Changelog

Contents

Changelog#

Full Changelog#

Changelog#

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

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

Recent Releases#

v0.1.9 (November 7, 2025) - Session Management & Computer Use Tools Complete session management system with conversation restoration, computer use automation tools for browser and desktop control, enhanced config builder with fuzzy model matching, and expanded backend support.

v0.1.8 (November 5, 2025) - Automation Mode & DSPy Integration Complete automation infrastructure for LLM agents with real-time status tracking, silent execution mode, and DSPy-powered question paraphrasing for enhanced multi-agent diversity.

v0.1.7 (November 3, 2025) - Agent Task Planning & Background Execution Agent task planning system with dependency tracking, background shell execution for long-running commands, and preemption-based coordination for improved multi-agent workflows.

[0.1.9] - 2025-11-07#

Added#

  • Session Management System: Comprehensive session state tracking and restoration for multi-turn conversations

    • New massgen/session/ module with session state and registry management (530 lines total)

    • SessionState dataclass for complete session state including conversation history, workspace paths, and turn metadata (_state.py, 219 lines)

    • SessionRegistry for listing, managing, and restoring previous sessions (_registry.py, 311 lines)

    • restore_session() function for seamless session continuation across CLI invocations

    • Session metadata tracking including winning agents history and orchestrator turn data

    • Automatic session storage with unique identifiers and timestamps

    • Test suite in test_session_registry.py (201 lines)

  • Computer Use Tools: Browser and desktop automation capabilities for multi-agent workflows

    • General Computer Use Tool: OpenAI computer-use-preview integration for automated browser/computer control (massgen/tool/_computer_use/computer_use_tool.py, 741 lines)

      • Support for browser environment (Playwright) and Docker container execution

      • Action execution: click, type, scroll, navigate, screenshot analysis

      • Configurable max iterations and safety controls

    • Claude Computer Use Tool: Anthropic Claude Computer Use API integration (massgen/tool/_claude_computer_use/claude_computer_use_tool.py, 473 lines)

      • Native Claude Computer Use beta API support

      • Browser and desktop control with safety confirmations

      • Async execution with Playwright integration

    • Gemini Computer Use Tool: Google Gemini-based computer control (massgen/tool/_gemini_computer_use/gemini_computer_use_tool.py, 503 lines)

      • Gemini model integration for computer use workflows

      • Screenshot analysis and action generation

    • Browser Automation Tool: Lightweight browser automation for specific tasks (massgen/tool/_browser_automation/browser_automation_tool.py, 176 lines)

      • Focused browser automation without full computer use overhead

    • Comprehensive test suite in test_computer_use.py (629 lines)

  • OpenAI Operator API Handler: Support for OpenAI’s computer-use-preview model

    • New massgen/api_params_handler/_openai_operator_api_params_handler.py (72 lines)

    • Specialized parameter handling for computer use actions

    • Integration with computer use tool execution flow

Changed#

  • Config Builder Enhancement: Intelligent model matching and discovery

    • Fuzzy Model Name Matching: New massgen/utils/model_matcher.py (214 lines) allowing approximate model name input

    • Model Catalog System: New massgen/utils/model_catalog.py (218 lines) with curated lists of common models across providers

    • Enhanced massgen/config_builder.py with automatic model search and suggestions

    • Support for partial model names with intelligent completion (e.g., “sonnet” → “claude-sonnet-4-5-20250929”)

    • Contribution from acrobat3 (K. from JP)

  • Backend Capabilities Enhancement: Expanded provider support with six new backend registrations

    • Added Cerebras AI backend capabilities (llama models with WSE hardware acceleration)

    • Added Together AI backend capabilities (Meta-Llama, Mixtral models)

    • Added Fireworks AI backend capabilities (Llama, Qwen models with fast inference)

    • Added Groq backend capabilities (Llama, Mixtral with LPU hardware)

    • Added OpenRouter backend capabilities (unified access to 200+ models with audio/video support)

    • Added Moonshot (Kimi) backend capabilities (Chinese-optimized models with long context)

    • Updated massgen/backend/capabilities.py with comprehensive backend specifications

  • Memory System Improvement: Enhanced memory update logic for multi-agent coordination

    • New massgen/memory/_update_prompts.py (276 lines) with specialized update prompts for mem0

    • MASSGEN_UNIVERSAL_UPDATE_MEMORY_PROMPT: Philosophy for accumulating qualitative patterns vs statistics

    • Improved fact merging logic focusing on actionable tool usage patterns and technical insights

  • Chat Agent Enhancement: Session restoration and improved orchestrator restart handling

    • Session state restoration in massgen/chat_agent.py

    • Enhanced turn tracking and workspace persistence

    • Improved logging and coordination with orchestrator restarts

  • CLI Enhancement: Extended command-line interface for session management

    • Session listing and restoration commands in massgen/cli.py

    • Enhanced display selection and output formatting

    • Support for continuing previous sessions with automatic state restoration

Documentations, Configurations and Resources#

  • Diversity System Documentation: Comprehensive guide for increasing agent diversity

    • New docs/source/user_guide/diversity.rst (388 lines)

    • Covers answer novelty requirements (lenient/balanced/strict)

    • Documents DSPy question paraphrasing integration (from v0.1.8)

    • Best practices for multi-agent diversity strategies

    • Configuration examples and recommendations

  • Memory System Documentation: Updated memory user guide

    • Updated docs/source/user_guide/memory.rst with enhanced memory update logic and configuration

  • Computer Use Configuration Examples: Five YAML configurations demonstrating computer use capabilities

    • massgen/configs/tools/custom_tools/claude_computer_use_example.yaml: Claude-specific computer use

    • massgen/configs/tools/custom_tools/gemini_computer_use_example.yaml: Gemini-specific computer use

    • massgen/configs/tools/custom_tools/computer_use_example.yaml: General computer use with OpenAI

    • massgen/configs/tools/custom_tools/computer_use_docker_example.yaml: Docker-based computer use

    • massgen/configs/tools/custom_tools/computer_use_browser_example.yaml: Browser automation focus

  • Session Management Configuration: Example demonstrating session continuation

    • massgen/configs/memory/grok4_gpt5_gemini_mcp_filesystem_test_with_claude_code.yaml: Multi-turn session with MCP filesystem

  • Computer Use Documentation:

    • New massgen/backend/docs/COMPUTER_USE_TOOLS_GUIDE.md: Comprehensive guide for computer use tools (494 lines)

    • New scripts/computer_use_setup.md: Setup instructions for computer use tools

    • New scripts/setup_docker_cua.sh: Automated Docker setup script for computer use

Technical Details#

  • Major Focus: Session management with conversation restoration, computer use automation tools, intelligent config builder with fuzzy matching, expanded backend support, memory system enhancements

  • Contributors: @franklinnwren @ncrispino @Henry-811 and the MassGen team

[0.1.8] - 2025-11-05#

Added#

  • Automation Mode for LLM Agents: Complete infrastructure for running MassGen via LLM agents and programmatic workflows

    • New --automation CLI flag for silent execution with minimal output (~10 lines vs 250-3,000+)

    • New SilentDisplay class in massgen/frontend/displays/silent_display.py for automation-friendly output

    • Real-time status.json monitoring file updated every 2 seconds via enhanced CoordinationTracker

    • Meaningful exit codes: 0 (success), 1 (config error), 2 (execution error), 3 (timeout), 4 (interrupted)

    • Automatic workspace isolation for parallel execution with unique suffixes

    • Meta-coordination capabilities: MassGen running MassGen configurations

    • Automatic log directory creation and management for automation sessions

  • DSPy Question Paraphrasing Integration: Intelligent question diversity for multi-agent coordination

    • New massgen/dspy_paraphraser.py module with semantic-preserving paraphrasing (557 lines)

    • Three paraphrasing strategies: “diverse”, “balanced” (default), “conservative”

    • Configurable number of variants per orchestrator session

    • Automatic semantic validation using SemanticValidationSignature to ensure meaning preservation

    • Thread-safe caching system with SHA-256 hashing for performance

    • Support for all backends (Gemini, OpenAI, Claude, etc.) as paraphrasing engines

  • Case Study Summary: Comprehensive documentation of MassGen capabilities

    • New docs/CASE_STUDIES_SUMMARY.md providing centralized overview of 33 case studies (368 lines)

    • Organized by category: Release Features, Research, Travel, Creative, In Development, Planned

    • Covers versions v0.0.3 to v0.1.5 with status tracking and links to videos

    • Statistics: 19 completed, 8 with video demonstrations, 6 categories

Changed#

  • Orchestrator Enhancement: Integration of DSPy paraphrasing and automation tracking

    • Question variant distribution to different agents based on configured strategy

    • Improved coordination event logging with structured status exports

  • CLI Enhancement: Extended command-line interface for automation workflows

    • Enhanced display selection logic automatically choosing SilentDisplay in automation mode

    • Improved output formatting optimized for LLM agent parsing and monitoring

Documentations, Configurations and Resources#

  • Case Study: Meta-level self-analysis demonstrating automation mode

    • New docs/source/examples/case_studies/meta-self-analysis-automation-mode.md: Comprehensive case study showing MassGen analyzing its own v0.1.8 codebase using automation mode

  • Automation Documentation: Comprehensive guides for LLM agent integration

    • New AI_USAGE.md: Complete guide for LLM agents running MassGen (319 lines)

    • New docs/source/user_guide/automation.rst: Full automation guide with BackgroundShellManager patterns (890 lines)

    • New docs/source/reference/status_file.rst: Complete status.json schema reference with field-by-field documentation (565 lines)

    • Updated README.md and README_PYPI.md with automation mode sections (135 lines each)

  • DSPy Documentation: Complete implementation and usage guide

    • New massgen/backend/docs/DSPY_IMPLEMENTATION_GUIDE.md: Comprehensive DSPy integration guide (653 lines)

    • Covers quick start, configuration, strategies, troubleshooting, and semantic validation

    • Includes paraphrasing examples and best practices

  • Meta-Coordination Configurations: MassGen running MassGen examples

    • massgen/configs/meta/massgen_runs_massgen.yaml: Single agent autonomously running MassGen experiments

    • massgen/configs/meta/massgen_suggests_to_improve_massgen.yaml: Self-improvement configuration

    • Demonstrates automation mode usage for meta-coordination workflows

  • DSPy Configuration Example: New YAML configuration for DSPy-enabled coordination

    • massgen/configs/basic/multi/three_agents_dspy_enabled.yaml: Three-agent setup with DSPy paraphrasing

  • Case Study Summary Documentation: Centralized case study reference

    • New docs/CASE_STUDIES_SUMMARY.md: Comprehensive overview of all MassGen case studies with categorization and status tracking

Technical Details#

  • Major Focus: Automation infrastructure for LLM agents, DSPy-powered question paraphrasing, meta-coordination capabilities, comprehensive case study documentation

  • Contributors: @ncrispino @praneeth999 @franklinnwren @qidanrui @sonichi @Henry-811 and the MassGen team

[0.1.7] - 2025-11-03#

Added#

  • Agent Task Planning System: MCP-based task management with dependency tracking

    • New massgen/mcp_tools/planning/ module with dedicated planning server (_planning_mcp_server.py)

    • Task dataclasses with dependency validation and status management (planning_dataclasses.py)

    • Support for task states (pending/in_progress/completed/blocked) with automatic transitions based on dependencies

    • Orchestrator integration for plan-aware coordination

    • Test suite in test_planning_integration.py and test_planning_tools.py

  • Background Shell Execution: Long-running command support with persistent sessions

    • New BackgroundShell class in massgen/filesystem_manager/background_shell.py

    • Shell lifecycle management with output streaming and real-time monitoring

    • Automatic timeout handling for long-running processes

    • Enhanced code execution server with background execution capabilities

    • Test coverage in test_background_shell.py

  • Preemption Coordination: Multi-agent coordination with interruption support

    • Agents can preempt ongoing coordination to submit better answers without full restart

    • Enhanced coordination tracker with preemption event logging

    • Improved orchestrator logic to preserve partial progress during preemption

Fixed#

  • System Message Handling: Resolved system message extraction in Claude Code backend for background shell execution

  • Case Study Documentation: Fixed broken links and outdated examples in older case studies

Documentations, Configurations and Resources#

  • Documentation Updates: New user guides and design documentation

    • New docs/source/user_guide/agent_task_planning.rst: Task planning guide with usage patterns and API reference

