core

CORE is an open-source unified, persistent memory layer for all AI tools, allowing developers to maintain context across different tools like Cursor, ChatGPT, and Claude. It aims to solve the issue of context switching and information loss between sessions by creating a knowledge graph that remembers conversations, decisions, and insights. With features like unified memory, temporal knowledge graph, browser extension, chat with memory, auto-sync from apps, and MCP integration hub, CORE provides a seamless experience for managing and recalling context. The tool's ingestion pipeline captures evolving context through normalization, extraction, resolution, and graph integration, resulting in a dynamic memory that grows and changes with the user. When recalling from memory, CORE utilizes search, re-ranking, filtering, and output to provide relevant and contextual answers. Security measures include data encryption, authentication, access control, and vulnerability reporting.

Kodit is a Code Indexing MCP Server that connects AI coding assistants to external codebases, providing accurate and up-to-date code snippets. It improves AI-assisted coding by offering canonical examples, indexing local and public codebases, integrating with AI coding assistants, enabling keyword and semantic search, and supporting OpenAI-compatible or custom APIs/models. Kodit helps engineers working with AI-powered coding assistants by providing relevant examples to reduce errors and hallucinations.

HAI Code Generator is a cutting-edge tool designed to simplify and automate task execution while enhancing code generation workflows. Leveraging Specif AI, it streamlines processes like task execution, file identification, and code documentation through intelligent automation and AI-driven capabilities. Built on Cline's powerful foundation for AI-assisted development, HAI Code Generator boosts productivity and precision by automating task execution and integrating file management capabilities. It combines intelligent file indexing, context generation, and LLM-driven automation to minimize manual effort and ensure task accuracy. Perfect for developers and teams aiming to enhance their workflows.

VoltAgent is an open-source TypeScript framework designed for building and orchestrating AI agents. It simplifies the development of AI agent applications by providing modular building blocks, standardized patterns, and abstractions. Whether you're creating chatbots, virtual assistants, automated workflows, or complex multi-agent systems, VoltAgent handles the underlying complexity, allowing developers to focus on defining their agents' capabilities and logic. The framework offers ready-made building blocks, such as the Core Engine, Multi-Agent Systems, Workflow Engine, Extensible Packages, Tooling & Integrations, Data Retrieval & RAG, Memory management, LLM Compatibility, and a Developer Ecosystem. VoltAgent empowers developers to build sophisticated AI applications faster and more reliably, avoiding repetitive setup and the limitations of simpler tools.

Flow-Like is an enterprise-grade workflow operating system built upon Rust for uncompromising performance, efficiency, and code safety. It offers a modular frontend for apps, a rich set of events, a node catalog, a powerful no-code workflow IDE, and tools to manage teams, templates, and projects within organizations. With typed workflows, users can create complex, large-scale workflows with clear data origins, transformations, and contracts. Flow-Like is designed to automate any process through seamless integration of LLM, ML-based, and deterministic decision-making instances.

LLM Polymath Chat Node is an advanced Chat Node for ComfyUI that integrates large language models to build text-driven applications and automate data processes, enhancing prompt responses by incorporating real-time web search, linked content extraction, and custom agent instructions. It supports both OpenAI’s GPT-like models and alternative models served via a local Ollama API. The core functionalities include Comfy Node Finder and Smart Assistant, along with additional agents like Flux Prompter, Custom Instructors, Python debugger, and scripter. The tool offers features for prompt processing, web search integration, model & API integration, custom instructions, image handling, logging & debugging, output compression, and more.

FloTorch is an innovative product designed to simplify and optimize the decision-making process for leveraging Large Language Models (LLMs) in Retrieval Augmented Generation (RAG) systems. It focuses on providing a well-architected framework, maximizing efficiency, eliminating complexity, accelerating selection, and fostering innovation. The tool offers a streamlined, user-friendly approach to help users achieve efficiency, accuracy, and cost-effectiveness in the fast-paced digital landscape of AI.

AutoPilot Observability (APO) is an out-of-the-box observability platform that provides one-click installation and ready-to-use capabilities. APO's OneAgent supports one-click configuration-free installation of Tracing probes, collects application fault scene logs, infrastructure metrics, network metrics of applications and downstream dependencies, and Kubernetes events. It supports collecting causality metrics based on eBPF implementation. APO integrates OpenTelemetry probes, otel-collector, Jaeger, ClickHouse, and VictoriaMetrics, reducing user configuration work. APO innovatively integrates eBPF technology with the OpenTelemetry ecosystem, significantly reducing data storage volume. It offers guided troubleshooting using eBPF technology to assist users in pinpointing fault causes on a single page.

