fix(hosted_vllm): normalize custom tools for chat completions (#25763)

* fix(hosted_vllm): normalize custom tools for chat completions

Convert custom tool definitions into OpenAI function tools before forwarding hosted_vllm chat requests to avoid provider-side validation failures. Add a regression test and include a local curl verification screenshot.

Made-with: Cursor

* Fix black issue

* Fix hosted vllm custom tool schema fallback

* fix black

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>

litellm/llms/hosted_vllm/chat/transformation.py

@@ -2,7 +2,18 @@
 Translate from OpenAI's `/v1/chat/completions` to VLLM's `/v1/chat/completions`
 """
 
-from typing import Any, Coroutine, List, Literal, Optional, Tuple, Union, cast, overload
+from typing import (
+    Any,
+    Coroutine,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Tuple,
+    Union,
+    cast,
+    overload,
+)
 
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     _get_image_mime_type_from_url,
@@ -21,6 +32,61 @@ from ...openai.chat.gpt_transformation import OpenAIGPTConfig
 
 
 class HostedVLLMChatConfig(OpenAIGPTConfig):
+    def _convert_custom_tools_to_function_tools(
+        self, tools: List[Dict[str, Any]]
+    ) -> List[Dict[str, Any]]:
+        """
+        vLLM chat completions currently accepts only OpenAI function tools.
+        Convert custom tools into function tools so request validation does not fail.
+        """
+        converted_tools: List[Dict[str, Any]] = []
+        for idx, tool in enumerate(tools):
+            if not isinstance(tool, dict):
+                converted_tools.append(tool)
+                continue
+
+            if tool.get("type") != "custom":
+                converted_tools.append(tool)
+                continue
+
+            custom_tool = tool.get("custom", {})
+            if not isinstance(custom_tool, dict):
+                custom_tool = {}
+
+            tool_name = (
+                custom_tool.get("name") or tool.get("name") or f"custom_tool_{idx}"
+            )
+            tool_description = custom_tool.get("description") or tool.get("description")
+            tool_parameters = custom_tool.get("input_schema") or tool.get(
+                "input_schema"
+            )
+
+            if not isinstance(tool_parameters, dict):
+                tool_parameters = {
+                    "type": "object",
+                    "properties": {
+                        "input": {
+                            "type": "string",
+                            "description": "Raw tool input payload.",
+                        }
+                    },
+                    "required": ["input"],
+                }
+
+            function_tool: Dict[str, Any] = {
+                "type": "function",
+                "function": {
+                    "name": str(tool_name),
+                    "parameters": tool_parameters,
+                },
+            }
+            if isinstance(tool_description, str):
+                function_tool["function"]["description"] = tool_description
+
+            converted_tools.append(function_tool)
+
+        return converted_tools
+
     def get_supported_openai_params(self, model: str) -> List[str]:
         params = super().get_supported_openai_params(model)
         params.extend(["reasoning_effort", "thinking"])
@@ -39,6 +105,8 @@ class HostedVLLMChatConfig(OpenAIGPTConfig):
             _tools = _remove_additional_properties(_tools)
             # remove 'strict' from tools
             _tools = _remove_strict_from_schema(_tools)
+            if isinstance(_tools, list):
+                _tools = self._convert_custom_tools_to_function_tools(_tools)
         if _tools is not None:
             non_default_params["tools"] = _tools
 

tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py

@@ -257,3 +257,65 @@ def test_hosted_vllm_thinking_blocks_with_list_content():
     }
     assert assistant_msg["content"][2] == {"type": "text", "text": "Response text"}
     assert "thinking_blocks" not in assistant_msg
+
+
+def test_hosted_vllm_custom_tools_are_converted_to_function_tools():
+    config = HostedVLLMChatConfig()
+    optional_params = config.map_openai_params(
+        non_default_params={
+            "tools": [
+                {
+                    "type": "custom",
+                    "custom": {
+                        "name": "apply_patch",
+                        "description": "Apply text patch",
+                        "format": {
+                            "type": "grammar",
+                            "grammar": {"syntax": "lark", "definition": "start: /.*/"},
+                        },
+                    },
+                }
+            ]
+        },
+        optional_params={},
+        model="hosted_vllm/gpt-oss-120b",
+        drop_params=False,
+    )
+
+    tools = optional_params["tools"]
+    assert len(tools) == 1
+    assert tools[0]["type"] == "function"
+    assert tools[0]["function"]["name"] == "apply_patch"
+    assert tools[0]["function"]["description"] == "Apply text patch"
+    assert tools[0]["function"]["parameters"]["type"] == "object"
+    assert "input" in tools[0]["function"]["parameters"]["properties"]
+
+
+def test_hosted_vllm_custom_tools_use_top_level_input_schema():
+    config = HostedVLLMChatConfig()
+    input_schema = {
+        "type": "object",
+        "properties": {"query": {"type": "string"}},
+        "required": ["query"],
+    }
+    optional_params = config.map_openai_params(
+        non_default_params={
+            "tools": [
+                {
+                    "type": "custom",
+                    "name": "search",
+                    "description": "Search docs",
+                    "input_schema": input_schema,
+                }
+            ]
+        },
+        optional_params={},
+        model="hosted_vllm/gpt-oss-120b",
+        drop_params=False,
+    )
+
+    tools = optional_params["tools"]
+    assert len(tools) == 1
+    assert tools[0]["function"]["name"] == "search"
+    assert tools[0]["function"]["description"] == "Search docs"
+    assert tools[0]["function"]["parameters"] == input_schema