Python

Cursor vs Windsurf: Which AI Code Editor Is Best for Python?

AI-powered code editors have moved beyond novelty to become everyday tools for many Python developers. Instead of having to switch between your editor and a separate AI chat, you can use tools like Cursor and Windsurf that bring AI directly into your workflow. As a result, the Cursor vs Windsurf question is a common one for developers deciding which to adopt. Both Cursor and Windsurf are VS Code forks that import your keybindings, themes, and Python extensions, and both run […]

Read more
Python

Quiz: Accessing Multiple AI Models With the OpenRouter API

Interactive Quiz ⋅ 8 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Accessing Multiple AI Models With the OpenRouter API. By working through this quiz, you’ll revisit how OpenRouter provides a unified routing layer, how to call AI models from a single Python script, how to switch between intelligent routing and a specific model, how to prioritize providers, and how to add model fallbacks for reliability. It also reinforces how to weigh trade-offs like cost, latency, […]

Read more
Python

Quiz: Embeddings and Vector Databases With ChromaDB

Interactive Quiz ⋅ 10 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Embeddings and Vector Databases With ChromaDB. By working through this quiz, you’ll revisit key concepts like vectors, cosine similarity, word and text embeddings, ChromaDB collections, metadata filtering, and retrieval-augmented generation (RAG). The quiz contains 10 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score […]

Read more
Python

Accessing Multiple AI Models With the OpenRouter API

One of the quickest ways to call multiple AI models from a single Python script is to use OpenRouter’s API, which acts as a unified routing layer between your code and multiple AI providers. By the end of this course, you’ll be able to access models from several providers through one unified API. This convenience matters because the AI ecosystem is highly fragmented: each provider exposes its own API, authentication scheme, rate limits, and model lineup. Working with multiple providers […]

Read more
Python

Python 3.15 Hits Feature Freeze and Other News for June 2026

While the Northern Hemisphere warms up for summer, Python 3.15 went the other way with its beta 1 feature freeze 🥶. Since May 7, the list of what will be included in the next release is final. That list includes a brand-new sentinel built-in that finally standardizes a pattern Python developers have been hand-rolling for decades. And while AI kept writing code, buggy or not, developers also directed it to look for bugs in code that had been sitting untouched […]

Read more
huggingface

Beyond LLMs: Why Scalable Enterprise AI Adoption Depends on Agent Logic

Guides have aided humanity throughout history. Prehistoric civilizations understood that the sun and the moon could be used to navigate vast distances on land and the high seas. Over time, various journeys facilitated the production of maps for better planning and faster travel time to repeat destinations. Centuries later, the introduction of the compass enabled seagoers to achieve greater accuracy in seeking unexplored destinations. And today, GPS navigation apps guide our every journey. In today’s world of agentic AI, AI […]

Read more
huggingface

Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains

Mellum2 is a 12B-parameter Mixture-of-Experts model trained from scratch on natural language and code. The model activates only 2.5B parameters per token, making it efficient for high-throughput, low-latency inference. Mellum2 is can be used for routing, RAG, summarization, sub-agents, high-throughput coding features, and private deployments. It is released under the Apache 2.0 license. Compared with similar-sized models, Mellum2 delivers competitive benchmark performance while achieving more than 2x faster inference. Download the model on Hugging Face: https://huggingface.co/collections/JetBrains/mellum-2 For architecture details, training […]

Read more
huggingface

Holo3.1: Fast & Local Computer Use Agents

Last March, we released Holo3, our state-of-the-art computer-use model. Adoption was immediate. Developers, enterprises, and partners started deploying Holo3 across a wide range of workflows, from browser automation and business software to internal tools and desktop applications. As adoption grew, we realized performance alone was no longer enough. Users want to run the same computer-use capabilities across desktop and mobile environments, with seamless integration with different agent frameworks. They want deployment flexibility, from cloud inference to fully local execution on […]

Read more
huggingface

Adding MCP Tools to Reachy Mini

Reachy Mini no longer has to look out the window to tell you the weather The Reachy Mini conversation app can now use tools hosted in public Hugging Face Spaces, called over MCP. You can give your robot a new ability, like checking the weather or searching the web, by adding a Space from the Hub instead of editing the app. The tool keeps running in the Space itself, so no code is downloaded onto your machine. And you can […]

Read more
huggingface

Direct Preference Optimization Beyond Chatbots

In April, we released DharmaOCR, our specialized structured OCR model (available on Hugging Face) along with a paper detailing the methodology behind it and a benchmark demonstrating its superior quality and cost efficiency. The paper benchmarked leading vision-language model families - both open-source and commercial - on a structured document extraction task: OCR on Brazilian Portuguese text. Among the reported metrics was text degeneration rate: the frequency with which a model produces a repetition loop instead of a transcription. Across the tested open-source families, […]

Read more
1 2 3 … 1,044