Version 0.1.9-alpha (Oct 3, 2025) - Stability & Security Update
- Mission Stability: Fixed pause/resume with proper checkpoint handling
- Security Update: Replaced passlib with maintained libpass fork
- Bug Fixes: Resolved Round/Pass counter and activity log persistence issues
- Password Compatibility: Fixed bcrypt compatibility for authentication
MAESTRO is an AI-powered research platform you can host on your own hardware. It's designed to manage complex research tasks from start to finish in a collaborative research environment. Plan your research, let AI agents carry it out, and watch as they generate detailed reports based on your documents and sources from the web.
- Quick Start - Get up and running in minutes
- Installation - Platform-specific setup
- Configuration - AI providers and settings
- User Guide - Complete feature guide
- Example Reports - Sample outputs from various models
- Troubleshooting - Common issues and solutions
Document Library
Document Groups
Mission Settings
Chat Interface
Writing Assistant
Research Transparency
AI-Generated Notes
Mission Tracking
Agent Reflection
- Docker and Docker Compose (v2.0+)
- 16GB RAM minimum (32GB recommended)
- 30GB free disk space
- API keys for at least one AI provider
# Clone and setup
git clone https://github.com/murtaza-nasir/maestro.git
cd maestro
./setup-env.sh # Linux/macOS
# or
.\setup-env.ps1 # Windows PowerShell
# Start services
docker compose up -d
# Monitor startup (takes 5-10 minutes first time)
docker compose logs -f maestro-backendAccess at http://localhost • Default: admin / pass found in .env
For detailed installation instructions, see the Installation Guide.
- CPU Mode: Use
docker compose -f docker-compose.cpu.yml up -d - GPU Support: Automatic detection on Linux/Windows with NVIDIA GPUs
- Network Access: Configure via setup script options
For troubleshooting and advanced configuration, see the documentation.
Mission Resilience & Document Intelligence Update
- Intelligent mission resume with complete checkpoint preservation
- arXiv paper fetcher for direct academic paper processing
- Writing phase resume support
- Document reprocessing and re-embedding capabilities
- Fixed progress indicators for accurate research tracking
Intelligent Document Management & Enhanced Research
- Auto-create document groups from discovered web sources
- Seamless transition from research to writing workspace
- Report versioning with multiple version tracking
- Clickable document references in writing mode
- Improved mission restart and revise functionality
Model Support & Cost Tracking
- GPT-5 support with configurable thinking levels
- Comprehensive cost tracking across all API calls
- Enhanced DeepSeek compatibility
- Improved error handling and retry logic
Major Performance Update
- Complete async backend migration (2-3x faster)
- 50+ bug fixes and stability improvements
- Enhanced UI/UX with LaTeX support
- Multi-Agent Research System: Planning, Research, Reflection, and Writing agents working in concert
- Advanced RAG Pipeline: Dual BGE-M3 embeddings with PostgreSQL + pgvector
- Document Management: PDF, Word, and Markdown support with semantic search
- Web Integration: Multiple search providers (Tavily, LinkUp, Jina, SearXNG)
- Self-Hosted: Complete control over your data and infrastructure
- Local LLM Support: OpenAI-compatible API for running your own models
This project is dual-licensed:
- GNU Affero General Public License v3.0 (AGPLv3): MAESTRO is offered under the AGPLv3 as its open-source license.
- Commercial License: For users or organizations who cannot comply with the AGPLv3, a separate commercial license is available. Please contact the maintainers for more details.
Feedback, bug reports, and feature suggestions are highly valuable. Please feel free to open an Issue on the GitHub repository.