Architecture

Zeus adopts a two-tier backend architecture: the Web API (Next.js) serves as the central gateway handling user management, database operations, and request forwarding for all clients; the AI Backend (FastAPI) focuses exclusively on AI Agent orchestration, tool execution, and node communication.

Overview

Web API is the single entry point for all clients — it handles auth, user data, session/message persistence, credits, tool configuration, and more
AI Backend receives forwarded agent requests from Web API and executes the Agent loop (LLM reasoning + tool calls)
Extension / Desktop nodes maintain a direct WebSocket connection to AI Backend’s Gateway for real-time tool execution (browser automation, desktop control)
Each user has an independent cloud workspace (Supabase Storage / S3) and session state (PostgreSQL Checkpointer)

Two-Tier Backend

Web API (Next.js) — Gateway & Data Layer

The Web API is a Next.js application that serves as the central API gateway for all clients. It owns the database and handles all non-AI concerns:

Responsibility	Details
Authentication	Better Auth (OAuth, email/password, SSO), JWT issuance & verification
User Management	User profiles, avatars, settings, agent preferences
Database	PostgreSQL via Drizzle ORM — sessions, messages, tools, skills, knowledge bases, projects, credits, showcase
Storage	Supabase Storage / S3 (MinIO) — workspace files, skill files, zeus config
Credit System	Usage metering — check & deduct credits before forwarding agent calls
Tool Configuration	CRUD for user tool settings (MCP servers, OAuth tokens, etc.)
Skill Management	Skill CRUD, file upload/download, resource content prefetching
Knowledge Base	KB metadata CRUD, document upload, chunk preview
Session Management	Create/list/delete sessions, message persistence, event tracking
Agent Forwarding	Assemble context (LLM config, tools, skills, env vars) and forward to AI Backend via HTTP SSE

Key API routes (93 total):

Route Group	Examples	Description
`/api/auth/*`	login, register, JWT, SSO, device-code	Authentication
`/api/sessions/*`	CRUD, messages, events, checkpoints	Session & message management
`/api/tools/*`	CRUD, MCP validation	Tool configuration
`/api/skills/*`	CRUD, files, toggle, import	Skill management
`/api/knowledge-base/*`	CRUD, documents, search, upload	Knowledge base
`/api/projects/*`	CRUD, resources, sessions	Project management
`/api/credits/*`	balance, transactions	Credit system
`/api/agent/invoke`	POST → forward to AI Backend	Agent invocation (forwarding)
`/api/agent/resume`	POST → forward to AI Backend	HITL resume (forwarding)
`/api/config/*`	LLM, embedding, sandbox	User configuration
`/api/memory/*`	CRUD, search, profile	Memory management
`/api/scheduled-tasks/*`	CRUD, callbacks	Scheduled task management
`/api/deploy/*`	deploy, restart-dev	Deployment
`/api/storage/*`	files, URLs	File storage

AI Backend (FastAPI) — Agent Execution Engine

The AI Backend is a FastAPI service dedicated to AI Agent orchestration. It receives forwarded requests from the Web API and handles all AI-related operations. The Agent Runtime is the core of the AI Backend — the other modules provide supporting infrastructure around it:

AI Backend (FastAPI)
├── Agent Runtime (Core)
│   ├── AgentService / BaseService — invoke/resume entry, context init
│   ├── DeepAgents Framework — LangGraph-based Agent loop
│   ├── Tool System — Built-in, MCP, OAuth, Connector (4 layers)
│   ├── Prompt Assembly — CORE / SOUL / TOOLS / WORKFLOW / MEMORY + dynamic injection
│   ├── Session & Checkpointer — state persistence, isolation, HITL recovery
│   └── HITL — human approval before sensitive tool execution
├── WebSocket Gateway — real-time communication with Extension / Desktop nodes
├── RAG Service — knowledge base retrieval (vector + BM25 hybrid search)
├── Sandbox — code execution environments (E2B / OpenSandbox / Daytona)
├── Scheduler — scheduled task execution (TaskIQ + RabbitMQ)
└── Channels — Feishu and other channel integrations

Responsibility	Details
Agent Runtime	Core Agent loop — LLM reasoning, tool planning, multi-step execution, prompt assembly, session management
WebSocket Gateway	Real-time bidirectional communication with Extension/Desktop nodes
RAG Service	Knowledge base retrieval (vector + BM25 hybrid search)
Sandbox	Code execution environment management (E2B / OpenSandbox / Daytona)
Scheduler	Task scheduling & async execution (via TaskIQ + RabbitMQ)
Channels	Feishu bot and other channel integrations

