Clean string values for schema.
Cleans the input text by replacing newline and carriage return characters.
Sanitize the input dictionary or list.
Sanitizes the input by removing embedding-like values, lists with more than 128 elements, that are mostly irrelevant for generating answers in a LLM context. These properties, if left in results, can occupy significant context space and detract from the LLM's performance by introducing unnecessary noise and cost.
Represents a graph document consisting of nodes and relationships.
Abstract class for graph operations.
Neo4j database wrapper for various graph operations.
Parameters: url (Optional[str]): The URL of the Neo4j database server. username (Optional[str]): The username for database authentication. password (Optional[str]): The password for database authentication. database (str): The name of the database to connect to. Default is 'neo4j'. timeout (Optional[float]): The timeout for transactions in seconds. Useful for terminating long-running queries. By default, there is no timeout set. sanitize (bool): A flag to indicate whether to remove lists with more than 128 elements from results. Useful for removing embedding-like properties from database responses. Default is False. refresh_schema (bool): A flag whether to refresh schema information at initialization. Default is True. enhanced_schema (bool): A flag whether to scan the database for example values and use them in the graph schema. Default is False. driver_config (Dict): Configuration passed to Neo4j Driver.
Security note: Make sure that the database connection uses credentials that are narrowly-scoped to only include necessary permissions. Failure to do so may result in data corruption or loss, since the calling code may attempt commands that would result in deletion, mutation of data if appropriately prompted or reading sensitive data if such data is present in the database. The best way to guard against such negative outcomes is to (as appropriate) limit the permissions granted to the credentials used with this tool.
See https://python.langchain.com/docs/security for more information.