Architecture
FERAL is structured as a layered system. The Brain is the central runtime — a FastAPI Python server that orchestrates reasoning, memory, tools, voice, hardware, and UI generation. Clients (web, CLI, hardware daemons, messaging channels) connect over HTTP and WebSocket.System Diagram
Core Layers
Reasoning Plane
The Orchestrator (feral-core/agents/orchestrator.py) runs the main agent loop:
- Receive user intent (text, voice, or hardware event).
- Load context: memory tiers, identity, session state.
- Route to an LLM provider via the multi-provider interface.
- Execute tools selected by the LLM.
- Store results in memory, update the knowledge graph.
- Return response — optionally as GenUI SDUI payload.
Memory Plane
| Tier | Storage | Lifecycle |
|---|---|---|
| Working Memory | RAM | Per-session; cleared on session end |
| Notes | SQLite + FTS | Persistent; user-created via “remember X” |
| Episodes | SQLite + FTS | Auto-generated conversation summaries |
| Knowledge Graph | SQLite (S-P-O triples) | Extracted facts and relationships |
- Memory Wiki — compiles notes, episodes, and graph entries into durable wiki pages with provenance tracking.
- Session Snapshots — snapshot, branch, and restore full conversation + working memory state.
~/.feral/memory.db.
Workflow Plane
TaskFlows (feral-core/agents/taskflow.py) are durable background workflows backed by SQLite:
- Persist through restarts.
- Support
wait(pause until a condition),resume, andcancel. - Each flow tracks a step timeline with status transitions.
- API:
POST /api/taskflows,GET /api/taskflows/{id},POST /api/taskflows/{id}/resume.
Interface Plane (GenUI)
The GenUI engine generates Server-Driven UI payloads from tool results and provider contracts:- A tool returns structured data.
- The GenUI engine selects an appropriate SDUI template (card, chart, map, form, list).
- The payload is sent to the client, which renders it without knowing the tool’s internals.
Execution Plane
- Tools & Skills — computer use (shell, files, grep), web search, browser automation, custom JSON manifests, Python plugins, WASM sandboxed skills.
- MCP — dual-role: expose FERAL’s tools as an MCP server, and consume external MCP servers.
- Channels — bridge to Telegram, Discord, Slack, WhatsApp.
- HUP (Hardware Use Protocol) — devices connect via WebSocket, register with a declarative manifest, stream telemetry, and receive commands.
Security
- Blind Vault — API keys stored encrypted, never exposed to the LLM.
- WASM Sandbox — untrusted skills run in a Wasmtime sandbox.
- Permission Plane — tool-level approval policies.
Wire Protocol
All client↔brain communication uses theFeralMessage envelope defined in feral-core/models/protocol.py:
| Path | Purpose |
|---|---|
/v1/session | Client sessions — chat, voice, UI events |
/v1/node | Hardware daemon connections |
/sync | Federated memory sync between nodes |
Data Storage
| Path | Contents |
|---|---|
~/.feral/config.yaml | Feature flags, LLM provider, voice mode |
~/.feral/credentials.json | API keys (chmod 600) |
~/.feral/identity.yaml | Agent name, personality, rules |
~/.feral/memory.db | Memory tiers + knowledge graph (SQLite) |
~/.feral/genui_surfaces/ | Cached compiled GenUI provider surfaces |
~/.feral/skills/ | User-installed skill manifests |
~/.feral/mcp_servers.json | External MCP server connections |
Tech Stack
| Layer | Technology |
|---|---|
| Brain | Python 3.11+, FastAPI, Uvicorn, Pydantic v2 |
| Storage | SQLite + FTS5 + optional sqlite-vec |
| LLM | OpenAI SDK, Anthropic, Google Generative AI, Groq, Ollama |
| Web UI | React 18, Vite 5, Tailwind CSS 4, React Router 7 |
| Desktop | Tauri 2 (Rust + React) |
| Hardware | WebSocket mesh, HUP protocol |
| Packaging | PyPI (feral-ai), npm (@feral/sdk), Nix flake, Docker Compose |
