MAESTRO is an AI-powered research application designed to streamline complex research tasks.

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

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

Screenshots

Document Library

 ![Document Library](images/01-document-library.png)

Document Groups

 ![Document Groups](images/02-document-groups.png)

Mission Settings

 ![Mission Settings](images/03-mission-settings.png)

Chat Interface

 ![Chat with Documents](images/04-chat-with-docs.png)

Writing Assistant

 ![Writing Assistant](images/05-writing-assistant.png)

Research Transparency

 ![Research Transparency](images/06-research-transparency.png)

AI-Generated Notes

 ![Automated Notes](images/07-automated-notes.png)

Mission Tracking

 ![Mission Tracking](images/08-mission-tracking.png)

Agent Reflection

 ![Agent Reflection](images/09-agent-reflection.png)

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

# 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.

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.

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:

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.

Contributing

Feedback, bug reports, and feature suggestions are highly valuable. Please feel free to open an Issue on the GitHub repository.