    • Updated docs/source/user_guide/code_execution.rst: Added 122 lines for background shell usage

    • New docs/dev_notes/agent_planning_coordination_design.md: Comprehensive design document for agent planning and coordination system

    • New docs/dev_notes/preempt_not_restart_design.md: 456-line design document with preemption algorithms

    • Updated docs/source/development/architecture.rst: Added 61 lines for preemption coordination architecture

  • Configuration Examples: New YAML configurations demonstrating v0.1.7 features

    • example_task_todo.yaml: Task planning configuration

    • background_shell_demo.yaml: Background shell execution demonstration

Technical Details#

  • Major Focus: Agent task planning with dependencies, background command execution, preemption-based coordination

  • Contributors: @ncrispino @Henry-811 and the MassGen team

[0.1.6] - 2025-10-31#

Added#

  • Framework Interoperability: External agent framework integration as MassGen custom tools

    • New massgen/tool/_extraframework_agents/ module with 5 framework integrations

    • AG2 Lesson Planner Tool: Nested chat functionality wrapped as custom tool for multi-agent lesson planning (supports streaming)

    • LangGraph Lesson Planner Tool: LangGraph graph-based workflows integrated as tool

    • AgentScope Lesson Planner Tool: AgentScope agent system wrapped for lesson creation

    • OpenAI Assistants Lesson Planner Tool: OpenAI Assistants API integrated as tool

    • SmoLAgent Lesson Planner Tool: HuggingFace SmoLAgent integration for lesson planning

    • Enables MassGen agents to delegate tasks to specialized external frameworks

    • Each framework runs autonomously and returns results to MassGen orchestrator

    • Note: Only AG2 currently supports streaming; other frameworks return complete results

  • Configuration Validator: Comprehensive YAML configuration validation system

    • New ConfigValidator class in massgen/config_validator.py for pre-flight validation

    • Memory configuration validation with detailed error messages

    • Pre-commit hook integration for automatic config validation

    • Comprehensive test suite in massgen/tests/test_config_validator.py

    • Validates agent configurations, backend parameters, tool settings, and memory options

    • Provides actionable error messages with suggestions for common mistakes

Changed#

  • Backend Architecture Refactoring: Unified tool execution with ToolExecutionConfig

    • New ToolExecutionConfig dataclass in base_with_custom_tool_and_mcp.py for standardized tool handling

    • Refactored ResponseBackend with unified tool execution flow

    • Refactored ChatCompletionsBackend with unified tool execution flow

    • Refactored ClaudeBackend with unified tool execution methods

    • Eliminates duplicate code paths between custom tools and MCP tools

    • Consistent error handling and status reporting across all tool types

    • Improved maintainability and extensibility for future tool systems

  • Gemini Backend Simplification: Major architectural cleanup and consolidation

    • Removed gemini_mcp_manager.py module

    • Removed gemini_trackers.py module

    • Refactored gemini.py to use manual tool execution via base class

    • Streamlined tool handling and cleanup logic

    • Removed continuation logic and duplicate code

    • Updated _gemini_formatter.py for simplified tool conversion

    • Net reduction of 1,598 lines through consolidation

    • Improved maintainability and performance

  • Custom Tool System Enhancement: Improved tool management and execution

    • Enhanced ToolManager with category management capabilities

    • Improved tool registration and validation system

    • Enhanced tool result handling and error reporting

    • Better support for async tool execution

    • Improved tool schema generation for LLM consumption

Documentations, Configurations and Resources#

  • Framework Interoperability Examples: 8 new configuration files demonstrating external framework integration

    • AG2 Examples: ag2_lesson_planner_example.yaml, ag2_and_langgraph_lesson_planner.yaml, ag2_and_openai_assistant_lesson_planner.yaml

    • LangGraph Examples: langgraph_lesson_planner_example.yaml

    • AgentScope Examples: agentscope_lesson_planner_example.yaml

    • OpenAI Assistants Examples: openai_assistant_lesson_planner_example.yaml

    • SmoLAgent Examples: smolagent_lesson_planner_example.yaml

    • Multi-Framework Examples: two_models_with_tools_example.yaml

Technical Details#

  • Major Focus: Framework interoperability for external agent integration, unified tool execution architecture, Gemini backend simplification, and configuration validation system

  • Contributors: @Eric-Shang @praneeth999 @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.1.5] - 2025-10-29#

Added#

  • Memory System: Complete long-term memory implementation with semantic retrieval

    • New massgen/memory/ module with comprehensive memory management

    • PersistentMemory via mem0 integration for semantic fact storage and retrieval

    • ConversationMemory for short-term verbatim message tracking

    • Automatic Context Compression when approaching token limits

    • Memory Sharing for Multi-Turn Conversations with turn-aware filtering to prevent temporal leakage

    • Session Management for memory isolation and continuation across runs

    • Qdrant Vector Database Integration for efficient semantic search (server and local modes)

    • Context Monitoring with real-time token usage tracking

    • Fact extraction prompts with customizable LLM and embedding providers

    • Supports OpenAI, Anthropic, Groq, and other mem0-compatible providers

  • Memory Configuration Support: New YAML configuration options

    • Memory enable/disable toggle at global and per-agent levels

    • Configurable compression thresholds (trigger_threshold, target_ratio)

    • Retrieval settings (limit, exclude_recent for smart retrieval)

    • Session naming for continuation and cross-session memory

    • LLM and embedding provider configuration for mem0

    • Qdrant connection settings (server/local mode, host, port, path)

Changed#

  • Chat Agent Enhancement: Memory integration for agent workflows

    • Memory recording after agent responses (conversation and persistent)

    • Memory retrieval on restart/reset for context restoration

    • Integration with compression and context monitoring modules

  • Orchestrator Enhancement: Memory coordination for multi-agent workflows

    • Memory initialization and management across agent lifecycles

    • Memory cleanup on orchestrator shutdown

Documentations, Configurations and Resources#

  • Memory Documentation: Comprehensive memory system user guide

    • New docs/source/user_guide/memory.rst

    • Complete usage guide with quick start, configuration reference, and examples

    • Design decisions documentation explaining architecture choices

    • Troubleshooting guide for common memory issues

    • Monitoring and debugging instructions with log examples

    • API reference for PersistentMemory, ConversationMemory, and ContextMonitor

  • Configuration Examples: 5 new memory-focused YAML configurations

    • gpt5mini_gemini_context_window_management.yaml: Multi-agent with context compression

    • gpt5mini_gemini_research_to_implementation.yaml: Research to implementation workflow

    • gpt5mini_high_reasoning_gemini.yaml: High reasoning agents with memory

    • gpt5mini_gemini_baseline_research_to_implementation.yaml: Baseline research workflow

    • single_agent_compression_test.yaml: Testing compression behavior

  • Infrastructure and Testing:

    • Memory test suite with 4 test files in massgen/tests/memory/

    • Additional memory tests: test_agent_memory.py, test_conversation_memory.py, test_orchestrator_memory.py, test_persistent_memory.py

Technical Details#

  • Major Focus: Long-term memory system with semantic retrieval and memory sharing for multi-turn conversations

  • Contributors: @ncrispino @qidanrui @kitrakrev @sonichi @Henry-811 and the MassGen team

[0.1.4] - 2025-10-27#

Added#

  • Multimodal Generation Tools: Comprehensive generation capabilities via OpenAI APIs

    • New text_to_image_generation tool for generating images from text prompts using DALL-E models

    • New text_to_video_generation tool for generating videos from text prompts

    • New text_to_speech_continue_generation tool for text-to-speech with continuation support

    • New text_to_speech_transcription_generation tool for audio transcription and generation

    • New text_to_file_generation tool for generating documents (PDF, DOCX, XLSX, PPTX)

    • New image_to_image_generation tool for image-to-image transformations

    • Implemented in massgen/tool/_multimodal_tools/ with 6 new modules

  • Binary File Protection System: Enhanced security for file operations

    • New binary file blocking in PathPermissionManager preventing text tools from reading binary files

    • Added BINARY_FILE_EXTENSIONS set covering images, videos, audio, archives, executables, and Office documents

    • New _validate_binary_file_access() method with intelligent tool suggestions

    • Prevents context pollution by blocking Read, read_text_file, and read_file tools from binary files

    • Comprehensive test suite in test_binary_file_blocking.py

  • Crawl4AI Web Scraping Integration: Advanced web content extraction tool

    • New crawl4ai_tool for intelligent web scraping with LLM-powered extraction

    • Implemented in massgen/tool/_web_tools/crawl4ai_tool.py

Changed#

  • Multimodal File Size Limits: Enhanced validation and automatic handling

    • Automatic image resizing for files exceeding size limits

    • Comprehensive size limit test suite in test_multimodal_size_limits.py

    • Enhanced validation in understand_audio and understand_video tools

Documentations, Configurations and Resources#

  • PyPI Package Documentation: Standalone README for PyPI distribution

    • New README_PYPI.md with comprehensive package documentation

    • Improved package metadata and installation instructions

  • Release Management Documentation: Comprehensive release workflow guide

    • New docs/dev_notes/release_checklist.md with step-by-step release procedures

    • Detailed checklist for testing, documentation, and deployment

  • Binary File Protection Documentation: Enhanced protected paths user guide

    • Updated docs/source/user_guide/protected_paths.rst with binary file protection section

    • Documents 40+ protected binary file types and specialized tool suggestions

  • Configuration Examples: 9 new YAML configuration files

    • Generation Tools: 8 multimodal generation configurations

      • text_to_image_generation_single.yaml and text_to_image_generation_multi.yaml

      • text_to_video_generation_single.yaml and text_to_video_generation_multi.yaml

      • text_to_speech_generation_single.yaml and text_to_speech_generation_multi.yaml

      • text_to_file_generation_single.yaml and text_to_file_generation_multi.yaml

    • Web Scraping: crawl4ai_example.yaml for Crawl4AI integration

Technical Details#

  • Major Focus: Multimodal generation tools, binary file protection system, web scraping integration

  • Contributors: @qidanrui @ncrispino @sonichi @Henry-811 and the MassGen team

[0.1.3] - 2025-10-24#

Added#

  • Post-Evaluation Workflow Tools: Submit and restart capabilities for winning agents

    • New PostEvaluationToolkit class in massgen/tool/workflow_toolkits/post_evaluation.py

    • submit tool for confirming final answers

    • restart_orchestration tool for restarting with improvements and feedback

    • Post-evaluation phase where winning agent evaluates its own answer

    • Support for all API formats (Claude, Response API, Chat Completions)

    • Configuration parameter enable_post_evaluation_tools for opt-in/out

  • Custom Multimodal Understanding Tools: Active tools for analyzing workspace files using OpenAI’s GPT-4.1 API

    • New understand_image tool for analyzing images (PNG, JPEG, JPG) with detailed metadata extraction

    • New understand_audio tool for transcribing and analyzing audio files (WAV, MP3, FLAC, OGG)

    • New understand_video tool for extracting frames and analyzing video content (MP4, AVI, MOV, WEBM)

    • New understand_file tool for processing documents (PDF, DOCX, XLSX, PPTX) with text and metadata extraction

    • Works with any backend (uses OpenAI for analysis)

    • Returns structured JSON with comprehensive metadata

  • Docker Sudo Mode: Enhanced Docker execution with privileged command support

    • New use_sudo parameter for Docker execution

    • Sudo mode for commands requiring elevated privileges

    • Enhanced security instructions and documentation

    • Test coverage in test_code_execution.py

Changed#

  • Interactive Config Builder Enhancement: Improved workflow and provider handling

    • Better flow from automatic setup to config builder

    • Auto-detection of environment variables

    • Improved provider-specific configuration handling

    • Integrated multimodal tools selection in config wizard

Fixed#

  • System Message Warning: Resolved deprecated system message configuration warning

    • Fixed system message handling in agent_config.py

    • Updated chat agent to properly handle system messages

    • Removed deprecated warning messages

  • Config Builder Issues: Multiple configuration builder improvements

    • Fixed config display errors

    • Improved config saving across different provider types

    • Better error handling for missing configurations

Documentations, Configurations and Resources#

  • Multimodal Tools Documentation: Comprehensive documentation for new multimodal tools

    • docs/source/user_guide/multimodal.rst: Updated with custom tools section

    • massgen/tool/docs/multimodal_tools.md: Complete 779-line technical documentation

  • Docker Sudo Mode Documentation: Enhanced Docker execution documentation

    • docs/source/user_guide/code_execution.rst: Added 98 lines documenting sudo mode

