Best AI tools for< Hammer Nails >

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

This repository provides a tool for forwarding SMS and call notifications using various notification methods such as Telegram, PushDeer, Bark, DingTalk, Feishu, WeCom, Pushover, email, Gotify, Inotify, and SMTP protocol. It also allows controlling devices via SMS, scheduling base station positioning, querying data usage, reporting device status, power button operations, low power mode, message queue usage for sending notifications without freezing, automatic resend on notification failure, and support for master-slave mode for message forwarding.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

AdaSociety is a multi-agent environment designed for simulating social structures and decision-making processes. It offers built-in resources, events, and player interactions. Users can customize the environment through JSON configuration or custom Python code. The environment supports training agents using RLlib and LLM frameworks. It provides a platform for studying multi-agent systems and social dynamics.

AppWorld is a high-fidelity execution environment of 9 day-to-day apps, operable via 457 APIs, populated with digital activities of ~100 people living in a simulated world. It provides a benchmark of natural, diverse, and challenging autonomous agent tasks requiring rich and interactive coding. The repository includes implementations of AppWorld apps and APIs, along with tests. It also introduces safety features for code execution and provides guides for building agents and extending the benchmark.

This prototype synthesizes verified code with an LLM using Monte Carlo Tree Search (MCTS). It explores the space of possible generation of a verified program and checks at every step that it's on the right track by calling the verifier. This prototype uses Dafny, Coq, Lean, Scala, or Rust. By using this technique, weaker models that might not even know the generated language all that well can compete with stronger models.

skpro is a library for supervised probabilistic prediction in python. It provides `scikit-learn`-like, `scikit-base` compatible interfaces to: * tabular **supervised regressors for probabilistic prediction** \- interval, quantile and distribution predictions * tabular **probabilistic time-to-event and survival prediction** \- instance-individual survival distributions * **metrics to evaluate probabilistic predictions** , e.g., pinball loss, empirical coverage, CRPS, survival losses * **reductions** to turn `scikit-learn` regressors into probabilistic `skpro` regressors, such as bootstrap or conformal * building **pipelines and composite models** , including tuning via probabilistic performance metrics * symbolic **probability distributions** with value domain of `pandas.DataFrame`-s and `pandas`-like interface

OpenVINO™ AI Plugins for Audacity* are a set of AI-enabled effects, generators, and analyzers for Audacity®. These AI features run 100% locally on your PC -- no internet connection necessary! OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU. * **Music Separation**: Separate a mono or stereo track into individual stems -- Drums, Bass, Vocals, & Other Instruments. * **Noise Suppression**: Removes background noise from an audio sample. * **Music Generation & Continuation**: Uses MusicGen LLM to generate snippets of music, or to generate a continuation of an existing snippet of music. * **Whisper Transcription**: Uses whisper.cpp to generate a label track containing the transcription or translation for a given selection of spoken audio or vocals.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

MLE-Agent is an intelligent companion designed for machine learning engineers and researchers. It features autonomous baseline creation, integration with Arxiv and Papers with Code, smart debugging, file system organization, comprehensive tools integration, and an interactive CLI chat interface for seamless AI engineering and research workflows.

Discourse-air is a clean and modern theme for forums, featuring light and dark modes, clickable topics, loading slider, search banner, and category + group boxes. Users need to enable specific settings for the theme components to render properly. It offers customization options for color schemes, search banner placement, and category organization.

sktime is a Python library for time series analysis that provides a unified interface for various time series learning tasks such as classification, regression, clustering, annotation, and forecasting. It offers time series algorithms and tools compatible with scikit-learn for building, tuning, and validating time series models. sktime aims to enhance the interoperability and usability of the time series analysis ecosystem by empowering users to apply algorithms across different tasks and providing interfaces to related libraries like scikit-learn, statsmodels, tsfresh, PyOD, and fbprophet.

AgentPoison is a repository that provides the official PyTorch implementation of the paper 'AgentPoison: Red-teaming LLM Agents via Memory or Knowledge Base Backdoor Poisoning'. It offers tools for red-teaming LLM agents by poisoning memory or knowledge bases. The repository includes trigger optimization algorithms, agent experiments, and evaluation scripts for Agent-Driver, ReAct-StrategyQA, and EHRAgent. Users can fine-tune motion planners, inject queries with triggers, and evaluate red-teaming performance. The codebase supports multiple RAG embedders and provides a unified dataset access for all three agents.

Perplexity is a module that utilizes emailnator to generate new accounts, providing users with 5 pro queries per account creation. It enables the creation of new Gmail accounts with emailnator, ensuring unlimited pro queries. The tool requires specific Python libraries for installation and offers both a web interface and an API for different usage scenarios. Users can interact with the tool to perform various tasks such as account creation, query searches, and utilizing different modes for research purposes. Perplexity also supports asynchronous operations and provides guidance on obtaining cookies for account usage and account generation from emailnator.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

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Consistent property auction game host with post-purchase renovation insights.

Where Curious Minds Hammer Out Everyday Innovations

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