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ghostwrightAgentic co-worker with dedicated compute and evolving capabilities
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An AI co-worker that operates autonomously on its own dedicated virtual machine, offering persistent memory and self-evolving capabilities. Phantom addresses the ephemeral nature of current AI agents by providing a persistent workspace where agents can install software, build infrastructure, and continuously improve their performance on user-specific tasks, benefiting both technical and non-technical users seeking a truly integrated AI assistant.
How It Works
Phantom runs as a Bun process on a dedicated VM, isolating the agent's operations from the user's local machine. It leverages a multi-tiered memory system (Qdrant, Ollama) for persistent recall and a novel "Self-Evolution Engine." This engine employs a 6-step pipeline—Observe, Critique, Generate, Validate (using LLM judges), Apply, and Consolidate—to allow the agent to autonomously rewrite its own configuration, adapt to user workflows, and improve over time. Agents can also dynamically create and register MCP tools at runtime, enhancing their capabilities on the fly.
Quick Start & Requirements
The recommended installation uses Docker:
curl -fsSL https://raw.githubusercontent.com/ghostwright/phantom/main/docker-compose.user.yaml -o docker-compose.yaml
curl -fsSL https://raw.githubusercontent.com/ghostwright/phantom/main/.env.example -o .env
Edit .env to include ANTHROPIC_API_KEY, Slack tokens, and OWNER_SLACK_USER_ID. Then run docker compose up -d. Ollama pulls the nomic-embed-text model. RESEND_API_KEY is needed for email sending. A managed, free service is available at ghostwright.dev/phantom.
Highlighted Details
Maintenance & Community
Phantom is part of the Ghostwright ecosystem, which includes Ghost OS, Shadow, and Specter. Contribution guidelines are available in CONTRIBUTING.md.
Licensing & Compatibility
Licensed under the Apache 2.0 license, permitting commercial use, modification, and distribution within closed-source projects.
Limitations & Caveats
The system relies heavily on Anthropic's Claude models and SDK. The self-evolution and dynamic tool-creation features, while powerful, introduce inherent complexity. A dedicated VM is required, incurring monthly costs ($7-20/month suggested), and integration with less established, low-star open-source projects may present stability risks.
1 week ago
Inactive