Module: braid.module

Main BRAID reasoning module for DSPy.

class braid.module.BraidResult(problem: str, grd: str, parsed_grd: GRDStructure | None, reasoning_steps: List[Dict[str, Any]], answer: str, execution_trace: List[Dict[str, Any]], valid: bool, error: str | None = None)

Bases: object

Result object returned by BraidReasoning module.

problem: str

grd: str

parsed_grd: GRDStructure | None

reasoning_steps: List[Dict[str, Any]]

answer: str

execution_trace: List[Dict[str, Any]]

valid: bool

error: str | None = None

__init__(problem: str, grd: str, parsed_grd: GRDStructure | None, reasoning_steps: List[Dict[str, Any]], answer: str, execution_trace: List[Dict[str, Any]], valid: bool, error: str | None = None) → None

class braid.module.BraidReasoning(*args, **kwargs)

Bases: Module

BRAID reasoning module for DSPy.

This module implements the BRAID (Bounded Reasoning for Autonomous Inference and Decisions) architecture: 1. Planning Phase: Generate a Guided Reasoning Diagram (GRD) in Mermaid format 2. Execution Phase: Execute the GRD step by step to solve the problem

Example

>>> import dspy
>>> from braid import BraidReasoning
>>>
>>> lm = dspy.OpenAI(model="gpt-4")
>>> dspy.configure(lm=lm)
>>>
>>> braid = BraidReasoning()
>>> result = braid(problem="If a train travels 120 km in 2 hours, what is its speed?")
>>> print(result.answer)
>>> print(result.grd)

__init__(use_generator: bool = True, max_execution_steps: int = 20, validate_grd: bool = True)

Initialize the BRAID reasoning module.

Parameters:

• use_generator – Whether to use GRDGenerator for planning (True) or direct LLM call (False)

• max_execution_steps – Maximum number of steps to execute

• validate_grd – Whether to validate GRD syntax before execution

forward(problem: str, grd: str | None = None, problem_type: str | None = None) → BraidResult

Execute BRAID reasoning on a problem.

Parameters:

• problem – The problem to solve

• grd – Optional pre-generated GRD (if None, will be generated)

• problem_type – Optional problem type hint for generation

Returns:

BraidResult object containing GRD, reasoning steps, and answer

__call__(problem: str, **kwargs) → BraidResult

Make the module callable.