LangManus: A domestic manufacturer copied Manus and made it open source
A domestic giant replicated Manus, a new breakthrough in open source AI Agent technology.
Core content:
1. Introduction to LangManus' community-driven AI automation framework
2. Analysis of LangManus' core features and project architecture
3. The rise of open source alternatives and the Manus craze
In the field of AI Agent, the emergence of Manus has caused a sensation. This general AI Agent has quickly become the focus of the AI field with its ability to autonomously perform complex tasks. As Manus became popular, the open source community also took quick action. Today, another project, LangManus, was discovered, which aims to provide a community-driven AI automation framework to enable more developers and users to access and utilize advanced AI Agent technology.
LangManus Introduction
LangManus is a community-driven AI automation framework built on top of the outstanding work of the open source community. Our goal is to combine language models with specialized tools such as web search, crawlers, and Python code execution .
Core Features
LangManus implements a hierarchical multi-agent system where a supervisor coordinates specialized agents to accomplish complex tasks:
1. Core Competencies
- ? LLM integration: support for open source models such as Qwen
- API interface compatible with OpenAI
- Multi-level LLM system to adapt to tasks of different complexity
2. Tools and Integrations
- ? Search and Retrieval: Web search via the Tavily API
- Neural search using Jina
- Advanced content extraction capabilities
3. Develop features
- ? Python integration: built-in Python REPL
- Code execution environment
- Use uv for package management
4. Workflow Management
- ? Visualization and control: workflow graph visualization
- Multi-agent coordination
- Task delegation and monitoring
Project Architecture
The LangManus system consists of the following agents working together:
1. Coordinator - the entry point that handles initial interactions and routes tasks
2. Planner - Analyzes tasks and creates execution strategies
3. Supervisor - Oversees and manages the execution of other agents
4. Researcher – collects and analyzes information
5. Coder - handles code generation and modification
6. Browser - performs web browsing and information retrieval
7. Reporter - Generates reports and summaries of workflow results
The rise of open source alternatives
As Manus became popular, the open source community quickly took action and created multiple open source alternatives:
OpenManus
Created by core members of the MetaGPT team in just 3 hours, OpenManus is a simplified Manus implementation that can be used without an invitation code. The project quickly gained more than 3,000 stars on GitHub.
OWL (CAMEL-AI)
OWL (Optimized Workforce Learning) launched by the CAMEL-AI team is another open source project worth paying attention to. It is a cutting-edge framework for multi-agent collaboration that pushes the boundaries of task automation. OWL achieved an average score of 58.18 in the GAIA benchmark, ranking first among open source frameworks.
In the context of the AI Agent craze sparked by Manus, LangManus and other open source projects such as OpenManus and OWL provide developers and users with opportunities to access advanced AI agent technology. These projects not only demonstrate the innovation and responsiveness of the open source community, but also make important contributions to the popularization and development of AI agent technology.
