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Product Roadmap

Aden Agent Framework aims to help developers build outcome-oriented, self-adaptive agents. Please find our roadmap here

flowchart TB
    %% Main Entity
    User([User])

    %% =========================================
    %% EXTERNAL EVENT SOURCES
    %% =========================================
    subgraph ExtEventSource [External Event Source]
        E_Sch["Schedulers"]
        E_WH["Webhook"]
        E_SSE["SSE"]
    end

    %% =========================================
    %% SYSTEM NODES
    %% =========================================
    subgraph WorkerBees [Worker Bees]
        WB_C["Conversation"]
        WB_SP["System prompt"]

        subgraph Graph [Graph]
            direction TB
            N1["Node"] --> N2["Node"] --> N3["Node"]
            N1 -.-> AN["Active Node"]
            N2 -.-> AN
            N3 -.-> AN

            %% Nested Event Loop Node
            subgraph EventLoopNode [Event Loop Node]
                ELN_L["listener"]
                ELN_SP["System Prompt<br/>(Task)"]
                ELN_EL["Event loop"]
                ELN_C["Conversation"]
            end
        end
    end

    subgraph JudgeNode [Judge]
        J_C["Criteria"]
        J_P["Principles"]
        J_EL["Event loop"] <--> J_S["Scheduler"]
    end

    subgraph QueenBee [Queen Bee]
        QB_SP["System prompt"]
        QB_EL["Event loop"]
        QB_C["Conversation"]
    end

    subgraph Infra [Infra]
        SA["Sub Agent"]
        TR["Tool Registry"]
        WTM["Write through Conversation Memory<br/>(Logs/RAM/Harddrive)"]
        SM["Shared Memory<br/>(State/Harddrive)"]
        EB["Event Bus<br/>(RAM)"]
        CS["Credential Store<br/>(Harddrive/Cloud)"]
    end

    subgraph PC [PC]
        B["Browser"]
        CB["Codebase<br/>v 0.0.x ... v n.n.n"]
    end

    %% =========================================
    %% CONNECTIONS & DATA FLOW
    %% =========================================

    %% External Event Routing
    E_Sch --> ELN_L
    E_WH --> ELN_L
    E_SSE --> ELN_L
    ELN_L -->|"triggers"| ELN_EL

    %% User Interactions
    User -->|"Talk"| WB_C
    User -->|"Talk"| QB_C
    User -->|"Read/Write Access"| CS

    %% Inter-System Logic
    ELN_C <-->|"Mirror"| WB_C
    WB_C -->|"Focus"| AN

    WorkerBees -->|"Inquire"| JudgeNode
    JudgeNode -->|"Approve"| WorkerBees

    %% Judge Alignments
    J_C <-.->|"aligns"| WB_SP
    J_P <-.->|"aligns"| QB_SP

    %% Escalate path
    J_EL -->|"Report (Escalate)"| QB_EL

    %% Pub/Sub Logic
    AN -->|"publish"| EB
    EB -->|"subscribe"| QB_C

    %% Infra and Process Spawning
    ELN_EL -->|"Spawn"| SA
    SA -->|"Inform"| ELN_EL
    SA -->|"Starts"| B
    B -->|"Report"| ELN_EL
    TR -->|"Assigned"| EventLoopNode
    CB -->|"Modify Worker Bee"| WorkerBees

    %% =========================================
    %% SHARED MEMORY & LOGS ACCESS
    %% =========================================

    %% Worker Bees Access
    Graph <-->|"Read/Write"| WTM
    Graph <-->|"Read/Write"| SM

    %% Queen Bee Access
    QB_C <-->|"Read/Write"| WTM
    QB_EL <-->|"Read/Write"| SM

    %% Credentials Access
    CS -->|"Read Access"| QB_C
Loading

Core Architecture & Swarm Primitives

Node-Based Architecture

Implement the core execution engine where every Agent operates as an isolated, asynchronous graph of nodes.

  • Core Node Implementation
    • NodeProtocol with JSON parsing utilities (graph/node.py)
    • EventLoopNode with LLM conversation management (graph/event_loop_node.py)
    • Flexible input/output keys with nullable output handling
    • Node wrapper SDK for agent creation
    • Tool access layer with MCP integration
  • Graph Executor
    • Graph traversal execution (graph/executor.py)
    • Node transition management
    • Error handling and output mapping
    • ExecutionResult with success/error status
  • Shared Memory Access
    • SharedState manager (runtime/shared_state.py)
    • Session-based storage (storage/session_store.py)
    • Isolation levels: ISOLATED, SHARED, SYNCHRONIZED
  • Default Monitoring Hooks
    • Performance metrics collection
    • Resource usage tracking
    • Health check endpoints

Node Protocol

Build the standard communication protocol for inter-node messaging and data passing.