TaskingAI brings Firebase's simplicity to **AI-native app development**. The platform enables the creation of GPTs-like multi-tenant applications using a wide range of LLMs from various providers. It features distinct, modular functions such as Inference, Retrieval, Assistant, and Tool, seamlessly integrated to enhance the development process. TaskingAI’s cohesive design ensures an efficient, intelligent, and user-friendly experience in AI application development.

IMGPrompt is an AI prompt editor tailored for image and video generation tools like Stable Diffusion, Midjourney, DALL·E, FLUX, and Sora. It offers a clean interface for viewing and combining prompts with translations in multiple languages. The tool includes features like smart recommendations, translation, random color generation, prompt tagging, interactive editing, categorized tag display, character count, and localization. Users can enhance their creative workflow by simplifying prompt creation and boosting efficiency.

Krita-AI-Diffusion is a plugin for Krita that allows users to generate images from within the program. It offers a variety of features, including inpainting, outpainting, generating images from scratch, refining existing content, live painting, and control over image creation. The plugin is designed to fit into an interactive workflow where AI generation is used as just another tool while painting. It is meant to synergize with traditional tools and the layer stack.

Mira is an agentic AI library designed for automating company research by gathering information from various sources like company websites, LinkedIn profiles, and Google Search. It utilizes a multi-agent architecture to collect and merge data points into a structured profile with confidence scores and clear source attribution. The core library is framework-agnostic and can be integrated into applications, pipelines, or custom workflows. Mira offers features such as real-time progress events, confidence scoring, company criteria matching, and built-in services for data gathering. The tool is suitable for users looking to streamline company research processes and enhance data collection efficiency.

KTransformers is a flexible Python-centric framework designed to enhance the user's experience with advanced kernel optimizations and placement/parallelism strategies for Transformers. It provides a Transformers-compatible interface, RESTful APIs compliant with OpenAI and Ollama, and a simplified ChatGPT-like web UI. The framework aims to serve as a platform for experimenting with innovative LLM inference optimizations, focusing on local deployments constrained by limited resources and supporting heterogeneous computing opportunities like GPU/CPU offloading of quantized models.

Inngest is a platform that offers durable functions to replace queues, state management, and scheduling for developers. It allows writing reliable step functions faster without dealing with infrastructure. Developers can create durable functions using various language SDKs, run a local development server, deploy functions to their infrastructure, sync functions with the Inngest Platform, and securely trigger functions via HTTPS. Inngest Functions support retrying, scheduling, and coordinating operations through triggers, flow control, and steps, enabling developers to build reliable workflows with robust support for various operations.

Simplifine is an open-source library designed for easy LLM finetuning, enabling users to perform tasks such as supervised fine tuning, question-answer finetuning, contrastive loss for embedding tasks, multi-label classification finetuning, and more. It provides features like WandB logging, in-built evaluation tools, automated finetuning parameters, and state-of-the-art optimization techniques. The library offers bug fixes, new features, and documentation updates in its latest version. Users can install Simplifine via pip or directly from GitHub. The project welcomes contributors and provides comprehensive documentation and support for users.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

CORE is an open-source unified, persistent memory layer for all AI tools, allowing developers to maintain context across different tools like Cursor, ChatGPT, and Claude. It aims to solve the issue of context switching and information loss between sessions by creating a knowledge graph that remembers conversations, decisions, and insights. With features like unified memory, temporal knowledge graph, browser extension, chat with memory, auto-sync from apps, and MCP integration hub, CORE provides a seamless experience for managing and recalling context. The tool's ingestion pipeline captures evolving context through normalization, extraction, resolution, and graph integration, resulting in a dynamic memory that grows and changes with the user. When recalling from memory, CORE utilizes search, re-ranking, filtering, and output to provide relevant and contextual answers. Security measures include data encryption, authentication, access control, and vulnerability reporting.

The 'bolt-python-ai-chatbot' is a Slack chatbot app template that allows users to integrate AI-powered conversations into their Slack workspace. Users can interact with the bot in conversations and threads, send direct messages for private interactions, use commands to communicate with the bot, customize bot responses, and store user preferences. The app supports integration with Workflow Builder, custom language models, and different AI providers like OpenAI, Anthropic, and Google Cloud Vertex AI. Users can create user objects, manage user states, and select from various AI models for communication.

ChatGPT-VSCode is a Visual Studio Code integration that allows users to prompt OpenAI's GPT-4, GPT-3.5, GPT-3, and Codex models within the editor. It offers features like using improved models via OpenAI API Key, Azure OpenAI Service deployments, generating commit messages, storing conversation history, explaining and suggesting fixes for compile-time errors, viewing code differences, and more. Users can customize prompts, quick fix problems, save conversations, and export conversation history. The extension is designed to enhance developer experience by providing AI-powered assistance directly within VS Code.

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.