2025-02-12 –, AI-Powered Test Automation: Integrating Robot Framework with OpenAI
In this hands-on workshop, you will learn how to integrate Robot Framework with OpenAI to supercharge your test automation. Over a full day, we’ll guide you through setting up the integration, generating dynamic test data, creating adaptive tests, and building AI-powered solutions for real-world testing challenges. No prior AI experience required.
Description:
This full-day workshop is designed for QA engineers and test automation developers interested in integrating Robot Framework with AI to create smarter, more adaptive test automation solutions. As applications become more complex, traditional test automation can struggle to keep up with dynamic requirements. By connecting OpenAI models to Robot Framework, you’ll learn how AI can transform your testing workflows—automating tasks that were previously manual or time-consuming.
Throughout the workshop, we’ll guide you step-by-step through setting up AI with Robot Framework, generating dynamic test data, creating adaptive and self-healing tests, and automating complex scenarios such as API and browser testing. The goal is to equip you with hands-on experience, allowing you to apply AI-enhanced testing in real-world projects.
Key Learning Areas:
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Why Use AI in Test Automation:
Understand the advantages of AI in testing, such as improving test coverage, automating decision-making, and generating realistic test data. -
Integrating OpenAI with Robot Framework:
Learn how to set up and configure OpenAI’s GPT models with Robot Framework to enhance your test automation process. -
Dynamic Test Data Generation:
Discover how AI can generate real-world test data on demand to simulate a wide variety of user behaviors. -
Building Adaptive and Self-Healing Tests:
Learn how to develop tests that adapt to feedback in real-time and automatically recover from failures, reducing test maintenance. -
Automating API and Browser Tests with AI:
Explore AI’s ability to generate complex API requests, handle browser tests dynamically, and manage edge cases automatically. -
Live AI Interactions During Tests:
Use Robot Framework listeners to capture live events during test execution and feed this information to AI for real-time adaptation of tests. -
Overcoming AI Challenges:
Address common issues such as response times, costs, and managing unpredictable AI outputs to ensure efficient AI integration.
Who Should Attend:
This workshop is perfect for QA engineers, test automation developers, and SDETs interested in applying AI to their testing strategies. Prior knowledge of Robot Framework is helpful, but no AI experience is required.
Takeaways:
By the end of this workshop, you will:
- Understand how to integrate AI models like OpenAI with Robot Framework.
- Learn to generate dynamic test data and build adaptive, self-healing tests.
- Gain hands-on experience in using AI for intelligent API and browser test automation.
- Know how to overcome challenges associated with AI integration in test automation.
AI, Robot Framework, Learning
Lessons Learned:In this workshop, participants will gain practical, hands-on experience with integrating AI models, specifically OpenAI, into Robot Framework for enhancing test automation. The workshop covers a range of topics aimed at giving participants the tools they need to implement AI-driven test automation effectively in real-world projects. Here’s what participants will take away:
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How to Set Up AI with Robot Framework:
- What You'll Learn: Participants will learn the complete setup process for integrating AI with Robot Framework, including how to configure AI models and ensure seamless communication between Robot Framework and AI tools.
- Practical Usage: Attendees will walk away with a step-by-step understanding of how to integrate OpenAI or other AI models into their existing test automation environments. -
Generating Dynamic, Real-World Test Data:
- What You'll Learn: We’ll cover how AI can generate realistic test data dynamically during test execution, including how to customize this data for different use cases.
- Practical Usage: Participants will leave with the ability to automate complex test data generation for various applications, such as simulating real-world user behaviors or creating edge-case scenarios effortlessly. -
Creating Adaptive and Self-Healing Tests:
- What You'll Learn: Participants will explore how to build tests that adapt based on real-time feedback from AI models. This includes self-healing capabilities, where tests can detect and fix issues automatically.
- Practical Usage: By the end of this session, attendees will be able to design tests that can adjust on-the-fly, reducing test maintenance and increasing test reliability. -
Automating API and Browser Tests with AI:
- What You'll Learn: Attendees will discover how AI can enhance API and browser testing by generating complex requests, automating responses, and covering difficult edge cases.
- Practical Usage: Participants will be equipped to use AI to handle intricate API interactions and browser tests that would normally require manual intervention, streamlining the automation process. -
Real-Time AI Interaction and Feedback:
- What You'll Learn: Participants will learn how to use Robot Framework listeners to capture live events during test execution and provide real-time feedback to AI models for dynamic adjustments during testing.
- Practical Usage: This will give participants the tools to implement real-time AI interactions, enabling tests to react to changes and unexpected conditions instantly. -
Overcoming AI Integration Challenges:
- What You'll Learn: We’ll discuss common challenges, such as managing AI response times, controlling costs, and handling unpredictable AI outputs.
- Practical Usage: Participants will leave with best practices on how to address these challenges, ensuring that AI integration is efficient and cost-effective in their test environments.
Takeaway Value:
By the end of the workshop, participants will have hands-on knowledge of how to:
- Integrate AI into Robot Framework for smarter test automation.
- Generate realistic, adaptable test data automatically.
- Create tests that can adapt and recover in real-time.
- Improve API and browser test automation using AI.
- Overcome common challenges in AI integration, ensuring smooth and efficient test execution.
This workshop will provide immediate, practical skills that can be applied directly to their test automation strategies, making their tests more dynamic, intelligent, and capable of handling complex scenarios.
Describe your intended audience:Anyone interested in RF with AI
Is this suitable for ..?:Beginner RF User, Intermediate RF User, Advanced RF User
David Fogl is a seasoned QA automation expert and founder of Continero, specializing in integrating cutting-edge technologies with test automation. With a deep passion for AI and its potential to revolutionize software testing, David has led the development of innovative testing tools, including the RobotFramework-AI library. As a frequent speaker at industry conferences like Robocon, David shares practical insights and hands-on approaches to implementing AI in test automation. His goal is to help developers and QA engineers build smarter, more adaptive testing frameworks that meet the demands of modern software development.