  • Edge Specifications
    • ALWAYS: Always traverse (graph/edge.py)
    • ON_SUCCESS: Success-based routing
    • ON_FAILURE: Failure-based routing
    • CONDITIONAL: Expression-based routing with safe_eval
    • LLM_DECIDE: Goal-aware LLM-powered routing
  • Event Bus System
    • Full event bus implementation (runtime/event_bus.py)
    • LLM text deltas, tool calls, node transitions
    • Graph-scoped event routing for multi-agent scenarios
  • Conversation Management
    • NodeConversation tracks message history (graph/conversation.py)
    • Tool results, streaming content, metadata support

Judge in Event Loop

A separate LLM-powered judge to determine if the workers finish their job.

  • Conversation Judge (Level 2)
    • Evaluates node completion against success criteria (graph/conversation_judge.py)
    • Reads recent conversation and assesses quality
    • Returns verdict: ACCEPT or RETRY with confidence scores
  • Test Evaluation Judge
    • Provider-agnostic (OpenAI, Anthropic, Google Gemini) (testing/llm_judge.py)
    • JSON response parsing for structured evaluation
  • Multi-Level Judgment Integration
    • Judge node integration with event loop
    • Automatic retry logic based on judge verdict
    • Judge performance monitoring

Swarm Hierarchy

Develop the distinct behavioral logic for the Queen Bee (Orchestrator), Judge Bee (Evaluator), and Worker Bee (Executor).

  • Judge Bee (Evaluator)
    • Evaluation criteria framework (graph/goal.py)
    • Success/failure determination
    • Quality assessment with confidence scores
  • Hive Coder Agent (Builder)
    • Coder node: forever-alive event loop (agents/hive_coder/nodes/)
    • Guardian node: event-driven watchdog for supervised agents
    • Tool discovery (discover_mcp_tools)
    • Agent aware (list_agents, inspect sessions)
    • Post-build testing (run_agent_tests)
    • Debugging capabilities (inspect checkpoints, memory)
  • Queen Bee (Orchestrator)
    • Multi-agent coordination layer
    • Task distribution logic
    • Dynamic worker agent creation
    • Swarm-level goal management
  • Worker Bee (Executor)
    • Worker taxonomy definition
    • Worker agent templates
    • Task execution patterns

Coding Agent Workflows

Implement the Goal Creation Session via the Queen Bee and the dynamic Worker Agent Creation flow.

  • Goal Creation Session
    • Goal object schema definition (graph/goal.py)
    • SuccessCriterion: Measurable success (5+ criteria per goal)
    • Constraint: Hard/soft boundaries (time, cost, safety, scope, quality)
    • GoalStatus: DRAFT → READY → ACTIVE → COMPLETED/FAILED
    • Instruction back and forth in Hive Coder
    • Test case generation
    • Test case validation for worker agent
  • Agent Creation Flow
    • Hive Coder reads templates and discovers tools (builder/package_generator.py)
    • Generates agent.py, nodes/init.py, config.py
    • MCP server configuration discovery
    • Dynamic tool binding
  • Worker Agent Dynamic Creation
    • Template agent initialization from Queen Bee
    • Runtime worker instantiation
    • Worker lifecycle management

Security Layer

Build robust, local Credential Management interfaces for secure API key handling.

  • Unified Credential Store
    • Multi-backend storage (credentials/store.py)
    • EncryptedFileStorage: Encrypted local storage (~/.hive/credentials)
    • EnvVarStorage: Environment variable mapping
    • InMemoryStorage: Testing
    • HashiCorp Vault: Enterprise secrets (credentials/storage.py)
    • Template resolution: {{cred.key}} patterns
    • Caching with TTL (default 5 min, configurable)
    • Thread-safe operations with RLock
  • OAuth2 Providers
    • Base provider pattern (credentials/oauth2/)
    • HubSpot provider integration
    • Lifecycle management (refresh tokens)
    • Browser opening for auth flows (tools/credentials/browser.py)
  • Aden Sync Provider
    • Syncs OAuth2 tokens from Aden authentication server (credentials/aden/)
    • Falls back to local storage if Aden unavailable
    • Auto-refresh on sync
  • Enterprise Secret Managers
    • AWS Secrets Manager integration
    • Azure Key Vault integration
    • Audit logging for compliance/tracking
    • Per-environment configuration support

Tooling Ecosystem & General Compute

Sub-agents Parallel Execution

Develop the Sub-agent execution environment for parallel tasks execution. The subagents are designed with isolation for repeatability.

