OpenManus setup with uv and comparison with Manus

This walkthrough presents OpenManus as an open source AI agent framework and compares it with hosted Manus. The speaker describes a loop that breaks a goal into steps, selects tools such as a browser or code interpreter, checks results, and decides what to do next. In the version covered, OpenManus runs in a terminal without a graphical interface.

The setup uses uv to create a virtual environment and install Python dependencies. It covers Mac and Linux installation and Windows environment activation. Browser control requires an optional Playwright installation. The model settings go in config.toml, with GPT-4o through the OpenAI API as the default. The speaker also discusses changing providers and using Ollama to run models locally.

The standard entry point is python main.py. Separate commands cover MCP tools and a multi-agent workflow that the speaker describes as unstable. For the test, the presenter requests an HTML habit tracker and reports that the agent writes a file with embedded CSS and JavaScript, saves it, and opens it to check its work in about four or five minutes. The result is described as imperfect.

The speaker finds OpenManus slower and less polished than Manus. Local execution still sends requests to the selected model provider when using a remote API. The stated limitations include repeated loops and API credit consumption, since each step makes an LLM call.