Install Fabric AI on Arch Linux

fabric-ai-arch-install.bash

# ------------------------------------------------------------
# Helpers
# ------------------------------------------------------------
zshrc_append() {
    # Append a line to ~/.zshrc only if it isn't already there.
    local line="$1"
    grep -qxF "$line" ~/.zshrc 2>/dev/null || echo "$line" >> ~/.zshrc
}
# ------------------------------------------------------------

sudo pacman -S --needed base-devel git pkgconf cmake make gcc

# Install Paru
if ! command -v paru >/dev/null 2>&1; then
  git clone https://aur.archlinux.org/paru.git
  cd paru || exit
  makepkg -si
fi

# Install Fabric AI + dependencies
paru -S --needed --noconfirm \
    cmake \
    fabric-ai \
    ffmpeg \
    python \
    python-html2text \
    python-readability-lxml \
    python-requests \
    xclip \
    yt-dlp

# Install Whisper.cpp
cd $HOME
git clone https://github.com/ggml-org/whisper.cpp.git
cd whisper.cpp
sh ./models/download-ggml-model.sh large-v2
# build the project
cmake -B build -DGGML_CUDA=1 -DCMAKE_CUDA_ARCHITECTURES="86" -D WHISPER_FFMPEG=yes
cmake --build build -j --config Release
cd $HOME

# Install Fabric completions
curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh | sh

zshrc_append 'source ~/.config/zsh/aliases/fabric-ai-zsh-aliases.zsh'

# Fabric Setup
fabric --setup

# Reload zsh config
source ~/.zshrc

fabric-ai-zsh-aliases.zsh

# =============================================================================
# Fabric AI
# =============================================================================

# Main Fabric command.
alias fabric=fabric-ai

# Pattern aliases.
# Creates aliases for all Fabric patterns so they can be invoked directly.
for pattern_file in "$HOME/.config/fabric/patterns"/*; do
    pattern_name="$(basename "$pattern_file")"
    alias_name="${FABRIC_ALIAS_PREFIX:-}${pattern_name}"
    alias_command="alias $alias_name='fabric --pattern $pattern_name'"
    eval "$alias_command"
done


# =============================================================================
# Clipboard Utilities
# =============================================================================

# Returns clipboard contents (Wayland first, X11 fallback).
p() {
    wl-paste --primary 2>/dev/null || xclip -selection clipboard -o
}


# =============================================================================
# Web Utilities
# =============================================================================

# Fetch a URL, extract the main readable content, and convert to Markdown.
#
# Usage:
#   html https://example.com
html() {
    python - "$1" <<'PY'
import sys, requests
from readability import Document
import html2text

url = sys.argv[1]
html = requests.get(url).text
doc = Document(html)

print(html2text.html2text(doc.summary()))
PY
}


# =============================================================================
# Whisper.cpp transcription helper
# =============================================================================
# Usage:
#   whisper <url-or-file>
#
# Supports local audio/video files and YouTube URLs.
#
# Environment:
#   WHISPER_MODEL        model name           (default: large-v2)
#   WHISPER_MODEL_FILE   explicit ggml path   (default: derived from WHISPER_MODEL)
#   WHISPER_CPP_DIR      whisper.cpp root     (default: ~/whisper.cpp)
#   WHISPER_CPP_BIN      whisper-cli path     (default: <dir>/build/bin/whisper-cli)
#   WHISPER_LANG         spoken language      (default: auto — set "pt"/"en"/... to force)
#   WHISPER_THREADS      thread count         (default: nproc)
#   WHISPER_VAD          enable Silero VAD    (0/1, default 1; needs model present)
#   WHISPER_VAD_MODEL    Silero VAD ggml path (default: <dir>/models/ggml-silero-v6.2.0.bin)
#   WHISPER_SUPPRESS_NST suppress (applause)/(music) tokens   (0/1, default 0)
#   WHISPER_MAX_LEN      max line length      (default: 0 = off; cosmetic line-wrap only)
#   WHISPER_EXTRA_ARGS   extra flags string   (passthrough, e.g. "--prompt 'tech jargon'")
#   WHISPER_QUIET        silence stderr       (0/1)
#   WHISPER_DEBUG        print resolved config (0/1)
#
# Note: whisper.cpp defaults -l to "en", NOT auto-detect. This wrapper defaults to
# "auto" so non-English audio isn't silently transcribed as English (the
# "(speaking in foreign language)" loop). Force WHISPER_LANG when you know the
# language and want to avoid mis-detection on silent/music intros.
whisper() {
    local input="$1"
    local model="${WHISPER_MODEL:-large-v2}"
    local WHISPER_CPP_DIR="${WHISPER_CPP_DIR:-$HOME/whisper.cpp}"
    local WHISPER_BIN="${WHISPER_CPP_BIN:-$WHISPER_CPP_DIR/build/bin/whisper-cli}"
    local MODEL_FILE="${WHISPER_MODEL_FILE:-$WHISPER_CPP_DIR/models/ggml-${model}.bin}"
    local TRANSCRIBE_LANG="${WHISPER_LANG:-auto}"   # NOT `LANG` — that shadows the locale env var
    local THREADS="${WHISPER_THREADS:-$(nproc)}"
    local MAX_LEN="${WHISPER_MAX_LEN:-0}"
    local VAD_MODEL="${WHISPER_VAD_MODEL:-$WHISPER_CPP_DIR/models/ggml-silero-v6.2.0.bin}"
    local quiet="${WHISPER_QUIET:-0}"

