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Semantic conventions for Azure AI Inference client operations

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.

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

Spans

Inference

gen_ai.provider.name MUST be set to "azure.ai.inference" and SHOULD be provided at span creation time.

Status: Development

Semantic Conventions for Azure AI Inference client spans extend and override the semantic conventions for Gen AI Spans.

gen_ai.provider.name MUST be set to "azure.ai.inference" and SHOULD be provided at span creation time.

Span name SHOULD be {gen_ai.operation.name} {gen_ai.request.model} when the model name is available and {gen_ai.operation.name} otherwise.

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.conversation.id string The unique identifier for a conversation (session, thread), used to store and correlate messages within this conversation. [3] conv_5j66UpCpwteGg4YSxUnt7lPY Conditionally Required when available Development
gen_ai.output.type string Represents the content type requested by the client. [4] text; json; image Conditionally Required [5] 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. [6] 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. [7] 80; 8080; 443 Conditionally Required If not default (443). Stable
azure.resource_provider.namespace string Azure Resource Provider Namespace as recognized by the client. [8] Microsoft.CognitiveServices Recommended Development
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_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 prompt tokens as reported in the usage prompt_tokens property of the response. 100 Recommended Development
gen_ai.usage.output_tokens int The number of completion tokens as reported in the usage completion_tokens property of the response. 180 Recommended Development
server.address string GenAI server address. [10] example.com; 10.1.2.80; /tmp/my.sock Recommended Stable
gen_ai.input.messages any The chat history provided to the model as an input. [11] [
  {
    "role": "user",
    "parts": [
      {
        "type": "text",
        "content": "Weather in Paris?"
      }
    ]
  },
  {
    "role": "assistant",
    "parts": [
      {
        "type": "tool_call",
        "id": "call_VSPygqKTWdrhaFErNvMV18Yl",
        "name": "get_weather",
        "arguments": {
          "location": "Paris"
        }
      }
    ]
  },
  {
    "role": "tool",
    "parts": [
      {
        "type": "tool_call_response",
        "id": " call_VSPygqKTWdrhaFErNvMV18Yl",
        "result": "rainy, 57°F"
      }
    ]
  }
]		 Opt-In Development
gen_ai.output.messages any Messages returned by the model where each message represents a specific model response (choice, candidate). [12] [
  {
    "role": "assistant",
    "parts": [
      {
        "type": "text",
        "content": "The weather in Paris is currently rainy with a temperature of 57°F."
      }
    ],
    "finish_reason": "stop"
  }
]		 Opt-In Development
gen_ai.system_instructions any The system message or instructions provided to the GenAI model separately from the chat history. [13] [
  {
    "type": "text",
    "content": "You are an Agent that greet users, always use greetings tool to respond"
  }
]; [
  {
    "type": "text",
    "content": "You are a language translator."
  },
  {
    "type": "text",
    "content": "Your mission is to translate text in English to French."
  }
]		 Opt-In Development
gen_ai.tool.definitions any The list of source system tool definitions available to the GenAI agent or model. [14] [
  {
    "type": "function",
    "name": "get_current_weather",
    "description": "Get the current weather in a given location",
    "parameters": {
      "type": "object",
      "properties": {
        "location": {
          "type": "string",
          "description": "The city and state, e.g. San Francisco, CA"
        },
        "unit": {
          "type": "string",
          "enum": [
            "celsius",
            "fahrenheit"
          ]
        }
      },
      "required": [
        "location",
        "unit"
      ]
    }
  }
]		 Opt-In 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.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.

[4] gen_ai.output.type: This attribute SHOULD be set to the output type requested by the client:

  • json for structured outputs with defined or undefined schema
  • image for image output
  • speech for speech output
  • text for plain text output

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

[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.

[11] gen_ai.input.messages: Instrumentations MUST follow Input messages JSON schema. When the attribute is recorded on events, it MUST be recorded in structured form. When recorded on spans, it MAY be recorded as a JSON string if structured format is not supported and SHOULD be recorded in structured form otherwise.

Messages MUST be provided in the order they were sent to the model. Instrumentations MAY provide a way for users to filter or truncate input messages.

[!Warning] This attribute is likely to contain sensitive information including user/PII data.

See Recording content on attributes section for more details.

[12] gen_ai.output.messages: Instrumentations MUST follow Output messages JSON schema

Each message represents a single output choice/candidate generated by the model. Each message corresponds to exactly one generation (choice/candidate) and vice versa - one choice cannot be split across multiple messages or one message cannot contain parts from multiple choices.

When the attribute is recorded on events, it MUST be recorded in structured form. When recorded on spans, it MAY be recorded as a JSON string if structured format is not supported and SHOULD be recorded in structured form otherwise.

Instrumentations MAY provide a way for users to filter or truncate output messages.

[!Warning] This attribute is likely to contain sensitive information including user/PII data.

See Recording content on attributes section for more details.

[13] gen_ai.system_instructions: This attribute SHOULD be used when the corresponding provider or API allows to provide system instructions or messages separately from the chat history.

Instructions that are part of the chat history SHOULD be recorded in gen_ai.input.messages attribute instead.

Instrumentations MUST follow System instructions JSON schema.

When recorded on spans, it MAY be recorded as a JSON string if structured format is not supported and SHOULD be recorded in structured form otherwise.

Instrumentations MAY provide a way for users to filter or truncate system instructions.

[!Warning] This attribute may contain sensitive information.

See Recording content on attributes section for more details.

[14] gen_ai.tool.definitions: The value of this attribute matches source system tool definition format.

It's expected to be an array of objects where each object represents a tool definition. In case a serialized string is available to the instrumentation, the instrumentation SHOULD do the best effort to deserialize it to an array. When recorded on spans, it MAY be recorded as a JSON string if structured format is not supported and SHOULD be recorded in structured form otherwise.

Since this attribute could be large, it's NOT RECOMMENDED to populate it by default. Instrumentations MAY provide a way to enable populating this attribute.

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

Embedding

See common embedding span definition.

Metrics

Azure AI Inference metrics follow generic Generative AI metrics.