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AI Agent Marketplace and Directory helps to list all AI Agents in Various Industry and Applications, such as Autonomous Agent, GUI Agent, Productivity Agent. You can find your desired AI Agents by using the AI Agent search engine also.

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Qwen Coding Agent offers an advanced framework for developing applications utilizing large language models (LLMs), enhancing capabilities such as instruction following, tool usage, planning, and memory. Introduction Qwen Coding Agent provides a robust platform for building LLM applications, leveraging the advanced features of Qwen models (version 2.0 and above). It facilitates the development of i

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Qwen Coding Agent offers an advanced framework for developing applications utilizing large language models (LLMs), enhancing capabilities such as instruction following, tool usage, planning, and memory. Introduction Qwen Coding Agent provides a robust platform for building LLM applications, leveraging the advanced features of Qwen models (version 2.0 and above). It facilitates the development of i

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The Open-Source AgentOS Join our growing community of over 20,000 agent builders Build production-ready multi-agent systems in minutes, not months. Github Discord Create specialized agents that work together seamlessly. AG2 makes it easy to define roles, configure behaviors, and orchestrate collaboration - all through simple, intuitive code. → Assistant agents for problem-solving → Executor agents

Teneo.AI Open menu Platform Platform Solutions Solutions Developers Developers Learning Hub Learning Hub Partners Partners About Us About Us Contact Contact AI Agent Teneo for Automotive Industry Make Your AI Agents the Smartest 2025 © TENEO.AI ALL RIGHTS RESERVED Unify LLM orchestration, scalable AI agents and enterprise AI solutions into one seamless platform. Teneo empowers adaptive AI to

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In the newly revised second edition of Age of Invisible Machines, renowned tech leader Robb Wilson delivers a startlingly insightful and eye-opening blueprint ...

* * * $11.5M * * * [.873] [.542] [.285] [.557] [.013] [.801] [.798] [.117]️ [.070] [.833] [.984] [.342] [.330] [.103] [.004] [.400] [.087] [.707] [.212] [.616] [.206][.505] [.043] [.245] [.273] [.143] [.095] [.891] [.104] [.784] [.805] [.505] [.891] [.820] [.034] [.381]️ [.679] [.034] [.810] [.707] [.642] [.660] [.790] [.081]️ [.445] [.810] [.322] [.381]️ [.817] [.353] [.663] [.027] [.452] [.045]

Designed with orchestration at it's core, AgentKit enables developers to build, test, and deploy reliable AI applications at scale. With AgentKit, you get: ✨ ...

@step def load_rag_documents dict # Load and chunk documents for RAG pipeline "https://www.zenml.io/" return "chunks" @step(experiment_tracker="mlflow") experiment_tracker="mlflow" "mlflow" def generate_embeddings data: dict dict None # Generate embeddings for RAG pipeline 'chunks' return "embeddings" @step( settings={"resources": ResourceSettings(memory="2Gi") }, settings={"resources": ResourceS

Topics About API Docs Contribute Toggle theme Toggle theme Search... ⌘ Orchestrating Agents: Routines and Handoffs Ilan Bigio(OpenAI) (OpenAI) Oct 10, 2024 Open in Github from openai import OpenAI from openai import OpenAI from pydantic import BaseModel from pydantic import BaseModel from typing import Optional from typing import Optional import json import json client = OpenAI() client = OpenAI

OpenAI Agents SDK Orchestrating multiple agents Intro Quickstart Documentation Agents Running agents Results Streaming Tools Handoffs Tracing Context management Guardrails Orchestrating multiple agents Orchestrating multiple agents Orchestrating via LLM Orchestrating via code Models Configuring the SDK API Reference Agents Agents module Agents Runner Tools Results Streaming events Handoffs

Qwen Coding Agent offers an advanced framework for developing applications utilizing large language models (LLMs), enhancing capabilities such as instruction following, tool usage, planning, and memory. Introduction Qwen Coding Agent provides a robust platform for building LLM applications, leveraging the advanced features of Qwen models (version 2.0 and above). It facilitates the development of i

AG2 Orchestrating agents Home User Guide Basic Concepts Installing AG2 LLM Configuration Conversable Agent Human In The Loop Orchestrating Agents Orchestrations Sequential Chat Nested Chat Swarm Ending A Chat Tools Advanced Concepts Model Providers Reference Agents API References Contributor Guide FAQs Ecosystem 2 weeks ago2025-02-26 2 weeks ago 2 weeks ago 2025-02-26 Previous Next

2024年10月31日 — To get the best results with Swarm, it's important to design your agents with clear and concise roles. Avoid creating agents that try to do too ...

2024年10月22日 — Swarm is used by instantiating a Swarm client which is nothing more than a simple OpenAI client. This client uses the run() function which is ...

— 14 min read — Diving into LlamaIndex AgentWorkflow: A Nearly Perfect Multi-Agent Orchestration Solution. Image by DALL-E-3 Don't Miss the Latest Practices on D.L.F Get practical, cutting-edge AI and data science insights for all levels. Subscribe now to stay ahead! Subscribe No spam. Unsubscribe anytime. Data Leads Future Peng Qian Data Leads Future Peng Qian Illustrations of various methods in

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Log in Menu Search Cart Search Home Business Information Systems Conference paper pp 103–117 Business Information Systems (BIS 2020) ORCID: orcid.org/0000-0001-5754-3207 ORCID: Part of the book series: Accesses Log in via an institution Springer+ Basic Subscribe now Chapter © 2021 Article Open access 01 June 2023 Chapter © 2023 Authors Jan Felix Zolitschka PubMed Google Scholar : https://

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Ask or search... More 0.75.0 ZenML Documentation ZenML API Docs SDK Docs 0.75.0 Introduction Installation Core concepts System Architecture Deploying ZenML ZenML Pro Starter guide Production guide LLMOps guide Manage your ZenML server Connect to a server Project Setup and Management Set up a ZenML project Collaborate with your team Interact with secrets Pipeline Development Bui

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