Preeti
The article discusses the use of large language models (LLMs) and other AI tools for automating tasks, particularly focusing on code or command generation. It warns that giving an LLM full access to a user’s terminal may result in data loss or system corruption. The author explores the effectiveness of LLMs in completing tasks when provided full access to the terminal. They mention the need for an ideal model with specific characteristics, such as a large context window, speed, and internet search ability. The author uses Cohere’s Command-R-Plus model, which offers a 128k token context limit and internet capabilities.
The goal is to have the LLM interact with the terminal like a human user, running commands, fixing errors, and completing tasks. The author creates a Python program to facilitate communication with the LLM and tests its performance with various tasks. Results show mixed outcomes, with the LLM successfully completing some tasks but struggling with more complex, multi-step tasks like installing software.
Overall, the author concludes that while LLMs can handle simple tasks, they are not yet ready to fully control a terminal for more complicated tasks. The article invites suggestions and improvements to the code on the GitHub repository for further development.
Source link
Source link: https://medium.com/@m5kro/giving-ai-access-to-the-terminal-d57874191e81?source=rss——llm-5
GIPHY App Key not set. Please check settings