UpTrainDataSchema#

class langchain_community.callbacks.uptrain_callback.UpTrainDataSchema(project_name: str)[source]#

The UpTrain data schema for tracking evaluation results.

Parameters:

project_name (str) – The project name to be shown in UpTrain dashboard.

project_name#

The project name to be shown in UpTrain dashboard.

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)

Initialize the UpTrain data schema.

__init__(project_name: str) None[source]#

Initialize the UpTrain data schema.

Parameters:

project_name (str) –

Return type:

None