Source: https://docs.nygen.io/CyteOnto/api/usage.html
Revision: cb82698da3fc9e2bc385eb9a70e07f9304835eba

Usage records
*************

"CyteOnto.usage" is an "AgentUsage" that adds up the requests and
tokens of the successful LLM calls of the instance, to describe and to
split labels, including those of "from_config()". Failed attempts are
not counted. "CyteOnto.model_pair_usage" is a "ModelPairUsage" that
records whether the primary or the fallback models were used.

   print(cyto.usage.requests, cyto.usage.totalTokens)
   print(cyto.model_pair_usage.to_status_dict())

"model_pair_usage.embedding" is the full embedding configuration,
including its "apiKey", so print or log "to_status_dict()", which
holds only the names. Models and providers explains when the fallback
models are used.

class cyteonto.AgentUsage(*, agentName='', modelName='', requests=0, inputTokens=0, outputTokens=0, totalTokens=0, toolUsage=<factory>)

   Tally of LLM calls made through a given agent.

   agentName: str = ''

      Name of the agent, "CyteOnto" for "CyteOnto.usage".

   modelName: str = ''

      The model id.

   requests: int = 0

      Number of model requests, including the requests that follow
      tool calls.

   inputTokens: int = 0

      Number of input tokens.

   outputTokens: int = 0

      Number of output tokens.

   totalTokens: int = 0

      Number of input and output tokens.

   toolUsage: dict[str, int] = {}

      Number of calls of each tool, such as "get_pubmed_abstracts".

   record(model_name, run_usage, tool_counts=None)

      Add the usage of one pydantic-ai run and its tool calls.

      Return type:
         "None"

   merge(other)

      Add the counts of "other" to this tally.

      Return type:
         "None"

class cyteonto.ModelPairUsage(*, llmTier='primary', embeddingTier='primary', llm, embedding)

   Which model pair tiers were used during a run.

   llmTier: str = 'primary'

      "primary" until the fallback agent is asked to describe labels,
      then "mixed". The type also allows "fallback".

   embeddingTier: str = 'primary'

      Which models made the label embeddings that were matched, new or
      cached: "primary", "fallback", or "mixed" for both. Embedding
      the ontology terms does not count.

   llm: cyteonto.LlmConfig

      Required. The primary LLM, replaced by "fallback_llm", if one
      was passed, when "llmTier" becomes "mixed".

   embedding: cyteonto.EmbdConfig

      Required. The primary embedding configuration, replaced by the
      fallback configuration once labels are matched with its
      embeddings.

   to_status_dict()

      Return the tiers and the provider and model names as strings.

      Return type:
         "dict"["str", "str"]