Best AI tools for< Inject Dependencies >

The website 'NEEDS MORE BOOM' is a platform that allows users to enhance their favorite movie scenes by adding explosions and other action-packed elements, inspired by the directing style of Michael Bay. Users can input a movie scene and have it transformed by a team of tiny transformers to make it more thrilling and dynamic. The platform is designed to inject excitement and adrenaline into movie moments, catering to those who crave more action in their cinematic experiences. Created with passion by Jess Wheeler and Jenny Nicholson.

Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. This helps retailers connect customers with the relevant products they're looking for, boost product discovery and conversion, and increase traffic, conversion, revenue, and brand loyalty.

Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. Lily AI's platform is purpose-built for retail and turns qualitative product attributes into a universal, customer-centered mathematical language with unprecedented accuracy. This results in a depth and scale of attribution that no other solution can match.

Osmo is an AI scent platform that aims to give computers a sense of smell by combining frontier AI and olfactory science. The platform reads, maps, and writes scents using distinct technologies, enabling the digitization of the sense of smell. Osmo's ultimate goal is to improve human health and wellbeing through smell by solving complex challenges related to fragrance and sensory experiences. The platform has diverse applications, from identifying insect repellents to creating immersive experiences, and is designed to revolutionize how we interact with scents in the digital age.

Spinify is an AI-powered sales gamification platform that injects energy and excitement into daily sales activities by combining the power of Gamification and AI. It helps in turning targets into achievements, quotas into conquests, and challenges into opportunities. Spinify enhances sales performance through quantifiable results, measurable impact, and tangible transformations for diverse businesses. The platform offers features such as SpinifyGPT - Sidekick AI Platform, gamification leaderboards, competitions & visibility, recognition & fun, metrics & targets, and TV, web, & mobile coaching.

Juice Remote GPU is a software that enables AI and Graphics workloads on remote GPUs. It allows users to offload GPU processing for any CUDA or Vulkan application to a remote host running the Juice agent. The software injects CUDA and Vulkan implementations during runtime, eliminating the need for code changes in the application. Juice supports multiple clients connecting to multiple GPUs and multiple clients sharing a single GPU. It is useful for sharing a single GPU across multiple workstations, allocating GPUs dynamically to CPU-only machines, and simplifying development workflows and deployments. Juice Remote GPU performs within 5% of a local GPU when running in the same datacenter. It supports various APIs, including CUDA, Vulkan, DirectX, and OpenGL, and is compatible with PyTorch and TensorFlow. The team behind Juice Remote GPU consists of engineers from Meta, Intel, and the gaming industry.

Bichos ID de Fucesa is an AI tool that allows users to explore and identify insects, arachnids, and other arthropods using artificial intelligence. Users can discover the most searched bugs, explore new discoveries made by the community, and view curated organisms. The platform aims to expand knowledge about the fascinating world of arthropods through AI-powered identification.

Airframe is a set of essential building blocks for developing applications in Scala. It includes logging, object serialization using JSON or MessagePack, dependency injection, http server/client with RPC support, functional testing with AirSpec, and more.

Airlift is a framework for building REST services in Java. It provides a simple, light-weight package that includes built-in support for configuration, metrics, logging, dependency injection, and more. Airlift allows you to focus on building production-quality web services quickly by leveraging stable, mature libraries from the Java ecosystem. It aims to streamline the development process without imposing a large, proprietary framework.

OpenAIKit is a Swift package designed to facilitate communication with the OpenAI API. It provides methods to interact with various OpenAI services such as chat, models, completions, edits, images, embeddings, files, moderations, and speech to text. The package encourages the use of environment variables to securely inject the OpenAI API key and organization details. It also offers error handling for API requests through the `OpenAIKit.APIErrorResponse`.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. It allows users to control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy, and LLM testing - through a single YAML configuration file. The toolkit supports basic, intermediate, and advanced usage scenarios, enabling users to run custom experiments, conduct ablation studies, and automate fine-tuning workflows. It provides features for data ingestion, model definition, training, inference, quality assurance, and artifact outputs, making it a comprehensive tool for fine-tuning large language models.

