open-telemetry
/
semantic-conventions
mirror of https://github.com/open-telemetry/semantic-conventions.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
semantic-conventions/docs/gen-ai/gen-ai-spans.md

29 KiB
Raw Blame History

Semantic conventions for generative client AI spans

Status: Development

[!Warning]

Existing GenAI instrumentations that are using v1.36.0 of this document (or prior):

  • SHOULD NOT change the version of the GenAI conventions that they emit by default. Conventions include, but are not limited to, attributes, metric, span and event names, span kind and unit of measure.
  • SHOULD introduce an environment variable OTEL_SEMCONV_STABILITY_OPT_IN as a comma-separated list of category-specific values. The list of values includes:
    • gen_ai_latest_experimental - emit the latest experimental version of GenAI conventions (supported by the instrumentation) and do not emit the old one (v1.36.0 or prior).
    • The default behavior is to continue emitting whatever version of the GenAI conventions the instrumentation was emitting (1.36.0 or prior).

This transition plan will be updated to include stable version before the GenAI conventions are marked as stable.

Spans

Inference

Status: Development

This span represents a client call to Generative AI model or service that generates a response or requests a tool call based on the input prompt.

Span name SHOULD be {gen_ai.operation.name} {gen_ai.request.model}. Semantic conventions for individual GenAI systems and frameworks MAY specify different span name format and MUST follow the overall guidelines for span names.

Span kind SHOULD be CLIENTand MAY be set to INTERNAL on spans representing call to models running in the same process. It's RECOMMENDED to use CLIENT kind when the GenAI system being instrumented usually runs in a different process than its client or when the GenAI call happens over instrumented protocol such as HTTP.

Span status SHOULD follow the Recording Errors document.

Attribute Type Description Examples Requirement Level Stability
gen_ai.operation.name string The name of the operation being performed. [1] chat; generate_content; text_completion Required Development
gen_ai.provider.name string The Generative AI provider as identified by the client or server instrumentation. [2] openai; gcp.gen_ai; gcp.vertex_ai Required Development
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 Stable
gen_ai.conversation.id string The unique identifier for a conversation (session, thread), used to store and correlate messages within this conversation. [4] conv_5j66UpCpwteGg4YSxUnt7lPY Conditionally Required when available Development
gen_ai.output.type string Represents the content type requested by the client. [5] text; json; image Conditionally Required [6] Development
gen_ai.request.choice.count int The target number of candidate completions to return. 3 Conditionally Required if available, in the request, and !=1 Development
gen_ai.request.model string The name of the GenAI model a request is being made to. [7] gpt-4 Conditionally Required If available. Development
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 Development
server.port int GenAI server port. [8] 80; 8080; 443 Conditionally Required If server.address is set. Stable
gen_ai.request.frequency_penalty double The frequency penalty setting for the GenAI request. 0.1 Recommended Development
gen_ai.request.max_tokens int The maximum number of tokens the model generates for a request. 100 Recommended Development
gen_ai.request.presence_penalty double The presence penalty setting for the GenAI request. 0.1 Recommended Development
gen_ai.request.stop_sequences string[] List of sequences that the model will use to stop generating further tokens. ["forest", "lived"] Recommended Development
gen_ai.request.temperature double The temperature setting for the GenAI request. 0.0 Recommended Development
gen_ai.request.top_k double The top_k sampling setting for the GenAI request. 1.0 Recommended Development
gen_ai.request.top_p double The top_p sampling setting for the GenAI request. 1.0 Recommended Development
gen_ai.response.finish_reasons string[] Array of reasons the model stopped generating tokens, corresponding to each generation received. ["stop"]; ["stop", "length"] Recommended Development
gen_ai.response.id string The unique identifier for the completion. chatcmpl-123 Recommended Development
gen_ai.response.model string The name of the model that generated the response. [9] gpt-4-0613 Recommended Development
gen_ai.usage.input_tokens int The number of tokens used in the GenAI input (prompt). 100 Recommended Development
gen_ai.usage.output_tokens int The number of tokens used in the GenAI response (completion). 180 Recommended Development
server.address string GenAI server address. [10] example.com; 10.1.2.80; /tmp/my.sock Recommended Stable

[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.provider.name: The attribute SHOULD be set based on the instrumentation's best knowledge and may differ from the actual model provider.

Multiple providers, including Azure OpenAI, Gemini, and AI hosting platforms are accessible using the OpenAI REST API and corresponding client libraries, but may proxy or host models from different providers.

The gen_ai.request.model, gen_ai.response.model, and server.address attributes may help identify the actual system in use.

The gen_ai.provider.name attribute acts as a discriminator that identifies the GenAI telemetry format flavor specific to that provider within GenAI semantic conventions. It SHOULD be set consistently with provider-specific attributes and signals. For example, GenAI spans, metrics, and events related to AWS Bedrock should have the gen_ai.provider.name set to aws.bedrock and include applicable aws.bedrock.* attributes and are not expected to include openai.* attributes.

