llm-resources is a repository providing resources to get started with Large Language Models (LLMs). It includes videos on Neural Networks and LLMs, free courses, prompt engineering guides, explored frameworks, AI assistants, and tips on making RAG work properly. The repository also contains important links and updates related to LLMs, AWS, RAG, agents, model context protocol, and more. It aims to help individuals with a basic understanding of NLP and programming knowledge to explore and utilize LLMs effectively.

This repository provides resources to understand and utilize GPT (Generative Pre-trained Transformer) by Azure OpenAI. It includes sample solutions, use cases, and quick start guides. Users can explore various applications of GPT, such as chatbots, customer service, and content generation. The repository also offers Langchain, Semantic Kernel, and Prompt Flow samples, along with Serverless SQL GPT for natural language processing in Azure Synapse Analytics. The samples are based on GPT 3.5, with plans to update for GPT-4. Users are encouraged to contribute to keep the repository updated with the latest technologies and solutions.

Writing Tools is an Apple Intelligence-inspired application for Windows, Linux, and macOS that supercharges your writing with an AI LLM. It allows users to instantly proofread, optimize text, and summarize content from webpages, YouTube videos, documents, etc. The tool is privacy-focused, open-source, and supports multiple languages. It offers powerful features like grammar correction, content summarization, and LLM chat mode, making it a versatile writing assistant for various tasks.

WordLift is a plugin that helps online content creators organize posts and pages by adding facts, links, and media to build beautifully structured websites for both humans and search engines. It allows users to create, own, and publish their own knowledge graph, and publishes content as Linked Open Data following Tim Berners-Lee's Linked Data Principles. The plugin supports writers by providing trustworthy and contextual facts, enriching content with images, links, and interactive visualizations, keeping readers engaged with relevant content recommendations, and producing content compatible with schema.org markup for better indexing and display on search engines. It also offers features like creating a personal Wikipedia, publishing metadata to share and distribute content, and supporting content tagging for better SEO.

LearnHouse is an open-source platform that allows anyone to easily provide world-class educational content. It supports various content types, including dynamic pages, videos, and documents. The platform is still in early development and should not be used in production environments. However, it offers several features, such as dynamic Notion-like pages, ease of use, multi-organization support, support for uploading videos and documents, course collections, user management, quizzes, course progress tracking, and an AI-powered assistant for teachers and students. LearnHouse is built using various open-source projects, including Next.js, TailwindCSS, Radix UI, Tiptap, FastAPI, YJS, PostgreSQL, LangChain, and React.

CodeGate is a local gateway that enhances the safety of AI coding assistants by ensuring AI-generated recommendations adhere to best practices, safeguarding code integrity, and protecting individual privacy. Developed by Stacklok, CodeGate allows users to confidently leverage AI in their development workflow without compromising security or productivity. It works seamlessly with coding assistants, providing real-time security analysis of AI suggestions. CodeGate is designed with privacy at its core, keeping all data on the user's machine and offering complete control over data.

Blox AI is a platform that allows users to effortlessly create flowcharts and diagrams, collaborate with teams, and receive explanations from the Google Gemini model. It offers rich text editing, versatile visualizations, secure workspaces, and limited files allotment. Users can install it as an app and use it for wireframes, mind maps, and algorithms. The platform is built using Next.Js, Typescript, ShadCN UI, TailwindCSS, Convex, Kinde, EditorJS, and Excalidraw.

Agent Pilot is an open source desktop app for creating, managing, and chatting with AI agents. It features multi-agent, branching chats with various providers through LiteLLM. Users can combine models from different providers, configure interactions, and run code using the built-in Open Interpreter. The tool allows users to create agents, manage chats, work with multi-agent workflows, branching workflows, context blocks, tools, and plugins. It also supports a code interpreter, scheduler, voice integration, and integration with various AI providers. Contributions to the project are welcome, and users can report known issues for improvement.

OpenLLMetry is a set of extensions built on top of OpenTelemetry that gives you complete observability over your LLM application. Because it uses OpenTelemetry under the hood, it can be connected to your existing observability solutions - Datadog, Honeycomb, and others. It's built and maintained by Traceloop under the Apache 2.0 license. The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly.