    • massgen/docker/README.md: Updated with sudo mode instructions

  • Configuration Examples: New example configurations

    • configs/tools/multimodal_tools/understand_image.yaml: Image analysis configuration

    • configs/tools/multimodal_tools/understand_audio.yaml: Audio transcription configuration

    • configs/tools/multimodal_tools/understand_video.yaml: Video analysis configuration

    • configs/tools/multimodal_tools/understand_file.yaml: Document processing configuration

  • Example Resources: New test resources for v0.1.3 features

    • massgen/configs/resources/v0.1.3-example/multimodality.jpg: Image example

    • massgen/configs/resources/v0.1.3-example/Sherlock_Holmes.mp3: Audio example

    • massgen/configs/resources/v0.1.3-example/oppenheimer_trailer_1920.mp4: Video example

    • massgen/configs/resources/v0.1.3-example/TUMIX.pdf: PDF document example

  • Case Studies: New case study demonstrating v0.1.3 features

    • docs/source/examples/case_studies/multimodal-case-study-video-analysis.md: Meta-level demonstration of multimodal video understanding with agents analyzing their own case study videos

Technical Details#

  • Major Focus: Post-evaluation workflow tools, custom multimodal understanding tools, Docker sudo mode

  • Contributors: @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.1.2] - 2025-10-22#

Added#

  • Claude 4.5 Haiku Support: Added latest Claude Haiku model

    • New model: claude-haiku-4-5-20251001

    • Updated model registry in backend/capabilities.py

Changed#

  • Planning Mode Enhancement: Intelligent automatic MCP tool blocking based on operation safety

    • New _analyze_question_irreversibility() method in orchestrator analyzes questions to determine if MCP operations are reversible

    • New set_planning_mode_blocked_tools(), get_planning_mode_blocked_tools(), and is_mcp_tool_blocked() methods in backend for selective tool control

    • Dynamically enables/disables planning mode - read-only operations allowed during coordination, write operations blocked

    • Planning mode supports different workspaces without conflicts

    • Zero configuration required - works transparently

  • Claude Model Priority: Reorganized model list in capabilities registry

    • Changed default model from claude-sonnet-4-20250514 to claude-sonnet-4-5-20250929

    • Moved claude-opus-4-1-20250805 higher in priority order

    • Updated in both Claude and Claude Code backends

Fixed#

  • Grok Web Search: Resolved web search functionality in Grok backend

    • Fixed extra_body parameter handling for Grok’s Live Search API

    • New _add_grok_search_params() method for proper search parameter injection

    • Enhanced _stream_with_custom_and_mcp_tools() to support Grok-specific parameters

    • Improved error handling for conflicting search configurations

    • Better integration with Chat Completions API params handler

Documentations, Configurations and Resources#

  • Intelligent Planning Mode Case Study: Complete feature documentation

    • docs/source/examples/case_studies/INTELLIGENT_PLANNING_MODE.md: Comprehensive guide for automatic planning mode

    • Demonstrates automatic irreversibility detection

    • Shows read/write operation classification

    • Includes examples for Discord, filesystem, and Twitter operations

  • Configuration Updates: Enhanced YAML examples

    • Updated 5 planning mode configurations in configs/tools/planning/ with selective blocking examples

    • Updated three_agents_default.yaml with Grok-4-fast model

    • Test coverage in test_intelligent_planning_mode.py

Technical Details#

  • Major Focus: Intelligent planning mode with selective tool blocking, model support enhancements

  • Contributors: @franklinnwren @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.1.1] - 2025-10-20#

Added#

  • Custom Tools System: Complete framework for registering and executing user-defined Python functions as tools

    • New ToolManager class in massgen/tool/_manager.py for centralized tool registration and lifecycle management

    • Support for custom tools alongside MCP servers across all backends (Claude, Gemini, OpenAI Response API, Chat Completions, Claude Code)

    • Three tool categories: builtin, mcp, and custom tools

    • Automatic tool discovery with name prefixing and conflict resolution

    • Tool validation with parameter schema enforcement

    • Comprehensive test coverage in test_custom_tools.py

  • Voting Sensitivity & Answer Novelty Controls: Three-tier system for multi-agent coordination

    • New voting_sensitivity parameter with three levels: “lenient”, “balanced”, “strict”

    • “Lenient”: Accepts any reasonable answer

    • “Balanced”: Default middle ground

    • “Strict”: High-quality requirement

    • Answer novelty detection with _check_answer_novelty() method in orchestrator.py preventing duplicate answers

    • Configurable max_new_answers_per_agent limiting submissions per agent

    • Token-based similarity thresholds (50-70% overlap) for duplicate detection

  • Interactive Configuration Builder: Wizard for creating YAML configurations

    • New config_builder.py module with step-by-step prompts

    • Guided workflow for backend selection, model configuration, and API key setup

    • Model-specific parameter handling (temperature, reasoning, verbosity)

    • Tool enablement options (MCP servers, custom tools, builtin tools)

    • Configuration validation and preview before saving

    • Integration with massgen --config-builder command

  • Backend Capabilities Registry: Centralized feature support tracking

    • New capabilities.py module in massgen/backend/ documenting backend capabilities

    • Feature matrix showing MCP, custom tools, multimodal, and code execution support

    • Runtime capability queries for backend selection

Changed#

  • Gemini Backend Architecture: Major refactoring for improved maintainability

    • Extracted MCP management into gemini_mcp_manager.py

    • Extracted tracking logic into gemini_trackers.py

    • Extracted utilities into gemini_utils.py

    • New API params handler _gemini_api_params_handler.py

    • Improved session management and tool execution flow

  • Python Version Requirements: Updated minimum supported version

    • Changed from Python 3.10+ to Python 3.11+ in pyproject.toml

    • Ensures compatibility with modern type hints and async features

  • API Key Setup Command: Simplified command name

    • Renamed massgen --setup-keys to massgen --setup for brevity

    • Maintained all functionality for interactive API key configuration

  • Configuration Examples: Updated example commands

    • Changed from python -m massgen.cli to simplified massgen command

    • Updated 40+ configuration files for consistency

Fixed#

  • CLI Configuration Selection: Resolved error with large config lists

    • Fixed crash when using massgen --select with many available configurations

    • Improved pagination and display of configuration options

    • Enhanced error handling for configuration discovery

  • CLI Help System: Improved documentation display

    • Fixed help text formatting in massgen --help

    • Better organization of command options and examples

Documentations, Configurations and Resources#

  • Case Study: Universal Code Execution via MCP: Comprehensive v0.0.31 feature documentation

    • docs/source/examples/case_studies/universal-code-execution-mcp.md

    • Demonstrates pytest test creation and execution across backends

    • Shows command validation, security layers, and result interpretation

  • Documentation Updates: Enhanced existing documentation

    • Added custom tools user guide and integration examples

    • Reorganized case studies for improved navigation

    • Updated configuration schema with new voting and tools parameters

  • Custom Tools Examples: 40+ example configurations

    • Basic single-tool setups for each backend

    • Multi-agent configurations with custom tools

    • Integration examples combining MCP and custom tools

    • Located in configs/tools/custom_tools/

  • Voting Sensitivity Examples: Configuration examples for voting controls

    • configs/voting/gemini_gpt_voting_sensitivity.yaml

    • Demonstrates lenient, balanced, and strict voting modes

    • Shows answer novelty threshold configuration

Technical Details#

  • Major Focus: Custom tools system, voting sensitivity controls, interactive config builder, and comprehensive documentation

  • Contributors: @qidanrui @ncrispino @praneeth999 @sonichi @Eric-Shang @Henry-811 and the MassGen team

[0.1.0] - 2025-10-17 (PyPI Release)#

Added#

  • PyPI Package Release: Official MassGen package available on PyPI for easy installation via pip

  • Enhanced Documentation: Comprehensive Sphinx documentation with improved structure and clarity

    • Rebuilt documentation with v0.1.0 version numbers

    • Improved backend capabilities table with split multimodal columns

    • Enhanced explanations for multimodal capabilities (Both, Understanding, Generation)

    • Updated homepage with v0.1.0 features

Changed#

  • Documentation Updates: Major documentation improvements for PyPI release

    • Updated version numbers across all documentation files

    • Clarified multimodal capability terminology

    • Enhanced backend configuration guides

Technical Details#

  • Major Focus: PyPI distribution and documentation improvements

  • Contributors: @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.32] - 2025-10-15#

Added#

  • Docker Execution Mode: Isolated command execution via Docker containers

    • New DockerManager class for persistent container lifecycle management

    • Container-based isolation with volume mounts for workspace and context paths

    • Configurable resource limits (CPU, memory) and network isolation modes (none/bridge/host)

    • Multi-agent support with dedicated containers per agent

    • Build script and comprehensive Dockerfile for massgen/mcp-runtime image

    • Enable via command_line_execution_mode: "docker" in agent configuration

    • Test suite in test_code_execution.py covering Docker and local execution modes

Changed#

  • Code Execution via MCP: Extended v0.0.31’s execute_command tool with Docker execution mode

    • Docker environment detection for automatic image verification

    • Local command execution remains available via command_line_execution_mode: "local"

    • Enhanced security layers for both local and Docker modes

  • Claude Code Backend: Docker mode integration and MCP tool handling improvements

    • Automatic Bash tool disablement when Docker mode is enabled

    • MCP tool auto-permission support via can_use_tool hook

    • MCP server configuration format conversion (list to dict format)

    • System message enhancements to prevent git repository confusion in Docker

  • MCP Tools Architecture: Major refactoring for simplicity and maintainability

    • Renamed MultiMCPClient to MCPClient reflecting simplified architecture

    • Removed deprecated converters.py module (275 lines removed)

    • Streamlined client.py with 1,029 lines removed through consolidation

    • Standardized type hints and module-level constants in backend_utils.py

    • Simplified exception handling in exceptions.py and security validation in security.py

Fixed#

  • Configuration Examples: Improved configuration organization and usability

    • Renamed configuration files for better discoverability

    • Fixed CPU limits in example configurations to be runnable

    • Reverted gemini_mcp_test.yaml for consistency

  • Orchestrator Timeout and Cleanup: Enhanced timeout handling and resource management

    • Improved timeout mechanisms for better reliability

    • Better cleanup of resources after orchestration sessions

Documentations, Configurations and Resources#

  • Docker Documentation: New comprehensive Docker mode guide in massgen/docker/README.md

    • Complete Docker setup and usage documentation

    • Build scripts and Dockerfile with detailed comments

    • Security considerations for container-based execution

    • Resource management and isolation strategies

  • Code Execution Design: Updated CODE_EXECUTION_DESIGN.md with Docker architecture details

  • New Configuration Files: Added 5 Docker-specific example configurations

    • docker_simple.yaml: Basic single-agent Docker execution

    • docker_multi_agent.yaml: Multi-agent Docker deployment

    • docker_with_resource_limits.yaml: Resource-constrained Docker setup

    • docker_claude_code.yaml: Claude Code with Docker execution

    • docker_verification.yaml: Docker setup verification configuration

Technical Details#

  • Commits: 17 commits including Docker execution, MCP refactoring, and Claude Code enhancements

  • Files Modified: 32 files across backend, filesystem manager, MCP tools, and configurations

  • Major Features: Docker execution mode, MCP architecture simplification, Claude Code Docker integration

  • New Module: _docker_manager.py with DockerManager class (438 lines)

  • Dependencies Updated: docker>=7.0.0 added as optional dependency

  • Contributors: @ncrispino @praneeth999 @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.31] - 2025-10-14#

Added#

  • Code Execution via MCP: Universal command execution through MCP

    • New execute_command MCP tool enabling bash/shell execution across Claude, Gemini, OpenAI (Response API), and Chat Completions providers (Grok, ZAI, etc.)

