fix(snowflake): transform string tool_choice to object format (#23318)

Snowflake's Cortex LLM API (like Anthropic) requires tool_choice as an
object with a "type" field, not as a bare string. Passing tool_choice="auto"
(or "required"/"none") results in error 390142 "invalid payload".

This fix transforms OpenAI string tool_choice values to the Snowflake
object format:
- "auto"     -> {"type": "auto"}
- "required" -> {"type": "any"}  (Snowflake/Anthropic convention)
- "none"     -> {"type": "none"}

The dict-to-dict transformation for specific function tool choices
({"type": "function", "function": {"name": "..."}} -> {"type": "tool",
"name": [...]}) remains unchanged.

Fixes #23284

Co-authored-by: gambletan <tan@echooo.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>

litellm/llms/snowflake/chat/transformation.py

@@ -219,17 +219,32 @@ class SnowflakeConfig(SnowflakeBaseConfig, OpenAIGPTConfig):
             tool_choice: Tool choice in OpenAI format (str or dict)
 
         Returns:
-            Tool choice in Snowflake format (always an object)
+            Tool choice in Snowflake format (always an object, never a string)
 
-        OpenAI format (string): "auto", "required", "none"
-        OpenAI format (object): {"type": "function", "function": {"name": "get_weather"}}
+        OpenAI format (string):
+        "auto", "required", "none"
 
-        Snowflake format (string values become objects): {"type": "auto"}
-        Snowflake format (specific tool): {"type": "tool", "name": ["get_weather"]}
+        OpenAI format (dict):
+        {"type": "function", "function": {"name": "get_weather"}}
+
+        Snowflake format:
+        {"type": "auto"} / {"type": "any"} / {"type": "none"}
+        {"type": "tool", "name": ["get_weather"]}
+
+        Snowflake's API (like Anthropic) requires tool_choice as an object
+        with a "type" field, not as a bare string.
         """
         if isinstance(tool_choice, str):
-            # Snowflake requires object format: {"type": "auto"} not string "auto"
-            return {"type": tool_choice}
+            # Snowflake requires object format, not string.
+            # Map OpenAI string values to Snowflake object format.
+            # "required" maps to "any" (Snowflake/Anthropic convention).
+            _type_map = {
+                "auto": "auto",
+                "required": "any",
+                "none": "none",
+            }
+            mapped_type = _type_map.get(tool_choice, tool_choice)
+            return {"type": mapped_type}
 
         if isinstance(tool_choice, dict):
             if tool_choice.get("type") == "function":

tests/test_litellm/llms/snowflake/chat/test_snowflake_chat_transformation.py

@@ -107,12 +107,19 @@ class TestSnowflakeToolTransformation:
         """
         Test that string tool_choice values are transformed to Snowflake object format.
 
-        Snowflake requires tool_choice to be an object, not a string.
-        Ref: https://docs.snowflake.com/en/developer-guide/snowflake-rest-api/reference/cortex-inference#post--api-v2-cortex-inference-complete-req-body-schema
+        Snowflake's API (like Anthropic) requires tool_choice as an object
+        with a "type" field, not as a bare string. OpenAI's "required" maps
+        to Snowflake's "any".
         """
         config = SnowflakeConfig()
 
-        for value in ["auto", "required", "none"]:
+        expected_mappings = {
+            "auto": {"type": "auto"},
+            "required": {"type": "any"},
+            "none": {"type": "none"},
+        }
+
+        for value, expected in expected_mappings.items():
             optional_params = {"tool_choice": value}
 
             transformed_request = config.transform_request(
@@ -123,8 +130,10 @@ class TestSnowflakeToolTransformation:
                 headers={},
             )
 
-            # Snowflake requires object format: {"type": "auto"} not string "auto"
-            assert transformed_request["tool_choice"] == {"type": value}
+            assert transformed_request["tool_choice"] == expected, (
+                f"tool_choice='{value}' should be transformed to {expected}, "
+                f"got {transformed_request['tool_choice']}"
+            )
 
     def test_transform_response_with_tool_calls(self):
         """