The 'LLM Applications with Java and Spring AI' repository provides samples demonstrating how to build Java applications powered by Generative AI and Large Language Models (LLMs) using Spring AI. It includes projects for question answering, chat completion models, prompts, templates, multimodality, output converters, embedding models, document ETL pipeline, function calling, image models, and audio models. The repository also lists prerequisites such as Java 21, Docker/Podman, Mistral AI API Key, OpenAI API Key, and Ollama. Users can explore various use cases and projects to leverage LLMs for text generation, vector transformation, document processing, and more.

ComfyUI-Ollama-Describer is an extension for ComfyUI that enables the use of LLM models provided by Ollama, such as Gemma, Llava (multimodal), Llama2, Llama3, or Mistral. It requires the Ollama library for interacting with large-scale language models, supporting GPUs using CUDA and AMD GPUs on Windows, Linux, and Mac. The extension allows users to run Ollama through Docker and utilize NVIDIA GPUs for faster processing. It provides nodes for image description, text description, image captioning, and text transformation, with various customizable parameters for model selection, API communication, response generation, and model memory management.

Ito is an intelligent voice assistant that provides seamless voice dictation to any application on your computer. It works in any app, offers global keyboard shortcuts, real-time transcription, and instant text insertion. It is smart and adaptive with features like custom dictionary, context awareness, multi-language support, and intelligent punctuation. Users can customize trigger keys, audio preferences, and privacy controls. It also offers data management features like a notes system, interaction history, cloud sync, and export capabilities. Ito is built as a modern Electron application with a multi-process architecture and utilizes technologies like React, TypeScript, Rust, gRPC, and AWS CDK.

J.A.R.V.I.S. 2.0 is an AI-powered assistant designed for voice commands, capable of tasks like providing weather reports, summarizing news, sending emails, and more. It features voice activation, speech recognition, AI responses, and handles multiple tasks including email sending, weather reports, news reading, image generation, database functions, phone call automation, AI-based task execution, website & application automation, and knowledge-based interactions. The assistant also includes timeout handling, automatic input processing, and the ability to call multiple functions simultaneously. It requires Python 3.9 or later and specific API keys for weather, news, email, and AI access. The tool integrates Gemini AI for function execution and Ollama as a fallback mechanism. It utilizes a RAG-based knowledge system and ADB integration for phone automation. Future enhancements include deeper mobile integration, advanced AI-driven automation, improved NLP-based command execution, and multi-modal interactions.

ComfyUI_Yvann-Nodes is a pack of custom nodes that enable audio reactivity within ComfyUI, allowing users to create AI-driven animations that sync with music. Users can generate audio reactive AI videos, control AI generation styles, content, and composition with any audio input. The tool is simple to use by dropping workflows in ComfyUI and specifying audio and visual inputs. It is flexible and works with existing ComfyUI AI tech and nodes like IPAdapter, AnimateDiff, and ControlNet. Users can pick workflows for Images → Video or Video → Video, download the corresponding .json file, drop it into ComfyUI, install missing custom nodes, set inputs, and generate audio-reactive animations.

LLxprt Code is an AI-powered coding assistant that works with any LLM provider, offering a command-line interface for querying and editing codebases, generating applications, and automating development workflows. It supports various subscriptions, provider flexibility, top open models, local model support, and a privacy-first approach. Users can interact with LLxprt Code in both interactive and non-interactive modes, leveraging features like subscription OAuth, multi-account failover, load balancer profiles, and extensive provider support. The tool also allows for the creation of advanced subagents for specialized tasks and integrates with the Zed editor for in-editor chat and code selection.

Retrace is a local-first screen recording and search application for macOS, inspired by Rewind AI. It captures screen activity, extracts text via OCR, and makes everything searchable locally on-device. The project is in very early development, offering features like continuous screen capture, OCR text extraction, full-text search, timeline viewer, dashboard analytics, Rewind AI import, settings panel, global hotkeys, HEVC video encoding, search highlighting, privacy controls, and more. Built with a modular architecture, Retrace uses Swift 5.9+, SwiftUI, Vision framework, SQLite with FTS5, HEVC video encoding, CryptoKit for encryption, and more. Future releases will include features like audio transcription and semantic search. Retrace requires macOS 13.0+ (Apple Silicon required) and Xcode 15.0+ for building from source, with permissions for screen recording and accessibility. Contributions are welcome, and the project is licensed under the MIT License.

