feat(ai): make ai mode model-configurable + add --compare for A/B testing
Default the ai mode to qwen2.5-coder:1.5b instead of the hardcoded (and uninstalled) westenfelder/NL2SH, which left ai mode broken. The model is now configurable via SUPERMAN_AI_MODEL / --model, with markdown-fence stripping and a coder-specific prompt wrapper so general coder models emit a single bare one-liner. NL2SH still receives the raw query. Adds --compare to run multiple models side by side (SUPERMAN_AI_COMPARE_MODELS) with timing for benchmarking. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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leetcrypt
@@ -28,9 +28,29 @@ super-man ask "find large files" # ask a question
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super-man task "monitor cpu usage" # describe what you want to do
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super-man category files # browse by category (files/text/network/system)
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super-man explain "tar -czf" # explain what a command does
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super-man ai "count lines in js files" # AI-powered NL2SH model (advanced)
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super-man ai "count lines in js files" # AI bash one-liner via local LLM (advanced)
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```
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### AI mode (local LLM via ollama)
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`ai` generates a bash one-liner from plain English using a local [ollama](https://ollama.com)
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model. The model is configurable, so you can A/B different local LLMs:
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```bash
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super-man ai "find python files modified last week" # default model
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super-man ai --model qwen2.5:3b "count lines in all js files" # override model
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super-man ai --compare "list the 5 largest files" # run several models side by side
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```
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| Env var | Purpose | Default |
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|---------|---------|---------|
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| `SUPERMAN_AI_MODEL` | Default model for `ai` | `qwen2.5-coder:1.5b` |
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| `SUPERMAN_AI_COMPARE_MODELS` | Space-separated list for `--compare` | `qwen2.5-coder:1.5b westenfelder/NL2SH` |
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General coder models (e.g. `qwen2.5-coder`) are prompt-wrapped to emit a single bare
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command; the purpose-built `westenfelder/NL2SH` model receives the raw query. Pull
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either with `ollama pull <model>`.
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`Esc` in the flag browser returns to the command list; `Esc` on the home screen
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exits.
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+125
-36
@@ -41,7 +41,7 @@ show_help() {
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echo -e " ${CYAN}Natural Language Queries:${NC}"
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echo -e " ${GREEN}ask${NC} \"query\" Ask in natural language (database)"
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echo -e " ${GREEN}task${NC} \"description\" Describe what you want to do (database)"
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echo -e " ${GREEN}ai${NC} \"complex query\" AI-powered NL2SH model (advanced) 🤖"
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echo -e " ${GREEN}ai${NC} \"complex query\" AI bash one-liner via local LLM (advanced) 🤖"
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echo ""
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echo -e " ${CYAN}Browse & Explore:${NC}"
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echo -e " ${GREEN}category${NC} NAME Browse by category (files/text/network/system)"
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@@ -77,15 +77,18 @@ show_help() {
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echo -e " ${GREEN}✓${NC} fzf (for interactive mode only)"
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echo ""
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echo -e "${BOLD}${YELLOW}AI MODE${NC} 🤖"
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echo -e " ${GREEN}✓ NL2SH model detected!${NC} Use AI for complex queries:"
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echo -e " Generate bash one-liners from plain English via a local ollama model:"
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echo -e " ${GREEN}super-man ai \"find python files modified last week\"${NC}"
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echo -e " ${GREEN}super-man ai \"count lines in all js files\"${NC}"
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echo -e " ${GREEN}super-man ai --model qwen2.5:3b \"count lines in all js files\"${NC}"
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echo -e " ${GREEN}super-man ai --compare \"list the 5 largest files\"${NC} # A/B models"
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echo ""
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echo " Other models available: llama3.2, qwen2.5"
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echo " To switch models, edit mode_ai() function"
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echo -e " Default model: ${CYAN}${SUPERMAN_AI_MODEL}${NC}"
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echo " Configure via env vars:"
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echo " SUPERMAN_AI_MODEL default model (e.g. westenfelder/NL2SH)"
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echo " SUPERMAN_AI_COMPARE_MODELS space-separated list for --compare"
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echo ""
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echo -e "${YELLOW}Database:${NC} $DB_FILE"
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echo -e "${YELLOW}Version:${NC} 2.1.0 (250+ commands, AI-powered)"
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echo -e "${YELLOW}Version:${NC} 2.2.0 (250+ commands, configurable local AI)"
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echo ""
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}
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@@ -308,15 +311,85 @@ mode_category() {
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}
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# AI mode - use NL2SH model for complex queries
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# Generate bash one-liners from natural language via a local ollama model.
