Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
@@ -99,3 +99,17 @@ def uses_chat_completions_tool_schema(model_name: str, settings: Settings) -> bo
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if model.startswith(("litellm/", "any-llm/")):
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return True
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return bool(settings.llm.api_base)
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def model_supports_reasoning(model_name: str) -> bool:
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import litellm
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name = model_name.strip().lower()
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for prefix in ("litellm/", "any-llm/"):
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if name.startswith(prefix):
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name = name[len(prefix) :]
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break
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entry = litellm.model_cost.get(name)
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if entry is None and "/" in name:
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entry = litellm.model_cost.get(name.rsplit("/", 1)[1])
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return bool(entry and entry.get("supports_reasoning"))
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@@ -8,7 +8,7 @@ from typing import TYPE_CHECKING, Any
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from agents.model_settings import ModelSettings
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from openai.types.shared import Reasoning
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from strix.config.models import DEFAULT_MODEL_RETRY
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from strix.config.models import DEFAULT_MODEL_RETRY, model_supports_reasoning
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if TYPE_CHECKING:
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@@ -108,13 +108,19 @@ def build_scope_context(scan_config: dict[str, Any]) -> dict[str, Any]:
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def make_model_settings(
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reasoning_effort: ReasoningEffort | None,
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*,
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model_name: str,
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) -> ModelSettings:
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# Anthropic + DeepSeek thinking reject ``tool_choice="required"`` outright
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# when reasoning is enabled; OpenAI o-series accepts both but doesn't need
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# the safety net. When reasoning is on we let the model self-select tools
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# and rely on the system prompt + the ``_finish_tool_use_behavior`` callback
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# to keep the loop converging on a lifecycle tool.
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use_reasoning = reasoning_effort is not None and reasoning_effort != "none"
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use_reasoning = (
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reasoning_effort is not None
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and reasoning_effort != "none"
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and model_supports_reasoning(model_name)
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)
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model_settings = ModelSettings(
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parallel_tool_calls=False,
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tool_choice=None if use_reasoning else "required",
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@@ -153,7 +153,10 @@ async def run_strix_scan(
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is_whitebox = any(t.get("type") == "local_code" for t in targets)
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skills = list(scan_config.get("skills") or [])
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root_task = build_root_task(scan_config)
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model_settings = make_model_settings(settings.llm.reasoning_effort)
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model_settings = make_model_settings(
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settings.llm.reasoning_effort,
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model_name=resolved_model,
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)
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run_config = RunConfig(
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model=resolved_model,
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model_settings=model_settings,
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