cuery.tools.flex.generic#

Tool(s) to iterate over data with a response model defined by json schemas.

The idea is to first generate a schema with an LLM using the SchemaGenerator tool, then use that schema process records with the Generic tool.

Attributes#

GENERIC_PROMPT

SCHEMA_CONVERSION_PROMPT

Classes#

Generic

Tools that iterates over records with a JSON-schema response model.

Auto

Fully automatic, general-purpose tool for processing data records.

Module Contents#

cuery.tools.flex.generic.GENERIC_PROMPT = ''#
cuery.tools.flex.generic.SCHEMA_CONVERSION_PROMPT = ''#
class cuery.tools.flex.generic.Generic(/, **data)#

Bases: cuery.tools.flex.base.FlexTool

Tools that iterates over records with a JSON-schema response model.

Parameters:

data (Any)

response_schema: dict#

JSON schema used as response model.

instructions: str#

Instructions for the tool, describing its purpose and how to use it.

property prompt: cuery.Prompt#

Generate a prompt string based on the instructions and current schema.

Return type:

cuery.Prompt

property response_model: cuery.ResponseClass#

Defines the response model for this tool (ClassVar or property).

Return type:

cuery.ResponseClass

class cuery.tools.flex.generic.Auto(/, **data)#

Bases: Generic

Fully automatic, general-purpose tool for processing data records.

First auto-generates a response model from the response model instructions, then iterates over the records using that model and the provided tools instructions.

Parameters:

data (Any)

response_schema: str | dict | None = None#

Instructions to generate a JSON schema used as response model.

schema_model: str = None#

Specific model to use to generate the JSON schema.

_response: cuery.ResponseSet | None = None#
property prompt: cuery.Prompt#

Generate a prompt string based on the instructions and current schema.

Return type:

cuery.Prompt

async response_model()#

Defines the response model for this tool (ClassVar or property).

Return type:

cuery.ResponseClass

async task()#

Create a Task instance for this tool.

Return type:

cuery.Task

async __call__(**kwargs)#

Normalize the nested input records back into individual columns in output.

Return type:

pandas.DataFrame