canopy
Xunit.Gherkin.Quick
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canopy | Xunit.Gherkin.Quick | |
---|---|---|
13 | 2 | |
870 | 190 | |
14.8% | - | |
9.8 | 0.0 | |
24 days ago | over 1 year ago | |
Python | C# | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
canopy
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How to choose the right type of database
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.
- Show HN: R2R – Open-source framework for production-grade RAG
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Using Stripe Docs in your RAG pipeline with LlamaIndex
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.
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7 Vector Databases Every Developer Should Know!
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.
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Using Vector Embeddings to Overengineer 404 pages
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.
- Pinecone: Build Knowledgeable AI
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How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
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.
- FLaNK Stack Weekly 11 Dec 2023
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Embracing Modern Python for Web Development
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).
- Canopy is an open-source Retrieval Augmented Generation (RAG) framework
Xunit.Gherkin.Quick
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NUnit vs XUnit for .net6+ microservices
Extensible: Has some really good extension support. There are libs that provide some very interesting ways to use xunit, such as Xunit.Gherkin.Quick, xunit-spec, xunit-bdd, CoreBDD, and many others
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BDD-style Testing in F# with Xunit.Gherkin, GherkinProvider and TickSpec
There is a hidden gem for Xunit called Xunit.Gherkin.Quick which allows you to create standard feature files using the Gherkin language, and automate these with Xunit-based tests.
What are some alternatives?
ragna - RAG orchestration framework ⛵️
SpecFlow - #1 .NET BDD Framework. SpecFlow automates your testing & works with your existing code. Find Bugs before they happen. Behavior Driven Development helps developers, testers, and business representatives to get a better understanding of their collaboration
simple-pgvector-python - An Abstraction Using a similar API to Pinecone but implemented with pgvector python
NUnit - NUnit Framework
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
xUnit - xUnit.net is a free, open source, community-focused unit testing tool for .NET.
tiger - Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)
SpecsFor - SpecsFor is a light-weight Behavior-Driven Development framework that focuses on ease of use for *developers* by minimizing testing friction.
mlx-examples - Examples in the MLX framework
Fluent Assertions - A very extensive set of extension methods that allow you to more naturally specify the expected outcome of a TDD or BDD-style unit tests. Targets .NET Framework 4.7, as well as .NET Core 2.1, .NET Core 3.0, .NET 6, .NET Standard 2.0 and 2.1. Supports the unit test frameworks MSTest2, NUnit3, XUnit2, MSpec, and NSpec3.
tonic_validate - Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
Canopy - f# web automation and testing library, built on top of Selenium (friendly to c# also)