From 6378c2a2f3aae6fface3438d319df417f01ad108 Mon Sep 17 00:00:00 2001
From: Ben Browning <bbrownin@redhat.com>
Date: Thu, 1 May 2025 08:47:29 -0400
Subject: [PATCH] fix: resolve BuiltinTools to strings for vllm tool_call
 messages (#2071)

# What does this PR do?

When the result of a ToolCall gets passed back into vLLM for the model
to handle the tool call result (as is often the case in agentic
tool-calling workflows), we forgot to handle the case where BuiltinTool
calls are not string values but instead instances of the BuiltinTool
enum. This fixes that, properly converting those enums to string values
before trying to serialize them into an OpenAI chat completion request
to vLLM.

PR #1931 fixed a bug where we weren't passing these tool calling results
back into vLLM, but as a side-effect it created this serialization bug
when using BuiltinTools.

Closes #2070

## Test Plan

I added a new unit test to the openai_compat unit tests to cover this
scenario, ensured the new test failed before this fix, and all the
existing tests there plus the new one passed with this fix.

```
python -m pytest -s -v tests/unit/providers/utils/inference/test_openai_compat.py
```

Signed-off-by: Ben Browning <bbrownin@redhat.com>
---
 .../utils/inference/openai_compat.py          |  7 ++++-
 .../utils/inference/test_openai_compat.py     | 28 ++++++++++++++++++-
 2 files changed, 33 insertions(+), 2 deletions(-)

diff --git a/llama_stack/providers/utils/inference/openai_compat.py b/llama_stack/providers/utils/inference/openai_compat.py
index e51119b79..1a8d82de2 100644
--- a/llama_stack/providers/utils/inference/openai_compat.py
+++ b/llama_stack/providers/utils/inference/openai_compat.py
@@ -532,12 +532,17 @@ async def convert_message_to_openai_dict(message: Message, download: bool = Fals
     if hasattr(message, "tool_calls") and message.tool_calls:
         result["tool_calls"] = []
         for tc in message.tool_calls:
+            # The tool.tool_name can be a str or a BuiltinTool enum. If
+            # it's the latter, convert to a string.
+            tool_name = tc.tool_name
+            if isinstance(tool_name, BuiltinTool):
+                tool_name = tool_name.value
             result["tool_calls"].append(
                 {
                     "id": tc.call_id,
                     "type": "function",
                     "function": {
-                        "name": tc.tool_name,
+                        "name": tool_name,
                         "arguments": tc.arguments_json if hasattr(tc, "arguments_json") else json.dumps(tc.arguments),
                     },
                 }
diff --git a/tests/unit/providers/utils/inference/test_openai_compat.py b/tests/unit/providers/utils/inference/test_openai_compat.py
index eb02f8203..fda762d7f 100644
--- a/tests/unit/providers/utils/inference/test_openai_compat.py
+++ b/tests/unit/providers/utils/inference/test_openai_compat.py
@@ -8,7 +8,7 @@ import pytest
 
 from llama_stack.apis.common.content_types import TextContentItem
 from llama_stack.apis.inference.inference import CompletionMessage, UserMessage
-from llama_stack.models.llama.datatypes import StopReason, ToolCall
+from llama_stack.models.llama.datatypes import BuiltinTool, StopReason, ToolCall
 from llama_stack.providers.utils.inference.openai_compat import convert_message_to_openai_dict
 
 
@@ -41,3 +41,29 @@ async def test_convert_message_to_openai_dict_with_tool_call():
             {"id": "123", "type": "function", "function": {"name": "test_tool", "arguments": '{"foo": "bar"}'}}
         ],
     }
+
+
+@pytest.mark.asyncio
+async def test_convert_message_to_openai_dict_with_builtin_tool_call():
+    message = CompletionMessage(
+        content="",
+        tool_calls=[
+            ToolCall(
+                call_id="123",
+                tool_name=BuiltinTool.brave_search,
+                arguments_json='{"foo": "bar"}',
+                arguments={"foo": "bar"},
+            )
+        ],
+        stop_reason=StopReason.end_of_turn,
+    )
+
+    openai_dict = await convert_message_to_openai_dict(message)
+
+    assert openai_dict == {
+        "role": "assistant",
+        "content": [{"type": "text", "text": ""}],
+        "tool_calls": [
+            {"id": "123", "type": "function", "function": {"name": "brave_search", "arguments": '{"foo": "bar"}'}}
+        ],
+    }