The Experimental AI Microkernel OS
Project description
FyodorOS
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The Experimental AI Microkernel
FyodorOS is a simulated operating system designed from the ground up for Autonomous AI Agents. Unlike traditional OSs designed for humans (GUI/CLI) or servers (API), FyodorOS exposes the entire system state as a Document Object Model (DOM), allowing Agents to "perceive" and interact with the kernel natively.
🚀 Vision
We believe that for AI Agents to be truly useful and safe, they need an environment built for them. FyodorOS provides:
- Structured Observation: The OS state (Filesystem, Processes, Users) is a queryable DOM tree.
- Cognitive Loop: Built-in ReAct (Reasoning + Acting) loop at the kernel level.
- Safety Sandbox: A strict, rule-based verification layer that constraints Agent actions before execution.
- Agent-Native Apps: Standard tools (
browser,explorer,calc) that return structured JSON/DOM instead of plain text, minimizing token usage and parsing errors. - Cloud Integration (v0.5.0): Native Docker and Kubernetes support.
- Long-Term Memory (v0.7.0): Persistent semantic storage allowing agents to learn and recall information.
📝 What's New
[0.7.0] - Persistent Memory & Performance
FyodorOS v0.7.0 introduces a major capability for Autonomous Agents: Memory.
- Semantic Storage: Agents can now store and recall information using
sys_memory_*syscalls, backed by ChromaDB. - Auto-Recall: The Agent loop automatically searches for relevant past memories before starting a new task, enabling context-aware execution.
- Persistence: Memory state is preserved in
~/.fyodor/memoryacross system reboots. - Optimization: Significant performance improvements in filesystem path resolution (
sys_ls).
[0.6.0] - Verified System Integrity (Test Sweep Phase 2.3)
FyodorOS v0.6.0 focuses on system integrity and reliability:
- Verified Core Subsystems: Successfully passed extensive adversarial tests for Service Manager, Kernel Boot, Sandbox, and Plugin Lifecycle.
- Boot Determinism: Confirmed clean, deterministic startup and shutdown cycles.
- Advanced Service Manager: New ServiceManager architecture supports DAG-based dependencies and 3-Phase Shutdown.
✨ Key Features
🧠 Kernel-Level Agent
The OS integrates an LLM-powered agent directly into the shell.
- Command:
agent "Research the latest news on AI" - Mechanism: The agent perceives the system via
SystemDOM, creates a To-Do list, and executes actions in a sandboxed loop.
💾 Persistent Memory
The Agent now remembers.
- Semantic Recall: Uses vector embeddings (ChromaDB) to find relevant past interactions.
- Auto-Injection: Relevant context is automatically injected into the Agent's prompt.
- Commands:
sys_memory_store,sys_memory_search,sys_memory_delete.
🌐 Agent Browser (Playwright Integration)
FyodorOS includes a specialized browser for agents.
- DOM Tree Output: Returns a simplified, semantic JSON representation of web pages.
- Interaction: Agents can
clickandtypeusing element IDs directly. - Efficiency: Strips unnecessary noise (CSS/Scripts) to save context window.
🛡️ Safety Sandbox (Verified v0.6.0)
Every action taken by the Agent is intercepted by the C++ reinforced AgentSandbox.
- Virtual Filesystem: The agent is jailed in
~/.fyodor/sandbox. All paths are virtualized. - Path Traversal Protection: C++ layer prevents escaping the sandbox.
- App Whitelisting: Only authorized "Agent Apps" can be executed.
🧪 Test Coverage (v0.6.0)
We maintain rigorous test suites to ensure system invariants hold under pressure.
- Service Manager: Boot correctness, reverse teardown, failure resilience.
- Kernel: Deterministic boot, double-boot isolation, controlled shutdown.
- Sandbox: File resolution integrity, IOError containment, leakage prevention.
Tests are run using pytest:
pytest tests/phase2_3/
🔌 Plugins (New in v0.3.0)
FyodorOS supports a powerful plugin system.
- Github Integration:
github- List repos, create issues, view PRs. - Slack Notifier:
slack_notifier- Send notifications to Slack. - Usage Dashboard:
usage_dashboard- Background system monitoring. View withfyodor dashboard.
Developing Plugins (Polyglot Support)
FyodorOS supports Python, C++, and Node.js plugins.
Create a new plugin:
fyodor plugin create my_plugin --lang cpp
📦 Installation & Usage
-
Clone the Repository
git clone https://github.com/Kiy-K/FyodorOS.git cd fyodoros
-
Install Package You can install FyodorOS as a Python package.
Via pip (Recommended):
pip install . playwright install chromium
Via Conda:
conda env create -f environment.yml conda activate fyodoros playwright install chromium
-
Launch the OS
Option A: Using the CLI (if installed)
# 1. Setup (Configure API Keys) fyodor setup # 2. Start (Auto-login as Guest) fyodor start # 3. Interactive Login fyodor login # 4. Open Launcher Menu (TUI) fyodor tui
-
Interact Inside the FyodorOS Shell:
# Run a standard command guest@fyodoros:/> ls # Task the Agent guest@fyodoros:/> agent "Create a file named hello.txt in my home folder" # Manual Creation guest@fyodoros:/> create notes.txt "Meeting at 5pm"
💡 Use Cases
1. Web Research & Memory
Scenario: You want the agent to look up information and remember it for later. Command:
agent "Find the current stock price of AAPL and save it to memory"
Agent Process:
- Calls
run_process("browser", ["navigate", ...]). - Parses the page for the price.
- Calls
sys_memory_store("AAPL price is $200", {"symbol": "AAPL"}). - Later, if you ask "What is the AAPL price?", the agent will recall this.
2. System Management
Scenario: You want to add a new user securely. Command:
agent "Create a new user named 'developer' with password 'secure123'"
Agent Process:
- Checks if user exists using
run_process("user", ["list"]). - Calls
run_process("user", ["add", "developer", "secure123"]). - Verifies the addition.
🏗️ Architecture
src/fyodoros/kernel/: Core logic including Scheduler, SyscallHandler, MemoryManager, and the new Agent Layer.src/fyodoros/bin/: User-space applications. These are "Agent-Aware" binaries that output JSON.src/fyodoros/shell/: The interactive CLI wrapper.src/fyodoros/cli.py: The launcher and configuration tool.
🤝 Contributing
FyodorOS is an experimental sandbox. We welcome contributions to:
- Expand the standard library of Agent Apps.
- Improve the DOM representation of system state.
- Implement more complex Sandbox rules.
Built for the future of Autonomous Computing.
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