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Merge 1c090d7d54 into cd63c7e5a7
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commit
ff611c8a7e
2 changed files with 277 additions and 2 deletions
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@ -2539,8 +2539,17 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger):
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tools: Final = optional_params["tools"]
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self.set_tools_attributes(span, tools)
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if kwargs.get("messages"):
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transformed_messages = self._transform_messages_to_otel_semantic_conventions(kwargs.get("messages"))
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# Coalesce messages from kwargs or optional_params: the
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# anthropic-native /v1/messages (call_type="anthropic_messages")
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# path stores the messages list on ``optional_params``, not on
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# ``kwargs``. Same coalesce pattern the system-instructions block
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# below uses. Without this, gen_ai.input.messages is empty for
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# the entire Anthropic Messages call type (#30121).
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input_messages = (
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kwargs.get("messages") if kwargs.get("messages") is not None else optional_params.get("messages")
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)
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if input_messages:
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transformed_messages = self._transform_messages_to_otel_semantic_conventions(input_messages)
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self.safe_set_attribute(
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span=span,
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key=SpanAttributes.GEN_AI_INPUT_MESSAGES.value,
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@ -2636,6 +2645,77 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger):
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value=value,
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)
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elif response_obj.get("content") and isinstance(response_obj.get("content"), list):
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# Anthropic Messages API response: top-level "content" is
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# a list of blocks (text / thinking / tool_use). The
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# finish reason lives on "stop_reason". Without this
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# branch, /v1/messages (call_type="anthropic_messages")
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# spans never get gen_ai.output.messages or
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# gen_ai.response.finish_reasons (#30121).
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content_blocks = response_obj.get("content") or []
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parts: List[dict] = []
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tool_calls = []
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for block in content_blocks:
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block_d = self._to_dict(block) or {}
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btype = block_d.get("type")
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if btype == "text":
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parts.append({"type": "text", "content": block_d.get("text", "")})
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elif btype == "thinking":
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parts.append(
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{
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"type": "text",
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"content": block_d.get("thinking", ""),
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}
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)
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elif btype == "tool_use":
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tool_input = block_d.get("input") or {}
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parts.append(
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{
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"type": "tool_call",
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"id": block_d.get("id", ""),
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"name": block_d.get("name", ""),
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"arguments": tool_input,
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}
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)
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tool_calls.append(
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{
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"function": {
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"name": block_d.get("name", ""),
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"arguments": safe_dumps(tool_input),
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}
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}
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)
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if parts:
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output_messages = [
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{
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"role": response_obj.get("role", "assistant"),
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"parts": parts,
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}
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]
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self.safe_set_attribute(
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span=span,
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key=SpanAttributes.GEN_AI_OUTPUT_MESSAGES.value,
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value=safe_dumps(output_messages),
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)
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if tool_calls:
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kv_pairs = OpenTelemetry._tool_calls_kv_pair(tool_calls) # type: ignore
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for key, value in kv_pairs.items():
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self.safe_set_attribute(
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span=span,
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key=key,
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value=value,
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)
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stop_reason = response_obj.get("stop_reason")
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if stop_reason:
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self.safe_set_attribute(
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span=span,
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key=SpanAttributes.GEN_AI_RESPONSE_FINISH_REASONS.value,
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value=safe_dumps([stop_reason]),
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)
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elif response_obj.get("output"):
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# Responses API: ResponsesAPIResponse has an "output"
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# list instead of "choices". Each item with
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@ -0,0 +1,195 @@
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"""
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Regression for #30121.
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OpenTelemetry.set_attributes() missed both gen_ai.input.messages and
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gen_ai.output.messages for the Anthropic-native /v1/messages route
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(call_type="anthropic_messages") because:
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- Input gate checked ``kwargs.get("messages")`` only, but the
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anthropic_messages handler stores the messages on
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``optional_params["messages"]``.
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- Output gate had branches for OpenAI ``choices`` and Responses API
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``output`` but none for the Anthropic top-level ``content`` block list.
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Span otherwise had cost/usage/model fine — only the prompt/completion
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content was missing in Langfuse, Phoenix, Arize, etc.