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# The model is configurable so we can A/B different local LLMs:
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# SUPERMAN_AI_MODEL default model (default: qwen2.5-coder:1.5b)
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# SUPERMAN_AI_COMPARE_MODELS space-separated list used by `ai --compare`
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# Override per call with `--model NAME`; run every comparison model side by
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# side with `--compare`. NL2SH is purpose-built for NL->shell so it receives
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# the raw query; general coder models get an instruction wrapper plus markdown
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# fence stripping so they too emit a single bare command.
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SUPERMAN_AI_MODEL="${SUPERMAN_AI_MODEL:-qwen2.5-coder:1.5b}"
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SUPERMAN_AI_COMPARE_MODELS="${SUPERMAN_AI_COMPARE_MODELS:-qwen2.5-coder:1.5b westenfelder/NL2SH}"
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# Build a model-appropriate prompt for a query.
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ai_build_prompt() {
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local model="$1" query="$2"
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case "$model" in
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*NL2SH*|*nl2sh*)
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printf '%s' "$query"
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;;
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*)
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printf 'You are a bash expert. Output ONLY a single bash one-liner that accomplishes the task. No explanation, no comments, no markdown code fences. Task: %s' "$query"
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;;
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esac
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}
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# Strip markdown fences and surrounding blank lines from a raw model response.
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ai_clean_response() {
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awk '/^[[:space:]]*```/ { next } { print }' \
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| sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//' \
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| sed '/^$/d'
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}
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# True if an ollama model is pulled locally.
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ai_model_installed() {
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ollama list 2>/dev/null | grep -q "$1"
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}
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# Generate a cleaned command from one model for a query.
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ai_generate() {
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local model="$1" query="$2"
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ollama run "$model" "$(ai_build_prompt "$model" "$query")" 2>/dev/null | ai_clean_response
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}
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# Print the man/help NAME line for the base command of a generated one-liner.
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ai_explain_base() {
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local base_cmd
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base_cmd=$(echo "$1" | awk '{print $1}')
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if type "$base_cmd" 2>/dev/null | grep -q "shell builtin"; then
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echo -e "${YELLOW}Command Info:${NC}"
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help "$base_cmd" 2>/dev/null | head -3
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echo ""
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elif command -v "$base_cmd" &> /dev/null; then
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echo -e "${YELLOW}Command Info:${NC}"
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man "$base_cmd" 2>/dev/null | col -b | grep -A 2 "^NAME" | tail -2
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echo ""
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fi
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}
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mode_ai() {
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local user_query="$1"
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local compare=false
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local model="$SUPERMAN_AI_MODEL"
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local args=()
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while [ $# -gt 0 ]; do
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case "$1" in
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--compare|-c) compare=true ;;
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--model|-m) shift; model="$1" ;;
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*) args+=("$1") ;;
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esac
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shift
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done
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local user_query="${args[*]}"
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if [ -z "$user_query" ]; then
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echo -e "${RED}Error: No query provided${NC}"
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echo "Usage: super-man ai \"your complex query\""
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echo "Usage: super-man ai [--model NAME|--compare] \"your query\""
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echo ""
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echo "Example:"
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echo "Examples:"
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echo " super-man ai \"find all python files modified in last week\""
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echo " super-man ai --model qwen2.5:3b \"count lines in all js files\""
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echo " super-man ai --compare \"list the 5 largest files\""
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return 1
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fi
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@@ -331,18 +404,50 @@ mode_ai() {
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return 1
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fi
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# Check if NL2SH model is available
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if ! ollama list | grep -q "westenfelder/NL2SH"; then
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echo -e "${YELLOW}NL2SH model not found. Available models:${NC}"
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# ── Compare mode: run every configured model side by side ──────────────────
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if $compare; then
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echo ""
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echo -e "${CYAN}🤖 AI Compare${NC}"
