Search Results for "catch"
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Showing 14 open source projects for "catch"
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1
promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API. -
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Sourcery AI Code Review
Instant AI code reviews
...It integrates directly into development workflows through plugins for editors like VS Code, JetBrains IDEs, and command-line tools, so suggestions appear where developers already write code. Because it continuously evaluates changes, it can catch inefficiencies and suggest enhancements both while typing and during dedicated refactor passes. Teams can standardize code quality across codebases by adopting Sourcery’s automated suggestions as part of review or CI pipelines. -
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Pearl
A Production-ready Reinforcement Learning AI Agent Library
...Tutorials demonstrate end-to-end workflows on OpenAI Gym tasks and contextual-bandit setups derived from tabular datasets, emphasizing reproducibility and clear baselines. Pearl’s design favors clarity and deployability: metrics, logging, and evaluation harnesses are integrated so you can monitor learning, compare agents, and catch regressions. -
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LLM Course
Course to get into Large Language Models (LLMs)
...The materials also cover inference optimization and quantization to make serving LLMs feasible on commodity GPUs or even CPUs, which is crucial for side projects and startups. Evaluation is treated as a first-class topic, with examples of automatic and human-in-the-loop methods to catch regressions and verify quality beyond simple loss values. By the end, students have a mental model and a practical toolkit for iterating on datasets, training configs, etc. -
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5
Thinc
A refreshing functional take on deep learning
...Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. -
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Groq AppGen
Project showcasing Llama 3.3 70B HTML codegen abilities
...For developers or non-coding designers alike, groq-appgen lowers the barrier to building full web interfaces or small apps by leveraging LLM-driven code generation rather than writing boilerplate by hand. It integrates safety/content-checking via LlamaGuard to catch undesirable outputs, and includes session management, export/share functionality, and history tracking so you can iterate on designs or revert as needed. -
7
PC Workman HCK
AI-powered PC monitoring that explains. Not shows numbers/spikes.
Your PC says CPU 87%. PC Workman says why, since when, and what to do about it. Real-time system monitor with built-in offline AI. No cloud. Your data stays on your machine. What's inside: -hck_GPT: 82-intent AI assistant. -Ask it anything about your PC in Polish or English. -9-layer routing, learns your usage patterns over weeks. -TURBO mode: one click stops unnecessary services (Gaming/Work/Economy profiles), switches power plan, flushes RAM, freezes idle apps. -One click restores... -
8
Joanium Classic
Your smart, reliable, and friendly personal AI assistant.
...Joanium is now live. Download: https://www.joanium.com/download GitHub: https://www.github.com/Joanium/Joanium Early adopters will understand it first. Everyone else will catch up later. #AI #Agents #OpenSource #BuildInPublic -
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Bloomer
Simple clicker for Bloom cryptogame
Bloom is a Telegram bot that allows you to mine cryptocurrency through various games and mining. In one of the games you have to catch blooms and thus accumulate them for a certain time while they fall. The bot allows you to facilitate the process and catch all the blooms in a very short period of time. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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10
Foolbox
Python toolbox to create adversarial examples
...Foolbox 3 is built on top of EagerPy and runs natively in PyTorch, TensorFlow, and JAX. Foolbox provides a large collection of state-of-the-art gradient-based and decision-based adversarial attacks. Catch bugs before running your code thanks to extensive type annotations in Foolbox. Foolbox is a Python library that lets you easily run adversarial attacks against machine learning models like deep neural networks. It is built on top of EagerPy and works natively with models in PyTorch, TensorFlow, and JAX. -
11
State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
This repository is the source for a book (or large written work) titled “The State of Open Source AI”. The goal of the project is to bring clarity to the rapidly evolving open-source AI ecosystem by documenting trends, models, tools, standards, deployment practices, and challenges. It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain.... -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot... -
13
PokemonGo-Bot
The Pokemon Go Bot, baking with community
...Diverse options for humanlike behavior from movement to overall game play. Ability to add multiple coordinates to select between your favorite botting locations. Support self defined path / route. Advanced catch, evolve and transfer confuration using our PokemonOptimizer settings. Determine which pokeball to use. Rules to determine the use of Razz and Pinap Berries. Exchange, evolve and catch Pokemon base on pre-configured rules. Transfer Pokemon in bulk. Auto switch mode. -
14
scholar-sidekick-mcp
Citations, exports & retraction checks for AI assistants (MCP)
...From any supported identifier - DOI, PMID, PMCID, ISBN, arXiv ID, ISSN, NASA ADS bibcode, or WHO IRIS URL - it can: - resolveIdentifier - return structured bibliographic metadata (CSL JSON) - formatCitation - format into 10,000+ CSL styles (Vancouver, APA, AMA, IEEE, CSE, or any CSL style ID) - exportCitation - export to BibTeX, RIS, CSL JSON, EndNote, RefWorks, MEDLINE, Zotero RDF, CSV, or plain text - checkRetraction - surface retractions, corrections, and expressions of concern (Crossref / Retraction Watch) - checkOpenAccess - report OA status and the best legal landing/PDF URL (Unpaywall) - verifyCitation - cross-check a claimed citation against the record at its identifier, detecting the AI-driven "real DOI + invented title" fabrication pattern that simple resolution cannot catch MIT licensed; source on GitHub.
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