    • AG2-inspired security with multi-layer protection: dangerous command sanitization, command filtering (whitelist/blacklist), PathPermissionManager hooks, path validation, timeout enforcement

    • Command filtering with regex patterns for whitelist/blacklist control

    • New MCP server _code_execution_server.py with subprocess-based local execution

    • Test coverage in test_code_execution.py covering basics, path validation, command sanitization, output handling, and virtual environment detection

  • Audio Generation Tools: Text-to-speech and audio transcription capabilities via OpenAI APIs

    • New generate_and_store_audio_no_input_audios tool for generating audio from text using gpt-4o-audio-preview model

    • New generate_text_with_input_audio tool for transcribing audio files using OpenAI’s Transcription API

    • New convert_text_to_speech tool for converting text to speech with gpt-4o-mini-tts model

    • Support for multiple voices (alloy, echo, fable, onyx, nova, shimmer, coral, sage) and audio formats (wav, mp3, opus, aac, flac)

    • Optional speaking instructions for tone and style control in TTS

    • Automatic workspace organization with timestamp-based filenames

  • Video Generation Tools: Text-to-video generation via OpenAI’s Sora-2 API

    • New generate_and_store_video_no_input_images tool for generating videos from text prompts

    • Support for Sora-2 model with configurable video duration

    • Asynchronous video generation with progress monitoring

    • Automatic MP4 format with workspace storage and organization

Changed#

  • AG2 Group Chat Support: Enhanced AG2 adapter with native multi-agent group chat coordination

    • New group chat manager integration with AG2’s GroupChat and GroupChatManager

    • Configurable speaker selection modes: auto (LLM-based), round_robin, manual

    • Support for nested conversations and workflow tools within group chat sessions

    • Automatic tool registration/unregistration for clean group chat lifecycle

    • Enhanced adapter architecture with group chat state management

    • Better agent reinitialization and termination logic for multi-turn group conversations

    • Test coverage in test_ag2_adapter.py and test_ag2_utils.py

  • File Operation Tracker: Enhanced with auto-generated file exemptions

    • New _is_auto_generated() method to identify build artifacts and cache files

    • Prevents permission errors when agents clean up after running tests or builds

  • Path Permission Manager: Added execute_command tool validation

    • Added execute_command to command_tools set for bash-like security validation

    • PreToolUse hooks now validate execute_command calls for dangerous patterns and path restrictions

    • Enhanced test coverage with 93 new test lines for command tool validation

  • Message Templates: Added code execution result guidance

    • New system message guidance when enable_command_execution=True instructing agents to explain test results and command outputs in their answers

    • Better agent behavior for explaining what was tested and what results mean

Documentations, Configurations and Resources#

  • Code Execution Design Documentation: Comprehensive technical design document

    • CODE_EXECUTION_DESIGN.md: Design doc covering architecture, security layers, implementation plan, virtual environment support, and future Docker enhancements

  • New Configuration Files: Added 8 new example configurations

    • AG2 Group Chat: ag2_groupchat.yaml, ag2_groupchat_gpt.yaml

    • Code Execution: basic_command_execution.yaml, code_execution_use_case_simple.yaml, command_filtering_whitelist.yaml, command_filtering_blacklist.yaml,

    • Audio Generation: single_gpt4o_audio_generation.yaml, gpt4o_audio_generation.yaml

    • Video Generation: single_gpt4o_video_generation.yaml

Technical Details#

  • Commits: 29 commits including AG2 group chat, code execution, audio/video generation, and enhancements

  • Files Modified: 39 files with 3,649 insertions and 154 deletions

  • Major Features: AG2 group chat, universal code execution via MCP, audio/video generation tools

  • New Tests: test_ag2_adapter.py, test_ag2_utils.py, test_code_execution.py

  • Contributors: @Eric-Shang @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.30] - 2025-10-10#

Changed#

  • Multimodal Support - Audio and Video Processing: Extended v0.0.27’s image-only multimodal foundation

    • Audio file support with WAV and MP3 formats for Chat Completions and Claude backends

    • Video file support with MP4, AVI, MOV, WEBM formats for Chat Completions and Claude backends

    • Audio/video path parameters (audio_path, video_path) for local files and HTTP/HTTPS URLs

    • Base64 encoding for local audio/video files with automatic MIME type detection

    • Configurable media file size limits (default 64MB, configurable via media_max_file_size_mb)

    • New audio/video content formatters in _chat_completions_formatter.py and _claude_formatter.py

    • Enhanced base_with_mcp.py with 340+ lines of multimodal content processing

  • Claude Code Backend SDK Update: Updated to newer Agent SDK package

    • Migrated from claude-code-sdk>=0.0.19 to claude-agent-sdk>=0.0.22

    • Updated internal SDK classes: ClaudeCodeOptions → ClaudeAgentOptions

    • Enhanced bash tool permission validation in PathPermissionManager

    • Improved system message handling with SDK preset support

    • New bash/shell/exec tool detection for dangerous operation prevention

  • Chat Completions Backend Enhancement: Qwen API provider integration

    • Added Qwen API support to existing Chat Completions provider ecosystem

    • New QWEN_API_KEY environment variable support

    • Qwen-specific configuration examples for video understanding

Fixed#

  • Planning Mode Configuration: Fixed crash when configuration lacks coordination_config

    • Added null check in orchestrator.py to prevent AttributeError

    • Improved graceful handling of missing planning mode configuration

  • Claude Code System Message Handling: Resolved system message processing issues

    • Fixed system message extraction and formatting in claude_code.py

    • Better integration with Agent SDK for message handling

  • AG2 Adapter Import Ordering: Resolved import sequence issues

    • Fixed import statements in adapters/utils/ag2_utils.py

    • Pre-commit isort formatting corrections

Documentations, Configurations and Resources#

  • Case Studies: Comprehensive documentation for v0.0.28 and v0.0.29 features

    • ag2-framework-integration.md: AG2 adapter system and external framework integration

    • mcp-planning-mode.md: MCP Planning Mode design and implementation guide

  • New Configuration Files: Added 7 new example configurations

    • ag2/ag2_case_study.yaml: AG2 framework integration case study configuration

    • filesystem/cc_gpt5_gemini_filesystem.yaml: Claude Code, GPT-5, and Gemini filesystem collaboration

    • basic/single/single_gemini2.5pro.yaml: Gemini 2.5 Pro single agent setup

    • basic/single/single_openrouter_audio_understanding.yaml: Audio understanding with OpenRouter

    • basic/single/single_qwen_video_understanding.yaml: Video understanding with Qwen API

    • debug/test_sdk_migration.yaml: Claude Code SDK migration testing

Technical Details#

  • Commits: 20 commits including multimodal enhancements, Claude Code SDK migration, and documentation

  • Files Modified: 25 files with 2,501 insertions and 84 deletions

  • Major Features: Audio/video multimodal support, Claude Code Agent SDK migration, Qwen API integration

  • Dependencies Updated: anthropic>=0.61.0, claudecode>=0.0.12

  • Contributors: @ncrispino @praneeth999 @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.29] - 2025-10-08#

Added#

  • MCP Planning Mode: New coordination strategy for irreversible MCP actions

    • New CoordinationConfig class with enable_planning_mode flag

    • Agents plan without executing during coordination, winning agent executes during final presentation

    • Orchestrator and frontend coordination UI support

    • Support for multiple backends: Response API, Chat Completions, and Gemini

    • Test suites in test_mcp_blocking.py and test_gemini_planning_mode.py

  • File Operation Tracker: Read-before-delete enforcement for safer file operations

    • New FileOperationTracker class in filesystem_manager/_file_operation_tracker.py

    • Prevents agents from deleting files they haven’t read first

    • Tracks read files and agent-created files (created files exempt from read requirement)

    • Directory deletion validation with comprehensive error messages

  • Path Permission Manager Enhancements: Integration with FileOperationTracker

    • Added read/write/delete operation tracking methods to PathPermissionManager

    • Integration with FileOperationTracker for read-before-delete enforcement

    • Enhanced delete validation for files and batch operations

    • Extended test coverage in test_path_permission_manager.py

Changed#

  • Message Templates: Improved multi-agent coordination guidance

    • Added has_irreversible_actions support for context path write access

    • Explicit temporary workspace path structure display for better agent understanding

    • Task handling priority hierarchy and simplified new_answer requirements

    • Unified evaluation guidance

  • MCP Tool Filtering: Enhanced multi-level filtering capabilities

    • Combined backend-level and per-MCP-server tool filtering

    • MCP-server-specific allowed_tools can override backend-level settings

    • Merged exclude_tools from both backend and MCP server configurations

  • Backend Planning Mode Support: Extended planning mode to multiple backends

    • Enhanced base.py, response.py, chat_completions.py, and gemini.py

    • Gemini backend now supports planning mode with session-based tool execution

    • Planning mode support across all major backend types

Fixed#

  • Circuit Breaker Logic: Enhanced MCP server initialization in base_with_mcp.py

  • Final Answer Context: Improved workspace copying when no new answer is provided

  • Multi-turn MCP Usage: Addressed non-use of MCP in certain scenarios and improved final answer autonomy

  • Configuration Issues: Updated Playwright automation configuration and fixed agent IDs

Documentations, Configurations and Resources#

  • MCP Planning Mode Examples: 5 new planning mode configurations in tools/planning/

    • five_agents_discord_mcp_planning_mode.yaml: Discord MCP with planning mode (5 agents)

    • five_agents_filesystem_mcp_planning_mode.yaml: Filesystem MCP with planning mode

    • five_agents_notion_mcp_planning_mode.yaml: Notion MCP with planning mode (5 agents)

    • five_agents_twitter_mcp_planning_mode.yaml: Twitter MCP with planning mode (5 agents)

    • gpt5_mini_case_study_mcp_planning_mode.yaml: Case study configuration

  • MCP Example Configurations: New example configurations for MCP integration in tools/mcp/

    • five_agents_travel_mcp_test.yaml: Travel planning MCP example (5 agents)

    • five_agents_weather_mcp_test.yaml: Weather service MCP example (5 agents)

  • Debug Configurations: New debugging and testing utilities

    • skip_coordination_test.yaml: Test configuration for skipping coordination rounds

  • Documentation Updates: Enhanced project documentation

    • Updated permissions_and_context_files.md in backend/docs/ with file operation tracking details

    • Updated README with AG2 as optional installation and uv tool instructions

Technical Details#

  • Commits: 23+ commits including planning mode, file operation tracking, and MCP enhancements

  • Files Modified: 43 files across agent config, backend, filesystem manager, MCP tools, and configurations

  • Major Features: MCP planning mode, FileOperationTracker, enhanced permissions, MCP tool filtering

  • New Tests: test_mcp_blocking.py, test_gemini_planning_mode.py for planning mode validation

  • Contributors: @ncrispino @franklinnwren @qidanrui @sonichi @praneeth999 and the MassGen team

[0.0.28] - 2025-10-06#

Added#

  • AG2 Framework Integration: Complete adapter system for external agent frameworks

    • New massgen/adapters/ module with base adapter architecture (base.py, ag2_adapter.py)

    • Support for AG2 ConversableAgent and AssistantAgent types

    • Code execution capabilities with multiple executor types: LocalCommandLineCodeExecutor, DockerCommandLineCodeExecutor, JupyterCodeExecutor, YepCodeCodeExecutor

    • Function/tool calling support for AG2 agents

    • Async execution with a_generate_reply for autonomous operation

    • AG2 utilities module for agent setup and API key management (adapters/utils/ag2_utils.py)

  • External Agent Backend: New backend type for integrating external frameworks

    • New ExternalAgentBackend class supporting adapter registry pattern

    • Bridge between MassGen orchestration and external agent frameworks via adapters

    • Framework-specific configuration extraction and validation

    • Currently supports AG2 with extensible architecture for future frameworks

  • AG2 Test Suite: Comprehensive test coverage for AG2 integration

    • test_ag2_adapter.py: AG2 adapter functionality tests

    • test_agent_adapter.py: Base adapter interface tests

    • test_external_agent_backend.py: External backend integration tests

Fixed#

  • MCP Circuit Breaker Logic: Enhanced initialization for MCP servers

    • Improved circuit breaker state management in base_with_mcp.py

    • Better error handling during MCP server initialization

Documentations, Configurations and Resources#

  • AG2 Configuration Examples: New YAML configurations demonstrating AG2 integration

    • ag2/ag2_single_agent.yaml: Basic single AG2 agent setup

    • ag2/ag2_coder.yaml: AG2 agent with code execution

    • ag2/ag2_coder_case_study.yaml: Multi-agent setup with AG2 and Gemini

    • ag2/ag2_gemini.yaml: AG2-Gemini hybrid configuration

  • Design Documentation: Enhanced multi-source agent integration design

    • Updated MULTI_SOURCE_AGENT_INTEGRATION_DESIGN.md with AG2 adapter architecture

Technical Details#

  • Commits: 12 commits including AG2 integration, testing, and configuration examples