A comprehensive web application for auto-subtitling videos and audio, translating SRT files, generating AI narration with voice cloning, creating background images, and rendering professional subtitled videos. Designed for content creators, educators, and general users who need high-quality subtitle generation and video production capabilities.

evi-run is a powerful, production-ready multi-agent AI system built on Python using the OpenAI Agents SDK. It offers instant deployment, ultimate flexibility, built-in analytics, Telegram integration, and scalable architecture. The system features memory management, knowledge integration, task scheduling, multi-agent orchestration, custom agent creation, deep research, web intelligence, document processing, image generation, DEX analytics, and Solana token swap. It supports flexible usage modes like private, free, and pay mode, with upcoming features including NSFW mode, task scheduler, and automatic limit orders. The technology stack includes Python 3.11, OpenAI Agents SDK, Telegram Bot API, PostgreSQL, Redis, and Docker & Docker Compose for deployment.

AI-Assisted DevOps is a 10-day course focusing on integrating artificial intelligence (AI) technologies into DevOps practices. The course covers various topics such as AI for observability, incident response, CI/CD pipeline optimization, security, and FinOps. Participants will learn about running large language models (LLMs) locally, making API calls, AI-powered shell scripting, and using AI agents for self-healing infrastructure. Hands-on activities include creating GitHub repositories with bash scripts, generating Docker manifests, predicting server failures using AI, and building AI agents to monitor deployments. The course culminates in a capstone project where learners implement AI-assisted DevOps automation and receive peer feedback on their projects.

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.

Timeline Studio is a next-generation professional video editor with AI integration that automates content creation for social media. It combines the power of desktop applications with the convenience of web interfaces. With 257 AI tools, GPU acceleration, plugin system, multi-language interface, and local processing, Timeline Studio offers complete video production automation. Users can create videos for various social media platforms like TikTok, YouTube, Vimeo, Telegram, and Instagram with optimized versions. The tool saves time, understands trends, provides professional quality, and allows for easy feature extension through plugins. Timeline Studio is open source, transparent, and offers significant time savings and quality improvements for video editing tasks.

ToolNeuron is a secure, offline AI ecosystem for Android devices that allows users to run private AI models and dynamic plugins fully offline, with hardware-grade encryption ensuring maximum privacy. It enables users to have an offline-first experience, add capabilities without app updates through pluggable tools, and ensures security by design with strict plugin validation and sandboxing.

Pipecat-examples is a collection of example applications built with Pipecat, an open-source framework for building voice and multimodal AI applications. It includes various examples demonstrating telephony & voice calls, web & client applications, realtime APIs, multimodal & creative solutions, translation & localization tasks, support, educational & specialized use cases, advanced features, deployment & infrastructure setups, monitoring & analytics tools, and testing & development scenarios.

RSTGameTranslation is a tool designed for translating game text into multiple languages efficiently. It provides a user-friendly interface for game developers to easily manage and localize their game content. With RSTGameTranslation, developers can streamline the translation process, ensuring consistency and accuracy across different language versions of their games. The tool supports various file formats commonly used in game development, making it versatile and adaptable to different project requirements. Whether you are working on a small indie game or a large-scale production, RSTGameTranslation can help you reach a global audience by making localization a seamless and hassle-free experience.

LAYRA is the world's first visual-native AI automation engine that sees documents like a human, preserves layout and graphical elements, and executes arbitrarily complex workflows with full Python control. It empowers users to build next-generation intelligent systems with no limits or compromises. Built for Enterprise-Grade deployment, LAYRA features a modern frontend, high-performance backend, decoupled service architecture, visual-native multimodal document understanding, and a powerful workflow engine.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.

Jupyter AI connects generative AI with Jupyter notebooks. It provides a user-friendly and powerful way to explore generative AI models in notebooks and improve your productivity in JupyterLab and the Jupyter Notebook. Specifically, Jupyter AI offers: * An `%%ai` magic that turns the Jupyter notebook into a reproducible generative AI playground. This works anywhere the IPython kernel runs (JupyterLab, Jupyter Notebook, Google Colab, Kaggle, VSCode, etc.). * A native chat UI in JupyterLab that enables you to work with generative AI as a conversational assistant. * Support for a wide range of generative model providers, including AI21, Anthropic, AWS, Cohere, Gemini, Hugging Face, NVIDIA, and OpenAI. * Local model support through GPT4All, enabling use of generative AI models on consumer grade machines with ease and privacy.

Khoj is an open-source, personal AI assistant that extends your capabilities by creating always-available AI agents. You can share your notes and documents to extend your digital brain, and your AI agents have access to the internet, allowing you to incorporate real-time information. Khoj is accessible on Desktop, Emacs, Obsidian, Web, and Whatsapp, and you can share PDF, markdown, org-mode, notion files, and GitHub repositories. You'll get fast, accurate semantic search on top of your docs, and your agents can create deeply personal images and understand your speech. Khoj is self-hostable and always will be.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.