maestro

# MAESTRO: Your Self-Hosted AI Research Assistant > **Version 0.1.10-alpha (Oct 12, 2025) - Azure OpenAI & Configuration Improvements** > > - **Azure OpenAI Support**: Support for Azure OpenAI including GPT-5 models with automatic parameter handling > - **Manual Model Entry**: New toggle to bypass automatic model fetching for providers like Azure that don't support `/models` endpoint > - **Improved Error Handling**: Fixed 401 errors from external providers no longer logging users out > - **Settings Fixes**: Mission settings now persist correctly across server restarts with proper priority handling > - **UX Improvements**: Disabled autocomplete on API key fields to prevent browser autofill issues 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. ## Documentation **[View Full Documentation](https://murtaza-nasir.github.io/maestro/)** - **[Quick Start](https://murtaza-nasir.github.io/maestro/getting-started/quickstart/)** - Get up and running in minutes - **[Installation](https://murtaza-nasir.github.io/maestro/getting-started/installation/)** - Platform-specific setup - **[Configuration](https://murtaza-nasir.github.io/maestro/getting-started/configuration/overview/)** - AI providers and settings - **[User Guide](https://murtaza-nasir.github.io/maestro/user-guide/)** - Complete feature guide - **[Example Reports](https://murtaza-nasir.github.io/maestro/example-reports/)** - Sample outputs from various models - **[Troubleshooting](https://murtaza-nasir.github.io/maestro/troubleshooting/)** - Common issues and solutions ## Screenshots

Document Library

Document Groups

Mission Settings

Chat Interface

Writing Assistant

Research Transparency

AI-Generated Notes

Mission Tracking

Agent Reflection

## Getting Started ### Prerequisites - Docker and Docker Compose (v2.0+) - 16GB RAM minimum (32GB recommended) - 30GB free disk space - API keys for at least one AI provider ### Quick Start ```bash # 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-backend ``` Access at **http://localhost** • Default: `admin` / `pass found in .env` For detailed installation instructions, see the [Installation Guide](https://murtaza-nasir.github.io/maestro/getting-started/installation/). ## Configuration - **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](https://murtaza-nasir.github.io/maestro/). ## Recent Releases ### Version 0.1.10-alpha (October 12, 2025) **Azure OpenAI & Configuration Improvements** - Azure OpenAI support including GPT-5 models with automatic parameter handling - Manual model entry toggle for providers without `/models` endpoint support - Fixed 401 errors from external providers no longer logging users out - Mission settings now persist correctly across server restarts - Disabled autocomplete on API key fields to prevent browser autofill issues ### Version 0.1.9-alpha (October 3, 2025) **Stability & Security Update** - Fixed mission pause/resume with proper checkpoint handling - Replaced passlib with maintained libpass fork - Resolved Round/Pass counter and activity log persistence issues - Fixed bcrypt compatibility for authentication ### Version 0.1.8-alpha (September 26, 2025) **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 ## Core Features - **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 ## License This project is **dual-licensed**: 1. **GNU Affero General Public License v3.0 (AGPLv3)**: MAESTRO is offered under the AGPLv3 as its open-source license. 2. **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. ## Contributing Feedback, bug reports, and feature suggestions are highly valuable. Please feel free to open an Issue on the GitHub repository.