Semantic Conventions for Generative AI Metrics
Status: Experimental
Generative AI Client Metrics
The conventions described in this section are specific to Generative AI client applications.
Disclaimer: These are initial Generative AI client metric instruments and attributes but more may be added in the future.
The following metric instruments describe Generative AI operations. An operation may be a request to an LLM, a function call, or some other distinct action within a larger Generative AI workflow.
Individual systems may include additional system-specific attributes. It is recommended to check system-specific documentation, if available.
Metric: gen_ai.client.token.usage
This metric is recommended when an operation involves the usage of tokens and the count is readily available.
For example, if GenAI system returns usage information in the streaming response, it SHOULD be used. Or if GenAI system returns each token independently, instrumentation SHOULD count number of output tokens and record the result.
If instrumentation cannot efficiently obtain number of input and/or output tokens, it MAY allow users to enable offline token counting. Otherwise it MUST NOT report usage metric.
When systems report both used tokens and billable tokens, instrumentation MUST report billable tokens.
This metric SHOULD be specified with ExplicitBucketBoundaries of [1, 4, 16, 64, 256, 1024, 4096, 16384, 65536, 262144, 1048576, 4194304, 16777216, 67108864].
Name | Instrument Type | Unit (UCUM) | Description | Stability |
---|---|---|---|---|
gen_ai.client.token.usage | Histogram | {token} | Measures number of input and output tokens used |
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 | |
gen_ai.token.type | string | The type of token being counted. | input ; output | Required | |
gen_ai.request.model | string | The name of the GenAI model a request is being made to. | gpt-4 | Conditionally Required If available. | |
server.port | int | GenAI server port. [3] | 80 ; 8080 ; 443 | Conditionally Required If server.address is set. | |
gen_ai.response.model | string | The name of the model that generated the response. | gpt-4-0613 | Recommended | |
server.address | string | GenAI server address. [4] | 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.
For example, when using OpenAI client libraries to communicate with Mistral, the gen_ai.system
is set to openai
based on the instrumentation’s best knowledge.
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] 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.
[4] 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.
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) |
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 | |
cohere | Cohere | |
ibm.watsonx.ai | IBM Watsonx AI | |
openai | OpenAI | |
vertex_ai | Vertex AI |
gen_ai.token.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 |
---|---|---|
input | Input tokens (prompt, input, etc.) | |
output | Output tokens (completion, response, etc.) |
Metric: gen_ai.client.operation.duration
This metric is required.
This metric SHOULD be specified with ExplicitBucketBoundaries of [0.01, 0.02, 0.04, 0.08, 0.16, 0.32, 0.64, 1.28, 2.56, 5.12, 10.24, 20.48, 40.96, 81.92].
Name | Instrument Type | Unit (UCUM) | Description | Stability |
---|---|---|---|---|
gen_ai.client.operation.duration | Histogram | s | GenAI operation duration |
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.request.model | string | The name of the GenAI model a request is being made to. | gpt-4 | Conditionally Required If available. | |
server.port | int | GenAI server port. [4] | 80 ; 8080 ; 443 | Conditionally Required If server.address is set. | |
gen_ai.response.model | string | The name of the model that generated the response. | gpt-4-0613 | Recommended | |
server.address | string | GenAI server address. [5] | 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.
For example, when using OpenAI client libraries to communicate with Mistral, the gen_ai.system
is set to openai
based on the instrumentation’s best knowledge.
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] 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] 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) |
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 | |
cohere | Cohere | |
ibm.watsonx.ai | IBM Watsonx AI | |
openai | OpenAI | |
vertex_ai | Vertex AI |
Generative AI Model Server Metrics
The following metric instruments describe Generative AI model servers' operational metrics. It includes both functional and performance metrics.
Metric: gen_ai.server.request.duration
This metric is recommended to report the model server latency in terms of time spent per request.
This metric SHOULD be specified with ExplicitBucketBoundaries of [0.01, 0.02, 0.04, 0.08, 0.16, 0.32, 0.64, 1.28, 2.56, 5.12, 10.24, 20.48, 40.96, 81.92].
