From 25674b52f429f8523e43e3b19bff7855f4020645 Mon Sep 17 00:00:00 2001
From: Gabriel Ruel-Fiset <gruel@coveo.com>
Date: Tue, 9 Jun 2026 15:10:05 -0400
Subject: [PATCH] Fix Bedrock reasoning for adaptive-thinking models (Claude
 Opus 4.8)

Models such as Claude Opus 4.8 on Bedrock reject the legacy
"thinking.type=enabled" payload that LiteLLM emits when it converts the
"reasoning_effort" argument, returning:

    "thinking.type.enabled" is not supported for this model. Use
    "thinking.type.adaptive" and "output_config.effort" to control
    thinking behavior.

LiteLLM's model metadata already flags these models with
"supports_adaptive_thinking", but its request conversion still sends the
old shape. Detect that flag and pass the adaptive-thinking API via
extra_args (thinking.type=adaptive + output_config.effort) instead of the
reasoning_effort scalar. All other models keep their existing behavior.
---
 strix/config/models.py | 18 +++++++++++++++++-
 strix/core/inputs.py   | 25 +++++++++++++++++++++----
 2 files changed, 38 insertions(+), 5 deletions(-)

diff --git a/strix/config/models.py b/strix/config/models.py
index f5826433..1f480ba7 100644
--- a/strix/config/models.py
+++ b/strix/config/models.py
@@ -138,7 +138,7 @@ def uses_chat_completions_tool_schema(model_name: str, settings: Settings) -> bo
     return not model_supports_reasoning(model_name)
 
 
-def model_supports_reasoning(model_name: str) -> bool:
+def _model_cost_entry(model_name: str) -> dict[str, object] | None:
     import litellm
 
     name = model_name.strip().lower()
@@ -149,9 +149,25 @@ def model_supports_reasoning(model_name: str) -> bool:
     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_supports_adaptive_thinking(model_name: str) -> bool:
+    """Whether the model uses Anthropic's newer adaptive-thinking API.
+
+    Models like Claude Opus 4.8 reject the legacy ``thinking.type=enabled`` shape
+    that LiteLLM emits when it converts ``reasoning_effort``. They require
+    ``thinking.type=adaptive`` plus ``output_config.effort`` instead.
+    """
+    entry = _model_cost_entry(model_name)
+    return bool(entry and entry.get("supports_adaptive_thinking"))
+
+
 def is_known_openai_bare_model(model_name: str) -> bool:
     import litellm
 
diff --git a/strix/core/inputs.py b/strix/core/inputs.py
index b86daa4c..9bdc4d9a 100644
--- a/strix/core/inputs.py
+++ b/strix/core/inputs.py
@@ -8,7 +8,11 @@ from typing import TYPE_CHECKING, Any
 from agents.model_settings import ModelSettings
 from openai.types.shared import Reasoning
 
-from strix.config.models import DEFAULT_MODEL_RETRY, model_supports_reasoning
+from strix.config.models import (
+    DEFAULT_MODEL_RETRY,
+    model_supports_adaptive_thinking,
+    model_supports_reasoning,
+)
 
 
 if TYPE_CHECKING:
@@ -121,9 +125,22 @@ def make_model_settings(
         and reasoning_effort != "none"
         and model_supports_reasoning(model_name)
     ):
-        model_settings = model_settings.resolve(
-            ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
-        )
+        if model_supports_adaptive_thinking(model_name):
+            # Newer Anthropic models (e.g. Claude Opus 4.8) reject the legacy
+            # ``thinking.type=enabled`` shape that LiteLLM emits from
+            # ``reasoning_effort``. Send the adaptive-thinking API instead.
+            model_settings = model_settings.resolve(
+                ModelSettings(
+                    extra_args={
+                        "thinking": {"type": "adaptive"},
+                        "output_config": {"effort": reasoning_effort},
+                    },
+                ),
+            )
+        else:
+            model_settings = model_settings.resolve(
+                ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
+            )
     return model_settings