qA_Ap.app.ai.methods

module documentation

Undocumented

Function	`initialize_vector_store`	Initializes the vector store from the database, or creates it if not found or fails.
Function	`vectorize_documents`	Create a vector store from all documents then save it in the database.
Function	`_context_from_query_results`	Builds a context string from query results for prompt construction.
Function	`_metadata_from_query_results`	Builds a context string from query results for prompt construction.

def initialize_vector_store(): ¶

Initializes the vector store from the database, or creates it if not found or fails.

def vectorize_documents(): ¶

Create a vector store from all documents then save it in the database. Raises: RuntimeError: If vectorization or saving fails.

@staticmethod

def _context_from_query_results(results: list[dict[str, any]]) -> str: ¶

Builds a context string from query results for prompt construction. Args: results (list[dict[str, any]]): list of query result dictionaries. Returns: str: Formatted context string.

@staticmethod

def _metadata_from_query_results(results: list[dict[str, any]]) -> str: ¶

Builds a context string from query results for prompt construction. Args: results (list[dict[str, any]]): list of query result dictionaries. Returns: str: Formatted context string.