AI-driven test automation agent for apps
Project description
Robot Framework Agent
Enable Agent-mode automation. Write natural-language steps; and let the Agent turns them into tool-based UI actions and checks on web and mobile.
Alpha — An evolving experiment, with varying levels of maturity across keywords - Not recommended for production yet.
Quick Start
*** Settings ***
Library Agent llm_client=openai llm_model=gpt-4.1 platform_type=mobile element_source=accessibility
*** Test Cases ***
Login
Agent.Do enter "user@example.com" in email field
Agent.Do enter "password1234" in the password field
Agent.Do click on login button
Agent.Check verify homepage is displayed
Installation
# Core
pip install robotframework-agent
# Web testing (coming soon)
pip install robotframework-agent[web]
# Mobile testing (+ Appium)
pip install robotframework-agent[mobile]
# Development (all tools)
pip install robotframework-agent[dev]
LLM Providers
Supports OpenAI (default), Anthropic Claude, and Google Gemini.
# With Anthropic/Claude
pip install robotframework-agent[anthropic]
# With Google Gemini
pip install robotframework-agent[gemini]
# Use Claude
Library Agent llm_client=anthropic llm_model=claude-sonnet-4
# Use Gemini
Library Agent llm_client=gemini llm_model=gemini-2.0-flash
Keywords
Agent.Do <instruction>
- Execute actions: click, scroll, input text, select, navigate
- Example:
Agent.Do scroll down to footer
Agent.Check <instruction>
- Perform a visual or semantic verification.
- Example:
Agent.Check verify login form is visible
Agent.Ask <question> format=text|json
- Query current UI state
- Example:
Agent.Ask What is the product price?
Agent.Find Visual Element <description> format=normalized|pixels|center
- Locate elements by description
- Example:
Agent.Find Visual Element search button
Technical Notes
Instruction → LLM → UI Context → Tool Selection → Execution
Experiments and design choices are informed by research on AI agents and UI perception:
- Support Vision-based UI parsing using OmniParser for element detection
- Set-of-Mark (SoM) technique for visual grounding
- Multi-provider LLM support (OpenAI, Anthropic, Gemini)
Ideas are tested and refined in AgentArena, our experimental testing environment.
Presented at RoboCon 2026 (Helsinki)
This project will be showcased at RoboCon 2026 during the talk "What if Robot Framework Had a Brain?"
👉 https://www.robocon.io/agenda/helsinki#what-if-robot-framework-have-a-brain
Contributing
Builders, testers, and curious minds welcome. Code, issues, and real-world use cases help shape the project.
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