  • Multi-Graph Sessions
    • Load multiple agent graphs in single session (runtime/agent_runtime.py)
    • Shared state between graphs
    • Independent execution streams
    • Graph lifecycle management (load/unload/start/restart)
  • Concurrent Execution Management
    • Max concurrent executions configuration
    • Isolation levels: isolated, shared, synchronized
  • Sub-agent Execution Environment
    • Isolated sub-agent runtime environment
    • Task isolation mechanisms
    • Result aggregation
    • Error handling for parallel tasks
    • Repeatability guarantees

Browser Use Node

Implement native browser-integrated automation so agents can take over a browser for auth and agents perform the automation jobs. This node comes with a specific set of tools and system prompts.

  • Web Scraping with Playwright
    • Headless Chromium launch (tools/web_scrape_tool/)
    • Stealth mode via playwright_stealth
    • JavaScript rendering with wait-for-domcontentloaded
    • CSS selector support
    • User-agent spoofing
    • Sandbox/automation detection evasion
  • Browser Launch Utilities
    • Platform-specific browser opening (macOS/Linux/Windows) (tools/credentials/browser.py)
    • OAuth2 flow integration
  • Full Browser Use Node
    • Multi-page automation workflows
    • Form filling with vision-guided interactions
    • Interactive screenshot capabilities
    • Session management across navigations
    • Browser-specific tool set
    • System prompts for browser tasks

Core Graph Framework Infra

Ship essential framework utilities: Node validation, HITL (Human-in-the-loop pause/approve), and node lifecycle management.

  • Node Validation
    • Pydantic-based validation
    • Schema enforcement
    • Output key validation (Level 0)
  • Human-in-the-Loop (HITL)
    • HITLRequest and HITLResponse protocol (graph/hitl.py)
    • Question types: FREE_TEXT, STRUCTURED, SELECTION, APPROVAL, MULTI_FIELD
    • Haiku-powered response parsing
    • User-friendly display formatting
    • Pause/approve workflow
    • State saved to checkpoint
    • Resume with HITLResponse merged into context
  • TUI Integration
    • Chat REPL with streaming support (tui/app.py)
    • Multi-graph session management
    • User presence detection
    • Real-time log viewing
  • Node Lifecycle Management
    • Start/stop/pause/resume in execution stream
    • State persistence via checkpoint store
    • Recovery mechanisms with checkpoint restore
  • Advanced HITL Features
    • Callback handlers for custom intervention logic
    • Streaming interface for real-time monitoring
    • Approval workflows at scale

Infrastructure Tools

Port popular tools, and build out the Runtime Log, Audit Trail, Excel, and Email integrations.

  • File Operations (36+ tools)
    • read_file, write_file, edit_file (builder/package_generator.py)
    • list_directory, search_files
    • apply_diff / apply_patch for code modification (tools/file_system_toolkits/)
    • data_tools (CSV/Excel parsing)
  • Web Tools
    • Web Search (tools/web_search_tool/)
    • Web Scraper (tools/web_scrape_tool/)
    • Exa Search (tools/exa_search_tool/)
    • News Tool (tools/news_tool/)
    • SerpAPI (tools/serpapi_tool/)
  • Data Tools
    • CSV tools (tools/csv_tool/)
    • Excel tools (tools/excel_tool/)
    • PDF tools (tools/pdf_read_tool/)
    • Vision tool for image analysis (tools/vision_tool/)
    • Time tool (tools/time_tool/)
  • Communication Tools (8 tools)
    • Email tool (tools/email_tool/)
    • Gmail tool (tools/gmail_tool/)
    • Slack tool (tools/slack_tool/)
    • Discord tool (tools/discord_tool/)
    • Telegram tool (tools/telegram_tool/)
    • Google Docs (tools/google_docs_tool/)
    • Google Maps (tools/google_maps_tool/)
    • Cal.com (tools/calcom_tool/)
  • CRM/API Integrations (5+ tools)
    • HubSpot (tools/hubspot_tool/)
    • GitHub (tools/github_tool/)
    • Apollo (tools/apollo_tool/)
    • BigQuery (tools/bigquery_tool/)
    • Razorpay (tools/razorpay_tool/)
    • Calendar (tools/calendar_tool/)
  • Security/Scanning Tools (5 tools)
    • DNS Security Scanner (tools/dns_security_scanner/)
    • SSL/TLS Scanner (tools/ssl_tls_scanner/)
    • Port Scanner (tools/port_scanner/)
    • Subdomain Enumerator (tools/subdomain_enumerator/)
    • Tech Stack Detector (tools/tech_stack_detector/)
  • Runtime & Logging
    • Runtime Log Tool (tools/runtime_logs_tool/)
    • Runtime Logger with L1/L2/L3 levels (runtime/runtime_logger.py)
  • Audit Trail System
    • Decision tracing beyond logs
    • Compliance reporting
    • Historical query capabilities

