Semantic Conventions for GenAI agent and framework spans

Status: Development

Generative AI models can be trained to use tools to access real-time information or suggest a real-world action. For example, a model can leverage a database retrieval tool to access specific information, like a customer’s purchase history, so it can generate tailored shopping recommendations. Alternatively, based on a user’s query, a model can make various API calls to send an email response to a colleague or complete a financial transaction on your behalf. To do so, the model must not only have access to a set of external tools, it needs the ability to plan and execute any task in a self-directed fashion. This combination of reasoning, logic, and access to external information that are all connected to a Generative AI model invokes the concept of an agent.

This document defines semantic conventions for GenAI agent calls that are defined by this whitepaper.

It MAY be applicable to agent operations that are performed by the GenAI framework locally.

The semantic conventions for GenAI agents extend and override the semantic conventions for Gen AI Spans.

Spans

Create Agent Span

Describes GenAI agent creation and is usually applicable when working with remote agent services.

The gen_ai.operation.name SHOULD be create_agent.

The span name SHOULD be create_agent {gen_ai.agent.name}. Semantic conventions for individual GenAI systems and frameworks MAY specify different span name format.

Attribute	Type	Description	Examples	Requirement Level	Stability
gen_ai.operation.name	string	The name of the operation being performed. [1]	chat; text_completion; embeddings	Required
gen_ai.system	string	The Generative AI product as identified by the client or server instrumentation. [2]	openai	Required
error.type	string	Describes a class of error the operation ended with. [3]	timeout; java.net.UnknownHostException; server_certificate_invalid; 500	Conditionally Required if the operation ended in an error
gen_ai.agent.description	string	Free-form description of the GenAI agent provided by the application.	Helps with math problems; Generates fiction stories	Conditionally Required If provided by the application.
gen_ai.agent.id	string	The unique identifier of the GenAI agent.	asst_5j66UpCpwteGg4YSxUnt7lPY	Conditionally Required if applicable.
gen_ai.agent.name	string	Human-readable name of the GenAI agent provided by the application.	Math Tutor; Fiction Writer	Conditionally Required If provided by the application.
gen_ai.output.type	string	Represents the content type requested by the client. [4]	text; json; image	Conditionally Required [5]
gen_ai.request.choice.count	int	The target number of candidate completions to return.	3	Conditionally Required if available, in the request, and !=1
gen_ai.request.model	string	The name of the GenAI model a request is being made to. [6]	gpt-4	Conditionally Required If provided by the application.
gen_ai.request.seed	int	Requests with same seed value more likely to return same result.	100	Conditionally Required if applicable and if the request includes a seed
gen_ai.request.temperature	double	The temperature setting for the GenAI request.	0.0	Conditionally Required If provided by the application.
gen_ai.request.top_p	double	The top_p sampling setting for the GenAI request.	1.0	Conditionally Required If provided by the application.
server.port	int	GenAI server port. [7]	80; 8080; 443	Conditionally Required If server.address is set.
gen_ai.request.encoding_formats	string[]	The encoding formats requested in an embeddings operation, if specified. [8]	["base64"]; ["float", "binary"]	Recommended
gen_ai.request.frequency_penalty	double	The frequency penalty setting for the GenAI request.	0.1	Recommended
gen_ai.request.max_tokens	int	The maximum number of tokens the model generates for a request.	100	Recommended
gen_ai.request.presence_penalty	double	The presence penalty setting for the GenAI request.	0.1	Recommended
gen_ai.request.stop_sequences	string[]	List of sequences that the model will use to stop generating further tokens.	["forest", "lived"]	Recommended
gen_ai.response.finish_reasons	string[]	Array of reasons the model stopped generating tokens, corresponding to each generation received.	["stop"]; ["stop", "length"]	Recommended
gen_ai.response.id	string	The unique identifier for the completion.	chatcmpl-123	Recommended
gen_ai.response.model	string	The name of the model that generated the response. [9]	gpt-4-0613	Recommended
gen_ai.usage.input_tokens	int	The number of tokens used in the GenAI input (prompt).	100	Recommended
gen_ai.usage.output_tokens	int	The number of tokens used in the GenAI response (completion).	180	Recommended
server.address	string	GenAI server address. [10]	example.com; 10.1.2.80; /tmp/my.sock	Recommended

[1] gen_ai.operation.name: If one of the predefined values applies, but specific system uses a different name it’s RECOMMENDED to document it in the semantic conventions for specific GenAI system and use system-specific name in the instrumentation. If a different name is not documented, instrumentation libraries SHOULD use applicable predefined value.

