AIProjectPulse

Discover the most innovative AI and machine learning projects from GitHub.

Promptimizer: Automated AI Prompt Optimization Tool

GitHub Stats Value
Stars 129
Forks 8
Language TypeScript
Created 2024-07-26
License Other

Promptimizer is an automated AI-powered framework designed to optimize prompts for large language models (LLMs) using genetic algorithms and machine learning techniques. This project aims to enhance the efficiency and accuracy of AI prompts, with a specific example focused on AI-driven stock screening. While it promises significant improvements, users should be cautious of the potential costs involved. For those concerned about expenses, local LLMs like Ollama are recommended for optimization tasks. Promptimizer is a valuable tool for anyone looking to refine AI prompts and achieve better results in various applications.

Radicalbit AI Monitoring: Comprehensive ML Model Tracker

GitHub Stats Value
Stars 70
Forks 5
Language Python
Created 2024-06-19
License Apache License 2.0

The Radicalbit AI Monitoring Platform is a robust solution designed to monitor and maintain the performance of your Machine Learning and Large Language models in production. It addresses the common issue of model degradation over time due to factors like data shifts or concept drift. By analyzing both your reference dataset and current datasets, the platform helps you proactively identify and address potential performance issues, ensuring optimal model quality, data quality, and detecting model drift. This comprehensive monitoring capability makes it a valuable tool for anyone looking to maintain the reliability and effectiveness of their AI models in real-world applications.

repromodel: AI Research Efficiency Toolbox for Developers

GitHub Stats Value
Stars 151
Forks 24
Language Python
Created 2024-05-02
License Other

The ReproModel project is an open-source toolbox designed to enhance the efficiency of AI research. It enables researchers to reproduce, compare, train, and test AI models more quickly and effectively. By providing standardized models, dataloaders, and processing procedures, ReproModel streamlines the research process, allowing scientists to focus on developing new datasets and models without the burden of repetitive tasks. The toolbox includes a suite of pre-existing experiments, a code extractor, and an LLM descriptor, making it easier to train models, visualize results, and automate methodology descriptions. This no-code solution reduces time and computational costs, making it a valuable resource for the AI research community.

safe-content-ai: Fast API for NSFW Image Detection

GitHub Stats Value
Stars 54
Forks 8
Language Python
Created 2024-04-22
License MIT License

The ‘safe-content-ai’ project is a robust and efficient API designed for detecting Not Safe For Work (NSFW) images, making it an essential tool for content moderation on digital platforms. Built using Python, the FastAPI framework, Transformers library, and TensorFlow, this API leverages the Falconsai/nsfw-image-detection AI model to provide accurate results. It also optimizes performance by caching results based on the SHA-256 hash of image data and automatically utilizing GPU if available. This project is worth exploring for its ease of use, high accuracy, and scalability, making it a valuable asset for maintaining a safe and compliant online environment.

Scrapegraph-ai: Intelligent Web Scraping Library

GitHub Stats Value
Stars 14521
Forks 1187
Language Python
Created 2024-01-27
License MIT License

ScrapeGraphAI is a Python library designed for efficient web scraping using large language models (LLM) and direct graph logic. It simplifies the process of creating scraping pipelines for various formats, including websites and local documents like XML, HTML, JSON, and Markdown. By specifying the information you need, ScrapeGraphAI handles the extraction process, making it an invaluable tool for developers and data analysts. This project is worth exploring for its ease of use and powerful capabilities in automating data extraction tasks.

screenpipe: Versatile Plugin Management Tool

GitHub Stats Value
Stars 1525
Forks 110
Language Rust
Created 2024-06-19
License MIT License

Screenpipe is a versatile tool designed to enhance your productivity and data management. It allows users to create, share, and install plugins (referred to as “pipes”) directly from the app interface, leveraging GitHub repositories or directories. Recent updates include improved audio input and output support across Windows, Linux, and MacOS, as well as multi-monitor capture and integration with Whisper Distil large v3 for speech-to-text functionality. The platform also features video embedding, where AI generates links to your video recordings in the chat. With a growing user base and a newly released pipe store, Screenpipe offers a user-friendly way to maximize your data utility, even for those without technical expertise.