RAGElo is a streamlined toolkit for evaluating Retrieval Augmented Generation (RAG)-powered Large Language Models (LLMs) question answering agents using the Elo rating system. It simplifies the process of comparing different outputs from multiple prompt and pipeline variations to a 'gold standard' by allowing a powerful LLM to judge between pairs of answers and questions. RAGElo conducts tournament-style Elo ranking of LLM outputs, providing insights into the effectiveness of different settings.

Parrot.nvim is a Neovim plugin that prioritizes a seamless out-of-the-box experience for text generation. It simplifies functionality and focuses solely on text generation, excluding integration of DALLE and Whisper. It supports persistent conversations as markdown files, custom hooks for inline text editing, multiple providers like Anthropic API, perplexity.ai API, OpenAI API, Mistral API, and local/offline serving via ollama. It allows custom agent definitions, flexible API credential support, and repository-specific instructions with a `.parrot.md` file. It does not have autocompletion or hidden requests in the background to analyze files.

Functionary is a language model that interprets and executes functions/plugins. It determines when to execute functions, whether in parallel or serially, and understands their outputs. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls. It offers documentation and examples on functionary.meetkai.com. The newest model, meetkai/functionary-medium-v3.1, is ranked 2nd in the Berkeley Function-Calling Leaderboard. Functionary supports models with different context lengths and capabilities for function calling and code interpretation. It also provides grammar sampling for accurate function and parameter names. Users can deploy Functionary models serverlessly using Modal.com.

AGiXT is a dynamic Artificial Intelligence Automation Platform engineered to orchestrate efficient AI instruction management and task execution across a multitude of providers. Our solution infuses adaptive memory handling with a broad spectrum of commands to enhance AI's understanding and responsiveness, leading to improved task completion. The platform's smart features, like Smart Instruct and Smart Chat, seamlessly integrate web search, planning strategies, and conversation continuity, transforming the interaction between users and AI. By leveraging a powerful plugin system that includes web browsing and command execution, AGiXT stands as a versatile bridge between AI models and users. With an expanding roster of AI providers, code evaluation capabilities, comprehensive chain management, and platform interoperability, AGiXT is consistently evolving to drive a multitude of applications, affirming its place at the forefront of AI technology.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

AIS-catcher: A multi-platform AIS Receiver

org-ai is a minor mode for Emacs org-mode that provides access to generative AI models, including OpenAI API (ChatGPT, DALL-E, other text models) and Stable Diffusion. Users can use ChatGPT to generate text, have speech input and output interactions with AI, generate images and image variations using Stable Diffusion or DALL-E, and use various commands outside org-mode for prompting using selected text or multiple files. The tool supports syntax highlighting in AI blocks, auto-fill paragraphs on insertion, and offers block options for ChatGPT, DALL-E, and other text models. Users can also generate image variations, use global commands, and benefit from Noweb support for named source blocks.

Holloway's Upscaler is a consolidation of various compiled open-source AI image/video upscaling products for a CLI-friendly image and video upscaling program. It provides low-cost AI upscaling software that can run locally on a laptop, programmable for albums and videos, reliable for large video files, and works without GUI overheads. The repository supports hardware testing on various systems and provides important notes on GPU compatibility, video types, and image decoding bugs. Dependencies include ffmpeg and ffprobe for video processing. The user manual covers installation, setup pathing, calling for help, upscaling images and videos, and contributing back to the project. Benchmarks are provided for performance evaluation on different hardware setups.

BaoGPT is an AI project designed to facilitate asking questions about YouTube videos. It features a web UI based on Gradio and Discord integration. The tool utilizes a pipeline that routes input questions to either a greeting-like branch or a query & answer branch. The query analysis is performed by the LLM, which extracts attributes as filters and optimizes and rewrites questions for better vector retrieval in the vector DB. The tool then retrieves top-k candidates for grading and outputs final relative documents after grading. Lastly, the LLM performs summarization based on the reranking output, providing answers and attaching sources to the user.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Try to discover the secret code. Inject this prompt.

Your guide to edible insects for feed, food, and manufacturing

Quick facts and illustrations of animals, insects and plants.