View usage cost metrics for used LLMs in the past 24 hours
==========================================================

Overview 
--------

A user can retrieve specific metrics related to a particular large language model (LLM) and its usage costs within the past 24 hours. Specifically, the user can obtain certain usage cost metrics for all LLMs involved in making a specific LLM request within that timeframe.

Example 
-------


.. code-block:: python

    from h2ogpte import H2OGPTE

    client = H2OGPTE(
        address="https://h2ogpte.genai.h2o.ai",
        api_key='sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX',
    )

    list = client.get_llm_usage_24h_by_llm()

    print(f"""\
    Call count: {list[0].call_count}
    Input tokens: {list[0].input_tokens}
    LLM cost: {list[0].llm_cost}
    LLM name: {list[0].llm_name}
    Model computed fields: {list[0].model_computed_fields}
    Model config: {list[0].model_config}
    Model fields: {list[0].model_fields}
    Output tokens: {list[0].output_tokens}
    """)


.. code-block:: text

    Call count: 2
    Input tokens: 132
    LLM cost: 5.02e-05
    LLM name: h2oai/h2o-danube3-4b-chat
    Model computed fields: {}
    Model config: {}
    Model fields: {'llm_name': FieldInfo(annotation=str, required=True), 'llm_cost': FieldInfo(annotation=float, required=True), 'call_count': FieldInfo(annotation=int, required=True), 'input_tokens': FieldInfo(annotation=int, required=True), 'output_tokens': FieldInfo(annotation=int, required=True)}
    Output tokens: 148