LM_Studio_Local_Server

Welcome to the LM Studio Local Server setup guide. This guide will walk you through the process of running a local server with LM Studio, enabling you to use Hugging Face models on your PC without an internet connection and without needing an API key. The repository includes six Python (.py) files. For comprehensive functionality, focus on lmst_inline.py and lmst_ext.py. You only need to run one of these files to start the local server.

Usage Note:

Please note that the method for starting the local server provided in this repository may not work on all systems or operating systems due to variations in dependencies and system configurations. Additionally, changes or updates to the OpenAI Whisper and or Openai libraries may affect the functionality of the code provided here.Users are encouraged to be aware of potential issues and to consult their GPT (Generative Pre-trained Transformer) for assistance when encountering problems. The initial code in this repository was developed with the help of ChatGPT, and users are encouraged to utilize similar resources for troubleshooting and finding solutions to any issues they may encounter.Furthermore, it's important to regularly check and update the requirements.txt file to ensure compatibility with different versions of dependencies.

The code provided by LM Studio may in fact work for some users and users are encouraged to try that as the first option.

Getting Started

Here's how to get the project up and running on your local machine.

Prerequisites

• Anaconda: Download it from Anaconda's official site.
• LM Studio: Available at LM Studio's website.

Setting Up Your Python Environment

1. Install Anaconda: Follow the installation instructions for your OS from the Anaconda website.

2. Create a New Conda Environment (recommended):

   conda create -n myenv python=3.11

   Replace myenv with a name of your choice for the environment.

3. Activate the Environment:

   conda activate myenv

Clone the Repository

Clone the LM_Studio_Local_Server repository:

git clone https://github.com/VideotronicMaker/LM_Studio_Local_Server.git

4. Install Required Packages: Navigate to the cloned directory and install the necessary packages:

   pip install -r requirements.txt

Running the Project

• LLM Python Script (lmst_ext.py): Main script for the language model.
• System Messages File (system_message.txt): Contains custom instructions or system messages for the model.

To run the script, execute this command in your terminal:

python lmst_ext.py

Ensure system_message.txt is in the same directory as lmst_ext.py, or modify the script to locate it.

Development Environment Setup

For detailed instructions on setting up and using Visual Studio Code with this project, please see VSCode Instructions.

Need More Help?

If you're new to using command line interfaces for tasks like navigating directories, creating folders, or managing Python environments, resources like ChatGPT or Gemini Pro can provide detailed, step-by-step guidance.