LLMstudio by TensorOps is a platform that offers prompt engineering tools for accessing models from providers like OpenAI, VertexAI, and Bedrock. It provides features such as Python Client Gateway, Prompt Editing UI, History Management, and Context Limit Adaptability. Users can track past runs, log costs and latency, and export history to CSV. The tool also supports automatic switching to larger-context models when needed. Coming soon features include side-by-side comparison of LLMs, automated testing, API key administration, project organization, and resilience against rate limits. LLMstudio aims to streamline prompt engineering, provide execution history tracking, and enable effortless data export, offering an evolving environment for teams to experiment with advanced language models.

VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!

The AI Workshop repository provides a comprehensive guide to utilizing OpenAI's APIs, including Chat Completion, Embedding, and Assistant APIs. It offers hands-on demonstrations and code examples to help users understand the capabilities of these APIs. The workshop covers topics such as creating interactive chatbots, performing semantic search using text embeddings, and building custom assistants with specific data and context. Users can enhance their understanding of AI applications in education, research, and other domains through practical examples and usage notes.

VividNode is a cross-platform AI desktop chatbot application for LLM such as GPT, Claude, Gemini, Llama chatbot interaction and image generation. It offers customizable features, local chat history, and enhanced performance without requiring a browser. The application is powered by GPT4Free and allows users to interact with chatbots and generate images seamlessly. VividNode supports Windows, Mac, and Linux, securely stores chat history locally, and provides features like chat interface customization, image generation, focus and accessibility modes, and extensive customization options with keyboard shortcuts for efficient operations.

LLM Agentic Tool Mesh is a platform by HPE Athonet that democratizes Generative Artificial Intelligence (Gen AI) by enabling users to create tools and web applications using Gen AI with Low or No Coding. The platform simplifies the integration process, focuses on key user needs, and abstracts complex libraries into easy-to-understand services. It empowers both technical and non-technical teams to develop tools related to their expertise and provides orchestration capabilities through an agentic Reasoning Engine based on Large Language Models (LLMs) to ensure seamless tool integration and enhance organizational functionality and efficiency.

Instrukt is a terminal-based AI integrated environment that allows users to create and instruct modular AI agents, generate document indexes for question-answering, and attach tools to any agent. It provides a platform for users to interact with AI agents in natural language and run them inside secure containers for performing tasks. The tool supports custom AI agents, chat with code and documents, tools customization, prompt console for quick interaction, LangChain ecosystem integration, secure containers for agent execution, and developer console for debugging and introspection. Instrukt aims to make AI accessible to everyone by providing tools that empower users without relying on external APIs and services.

ChatFAQ is an open-source comprehensive platform for creating a wide variety of chatbots: generic ones, business-trained, or even capable of redirecting requests to human operators. It includes a specialized NLP/NLG engine based on a RAG architecture and customized chat widgets, ensuring a tailored experience for users and avoiding vendor lock-in.

llm-resources is a repository providing resources to get started with Large Language Models (LLMs). It includes videos on Neural Networks and LLMs, free courses, prompt engineering guides, explored frameworks, AI assistants, and tips on making RAG work properly. The repository also contains important links and updates related to LLMs, AWS, RAG, agents, model context protocol, and more. It aims to help individuals with a basic understanding of NLP and programming knowledge to explore and utilize LLMs effectively.

Awesome-LLM-RAG-Application is a repository that provides resources and information about applications based on Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) pattern. It includes a survey paper, GitHub repo, and guides on advanced RAG techniques. The repository covers various aspects of RAG, including academic papers, evaluation benchmarks, downstream tasks, tools, and technologies. It also explores different frameworks, preprocessing tools, routing mechanisms, evaluation frameworks, embeddings, security guardrails, prompting tools, SQL enhancements, LLM deployment, observability tools, and more. The repository aims to offer comprehensive knowledge on RAG for readers interested in exploring and implementing LLM-based systems and products.

Welcome to the comprehensive collection of advanced + agentic Retrieval-Augmented Generation (RAG) techniques. This repository covers the most effective advanced + agentic RAG techniques with clear implementations and explanations. It aims to provide a helpful resource for researchers and developers looking to use advanced RAG techniques in their projects, offering ready-to-use implementations and guidance on evaluation methods. The RAG framework addresses limitations of Large Language Models by using external documents for in-context learning, ensuring contextually relevant and accurate responses. The repository includes detailed descriptions of various RAG techniques, tools used, and implementation guidance for each technique.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

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.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.