ask-claude uses Zellij and llm to give you an AI helper in your terminal that can see what you are doing.

ask.sh

#!/bin/bash

# Check for newer version at gist
local_hash=$(tr -d '\r\n' < "$0" | md5sum | cut -d ' ' -f 1)
remote_hash=$(curl -s https://gist.githubusercontent.com/NigelThorne/385ebbbe2060cc16414ced49e853f12f/raw/ | tr -d '\r\n' | md5sum | cut -d ' ' -f 1)

if [ "$local_hash" != "$remote_hash" ]; then
    echo "A newer version is available at: https://gist.github.com/NigelThorne/385ebbbe2060cc16414ced49e853f12f" >&2
fi

##########
# This script helps you get AI assistance for code and text analysis.
#
# Two ways to use it:
# 1. Pipe input directly:
#    echo "some text" | ask claude "analyze this"
#
# 2. Use your current zellij terminal screen:
#    ask claude "analyze what's on my screen"
#    (Defaults to last 300 lines, use -n <number> to adjust)
#
# The script will send your context and question to Claude and return the response.
#
# Options:
#   -n <number>    Number of lines to include from screen (default: 300)
#
##########

##########
# Example use:
#
# rewrite my last git commit comment
# git diff main | ask-claude "write a git commit comment for this change. It can be multiline. I will pipe your response directly into my git commit -m command" | git commit --amend -F -
#########

# Model mapping using case statement instead of associative array
get_model_name() {
    case "$1" in
        "sonnet") echo "claude-3.5-sonnet" ;;
        "haiku") echo "claude-3.5-haiku" ;;
        "claude") echo "claude-3.5-sonnet" ;;
        "quen") echo "qwen2.5-coder:32b" ;;
        "local") echo "llama2" ;;
        *) echo "$1" ;;
    esac
}

# Default model and number of lines
model=${1:-claude}
model_name=$(get_model_name "$model")
shift
num_lines=300

# Parse command line options
while getopts "n:" opt; do
  case $opt in
    n)
      num_lines=$OPTARG
      shift 2
      ;;
    *)
      ;;
  esac
done

# Check if we're getting input from pipe
if [ -p /dev/stdin ]; then
    # Read from pipe
    log=$(cat)
else
    # Get from zellij
    zellij action dump-screen /tmp/screen-dump.txt 2>/dev/null
    if [ $? -ne 0 ]; then
        echo "You need to be in a zellij session"
        exit 1
    fi
    log=$(cat /tmp/screen-dump.txt | tail -n $num_lines)
fi

# Get the user's prompt from command line arguments
user_prompt="$*"

# Make sure we have a prompt
if [ -z "$user_prompt" ]; then
    echo "Error: Please provide a prompt"
    exit 1
fi

# Combine the context and prompt
if [ "$num_lines" -eq 0 ]; then
  full_prompt=$user_prompt
else
  full_prompt="Context:
------
$log
------

User question: $user_prompt"
fi

# Send to llm with specified model
echo "$full_prompt" | llm -m $model_name