fix(core): add check_api_key method to MiniMaxProvider (#9112)

The MiniMaxProvider class was missing a check_api_key() implementation,
causing /v1/providers/check to return a 500 error when validating
MiniMax API keys. The base Provider class raises NotImplementedError.

This adds check_api_key() using the Anthropic client (since MiniMax uses
an Anthropic-compatible API), following the same pattern as AnthropicProvider.

👾 Generated with [Letta Code](https://letta.com)

Co-authored-by: Letta <noreply@letta.com>

letta/schemas/providers/minimax.py

@@ -1,7 +1,9 @@
 from typing import Literal
 
+import anthropic
 from pydantic import Field
 
+from letta.errors import ErrorCode, LLMAuthenticationError, LLMError
 from letta.log import get_logger
 from letta.schemas.enums import ProviderCategory, ProviderType
 from letta.schemas.llm_config import LLMConfig
@@ -48,6 +50,22 @@ class MiniMaxProvider(Provider):
     api_key: str | None = Field(None, description="API key for the MiniMax API.", deprecated=True)
     base_url: str = Field("https://api.minimax.io/anthropic", description="Base URL for the MiniMax Anthropic-compatible API.")
 
+    async def check_api_key(self):
+        """Check if the API key is valid by making a test request to the MiniMax API."""
+        api_key = await self.api_key_enc.get_plaintext_async() if self.api_key_enc else None
+        if not api_key:
+            raise ValueError("No API key provided")
+
+        try:
+            # Use async Anthropic client pointed at MiniMax's Anthropic-compatible endpoint
+            client = anthropic.AsyncAnthropic(api_key=api_key, base_url=self.base_url)
+            # Use count_tokens as a lightweight check - similar to Anthropic provider
+            await client.messages.count_tokens(model=MODEL_LIST[-1]["name"], messages=[{"role": "user", "content": "a"}])
+        except anthropic.AuthenticationError as e:
+            raise LLMAuthenticationError(message=f"Failed to authenticate with MiniMax: {e}", code=ErrorCode.UNAUTHENTICATED)
+        except Exception as e:
+            raise LLMError(message=f"{e}", code=ErrorCode.INTERNAL_SERVER_ERROR)
+
     def get_default_max_output_tokens(self, model_name: str) -> int:
         """Get the default max output tokens for MiniMax models."""
         # All MiniMax models support 128K output tokens
@@ -73,7 +91,7 @@ class MiniMaxProvider(Provider):
             configs.append(
                 LLMConfig(
                     model=model["name"],
-                    model_endpoint_type="anthropic",
+                    model_endpoint_type="minimax",
                     model_endpoint=self.base_url,
                     context_window=model["context_window"],
                     handle=self.get_handle(model["name"]),