This article provides a guide on how to run a Flask application with Gunicorn, including installing Gunicorn, setting up a Flask application, and running the application with Gunicorn.
Key quote "When you run the server via Gunicorn, you need to specify the module name and the variable name of the app for Gunicorn to access it. Note that the variable should be a WSGI callable object for e.g a flask app object. "
This is a hands-on guide with Python example code that walks through the deployment of an ML-based search API using a simple 3-step approach. The article provides a deployment strategy applicable to most machine learning solutions, and the example code is available on GitHub.
An exploration of the benefits of switching from the popular Python library Pandas to the newer Polars for data manipulation tasks, highlighting improvements in performance, concurrency, and ease of use.
A light-weight codebase that enables memory-efficient and performant finetuning of Mistral's models. It is based on LoRA, a training paradigm where most weights are frozen and only 1-2% additional weights in the form of low-rank matrix perturbations are trained.
Learn how to build an open LLM app using Hermes 2 Pro, a powerful LLM based on Meta's Llama 3 architecture. This tutorial explains how to deploy Hermes 2 Pro locally, create a function to track flight status using FlightAware API, and integrate it with the LLM.
This article describes the process of implementing function-calling in an AI system, specifically using the Mistral AI platform. The example showcases the development of an assistant that can manage a home automation system through natural language interactions with the user, including the use of available functions, function logic, and the integration of these functions into the AI system.
MicroPython, a Python interpreter for microcontrollers, has released version 1.23 with several improvements. Notably, it now supports creating custom USB devices on multiple levels and has received improvements for OpenAMP, an inter-core communication protocol.
An in-process analytics database, DuckDB can work with surprisingly large data sets without having to maintain a distributed multiserver system. Best of all? You can analyze data directly from your Python app.
LlamaFS is a self-organizing file manager that automatically renames and organizes files based on their contents. It supports various file types and even images and audio. It can run in two modes - batch mode and watch mode. In batch mode, LlamaFS suggests a file structure and organizes files. In watch mode, it watches your directory and proactively learns your file organization habits. The project is built on a Python backend and Electron for the frontend.
An article discussing a simple and free way to automate data workflows using Python and GitHub Actions, written by Shaw Talebi.
Bookmarks on this page are managed by an admin user. 