309 lines
11 KiB
YAML
309 lines
11 KiB
YAML
groups:
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- id: gen_ai.common.event.attributes
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type: attribute_group
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stability: experimental
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brief: >
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Describes common Gen AI event attributes.
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attributes:
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- ref: gen_ai.system
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- id: event.gen_ai.system.message
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name: gen_ai.system.message
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type: event
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stability: experimental
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brief: >
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This event describes the system instructions passed to the GenAI model.
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extends: gen_ai.common.event.attributes
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body:
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id: gen_ai.system.message
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requirement_level: opt_in
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type: map
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fields:
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- id: content
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type: undefined
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stability: experimental
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brief: >
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The contents of the system message.
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examples: ["You're a helpful bot"]
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requirement_level: opt_in
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- id: role
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type: string
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stability: experimental
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brief: >
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The actual role of the message author as passed in the message.
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examples: ["system", "instruction"]
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requirement_level:
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conditionally_required: if available and not equal to `system`.
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- id: event.gen_ai.user.message
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name: gen_ai.user.message
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type: event
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stability: experimental
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brief: >
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This event describes the user message passed to the GenAI model.
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extends: gen_ai.common.event.attributes
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body:
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id: gen_ai.user.message
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requirement_level: opt_in
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type: map
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fields:
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- id: content
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type: undefined
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stability: experimental
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brief: >
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The contents of the user message.
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examples: ["What's the weather in Paris?"]
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requirement_level: opt_in
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- id: role
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type: string
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stability: experimental
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brief: >
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The actual role of the message author as passed in the message.
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examples: ["user", "customer"]
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requirement_level:
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conditionally_required: if available and not equal to `user`.
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- id: event.gen_ai.assistant.message
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name: gen_ai.assistant.message
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type: event
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stability: experimental
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brief: >
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This event describes the assistant message passed to GenAI system.
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extends: gen_ai.common.event.attributes
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body:
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id: gen_ai.assistant.message
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requirement_level: opt_in
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type: map
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fields:
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- id: content
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type: undefined
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stability: experimental
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brief: >
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The contents of the tool message.
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examples: ["The weather in Paris is rainy and overcast, with temperatures around 57°F"]
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requirement_level: opt_in
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- id: role
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type: string
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stability: experimental
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brief: >
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The actual role of the message author as passed in the message.
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examples: ["assistant", "bot"]
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requirement_level:
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conditionally_required: if available and not equal to `assistant`.
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- id: tool_calls
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type: map[]
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stability: experimental
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brief: >
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The tool calls generated by the model, such as function calls.
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requirement_level:
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conditionally_required: if available
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fields:
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- id: id
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type: string
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stability: experimental
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brief: >
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The id of the tool call.
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examples: ["call_mszuSIzqtI65i1wAUOE8w5H4"]
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requirement_level: required
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- id: type
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type: enum
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members:
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- id: function
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value: 'function'
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brief: Function
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stability: experimental
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brief: >
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The type of the tool.
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examples: ["function"]
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requirement_level: required
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- id: function
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type: map
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stability: experimental
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brief: >
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The function call.
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requirement_level: required
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fields:
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- id: name
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type: string
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stability: experimental
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brief: >
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The name of the function.
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examples: ["get_weather"]
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requirement_level: required
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- id: arguments
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type: undefined
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stability: experimental
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brief: >
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The arguments of the function as provided in the LLM response.
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note: >
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Models usually return arguments as a JSON string. In this case, it's
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RECOMMENDED to provide arguments as is without attempting to deserialize them.
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Semantic conventions for individual systems MAY specify a different type for
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arguments field.
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examples: ['{\"location\": \"Paris\"}']
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requirement_level: opt_in
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- id: event.gen_ai.tool.message
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name: gen_ai.tool.message
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type: event
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stability: experimental
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brief: >
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This event describes the response from a tool or function call passed to the GenAI model.
