Strip model-aware branches from LLM configuration

Drop every hand-rolled provider table and per-model gating that had
accumulated in the model-handling layer:

  * normalize_model_name no longer auto-prefixes bare claude-* / gemini-*
    names. Users supply the full <provider>/<model> form. The function
    became literally model_name.strip(), so callers now inline that and
    the function is removed.
  * tool_choice="required" is gone everywhere. Thinking-mode endpoints
    (Anthropic, DeepSeek /beta) reject it; modern reasoning models don't
    need it; non-interactive runs already have
    _append_noninteractive_tool_required_message as the convergence
    backstop. model_supports_reasoning, model_known_to_registry, and
    _model_cost_entry were only used to gate this and follow it out.
  * Reasoning(effort=...) is now attached whenever
    STRIX_REASONING_EFFORT is non-none. litellm.drop_params=True absorbs
    it for non-reasoning models.
  * Warm-up's bare-name OpenAI 401 hint is removed (false-positive prone,
    relied on substring matching).
  * reset_tool_choice on SandboxAgent is no-op now (no tool_choice gets
    set) and is removed.
  * report/dedupe.py was still routing through stock MultiProvider, so
    non-OpenAI configs failed the dedupe LLM pass; switch it to
    StrixProvider.

Verified end-to-end against modern provider strings (openai/gpt-5.4,
anthropic/claude-opus-4-7, deepseek/deepseek-reasoner,
gemini/gemini-2.5-pro, groq/, xai/, mistral/, together_ai/, perplexity/,
openrouter/, litellm/ legacy form, and whitespace-padded input): 18/18
cases route correctly, env vars mirror via litellm.validate_environment,
and ModelSettings carries no tool_choice. mypy strict passes.

strix/agents/factory.py

@@ -395,7 +395,6 @@ def build_strix_agent(
         instructions=instructions,
         tools=tools,
         tool_use_behavior=_finish_tool_use_behavior,
-        reset_tool_choice=interactive,
         model=None,
         capabilities=[
             Filesystem(

strix/config/models.py

@@ -59,12 +59,7 @@ DEFAULT_MODEL_RETRY = ModelRetrySettings(
 
 
 def configure_sdk_model_defaults(settings: Settings) -> None:
-    """Apply Strix config to SDK-native defaults.
+    """Apply Strix config to SDK-native defaults."""
-
-    OpenAI-compatible base URLs are handled by the SDK OpenAI provider.
-    Non-OpenAI providers should use the SDK's native ``litellm/`` or
-    ``any-llm/`` routing, produced by :func:`normalize_model_name`.
-    """
     llm = settings.llm
     set_tracing_disabled(True)
     _configure_litellm_compatibility()
@@ -85,7 +80,7 @@ def _mirror_api_key_to_provider_env(model_name: str | None, api_key: str) -> Non
         return
     import litellm
 
-    name = normalize_model_name(model_name)
+    name = model_name.strip()
     for prefix in ("litellm/", "any-llm/"):
         if name.lower().startswith(prefix):
             name = name[len(prefix) :]
@@ -114,50 +109,9 @@ def _configure_litellm_default(name: str, value: str) -> None:
     setattr(litellm, name, value)
 
 
-def normalize_model_name(model_name: str) -> str:
-    """Normalize friendly Strix model names to SDK-native model ids."""
-    model = model_name.strip()
-    if not model:
-        return model
-
-    if "/" in model:
-        return model
-
-    lower = model.lower()
-    if lower.startswith("claude"):
-        return f"anthropic/{model}"
-    if lower.startswith("gemini"):
-        return f"gemini/{model}"
-
-    return model
-
-
 def uses_chat_completions_tool_schema(model_name: str, settings: Settings) -> bool:
     """Return whether the resolved SDK route can only receive JSON function tools."""
     model = model_name.strip().lower()
     if "/" in model and not model.startswith("openai/"):
         return True
     return bool(settings.llm.api_base)
-
-
-def _model_cost_entry(model_name: str) -> dict[str, object] | None:
-    import litellm
-
-    name = model_name.strip().lower()
-    for prefix in ("litellm/", "any-llm/"):
-        if name.startswith(prefix):
-            name = name[len(prefix) :]
-            break
-    entry = litellm.model_cost.get(name)
-    if entry is None and "/" in name:
-        entry = litellm.model_cost.get(name.rsplit("/", 1)[1])
-    return entry
-
-
-def model_supports_reasoning(model_name: str) -> bool:
-    entry = _model_cost_entry(model_name)
-    return bool(entry and entry.get("supports_reasoning"))
-
-
-def model_known_to_registry(model_name: str) -> bool:
-    return _model_cost_entry(model_name) is not None

strix/core/inputs.py

@@ -8,11 +8,7 @@ from typing import TYPE_CHECKING, Any
 from agents.model_settings import ModelSettings
 from openai.types.shared import Reasoning
 
-from strix.config.models import (
+from strix.config.models import DEFAULT_MODEL_RETRY
-    DEFAULT_MODEL_RETRY,
-    model_known_to_registry,
-    model_supports_reasoning,
-)
 
 
 if TYPE_CHECKING:
@@ -110,30 +106,13 @@ def build_scope_context(scan_config: dict[str, Any]) -> dict[str, Any]:
     }
 
