View  usage metrics for each LLM used 
=====================================


Overview 
--------

Users can view their usage metrics for each large language model (LLM) they've used, regardless of whether the LLM is currently configured or unconfigured.


Example 
-------


.. code-block:: python

    from h2ogpte import H2OGPTE

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

    # The available units for time intervals are:
    # - minute / minutes (for example, 5 minutes)
    # - hour / hours (for example, 2 hours)
    # - day / days (for example, 3 days)
    # - week / weeks (for example, 1 week)
    # - year / years (for example, 1 year)
    list = client.get_llm_usage_by_llm(interval="1 month")

    for llm in list: 
        print(
        f"Call count: {llm.call_count}\n"
        f"Input tokens: {llm.input_tokens}\n"
        f"LLM cost: {llm.llm_cost}\n"
        f"LLM name: {llm.llm_name}\n"
        f"Model computed fields: {llm.model_computed_fields}\n"
        f"Model configuration: {llm.model_config}\n"
        f"Model fields: {llm.model_fields}\n"
        f"Output tokens: {llm.output_tokens}"
        )
        print("--" * 50)


.. code-block:: text

    Call count: 7
    Input tokens: 256952
    LLM cost: 0.998826
    LLM name: claude-3-5-sonnet-20240620
    Model computed fields: {}
    Model configuration: {}
    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: 15198
    ----------------------------------------------------------------------------------------------------
    Call count: 9
    Input tokens: 76554
    LLM cost: 0.02205975
    LLM name: claude-3-haiku-20240307
    Model computed fields: {}
    Model configuration: {}
    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: 2337
    ....