AutoAgent - An AI agent framework launched by the University of Hong Kong, enabling the creation of intelligent assistants with zero code.

What is AutoAgent?

AutoAgent is a no-code, automated LLM (Learning Modeling) agent framework developed by the University of Hong Kong. Based on natural language interaction, it allows users to create intelligent assistants without programming, suitable for scenarios such as intelligent search, data analysis, and report generation. AutoAgent's core functionality includes three usage modes: user mode, agent editor, and workflow editor, catering to different user needs. AutoAgent supports multiple LLM models, is easy to install and deploy, and provides Docker support. AutoAgent performs excellently in the GAIA benchmark and is an open-source alternative to Manus and Deep Research.

AutoAgent's main functions

• Three usage modes:
  • User ModeUsers can directly experience intelligent web search, data analysis, information processing, and other functions without any configuration.
  • Agent EditorConfigure the AI assistant based on dialogue, adjust parameters, instructions and task logic, without writing code.
  • Workflow EditorUse natural language to describe tasks, create automated workflows, and enable AI agents to perform complex tasks.
• Dual Interaction Mode:
  • ReAct modeAI dynamically adjusts strategies, making it suitable for complex reasoning tasks.
  • Function call patternAI calls APIs or databases to complete specific tasks, such as online searches and data queries.
• Built-in self-managed vector database:
  • Long-term AI memoryAI can remember past interactions, improving its ability to understand context.
  • Knowledge-enhanced retrieval (RAG)AI retrieves information from local databases, improving accuracy.
  • Data-driven AIAI agents can learn and optimize their strategies to improve their task processing capabilities.

AutoAgent's technical principles

• Natural Language-Driven Multi-Agent ConstructionAgent Profiling: The Agent analyzes user needs and generates a structured agent form. Tool Editor: The Agent creates tools based on requirements and supports third-party API integration. Agent Editor: The Agent creates agents based on the form and supports multi-agent collaboration.
• LLM Power Action EngineDirect Tool-Use Paradigm directly uses LLM's tool usage capabilities to generate the next action. Transformed Tool-Use Paradigm transforms tool usage into a structured XML code generation task, which is then parsed and executed.
• Self-managed file systemVector databases convert files into vector databases, supporting efficient retrieval. The tool automatically stores files into a vector database, supporting multiple file formats.
• Self-developed agency customizationTransform natural language requirements into executable agents and tools. Generate efficient agents and workflows based on self-tuning and optimization.
• Multi-agent collaborationThe Orchestrator agent breaks down tasks and assigns them to Worker agents. It enables flexible agent collaboration based on event listening and triggering mechanisms.
• Technical ArchitectureAgentic System Utilities provides a basic multi-agent architecture. The LLM-powered action engine supports multiple LLM providers and dynamically generates actions. A self-managed file system manages user multimodal data and supports efficient retrieval. Agents are generated and optimized using natural language.

AutoAgent project address

• Project official website:https://autoagent-ai.github.io/
• GitHub repository:https://github.com/HKUDS/AutoAgent
• arXiv technical paper:https://arxiv.org/pdf/2502.05957

Application scenarios of AutoAgent

• Intelligent web searchIt enables users to independently search for information on the internet, filter and summarize key content, and help them quickly obtain the information they need.
• Data Analysis and ProcessingIt parses data files in various formats, automatically organizes them, and generates detailed data analysis reports.
• Automatic report generationBased on user needs or data input, it generates professional-grade reports, such as market research or industry analysis.
• Intelligent AI AgentIndependently perform various tasks, such as searching for information, sending emails, and processing documents, to improve work efficiency.
• AI office assistantAutomatically organizes schedules, emails, and task lists, provides smart reminders, and optimizes work processes.