Memory, Storage & File System Capabilities

Memory Tools

Simple pure file-based memory management

  • Short-Term Memory (STM)
    • SharedState manager for in-memory state (runtime/shared_state.py)
    • Session-based storage (storage/session_store.py)
    • State-based short-term memory layer
  • Conversation Memory
    • NodeConversation tracks message history (graph/conversation.py)
    • Tool results, streaming content, metadata
    • Context building for LLM prompts
  • Long-Term Memory (LTM)
    • Semantic indexing for memory retrieval
    • RLM (Retrieval-augmented Long-term Memory) implementation
    • Memory persistence beyond session
    • Content-based memory search

Durable Scratchpad

Integrate a lightweight, persistent DB for long-term memory using the filesystem-as-scratchpad pattern.

  • Filesystem as Scratchpad
    • File-based persistence layer (storage/)
    • Session store implementation
    • Data durability guarantees
  • Checkpoint System
    • Save/restore execution state (storage/checkpoint_store.py)
    • TTL-based cleanup
    • Async checkpoint support
    • Max age configuration
  • Message Model & Session Management
    • Message class with structured content types
    • Session classes for conversation state
    • Per-message file persistence
    • Migration from monolithic run storage

Memory Isolation

Enforce session-local memory isolation to prevent data bleed between concurrent agent runs.

  • Session Isolation
    • Session-local memory implementation (storage/session_store.py)
    • Data bleed prevention
    • Concurrent run safety
    • Isolation levels: ISOLATED, SHARED, SYNCHRONIZED
  • State Management
    • SharedState with thread-safe operations (runtime/shared_state.py)
    • Session-scoped state access
  • Context Management
    • Message.stream(sessionID) implementation
    • Full context building optimization
    • Message to model conversion improvements

Agent Capabilities

Implement File I/O support, streaming mode, and allow users to supply custom functions as libraries/nodes.

  • File I/O
    • File read/write operations (builder/package_generator.py)
    • File system navigation
    • Directory listing and search
  • Execution Streaming
    • Real-time event streaming (runtime/execution_stream.py)
    • Token-by-token output via event bus
    • Tool call streaming
  • Custom Tool Integration
    • MCP server discovery (builder/package_generator.py)
    • Dynamic tool binding
    • Custom tool registration
  • Streaming Mode Enhancements
    • Progressive result delivery optimization
    • Backpressure handling
  • Custom Function Libraries
    • User-supplied function libraries as nodes
    • Library versioning and management
  • Proactive Memory Compaction
    • Overflow detection
    • Backward-scanning pruning strategy
    • Token tracking integration for compaction decisions

File System Enhancements

Add semantic search capabilities and an interactive file system for frontend product integration.

  • File Search
    • search_files tool (builder/package_generator.py)
    • Directory traversal
  • Semantic Search
    • Semantic indexing of files
    • Natural language file search
    • Content-based retrieval with embeddings
  • Interactive File System
    • Frontend file browser integration
    • Real-time file system updates
    • Visual file navigation in GUI

Eval System, DX, & Open Source Guardrails

Eval System

Build the failure recording mechanism and an SDK for defining custom failure conditions.