  • Files Modified: 18 files with 1,423 insertions and 71 deletions

  • Major Features: AG2 framework integration, external agent backend, adapter architecture

  • New Module: massgen/adapters/ with AG2 support

  • Contributors: @Eric-Shang @praneeth999 @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.27] - 2025-10-03#

Added#

  • Multimodal Support - Image Processing: Foundation for multimodal content processing

    • New stream_chunk module with base classes for multimodal content (base.py, text.py, multimodal.py)

    • Support for image input and output in conversation messages

    • Image generation and understanding capabilities for multi-agent workflows

    • Multimodal content structure supporting images, audio, video, and documents (architecture ready)

  • File Upload and File Search: Extended backend capabilities for document operations

    • File upload support integrated into Response backend via _response_api_params_handler.py

    • File search functionality for enhanced context retrieval and Q&A

    • Vector store management for file search operations

    • Cleanup utilities for uploaded files and vector stores

  • Workspace Tools Enhancements: Extended MCP-based workspace management

    • Added read_multimodal_files tool for reading images as base64 data with MIME type

  • Claude Sonnet 4.5 Support: Added latest Claude model to model mappings

    • Support for Claude Sonnet 4.5 (claude-sonnet-4-5-20250929)

    • Updated model registry in utils.py

Changed#

  • Message Architecture Refactoring: Extracted and refactored messaging system for multimodal support

    • Extracted StreamChunk classes into dedicated module (massgen/stream_chunk/)

    • Enhanced message templates for image generation workflows

    • Improved orchestrator and chat agent for multimodal message handling

  • Backend Enhancements: Extended backends for multimodal and file operations

    • Enhanced response.py with image generation, understanding, and saving capabilities

    • Improved base_with_mcp.py with image handling for MCP-based workflows

    • New api_params_handler module for centralized parameter management including file uploads

    • Better streaming and error handling for multimodal content

  • Frontend Display Improvements: Enhanced terminal UI for multimodal content

    • Refactored rich_terminal_display.py for rendering images in terminal

    • Improved message formatting and visual presentation

Documentations, Configurations and Resources#

  • New Configuration Files: Added multimodal and enhanced filesystem examples

    • gpt4o_image_generation.yaml: Multi-agent image generation setup

    • gpt5nano_image_understanding.yaml: Multi-agent image understanding configuration

    • single_gpt4o_image_generation.yaml: Single agent image generation

    • single_gpt5nano_image_understanding.yaml: Single agent image understanding

    • single_gpt5nano_file_search.yaml: Single agent file search example

    • grok4_gpt5_gemini_filesystem.yaml: Enhanced filesystem configuration

    • Updated claude_code_gpt5nano.yaml with improved filesystem settings

  • Case Study Documentation: New multi-turn-filesystem-support.md demonstrating v0.0.25 multi-turn capabilities with Bob Dylan website example

  • Presentation Materials: New applied-ai-summit.html presentation with updated build scripts and call-to-action slides

  • Example Resources: New multimodality.jpg for testing multimodal capabilities under massgen/configs/resources/v0.0.27-example/

Technical Details#

  • Major Features: Image processing foundation, StreamChunk architecture, file upload/search, workspace multimodal tools

  • New Module: massgen/stream_chunk/ with base, text, and multimodal classes

  • Contributors: @qidanrui @sonichi @praneeth999 @ncrispino @Henry-811 and the MassGen team

[0.0.26] - 2025-10-01#

Added#

  • File Deletion and Workspace Management: New MCP tools for workspace file operations

    • New workspace deletion tools: delete_file, delete_files_batch for managing workspace files

    • New comparison tools: compare_directories, compare_files for file diffing

    • Consolidated _workspace_tools_server.py replacing previous _workspace_copy_server.py

    • Improved workspace cleanup mechanisms for multi-turn sessions

    • Proper permission checks for all file operations

  • File-Based Context Paths: Support for single file access without exposing entire directories

    • Context paths can now be individual files, not just directories

    • Better control over agent access to specific reference files

    • Enhanced path validation distinguishing between file and directory contexts

  • Protected Paths Feature: Prevent agents from modifying specific reference files

    • Protected paths within write-permitted context paths

    • Agents can read but not modify protected files

Changed#

  • Code Refactoring: Improved module structure and import paths

    • Moved utility modules from backend/utils/ to top-level massgen/ directory

    • Relocated api_params_handler, formatter, and filesystem_manager modules

    • Simplified import paths and improved code discoverability

    • Better separation of concerns between backend-specific and shared utilities

  • Path Permission Manager: Major enhancements to permission system

    • Enhanced will_be_writable logic for better permission state tracking

    • Improved path validation distinguishing between context paths and workspace paths

    • Comprehensive test coverage in test_path_permission_manager.py

    • Better handling of edge cases and nested path scenarios

Fixed#

  • Path Permission Edge Cases: Resolved various permission checking issues

    • Fixed file context path validation logic

    • Corrected protected path matching behavior

    • Improved handling of nested paths and symbolic links

    • Better error handling for non-existent paths

Documentations, Configurations and Resources#

  • Example Resources: Added v0.0.26 example resources for testing new features

    • Bob Dylan themed website with multiple pages and styles

    • Additional HTML, CSS, and JavaScript examples

    • Resources organized under massgen/configs/resources/v0.0.26-example/

  • Design Documentation: Added comprehensive design documentation

    • New file_deletion_and_context_files.md documenting file deletion and context file features

    • Updated permissions_and_context_files.md with v0.0.26 features

    • Added detailed examples for protected paths and file context paths

  • Release Workflow Documentation: Added comprehensive release example checklist

    • Step-by-step guide for release preparation in docs/workflows/release_example_checklist.md

    • Best practices for testing new features

  • Configuration Examples: New configuration examples for v0.0.26 features

    • gemini_gpt5nano_protected_paths.yaml: Protected paths example

    • gemini_gpt5nano_file_context_path.yaml: File-based context paths example

    • gemini_gemini_workspace_cleanup.yaml: Workspace cleanup example

Technical Details#

  • Commits: 20+ commits including file deletion tools, protected paths, and refactoring

  • Files Modified: 46 files with 4,343 insertions and 836 deletions

  • Major Features: File deletion tools, protected paths, file-based context paths, enhanced CLI prompts

  • New Tools: delete_file, delete_files_batch, compare_directories, compare_files MCP tools

  • Contributors: @praneeth999 @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.25] - 2025-09-29#

Added#

  • Multi-Turn Filesystem Support: Complete implementation for persistent filesystem context across conversation turns

    • Automatic session management (no flag needed)

    • Persistent workspace management across conversation turns with .massgen directory

    • Workspace snapshot preservation and restoration between turns

    • Support for maintaining file context and modifications throughout multi-turn sessions

    • New configuration examples: two_gemini_flash_filesystem_multiturn.yaml, grok4_gpt5_gemini_filesystem_multiturn.yaml, grok4_gpt5_claude_code_filesystem_multiturn.yaml

    • Design documentation in multi_turn_filesystem_design.md

  • SGLang Backend Integration: Added SGLang support to inference backend alongside existing vLLM

    • New SGLang server support with default port 30000 and SGLANG_API_KEY environment variable

    • SGLang-specific parameters support (e.g., separate_reasoning for guided generation)

    • Auto-detection between vLLM and SGLang servers based on configuration

    • New configuration two_qwen_vllm_sglang.yaml for mixed server deployments

    • Unified InferenceBackend class replacing separate vllm.py implementation

    • Updated documentation renamed from vllm_implementation.md to inference_backend.md

  • Enhanced Path Permission System: New exclusion patterns and validation improvements

    • Added DEFAULT_EXCLUDED_PATTERNS for common directories (.git, node_modules, .venv, etc.)

    • New will_be_writable flag for better permission state tracking

    • Improved path validation with different handling for context vs workspace paths

    • Enhanced test coverage in test_path_permission_manager.py

Changed#

  • CLI Enhancements: Major improvements to command-line interface

    • Enhanced logging with configurable log levels and file output

    • Improved error handling and user feedback

  • System Prompt Improvements: Refined agent system prompts for better performance

    • Clearer instructions for file context handling

    • Better guidance for multi-turn conversations

    • Improved prompt templates for filesystem operations

  • Documentation Updates: Comprehensive documentation improvements

    • Updated README with clearer installation instructions

Fixed#

  • Filesystem Manager: Resolved workspace and permission issues

    • Fixed warnings for non-existent temporary workspaces

    • Better cleanup of old workspaces

    • Fixed relative path issues in workspace copy operations

  • Configuration Issues: Multiple configuration fixes

    • Fixed multi-agent configuration templates

    • Fixed code generation prompts for consistency

Technical Details#

  • Commits: 30+ commits including multi-turn filesystem, SGLang integration, and bug fixes

  • Files Modified: 33 files with 3,188 insertions and 642 deletions

  • Major Features: Multi-turn filesystem support, unified vLLM/SGLang backend, enhanced permissions

  • New Backend: SGLang integration alongside existing vLLM support

  • Contributors: @praneeth999 @ncrispino @qidanrui @sonichi @Henry-811 and the MassGen team

[0.0.24] - 2025-09-26#

Added#

  • vLLM Backend Support: Complete integration with vLLM for high-performance local model serving

    • New vllm.py backend supporting VLLM’s OpenAI-compatible API

    • Configuration examples in three_agents_vllm.yaml

    • Comprehensive documentation in vllm_implementation.md

    • Support for large-scale model inference with optimized performance

  • POE Provider Support: Extended ChatCompletions backend to support POE (Platform for Open Exploration)

    • Added POE provider integration for accessing multiple AI models through a single platform

    • Seamless integration with existing ChatCompletions infrastructure

  • GPT-5-Codex Model Recognition: Added GPT-5-Codex to model registry

    • Extended model mappings in utils.py to recognize gpt-5-codex as a valid OpenAI model

  • Backend Utility Modules: Major refactoring for improved modularity

    • New api_params_handler module for centralized API parameter management

    • New formatter module for standardized message formatting across backends

    • New token_manager module for unified token counting and management

    • Extracted filesystem utilities into dedicated filesystem_manager module

Changed#

  • Backend Consolidation: Significant code refactoring and simplification

    • Refactored chat_completions.py and response.py with cleaner API handler patterns

    • Moved filesystem management from mcp_tools to backend/utils/filesystem_manager

    • Improved separation of concerns with specialized handler modules

    • Enhanced code reusability across different backend implementations

  • Documentation Updates: Improved documentation structure

    • Moved permissions_and_context_files.md to backend docs

    • Added multi-source agent integration design documentation

    • Updated filesystem permissions case study for v0.0.21 and v0.0.22 features

  • CI/CD Pipeline: Enhanced automated release process

    • Updated auto-release workflow for better reliability

    • Improved GitHub Actions configuration

  • Pre-commit Configuration: Updated code quality tools

    • Enhanced pre-commit hooks for better code consistency

    • Updated linting rules for improved code standards

Fixed#

  • Streaming Chunk Processing: Resolved critical bugs in chunk handling

    • Fixed chunk processing errors in response streaming

    • Improved error handling for malformed chunks

    • Better resilience in stream processing pipeline

  • Gemini Backend Session Management: Improved cleanup

    • Implemented proper session closure for google-genai aiohttp client

    • Added explicit cleanup of aiohttp sessions to prevent potential resource leaks

Technical Details#

  • Commits: 35 commits including backend refactoring, vLLM integration, and bug fixes

  • Files Modified: 50+ files across backend, utilities, configurations, and documentation

  • Major Refactor: Complete restructuring of backend utilities

  • New Backend: vLLM integration for high-performance local inference

  • Contributors: @qidanrui @sonichi @praneeth999 @ncrispino @Henry-811 and the MassGen team

[0.0.23] - 2025-09-24#

Added#

  • Backend Architecture Refactoring: Major consolidation of MCP functionality

    • New base_with_mcp.py base class consolidating common MCP functionality (488 lines)

    • Extracted shared MCP logic from individual backends into unified base class

    • Standardized MCP client initialization and error handling across all backends

  • Formatter Module: Extracted message and tool formatting logic into dedicated module

