Add ZeroScript_AI_TestExecutor Notebook #716
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| GitGuardian id | GitGuardian status | Secret | Commit | Filename | |
|---|---|---|---|---|---|
| - | - | Username Password | 0cddc3f | examples/cookbooks/ZeroScript_AI_TestExecutor.ipynb | View secret |
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…ment-Services-Assistant.ipynb
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Summary of Changes
Hello @Dhivya-Bharathy, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request introduces five new cookbook examples as Jupyter notebooks, demonstrating various AI agent capabilities using PraisonAI. These include a Chilean government services assistant, an intelligent cognitive agent, a memory-enhanced search agent, a cybersecurity PoC agent, and an AI-powered test executor. Each notebook provides a practical, ready-to-use example for different use cases.
Highlights
- New Notebook: Chile Government Services Assistant: Adds a new notebook demonstrating an AI chatbot that answers questions about Chilean government services using the Firecrawl API and a conversational approach.
- New Notebook: Intelligent Cognitive Agent: Introduces a notebook showcasing a multi-specialist cognitive assistant using PraisonAI, where each specialist is implemented as a tool.
- New Notebook: MemoryPal Search Agent: Adds a notebook providing a minimal example of using PraisonAI's Agent with a custom internet search tool (DuckDuckGo) in Python, designed for Google Colab.
- New Notebook: Pocky Cybersecurity PoC Agent: Introduces a notebook for automated CVE PoC search and validation, which helps find, filter, and fetch real-world PoC exploits.
- New Notebook: ZeroScript AI Test Executor: Adds a notebook for AI-powered browser test automation using PraisonAI Agent and OpenAI, which executes YAML-defined test cases, captures screenshots, and generates JSON reports.
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Code Review
This pull request adds Jupyter notebook examples demonstrating the PraisonAI framework. The notebooks share a critical security issue: hardcoding placeholder API keys. This should be addressed. There are also opportunities to improve code clarity and robustness.
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #716 +/- ##
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- Coverage 14.50% 14.23% -0.27%
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Files 25 25
Lines 2517 2571 +54
Branches 357 367 +10
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+ Hits 365 366 +1
- Misses 2136 2189 +53
Partials 16 16
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A lightweight AI agent designed to interpret and execute functional test instructions written in plain language.
It converts natural language inputs into executable Python test cases, making QA processes more accessible.
Powered by PraisonAI Agents and Python execution, it’s ideal for zero-code test automation workflows.