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.

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

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.

LLMariner is an extensible open source platform built on Kubernetes to simplify the management of generative AI workloads. It enables efficient handling of training and inference data within clusters, with OpenAI-compatible APIs for seamless integration with a wide range of AI-driven applications.

Qdrant is a vector similarity search engine and vector database. It is written in Rust, which makes it fast and reliable even under high load. Qdrant can be used for a variety of applications, including: * Semantic search * Image search * Product recommendations * Chatbots * Anomaly detection Qdrant offers a variety of features, including: * Payload storage and filtering * Hybrid search with sparse vectors * Vector quantization and on-disk storage * Distributed deployment * Highlighted features such as query planning, payload indexes, SIMD hardware acceleration, async I/O, and write-ahead logging Qdrant is available as a fully managed cloud service or as an open-source software that can be deployed on-premises.

This is the official repository for 'Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing'. Magpie is a tool designed to synthesize high-quality instruction data at scale by extracting it directly from an aligned Large Language Models (LLMs). It aims to democratize AI by generating large-scale alignment data and enhancing the transparency of model alignment processes. Magpie has been tested on various model families and can be used to fine-tune models for improved performance on alignment benchmarks such as AlpacaEval, ArenaHard, and WildBench.

Awesome GPT + Security is a curated list of awesome security tools, experimental case or other interesting things with LLM or GPT. It includes tools for integrated security, auditing, reconnaissance, offensive security, detecting security issues, preventing security breaches, social engineering, reverse engineering, investigating security incidents, fixing security vulnerabilities, assessing security posture, and more. The list also includes experimental cases, academic research, blogs, and fun projects related to GPT security. Additionally, it provides resources on GPT security standards, bypassing security policies, bug bounty programs, cracking GPT APIs, and plugin security.

Languine is a CLI tool that helps developers streamline the localization process by providing AI-powered translations, automation features, and developer-centric design. It allows users to easily manage translation files, maintain consistency in tone and style, and save time by automating tasks. With support for over 100 languages and smart detection capabilities, Languine simplifies the localization workflow for developers.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

Fiction is a next-generation CMS and application framework designed to streamline the creation of AI-generated content. The first-of-its-kind platform empowers developers and content creators by integrating cutting-edge AI technologies with a robust content management system.

Languine is a CLI tool powered by AI that helps developers streamline the localization process by providing AI-powered translations, automation features, consistent localization, developer-centric design, and time-saving workflows. It automates the identification of translation keys, supports multiple file formats, delivers accurate translations in over 100 languages, aligns translations with the original text's tone and intent, extracts translation keys from codebase, and supports hooks for content formatting with Biome or Prettier. Languine is designed to simplify and enhance the localization experience for developers.

LAMBDA is a code-free multi-agent data analysis system that utilizes large models to address data analysis challenges in complex data-driven applications. It allows users to perform complex data analysis tasks through human language instruction, seamlessly generate and debug code using two key agent roles, integrate external models and algorithms, and automatically generate reports. The system has demonstrated strong performance on various machine learning datasets, enhancing data science practice by integrating human and artificial intelligence.

AgentSociety is an advanced framework designed for building agents in urban simulation environments. It integrates LLMs' planning, memory, and reasoning capabilities to generate realistic behaviors. The framework supports dataset-based, text-based, and rule-based environments with interactive visualization. It includes tools for interviews, surveys, interventions, and metric recording tailored for social experimentation.

Cloudflare Agents is a framework for building intelligent, stateful agents that persist, think, and evolve at the edge of the network. It allows for maintaining persistent state and memory, real-time communication, processing and learning from interactions, autonomous operation at global scale, and hibernating when idle. The project is actively evolving with focus on core agent framework, WebSocket communication, HTTP endpoints, React integration, and basic AI chat capabilities. Future developments include advanced memory systems, WebRTC for audio/video, email integration, evaluation framework, enhanced observability, and self-hosting guide.

CodeFuse-muAgent is a Multi-Agent framework designed to streamline Standard Operating Procedure (SOP) orchestration for agents. It integrates toolkits, code libraries, knowledge bases, and sandbox environments for rapid construction of complex Multi-Agent interactive applications. The framework enables efficient execution and handling of multi-layered and multi-dimensional tasks.

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.

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.

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.

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.

The llms.txt hub is a centralized repository for llms.txt implementations and resources, facilitating interactions between LLM-powered tools and services with documentation and codebases. It standardizes documentation access, enhances AI model interpretation, improves AI response accuracy, and sets boundaries for AI content interaction across various projects and platforms.

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.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.