dify

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

LangWatch is a monitoring and analytics platform designed to track, visualize, and analyze interactions with Large Language Models (LLMs). It offers real-time telemetry to optimize LLM cost and latency, a user-friendly interface for deep insights into LLM behavior, user analytics for engagement metrics, detailed debugging capabilities, and guardrails to monitor LLM outputs for issues like PII leaks and toxic language. The platform supports OpenAI and LangChain integrations, simplifying the process of tracing LLM calls and generating API keys for usage. LangWatch also provides documentation for easy integration and self-hosting options for interested users.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

Blinko is an innovative open-source project designed for individuals who want to quickly capture and organize their fleeting thoughts. It allows users to seamlessly jot down ideas the moment they strike, ensuring that no spark of creativity is lost. With advanced AI-powered note retrieval, data ownership, efficient and fast capturing, lightweight architecture, and open collaboration, Blinko offers a comprehensive solution for managing and accessing notes.

Haystack is an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. Whether you want to perform retrieval-augmented generation (RAG), document search, question answering or answer generation, Haystack can orchestrate state-of-the-art embedding models and LLMs into pipelines to build end-to-end NLP applications and solve your use case.

Rocketnotes is a web-based Markdown note taking app with LLM-powered text completion, chat and semantic search. It utilizes a 100% serverless RAG pipeline build with langchain, sentence-transformers, faiss and OpenAI or Anthropic API.

Aria is a Zotero plugin that serves as an AI Research Assistant powered by Large Language Models (LLMs). It offers features like drag-and-drop referencing, autocompletion for creators and tags, visual analysis using GPT-4 Vision, and saving chats as notes and annotations. Aria requires the OpenAI GPT-4 model family and provides a configurable interface through preferences. Users can install Aria by downloading the latest release from GitHub and activating it in Zotero. The tool allows users to interact with Zotero library through conversational AI and probabilistic models, with the ability to troubleshoot errors and provide feedback for improvement.

A package to help benchmark various LLM related tasks. The benchmarks are organized by end-to-end use cases, and utilize LangSmith heavily. We have several goals in open sourcing this: * Showing how we collect our benchmark datasets for each task * Showing what the benchmark datasets we use for each task is * Showing how we evaluate each task * Encouraging others to benchmark their solutions on these tasks (we are always looking for better ways of doing things!)

CodeGPT is an extension for JetBrains IDEs that provides access to state-of-the-art large language models (LLMs) for coding assistance. It offers a range of features to enhance the coding experience, including code completions, a ChatGPT-like interface for instant coding advice, commit message generation, reference file support, name suggestions, and offline development support. CodeGPT is designed to keep privacy in mind, ensuring that user data remains secure and private.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

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.

Refact.ai is an open-source AI coding assistant that boosts developer's productivity. It supports 25+ programming languages and offers features like code completion, AI Toolbox for code explanation and refactoring, integrated in-IDE chat, and self-hosting or cloud version. The Enterprise plan provides enhanced customization, security, fine-tuning, user statistics, efficient inference, priority support, and access to 20+ LLMs for up to 50 engineers per GPU.

Amurex is a powerful AI meeting assistant that integrates seamlessly into your workflow. It ensures you never miss details, stay on top of action items, and make meetings more productive. With real-time suggestions, smart summaries, and follow-up emails, Amurex acts as your personal copilot. It is open-source, transparent, secure, and privacy-focused, providing a seamless AI-driven experience to take control of your meetings and focus on what truly matters.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

Cody is a free, open-source AI coding assistant that can write and fix code, provide AI-generated autocomplete, and answer your coding questions. Cody fetches relevant code context from across your entire codebase to write better code that uses more of your codebase's APIs, impls, and idioms, with less hallucination.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

This repository introduces and helps organizations get started with building AI Apps and incorporating Large Language Models (LLMs) into them. The workshop covers topics such as prompt engineering, AI orchestration, and deploying AI apps. Participants will learn how to use Azure OpenAI, Langchain/ Semantic Kernel, Qdrant, and Azure AI Search to build intelligent applications.

Runhouse is a tool that allows you to build, run, and deploy production-quality AI apps and workflows on your own compute. It provides simple, powerful APIs for the full lifecycle of AI development, from research to evaluation to production to updates to scaling to management, and across any infra. By automatically packaging your apps into scalable, secure, and observable services, Runhouse can also turn otherwise redundant AI activities into common reusable components across your team or company, which improves cost, velocity, and reproducibility.

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.

SDFX is the ultimate no-code platform for building and sharing AI apps with beautiful UI. It enables the creation of user-friendly interfaces for complex workflows by combining Comfy workflow with a UI. The tool is designed to merge the benefits of form-based UI and graph-node based UI, allowing users to create intricate graphs with a high-level UI overlay. SDFX is fully compatible with ComfyUI, abstracting the need for installing ComfyUI. It offers features like animated graph navigation, node bookmarks, UI debugger, custom nodes manager, app and template export, image and mask editor, and more. The tool compiles as a native app or web app, making it easy to maintain and add new features.

This repository serves as a hub for Microsoft Official Build & Modernize AI Applications reference solutions and content. It provides access to projects demonstrating how to build Generative AI applications using Azure services like Azure OpenAI, Azure Container Apps, Azure Kubernetes, and Azure Cosmos DB. The solutions include Vector Search & AI Assistant, Real-Time Payment and Transaction Processing, and Medical Claims Processing. Additionally, there are workshops like the Intelligent App Workshop for Microsoft Copilot Stack, focusing on infusing intelligence into traditional software systems using foundation models and design thinking.

RAGHack is a hackathon focused on building AI applications using the power of RAG (Retrieval Augmented Generation). RAG combines large language models with search engine knowledge to provide contextually relevant answers. Participants can learn to build RAG apps on Azure AI using various languages and retrievers, explore frameworks like LangChain and Semantic Kernel, and leverage technologies such as agents and vision models. The hackathon features live streams, hack submissions, and prizes for innovative projects.

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.

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.