> ## Documentation Index
> Fetch the complete documentation index at: https://tracevell.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# SDK Constants

> [tab] TypeScript
>
> LaminarAttributes
>
> Attribute constants for manual LLM span creation.
>
> ```typescript theme={null}
> import { LaminarAttributes } from '@lmnr-ai/lmnr';
>
> span.setAttributes({
>   [LaminarAttributes.PROVIDER]: 'anthropic',
>   [LaminarAttributes.REQUEST_MODEL]: 'claude-3-5-sonnet',
>   [LaminarAttributes.RESPONSE_MODEL]: response.model,
>   [LaminarAttributes.INPUT_TOKEN_COUNT]: response.usage.input_tokens,
>   [LaminarAttributes.OUTPUT_TOKEN_COUNT]: response.usage.output_tokens,
> });
> ```
>
> | Constant | Value | Description |
> | - | - | - |
> | `PROVIDER` | `gen_ai.system` | LLM provider name |
> | `REQUEST_MODEL` | `gen_ai.request.model` | Requested model |
> | `RESPONSE_MODEL` | `gen_ai.response.model` | Actual model used |
> | `INPUT_TOKEN_COUNT` | `gen_ai.usage.input_tokens` | Input tokens |
> | `OUTPUT_TOKEN_COUNT` | `gen_ai.usage.output_tokens` | Output tokens |
> | `TOTAL_TOKEN_COUNT` | `llm.usage.total_tokens` | Total tokens |
> | `INPUT_COST` | `gen_ai.usage.input_cost` | Input cost |
> | `OUTPUT_COST` | `gen_ai.usage.output_cost` | Output cost |
> | `TOTAL_COST` | `gen_ai.usage.cost` | Total cost |
>
> ***
>
> SpanType / TraceType
>
> ```typescript theme={null}
> import type { SpanType, TraceType } from '@lmnr-ai/lmnr';
>
> // SpanType:
> // 'DEFAULT' | 'LLM' | 'EXECUTOR' | 'EVALUATOR' | 'HUMAN_EVALUATOR'
> // | 'EVALUATION' | 'TOOL' | 'CACHED'
> //
> // TraceType: 'DEFAULT' | 'EVALUATION'
> ```

> [tab] Python
>
> Attributes
>
> Attribute constants for manual LLM span creation.
>
> ```python theme={null}
> from lmnr import Tracevell, Attributes
>
> Laminar.set_span_attributes({
>     Attributes.PROVIDER: "anthropic",
>     Attributes.REQUEST_MODEL: "claude-3-5-sonnet",
>     Attributes.RESPONSE_MODEL: response["model"],
>     Attributes.INPUT_TOKEN_COUNT: response["usage"]["input_tokens"],
>     Attributes.OUTPUT_TOKEN_COUNT: response["usage"]["output_tokens"],
> })
> ```
>
> | Constant | Value | Description |
> | - | - | - |
> | `PROVIDER` | `gen_ai.system` | LLM provider name |
> | `REQUEST_MODEL` | `gen_ai.request.model` | Requested model |
> | `RESPONSE_MODEL` | `gen_ai.response.model` | Actual model used |
> | `INPUT_TOKEN_COUNT` | `gen_ai.usage.input_tokens` | Input tokens |
> | `OUTPUT_TOKEN_COUNT` | `gen_ai.usage.output_tokens` | Output tokens |
> | `TOTAL_TOKEN_COUNT` | `gen_ai.usage.total_tokens` | Total tokens |
> | `INPUT_COST` | `gen_ai.usage.input_cost` | Input cost |
> | `OUTPUT_COST` | `gen_ai.usage.output_cost` | Output cost |
> | `TOTAL_COST` | `gen_ai.usage.cost` | Total cost |
> | `RESPONSE_ID` | `gen_ai.response.id` | Response ID |
>
> ***
>
> SpanType / TraceType
>
> ```python theme={null}
> from lmnr import SpanType, TraceType
>
> # SpanType: DEFAULT, LLM, TOOL, EXECUTOR, EVALUATOR, HUMAN_EVALUATOR, EVALUATION
> #   (PIPELINE is reserved internally)
> # TraceType: DEFAULT, EVALUATION
> ```


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