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Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view
Orchestrator Kit for Agentic Reasoning - OrKa is a modular AI orchestration system that transforms Large Language Models (LLMs) into composable agents capable of reasoning, fact-checking, and constructing answers with transparent traceability.
ISON (Interchange Simple Object Notation) is a text format that is completely language independent but represents data in a way that maximizes token efficiency and minimizes cognitive load for AI systems. These properties make ISON an ideal data interchange format for Agentic AI and LLM workflows.
Ship 10x faster by running multiple Claude Code sub agents in parallel. GitHub-native orchestration for AI coding agents—no conflicts, no complexity, just pure parallelized productivity.
Agent Git: Agent Version Control, Open-Branching, and Reinforcement Learning MDP for Agentic AI. A Standalone Agentic AI Infrastructure Layer for LangGraph Ecosystems
The first 100% file-based Local-First AgenticAI dev "construction yard", with its own memory & context, planning, writing and reviewing your code in safe sandboxes on your own machine.
This project is a multi-agent customer service chatbot designed for an e-commerce platform. The chatbot employ specialized agents handle distinct tasks to ensure efficient and accurate interactions. The chatbot aims to enhance user experience by streamlining order processing, answering FAQs, and providing personalized recommendations.
Agent As Function. CodeAct. FS as World. Actium is a Product-Ready CodeAct Agent Framework that lets you define intelligent agents as simple functions. With Skills that auto-discover through the file system, agents explore and use capabilities just like human developers do.
MAPLE - Production-ready multi agent communication protocol with integrated resource management, type-safe error handling, secure link identification, and distributed state synchronization.
🕵️ AI-powered root cause analysis for containerized environments. Hypothesis-driven debugging using LLMs + deterministic probes. Investigate Docker failures like an experienced engineer—systematically, explainably, evidence-based.
🤖 An autonomous multi-agent travel assistant built with CrewAI, Streamlit and Python. Features a resilient 5-Tier Hybrid LLM Architecture (orchestrating Groq, Google Gemini, and local Ollama models) to generate fail-safe, detailed travel itineraries and booking logistic