[2] gen_ai.system: The gen_ai.system describes a family of GenAI models with specific model identified by gen_ai.request.model and gen_ai.response.model attributes.

The actual GenAI product may differ from the one identified by the client. Multiple systems, including Azure OpenAI and Gemini, are accessible by OpenAI client libraries. In such cases, the gen_ai.system is set to openai based on the instrumentation’s best knowledge, instead of the actual system. The server.address attribute may help identify the actual system in use for openai.

For custom model, a custom friendly name SHOULD be used. If none of these options apply, the gen_ai.system SHOULD be set to _OTHER.

[3] error.type: The error.type SHOULD match the error code returned by the Generative AI provider or the client library, the canonical name of exception that occurred, or another low-cardinality error identifier. Instrumentations SHOULD document the list of errors they report.

[4] gen_ai.output.type: This attribute SHOULD be used when the client requests output of a specific type. The model may return zero or more outputs of this type. This attribute specifies the output modality and not the actual output format. For example, if an image is requested, the actual output could be a URL pointing to an image file. Additional output format details may be recorded in the future in the gen_ai.output.{type}.* attributes.

[5] gen_ai.output.type: when applicable and if the request includes an output format.

[6] gen_ai.request.model: The name of the GenAI model a request is being made to. If the model is supplied by a vendor, then the value must be the exact name of the model requested. If the model is a fine-tuned custom model, the value should have a more specific name than the base model that’s been fine-tuned.

[7] server.port: When observed from the client side, and when communicating through an intermediary, server.port SHOULD represent the server port behind any intermediaries, for example proxies, if it’s available.

[8] gen_ai.request.encoding_formats: In some GenAI systems the encoding formats are called embedding types. Also, some GenAI systems only accept a single format per request.

[9] gen_ai.response.model: If available. The name of the GenAI model that provided the response. If the model is supplied by a vendor, then the value must be the exact name of the model actually used. If the model is a fine-tuned custom model, the value should have a more specific name than the base model that’s been fine-tuned.

[10] server.address: When observed from the client side, and when communicating through an intermediary, server.address SHOULD represent the server address behind any intermediaries, for example proxies, if it’s available.

error.type has the following list of well-known values. If one of them applies, then the respective value MUST be used; otherwise, a custom value MAY be used.

Value	Description	Stability
_OTHER	A fallback error value to be used when the instrumentation doesn’t define a custom value.

gen_ai.operation.name has the following list of well-known values. If one of them applies, then the respective value MUST be used; otherwise, a custom value MAY be used.

Value	Description	Stability
chat	Chat completion operation such as OpenAI Chat API
create_agent	Create GenAI agent
embeddings	Embeddings operation such as OpenAI Create embeddings API
execute_tool	Execute a tool
text_completion	Text completions operation such as OpenAI Completions API (Legacy)

gen_ai.output.type has the following list of well-known values. If one of them applies, then the respective value MUST be used; otherwise, a custom value MAY be used.

Value	Description	Stability
image	Image
json	JSON object with known or unknown schema
speech	Speech
text	Plain text

gen_ai.system has the following list of well-known values. If one of them applies, then the respective value MUST be used; otherwise, a custom value MAY be used.

Value	Description	Stability
anthropic	Anthropic
aws.bedrock	AWS Bedrock
az.ai.inference	Azure AI Inference
az.ai.openai	Azure OpenAI
cohere	Cohere
deepseek	DeepSeek
gemini	Gemini
groq	Groq
ibm.watsonx.ai	IBM Watsonx AI
mistral_ai	Mistral AI
openai	OpenAI
perplexity	Perplexity
vertex_ai	Vertex AI
xai	xAI

Agent Execute Tool Span

If you are using some tools in your agent, refer to Execute Tool Span.