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"""
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import unittest
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from unittest.mock import MagicMock
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from litellm.integrations.opentelemetry import OpenTelemetry
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def _base_kwargs() -> dict:
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return {
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"model": "claude-opus-4-7",
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"litellm_params": {"custom_llm_provider": "anthropic"},
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"standard_logging_object": {
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"id": "test-id",
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"call_type": "anthropic_messages",
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"metadata": {},
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},
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}
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def _attr_set(mock_span: MagicMock) -> dict:
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out = {}
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for c in mock_span.set_attribute.call_args_list:
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args, _ = c
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out[args[0]] = args[1]
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return out
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class TestOtelAnthropicMessagesInput(unittest.TestCase):
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def test_messages_on_optional_params_populate_input_messages(self):
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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kwargs["optional_params"] = {
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"messages": [
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{"role": "user", "content": "list files"},
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{"role": "assistant", "content": "ok"},
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]
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}
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response_obj = {
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"content": [{"type": "text", "text": "done"}],
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"role": "assistant",
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"stop_reason": "end_turn",
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}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj)
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attrs = _attr_set(mock_span)
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self.assertIn("gen_ai.input.messages", attrs)
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self.assertIn("list files", attrs["gen_ai.input.messages"])
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def test_kwargs_messages_still_win_when_both_present(self):
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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kwargs["messages"] = [{"role": "user", "content": "from kwargs"}]
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kwargs["optional_params"] = {"messages": [{"role": "user", "content": "from optional"}]}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj={"content": []})
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attrs = _attr_set(mock_span)
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self.assertIn("gen_ai.input.messages", attrs)
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self.assertIn("from kwargs", attrs["gen_ai.input.messages"])
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self.assertNotIn("from optional", attrs["gen_ai.input.messages"])
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class TestOtelAnthropicMessagesOutput(unittest.TestCase):
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def test_anthropic_content_blocks_populate_output_messages(self):
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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kwargs["optional_params"] = {"messages": [{"role": "user", "content": "hi"}]}
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response_obj = {
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"content": [
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{"type": "text", "text": "hello"},
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{
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"type": "tool_use",
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"id": "tool_abc",
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"name": "bash",
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"input": {"command": "ls"},
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},
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],
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"role": "assistant",
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"stop_reason": "tool_use",
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}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj)
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attrs = _attr_set(mock_span)
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self.assertIn("gen_ai.output.messages", attrs)
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out = attrs["gen_ai.output.messages"]
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self.assertIn("hello", out)
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self.assertIn("bash", out)
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self.assertIn("tool_abc", out)
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self.assertIn("gen_ai.response.finish_reasons", attrs)
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self.assertIn("tool_use", attrs["gen_ai.response.finish_reasons"])
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def test_thinking_block_is_serialised_as_text_part(self):
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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response_obj = {
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"content": [
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{
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"type": "thinking",
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"thinking": "deliberating...",
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"signature": "sig",
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},
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{"type": "text", "text": "answer"},
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],
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"role": "assistant",
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"stop_reason": "end_turn",
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}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj)
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attrs = _attr_set(mock_span)
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self.assertIn("gen_ai.output.messages", attrs)
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out = attrs["gen_ai.output.messages"]
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self.assertIn("deliberating...", out)
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self.assertIn("answer", out)
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def test_empty_or_unrecognised_content_blocks_skip_output_messages_emit(self):
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"""Greptile flagged the unconditional emit as inconsistent with the
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Responses API branch, which guards ``if output_messages:``. Mirror
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that guard so a content list of only unknown block types doesn't
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leave a blank assistant-message entry in observability tools."""
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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response_obj = {
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"content": [
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{"type": "future_block_type_unknown_to_litellm", "payload": "..."},
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],
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"role": "assistant",
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"stop_reason": "end_turn",
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}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj)
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attrs = _attr_set(mock_span)
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self.assertNotIn("gen_ai.output.messages", attrs)
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# stop_reason still emits even with empty parts.
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self.assertIn("gen_ai.response.finish_reasons", attrs)
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def test_choices_still_takes_precedence_over_content_for_openai_shape(self):
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otel = OpenTelemetry()
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mock_span = MagicMock()
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kwargs = _base_kwargs()
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kwargs["standard_logging_object"]["call_type"] = "completion"
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kwargs["messages"] = [{"role": "user", "content": "hi"}]
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# response with BOTH choices (openai shape) and a spurious content
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# field — choices branch must win to preserve the openai contract.
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response_obj = {
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"choices": [
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{
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"message": {"role": "assistant", "content": "openai-out"},
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"finish_reason": "stop",
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}
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],
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"content": [{"type": "text", "text": "anthropic-out"}],
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}
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otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj)
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attrs = _attr_set(mock_span)
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self.assertIn("gen_ai.output.messages", attrs)
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out = attrs["gen_ai.output.messages"]
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self.assertIn("openai-out", out)
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self.assertNotIn("anthropic-out", out)
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