Hands‑On Review of OpenManus: An Open‑Source AI Agent Framework

Overview

OpenManus is an open‑source AI agent framework that reproduces the core functionality of the commercial Manus product. It can be run locally under the MIT license, eliminating the need for invitation codes or subscriptions and improving data privacy.

Project Structure

The framework consists of four core components:

Agent : classes inheriting from BaseAgent that execute tasks.

Tools : modular utilities that agents can invoke.

LLM Integration : abstraction layer for communicating with large language models.

Configuration System : manages framework settings.

Agent System

Agents follow an object‑oriented inheritance hierarchy. The key class that enables tool usage is ToolCallAgent . Primary agent types are:

BaseAgent : manages state and memory.

ReActAgent : implements a think‑act loop.

ToolCallAgent : processes tool calls based on LLM decisions.

Manus : the default general‑purpose agent used in standard mode.

BrowserAgent : specialized for browser interactions.

Manus runs a 20‑step think‑act cycle:

Agent asks the LLM to think (decide what to do).

LLM suggests a tool call.

Agent executes the tool and observes the result.

The loop repeats until the task completes or the maximum step count is reached.

Tool System

All tools inherit from BaseTool and are organized by category. The Manus agent includes five built‑in tools:

PythonExecute : runs Python code.

BrowserUseTool : controls a browser for navigation and interaction.

StrReplaceEditor : performs file operations.

AskHuman : enables user interaction.

Terminate : ends the session.

Usage Example

The following script starts a Manus agent in standard mode and processes a user prompt:

import asyncio
from app.agent.manus import Manus
from app.logger import logger

async def main():
    agent = await Manus.create()
    try:
        prompt = input("Enter your prompt: ")
        if not prompt.strip():
            logger.warning("Empty prompt provided.")
            return
        logger.warning("Processing your request...")
        await agent.run(prompt)
        logger.info("Request processing completed.")
    except KeyboardInterrupt:
        logger.warning("Operation interrupted.")
    finally:
        await agent.cleanup()

if __name__ == "__main__":
    asyncio.run(main())

Example scenario: the user asks for a three‑day travel itinerary for Beijing. The interaction proceeds as:

Agent calls the LLM to think about the request.

LLM suggests using the browser_use tool.

Agent executes the tool, retrieves information, and iterates through the think‑act loop.

After the loop finishes, the agent outputs a detailed itinerary with sites, durations, ticket prices, and highlights.

### Day 1: Historical and Cultural Exploration
1. Tiantan (Temple of Heaven) – Duration: 2‑3 hours, Ticket: ¥15 (basic) or ¥34 (combo), Highlights: Largest sacrificial building complex.
2. Beihai Park – Imperial garden with lake.
3. Prince Gong's Mansion – Well‑preserved Qing‑Dynasty mansion.
4. Shichahai – Scenic area with lakes and hutongs.
5. Nanluoguxiang – Lively alley with shops and cafes.
---
### Day 2: Iconic Landmarks and Shopping
1. Tiananmen Square – World’s largest public square.
2. Forbidden City – Imperial palace of the Ming and Qing dynasties.
3. Jingshan Park – Panoramic views of the Forbidden City.
4. Wangfujing Street – Bustling shopping street.
---
### Day 3: Royal Gardens and Modern Landmarks
1. Summer Palace – Imperial garden with Kunming Lake.
2. Old Summer Palace (Yuanmingyuan) – Ruins with mixed Chinese‑Western architecture.
3. Olympic Park – Bird's Nest and Water Cube.

Alibaba Cloud Deployment

One‑click deployment integrates OpenManus with Alibaba Cloud Function Compute and the Bailei large‑model service. Deployment steps:

Apply for a Bailei API‑KEY on the Alibaba Cloud model service console.

Deploy the Function Compute project template, which redirects to an access‑control authorization page.

Authorize the application, return to the console, and complete the deployment.

Access the deployed application via the provided URL, e.g., https://developer.aliyun.com/topic/tech-solution/open-manus.

Verification: visit the URL, submit a sample query such as “today’s AI hotspot news,” and observe the AI assistant’s response.