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refactor(agent): drop the orphaned hand-rolled summary kwargs builder

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`_chat_summary_attempt` now builds through `_build_api_kwargs`, leaving
`_iteration_summary_chat_kwargs` (56 lines mirroring the transport by hand)
and its only consumer `AIAgent._resolve_lmstudio_summary_reasoning_effort`
without a caller. The transport already owns every quirk they re-derived
(fixed temperature, LM Studio `reasoning_effort`, portal tags, provider
preferences, pareto router plugin), so there is nothing to keep in sync.
This commit is contained in:
kshitijk4poor
2026-09-14 14:31:40 +00:00
committed by kshitij
parent 419a050427
commit 488f2fc86d
2 changed files with 0 additions and 63 deletions
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58
agent/chat_completion_helpers.py
View File

@@ -2011,64 +2011,6 @@ def _managed_summary_call(agent, api_request_id: str, request, callback, *, retr
)
def _iteration_summary_chat_kwargs(agent, api_messages: list) -> dict:
"""chat.completions.create kwargs for the summary, mirroring ChatCompletionsTransport.build_kwargs()."""
try:
from agent.auxiliary_client import _fixed_temperature_for_model, OMIT_TEMPERATURE as _OMIT_TEMP
except Exception:
_fixed_temperature_for_model = _OMIT_TEMP = None
raw_temp = _fixed_temperature_for_model(agent.model, agent.base_url) if _fixed_temperature_for_model is not None else None
temperature = None if raw_temp is _OMIT_TEMP else raw_temp
provider_name = (agent.provider or "").strip().lower()
# LM Studio uses top-level `reasoning_effort` (not extra_body.reasoning).
is_lmstudio = provider_name == "lmstudio" and agent._supports_reasoning_extra_body()
lm_reasoning_effort = agent._resolve_lmstudio_summary_reasoning_effort() if is_lmstudio else None
extra_body = {}
if not is_lmstudio and agent._supports_reasoning_extra_body():
extra_body["reasoning"] = agent.reasoning_config if agent.reasoning_config is not None else {"enabled": True, "effort": "medium"}
if "nousresearch" in agent._base_url_lower:
from agent.portal_tags import nous_portal_tags
extra_body["tags"] = nous_portal_tags()
summary_kwargs = {"model": agent.model, "messages": api_messages}
if temperature is not None:
summary_kwargs["temperature"] = temperature
if agent.max_tokens is not None:
summary_kwargs.update(agent._max_tokens_param(agent.max_tokens))
if lm_reasoning_effort is not None:
summary_kwargs["reasoning_effort"] = lm_reasoning_effort
# Merge the profile's canonical body even when routing is unset (e.g. required Portal tags).
provider_preferences = _provider_preferences_for_agent(agent)
profile_extra_body = {}
with contextlib.suppress(Exception):
from providers import get_provider_profile
provider_profile = get_provider_profile(agent.provider)
if provider_profile is not None:
profile_extra_body = provider_profile.build_extra_body(
session_id=getattr(agent, "session_id", None), provider_preferences=provider_preferences or None,
model=agent.model, base_url=agent.base_url, reasoning_config=agent.reasoning_config)
if profile_extra_body:
extra_body.update(profile_extra_body)
def _is_openrouter() -> bool:
return provider_name == "openrouter" or agent._is_openrouter_url()
if provider_preferences and "provider" not in profile_extra_body and _is_openrouter():
extra_body["provider"] = provider_preferences
# Pareto Code router plugin — model-gated, same shape as the main-loop emission.
_score = agent.openrouter_min_coding_score
if agent.model == "openrouter/pareto-code" and _is_openrouter() and _score is not None and _score != "":
with contextlib.suppress(TypeError, ValueError):
_ps = float(_score)
if 0.0 <= _ps <= 1.0:
extra_body["plugins"] = [{"id": "pareto-router", "min_coding_score": _ps}]
if extra_body:
summary_kwargs["extra_body"] = extra_body
return summary_kwargs
def _summary_text_with_scrub(agent, response, **normalize_kwargs) -> str:
"""Keep summary text while discarding any tool calls emitted alongside it.

5
agent/reasoning_params.py
View File

@@ -98,11 +98,6 @@ class ReasoningParamsMixin:
return False
return bool(_cached_probe(self, "_ollama_thinking_cache", ollama_model_supports_thinking, None, lambda v: v is not None))
def _resolve_lmstudio_summary_reasoning_effort(self) -> Optional[str]:
"""Safe top-level ``reasoning_effort`` for LM Studio; shared with the iteration-limit summary call."""
from agent.lmstudio_reasoning import resolve_lmstudio_effort
return resolve_lmstudio_effort(self.reasoning_config, self._lmstudio_reasoning_options_cached())
def _github_models_reasoning_extra_body(self) -> dict | None:
"""Format reasoning payload for GitHub Models/OpenAI-compatible routes."""
try: