OpenTelemetry GenAI Semantic Conventions

Reference for instrumenting agents with OpenTelemetry GenAI semantic conventions.

Spec: https://opentelemetry.io/docs/specs/semconv/gen-ai/

Architecture

Agent (gen_ai.* only) → OTEL Collector → Transform → Phoenix (llm.*) + MLflow (mlflow.trace.*)

Agents emit only gen_ai.* attributes. The OTEL Collector transforms these to:

• OpenInference format (llm.*) for Phoenix
• MLflow metadata (mlflow.trace.*) for MLflow session tracking

Core Attributes

Request Attributes (on LLM call spans)

Attribute	Type	Description	Example
gen_ai.system	string	GenAI provider/system	openai, anthropic, langchain
gen_ai.request.model	string	Model requested	gpt-4, claude-3-opus
gen_ai.request.max_tokens	int	Max tokens to generate	1024
gen_ai.request.temperature	float	Sampling temperature	0.7
gen_ai.request.top_p	float	Nucleus sampling	0.9

Response Attributes

Attribute	Type	Description	Example
gen_ai.response.model	string	Model that responded	gpt-4-0613
gen_ai.response.id	string	Response identifier	chatcmpl-abc123
gen_ai.response.finish_reasons	string[]	Why generation stopped	["stop"]
gen_ai.usage.input_tokens	int	Prompt tokens	150
gen_ai.usage.output_tokens	int	Completion tokens	250

Conversation/Session Attributes

Attribute	Type	Description	Example
gen_ai.conversation.id	string	Session/conversation ID	uuid-123-456
gen_ai.prompt	string	User prompt (truncated)	What is the weather?
gen_ai.completion	string	Response (truncated)	The weather is sunny

Agent Attributes (custom, for A2A agents)

Attribute	Type	Description	Example
gen_ai.agent.name	string	Agent name	weather-assistant
gen_ai.agent.id	string	Agent/task ID	task-uuid-789

Python Usage

Auto-instrumentation (Recommended)

# Install: pip install opentelemetry-instrumentation-openai
from opentelemetry.instrumentation.openai import OpenAIInstrumentor

# Instruments all OpenAI SDK calls automatically
OpenAIInstrumentor().instrument()

Manual Span Attributes

from opentelemetry import trace

tracer = trace.get_tracer(__name__)

with tracer.start_as_current_span(
    "gen_ai.agent.invoke",
    attributes={
        "gen_ai.conversation.id": context_id,
        "gen_ai.agent.name": "my-agent",
        "gen_ai.system": "langchain",
        "gen_ai.request.model": "gpt-4",
        "gen_ai.prompt": user_input[:500],  # Truncate for size
    }
) as span:
    # Agent logic here
    result = await agent.run(user_input)

    # Add response attributes
    span.set_attribute("gen_ai.completion", str(result)[:500])

Adding to Existing Span

current_span = trace.get_current_span()
if current_span and current_span.is_recording():
    current_span.set_attribute("gen_ai.conversation.id", session_id)
    current_span.set_attribute("gen_ai.agent.name", "weather-assistant")

OTEL Collector Transforms

The collector transforms gen_ai.* to target formats:

GenAI → OpenInference (Phoenix)

GenAI Attribute	OpenInference Attribute
gen_ai.request.model	llm.model_name
gen_ai.usage.input_tokens	llm.token_count.prompt
gen_ai.usage.output_tokens	llm.token_count.completion
gen_ai.system	llm.provider, llm.system

GenAI → MLflow

GenAI Attribute	MLflow Metadata
gen_ai.conversation.id	mlflow.trace.session (resource)
Span name gen_ai.agent.*	mlflow.spanType=AGENT
Span with gen_ai.request.model	mlflow.spanType=LLM
Span name gen_ai.tool.*	mlflow.spanType=TOOL

Span Naming Conventions

Use GenAI operation names for spans:

Operation	Span Name
Agent invocation	gen_ai.agent.invoke
LLM chat completion	gen_ai.chat
Tool call	gen_ai.tool.{tool_name}
Embedding	gen_ai.embeddings

Best Practices

1. Always set gen_ai.conversation.id for session tracking in MLflow
2. Truncate prompts/completions to ~500 chars to avoid span size issues
3. Use auto-instrumentation when available (OpenAI, Anthropic SDKs)
4. Add manual attributes for custom agent spans
5. Never emit OpenInference (llm.*) directly - let the collector transform

Dependencies

# pyproject.toml
dependencies = [
    "opentelemetry-sdk",
    "opentelemetry-exporter-otlp",
    "opentelemetry-instrumentation-openai>=0.34b0",  # For OpenAI auto-instrumentation
]

Related Skills

• auth:otel-oauth2-exporter - Configure OTel Collector with OAuth2
• k8s:health - Platform health including observability components
• OpenTelemetry GenAI Spec
• MLflow Tracing
• OpenInference Spec