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echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
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echo -e "${YELLOW}Query:${NC} $user_query"
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echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
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local m
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for m in $SUPERMAN_AI_COMPARE_MODELS; do
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echo ""
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echo -e "${BOLD}${MAGENTA}▸ $m${NC}"
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if ! ai_model_installed "$m"; then
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echo -e " ${DIM}not installed — pull with: ollama pull $m${NC}"
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continue
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fi
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local start end elapsed out
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start=$(date +%s.%N)
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out=$(ai_generate "$m" "$user_query")
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end=$(date +%s.%N)
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elapsed=$(awk "BEGIN{printf \"%.1f\", $end-$start}")
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if [ -z "$out" ]; then
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echo -e " ${RED}(no response)${NC} ${DIM}(${elapsed}s)${NC}"
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else
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echo -e " ${GREEN}$out${NC} ${DIM}(${elapsed}s)${NC}"
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fi
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done
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echo ""
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echo -e "${DIM}Note: Always review AI-generated commands before running them!${NC}"
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echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
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return 0
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fi
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# ── Single-model mode ──────────────────────────────────────────────────────
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if ! ai_model_installed "$model"; then
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echo -e "${YELLOW}Model '$model' not found. Installed models:${NC}"
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ollama list
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echo ""
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echo "Pull NL2SH model with:"
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echo " ollama pull westenfelder/NL2SH"
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echo "Pull it with: ollama pull $model"
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echo "Or pick another: super-man ai --model NAME \"$user_query\""
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return 1
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fi
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echo ""
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echo -e "${CYAN}🤖 AI Assistant - Using NL2SH Model${NC}"
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echo -e "${CYAN}🤖 AI Assistant — $model${NC}"
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echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
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echo -e "${YELLOW}Query:${NC} $user_query"
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echo -e "${BLUE}═══════════════════════════════════════════════════════════${NC}"
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@@ -350,8 +455,7 @@ mode_ai() {
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echo -e "${DIM}Generating bash command...${NC}"
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echo ""
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# Query the NL2SH model
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local response=$(ollama run westenfelder/NL2SH "$user_query" 2>/dev/null)
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local response=$(ai_generate "$model" "$user_query")
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if [ -z "$response" ]; then
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echo -e "${RED}Error: No response from AI model${NC}"
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@@ -365,19 +469,7 @@ mode_ai() {
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echo -e " ${MAGENTA}$response${NC}"
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echo ""
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# Extract the base command for explanation
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local base_cmd=$(echo "$response" | awk '{print $1}')
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# Try to provide explanation
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if command -v "$base_cmd" &> /dev/null || type "$base_cmd" 2>/dev/null | grep -q "shell builtin"; then
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echo -e "${YELLOW}Command Info:${NC}"
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if type "$base_cmd" 2>/dev/null | grep -q "shell builtin"; then
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help "$base_cmd" 2>/dev/null | head -3
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else
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man "$base_cmd" 2>/dev/null | col -b | grep -A 2 "^NAME" | tail -2
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fi
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echo ""
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fi
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ai_explain_base "$response"
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echo -e "${DIM}Note: Always review AI-generated commands before running them!${NC}"
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echo ""
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@@ -1250,8 +1342,9 @@ else
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QUERY="$2"
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;;
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ai)
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MODE="ai"
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QUERY="$2"
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shift
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mode_ai "$@"
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exit $?
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;;
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-*)
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echo "Unknown option: $1"
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@@ -1280,10 +1373,6 @@ if [ -n "$MODE" ]; then
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mode_category "$QUERY"
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exit $?
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;;
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ai)
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mode_ai "$QUERY"
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exit $?
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;;
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esac
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fi
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