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remove tool metadata

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mubashir1osmani 2026-01-17 00:53:24 -05:00
parent 3eb0bf566b
commit b13baffeb5
1 changed files with 6 additions and 12 deletions
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18
litellm/integrations/arize/_utils.py
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@ -88,15 +88,18 @@ class ArizeOTELAttributes(BaseLLMObsOTELAttributes):
)
def _set_tool_attributes(span: "Span", optional_params: dict):
"""Helper to set tool and function call attributes on span."""
def _set_tool_attributes(span: "Span", optional_params: dict, metadata_tools: Optional[list] = None):
"""Helper to set tool and function call attributes on span.
Supports both classic optional_params.tools and metadata-provided llm.tools (e.g., responses API).
"""
from litellm.integrations._types.open_inference import (
MessageAttributes,
SpanAttributes,
ToolCallAttributes,
)
tools = optional_params.get("tools")
tools = optional_params.get("tools") or metadata_tools or []
if tools:
for idx, tool in enumerate(tools):
function = tool.get("function")
@ -250,8 +253,6 @@ def _set_retrieval_documents(span: "Span", metadata: Optional[dict], max_docs: i
if doc_entry:
docs.append(doc_entry)
# Also set Phoenix/OpenInference-friendly flattened attributes per document so they render on retriever spans.
doc_index = len(docs) - 1
doc_id = item.get("id") or file_id
if doc_id is not None:
@ -260,7 +261,6 @@ def _set_retrieval_documents(span: "Span", metadata: Optional[dict], max_docs: i
)
if contents:
# Join content pieces to a single string for UI display
safe_set_attribute(
span,
f"{SpanAttributes.RETRIEVAL_DOCUMENTS}.{doc_index}.document.content",
@ -409,15 +409,9 @@ def set_attributes(
span_kind = _infer_open_inference_span_kind(call_type=call_type)
# If MCP tool calls are present, report span as TOOL even when call_type is generic (e.g., responses).
if metadata and metadata.get("mcp_tool_call_metadata"):
span_kind = OpenInferenceSpanKindValues.TOOL.value
safe_set_attribute(span, SpanAttributes.OPENINFERENCE_SPAN_KIND, span_kind)
attributes.set_messages(span, kwargs)
_set_tool_attributes(span=span, optional_params=optional_params)
model_params = (
standard_logging_payload.get("model_parameters")
if standard_logging_payload