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extends: gen_ai.common.event.attributes
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body:
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id: gen_ai.tool.message
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requirement_level: opt_in
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type: map
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fields:
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- id: content
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type: undefined
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stability: experimental
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brief: >
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The contents of the tool message.
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examples: ["rainy, 57°F"]
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requirement_level: opt_in
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- id: role
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type: string
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stability: experimental
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brief: >
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The actual role of the message author as passed in the message.
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examples: ["tool", "function"]
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requirement_level:
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conditionally_required: if available and not equal to `tool`.
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- id: id
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type: string
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stability: experimental
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brief: >
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Tool call id that this message is responding to.
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examples: ["call_mszuSIzqtI65i1wAUOE8w5H4"]
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requirement_level: required
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- id: event.gen_ai.choice
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name: gen_ai.choice
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type: event
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stability: experimental
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brief: >
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This event describes the Gen AI response message.
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extends: gen_ai.common.event.attributes
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body:
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id: gen_ai.choice
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requirement_level: opt_in
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type: map
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note: >
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If GenAI model returns multiple choices, each choice SHOULD be recorded as an individual event.
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When response is streamed, instrumentations that report response events MUST reconstruct and report
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the full message and MUST NOT report individual chunks as events.
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If the request to GenAI model fails with an error before content is received,
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instrumentation SHOULD report an event with truncated content (if enabled).
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If `finish_reason` was not received, it MUST be set to `error`.
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fields:
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- id: index
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type: int
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stability: experimental
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brief: >
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The index of the choice in the list of choices.
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examples: [0, 1]
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requirement_level: required
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- id: finish_reason
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type: enum
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members:
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- id: stop
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value: 'stop'
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stability: experimental
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brief: Stop
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- id: tool_calls
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value: 'tool_calls'
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stability: experimental
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brief: Tool Calls
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- id: content_filter
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value: 'content_filter'
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stability: experimental
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brief: Content Filter
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- id: length
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value: 'length'
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stability: experimental
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brief: Length
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- id: error
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value: 'error'
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stability: experimental
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brief: Error
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stability: experimental
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brief: >
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The reason the model stopped generating tokens.
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requirement_level: required
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- id: message
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type: map
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stability: experimental
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brief: >
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GenAI response message.
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requirement_level: recommended
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fields:
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- id: content
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type: undefined
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stability: experimental
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brief: >
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The contents of the assistant message.
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examples: ["The weather in Paris is rainy and overcast, with temperatures around 57°F"]
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requirement_level: opt_in
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- id: role
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type: string
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stability: experimental
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brief: >
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The actual role of the message author as passed in the message.
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examples: ["assistant", "bot"]
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requirement_level:
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conditionally_required: if available and not equal to `assistant`.
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- id: tool_calls
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type: map[]
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stability: experimental
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brief: >
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The tool calls generated by the model, such as function calls.
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requirement_level:
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conditionally_required: if available
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fields:
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- id: id
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type: string
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stability: experimental
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brief: >
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The id of the tool call.
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examples: ["call_mszuSIzqtI65i1wAUOE8w5H4"]
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requirement_level: required
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- id: type
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type: enum
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members:
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- id: function
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value: 'function'
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brief: Function
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stability: experimental
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brief: >
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The type of the tool.
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requirement_level: required
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- id: function
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type: map
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stability: experimental
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brief: >
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The function that the model called.
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requirement_level: required
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fields:
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- id: name
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type: string
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stability: experimental
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brief: >
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The name of the function.
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examples: ["get_weather"]
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requirement_level: required
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- id: arguments
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type: undefined
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stability: experimental
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brief: >
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The arguments of the function as provided in the LLM response.
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note: >
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Models usually return arguments as a JSON string. In this case, it's
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RECOMMENDED to provide arguments as is without attempting to deserialize them.
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Semantic conventions for individual systems MAY specify a different type for
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arguments field.
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examples: ['{\"location\": \"Paris\"}']
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requirement_level: opt_in
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