• Intelligent Decomposition — LLM analyzes tasks and generates dependency-based subtask graphs
• Automatic Chain Execution — SubAgent completions automatically trigger dependent tasks
• Parallel Execution — Parallel-safe tasks run simultaneously for maximum efficiency
• Dynamic Adjustment — Add/remove subtasks during runtime

WebUI

🔄 Experience Self-Evolution System

A self-learning system that continuously improves from problem-solving experiences:

{
  "id": "exp_86788c0e",
  "timestamp": "2026-04-20T21:19:17",
  "tool_name": "exec",
  "error_type": "argument error",
  "error_message": "",
  "params": {},
  "outcome": "resolved",
  "resolution": "当使用opencli的scroll命令时，确保只传递一个参数，避免参数过多错误。检查命令调用格式，正确示例为`scroll(distance)`或`scroll(selector)`，而非多个参数。在工具调用前验证参数数量，可参考opencli文档或使用测试命令确认API要求。",
  "context_summary": "网页自动化执行：使用opencli执行JavaScript命令时参数错误和代码语法/类型错误，通过调整命令和防御性编程解决",
  "confidence": 0.7,
  "session_key": "cli:direct",
  "merged_count": 0,
  "last_used_at": "2026-04-20T21:19:17",
  "category": "api",
  "tags": ["opencli", "scroll", "参数错误", "浏览器自动化"],
  "use_count": 0,
  "success_count": 0,
  "feedback_positive": 0,
  "feedback_negative": 0
}

• Semantic Experience Search — Vector-based search understands problem intent, not just keywords
• Auto Context Injection — Relevant past solutions automatically appear when you need them
• Proactive Error Diagnosis — Tool failures trigger automatic suggestions from resolved experiences
• Smart Confidence Model — Multi-dimensional scoring: usage frequency, success rate, freshness, feedback
• Automatic Categorization — Experiences tagged by category (path, permission, encoding, network, etc.)

🤖 SubAgent Asynchronous Execution

• Non-blocking Execution — Background tasks don't block main conversation
• Concurrency Control — Configurable max concurrency to prevent overload
• Heartbeat Monitoring — Auto-detects timeout tasks, prevents zombie processes
• Auto-notification — Automatically triggers main Agent to summarize results when complete

💭 Dream Memory Processing

Two-phase autonomous memory consolidation during idle periods:

• Phase 1: Analysis — LLM analyzes conversation history, extracts insights
• Phase 2: Editing — AgentRunner makes targeted edits to memory files
• Phase 3: Experience Update — Merges similar experiences, updates strategy documents
• Vector Storage Integration — Semantic search across consolidated memories

📊 CLI Real-time Progress Display

Task execution shows real-time progress in CLI without disrupting main conversation

⚙️ Integrated Configuration Editor

Full-screen terminal configuration editor accessible directly within the interactive chat:

• Press Ctrl+O or type /config to open the editor
• No need to exit the chat session
• Edit provider settings, model parameters, tool configs, etc.
• Press q to save and return to chat

🔌 MCP (Model Context Protocol) Support

Connect to external MCP servers and use their tools seamlessly:

• Native Tool Wrapping — MCP tools appear as native tinybot tools
• Multiple Server Support — Connect to multiple MCP servers simultaneously
• Auto Tool Discovery — Automatically discovers and registers available tools

🚀 Basic Features

• Multi-platform Integration — Built-in WeChat, DingTalk, Feishu channels; plugin extensibility
• Rich Tools — File read/write, shell execution, browser automation, web search, scheduled tasks
• Intelligent Memory — Vector storage-based memory system with session integration and semantic search
• Multi-LLM Support — Compatible with OpenAI, DeepSeek, Zhipu, Qwen, Gemini, and 14+ providers
• Skills System — Define skills via Markdown files, teach Agent specific workflows without coding
• Automation — Cron scheduled tasks + heartbeat service for periodic auto-execution
• OpenAI Compatible API — Run as OpenAI-compatible backend service, integrate with any OpenAI client
• Session Management — Persistent conversation history with checkpoint recovery
• Security — Workspace restriction, command audit, encrypted credential storage

Quick Start

# Install
uv sync

# Initialize configuration (interactive wizard)
uv run tinybot onboard

# Interactive chat mode
uv run tinybot agent

# Send single message
uv run tinybot agent -m "Hello"

# Start gateway (multi-channel + scheduled tasks + heartbeat)
uv run tinybot gateway

# Run as OpenAI-compatible API server
uv run tinybot api

WebUI Usage

Tinybot provides a browser-based web interface for chatting with the AI agent.

Steps to Enable WebUI

1. Enable WebSocket Channel in Config

Edit your ~/.tinybot/config.json file, add the following under channels:

{
  "channels": {
    "websocket": {
      "enabled": true,
      "host": "127.0.0.1",
      "port": 18790
    }
  }
}

2. Start the Gateway

uv run tinybot gateway

3. Open Browser

Visit http://127.0.0.1:18790 in your browser.

Available API Endpoints

| Endpoint | Method | Description | |----------|--------|-------------| | /api/sessions | GET | List all chat sessions | | /api/sessions/{key}/messages | GET | Get session messages | | /api/sessions/{key} | DELETE/PATCH | Delete/update session | | /api/sessions/{key}/clear | POST | Clear session history | | /api/sessions/{key}/profile | GET | Get user profile | | /api/config | GET/PATCH | Get/update configuration | | /api/status | GET | Get system status | | /api/tools | GET | Get available tools | | /api/skills | GET | Get all skills | | /api/skills/{name} | GET | Get skill detail | | /api/workspace/files | GET | List workspace files | | /ws | WebSocket | Real-time chat connection |

WebSocket Events

| Event | Direction | Description | |-------|-----------|-------------| | new_chat | Client → Server | Create new chat | | attach | Client → Server | Attach to existing chat | | message | Client → Server | Send message | | interrupt | Client → Server | Stop AI generation | | ping | Client → Server | Heartbeat | | delta | Server → Client | Streaming text chunk | | stream_end | Server → Client | Stream finished | | message | Server → Client | Full message | | file_updated | Server → Client | Workspace file changed |

Interactive Chat Commands

When in interactive mode, the following commands are available:

| Command | Description | |---------|-------------| | /config or Ctrl+O | Open configuration editor | | /help | Show available commands | | /clear | Clear conversation history | | /new | Start new conversation session | | /exit or :q | Exit the chat |

Skills System

Define custom skills through simple Markdown files.

Skills are automatically loaded and the Agent follows defined workflows when conditions match.

Before use browser

1. Install OpenCLI

npm install -g @jackwener/opencli

2. Install the Browser Bridge Extension

OpenCLI connects to Chrome/Chromium through a lightweight Browser Bridge extension plus a small local daemon. The daemon auto-starts when needed.

1. Download the latest opencli-extension-v{version}.zip from the GitHub Releases page.
2. Unzip it, open chrome://extensions, and enable Developer mode.
3. Click Load unpacked and select the unzipped folder.

3. Verify the setup

opencli doctor

Experience Tools

The Agent can actively manage its learning experiences:

| Tool | Description | |------|-------------| | query_experience | Search past problem-solving experiences | | save_experience | Save a new solution for future reference | | feedback_experience | Mark an experience as helpful or not | | delete_experience | Remove outdated or incorrect experiences |

Requirements

• Python >= 3.13

License

MIT