Name | Instrument Type | Unit (UCUM) | Description | Stability |
---|---|---|---|---|
gen_ai.server.request.duration | Histogram | s | Generative AI server request duration such as time-to-last byte or last output token |
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.request.model | string | The name of the GenAI model a request is being made to. | gpt-4 | Conditionally Required If available. | |
server.port | int | GenAI server port. [4] | 80 ; 8080 ; 443 | Conditionally Required If server.address is set. | |
gen_ai.response.model | string | The name of the model that generated the response. | gpt-4-0613 | Recommended | |
server.address | string | GenAI server address. [5] | 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.
For example, when using OpenAI client libraries to communicate with Mistral, the gen_ai.system
is set to openai
based on the instrumentation’s best knowledge.
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 service,
the canonical name of exception that occurred, or another low-cardinality error identifier.
Instrumentations SHOULD document the list of errors they report.
[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] 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) |
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 | |
cohere | Cohere | |
ibm.watsonx.ai | IBM Watsonx AI | |
openai | OpenAI | |
vertex_ai | Vertex AI |
Metric: gen_ai.server.time_per_output_token
This metric is recommended to report the model server latency in terms of time per token generated after the first token for any model servers which support serving LLMs. It is measured by subtracting the time taken to generate the first output token from the request duration and dividing the rest of the duration by the number of output tokens generated after the first token. This is important in measuring the performance of the decode phase of LLM inference.
This metric SHOULD be specified with ExplicitBucketBoundaries of [0.01, 0.025, 0.05, 0.075, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 0.75, 1.0, 2.5].
Name | Instrument Type | Unit (UCUM) | Description | Stability |
---|---|---|---|---|
gen_ai.server.time_per_output_token | Histogram | s | Time per output token generated after the first token for successful responses |
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 | |
gen_ai.request.model | string | The name of the GenAI model a request is being made to. | gpt-4 | Conditionally Required If available. | |
server.port | int | GenAI server port. [3] | 80 ; 8080 ; 443 | Conditionally Required If server.address is set. | |
gen_ai.response.model | string | The name of the model that generated the response. | gpt-4-0613 | Recommended | |
server.address | string | GenAI server address. [4] | 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.
For example, when using OpenAI client libraries to communicate with Mistral, the gen_ai.system
is set to openai
based on the instrumentation’s best knowledge.
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] 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.
[4] 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.
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) |
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 | |
cohere | Cohere | |
ibm.watsonx.ai | IBM Watsonx AI | |
openai | OpenAI | |
vertex_ai | Vertex AI |
Metric: gen_ai.server.time_to_first_token
This metric is recommended to report the model server latency in terms of time spent to generate the first token of the response for any model servers which support serving LLMs. It helps measure the time spent in the queue and the prefill phase. It is important especially for streaming requests. It is calculated at a request level and is reported as a histogram using the buckets mentioned below.
This metric SHOULD be specified with ExplicitBucketBoundaries of [0.001, 0.005, 0.01, 0.02, 0.04, 0.06, 0.08, 0.1, 0.25, 0.5, 0.75, 1.0, 2.5, 5.0, 7.5, 10.0].
Name | Instrument Type | Unit (UCUM) | Description | Stability |
---|---|---|---|---|
gen_ai.server.time_to_first_token | Histogram | s | Time to generate first token for successful responses |
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 | |
gen_ai.request.model | string | The name of the GenAI model a request is being made to. | gpt-4 | Conditionally Required If available. | |
server.port | int | GenAI server port. [3] | 80 ; 8080 ; 443 | Conditionally Required If server.address is set. | |
gen_ai.response.model | string | The name of the model that generated the response. | gpt-4-0613 | Recommended | |
server.address | string | GenAI server address. [4] | 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.
For example, when using OpenAI client libraries to communicate with Mistral, the gen_ai.system
is set to openai
based on the instrumentation’s best knowledge.
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] 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.
[4] 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.
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) |
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 | |
cohere | Cohere | |
ibm.watsonx.ai | IBM Watsonx AI | |
openai | OpenAI | |
vertex_ai | Vertex AI |
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