Skip to content

fix: add traces for tool calls and mcp tool listing #3722

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 9, 2025
Merged

fix: add traces for tool calls and mcp tool listing #3722

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 14 additions & 5 deletions llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,7 @@
OpenAIMessageParam,
)
from llama_stack.log import get_logger
from llama_stack.providers.utils.telemetry import tracing

from .types import ChatCompletionContext, ChatCompletionResult
from .utils import convert_chat_choice_to_response_message, is_function_tool_call
Expand Down Expand Up @@ -586,14 +587,22 @@ async def _process_mcp_tool(
never_allowed = mcp_tool.allowed_tools.never

# Call list_mcp_tools
tool_defs = await list_mcp_tools(
endpoint=mcp_tool.server_url,
headers=mcp_tool.headers or {},
)
tool_defs = None
list_id = f"mcp_list_{uuid.uuid4()}"
attributes = {
"server_label": mcp_tool.server_label,
"server_url": mcp_tool.server_url,
"mcp_list_tools_id": list_id,
}
async with tracing.span("list_mcp_tools", attributes):
tool_defs = await list_mcp_tools(
endpoint=mcp_tool.server_url,
headers=mcp_tool.headers or {},
)

# Create the MCP list tools message
mcp_list_message = OpenAIResponseOutputMessageMCPListTools(
id=f"mcp_list_{uuid.uuid4()}",
id=list_id,
server_label=mcp_tool.server_label,
tools=[],
)
Expand Down
40 changes: 26 additions & 14 deletions llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@
from llama_stack.apis.tools import ToolGroups, ToolInvocationResult, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
from llama_stack.log import get_logger
from llama_stack.providers.utils.telemetry import tracing

from .types import ChatCompletionContext, ToolExecutionResult

Expand Down Expand Up @@ -219,12 +220,18 @@ async def _execute_tool(
from llama_stack.providers.utils.tools.mcp import invoke_mcp_tool

mcp_tool = mcp_tool_to_server[function_name]
result = await invoke_mcp_tool(
endpoint=mcp_tool.server_url,
headers=mcp_tool.headers or {},
tool_name=function_name,
kwargs=tool_kwargs,
)
attributes = {
"server_label": mcp_tool.server_label,
"server_url": mcp_tool.server_url,
"tool_name": function_name,
}
async with tracing.span("invoke_mcp_tool", attributes):
result = await invoke_mcp_tool(
endpoint=mcp_tool.server_url,
headers=mcp_tool.headers or {},
tool_name=function_name,
kwargs=tool_kwargs,
)
elif function_name == "knowledge_search":
response_file_search_tool = next(
(t for t in ctx.response_tools if isinstance(t, OpenAIResponseInputToolFileSearch)),
Expand All @@ -234,15 +241,20 @@ async def _execute_tool(
# Use vector_stores.search API instead of knowledge_search tool
# to support filters and ranking_options
query = tool_kwargs.get("query", "")
result = await self._execute_knowledge_search_via_vector_store(
query=query,
response_file_search_tool=response_file_search_tool,
)
async with tracing.span("knowledge_search", {}):
result = await self._execute_knowledge_search_via_vector_store(
query=query,
response_file_search_tool=response_file_search_tool,
)
else:
result = await self.tool_runtime_api.invoke_tool(
tool_name=function_name,
kwargs=tool_kwargs,
)
attributes = {
"tool_name": function_name,
}
async with tracing.span("invoke_tool", attributes):
result = await self.tool_runtime_api.invoke_tool(
tool_name=function_name,
kwargs=tool_kwargs,
)
except Exception as e:
error_exc = e

Expand Down
Loading