[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.conversation.id: Instrumentations SHOULD populate conversation id when they have it readily available for a given operation, for example:

Application developers that manage conversation history MAY add conversation id to GenAI and other spans or logs using custom span or log record processors or hooks provided by instrumentation libraries.

[5] 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.

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

[7] 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.

[8] 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.

[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. Stable

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 Development
create_agent Create GenAI agent Development
embeddings Embeddings operation such as OpenAI Create embeddings API Development
execute_tool Execute a tool Development
generate_content Multimodal content generation operation such as Gemini Generate Content Development
invoke_agent Invoke GenAI agent Development
text_completion Text completions operation such as OpenAI Completions API (Legacy) Development

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 Development
json JSON object with known or unknown schema Development
speech Speech Development
text Plain text Development

gen_ai.provider.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
anthropic Anthropic Development
aws.bedrock AWS Bedrock Development
azure.ai.inference Azure AI Inference Development
azure.ai.openai Azure OpenAI Development
cohere Cohere Development
deepseek DeepSeek Development
gcp.gemini Gemini [11] Development
gcp.gen_ai Any Google generative AI endpoint [12] Development
gcp.vertex_ai Vertex AI [13] Development
groq Groq Development
ibm.watsonx.ai IBM Watsonx AI Development
mistral_ai Mistral AI Development
openai OpenAI Development
perplexity Perplexity Development
x_ai xAI Development

[11]: Used when accessing the 'generativelanguage.googleapis.com' endpoint. Also known as the AI Studio API.

[12]: May be used when specific backend is unknown.

[13]: Used when accessing the 'aiplatform.googleapis.com' endpoint.

Embeddings

Status: Development

Describes GenAI embeddings span - a request to a Generative AI model or service that generates an embeddings based on the input. The gen_ai.operation.name SHOULD be embeddings. Span name SHOULD be {gen_ai.operation.name} {gen_ai.request.model}.

Span kind SHOULD be CLIENT.

Span status SHOULD follow the Recording Errors document.

Attribute Type Description Examples Requirement Level Stability
gen_ai.operation.name string The name of the operation being performed. [1] chat; generate_content; text_completion Required Development
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 Stable
gen_ai.request.model string The name of the GenAI model a request is being made to. [3] gpt-4 Conditionally Required If available. Development
server.port int GenAI server port. [4] 80; 8080; 443 Conditionally Required If server.address is set. Stable
gen_ai.request.encoding_formats string[] The encoding formats requested in an embeddings operation, if specified. [5] ["base64"]; ["float", "binary"] Recommended Development
gen_ai.usage.input_tokens int The number of tokens used in the GenAI input (prompt). 100 Recommended Development
server.address string GenAI server address. [6] example.com; 10.1.2.80; /tmp/my.sock Recommended Stable

[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] 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.

[6] 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. Stable

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 Development
create_agent Create GenAI agent Development
embeddings Embeddings operation such as OpenAI Create embeddings API Development
execute_tool Execute a tool Development
generate_content Multimodal content generation operation such as Gemini Generate Content Development
invoke_agent Invoke GenAI agent Development
text_completion Text completions operation such as OpenAI Completions API (Legacy) Development

Execute tool span

Status: Development

Describes tool execution span.

gen_ai.operation.name SHOULD be execute_tool.

Span name SHOULD be execute_tool {gen_ai.tool.name}.

GenAI instrumentations that are able to instrument tool execution call SHOULD do so. However, it's common for tools to be executed by the application code. It's recommended for the application developers to follow this semantic convention for tools invoked by the application code.

Span kind SHOULD be INTERNAL.

Span status SHOULD follow the Recording Errors document.

Attribute Type Description Examples Requirement Level Stability
gen_ai.operation.name string The name of the operation being performed. [1] chat; generate_content; text_completion Required Development
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 Stable
gen_ai.tool.call.id string The tool call identifier. call_mszuSIzqtI65i1wAUOE8w5H4 Recommended if available Development
gen_ai.tool.description string The tool description. Multiply two numbers Recommended if available Development
gen_ai.tool.name string Name of the tool utilized by the agent. Flights Recommended Development
gen_ai.tool.type string Type of the tool utilized by the agent [3] function; extension; datastore Recommended if available Development

[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.tool.type: Extension: A tool executed on the agent-side to directly call external APIs, bridging the gap between the agent and real-world systems. Agent-side operations involve actions that are performed by the agent on the server or within the agent's controlled environment. Function: A tool executed on the client-side, where the agent generates parameters for a predefined function, and the client executes the logic. Client-side operations are actions taken on the user's end or within the client application. Datastore: A tool used by the agent to access and query structured or unstructured external data for retrieval-augmented tasks or knowledge updates.

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. Stable

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 Development
create_agent Create GenAI agent Development
embeddings Embeddings operation such as OpenAI Create embeddings API Development
execute_tool Execute a tool Development
generate_content Multimodal content generation operation such as Gemini Generate Content Development
invoke_agent Invoke GenAI agent Development
text_completion Text completions operation such as OpenAI Completions API (Legacy) Development

Capturing inputs and outputs

User inputs and model responses may be recorded as events parented to GenAI operation span. See Semantic Conventions for GenAI events for the details.