  • Multi-Level Evaluation
    • Level 0: Output key validation (all required keys set)
    • Level 1: Literal checks (output_contains, output_equals)
    • Level 2: Conversation-aware judgment (graph/conversation_judge.py)
  • Goal-Based Constraints
    • Hard constraints (violation = failure) (graph/goal.py)
    • Soft constraints (prefer not to violate)
    • Categories: time, cost, safety, scope, quality
    • Constraint checking infrastructure
  • Success Criteria Definition
    • Weighted criteria (0.0-1.0)
    • Metrics: output_contains, output_equals, llm_judge, custom
    • 90% threshold for goal success
  • Test Framework
    • TestCase, TestResult, TestStorage classes (testing/)
    • LLM-based judgment for semantic evaluation (testing/llm_judge.py)
    • Approval CLI for manual approval workflows
    • Categorization and test result reporting
  • Failure Recording
    • Failure capture mechanism
    • Failure analysis tools
    • Historical failure tracking
    • Continuous improvement loop
  • Custom Failure Conditions SDK
    • SDK for defining custom failure conditions
    • Custom evaluator framework extension
    • Condition validation DSL

Guardrails SDK

Implement deterministic condition guardrails directly in the node, complete with mitigation tracking and audit logs.

  • Goal Constraints (Basic Guardrails)
    • Hard/soft constraint definitions (graph/goal.py)
    • Constraint checking in goals
  • Deterministic Guardrails SDK
    • In-node guardrail implementation
    • Condition-based guardrails
    • Guardrail SDK for custom rules
  • Monitoring & Tracking
    • Mitigation tracking for violations
    • Audit log system for guardrails
    • Compliance reporting
  • Basic Monitoring Hooks
    • Agent node SDK monitoring hooks
    • Event hook system for guardrails
    • Default monitoring hooks in nodes

DevTools CLI

Release CLI tools specifically for rapid memory management and credential store editing.

  • Main CLI
    • Run, info, validate, list commands (cli.py)
    • Dispatch mode for batch execution
    • Shell mode for interactive use
    • Model selection configuration
  • Testing CLI
    • test-run, test-debug, test-list, test-stats (testing/cli.py)
    • Pytest integration
    • Test categorization
  • TUI (Terminal UI)
    • Interactive chat with streaming (tui/app.py)
    • Multi-graph management UI
    • Log pane for real-time output
    • Keyboard shortcuts (Ctrl+C, Ctrl+D, etc.)
  • Memory Management CLI
    • Memory inspection commands
    • Memory cleanup utilities
    • Session management commands
  • Credential Store CLI
    • Interactive credential editing
    • Secure credential viewer
    • Credential validation tools
  • Debugging Tools
    • Interactive debugging mode beyond TUI
    • Breakpoint support in execution
    • Step-through execution

Observability

Support user-driven log analysis, basic monitoring hooks from the SDK, and an interactive debugging mode.

  • Runtime Logging
    • L1 (summary), L2 (detailed), L3 (tool) logging levels (runtime/runtime_logger.py)
    • Session logs directory storage
    • Audit trail for decision tracing in logs
  • Event Bus Monitoring
    • Real-time event streaming (runtime/event_bus.py)
    • LLM text deltas, tool calls, node transitions
    • Graph-scoped event routing
  • Log Analysis Tools
    • User-driven log analysis (OSS approach)
    • Log aggregation utilities
    • Log visualization tools
  • Monitoring Hooks
    • Basic observability hooks from SDK
    • Performance metrics collection
    • Health checks system
  • Token Tracking
    • Reasoning token tracking
    • Cache token tracking
    • Token metrics in compaction logic

Developer Success

Write the Quick Start guide, detailed tool usage documentation, and set up the MVP README examples.

  • Documentation
    • Quick start guide
    • Goal creation guide
    • Agent creation guide
    • README with examples
    • Contributing guidelines
    • GitHub Page setup
  • Tool Usage Documentation
    • Comprehensive tool documentation
    • Tool integration examples
    • Best practices guide
  • Video Content
    • Introduction video
    • Tutorial videos
  • Example Agents
    • Knowledge agent template
    • Blog writer agent template
    • SDR agent template

Deployment, CI/CD & Community Templates

Self-Deployment

Standardize the Docker container builds and establish headless backend execution APIs.

