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039efe4198
Preserve free text and reasoning-only output in the current generation and retry without intermediate warning rows. Require an explicit response tool call to finish in both API modes, including after provider built-in actions. Keep history metadata, Responses state, tool validation and the consecutive-failure stop intact. Allow core retries when Context Doctor and its prompts are unavailable. Validation: 411 backend tests and 2 Chromium live/replay grouping tests passed; live runtime health check passed.
59 lines
2.2 KiB
Python
59 lines
2.2 KiB
Python
"""Retry model turns cut off by the output token limit with a specific warning."""
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from __future__ import annotations
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import json
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from typing import Any
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from helpers import extract_tools
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from helpers.extension import Extension
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from helpers.print_style import PrintStyle
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class TruncatedResponse(Extension):
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def execute(self, result_data: dict[str, Any] | None = None, **kwargs: Any) -> None:
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if not self.agent or not isinstance(result_data, dict):
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return
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if result_data.get("skip_default_processing"):
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return
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llm_result = result_data.get("llm_result")
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if not getattr(llm_result, "truncated", False):
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return
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function_calls = getattr(llm_result, "function_calls", None)
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response = getattr(llm_result, "response", "")
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if function_calls:
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for call in function_calls:
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arguments = call.raw.get("arguments")
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if isinstance(arguments, str):
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try:
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arguments = json.loads(arguments)
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except ValueError:
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break
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if not isinstance(arguments, dict):
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break
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else:
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return
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elif isinstance(response, str) and extract_tools.extract_tool_request(response):
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return
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elif (
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isinstance(response, str) and not response.strip()
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and getattr(llm_result, "reasoning", "").strip()
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and not getattr(llm_result, "builtin_items", None)
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):
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return # Reasoning-only recovery preserves the emitted thoughts.
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# Name truncation as the cause instead of the generic misformat warning.
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warning = self.agent.read_prompt("fw.msg_output_limit.md")
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warning_message = self.agent.hist_add_warning(message=warning)
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notice = self.agent.read_prompt(
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"fw.msg_output_limit_response.md",
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finish_reason=getattr(llm_result, "finish_reason", ""),
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)
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PrintStyle(font_color="orange", padding=True).print(notice)
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self.agent.context.log.log(
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type="warning",
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content=notice,
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id=warning_message.id,
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)
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result_data["skip_default_processing"] = True
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