    [[ -z "$input" ]] && {
        echo "Usage: whisper <url-or-file>" >&2
        return 1
    }
    [[ ! -x "$WHISPER_BIN" ]] && {
        echo "whisper-cli not found at $WHISPER_BIN" >&2
        echo "Build: cmake -B build -DGGML_CUDA=1 && cmake --build build -j --config Release" >&2
        return 1
    }
    [[ ! -f "$MODEL_FILE" ]] && {
        echo "Model not found: $MODEL_FILE" >&2
        echo "Download: $WHISPER_CPP_DIR/models/download-ggml-model.sh $model" >&2
        return 1
    }
    command -v ffmpeg >/dev/null 2>&1 || {
        echo "ffmpeg not found in PATH" >&2
        return 1
    }
    if [[ "$input" =~ ^https?:// ]]; then
        command -v yt-dlp >/dev/null 2>&1 || {
            echo "yt-dlp not found in PATH (required for URLs)" >&2
            return 1
        }
    elif [[ ! -f "$input" ]]; then
        echo "File not found: $input" >&2
        return 2
    fi

    [[ "${WHISPER_DEBUG:-0}" == 1 ]] && {
        local vad_state="off"
        [[ "${WHISPER_VAD:-1}" == 1 && -f "$VAD_MODEL" ]] && vad_state="on ($VAD_MODEL)"
        echo "whisper: model=$MODEL_FILE lang=$TRANSCRIBE_LANG threads=$THREADS vad=$vad_state max_len=$MAX_LEN" >&2
    }

    (
        set -o pipefail
        [[ "$quiet" == 1 ]] && exec 2>/dev/null

        local tmpwav
        tmpwav=$(mktemp --suffix=.wav) || exit 1
        trap 'rm -f "$tmpwav"' EXIT

        # 16 kHz mono PCM s16le — the format whisper-cli requires
        if [[ "$input" =~ ^https?:// ]]; then
            yt-dlp -f bestaudio -o - "$input" \
                | ffmpeg -loglevel error -i pipe:0 -ar 16000 -ac 1 -c:a pcm_s16le -y "$tmpwav" </dev/null \
                || { echo "Audio prep failed" >&2; exit 3; }
        else
            ffmpeg -loglevel error -i "$input" -ar 16000 -ac 1 -c:a pcm_s16le -y "$tmpwav" </dev/null \
                || { echo "Audio prep failed" >&2; exit 3; }
        fi

        local args=(
            -m "$MODEL_FILE"
            -f "$tmpwav"
            -l "$TRANSCRIBE_LANG"   # the one real fix: don't let it silently fall back to "en"
            -t "$THREADS"
            -nt -np
        )

        # opt-in hardening
        [[ "${WHISPER_SUPPRESS_NST:-0}" == 1 ]] && args+=( --suppress-nst )
        [[ "${WHISPER_VAD:-1}" == 1 && -f "$VAD_MODEL" ]] && args+=( --vad --vad-model "$VAD_MODEL" )
        [[ "$MAX_LEN" != "0" ]] && args+=( --max-len "$MAX_LEN" --split-on-word )

        # passthrough — quote-aware via xargs, no eval (no injection / no broken quoting).
        # Prefer a real array if you embed odd characters: WHISPER_EXTRA_ARGS_ARR=(--prompt "x y")
        if [[ -n "${WHISPER_EXTRA_ARGS:-}" ]]; then
            local extra=()
            mapfile -t extra < <(printf '%s' "$WHISPER_EXTRA_ARGS" | xargs printf '%s\n')
            args+=( "${extra[@]}" )
        fi
        [[ -n "${WHISPER_EXTRA_ARGS_ARR:-}" ]] && args+=( "${WHISPER_EXTRA_ARGS_ARR[@]}" )

        "$WHISPER_BIN" "${args[@]}"
    )
}


# =============================================================================
# YouTube Helpers
# =============================================================================

# Extract transcript using Fabric.
#
# Usage:
#   yt <youtube-url>
#   yt -t <youtube-url>
#
# Options:
#   -t, --timestamps
#       Include timestamps in transcript output.
yt() {
    if [ "$#" -eq 0 ] || [ "$#" -gt 2 ]; then
        echo "Usage: yt [-t | --timestamps] youtube-link"
        echo "Use the '-t' flag to get the transcript with timestamps."
        return 1
    fi

    transcript_flag="--transcript"

    if [ "$1" = "-t" ] || [ "$1" = "--timestamps" ]; then
        transcript_flag="--transcript-with-timestamps"
        shift
    fi

    local video_link="$1"
    fabric -y "$video_link" $transcript_flag
}

~refs.md

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