Introduction

AIChat is a versatile tool that allows you to interact with various Language Learning Models (LLMs) directly from your terminal. It’s designed to be both user-friendly for beginners and powerful enough for advanced users who want to automate workflows using macros and shell integration.

Terminal Setup

To begin, you’ll first need to install AIChat, the exact process for which will depend on your operating system. Once installed, running aichat for the first time will prompt you to create a configuration file. This file, typically located at ~/.config/aichat/config.yaml on Linux, C:\Users\Alice\AppData\Roaming\aichat\config.yaml on Windows, or /Users/Alice/Library/Application Support/aichat/config.yaml on macOS, stores your API key and other settings. You’ll be asked to specify the platform and API key during this initial setup.

Environment Management

AIChat also supports the use of environment variables which are useful for sensitive information such as API keys, or model paths, it’s essential to keep them out of configuration files.

AIChat REPL

The heart of AIChat is its Read-Eval-Print Loop (REPL), which provides an interactive environment for engaging with LLMs. Here’s a simplified view of the REPL workflow:

REPL Command Workflow

• Command Input (e.g., .model gpt-4o) ⬇️
• Processing (AIChat interprets the command and config settings) ⬇️
• Output Generation (Command response or AI output) ⬇️
• Optional Continuation (e.g., .continue, .regenerate)

Here are some basic examples of REPL usage:

• aichat: Starts the REPL.
• aichat Tell a joke: Sends a simple query to the LLM.
• aichat -e install nvim: Executes a command in the shell using AIChat to create the command.
• aichat -c fibonacci in js: Generates code output.
• aichat -m openai:gpt-4o: Selects the LLM to use.
• aichat -r role1: Uses the role role1.
• aichat -s: Starts a temporary session.
• aichat -s session1: Uses session session1.
• aichat -a agent1: Uses agent agent1.
• aichat --rag rag1: Uses RAG rag1.
• aichat --info: Shows system information.
• aichat -r role1 --info: Shows role info.
• aichat -s session1 --info: Shows session info.
• aichat -a agent1 --info: Shows agent info.
• aichat --rag rag1 --info: Shows RAG info.

Beginner Tips:

• 💡 Start simple: Enter aichat Tell me a joke to experience the magic!
• 💡 Use aichat --info to explore your configuration and capabilities.

Macros

Macros are a powerful feature allowing you to automate sequences of REPL commands. These are defined in YAML files located in the <aichat-config-dir>/macros/ directory. For example, a macro to generate a commit message could be defined in a generate-commit-message.yaml file like this:

steps:
  - .file `git diff` -- generate git commit message

You can then execute it with aichat --macro generate-commit-message.

Imagine chaining .file and .prompt commands to write and deploy a script:

Create a macro in <aichat-config-dir>/macros/ like this:

steps:
  - .file script.py -- improve code style
  - .file script.py -- deploy changes

Run it with aichat --macro deploy-script for instant automation.

Function Calling

AIChat supports function calling, enabling it to interact with external tools. You can configure tools in your configuration file using mapping_tools. For example:

function_calling: true
mapping_tools:
  fs: 'fs_cat,fs_ls,fs_mkdir,fs_rm,fs_write'
use_tools: null

And then use the fs tool group by setting use_tools: fs.

Shell Assistant

AIChat can act as a shell assistant, generating commands based on your natural language input. It’s aware of the OS and shell you are using, and will generate appropriate commands for your system.

Shell Integration and Autocompletion

AIChat also offers shell integration and autocompletion, allowing you to use alt+e to get intelligent completions in your terminal, and suggesting commands, options, and filenames as you type, enhancing your workflow. Here’s how to set up shell integration:

Shell Integration Steps

1. Install AIChat binary.
2. Add aichat to PATH.
3. Source completion scripts based on shell type:

   source <(aichat completion bash)
   

Integration scripts are available for various shells such as bash, zsh, PowerShell, fish, and nushell.

Generate Code & Use Files

The -c/--code flag will provide pure code output, while the -f/--file can be used to send file contents to LLMs. For example:

• aichat -c fibonacci in js will generate JavaScript code.
• aichat -f data.txt will send the contents of data.txt to the LLM.
• aichat -f image.png ocr will send the image for OCR analysis.

Real-World Use Cases:

Quickly summarize documents with AIChat: Use aichat -f report.txt summarize to get key insights from long files.

ARGC and JQ Enhancements

These enhancements allow for more sophisticated input and output manipulation, allowing AIChat to fit seamlessly into scripting workflows.

Gemini EXP and Ollama Integration

AIChat supports integration with Gemini EXP and alternatives using Ollama, providing greater flexibility in selecting the models you want to use.

Troubleshooting

Here’s a table to help with common issues:

This guide provides a foundation for understanding AIChat. By experimenting and using these features, you can unlock a powerful set of LLM tools from your command line. If you need more specific guidance, don’t hesitate to ask!