AI Backend API routes:

Route	Description	Protocol
`/api/agent/invoke`	Agent conversation invocation	HTTP POST → SSE Stream
`/api/agent/resume`	HITL resume execution	HTTP POST → SSE Stream
`/api/knowledge-base/*`	Knowledge base RAG operations	HTTP REST
`/api/node/*`	Node device queries	HTTP REST
`/api/scheduled-task/*`	Scheduled task management	HTTP REST
`/api/deploy/*`	Coding project deployment	HTTP REST
`/api/sandbox/*`	Sandbox management	HTTP REST
`/ws/extension`	Browser extension WebSocket	WebSocket
`/ws/desktop`	Desktop application WebSocket	WebSocket
`/ws/web`	Web client WebSocket	WebSocket

Components & Data Flow

Request Flow — Agent Invocation

WebSocket Gateway

The Gateway manages all WebSocket connections through ConnectionManager, supporting three node types:

Extension / Desktop nodes: Each node is uniquely identified by node_id; a user can have multiple nodes
Web clients: Managed by user_id; the same user can have multiple Web connections
Tool calls: The Agent initiates JSON-RPC requests via call_tool(); the Gateway routes requests to the corresponding node and awaits responses (Future-based)

Agent Service

The Agent Service is the core orchestration layer, built on the DeepAgents framework (a higher-level wrapper over LangGraph): Service Layer:

Service	File	Responsibility
BaseService	`services/base.py`	Context initialization, tool assembly, prompt construction, SSE event streaming
AgentService	`services/agent.py`	Agent mode invoke/resume entry point
RAGService	`services/rag.py`	Knowledge base retrieval (vector + BM25 hybrid search)
DocumentService	`services/document.py`	Document processing and chunking
FeishuService	`services/feishu.py`	Feishu channel integration
SchedulerService	`services/scheduler.py`	Scheduled task scheduling

Tool System

Zeus tools are organized into four layers:

Layer	Source	Registration	Execution Location
Built-in	`utils/tools/built_in/`	Registered directly in code	AI Backend local
MCP	Passed from frontend config	`langchain_mcp_adapters`	MCP Server (remote)
OAuth	Passed from frontend config	Dynamically built LangChain Tool	AI Backend → OAuth API
Connector	Reported by WebSocket nodes	Bound via SessionManager	Remote nodes (Extension/Desktop)

Connector Tools call chain: Agent → ToolRouter → Gateway → WebSocket → Node → Execute → Return via same path.

Node Management

Node management is handled by three cooperating components:

Component	Description
NodeManager	Node registration/deregistration, heartbeat TTL (60s), periodic cleanup (30s)
SessionManager	Binds sessions to specific nodes, supports `preferred_node_id` specification
ToolRouter	Routes tool calls to the appropriate node based on session binding

Each user can have up to 10 nodes; nodes that miss heartbeats are automatically marked offline and deregistered.

Storage & State

Storage	Technology	Owner	Purpose
App Database	PostgreSQL (Drizzle ORM)	Web API	Users, sessions, messages, tools, skills, credits, projects, showcase
Checkpointer	PostgreSQL (`PostgresSaver`)	AI Backend	Session-level Agent state persistence, supports HITL recovery
Memory	PostgreSQL + pgvector	AI Backend	Long-term memory (vectors + metadata), three-tier scoping
Knowledge Base	PostgreSQL + pgvector + BM25	AI Backend	RAG document storage and hybrid retrieval
Workspace	Supabase Storage / S3 (MinIO)	Web API	User files (outputs, uploads, sandbox results). Auto-selects S3 when `S3_ENDPOINT` is configured
Cache	Redis	Both	Workspace cache (5min), memory cache (10min), TaskIQ result backend
Message Queue	RabbitMQ (TaskIQ)	AI Backend	Async task broker for scheduled tasks, RAG processing, cloud sync

Communication Protocols

HTTP SSE (Agent Response Stream)

Agent invocations return text/event-stream. SSE event types:

Event Type	data Field	Description
`text`	`{type, content}`	Streaming text tokens
`tool_call`	`{type, tool_name, tool_args, tool_call_id}`	Agent initiates a tool call
`tool_call_result`	`{type, tool_name, result, ...}`	Tool execution result
`interrupt`	`{type, tool_calls, ...}`	HITL interrupt, awaiting user approval
`complete`	`{type, finish_reason}`	Stream ended
`error`	`{type, error}`	Error message

