Awesome GitHub RepositoriesAgentic Search Tools

Chroma is a specialized vector database designed to index and retrieve high-dimensional data representations for semantic similarity search. It functions as a comprehensive platform for information retrieval, enabling the storage and management of unstructured documents alongside structured metadata. By mapping data into numerical representations, the system facilitates rapid similarity lookups across large datasets. The platform distinguishes itself through a hybrid search infrastructure that combines dense vector embeddings with sparse keyword and regular expression matching to balance sema

Weaviate is an AI-native vector database designed to store and index high-dimensional vector embeddings alongside traditional data objects. It serves as a backend infrastructure for retrieval-augmented generation, enabling applications to ground language model responses in private, context-aware data. The platform distinguishes itself by combining vector similarity search with traditional keyword filtering through a hybrid storage architecture. It integrates directly with external machine learning models to automate the generation of embeddings and perform complex inference tasks during inges

Ragas is an evaluation framework designed to measure the performance of retrieval-augmented generation pipelines and autonomous agent workflows. It provides a comprehensive suite of tools for benchmarking system outputs, utilizing language models as automated judges to score performance against defined rubrics and reference data. By standardizing inputs, retrieved contexts, and generated responses into a unified schema, the project enables consistent analysis across complex AI applications. The framework distinguishes itself through its ability to generate synthetic test datasets from existin

Civitai is a platform for generative media creation and AI model distribution. It provides a centralized service for producing images, videos, audio, and music, while serving as a repository where users can share, discover, and browse custom model weights and fine-tuned adaptations. The platform distinguishes itself through a provider-agnostic orchestration layer that manages multi-step generation pipelines and complex workflows across different backends. It integrates with autonomous AI agents and editors via the Model Context Protocol, allowing external tools to access generation pipelines

Airweave is a unified AI knowledge base platform that syncs data from external APIs into a searchable layer for retrieval-augmented generation. It provides a pre-built data connector library and a framework for building custom connectors, enabling the extraction, transformation, and synchronization of structured and unstructured data from SaaS applications. The platform includes a hybrid vector retrieval system that combines semantic, neural, and keyword search strategies to deliver grounded context for AI agents. The platform distinguishes itself through an agentic search engine that iterati

This project is a conversational assistant and retrieval-augmented generation system designed to provide technical answers from official documentation and support knowledge bases. It implements a retrieval architecture that routes queries through specialized tools and utilizes a model abstraction layer to switch between different chat and embedding providers without modifying core integration code. The system employs a graph-based state machine for durable agent execution, enabling state persistence and human-in-the-loop interactions. It features an agentic middleware framework that allows fo

PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

Kiln ist eine LLM-Entwicklungs-Workbench und ein Evaluierungs-Framework, das für das Design, das Testen und die Optimierung von Prompts und KI-Agenten entwickelt wurde. Es fungiert als Multi-Agenten-Orchestrator und RAG-Optimierungstool und bietet eine visuelle Schnittstelle für die iterative Entwicklung von KI-Systemen. Das Projekt zeichnet sich durch eine umfassende Fine-Tuning-Pipeline aus, die Zero-Code-Modelltraining und Reasoning-Destillation unterstützt. Es ermöglicht die Erstellung hierarchischer Multi-Agenten-Systeme, in denen spezialisierte Akteure über Tool-Calling koordinieren, und implementiert einen Model Context Protocol-Server, um diese Agenten und Suchfunktionen als standardisierte Tools für externe Clients bereitzustellen. Die Plattform deckt ein breites Spektrum an Fähigkeiten ab, einschließlich automatisierter KI-Jury-Bewertung zur Qualitätssicherung, synthetischer Datengenerierung für Training und Evaluierung sowie hybrider Vektor-Keyword-Suche zur Erdung von Modellantworten. Sie bietet zudem Tools für Prompt-Evolution, Trace-Auditing und die Verwaltung kollaborativer Datensätze via Git-Integration. Die Workbench ist über eine selbst-hostbare REST-API und eine dedizierte Python-Bibliothek für die programmatische Workflow-Ausführung zugänglich.

Oasis ist ein LLM-gestützter Multi-Agenten-Sozialsimulator und ein Forschungstool zur Untersuchung synthetischer sozialer Phänomene. Es fungiert als Plattform für synthetische soziale Netzwerke, die die Infrastruktur sozialer Seiten – einschließlich Benutzerprofilen, Follow-Beziehungen und Mechanismen zur Inhaltsentdeckung – repliziert, um menschenähnliches soziales Verhalten in großem Maßstab zu modellieren. Das Framework orchestriert große Agentenpopulationen und unterstützt bis zu eine Million autonome Agenten. Es zeichnet sich dadurch aus, dass es Ausgaben von Sprachmodellen durch einen Tool-Calling-Orchestrator in konkrete soziale Aktionen und externe Tool-Ausführungen übersetzt, während es eine zeitbeschleunigte Simulationsuhr verwendet, um Ereignissequenzen von der Echtzeit zu entkoppeln. Das System deckt breite Funktionsbereiche ab, darunter die Modellierung sozialer Plattformen, graphbasierte Kartierung sozialer Netzwerke und algorithmische Inhaltsempfehlungen. Es bietet spezialisierte Forschungstools für die Modellierung von Informationsverbreitung, die Analyse von Gruppenpolarisierung und Agenten-Interviews, unterstützt durch persistentes Aktivitäts-Logging für retrospektive Datenanalysen. Das Projekt ist in Python implementiert.

Youtu Agent is an open-source framework for building, running, and evaluating autonomous agents powered by large language models. It provides the core infrastructure for creating agents that follow reasoning loops, use toolkits, and coordinate with other agents to solve complex tasks, all managed through YAML-driven configuration files. The framework distinguishes itself through its support for multi-agent orchestration, where a planner agent decomposes tasks and coordinates specialized worker agents, and through its integration with the Model Context Protocol for connecting to external toolk

This repository is a collection of node-based pipeline configurations, examples, and templates for generating AI media. It provides a workflow library and a curated gallery of blueprints designed for creating images, videos, and 3D assets using diffusion models. The project specifically offers a set of pre-configured node graphs for implementing advanced image generation and refinement techniques, with a focus on Stable Diffusion workflows. These examples demonstrate how to interconnect processing nodes to define complex generative logic without writing code. The available templates cover a

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

This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing