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satif_ai.adapters.tidy

execute_tidy_adaptation​

@function_tool
async def execute_tidy_adaptation(code: str) -> str

Tool implementation for the agent to execute the tidying adaptation code. Runs the code against a copy of the input SDIF, creating a new output SDIF, and returns a sample analysis of the modified output.

TidyAdapter Objects​

class TidyAdapter(Adapter)

Uses an AI agent (via agents library) to generate and execute Python code that transforms tables in an SDIF file into a tidy format using CodeAdapter.

__init__​

def __init__(mcp_server: MCPServer,
             mcp_session: ClientSession,
             llm_model: str = "o4-mini",
             max_iterations: int = 5)

Initialize the TidyAdapter.

Arguments:

  • mcp_server - An instance of MCPServer for agent communication.
  • mcp_session - An instance of ClientSession for resource/prompt fetching.
  • llm_model - Name of the language model to use for the agent.
  • max_iterations - Maximum number of attempts the agent gets to refine the code.

parse_code​

def parse_code(code_text: str) -> Optional[str]

Extracts Python code from markdown code blocks.

adapt​

async def adapt(sdif: Union[SDIFPath, SDIFDatabase]) -> Datasource

Transforms the data in the input SDIF to be tidy using an AI agent.

Arguments:

  • sdif - The input SDIF database instance. Connection will be closed.

Returns:

Path to the new SDIF file containing the tidied data.

Raises:

  • FileNotFoundError - If the input SDIF path doesn't exist.
  • RuntimeError - If the agent fails to produce valid tidy code.
  • Exception - For unexpected errors during the process.