    • New massgen/formatter/ module with specialized formatters

    • message_formatter.py: Handles message formatting across backends

    • tool_formatter.py: Manages tool call formatting

    • mcp_tool_formatter.py: Specialized MCP tool formatting

Changed#

  • Backend Consolidation: Massive code deduplication across backends

    • Reduced chat_completions.py by 700+ lines

    • Reduced claude.py by 700+ lines

    • Simplified response.py by 468+ lines

    • Total reduction: ~1,932 lines removed across core backend files

Fixed#

  • Coordination Table Display: Fixed escape key handling on macOS

    • Updated create_coordination_table.py and rich_terminal_display.py

Technical Details#

  • Commits: 20+ commits focusing on backend refactoring and infrastructure improvements

  • Files Modified: 100+ files across backend, documentation, CI/CD, and presentation components

  • Lines Changed: Net reduction of ~1,932 lines through backend consolidation

  • Major Refactor: MCP functionality extracted into shared base_with_mcp.py base class

  • Contributors: @qidanrui @ncrispino @Henry-811 and the MassGen team

[0.0.22] - 2025-09-22#

Added#

  • Workspace Copy Tools via MCP: New file copying capabilities for efficient workspace operations

    • Added workspace_copy_server.py with MCP-based file copying functionality (369 lines)

    • Support for copying files and directories between workspaces

    • Efficient handling of large files with streaming operations

    • Testing infrastructure for copy operations

  • Configuration Organization: Major restructuring of configuration files for better usability

    • New hierarchical structure: basic/, providers/, tools/, teams/ directories

    • Added comprehensive README.md for configuration guide

    • New BACKEND_CONFIGURATION.md with detailed backend setup

    • Organized configs by use case and provider for easier navigation

    • Added provider-specific examples (Claude, OpenAI, Gemini, Azure)

  • Enhanced File Operations: Improved file handling for large-scale operations

    • Clear all temporary workspaces at startup for clean state

    • Enhanced security validation in MCP tools

Changed#

  • Workspace Management: Optimized workspace operations and path handling

    • Enhanced filesystem_manager.py with 193 additional lines

    • Run MCP servers through FastMCP to avoid banner displays

  • Backend Enhancements: Improved backend capabilities

    • Improved response.py with better error handling

Fixed#

  • Write Tool Call Issues: Resolved large character count problems

    • Fixed write tool call issues when dealing with large character counts

  • Path Resolution Issues: Resolved various path-related bugs

    • Fixed relative/absolute path workspace issues

    • Improved path validation and normalization

  • Documentation Fixes: Corrected multiple documentation issues

    • Fixed broken links in case studies

    • Fixed config file paths in documentation and examples

    • Corrected example commands with proper paths

Technical Details#

  • Commits: 50+ commits including workspace copy, configuration restructuring, and documentation improvements

  • Files Modified: 90+ files across configs, backend, mcp_tools, and documentation

  • Major Refactoring: Configuration file reorganization into logical categories

  • New Documentation: Added 762+ lines of documentation for configs and backends

  • Contributors: @ncrispino @qidanrui @Henry-811 and the MassGen team

[0.0.21] - 2025-09-19#

Added#

  • Advanced Filesystem Permissions System: Comprehensive permission management for agent file access

    • New PathPermissionManager class for granular permission validation

    • User context paths with configurable READ/WRITE permissions for multi-agent file sharing

    • Test suite for permission validation in test_path_permission_manager.py

    • Documentation in permissions_and_context_files.md for implementation guide

  • Function Hook Manager: Per-agent function call permission system

    • Refactored FunctionHookManager to be per-agent rather than global

    • Pre-tool-use hooks for validating file operations before execution

    • Support for write permission enforcement during context agent operations

    • Integration with all function-based backends (OpenAI, Claude, Chat Completions)

  • Grok MCP Integration: Extended MCP support to Grok backend

    • Migrated Grok backend to inherit from Chat Completions backend

    • Full MCP server support for Grok including stdio and HTTP transports

    • Filesystem support through MCP servers

  • New Configuration Files: Added test and example configurations

    • grok3_mini_mcp_test.yaml: Grok MCP testing configuration

    • grok3_mini_mcp_example.yaml: Grok MCP usage example

    • grok3_mini_streamable_http_test.yaml: Grok HTTP streaming test

    • grok_single_agent.yaml: Single Grok agent configuration

    • fs_permissions_test.yaml: Filesystem permissions testing configuration

Changed#

  • Backend Architecture: Unified backend implementations and permission support

    • Grok backend refactored to use Chat Completions backend

    • All backends now support per-agent permission management

    • Enhanced context file support across Claude, Gemini, and OpenAI backends

Technical Details#

  • Commits: 20+ commits including permission system, Grok MCP, and terminal improvements

  • Files Modified: 40+ files across backends, MCP tools, permissions, and display modules

  • New Features: Filesystem permissions, per-agent hooks, Grok MCP via Chat Completions

  • Contributors: @Eric-Shang @ncrispino @qidanrui @Henry-811 and the MassGen team

[0.0.20] - 2025-09-17#

Added#

  • Claude Backend MCP Support: Extended MCP (Model Context Protocol) integration to Claude backend

    • Filesystem support through MCP servers (FilesystemSupport.MCP) for Claude backend

    • Support for both stdio and HTTP-based MCP servers with Claude Messages API

    • Seamless integration with existing Claude function calling and tool use

    • Recursive execution model allowing Claude to autonomously chain multiple tool calls in sequence without user intervention

    • Enhanced error handling and retry mechanisms for Claude MCP operations

  • MCP Configuration Examples: New YAML configurations for Claude MCP usage

    • claude_mcp_test.yaml: Basic Claude MCP testing with test server

    • claude_mcp_example.yaml: Claude MCP integration example

    • claude_streamable_http_test.yaml: HTTP transport testing for Claude MCP

  • Documentation: Enhanced MCP technical documentation

    • MCP_IMPLEMENTATION_CLAUDE_BACKEND.md: Complete technical documentation for Claude MCP integration

    • Detailed architecture diagrams and implementation guides

Changed#

  • Backend Enhancements: Improved MCP support across backends

    • Extended MCP integration from Gemini and Chat Completions to include Claude backend

    • Enhanced error reporting and debugging for MCP operations

    • Added Kimi/Moonshot API key support in Chat Completions backend

Technical Details#

  • New Features: Claude backend MCP integration with recursive execution model

  • Files Modified: Claude backend modules (claude.py), MCP tools, configuration examples

  • MCP Coverage: Major backends now support MCP (Claude, Gemini, Chat Completions including OpenAI)

  • Contributors: @praneeth999 @qidanrui @sonichi @ncrispino @Henry-811 MassGen development team

[0.0.19] - 2025-09-15#

Added#

  • Coordination Tracking System: Comprehensive tracking of multi-agent coordination events

    • New coordination_tracker.py with CoordinationTracker class for capturing agent state transitions

    • Event-based tracking with timestamps and context preservation

    • Support for recording answers, votes, and coordination phases

    • New create_coordination_table.py utility in massgen/frontend/displays/ for generating coordination reports

  • Enhanced Agent Status Management: New enums for better state tracking

    • Added ActionType enum in massgen/utils.py: NEW_ANSWER, VOTE, VOTE_IGNORED, ERROR, TIMEOUT, CANCELLED

    • Added AgentStatus enum in massgen/utils.py: STREAMING, VOTED, ANSWERED, RESTARTING, ERROR, TIMEOUT, COMPLETED

    • Improved state machine for agent coordination lifecycle

Changed#

  • Frontend Display Enhancements: Improved terminal interface with coordination visualization

    • Modified massgen/frontend/displays/rich_terminal_display.py to add coordination table display method

    • Added new terminal menu option ‘r’ to display coordination table

    • Enhanced menu system with better organization of debugging tools

    • Support for rich-formatted tables showing agent interactions across rounds

Technical Details#

  • Commits: 20+ commits including coordination tracking system and frontend enhancements

  • Files Modified: 5+ files across coordination tracking, frontend displays, and utilities

  • New Features: Coordination event tracking with visualization capabilities

  • Contributors: @ncrispino @qidanrui @sonichi @a5507203 @Henry-811 and the MassGen team

[0.0.18] - 2025-09-12#

Added#

  • Chat Completions MCP Support: Extended MCP (Model Context Protocol) integration to ChatCompletions-based backends

    • Full MCP support for all Chat Completions providers (Cerebras AI, Together AI, Fireworks AI, Groq, Nebius AI Studio, OpenRouter)

    • Filesystem support through MCP servers (FilesystemSupport.MCP) for Chat Completions backend

    • Cross-provider function calling compatibility enabling seamless MCP tool execution across different providers

    • Universal MCP server compatibility with existing stdio and streamable-http transports

  • New MCP Configuration Examples: Added 9 new Chat Completions MCP configurations

    • GPT-OSS configurations: gpt_oss_mcp_example.yaml, gpt_oss_mcp_test.yaml, gpt_oss_streamable_http_test.yaml

    • Qwen API configurations: qwen_api_mcp_example.yaml, qwen_api_mcp_test.yaml, qwen_api_streamable_http_test.yaml

    • Qwen Local configurations: qwen_local_mcp_example.yaml, qwen_local_mcp_test.yaml, qwen_local_streamable_http_test.yaml

  • Enhanced LMStudio Backend: Improved local model support

    • Better tracking of attempted model loads

    • Improved server output handling and error reporting

Changed#

  • Backend Architecture: Major MCP framework expansion

    • Extended existing v0.0.15 MCP infrastructure to support all ChatCompletions providers

    • Refactored chat_completions.py with 1200+ lines of MCP integration code

    • Enhanced error handling and retry mechanisms for provider-specific quirks

  • CLI Improvements: Better backend creation and provider detection

    • Enhanced backend creation logic for improved provider handling

    • Better system message handling for different backend types

Technical Details#

  • Main Feature: Chat Completions MCP integration enabling all providers to use MCP tools

  • Files Modified: 20+ files across backend, mcp_tools, configurations, and CLI

  • Contributors: @praneeth999 @qidanrui @sonichi @a5507203 @ncrispino @Henry-811 and the MassGen team

[0.0.17] - 2025-09-10#

Added#

  • OpenAI Backend MCP Support: Extended MCP (Model Context Protocol) integration to OpenAI backend

    • Full MCP tool discovery and execution capabilities for OpenAI models

    • Support for both stdio and HTTP-based MCP servers with OpenAI

    • Seamless integration with existing OpenAI function calling

    • Robust error handling and retry mechanisms

  • MCP Configuration Examples: New YAML configurations for OpenAI MCP usage

    • gpt5_mini_mcp_test.yaml: Basic OpenAI MCP testing with test server

    • gpt5_mini_mcp_example.yaml: Weather service integration example for OpenAI

    • gpt5_mini_streamable_http_test.yaml: HTTP transport testing for OpenAI MCP

    • Enhanced existing multi-agent configurations with OpenAI MCP support

  • Documentation: Added case studies and technical documentation

    • unified-filesystem-mcp-integration.md: Case study demonstrating unified filesystem capabilities with MCP integration across multiple backends (from v0.0.16)

    • MCP_INTEGRATION_RESPONSE_BACKEND.md: Technical documentation for MCP integration with response backends

Changed#

  • Backend Enhancements: Improved MCP support across backends

    • Extended MCP integration from Gemini and Claude Code to include OpenAI backend

    • Unified MCP tool handling across all supported backends

    • Enhanced error reporting and debugging for MCP operations

Technical Details#

  • New Features: OpenAI backend MCP integration

  • Documentation: Added case study for unified filesystem MCP integration

  • Contributors: @praneeth999 @qidanrui @sonichi @ncrispino @a5507203 @Henry-811 and the MassGen team

[0.0.16] - 2025-09-08#

Added#

  • Unified Filesystem Support with MCP Integration: Advanced filesystem capabilities designed for all backends

    • Complete FilesystemManager class providing unified filesystem access with extensible backend support

    • Currently supports Gemini and Claude Code backends, designed for seamless expansion to all backends

    • MCP-based filesystem operations enabling file manipulation, workspace management, and cross-agent collaboration

  • Expanded Configuration Library: New YAML configurations for various use cases

    • Gemini MCP Filesystem Testing: gemini_mcp_filesystem_test.yaml, gemini_mcp_filesystem_test_sharing.yaml, gemini_mcp_filesystem_test_single_agent.yaml, gemini_mcp_filesystem_test_with_claude_code.yaml

    • Hybrid Model Setups: geminicode_gpt5nano.yaml

  • Case Studies: Added comprehensive case studies from previous versions

    • gemini-mcp-notion-integration.md: Gemini MCP Notion server integration and productivity workflows

    • claude-code-workspace-management.md: Claude Code context sharing and workspace management demonstrations

