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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

0.8.0 - 2026-02-02

Added

  • LearningMachine-backed agent learning with culture updates and reasoning tools for synthesis agents
  • Event-driven token usage tracking from model request events

Changed

  • Upgraded Agno dependency to >=2.4.7
  • BREAKING: Routing simplified to mandatory full_exploration (legacy single/double/triple strategy modes removed)
  • Workflow now runs complexity analysis + full sequence only (condition-based simple/full branching removed)
  • Forced strategy validation now rejects legacy strategy keys and accepts only full_exploration
  • sequentialthinking tool contract now documents multi-step loop orchestration in tool description and input schema metadata
  • sequentialthinking now publishes outputSchema and returns structuredContent control fields (should_continue, next_thought_number, stop_reason, and parameter guidance)
  • Tool description and usage guidance now explicitly require active reflection (isRevision=true when correcting prior steps)

Fixed

  • Fixed type error in thinking sequence synthesis in MultiThinkingSequentialProcessor

0.7.0 - 2025-09-24

Added

  • Parallel execution for thinking agents to improve processing performance
  • Comprehensive Mermaid diagrams in documentation showing parallel processing flows
  • Detailed agent descriptions in README files with multi-dimensional thinking methodology
  • Comparison table with original TypeScript version highlighting architectural differences

Changed

  • PERFORMANCE: Converted non-synthesis agents to run in parallel using asyncio.gather for significant speed improvements
  • GROQ PROVIDER: Updated Groq provider to use OpenAI GPT-OSS models (openai/gpt-oss-120b for enhanced, openai/gpt-oss-20b for standard)
  • Complete restructure of README files with cleaner formatting and better organization
  • Improved documentation clarity by removing all emoji characters from codebase and documentation

Fixed

  • Resolved MetricsLogger import error that was preventing server startup
  • Fixed missing MetricsLogger class implementation in logging configuration
  • Corrected Mermaid diagram syntax errors in README files
  • Removed references to non-existent PerformanceTracker class

0.5.0 - 2025-09-17

Added

  • Comprehensive TDD test coverage for refactoring and quality improvement
  • Default settings and processing strategy enum for enhanced configuration
  • Adaptive architecture with cost optimization capabilities
  • Comprehensive test infrastructure and unit tests
  • Magic number extraction to constants for better maintainability

Changed

  • BREAKING: Migration to Agno v2.0 with architectural updates (~10,000x faster agent creation, ~50x less memory usage)
  • Upgraded Agno to version 2.0.5 with enhanced agent features
  • Reorganized types module and cleaned duplicates for better structure
  • Modernized codebase with enhanced type safety and annotations
  • Adopted src layout for Python project structure following best practices
  • Optimized code structure and performance across modules

Fixed

  • Resolved mypy type checking errors across all modules
  • Comprehensive security and quality improvements
  • Updated minimum Agno version to 2.0.5 for compatibility

Documentation

  • Updated CLAUDE.md with Agno v2.0 migration details and corrected commands
  • Enhanced guidance for src layout and development requirements
  • Improved test documentation and GitHub provider information

0.4.1 - 2025-08-06

Fixed

  • app_lifespan function signature for FastMCP compatibility

Changed

  • Restructured main.py with modular architecture for better maintainability

0.4.0 - 2025-08-06

Added

  • Support for Kimi K2 model via OpenRouter integration
  • Enhanced model provider options and configuration flexibility

Changed

  • CHANGELOG.md following Keep a Changelog standards
  • Moved changelog from README.md to dedicated CHANGELOG.md file

0.3.0 - 2025-08-01

Added

  • Support for Ollama FULL LOCAL (no API key needed, but requires Ollama installed and running locally)
  • Local LLM inference capabilities through Ollama integration
  • Enhanced model configuration options for local deployment
  • MseeP.ai security assessment badge

Changed

  • Restored DeepSeek as default LLM provider
  • Improved package naming and configuration
  • Updated dependencies to support local inference
  • Enhanced agent memory management (disabled for individual agents)

Fixed

  • Package naming issues in configuration
  • Dependency conflicts resolved
  • Merge conflicts between branches

0.2.3 - 2025-04-22

Changed

  • Updated version alignment in project configuration and lock file

0.2.2 - 2025-04-10

Changed

  • Default agent model ID for DeepSeek changed from deepseek-reasoner to deepseek-chat
  • Improved model selection recommendations

0.2.1 - 2025-04-10

Changed

  • Model selection recommendations updated in documentation
  • Enhanced guidance for coordinator vs specialist model selection

0.2.0 - 2025-04-06

Added

  • Major refactoring of sequential thinking team structure
  • Enhanced coordination logic
  • Improved JSON output format
  • LLM configuration and model selection enhancements

Changed

  • Agent model IDs updated for better performance
  • Project structure improvements

0.1.3 - 2025-04-06

Changed

  • Project entry point script from main:main to main:run
  • Updated documentation for improved user guidance
  • Cleaned up dependencies in lock file

0.1.0 - 2025-04-06

Added

  • Initial project structure and configuration files
  • Multi-Agent System (MAS) architecture using Agno framework
  • Sequential thinking tool with coordinated specialist agents
  • Support for multiple LLM providers (DeepSeek, Groq, OpenRouter)
  • Pydantic validation for robust data integrity
  • Integration with external tools (Exa for research)
  • Structured logging with file and console output
  • Support for thought revisions and branching
  • MCP server implementation with FastMCP
  • Distributed intelligence across specialized agents