WebSocket JSON-RPC 2.0 (Node Tool Calls)

Node tool calls follow the MCP (Model Context Protocol) specification: Request:

{
  "jsonrpc": "2.0",
  "id": "uuid-string",
  "method": "tools/call",
  "params": {
    "name": "browser_click",
    "arguments": { "selector": "#submit-btn" },
    "session_id": "session_abc123"
  }
}

Response (Success):

{
  "jsonrpc": "2.0",
  "id": "uuid-string",
  "result": {
    "content": [
      { "type": "text", "text": "Clicked element successfully" },
      { "type": "image", "data": "base64...", "mimeType": "image/jpeg" }
    ],
    "isError": false
  }
}

Response (Error):

{
  "jsonrpc": "2.0",
  "id": "uuid-string",
  "error": {
    "code": -32603,
    "message": "Element not found"
  }
}

WebSocket Message Types (Non JSON-RPC)

Direction	type	Description
Node → Gateway	`register`	Node registration (capabilities, tools)
Gateway → Node	`registered`	Registration confirmation
Node → Gateway	`heartbeat`	Heartbeat report (status, current_tasks)
Gateway → Node	`heartbeat_ack`	Heartbeat acknowledgment
Node ↔ Gateway	`ping` / `pong`	Keepalive
Web → Gateway	`get_workflows`	Request workflow list (forwarded to Extension)
Web → Gateway	`execute_workflow`	Execute workflow
Node → Gateway	`task_complete`	Workflow execution completed

Startup & Lifecycle

Web API Startup

The Next.js application starts automatically and serves:

All API routes under /api/*
Web frontend pages under /[locale]/*
Authentication via Better Auth middleware

AI Backend Startup

Key Environment Variables

Web API (Next.js):

Variable	Description
`DATABASE_URL`	PostgreSQL connection string (app database)
`BACKEND_URL`	AI Backend URL for agent forwarding (default: `http://localhost:8000`)
`BETTER_AUTH_SECRET`	Better Auth secret key
`SUPABASE_URL` / `SUPABASE_SERVICE_KEY`	Supabase Storage configuration
`S3_ENDPOINT` / `S3_ACCESS_KEY` / `S3_SECRET_KEY`	S3/MinIO storage (alternative to Supabase, optional)

AI Backend (FastAPI):

Variable	Description
`DATABASE_URL`	PostgreSQL connection string (Checkpointer + pgvector)
`NEXTJS_API_URL`	Web API URL for callbacks (user data, config lookups)
`OPENAI_API_KEY` / `OPENAI_BASE_URL`	Default LLM configuration
`REDIS_URL`	Redis cache and TaskIQ result backend (optional)
`RABBITMQ_URL`	RabbitMQ message queue for async tasks (optional)
`LANGCHAIN_API_KEY`	LangSmith tracing (optional)

Health Checks

AI Backend: GET /health → {"status": "ok"}
AI Backend: GET / → {"name": "Zeus Backend API", "version": "1.0.0", "status": "running"}

System Invariants

JWT Authentication: All Web API routes require a valid JWT Token; AI Backend receives a forwarded token from Web API
Session Isolation: Each session_id has independent Checkpointer state; different sessions do not interfere
Node Heartbeat: Nodes that miss heartbeats for over 60 seconds are automatically marked offline; the Gateway immediately deregisters nodes on disconnect
Tool Call Timeout: WebSocket tool calls default to 60-second timeout; workflow execution has a 300-second timeout
SSE Non-Replay: Agent invocation SSE streams are one-time; after disconnect, context must be restored via Checkpointer
Credit Gate: Web API checks and deducts credits before forwarding any agent request to AI Backend
Single-Instance Gateway: The current ConnectionManager is a per-process singleton; WebSocket connections are not shared across processes

Directory Structure

Web API (Next.js):

apps/web/src/
├── app/
│   ├── [locale]/                    # Page routes (i18n)
│   └── api/                         # API routes (93 routes)
│       ├── agent/                   # Agent forwarding → AI Backend
│       ├── auth/                    # Authentication
│       ├── sessions/                # Session management
│       ├── tools/                   # Tool configuration
│       ├── skills/                  # Skill management
│       ├── knowledge-base/          # Knowledge base
│       ├── projects/                # Project management
│       ├── credits/                 # Credit system
│       ├── memory/                  # Memory management
│       ├── config/                  # LLM / Embedding / Sandbox config
│       └── ...
├── db/
│   ├── schema/                      # Drizzle ORM table definitions
│   ├── model/                       # Data access layer (CRUD)
│   ├── service/                     # Business logic layer
│   └── storage/                     # Storage operations
├── lib/auth/                        # Authentication (Better Auth, JWT)
└── ...

