frozenset({
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"web_search", "web_fetch", "list_dir",
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})
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_BACKFILL_CONTENT = "[Tool result unavailable — call was interrupted or lost]"
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@dataclass(slots=True)
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class AgentRunSpec:
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"""Configuration for a single agent execution."""
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@@ -66,6 +72,7 @@ class AgentRunSpec:
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provider_retry_mode: str = "standard"
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progress_callback: Any | None = None
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checkpoint_callback: Any | None = None
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injection_callback: Any | None = None
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@dataclass(slots=True)
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@@ -79,6 +86,7 @@ class AgentRunResult:
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stop_reason: str = "completed"
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error: str | None = None
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tool_events: list[dict[str, str]] = field(default_factory=list)
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had_injections: bool = False
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class AgentRunner:
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@@ -87,6 +95,90 @@ class AgentRunner:
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def __init__(self, provider: LLMProvider):
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self.provider = provider
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@staticmethod
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def _merge_message_content(left: Any, right: Any) -> str | list[dict[str, Any]]:
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if isinstance(left, str) and isinstance(right, str):
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return f"{left}\n\n{right}" if left else right
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def _to_blocks(value: Any) -> list[dict[str, Any]]:
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if isinstance(value, list):
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return [
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item if isinstance(item, dict) else {"type": "text", "text": str(item)}
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for item in value
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]
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if value is None:
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return []
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return [{"type": "text", "text": str(value)}]
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return _to_blocks(left) + _to_blocks(right)
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@classmethod
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def _append_injected_messages(
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cls,
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messages: list[dict[str, Any]],
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injections: list[dict[str, Any]],
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) -> None:
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"""Append injected user messages while preserving role alternation."""
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for injection in injections:
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if (
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messages
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and injection.get("role") == "user"
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and messages[-1].get("role") == "user"
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):
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merged = dict(messages[-1])
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merged["content"] = cls._merge_message_content(
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merged.get("content"),
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injection.get("content"),
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)
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messages[-1] = merged
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continue
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messages.append(injection)
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async def _drain_injections(self, spec: AgentRunSpec) -> list[dict[str, Any]]:
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"""Drain pending user messages via the injection callback.
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Returns normalized user messages (capped by
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``_MAX_INJECTIONS_PER_TURN``), or an empty list when there is
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nothing to inject. Messages beyond the cap are logged so they
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are not silently lost.
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"""
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if spec.injection_callback is None:
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return []
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try:
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signature = inspect.signature(spec.injection_callback)
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accepts_limit = (
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"limit" in signature.parameters
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or any(
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parameter.kind is inspect.Parameter.VAR_KEYWORD
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for parameter in signature.parameters.values()
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)
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)
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if accepts_limit:
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items = await spec.injection_callback(limit=_MAX_INJECTIONS_PER_TURN)
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else:
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items = await spec.injection_callback()
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except Exception:
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logger.exception("injection_callback failed")
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return []
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if not items:
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return []
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injected_messages: list[dict[str, Any]] = []
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for item in items:
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if isinstance(item, dict) and item.get("role") == "user" and "content" in item:
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injected_messages.append(item)
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continue
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text = getattr(item, "content", str(item))
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if text.strip():
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injected_messages.append({"role": "user", "content": text})
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if len(injected_messages) > _MAX_INJECTIONS_PER_TURN:
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dropped = len(injected_messages) - _MAX_INJECTIONS_PER_TURN
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logger.warning(
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"Injection callback returned {} messages, capping to {} ({} dropped)",
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len(injected_messages), _MAX_INJECTIONS_PER_TURN, dropped,
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)
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injected_messages = injected_messages[:_MAX_INJECTIONS_PER_TURN]
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return injected_messages
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async def run(self, spec: AgentRunSpec) -> AgentRunResult:
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hook = spec.hook or AgentHook()
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messages = list(spec.initial_messages)
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@@ -99,6 +191,8 @@ class AgentRunner:
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external_lookup_counts: dict[str, int] = {}
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empty_content_retries = 0
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length_recovery_count = 0
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had_injections = False
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injection_cycles = 0
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for iteration in range(spec.max_iterations):
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try:
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@@ -207,6 +301,17 @@ class AgentRunner:
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)
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empty_content_retries = 0
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length_recovery_count = 0
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# Checkpoint 1: drain injections after tools, before next LLM call
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if injection_cycles < _MAX_INJECTION_CYCLES:
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injections = await self._drain_injections(spec)
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if injections:
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had_injections = True
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injection_cycles += 1
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self._append_injected_messages(messages, injections)
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logger.info(
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"Injected {} follow-up message(s) after tool execution ({}/{})",
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len(injections), injection_cycles, _MAX_INJECTION_CYCLES,
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)
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await hook.after_iteration(context)
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continue
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@@ -263,8 +368,49 @@ class AgentRunner:
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await hook.after_iteration(context)
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continue
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assistant_message: dict[str, Any] | None = None
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if response.finish_reason != "error" and not is_blank_text(clean):
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assistant_message = build_assistant_message(
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clean,
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reasoning_content=response.reasoning_content,
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thinking_blocks=response.thinking_blocks,
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)
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# Check for mid-turn injections BEFORE signaling stream end.
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# If injections are found we keep the stream alive (resuming=True)
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# so streaming channels don't prematurely finalize the card.
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_injected_after_final = False
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if injection_cycles < _MAX_INJECTION_CYCLES:
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injections = await self._drain_injections(spec)
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if injections:
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had_injections = True
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injection_cycles += 1
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_injected_after_final = True
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if assistant_message is not None:
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messages.append(assistant_message)
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await self._emit_checkpoint(
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spec,
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{
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"phase": "final_response",
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"iteration": iteration,
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"model": spec.model,
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"assistant_message": assistant_message,
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"completed_tool_results": [],
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"pending_tool_calls": [],
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},
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)
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self._append_injected_messages(messages, injections)
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logger.info(
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"Injected {} follow-up message(s) after final response ({}/{})",
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len(injections), injection_cycles, _MAX_INJECTION_CYCLES,
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)
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if hook.wants_streaming():
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await hook.on_stream_end(context, resuming=False)
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await hook.on_stream_end(context, resuming=_injected_after_final)
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if _injected_after_final:
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await hook.after_iteration(context)
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continue
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if response.finish_reason == "error":
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final_content = clean or spec.error_message or _DEFAULT_ERROR_MESSAGE
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@@ -287,7 +433,7 @@ class AgentRunner:
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await hook.after_iteration(context)
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break
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messages.append(build_assistant_message(
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messages.append(assistant_message or build_assistant_message(
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clean,
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reasoning_content=response.reasoning_content,
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thinking_blocks=response.thinking_blocks,
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@@ -330,6 +476,7 @@ class AgentRunner:
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stop_reason=stop_reason,
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error=error,
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tool_events=tool_events,
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had_injections=had_injections,
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)
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def _build_request_kwargs(
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