Semantic Conventions for Azure AI Inference

Status: Experimental

The Semantic Conventions for Azure AI Inference extend and override the GenAI Semantic Conventions.

Azure AI Inference Spans

gen_ai.system MUST be set to "az.ai.inference" and SHOULD be provided at span creation time.

Attributes

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
error.type	string	Describes a class of error the operation ended with. [2]	timeout; java.net.UnknownHostException; server_certificate_invalid; 500	Conditionally Required if the operation ended in an error
gen_ai.request.model	string	The name of the GenAI model a request is being made to. [3]	gpt-4	Conditionally Required If available.
server.port	int	GenAI server port. [4]	80; 8080; 443	Conditionally Required If not default (443).
az.namespace	string	Azure Resource Provider Namespace as recognized by the client. [5]	Microsoft.CognitiveServices	Recommended
gen_ai.request.encoding_formats	string[]	The encoding formats requested in an embeddings operation, if specified. [6]	["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.request.temperature	double	The temperature setting for the GenAI request.	0.0	Recommended
gen_ai.request.top_p	double	The top_p sampling setting for the GenAI request.	1.0	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. [7]	gpt-4-0613	Recommended
gen_ai.usage.input_tokens	int	The number of prompt tokens as reported in the usage prompt_tokens property of the response.	100	Recommended
gen_ai.usage.output_tokens	int	The number of completion tokens as reported in the usage completion_tokens property of the response.	180	Recommended
server.address	string	GenAI server address. [8]	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] 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.

[3] 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.

[4] 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.

[5] az.namespace: When az.namespace attribute is populated, it MUST be set to Microsoft.CognitiveServices for all operations performed by Azure AI Inference clients.

[6] 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.

[7] 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.

[8] 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
embeddings	Embeddings operation such as OpenAI Create embeddings API
text_completion	Text completions operation such as OpenAI Completions API (Legacy)

Azure AI Inference Metrics

Azure AI Inference metrics follow generic Generative AI metrics.