clawome 0.1.5

Clawome — AI browser agent. One command to run any web task.

中文 | English

Clawome

One API call. Any web task. Done.
Give your AI agent a natural language goal — Clawome plans, browses, and returns structured results.

Task Agent API • Quick Start • DOM Compression • Benchmarks • Roadmap

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Task Agent API

One POST request. Clawome handles the rest — planning subtasks, controlling the browser, reading pages, and returning results.

curl -X POST http://localhost:5001/api/agent/start \
  -H "Content-Type: application/json" \
  -d '{"description": "Find AI-related graduate programs at NYU Tandon School of Engineering"}'

Poll progress:

curl http://localhost:5001/api/agent/status

{
  "status": "completed",
  "final_result": "NYU Tandon offers these AI-related programs: ...",
  "subtasks": [
    {"step": 1, "goal": "Visit NYU Tandon website", "status": "completed"},
    {"step": 2, "goal": "Extract program list", "status": "completed"}
  ],
  "llm_usage": {"calls": 12, "input_tokens": 25000, "total_tokens": 28000}
}

Cancel if needed:

curl -X POST http://localhost:5001/api/agent/stop

Method	Endpoint	Description
POST	/api/agent/start	Submit a task (natural language)
GET	/api/agent/status	Poll progress, subtasks, and results
POST	/api/agent/stop	Cancel running task

Start parameters:

Field	Type	Description
task	string	Task description (required)
max_steps	number	Override step limit for this task (default: 15)

Status values: idle → starting → running → completed / failed / cancelled

Tips for Writing Tasks

Bad:  "打开深圳大学网站看看有什么内容"
Good: "打开 https://www.szu.edu.cn 首页，提取导航栏、最新3条新闻和通知公告"

• Give a URL — avoid letting the agent guess where to go
• Specify what to extract — "top 5 news" is better than "all news"
• Complex tasks? Increase steps — "max_steps": 30 for multi-page tasks
• Or split into smaller tasks — each task focused on one page or one goal

How It Works

Your API call → Task Agent → Plan subtasks → Execute browser actions → Return results
                                  ↑                                        |
                                  └── evaluate & replan if needed ─────────┘

The agent uses a LangGraph state machine internally: perceive page → plan next step → execute action → sense result → repeat until done.

Features

• Natural language tasks — Describe what you want in plain language
• Multi-step planning — Automatically breaks complex tasks into subtasks
• Smart execution — Perceive → Plan → Act → Sense loop with retry and anomaly detection
• Markdown results — Final results formatted in Markdown with structured data
• 12+ LLM providers — OpenAI, Anthropic, Google, DeepSeek, DashScope, Moonshot, Zhipu, Mistral, Groq, xAI, and more
• Safety constraints — Browser-only actions, hard step limits

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DOM Compression

Under the hood, the Task Agent sees web pages through Clawome's DOM compressor — turning 300K tokens of raw HTML into ~3K tokens of clean, structured trees.

You can also use this directly as a standalone API for your own agents:

# Open a page
curl -X POST http://localhost:5001/api/browser/open \
  -d '{"url": "https://www.google.com"}'

# Read compressed DOM
curl http://localhost:5001/api/browser/dom

[1] form(role="search")
  [1.1] textarea(name="q", placeholder="Search")
  [1.2] button: Google Search
  [1.3] button: I'm Feeling Lucky
[2] a(href): About
[3] a(href): Gmail

• 100:1 compression ratio on typical web pages
• Preserves visible text, interactive elements, and semantic structure
• Hierarchical node IDs (e.g., 1.2.3) for precise element targeting
• Site-specific optimizers for Google, Wikipedia, Stack Overflow, YouTube, etc.
• Lite mode for even more aggressive token savings

Dashboard

• Browser Playground — Interactive DOM viewer and browser control
• Agent UI — Task input, real-time progress tracking, collapsible step details
• Settings — LLM provider config, browser options, compression settings
• API Docs — Built-in documentation with Chinese/English support

Quick Start

Prerequisites: Python 3.10+

pip install clawome         # Install from PyPI
clawome start               # Guided setup + start server

If clawome command is not found after install, use:

python -m clawome start     # Alternative way to run

clawome start will walk you through LLM configuration (provider, API key, model), then start the backend and install Playwright chromium automatically.

