PearBerry Documentation

Comprehensive guides and reference material for the PearBerry CLI tool

Installation

PearBerry CLI can be installed using several methods. Choose the one that best fits your environment.

NPM Installation

The recommended way to install PearBerry is via npm:

npm install -g pearberry-cli

This makes the pearberry command available globally on your system.

Binary Installation

Alternatively, you can download precompiled binaries from our GitHub releases page:

  1. Download the appropriate binary for your platform (Windows, macOS, or Linux)
  2. Extract the archive to a directory of your choice
  3. Add the binary to your PATH or move it to a directory already in your PATH

Verifying Installation

To verify that PearBerry was installed correctly, run:

pearberry --version

You should see the current version number displayed in your terminal.


Basic Usage

Once PearBerry is installed, you can start using it with these basic commands:

1. Install a Model

pearberry install deepseek-7b

This downloads and installs the specified model (in this case, DeepSeek Coder 7B).

2. Run the Model

pearberry run

This starts the LLM server with the default model. You can specify a model with --model flag.

3. Chat with the Model

pearberry chat

This opens an interactive chat interface to converse with the running model.

Note: You must have a model running with pearberry run before using the chat command.


Configuration

PearBerry can be configured through the config.yaml file located at ~/.pearberry/config.yaml.

Example Configuration File

# PearBerry Configuration File # Model settings models: default: "deepseek-7b" storage_path: "~/pearberry/models" # Runtime settings runtime: threads: 4 context_length: 4096 temperature: 0.7 # Interface settings interface: theme: "dark" save_history: true history_file: "~/pearberry/history.json"

Configuration Commands

You can also modify configuration using the config command:

pearberry config set runtime.threads 8

View current configuration:

pearberry config get

This documentation is a work in progress. Check back for updates!

Ready to Start Using PearBerry?

Download PearBerry CLI now and start exploring the power of local LLMs.