AI Backend (FastAPI):

apps/ai-backend/src/
├── api/                             # FastAPI routing layer
│   ├── main.py                      # Entry point & lifecycle
│   ├── gateway.py                   # WebSocket gateway
│   ├── agent.py                     # Agent API (invoke/resume)
│   ├── mcp_gateway.py               # MCP protocol gateway
│   ├── skill.py                     # Skill API
│   ├── tools.py                     # Tools API
│   ├── knowledge_base.py            # Knowledge base RAG API
│   ├── node.py                      # Node query API
│   ├── scheduled_task.py            # Scheduled task API
│   ├── deploy.py                    # Deployment API
│   ├── sandbox.py                   # Sandbox API
│   └── channels/                    # Channels (Feishu)
├── services/                        # Business logic layer
│   ├── base.py                      # BaseService (Agent core)
│   ├── agent.py                     # AgentService
│   ├── rag.py                       # RAG retrieval
│   ├── document.py                  # Document processing
│   ├── sandbox.py                   # Sandbox management
│   ├── notification.py              # Notification service
│   ├── feishu.py                    # Feishu service
│   └── scheduler.py                 # Scheduled tasks
├── repository/                      # Data models & prompts
│   ├── models/                      # Pydantic Models
│   ├── prompts/                     # System Prompts (.md)
│   └── skills/                      # Skill definitions
└── utils/                           # Utility layer
    ├── core/                        # LLM, Memory, Skills, HITL
    ├── infra/                       # Backend, Checkpoint, Node, Redis, Auth
    ├── tools/                       # Tool implementations
    │   ├── built_in/                # Built-in tools
    │   └── plugin/                  # Plugin tools (Feishu)
    ├── sandbox/                     # Sandbox providers (E2B, OpenSandbox, Daytona)
    ├── knowledge_base/              # Vector storage & chunking
    └── channels/                    # Channel integrations

Agent Runtime

Runtime detailed design — Workspace, Session, Modes

Gateway Protocol

Channels & Gateway — Feishu, WebSocket node communication

Tool System

Four-layer tool system — Built-in, MCP, OAuth, Connector

File System

Storage architecture — CloudDriveBackend, Checkpoint

Get Started

Fundamentals

Core Capabilities

Infra

Channels

Architecture

Overview

Two-Tier Backend

Web API (Next.js) — Gateway & Data Layer

AI Backend (FastAPI) — Agent Execution Engine

Components & Data Flow

Request Flow — Agent Invocation

WebSocket Gateway

Agent Service

Tool System

Node Management

Storage & State

Communication Protocols

HTTP SSE (Agent Response Stream)

WebSocket JSON-RPC 2.0 (Node Tool Calls)

WebSocket Message Types (Non JSON-RPC)

Startup & Lifecycle

Web API Startup

AI Backend Startup

Key Environment Variables

Health Checks

System Invariants

Directory Structure

Agent Runtime

Gateway Protocol

Tool System

File System

Get Started

Fundamentals

Core Capabilities

Infra

Channels

​Overview

​Two-Tier Backend

​Web API (Next.js) — Gateway & Data Layer

​AI Backend (FastAPI) — Agent Execution Engine

​Components & Data Flow

​Request Flow — Agent Invocation

​WebSocket Gateway

​Agent Service

​Tool System

​Node Management

​Storage & State

​Communication Protocols

​HTTP SSE (Agent Response Stream)

​WebSocket JSON-RPC 2.0 (Node Tool Calls)

​WebSocket Message Types (Non JSON-RPC)

​Startup & Lifecycle

​Web API Startup

​AI Backend Startup

​Key Environment Variables

​Health Checks

​System Invariants

​Directory Structure

Agent Runtime

Gateway Protocol

Tool System

File System

Overview

Two-Tier Backend

Web API (Next.js) — Gateway & Data Layer

AI Backend (FastAPI) — Agent Execution Engine

Components & Data Flow

Request Flow — Agent Invocation

WebSocket Gateway

Agent Service

Tool System

Node Management

Storage & State

Communication Protocols

HTTP SSE (Agent Response Stream)

WebSocket JSON-RPC 2.0 (Node Tool Calls)

WebSocket Message Types (Non JSON-RPC)

Startup & Lifecycle

Web API Startup

AI Backend Startup

Key Environment Variables

Health Checks

System Invariants

Directory Structure