Dashboard:  http://localhost:5173
API:        http://localhost:5001

Then run tasks from the terminal:

clawome "去Hacker News找最新AI新闻"          # Submit task & auto-poll
clawome status                               # Check progress
clawome stop                                 # Cancel task
clawome "complex task" --max-steps 30        # Override step limit
clawome setup                                # Reconfigure LLM settings

You can also skip CLI setup and configure via Dashboard > Settings.

Start backend or frontend separately

./start-backend.sh         # Only API server → http://localhost:5001
./start-frontend.sh        # Only Dashboard  → http://localhost:5173

Manual setup

# Backend
cd backend
python -m venv venv
source venv/bin/activate    # Windows: venv\Scripts\activate
pip install -r requirements.txt
playwright install chromium
python app.py               # http://localhost:5001

# Frontend (in another terminal)
cd frontend
npm install
npm run dev                 # http://localhost:5173

Full API Reference

Browser APIs — Navigation, DOM, Interaction (used internally by Task Agent, also available standalone)

Navigation

Method	Endpoint	Description
POST	/api/browser/open	Open URL (launches browser if needed)
POST	/api/browser/back	Navigate back
POST	/api/browser/forward	Navigate forward
POST	/api/browser/refresh	Reload page

DOM

Method	Endpoint	Description
GET/POST	/api/browser/dom	Get compressed DOM tree
POST	/api/browser/dom/detail	Get element details (rect, attributes)
POST	/api/browser/text	Get plain text content of a node
GET	/api/browser/source	Get raw page HTML

Interaction

Method	Endpoint	Description
POST	/api/browser/click	Click element
POST	/api/browser/type	Type text (keyboard events)
POST	/api/browser/fill	Fill input field
POST	/api/browser/select	Select dropdown option
POST	/api/browser/check	Toggle checkbox
POST	/api/browser/hover	Hover element
POST	/api/browser/scroll/down	Scroll down
POST	/api/browser/scroll/up	Scroll up
POST	/api/browser/keypress	Press key
POST	/api/browser/hotkey	Press key combo

Token Optimization

All action endpoints support optional parameters to reduce response size:

• refresh_dom: false — Skip DOM refresh after action (saves tokens)
• fields: ["dom", "stats"] — Return only selected fields

Benchmarks

Page	Raw HTML	Compressed	Savings	Completeness
Google Homepage	51K	238	99.5%	100%
Google Search	298K	2,866	99.0%	100%
Wikipedia Article	225K	40K	82.1%	99.7%
Baidu Homepage	192K	457	99.8%	100%
Baidu Search	390K	4,960	98.7%	100%

Completeness = percentage of visible text preserved in the compressed tree.

Supported LLM Providers

Provider	Model Examples
DashScope (Qwen)	qwen-plus, qwen-max, qwen3.5-plus
OpenAI	gpt-4o, gpt-4o-mini
Anthropic	claude-sonnet-4-20250514, claude-haiku
Google	gemini-2.0-flash, gemini-pro
DeepSeek	deepseek-chat, deepseek-reasoner
Mistral	mistral-large-latest
Groq	llama-3.1-70b
xAI	grok-2
Moonshot	moonshot-v1-8k
Zhipu	glm-4
Custom	Any OpenAI-compatible endpoint

Roadmap

• DOM compression API with pluggable site-specific scripts
• Task Agent with multi-step planning and autonomous browsing
• Multi-provider LLM support (12+ providers)
• Chinese/English bilingual dashboard
• MCP (Model Context Protocol) server integration
• Visual grounding — screenshot-based element location
• Multi-agent collaboration

Third-Party Libraries

Library	License	Usage
Playwright	Apache 2.0	Browser automation
Flask	BSD 3-Clause	REST API server
React	MIT	Frontend UI
LangGraph	MIT	Agent workflow engine
LiteLLM	MIT	Multi-provider LLM routing
Pydantic	MIT	Schema validation

License

Apache License 2.0 - see LICENSE for details.