Technical Details#

  • Commits: 30+ commits including workspace redesign and orchestrator enhancements

  • Files Modified: 40+ files across orchestrator, mcp_tools, configurations, and case studies

  • New Architecture: Complete workspace management system with FilesystemManager

  • Contributors: @ncrispino @a5507203 @sonichi @Henry-811 and the MassGen team

[0.0.15] - 2025-09-05#

Added#

  • MCP (Model Context Protocol) Integration Framework: Complete implementation for external tool integration

    • New massgen/mcp_tools/ package with 8 core modules for MCP support

    • Multi-server MCP client supporting simultaneous connections to multiple MCP servers

    • Two transport types: stdio (process-based) and streamable-http (web-based)

    • Circuit breaker patterns for fault tolerance and reliability

    • Comprehensive security framework with command sanitization and validation

    • Automatic tool discovery with name prefixing for multi-server setups

  • Gemini MCP Support: Full MCP integration for Gemini backend

    • Session-based tool execution via Gemini SDK

    • Automatic tool discovery and calling capabilities

    • Robust error handling with exponential backoff

    • Support for both stdio and HTTP-based MCP servers

    • Integration with existing Gemini function calling

  • Test Infrastructure for MCP: Development and testing utilities

    • Simple stdio-based MCP test server (mcp_test_server.py)

    • FastMCP streamable-http test server (test_http_mcp_server.py)

    • Comprehensive test suite for MCP integration

  • MCP Configuration Examples: New YAML configurations for MCP usage

    • gemini_mcp_test.yaml: Basic Gemini MCP testing

    • gemini_mcp_example.yaml: Weather service integration example

    • gemini_streamable_http_test.yaml: HTTP transport testing

    • multimcp_gemini.yaml: Multi-server MCP configuration

    • Additional Claude Code MCP configurations

Changed#

  • Dependencies: Updated package requirements

    • Added mcp>=1.12.0 for official MCP protocol support

    • Added aiohttp>=3.8.0 for HTTP-based MCP communication

    • Updated pyproject.toml and requirements.txt

  • Documentation: Enhanced project documentation

    • Created technical analysis documents for Gemini MCP integration

    • Added comprehensive MCP tools README with architecture diagrams

    • Added security and troubleshooting guides for MCP

Technical Details#

  • Commits: 40+ commits including MCP integration, documentation, and bug fixes

  • Files Modified: 35+ files across MCP modules, backends, configurations, and tests

  • Security Features: Configurable security levels (strict/moderate/permissive)

  • Contributors: @praneeth999 @qidanrui @sonichi @a5507203 @ncrispino @Henry-811 and the MassGen team

[0.0.14] - 2025-09-02#

Added#

  • Enhanced Logging System: Improved logging infrastructure with add_log feature

    • Better log organization and preservation for multi-agent workflows

    • Enhanced workspace management for Claude Code agents

    • New final answer directory structure in Claude Code and logs for storing final results

Documentation#

  • Release Documents: Updated release documentation and materials

    • Updated CHANGELOG.md for better release tracking

    • Removed unnecessary use case documentation

Technical Details#

  • Commits: 19 commits

  • Files Modified: Logging system enhancements, documentation updates

  • New Features: Enhanced logging, improved final presentation logging for Claude Code

  • Contributors: @qidanrui @sonichi and the MassGen team

[0.0.13] - 2025-08-28#

Added#

  • Unified Logging System: Better logging infrastructure for better debugging and monitoring

    • New centralized logger_config.py with colored console output and file logging

    • Debug mode support via --debug CLI flag for verbose logging

    • Consistent logging format across all backends, including Claude, Gemini, Grok, Azure OpenAI, and other providers

    • Color-coded log levels for better visibility (DEBUG: cyan, INFO: green)

  • Windows Platform Support: Enhanced cross-platform compatibility

    • Windows-specific fixes for terminal display and color output

    • Improved path handling for Windows file systems

    • Better process management on Windows platform

Changed#

  • Frontend Improvements: Refined display

    • Enhanced rich terminal display formatting to not show debug info in the final presentation

  • Documentation Updates: Improved project documentation

    • Updated CONTRIBUTING.md with better guidelines

    • Enhanced README with logging configuration details

    • Renamed roadmap from v0.0.13 to v0.0.14 for future planning

Technical Details#

  • Commits: 35+ commits including new logging system and Windows support

  • Files Modified: 24+ files across backend, frontend, logging, and CLI modules

  • New Features: Unified logging system with debug mode, Windows platform support

  • Contributors: @qidanrui @sonichi @Henry-811 @JeffreyCh0 @voidcenter and the MassGen team

[0.0.12] - 2025-08-27#

Added#

  • Enhanced Claude Code Agent Context Sharing: Improved multiple Claude Code agent coordination with workspace sharing

    • New workspace snapshot stored in orchestrator’s space for better context management

    • New temporary working directory for each agent, stored in orchestrator’s space

    • Claude Code agents can now share context by referencing their own temporary working directory in the orchestrator’s workspace

    • Anonymous agent context mapping when referencing temporary directories

    • Improved context preservation across agent coordination cycles

  • Advanced Orchestrator Configurations: Enhanced orchestrator configurations

    • Configurable system message support for orchestrator

    • New snapshot and temporary workspace settings for better context management

Changed#

  • Documentation Updates: documentation improvements

    • Updated README with current features and usage examples

    • Improved configuration examples and setup instructions

Technical Details#

  • Commits: 10+ commits including context sharing enhancements, workspace management, and configuration improvements

  • Files Modified: 20+ files across orchestrator, backend, configuration, and documentation

  • New Features: Enhanced Claude Code agent workspace sharing with temporary working directories and snapshot mechanisms

  • Contributors: @qidanrui @sonichi @Henry-811 @JeffreyCh0 @voidcenter and the MassGen team

[0.0.11] - 2025-08-25#

Known Issues#

  • System Message Handling in Multi-Agent Coordination: Critical issues affecting Claude Code agents

    • Lost System Messages During Final Presentation (orchestrator.py:1183)

      • Claude Code agents lose domain expertise during final presentation

      • ConfigurableAgent doesn’t properly expose system messages via agent.system_message

    • Backend Ignores System Messages (claude_code.py:754-762)

      • Claude Code backend filters out system messages from presentation_messages

      • Only processes user messages, causing loss of agent expertise context

      • System message handling only works during initial client creation, not with reset_chat=True

    • Ambiguous Configuration Sources

      • Multiple conflicting system message sources: custom_system_instruction, system_prompt, append_system_prompt

      • Backend parameters silently override AgentConfig settings

      • Unclear precedence and behavior documentation

    • Architecture Violations

      • Orchestrator contains Claude Code-specific implementation details

      • Tight coupling prevents easy addition of new backends

      • Violates separation of concerns principle

Fixed#

  • Custom System Message Support: Enhanced system message configuration and preservation

    • Added base_system_message parameter to conversation builders for agent’s custom system message

    • Orchestrator now passes agent’s get_configurable_system_message() to conversation builders

    • Custom system messages properly combined with MassGen coordination instructions instead of being overwritten

    • Backend-specific system prompt customization (system_prompt, append_system_prompt)

  • Claude Code Backend Enhancements: Improved integration and configuration

    • Better system message handling and extraction

    • Enhanced JSON structured response parsing

    • Improved coordination action descriptions

  • Final Presentation & Agent Logic: Enhanced multi-agent coordination (#135)

    • Improved final presentation handling for Claude Code agents

    • Better coordination between agents during final answer selection

    • Enhanced CLI presentation logic

    • Agent configuration improvements for workflow coordination

  • Evaluation Message Enhancement: Improved synthesis instructions

    • Changed to “digest existing answers, combine their strengths, and do additional work to address their weaknesses”

    • Added “well” qualifier to evaluation questions

    • More explicit guidance for agents to synthesize and improve upon existing answers

Changed#

  • Documentation Updates: Enhanced project documentation

    • Renamed roadmap from v0.0.11 to v0.0.12 for future planning

    • Updated README with latest features and improvements

    • Improved CONTRIBUTING guidelines

    • Enhanced configuration examples and best practices

Added#

  • New Configuration Files: Introduced additional YAML configuration files

    • Added multi_agent_playwright_automation.yaml for browser automation workflows

Removed#

  • Deprecated Configurations: Cleaned up configuration files

    • Removed gemini_claude_code_paper_search_mcp.yaml

    • Removed gpt5_claude_code_paper_search_mcp.yaml

  • Gemini CLI Tests: Removed Gemini CLI related tests

Technical Details#

  • Commits: 25+ commits including bug fixes, feature additions, and improvements

  • Files Modified: 35+ files across backend, orchestrator, frontend, configuration, and documentation

  • New Configuration: multi_agent_playwright_automation.yaml for browser automation workflows

  • Contributors: @qidanrui @Leezekun @sonichi @voidcenter @Daucloud @Henry-811 and the MassGen team

[0.0.10] - 2025-08-22#

Added#

  • Azure OpenAI Support: Integration with Azure OpenAI services

    • New azure_openai.py backend with async streaming capabilities

    • Support for Azure-hosted GPT-4.1 and GPT-5-chat models

    • Configuration examples for single and multi-agent Azure setups

    • Test suite for Azure OpenAI functionality

  • Enhanced Claude Code Backend: Major refactoring and improvements

    • Simplified MCP (Model Context Protocol) integration

  • Final Presentation Support: New orchestrator presentation capabilities

    • Support for final answer presentation in multi-agent scenarios

    • Fallback mechanisms for presentation generation

    • Test coverage for presentation functionality

Fixed#

  • Claude Code MCP: Cleaned up and simplified MCP implementation

    • Removed redundant MCP server and transport modules

  • Configuration Management: Improved YAML configuration handling

    • Fixed Azure OpenAI deployment configurations

    • Updated model mappings for Azure services

Changed#

  • Backend Architecture: Significant refactoring of backend systems

    • Consolidated Azure OpenAI implementation using AsyncAzureOpenAI

    • Improved error handling and streaming capabilities

    • Enhanced async support across all backends

  • Documentation Updates: Enhanced project documentation

    • Updated README with Azure OpenAI setup instructions

    • Renamed roadmap from v0.0.10 to v0.0.11

    • Improved presentation materials for DataHack Summit 2025

  • Test Infrastructure: Expanded test coverage

    • Added comprehensive Azure OpenAI backend tests

    • Integration tests for final presentation functionality

    • Simplified test structure with better coverage

Removed#

  • Deprecated MCP Components: Removed unused MCP modules

    • Removed standalone MCP client, transport, and server implementations

    • Cleaned up MCP test files and testing checklist

    • Simplified Claude Code backend by removing redundant MCP code

Technical Details#

  • Commits: 35+ commits including Azure OpenAI integration and Claude Code improvements

  • Files Modified: 30+ files across backend, configuration, tests, and documentation

  • New Backend: Azure OpenAI backend with full async support

  • Contributors: @qidanrui @Leezekun @sonichi and the MassGen team

[0.0.9] - 2025-08-22#

Added#

  • Quick Start Guide: Comprehensive quickstart documentation in README

    • Streamlined setup instructions for new users

    • Example configurations for getting started quickly

    • Clear installation and usage steps

  • Multi-Agent Configuration Examples: New configuration files for various setups

    • Paper search configuration with GPT-5 and Claude Code

    • Multi-agent setups with different model combinations

  • Roadmap Documentation: Added comprehensive roadmap for version 0.0.10

    • Focused on Claude Code context sharing between agents

    • Multi-agent context synchronization planning

    • Enhanced backend features and CLI improvements roadmap

Fixed#

  • Web Search Processing: Fixed bug in response handling for web search functionality

    • Improved error handling in web search responses

    • Better streaming of search results

  • Rich Terminal Display: Fixed rendering issues in terminal UI

    • Resolved display formatting problems

    • Improved message rendering consistency

Changed#

  • Claude Code Integration: Optimized Claude Code implementation

    • MCP (Model Context Protocol) integration

    • Streamlined Claude Code backend configuration

  • Documentation Updates: Enhanced project documentation

    • Updated README with quickstart guide

    • Added CONTRIBUTING.md guidelines

    • Improved configuration examples

Technical Details#

  • Commits: 10 commits including bug fixes, code cleanup, and documentation updates

  • Files Modified: Multiple files across backend, configurations, and documentation

  • Contributors: @qidanrui @sonichi @Leezekun @voidcenter @JeffreyCh0 @stellaxiang

