AiPy

AiPy is a product we developed based on a new paradigm, Python-Use, to enable more universal and rapid utilization of large models for various tasks. The traditional classic paradigm for large model AI Agents involves developing a large number of tool agents and then relying on their collaboration to accomplish various tasks. This approach depends on the development, deployment, and installation of more and more agents. However, from a certain perspective, developing and deploying more agents actually limits the full potential of large models. In contrast, AiPy (Python-Use), a new paradigm, takes a different approach: it's a way of "enabling AI to use Python and Python to use AI." This means that the large model understands and breaks down user tasks, then achieves automatic coding and code execution through API Calling and Packages Calling. It can also continuously improve and iterate through a feedback mechanism, ultimately enabling AI to interact with the environment and complete tasks. Therefore, we propose the concept: "The real general AI Agent is NO Agents!" AiPy (Python-Use) implements the new paradigm of "No Agents, Code is Agent." Python uses data, Python uses computers, Python uses the network, Python uses the Internet of Things, Python uses everything, ultimately achieving true AI Think Do! The specific code related to Python-Use has already been open-sourced: https://github.com/knownsec/aipyapp Based on this concept, we believe this is the biggest difference compared to Manus, MCP, etc.! For users: The biggest difference between AiPy and Manus is that AiPy itself is open-source and free. Users only need to bear the cost of tokens for calling APIs of large models (of course, you can also use free large models). Because it doesn't require the invocation of numerous agents, AiPy also consumes relatively fewer tokens for the same task. Another major advantage is that AiPy supports local deployment, eliminating the need for users to upload their sensitive data and documents to the cloud. This is because AiPy is only responsible for the corresponding code generation for the task, and all data processing is done locally, offering a secure and reliable advantage for handling very large files and sensitive data. The biggest advantage of AiPy compared to MCP Server is that users don't need to rely on various custom-developed MCP Servers for different services, nor do they need to deploy, install, or use them. They also don't need to worry about the security risks posed by unreliable MCP Server providers. AiPy can achieve the invocation of various APIs and accomplish diverse functions through real-time coding. You can see the examples shown above or experience the power of AiPy for yourselves. In summary, AiPy offers multiple deployment options, is no longer limited by the various restrictions of cloud-based hosts, and doesn't require the development, downloading, installation, or complex configuration of various tools. All you need to do is converse with the large model.