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# `langchain_community.callbacks.uptrain_callback`.UpTrainDataSchema

class langchain_community.callbacks.uptrain_callback.UpTrainDataSchema(project_name_prefix: str)

  The UpTrain data schema for tracking evaluation results.

  Parameters

    project_name_prefix (str) – Prefix for the project name.

  project_name_prefix

    Prefix for the project name.

    Type

      str

  uptrain_results

    Dictionary to store evaluation results.

    Type

      DefaultDict[str, Any]

  eval_types

    Set to store the types of evaluations.

    Type

      Set[str]

  query

    Query for the RAG evaluation.

    Type

      str

  context

    Context for the RAG evaluation.

    Type

      str

  response

    Response for the RAG evaluation.

    Type

      str

  old_context

    Old context nodes for Context Conciseness evaluation.

    Type

      List[str]

  new_context

    New context nodes for Context Conciseness evaluation.

    Type

      List[str]

  context_conciseness_run_id

    Run ID for Context Conciseness evaluation.

    Type

      str

  multi_queries

    List of multi queries for Multi Query evaluation.

    Type

      List[str]

  multi_query_run_id

    Run ID for Multi Query evaluation.

    Type

      str

  multi_query_daugher_run_id

    Run ID for Multi Query daughter evaluation.

    Type

      str

  Initialize the UpTrain data schema.

  Methods

  `__init__`(project_name_prefix) | Initialize the UpTrain data schema.

  __init__(project_name_prefix: str) → None

    Initialize the UpTrain data schema.

    Parameters

      project_name_prefix (str) –

    Return type

      None