 
-def make_model_settings(
+def make_model_settings(reasoning_effort: ReasoningEffort | None) -> ModelSettings:
-    reasoning_effort: ReasoningEffort | None,
-    *,
-    model_name: str,
-) -> ModelSettings:
-    # Anthropic + DeepSeek thinking reject ``tool_choice="required"`` outright;
-    # when reasoning is enabled we let the model self-select tools and rely on
-    # the system prompt + the ``_finish_tool_use_behavior`` callback to keep
-    # the loop converging. When the user opted into reasoning but the model
-    # is unknown to LiteLLM's registry (e.g. a private DeepSeek SKU, a fresh
-    # release the registry hasn't picked up), drop ``tool_choice`` too —
-    # server-side thinking-mode endpoints reject it and we can't confirm.
-    user_wants_reasoning = reasoning_effort is not None and reasoning_effort != "none"
-    confirmed_reasoning = model_supports_reasoning(model_name)
-    drop_tool_choice = user_wants_reasoning and (
-        confirmed_reasoning or not model_known_to_registry(model_name)
-    )
     model_settings = ModelSettings(
         parallel_tool_calls=False,
-        tool_choice=None if drop_tool_choice else "required",
         retry=DEFAULT_MODEL_RETRY,
         include_usage=True,
     )
-    if user_wants_reasoning and confirmed_reasoning:
+    if reasoning_effort is not None and reasoning_effort != "none":
         model_settings = model_settings.resolve(
             ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
         )

strix/core/runner.py

@@ -17,7 +17,6 @@ from strix.config import load_settings
 from strix.config.models import (
     StrixProvider,
     configure_sdk_model_defaults,
-    normalize_model_name,
     uses_chat_completions_tool_schema,
 )
 from strix.core.agents import AgentCoordinator
@@ -91,7 +90,7 @@ async def run_strix_scan(
 
     settings = load_settings()
     configure_sdk_model_defaults(settings)
-    resolved_model = normalize_model_name(model or settings.llm.model or "")
+    resolved_model = (model or settings.llm.model or "").strip()
     if not resolved_model:
         raise RuntimeError(
             "No LLM model configured. Set STRIX_LLM env or pass model= to run_strix_scan().",
@@ -154,10 +153,7 @@ async def run_strix_scan(
         is_whitebox = any(t.get("type") == "local_code" for t in targets)
         skills = list(scan_config.get("skills") or [])
         root_task = build_root_task(scan_config)
-        model_settings = make_model_settings(
+        model_settings = make_model_settings(settings.llm.reasoning_effort)
-            settings.llm.reasoning_effort,
-            model_name=resolved_model,
-        )
         run_config = RunConfig(
             model=resolved_model,
             model_provider=StrixProvider(),

strix/interface/main.py

@@ -5,7 +5,6 @@ Strix Agent Interface
 
 import argparse
 import asyncio
-import contextlib
 import shutil
 import sys
 from datetime import UTC, datetime
@@ -23,7 +22,7 @@ from strix.config import (
     load_settings,
     persist_current,
 )
-from strix.config.models import StrixProvider, configure_sdk_model_defaults, normalize_model_name
+from strix.config.models import StrixProvider, configure_sdk_model_defaults
 from strix.core.paths import run_dir_for, runtime_state_dir
 from strix.interface.cli import run_cli
 from strix.interface.tui import run_tui
@@ -216,7 +215,7 @@ async def warm_up_llm() -> None:
         configure_sdk_model_defaults(settings)
         llm = settings.llm
 
-        model = StrixProvider().get_model(normalize_model_name(llm.model or ""))
+        model = StrixProvider().get_model((llm.model or "").strip())
         await asyncio.wait_for(
             model.get_response(
                 system_instructions="You are a helpful assistant.",
@@ -232,7 +231,7 @@ async def warm_up_llm() -> None:
             ),
             timeout=llm.timeout,
         )
-        logger.info("LLM warm-up succeeded for model %s", normalize_model_name(llm.model or ""))
+        logger.info("LLM warm-up succeeded for model %s", (llm.model or "").strip())
 
     except Exception as e:
         logger.exception("LLM warm-up failed")
@@ -243,24 +242,6 @@ async def warm_up_llm() -> None:
         error_text.append("Please check your configuration and try again.\n", style="white")
         error_text.append(f"\nError: {e}", style="dim white")
 
-        raw_model = ""
-        resolved = ""
-        with contextlib.suppress(Exception):
-            raw_model = (load_settings().llm.model or "").strip()
-            resolved = normalize_model_name(raw_model)
-        err_lc = str(e).lower()
-        unprefixed = bool(resolved) and "/" not in resolved
-        looks_openai = "platform.openai.com" in err_lc or "openai" in err_lc
-        if unprefixed and looks_openai:
-            error_text.append(
-                f"\n\nHint: '{raw_model}' has no provider prefix, so the SDK "
-                f"routed it through OpenAI by default. For non-OpenAI providers "
-                f"use the '<provider>/<model>' form, e.g. "
-                f"'anthropic/claude-opus-4-7', 'deepseek/deepseek-reasoner', "
-                f"'openai/gpt-5.4'.",
-                style="yellow",
-            )
-
         panel = Panel(
             error_text,
             title="[bold white]STRIX",

strix/report/dedupe.py

@@ -8,14 +8,13 @@ from typing import TYPE_CHECKING, Any
 
 from agents.model_settings import ModelSettings
 from agents.models.interface import ModelTracing
-from agents.models.multi_provider import MultiProvider
 from openai.types.responses import ResponseOutputMessage
 
 from strix.config import load_settings
 from strix.config.models import (
     DEFAULT_MODEL_RETRY,
+    StrixProvider,
     configure_sdk_model_defaults,
-    normalize_model_name,
 )
 from strix.report.state import get_global_report_state
 
@@ -188,8 +187,8 @@ async def check_duplicate(
         )
 
         configure_sdk_model_defaults(settings)
-        resolved_model = normalize_model_name(model_name)
+        resolved_model = model_name.strip()
-        model = MultiProvider().get_model(resolved_model)
+        model = StrixProvider().get_model(resolved_model)
         response = await model.get_response(
             system_instructions=DEDUPE_SYSTEM_PROMPT,
             input=user_msg,