Semantic Conventions for LLM requests

Status: Experimental

A request to an LLM is modeled as a span in a trace.

Span kind: MUST always be CLIENT.

The span name SHOULD be set to a low cardinality value describing an operation made to an LLM. For example, the API name such as Create chat completion could be represented as ChatCompletions gpt-4 to include the API and the LLM.

Configuration

Instrumentations for LLMs MAY capture prompts and completions. Instrumentations that support it, MUST offer the ability to turn off capture of prompts and completions. This is for three primary reasons:

1. Data privacy concerns. End users of LLM applications may input sensitive information or personally identifiable information (PII) that they do not wish to be sent to a telemetry backend.
2. Data size concerns. Although there is no specified limit to sizes, there are practical limitations in programming languages and telemetry systems. Some LLMs allow for extremely large context windows that end users may take full advantage of.
3. Performance concerns. Sending large amounts of data to a telemetry backend may cause performance issues for the application.

LLM Request attributes

These attributes track input data and metadata for a request to an LLM. Each attribute represents a concept that is common to most LLMs.

Attribute	Type	Description	Examples	Requirement Level	Stability
gen_ai.request.model	string	The name of the LLM a request is being made to. [1]	gpt-4	Required
gen_ai.system	string	The Generative AI product as identified by the client instrumentation. [2]	openai	Required
gen_ai.request.max_tokens	int	The maximum number of tokens the LLM generates for a request.	100	Recommended
gen_ai.request.temperature	double	The temperature setting for the LLM request.	0.0	Recommended
gen_ai.request.top_p	double	The top_p sampling setting for the LLM request.	1.0	Recommended
gen_ai.response.finish_reasons	string[]	Array of reasons the model stopped generating tokens, corresponding to each generation received.	stop	Recommended
gen_ai.response.id	string	The unique identifier for the completion.	chatcmpl-123	Recommended
gen_ai.response.model	string	The name of the LLM a response was generated from. [3]	gpt-4-0613	Recommended
gen_ai.usage.completion_tokens	int	The number of tokens used in the LLM response (completion).	180	Recommended
gen_ai.usage.prompt_tokens	int	The number of tokens used in the LLM prompt.	100	Recommended

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

[2]: If not using a vendor-supplied model, provide a custom friendly name, such as a name of the company or project. If the instrumetnation reports any attributes specific to a custom model, the value provided in the gen_ai.system SHOULD match the custom attribute namespace segment. For example, if gen_ai.system is set to the_best_llm, custom attributes should be added in the gen_ai.the_best_llm.* namespace. If none of above options apply, the instrumentation should set _OTHER.

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

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
openai	OpenAI

Events

In the lifetime of an LLM span, an event for prompts sent and completions received MAY be created, depending on the configuration of the instrumentation.

The event name MUST be gen_ai.content.prompt.

Attribute	Type	Description	Examples	Requirement Level	Stability
gen_ai.prompt	string	The full prompt sent to an LLM. [1]	[{'role': 'user', 'content': 'What is the capital of France?'}]	Conditionally Required if and only if corresponding event is enabled

[1]: It’s RECOMMENDED to format prompts as JSON string matching OpenAI messages format

The event name MUST be gen_ai.content.completion.

Attribute	Type	Description	Examples	Requirement Level	Stability
gen_ai.completion	string	The full response received from the LLM. [1]	[{'role': 'assistant', 'content': 'The capital of France is Paris.'}]	Conditionally Required if and only if corresponding event is enabled

[1]: It’s RECOMMENDED to format completions as JSON string matching OpenAI messages format