Awesome GitHub RepositoriesAgent-Specific Query Routing

This project provides a dockerized AI workflow stack and orchestration templates for deploying a self-hosted AI environment. It establishes a localized infrastructure for building autonomous agents and model chains that process private data on-premises without external cloud dependencies. The environment is designed to support autonomous agent development, allowing models to dynamically select tools, execute shell commands, and interact with local file systems. It includes integrated vector database support to enable retrieval augmented generation and private document analysis. The stack cov

Omi is an open-source wearable AI platform that captures audio and screen data to provide real-time conversational assistance and memory. It integrates a wearable hardware development kit with a vector memory database and large language model capabilities to create a persistent digital record of user interactions. The platform is distinguished by its BLE audio streaming pipeline, which transmits raw audio from wearable hardware for real-time transcription and speaker identification. It utilizes a plugin-based agent tool framework that allows AI assistants to autonomously invoke custom functio

XianyuAutoAgent is a multi-agent orchestration framework and large language model chatbot designed to automate customer service and sales interactions on a marketplace platform. It functions as a system of specialized AI entities, including context-aware conversational agents and automated price negotiation bots, to manage peer-to-peer conversational commerce. The framework distinguishes itself through an intent-based routing mechanism that dispatches queries to specialized agents and utilizes a multi-expert collaborative decision process to determine response strategies. It features dedicate

Agent Squad is a multi-agent system orchestrator and language model agent orchestration framework. It serves as an AI workflow automation engine and tool integration layer designed to coordinate teams of specialized agents to solve complex tasks through routing, parallel execution, and state management. The project is distinguished by its ability to dynamically compose purpose-specific agents on-demand and route requests based on intent, language, or domain expertise. It supports advanced coordination patterns, including parallel subtask distribution, sequential task pipelines, and the abilit

Genkit هو إطار عمل لتطبيقات النماذج اللغوية الكبيرة (LLM) ومجموعة أدوات مطوري الذكاء الاصطناعي التوليدي المصممة لبناء تطبيقات ذكاء اصطناعي جاهزة للإنتاج. يعمل كمنسق لسير عمل الذكاء الاصطناعي الذي ينسق استدعاءات النماذج واستخدام الأدوات الوكيلة من خلال تدفقات تنفيذ آمنة من حيث النوع (type-safe). يوفر المشروع واجهة نموذج موحدة وبنية إضافات (plugin) لتوحيد الوصول إلى نماذج لغوية كبيرة متنوعة، ومخازن المتجهات، وخلفيات القياس عن بُعد. يتميز بمجموعة مراقبة مخصصة لتتبع خطوات التنفيذ ومجموعة أدوات للمطورين للتوجيه (prompting)، وتصحيح الأخطاء، وتقييم منطق الذكاء الاصطناعي عبر واجهة محلية. يغطي إطار العمل مساحة قدرات واسعة بما في ذلك تنسيق الوكلاء مع استدعاء الأدوات وتفويض الوكلاء الفرعيين، والتوليد المعزز بالاسترجاع (RAG) عبر تكامل قاعدة بيانات المتجهات، وتوليد المخرجات المهيكلة باستخدام التحقق القائم على المخطط (schema). كما يتضمن أنظمة لإدارة الجلسات ذات الحالة، وبث الاستجابات القائم على الأحداث، والقدرة على عرض تدفقات الذكاء الاصطناعي كنقاط نهاية HTTP قابلة للتوسع. يتم دعم التطوير بواسطة واجهة سطر أوامر لتشغيل الدوال وإدارة السجلات.

Plano is an AI agent orchestrator and LLM gateway proxy that unifies access to multiple AI providers through a single interoperable interface. It functions as a model routing engine that decouples applications from specific vendors using semantic aliases, allowing traffic to be shifted between providers without modifying application code. The system distinguishes itself with intent-based agent routing, which directs prompts to specialized agents based on semantic analysis. It features an interceptor-based filter chain system that acts as guardrail middleware to enforce safety policies, rewrit

Koog is an LLM agent framework used to build autonomous entities that execute tool-based workflows. It utilizes a graph-based workflow engine to define agent behaviors and decision paths as a directed graph of nodes and edges. The framework distinguishes itself through a model provider orchestrator that enables dynamic switching, load balancing, and automatic fallbacks between different AI backends. It implements the Model Context Protocol to connect agents to remote tool servers and features a RAG memory system using vector embeddings to maintain long-term conversation context. The project