API Reference

Complete API documentation for all CAIS modules, classes, and functions. This reference provides detailed information about parameters, return values, and usage examples for every public interface.

API Overview

The CAIS API is organized into several key modules:

causal_agent

Causal Agent - Automated Causal Inference with Large Language Models.

Core Components
  • causal_agent.agent.CausalAgent: Main interface for causal analysis

  • causal_agent.components.dataset_analyzer.DatasetAnalyzer: Data validation and preprocessing

  • causal_agent.components.decision_tree.DecisionTree: Automatic method selection logic

  • causal_agent.components.explanation_generator.ExplanationGenerator: Result formatting and explanation

Causal Methods
Tools and Utilities

Quick Reference

Basic Usage

from causal_agent import CausalAgent

agent = CausalAgent()
result = agent.analyze(data, treatment, outcome)

Method-Specific Analysis

from causal_agent.methods import DifferenceInDifferences

did = DifferenceInDifferences()
result = did.estimate(data, treatment, outcome, time_var)

Custom Configuration

from causal_agent import CausalAgent, Config

config = Config(llm_provider="openai", model="gpt-4")
agent = CausalAgent(config=config)