Changelog

This document tracks all notable changes to the Causal Agent project.

Version 0.1.2 (Current)

Released: October 2025

Improvements

  • Build System Enhancement: Fixed scipy version compatibility issues with statsmodels

  • Documentation Build: Resolved langchain import dependencies for ReadTheDocs builds

  • Package Distribution: Improved wheel and source distribution generation for PyPI

  • Testing Infrastructure: Enhanced local build testing and validation processes

  • Dependency Management: Added proper autodoc mock imports for documentation generation

Bug Fixes

  • Fixed scipy version constraint to prevent conflicts with statsmodels (scipy>=1.10,<1.15)

  • Resolved langchain import errors during documentation builds

  • Fixed missing dependencies in docs/requirements.txt for proper Sphinx builds

  • Corrected autodoc configuration to handle unavailable imports gracefully

Technical Improvements

  • Enhanced pyproject.toml configuration for better package metadata

  • Improved build process reliability for both wheel and source distributions

  • Added comprehensive local testing workflow before PyPI releases

  • Better error handling for missing optional dependencies

  • Critical Fix: Added missing langchain>=0.3.26 dependency to prevent import errors

  • Dependency Update: Updated dowhy to version 0.12 for better compatibility

Version 0.1.1

New Features

  • Enhanced Decision Tree Logic: Improved method selection algorithm with better handling of edge cases

  • Synthetic Data Generation: Added comprehensive synthetic data generation system for testing and validation

  • Interactive Documentation: Added interactive decision tree visualization and method selection tools

  • Batch Processing: Enhanced support for processing multiple datasets in batch mode

  • LLM Provider Support: Added support for multiple LLM providers (OpenAI, Anthropic, Google)

Improvements

  • Performance Optimization: Reduced memory usage and improved processing speed for large datasets

  • Error Handling: Better error messages and recovery mechanisms throughout the system

  • Documentation: Comprehensive documentation overhaul with ReadTheDocs integration

  • Testing Framework: Expanded test coverage with integration and performance tests

  • Code Quality: Improved code organization and added type hints throughout

Bug Fixes

  • Fixed issue with propensity score matching when treatment groups are highly imbalanced

  • Resolved memory leak in batch processing mode

  • Fixed incorrect confidence interval calculations for difference-in-differences estimator

  • Corrected handling of missing values in instrumental variable analysis

  • Fixed visualization rendering issues in Jupyter notebooks

Breaking Changes

  • Changed API for custom method registration (see migration guide)

  • Updated configuration file format for LLM providers

  • Renamed several internal classes for consistency (backward compatibility maintained through deprecation warnings)

Dependencies

  • Updated pandas to 2.1.0+ for better performance

  • Added support for Python 3.11 and 3.12

  • Updated scikit-learn to 1.3.0+ for improved estimators

  • Added optional dependencies for enhanced visualization

Version 0.1.0

Initial Release

This is the first public release of the Causal AI Scientist, featuring:

Core Features

  • Autonomous Agent Architecture: LLM-powered agent for automated causal inference

  • Decision Tree Algorithm: Sophisticated method selection based on dataset properties

  • Multiple Causal Methods: Support for RCT, DiD, IV, RDD, PSM, and observational methods

  • Automated Analysis Pipeline: End-to-end analysis from data input to result interpretation

  • Result Interpretation: Natural language explanations of causal analysis results

Supported Methods

  • Experimental Methods

    • Randomized Controlled Trials (RCT)

    • Difference in Means

    • Difference-in-Differences (DiD)

    • Instrumental Variables (IV)

    • Regression Discontinuity Design (RDD)

  • Observational Methods

    • Propensity Score Matching

    • Propensity Score Weighting

    • Backdoor Adjustment

    • Linear Regression

Technical Infrastructure

  • Python Package: Installable via pip with comprehensive API

  • CLI Interface: Command-line tool for batch processing

  • Jupyter Integration: Seamless integration with Jupyter notebooks

  • Extensible Architecture: Plugin system for adding new methods

  • Comprehensive Testing: Unit, integration, and end-to-end tests

Documentation

  • Getting Started Guide: Step-by-step installation and first analysis

  • API Documentation: Complete reference for all functions and classes

  • Method Documentation: Detailed explanation of each causal inference method

  • Tutorials: Jupyter notebook tutorials for different domains

  • Case Studies: Real-world examples across education, healthcare, and economics

Contributing to Changelog

When contributing to CAIS, please help maintain this changelog by:

  • Adding entries for new features, improvements, and bug fixes

  • Following the format established in this document

  • Including breaking changes and migration information

  • Updating the “Known Issues” section as appropriate

For more information on contributing, see our ../development/contributing guide.

Release Process

Our release process follows these steps:

  1. Feature Development: New features developed in feature branches

  2. Testing: Comprehensive testing including unit, integration, and performance tests

  3. Documentation: Update documentation and changelog

  4. Review: Code review and approval process

  5. Release Candidate: Create release candidate for final testing

  6. Release: Tag release and publish to PyPI

  7. Announcement: Announce release to community

Release Schedule

  • Major Releases (x.0.0): Every 6-12 months with significant new features

  • Minor Releases (x.y.0): Every 2-3 months with new features and improvements

  • Patch Releases (x.y.z): As needed for bug fixes and security updates

Support Policy

  • Current Version: Full support with new features and bug fixes

  • Previous Minor Version: Bug fixes and security updates for 6 months

  • Older Versions: Security updates only for critical vulnerabilities

Contact for Release Information

  • Release Notifications: Watch our GitHub repository for release notifications

  • Beta Testing: Join our beta testing program by contacting cais-team@your-org.com

  • Release Questions: Open an issue on GitHub or email cais-team@your-org.com