pywebtask 0.1.1

LLM-powered web automation library with autonomous agents and natural language selectors

webtask

LLM-powered web automation library with autonomous agents and natural language selectors.

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What it does

Three ways to use it:

High-level - Give it a task, let it figure out the steps Step-by-step - Execute tasks one step at a time for debugging/control Low-level - Tell it exactly what to do with natural language selectors

Uses LLMs to understand pages, plan actions, and select elements. Built with Playwright for the browser stuff.

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Quick look

Setup:

from webtask import Webtask
from webtask.integrations.llm import GeminiLLM

# Create Webtask manager (browser launches lazily)
wt = Webtask()

# Choose your LLM (Gemini or OpenAI)
llm = GeminiLLM.create(model="gemini-2.5-flash")

# Create agent
agent = await wt.create_agent(llm=llm)

High-level autonomous:

# Agent figures out the steps
result = await agent.execute("search for cats and click the first result")
print(f"Completed: {result.completed}")

Step-by-step execution:

# Execute task one step at a time
agent.set_task("add 2 items to cart")

for i in range(10):
    step = await agent.run_step()

    print(f"Step {i+1}: {len(step.proposals)} actions")
    print(f"Verification: {step.verification.message}")

    if step.verification.complete:
        break

# Useful for debugging, progress tracking, or custom control flow

Low-level imperative:

# You control the steps, agent handles the selectors
await agent.navigate("https://google.com")

search_box = await agent.select("search box")
await search_box.fill("cats")

button = await agent.select("search button")
await button.click()

# Wait for page to stabilize
await agent.wait_for_idle()

# Take screenshot
await agent.screenshot("result.png")

No CSS selectors. No XPath. Just describe what you want.

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How it works

High-level mode - The agent loop:

1. Proposer looks at the page and task, decides next action
2. Executer runs it (click, type, navigate, etc.)
3. Verifier checks if task complete
4. Repeat until done

Step-by-step mode - Same as high-level but you control the loop:

• agent.set_task(description) - Set the task
• agent.execute_step() - Execute one step (propose → execute → verify)
• agent.clear_history() - Reset for new task

Low-level mode - You call methods directly:

• agent.navigate(url) - Go to a page
• agent.select(description) - Find element by natural language
• element.click(), element.fill(text), element.type(text) - Interact with elements
• agent.wait(seconds) - Wait for specific duration
• agent.wait_for_idle() - Wait for network/DOM to stabilize
• agent.screenshot(path) - Capture page screenshot

All modes use the same core: LLM sees cleaned DOM with element IDs like button-0 instead of raw HTML. Clean input, clean output.

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Status

🚧 Work in progress

Core implementation complete. See TODO for testing plan and future work.

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Benchmarks

Evaluate webtask on standard web agent benchmarks:

webtask-benchmarks - Evaluation framework for Mind2Web and other benchmarks

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Install

pip install pywebtask
playwright install chromium

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License

MIT