My Testing Thoughts

  What is an ARIA Snapshot in Playwright? An  ARIA snapshot  in Playwright is a structured representation of a page’s  accessibility tree , which is used by assistive technologies (e.g., screen readers) to interpret the content of a web page. This snapshot helps verify if elements have the correct  roles, names, and properties  required for accessibility. Playwright provides the page.accessibility.snapshot() API to capture this accessibility tree at any given moment during test execution. How Does ARIA Work? ARIA ( Accessible Rich Internet Applications ) is a set of attributes that help improve accessibility by defining roles, states, and properties for elements that are not natively accessible. Example: In this case, the aria-label ensures that screen readers identify the button as “Submit Form.” How to Use ARIA Snapshots in Playwright? Playwright’s  accessibility.snapshot()   method retrieves the  accessible structure  of the page. Ex...

  ExtentReports is being sunset and will be replaced by ChainTest Reporting Framework. 1. What is ChainTest? ChainTest is an open-source test reporting and analytics framework designed to enhance the way QA teams manage and analyze their test results. Think of it as a central hub for all your test data, offering: Real-time analytics : Stay updated with the latest test outcomes. Historical reports : Compare results over time to identify trends and improve processes. Static reports : Easily share detailed HTML reports with stakeholders. Multi-project dashboards : Consolidate data from different projects into a single view. This tool is designed to integrate seamlessly into your existing testing workflows, providing both flexibility and scalability. 2. Why Use ChainTest? Let’s talk about why ChainTest stands out: Enhanced Visibility : Gain clear insights into your test execution metrics, helping your tea...

  Custom Instructions in ChatGPT, also known as   Tailored Preferences   are the best way to control ChatGPT’s output easily. Example 1: Like, if you are drained of typing “Give a brief response” or “Please respond in length” like me? Try following this instruction. If I add * at the end of my question, please provide a concise, to-the-point response. If I add **, provide a full and comprehensive response. If I do not provide any symbols, please provide a standard response. Example 2: We can control the model’s temperature using APIs, but there is no way to do it through the UI. You can use the following instruction to have GPT follow temperature. If I specify a temperature range of 0 to 1 at the conclusion of the question, please react accordingly: Temperature 0 indicates highly deterministic responses, thus you should always run a web search before responding. Temperature 1 gives for greater creativity and freedom in reaction.

  1. Generative AI A subset of artificial intelligence focused on creating new content, such as text, images, audio, video, or code. It relies on models trained on vast datasets to identify patterns and generate similar but unique outputs. 2. Large Language Model (LLM) An AI model trained to process and generate human-like text. Examples include GPT (Generative Pre-trained Transformer), BERT, and LaMDA, all of which leverage deep learning architectures, specifically transformers. 3. Transformer A neural network architecture known for its ability to process sequential data, like text. Transformers use self-attention mechanisms, enabling the model to learn relationships between words and capture long-range dependencies efficiently. 4. Retrieval-Augmented Generation (RAG) A hybrid approach combining retrieval-based and generative AI techniques. RAG models retrieve relevant information from external sources (e.g., databases or documents) and then use this information to generate contex...

  What is LlamaParse? LlamaParse is a proprietary parsing service that is incredibly good at parsing PDFs with complex tables into a well-structured markdown format. It directly integrates with LlamaIndex ingestion and retrieval to let you build retrieval over complex, semi-structured documents. It is promised to be able to answer complex questions that weren’t possible previously. This service is available in a public preview mode: available to everyone, but with a usage limit (1k pages per day) with 7,000 free pages per week. Then $0.003 per page ($3 per 1,000 pages). It operates as a standalone service that can also be plugged into the managed ingestion and retrieval API Currently, LlamaParse primarily supports PDFs with tables, but they are also building out better support for figures, and an expanded set of the most popular document types: .docx, .pptx, .html as a part of the next enhancements. Code Implementation: Install required dependencies: a) Create requirements.txt in t...

  Using Generative AI for Audio/Video Processing: Power of Summarization What Is the Purpose of This Application ? This application is for audio and video summarization. For users who wish to quickly create bullet point summaries of audio/video content, it is a useful tool. Sample code: from langchain.document_loaders import youtube from langchain.text_splitter import RecursiveCharacterTextSplitter import openai import streamlit as st openai.api_key = "<<Add your key here>>" st.set_page_config(page_title= "YouTube Audio/Video Summariser App" ) st.markdown( """<p style="color: #3fd100;font-size: 30px;font-family: sans-serif; text-align:center;margin-bottom:0px;"><b>YouTube Audio/Video </b><span style="color: #3fd100;font-size: 30px;font-family: sans-serif;"><b>Summariser App</b></span></p><p></p>""" , unsafe_allow_html= True ) st.head...