  • Docker Support
    • Python 3.11-slim base image (tools/Dockerfile)
    • Playwright Chromium installation
    • Non-root user for security
    • Health check endpoint
    • Volume mount for workspace persistence
    • Exposes port 4001 for MCP server
  • Agent Runtime
    • AgentRuntime: Top-level orchestrator (runtime/agent_runtime.py)
    • Multiple entry points (manual, webhook, timer, event, api)
    • Concurrent execution management
    • State persistence via session store
    • Outcome aggregation
  • Async Entry Points
    • AsyncEntryPointSpec: Webhook, timer, event triggers (graph/edge.py)
    • Timer config: cron expressions or interval_minutes
    • Event triggers for custom events
    • Isolation levels: isolated, shared, synchronized
  • Headless Backend Enhancements
    • Standardized backend execution APIs
    • Frontend attachment interface
    • Self-hosted setup guide with examples

Lifecycle APIs

Expose basic REST/WebSocket endpoints for external control (Start, Stop, Pause, Resume).

  • Webhook Server
    • FastAPI-based webhook server (runtime/webhook_server.py)
    • Route configuration per entry point
    • Optional secret validation
  • Graph Lifecycle Management
    • Load/unload/start/restart in AgentRuntime
    • State persistence
    • Recovery mechanisms
  • REST API Endpoints
    • Start endpoint for agent execution
    • Stop endpoint for graceful shutdown
    • Pause endpoint for execution suspension
    • Resume endpoint for continuation
    • Status query endpoint for monitoring
  • WebSocket API
    • Real-time event streaming to clients
    • Bidirectional communication
    • Connection management with reconnection

CI/CD Pipelines

Implement automated test execution, agent version control, and mandatory test-passing for deployment.

  • Test Execution
    • Test framework with pytest integration (testing/)
    • Test result reporting
    • Test CLI commands (test-run, test-debug, etc.)
  • Automated Testing Pipeline
    • CI integration (GitHub Actions, etc.)
    • Mandatory test-passing gates
    • Coverage reporting
  • Version Control
    • Agent versioning system
    • Semantic versioning for agents
    • Version compatibility checks
  • Deployment Automation
    • Continuous deployment pipeline
    • Rollback mechanisms
    • Blue-green deployment support

Distribution

Launch the official PyPI package, Docker Hub image, and the community Discord channel.

  • Package Distribution
    • Official PyPI package
    • Docker Hub image publication
    • Version release automation
    • Installation documentation
  • Community Channels
    • Discord channel setup
    • Community support structure
    • Contribution guidelines enforcement
  • Cloud Deployment
    • AWS Lambda integration
    • GCP Cloud Functions support
    • Azure Functions support
    • 3rd-party platform integrations
    • Self-deploy with orchestrator connection

Example Agents

Ship ~20 ready-to-use templates including GTM Sales, Marketing, Analytics, Training, and Smart Entry agents.

  • Hive Coder Agent
    • Agent builder template (agents/hive_coder/)
    • Guardian node for supervision
  • Sales & Marketing Agents
    • GTM Sales Agent (workflow automation)
    • GTM Marketing Agent (campaign management)
    • Lead generation agent
    • Email campaign agent
    • Social media agent
  • Analytics & Insights Agents
    • Analytics Agent (data analysis)
    • Data processing agent
    • Report generation agent
    • Dashboard agent
  • Training & Education Agents
    • Training Agent (onboarding)
    • Content creation agent
    • Knowledge base agent
    • Documentation agent
  • Automation & Forms Agents
    • Smart Entry / Form Agent (self-evolution emphasis)
    • Data validation agent
    • Workflow automation agent
    • Integration agent
  • Additional Templates
    • Customer support agent
    • Document processing agent
    • Scheduling agent
    • Research agent
    • Code review agent

Open Hive

Local API Gateway

Build a lightweight local server (e.g., FastAPI or Node) that securely exposes the Hive framework's core Event Bus and Memory Layer to the local browser environment.

  • MCP Server Foundation
    • FastMCP server implementation (builder/package_generator.py)
    • Agent builder tools exposed
    • Port 4001 exposed in Docker
  • Event Bus Architecture
    • Event Bus implementation (runtime/event_bus.py)
    • Real-time event streaming
    • Graph-scoped event routing
  • Local API Gateway
    • Lightweight local server (FastAPI or Node)
    • Secure authentication layer for browser
    • CORS and security configuration
    • Event Bus API endpoints for browser access
    • Event subscription management for frontend
  • Memory Layer API
    • Memory read/write endpoints
    • Session management API for frontend
    • Memory visualization data endpoints

Visual Graph Explorer

Implement an interactive, drag-and-drop canvas (using libraries like React Flow) to visualize the Worker Graph, Queen Bee, and active execution paths in real-time.

