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LogSpanVariable

Variable attached to a Model or ModelStream span for evaluation tracking.

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Overview

LogSpanVariable pairs a variable name with a content value. When attached to a LogSpanModelContent or LogSpanModelStreamContent span, the variable is available for continuous evaluations in Adaline. 
from adaline_api.models.log_span_variable import LogSpanVariable

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Fields

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name
str
required
The variable name. 1–200 characters.
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value
LogSpanVariableValue
required
The variable’s content value. LogSpanVariableValue is a discriminated union (on modality) that wraps one of: TextContent, ImageContent, PdfContent, ReasoningContent, ToolCallContent, or ToolResponseContent.

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LogSpanVariableValue

The value field accepts any content type supported by the Adaline message schema, wrapped in a LogSpanVariableValue union via actual_instance. 
from adaline_api.models.log_span_variable_value import LogSpanVariableValue
Content TypeModalityDescription
TextContent"text"Plain text content
ImageContent"image"Image content (URL or base64)
PdfContent"pdf"PDF document content
ReasoningContent"reasoning"Model reasoning/chain-of-thought
ToolCallContent"tool-call"Tool invocation request
ToolResponseContent"tool-response"Tool execution result

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Examples

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Text Variable

from adaline_api.models.log_span_variable import LogSpanVariable
from adaline_api.models.text_content import TextContent

variable = LogSpanVariable(
    name="user_question",
    value=TextContent(modality="text", value="What is quantum computing?")
)

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Image Variable

from adaline_api.models.log_span_variable import LogSpanVariable
from adaline_api.models.image_content import ImageContent
from adaline_api.models.image_content_value import ImageContentValue

variable = LogSpanVariable(
    name="uploaded_image",
    value=ImageContent(
        modality="image",
        detail="high",
        value=ImageContentValue.from_dict({
            "type": "url",
            "url": "https://example.com/image.jpg"
        })
    )
)

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Attaching to a Model Span

import json
from adaline_api.models.log_span_content import LogSpanContent
from adaline_api.models.log_span_model_content import LogSpanModelContent
from adaline_api.models.log_span_variable import LogSpanVariable
from adaline_api.models.text_content import TextContent

span.update({
    "status": "success",
    "content": LogSpanContent(
        actual_instance=LogSpanModelContent(
            type="Model",
            provider="openai",
            model="gpt-4o",
            input=json.dumps(params),
            output=json.dumps(response.model_dump()),
            variables=LogSpanVariable(
                name="user_question",
                value=TextContent(
                    modality="text",
                    value="Explain quantum computing simply."
                )
            ),
        )
    ),
})

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Serialization

from adaline_api.models.log_span_variable import LogSpanVariable
from adaline_api.models.text_content import TextContent

variable = LogSpanVariable(
    name="user_question",
    value=TextContent(modality="text", value="Hello")
)

d = variable.to_dict()
j = variable.to_json()

restored = LogSpanVariable.from_dict(d)
restored = LogSpanVariable.from_json(j)

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JSON Example

{
  "name": "user_question",
  "value": {
    "modality": "text",
    "value": "What is quantum computing?"
  }
}