[0.0.8] - 2025-08-18#

Added#

  • Timeout Management System: Timeout capabilities for better control and time management

    • New TimeoutConfig class for configuring timeout settings at different levels

    • Orchestrator-level timeout with graceful fallback

    • Added fast_timeout_example.yaml configuration demonstrating conservative timeout settings

    • Test suite for timeout mechanisms in test_timeout.py

    • Timeout indicators in Rich Terminal Display showing remaining time

  • Enhanced Display Features: Improved visual feedback and user experience

    • Optimized message display formatting for better readability

    • Enhanced status indicators for timeout warnings and fallback notifications

    • Improved coordination UI with better multi-agent status tracking

Fixed#

  • Display Optimization: Multiple improvements to message rendering

    • Fixed message display synchronization issues

    • Optimized terminal display refresh rates

    • Improved handling of concurrent agent outputs

    • Better formatting for multi-line responses

  • Configuration Management: Enhanced robustness of configuration loading

    • Fixed import ordering issues in CLI module

    • Improved error handling for missing configurations

    • Better validation of timeout settings

Changed#

  • Orchestrator Architecture: Simplified and enhanced timeout implementation

    • Refactored timeout handling to be more efficient and maintainable

    • Improved graceful degradation when timeouts occur

    • Better integration with frontend displays for timeout notifications

    • Enhanced error messages for timeout scenarios

  • Code Cleanup: Removed deprecated configurations and improved code organization

    • Removed obsolete two_agents_claude_code configuration

    • Cleaned up unused imports and redundant code

    • Reformatted files for better consistency

  • CLI Enhancements: Improved command-line interface functionality

    • Better timeout configuration parsing

    • Enhanced error reporting for timeout scenarios

    • Improved help documentation for timeout settings

Technical Details#

  • Commits: 18 commits including various optimizations and bug fixes

  • Files Modified: 13+ files across orchestrator, frontend, configuration, and test modules

  • Key Features: Timeout management system with graceful fallback, enhanced display optimizations

  • New Configuration: fast_timeout_example.yaml for time-conscious usage

  • Contributors: @qidanrui @Leezekun @sonichi @voidcenter

[0.0.7] - 2025-08-15#

Added#

  • Local Model Support: Complete integration with LM Studio for running open-weight models locally

    • New lmstudio.py backend with automatic server management

    • Automatic model downloading and loading capabilities

    • Zero-cost reporting for local model usage

  • Extended Provider Support: Enhanced ChatCompletionsBackend to support multiple providers

    • Cerebras AI, Together AI, Fireworks AI, Groq, Nebius AI Studio, OpenRouter

    • Provider-specific environment variable detection

    • Automatic provider name inference from base URLs

  • New Configuration Files: Added configurations for local and hybrid model setups

    • lmstudio.yaml: Single agent configuration for LM Studio

    • two_agents_opensource_lmstudio.yaml: Hybrid setup with GPT-5 and local Qwen model

    • gpt5nano_glm_qwen.yaml: Three-agent setup combining Cerebras, ZAI GLM-4.5, and local Qwen

    • Updated three_agents_opensource.yaml for open-source model combinations

Fixed#

  • Backend Stability: Improved error handling across all backend systems

    • Fixed API key resolution and client initialization

    • Enhanced provider name detection and configuration

    • Resolved streaming issues in ChatCompletionsBackend

  • Documentation: Corrected references and updated model naming conventions

    • Fixed GPT model references in documentation diagrams

    • Updated case study file naming consistency

Changed#

  • Backend Architecture: Refactored ChatCompletionsBackend for better extensibility

    • Improved provider registry and configuration management

    • Enhanced logging and debugging capabilities

    • Streamlined message processing and tool handling

  • Dependencies: Added new requirements for local model support

    • Added lmstudio==1.4.1 for LM Studio Python SDK integration

  • Documentation Updates: Enhanced documentation for local model usage

    • Updated environment variables documentation

    • Added setup instructions for LM Studio integration

    • Improved backend configuration examples

Technical Details#

  • Commits: 16 commits including merge pull requests #80 and #100

  • Files Modified: 17+ files across backend, configuration, documentation, and CLI modules

  • New Dependencies: LM Studio SDK (lmstudio==1.4.1)

  • Contributors: @qidanrui @sonichi @Leezekun @praneeth999 @voidcenter

[0.0.6] - 2025-08-13#

Added#

  • GLM-4.5 Model Support: Integration with ZhipuAI’s GLM-4.5 model family

    • Added GLM-4.5 backend support in chat_completions.py

    • New configuration file zai_glm45.yaml for GLM-4.5 agent setup

    • Updated zai_coding_team.yaml with GLM-4.5 integration

    • Added GLM-4.5 model mappings and environment variable support

  • Enhanced Reasoning Display: Improved reasoning presentation for GLM models

    • Added reasoning start and completion indicators in frontend displays

    • Enhanced coordination UI to show reasoning progress

    • Better visual formatting for reasoning states in terminal display

Fixed#

  • Claude Code Backend: Updated default allowed tools configuration

    • Fixed default tools setup in claude_code.py backend

Changed#

  • Documentation Updates: Updated README.md with GLM-4.5 support information

    • Added GLM-4.5 to supported models list

    • Updated environment variables documentation for ZhipuAI integration

    • Enhanced model comparison and configuration examples

  • Configuration Management: Enhanced agent configuration system

    • Updated agent_config.py with GLM-4.5 support

    • Improved CLI integration for GLM models

    • Better model parameter handling in utils.py

Technical Details#

  • Commits: 6 major commits including merge pull requests #90 and #94

  • Files Modified: 12+ files across backend, frontend, configuration, and documentation

  • New Dependencies: ZhipuAI GLM-4.5 model integration

  • Contributors: @Stanislas0 @qidanrui @sonichi @Leezekun @voidcenter

[0.0.5] - 2025-08-11#

Added#

  • Claude Code Integration: Complete integration with Claude Code CLI backend

    • New claude_code.py backend with streaming capabilities and tool support

    • Support for Claude Code SDK with stateful conversation management

    • JSON tool call functionality and proper tool result handling

    • Session management with append system prompt support

  • New Configuration Files: Added Claude Code specific YAML configurations

    • claude_code_single.yaml: Single agent setup using Claude Code backend

    • claude_code_flash2.5.yaml: Multi-agent setup with Claude Code and Gemini Flash 2.5

    • claude_code_flash2.5_gptoss.yaml: Multi-agent setup with Claude Code, Gemini Flash 2.5, and GPT-OSS

  • Test Coverage: Added test suite for Claude Code functionality

    • test_claude_code_orchestrator.py: orchestrator testing

    • Backend-specific test coverage for Claude Code integration

Fixed#

  • Backend Stability: Multiple critical bug fixes across all backend systems

    • Fixed parameter handling in chat_completions.py, claude.py, gemini.py, grok.py

    • Resolved response processing issues in response.py

    • Improved error handling and client existence validation

  • Tool Call Processing: Enhanced tool call parsing and execution

    • Deduplicated tool call parsing logic across backends

    • Fixed JSON tool call functionality and result formatting

    • Improved builtin tool result handling in streaming contexts

  • Message Handling: Resolved system message processing issues

    • Fixed SystemMessage to StreamChunk conversion

    • Proper session info extraction from system messages

    • Cleaned up message formatting and display consistency

  • Frontend Display: Fixed output formatting and presentation

    • Improved rich terminal display formatting

    • Better coordination UI integration and multi-turn conversation display

    • Enhanced status message display with proper newline handling

Changed#

  • Code Architecture: Significant refactoring and cleanup across the codebase

    • Renamed and consolidated backend files for consistency

    • Simplified chat agent architecture and removed redundant code

    • Streamlined orchestrator logic with improved error handling

  • Configuration Management: Updated and cleaned up configuration files

    • Updated agent configuration with Claude Code support

  • Backend Infrastructure: Enhanced backend parameter handling

    • Improved stateful conversation management across all backends

    • Better integration with orchestrator for multi-agent coordination

    • Enhanced streaming capabilities with proper chunk processing

  • Documentation: Updated project documentation

    • Added Claude Code setup instructions in README

    • Updated backend architecture documentation

    • Improved reasoning and streaming integration notes

Technical Details#

  • Commits: 50+ commits since version 0.0.4

  • Files Modified: 25+ files across backend, configuration, frontend, and test modules

  • Major Components Updated: Backend systems, orchestrator, frontend display, configuration management

  • New Dependencies: Added Claude Code SDK integration

  • Contributors: @qidanrui @randombet @sonichi

[0.0.4] - 2025-08-08#

Added#

  • GPT-5 Series Support: Full support for OpenAI’s GPT-5 model family

    • GPT-5: Full-scale model with advanced capabilities

    • GPT-5-mini: Efficient variant for faster responses

    • GPT-5-nano: Lightweight model for resource-constrained deployments

  • New Model Parameters: Introduced GPT-5 specific configuration options

    • text.verbosity: Control response detail level (low/medium/high)

    • reasoning.effort: Configure reasoning depth (minimal/medium/high)

    • Note: reasoning parameter is mutually exclusive with web search capability

  • Configuration Files: Added dedicated YAML configurations

    • gpt5.yaml: Three-agent setup with GPT-5, GPT-5-mini, and GPT-5-nano

    • gpt5_nano.yaml: Three GPT-5-nano agents with different reasoning levels

  • Extended Model Support: Added GPT-5 series to model mappings in utils.py

  • Reasoning for All Models: Extended reasoning parameter support beyond GPT-5 models

Fixed#

  • Tool Output Formatting: Added proper newline formatting for provider tool outputs

    • Web search status messages now display on new lines

    • Code interpreter status messages now display on new lines

    • Search query display formatting improved

  • YAML Configuration: Fixed configuration syntax in GPT-5 related YAML files

  • Backend Response Handling: Multiple bug fixes in response.py for proper parameter handling

Changed#

  • Documentation Updates:

    • Updated README.md to highlight GPT-5 series support

    • Changed example commands to use GPT-5 models

    • Added new backend configuration examples with GPT-5 specific parameters

    • Updated models comparison table to show GPT-5 as latest OpenAI model

  • Parameter Handling: Improved backend parameter validation

    • Temperature parameter now excluded for GPT-5 series models (like o-series)

    • Max tokens parameter now excluded for GPT-5 series models

    • Added conditional logic for GPT-5 specific parameters (text, reasoning)

  • Version Number: Updated to 0.0.4 in massgen/init.py

Technical Details#

  • Commits: 9 commits since version 0.0.3

  • Files Modified: 6 files (response.py, utils.py, README.md, init.py, and 2 new config files)

  • Contributors: @qidanrui @sonichi @voidcenter @JeffreyCh0 @praneeth999

[0.0.3] - 2025-08-03#

Added#

  • Complete architecture with foundation release

  • Multi-backend support: Claude (Messages API), Gemini (Chat API), Grok (Chat API), OpenAI (Responses API)

  • Builtin tools: Code execution and web search with streaming results

  • Async streaming with proper chat agent interfaces and tool result handling

  • Multi-agent orchestration with voting and consensus mechanisms

  • Real-time frontend displays with multi-region terminal UI

  • CLI with file-based YAML configuration and interactive mode

  • Proper StreamChunk architecture separating tool_calls from builtin_tool_results

  • Multi-turn conversation support with dynamic context reconstruction

  • Chat interface with orchestrator supporting async streaming

  • Case study configurations and specialized YAML configs

  • Claude backend support with production-ready multi-tool API and streaming

  • OpenAI builtin tools support for code execution and web search streaming

Fixed#

  • Grok backend testing and compatibility issues

  • CLI multi-turn conversation display with coordination UI integration

  • Claude streaming handler with proper tool argument capture

  • CLI backend parameter passing with proper ConfigurableAgent integration

Changed#

  • Restructured codebase with new architecture

  • Improved message handling and streaming capabilities

  • Enhanced frontend features and user experience

[0.0.1] - Initial Release#

Added#

  • Basic multi-agent system framework

  • Support for OpenAI, Gemini, and Grok backends

  • Simple configuration system

  • Basic streaming display

  • Initial logging capabilities

See Also#

—

Last synced with CHANGELOG.md: October 2025

Note

Primary Source: This page includes content from the root CHANGELOG.md file, which is the authoritative source for all MassGen release history.

This changelog follows the Keep a Changelog format and adheres to Semantic Versioning.

Contents