Treat MiniMax M2 thinking as always on

unstract/sdk1/src/unstract/sdk1/adapters/base1.py

@@ -565,6 +565,35 @@ def _minimax_context_window(model_id: str) -> int | None:
     return None
 
 
+def _normalize_minimax_thinking(
+    adapter_metadata: dict[str, "Any"], model_id: str
+) -> None:
+    is_m2_model = _is_minimax_m2_model(model_id)
+    if "enable_thinking" in adapter_metadata:
+        enable_thinking = adapter_metadata.pop("enable_thinking")
+        if not isinstance(enable_thinking, bool):
+            raise ValueError("enable_thinking must be a boolean.")
+        if is_m2_model and not enable_thinking:
+            raise ValueError(f"{model_id} does not support disabling thinking.")
+        if not is_m2_model:
+            adapter_metadata["thinking"] = {
+                "type": "adaptive" if enable_thinking else "disabled"
+            }
+
+    thinking = adapter_metadata.get("thinking")
+    if thinking is None:
+        return
+    if is_m2_model:
+        # M2.x always thinks; the provider accepts this parameter but ignores it.
+        adapter_metadata.pop("thinking")
+        return
+    if not isinstance(thinking, dict) or thinking.get("type") not in {
+        "adaptive",
+        "disabled",
+    }:
+        raise ValueError("thinking.type must be adaptive or disabled.")
+
+
 class NvidiaBuildLLMParameters(OpenAICompatibleLLMParameters):
     """OpenAI-compatible adapter for NVIDIA's hosted models (build.nvidia.com)."""
 
@@ -601,26 +630,7 @@ def validate(adapter_metadata: dict[str, "Any"]) -> dict[str, "Any"]:
         if service_tier not in {None, "standard", "priority"}:
             raise ValueError("service_tier must be standard or priority.")
 
-        if "enable_thinking" in adapter_metadata:
-            enable_thinking = adapter_metadata.pop("enable_thinking")
-            if not isinstance(enable_thinking, bool):
-                raise ValueError("enable_thinking must be a boolean.")
-            adapter_metadata["thinking"] = {
-                "type": "adaptive" if enable_thinking else "disabled"
-            }
-
-        thinking = adapter_metadata.get("thinking")
-        if thinking is None and _is_minimax_m2_model(model_id):
-            thinking = {"type": "adaptive"}
-            adapter_metadata["thinking"] = thinking
-        if thinking is not None:
-            if not isinstance(thinking, dict) or thinking.get("type") not in {
-                "adaptive",
-                "disabled",
-            }:
-                raise ValueError("thinking.type must be adaptive or disabled.")
-            if _is_minimax_m2_model(model_id) and thinking["type"] == "disabled":
-                raise ValueError(f"{model_id} does not support disabling thinking.")
+        _normalize_minimax_thinking(adapter_metadata, model_id)
 
         validated = MiniMaxLLMParameters(**adapter_metadata).model_dump()
         validated["cost_model"] = f"{_MINIMAX_PROVIDER_PREFIX}{model_id}"

unstract/sdk1/src/unstract/sdk1/adapters/llm1/static/minimax.json

@@ -73,7 +73,7 @@
     "enable_thinking": {
       "type": "boolean",
       "title": "Enable Thinking",
-      "description": "Override the protocol default for MiniMax-M3: OpenAI-compatible requests default to adaptive thinking, while Anthropic-compatible requests default to disabled thinking. MiniMax-M2.x models always keep thinking enabled. See [MiniMax API docs](https://platform.minimax.io/docs/api-reference/text-openai-api)."
+      "description": "Override the protocol default for MiniMax-M3: OpenAI-compatible requests default to adaptive thinking, while Anthropic-compatible requests default to disabled thinking. MiniMax-M2.x models use always-on thinking and only accept this setting as true. See [MiniMax API docs](https://platform.minimax.io/docs/api-reference/text-openai-api)."
     }
   }
 }

unstract/sdk1/tests/test_branded_openai_adapters.py

@@ -186,10 +186,30 @@ def test_minimax_m2_rejects_disabling_thinking() -> None:
         )
 
 
-def test_minimax_m2_defaults_to_adaptive_thinking() -> None:
+def test_minimax_m2_uses_always_on_thinking_without_request_parameter() -> None:
     validated = MiniMaxLLMParameters.validate({"model": "MiniMax-M2.7", "api_key": "k"})
 
-    assert validated["thinking"] == {"type": "adaptive"}
+    assert validated["thinking"] is None
+    assert MiniMaxLLMParameters.validate(dict(validated))["thinking"] is None
+
+    explicitly_enabled = MiniMaxLLMParameters.validate(
+        {"model": "MiniMax-M2.7", "api_key": "k", "enable_thinking": True}
+    )
+    assert explicitly_enabled["thinking"] is None
+
+
+def test_minimax_m2_strips_explicit_thinking_payload() -> None:
+    # The provider accepts a thinking payload for M2.x but ignores it, so drop it
+    # instead of failing a call that works today.
+    validated = MiniMaxLLMParameters.validate(
+        {
+            "model": "MiniMax-M2.7",
+            "api_key": "k",
+            "thinking": {"type": "disabled"},
+        }
+    )
+
+    assert validated["thinking"] is None
 
 
 def test_minimax_m2_thinking_rules_require_model_family_boundary() -> None: