Step-by-Step Guide for Local LLM API Project in Python

A detailed guide has been published on how to set up a local large language model (LLM) API using Python. This project allows users to send prompts to an LLM downloaded on their own machine and receive responses, similar to ChatGPT, but entirely local.

The tutorial presumes that users have Python version 3.9 or later installed and possess a basic to intermediate understanding of the Python programming language. It is designed for implementation in an integrated development environment (IDE) like Visual Studio Code, emphasizing that this is not suitable for online notebook environments as it requires local model downloads.

Users are instructed to download a version of Ollama from its website, which enables the local use of an LLM known as Llama 3. The initial download may take some time, influenced by the user's internet connection speed. Once the model is downloaded, a conversation assistant will launch in the terminal.

The guide details the creation of a project folder named "local-llm-api" and the addition of two files: "main.py" and "requirements.txt". It recommends setting up a virtual environment to manage dependencies effectively and prevent conflicts.

Upon completion of the setup, users can run their Python file and access the REST server via a local URL. The interface allows users to prompt the LLM by entering queries in a specific JSON-like format. The guide concludes with tips for advanced users on potential improvements, such as integrating a frontend that utilizes the FastAPI-based API.