  • Graph Visualization
    • React Flow integration
    • Worker Graph rendering from agent definitions
    • Node type visualization (EventLoop, Function, etc.)
    • Edge visualization with condition types
    • Active execution path highlighting
  • Interactive Features
    • Drag-and-drop canvas for graph editing
    • Node editing capabilities
    • Real-time graph updates during execution
    • Zoom and pan controls
    • Node inspection on click
  • Integration with Runtime
    • Live execution visualization
    • Node state indicators
    • Edge traversal animation

TUI to GUI Upgrade

Port the existing Terminal User Interface (TUI) into a rich web application, allowing users to interact directly with the Queen Bee / Coding Agent via a browser chat interface.

  • TUI Foundation
    • Terminal chat interface (tui/app.py)
    • Streaming support
    • Multi-graph management
    • Log pane display
    • Keyboard shortcuts
  • Web Application
    • Modern web UI framework setup (React/Vue/Svelte)
    • Responsive design implementation
    • Cross-browser compatibility
  • Chat Interface
    • Browser-based chat UI
    • Hive Coder interaction (Queen Bee proxy)
    • Coding Agent interface
    • Message history and search
    • Rich message formatting (markdown, code blocks)
  • TUI Feature Parity
    • All TUI commands in GUI
    • Keyboard shortcuts in browser
    • Command palette (Cmd+K style)

Memory & State Inspector

Create a UI component to inspect the Shared Memory and Write-Through Conversation Memory, allowing developers to click on any node and see exactly what it is thinking.

  • Runtime Logs Tool
    • Inspect agent session logs (tools/runtime_logs_tool/)
    • Session state retrieval (builder/package_generator.py)
  • Memory Inspector UI
    • Shared Memory visualization
    • Conversation memory view (NodeConversation display)
    • Memory search and filter
    • Memory timeline view
  • Node State Inspection
    • Click-to-inspect functionality
    • Node thought process display (LLM reasoning)
    • State history timeline per node
    • Input/output inspection
  • Debug Tools
    • Memory diff viewer (state changes between nodes)
    • State snapshot comparison
    • Memory leak detection

Local Control Panel

Build a dashboard for localized Credential Management (editing the ~/.hive/credentials store safely) and swarm lifecycle management (Start, Pause, Kill, and HITL approvals).

  • Credential Management Backend
    • CredentialStore with file/env/vault backends (credentials/store.py)
    • OAuth2 provider support (credentials/oauth2/)
    • Template resolution and caching
  • Credential Management Dashboard
    • Safe credential editing interface (web UI)
    • ~/.hive/credentials store management UI
    • Credential validation and testing UI
    • Encryption status display
    • OAuth2 flow initiation from browser
  • Swarm Lifecycle Management
    • Start/Stop controls for agents
    • Pause/Resume functionality
    • Kill process management
    • HITL approval interface in browser
    • Multi-agent orchestration view
  • Monitoring Dashboard
    • Active agents display
    • Resource usage monitoring (CPU, memory, tokens)
    • Performance metrics visualization
    • Execution history

Local Model Integration

Build native frontend configurations to easily connect Open Hive's backend to local open-source inference engines like Ollama, keeping the entire stack offline and private.

  • LLM Integration Layer
    • Provider-agnostic LLM support via LiteLLM (graph/event_loop_node.py)
    • Model configuration in agent definitions
  • Local Model Support
    • Ollama integration and configuration
    • Local LLM configuration UI
    • Model selection and management dashboard
    • Model performance monitoring
  • Offline Mode
    • Full offline functionality (no cloud API calls)
    • Local-only execution mode flag
    • Privacy-first architecture enforcement
    • Local model fallback mechanisms
  • Model Configuration
    • Easy model switching in UI
    • Model parameter tuning (temperature, top_p, etc.)
    • Performance optimization settings
    • Multi-model support (different models per node)
    • Model cost tracking for local models

Cross-Platform Support

  • JavaScript/TypeScript SDK
    • TypeScript SDK development
    • npm package distribution
    • Node.js runtime support
    • Browser runtime support
  • Platform Compatibility
    • Windows support improvements
    • macOS optimization
    • Linux distribution support

Coding Agent Integration

  • IDE Integrations
    • Claude Code integration
    • Cursor integration
    • Opencode integration
    • Antigravity integration
    • Codex CLI integration (in progress)