canopy VS WebdriverIO

Pinecone: A scalable vector database service that facilitates efficient similarity search in high-dimensional spaces. Ideal for building real-time applications in AI, such as personalized recommendation engines and content-based retrieval systems.

In this post we’ll build a Python script that uses StripeDocs Reader, a loader on LlamaIndex, that creates vector embeddings of Stripe's documentation in Pinecone. This allows a user to ask questions about Stripe Docs to an LLM, in this case OpenAI, and receive a generated response.

Pinecone is a managed vector database service that simplifies the process of building and scaling vector search applications. It offers a simple API for embedding vector search into applications, providing accurate, scalable similarity search with minimal setup and maintenance.

In case of AIMD, I am doing this all in-memory, but you could also do this in a database (e.g. Pinecone). It all depends on how much data you have and how much compute you have available.

A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving to meet the new challenge.

In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).

3.WebdriverIO: WebdriverIO is another popular open-source test automation framework. Key Features: Integrates well with popular testing frameworks (e.g., Mocha, Jasmine). Supports both synchronous and asynchronous commands. Works with various browsers and platforms

Webdriver.io

There is a tool called webdriver.io which purports to handle mobile automation. I haven't had a chance to play with it yet but it's on my radar.

We recently hired an engineer to write us integration tests with webdriver.io. All of our other tests run fine in Github actions - rspec, javascript jest, etc.

Your automated tests will act on behalf of a real user, open a real web browser (typically Chromium, Chrome, Firefox) using one an existing technology like Webdriver and add some syntactical sugar on top.

WebdriverIO (abbreviated as WDIO) is an E2E testing framework for Node.js. It allows you to automate all kinds of web and mobile applications using the Webdriver or Chrome DevTools protocols.

i recall having to deal with elements inside iframes and shadow roots when using webdriver.io for testing. you can always inspect an element and copy the selector. if it is unique to the page it should work