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This commit is contained in:
Marco Olimpi
2025-11-01 15:38:32 +01:00
کامیت 9eead317bd
46فایلهای تغییر یافته به همراه1821 افزوده شده و 0 حذف شده
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25
.gitignore فروخته شده Normal file
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# Ignora file temporanei e di sistema
*.log
*.tmp
*.swp
.DS_Store
# Ignora file di build o output comuni
build/
dist/
tmp/
*.out
# Ignora file di configurazione locali
.env
*.local
# Ignora file container qadlet
*.qadlet
# (Facoltativo) Ignora tutti i file Markdown tranne README.md
# *.md
# !README.md
# (Facoltativo) Ignora file Containerfile se non vuoi versionarli
# Containerfile

142
BadAI/badai Normal file
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#!/usr/bin/env bash
# DuckAI command-line tool
# Usage: duckai restart [--sleep N]
set -e # Exit on error
sleep_time=3 # Default sleep time in seconds
# Parse arguments
if [[ "$1" == "restart" ]]; then
name=""
if [[ "$2" == "--sleep" && -n "$3" && "$3" =~ ^[0-9]+$ ]]; then
sleep_time="$3"
name="$4"
elif [[ -n "$2" ]]; then
name="$2"
fi
echo "Reloading systemd user daemon..."
systemctl --user daemon-reload
if [[ -n "$name" ]]; then
# Riavvia servizio specifico
# Cerca container
container_file=""
for file in ~/.config/containers/systemd/*.container; do
if [[ -f "$file" ]]; then
if [[ "$(basename "$file")" =~ ^99_ ]]; then continue; fi
service_name=$(basename "$file" .container)
display_name=$(echo "$service_name" | sed 's/^[0-9]*_//')
if [[ "$display_name" == "$name" ]]; then
container_file="$file"
break
fi
fi
done
if [[ -n "$container_file" ]]; then
service_name=$(basename "$container_file" .container)
echo "Restarting container $name..."
if systemctl --user restart "$service_name" 2>/dev/null; then
echo " ✓ $name restarted successfully"
else
echo " ✗ Failed to restart $name"
fi
else
# Cerca network
network_file=""
for file in ~/.config/containers/systemd/*.network; do
if [[ -f "$file" ]]; then
if [[ "$(basename "$file")" =~ ^99_ ]]; then continue; fi
service_name=$(basename "$file" .network)-network
display_name=$(echo "$service_name" | sed 's/^[0-9]*_//')
if [[ "$display_name" == "$name" ]]; then
network_file="$file"
break
fi
fi
done
if [[ -n "$network_file" ]]; then
service_name=$(basename "$network_file" .network)-network
echo "Restarting network $name..."
if systemctl --user try-restart "$service_name" 2>/dev/null || systemctl --user start "$service_name" 2>/dev/null; then
echo " ✓ $name restarted successfully"
else
echo " ✗ Failed to restart $name"
fi
else
echo "Service $name not found."
exit 1
fi
fi
# Riavvia nginx
nginx_file=""
for file in ~/.config/containers/systemd/*nginx*.container; do
if [[ -f "$file" ]]; then
nginx_file="$file"
break
fi
done
if [[ -n "$nginx_file" ]]; then
service_name=$(basename "$nginx_file" .container)
echo "Restarting nginx..."
if systemctl --user restart "$service_name" 2>/dev/null; then
echo " ✓ nginx restarted successfully"
else
echo " ✗ Failed to restart nginx"
fi
fi
else
# Riavvia tutti
echo "Restarting all quadlet networks..."
for file in ~/.config/containers/systemd/*.network; do
if [[ -f "$file" ]]; then
if [[ "$(basename "$file")" =~ ^99_ ]]; then continue; fi
service_name=$(basename "$file" .network)-network
display_name=$(echo "$service_name" | sed 's/^[0-9]*_//')
echo "Restarting $display_name..."
if systemctl --user try-restart "$service_name" 2>/dev/null || systemctl --user start "$service_name" 2>/dev/null; then
echo " ✓ $display_name restarted successfully"
else
echo " ✗ Failed to restart $display_name"
fi
sleep "$sleep_time"
fi
done
echo "Restarting all quadlet containers..."
for file in ~/.config/containers/systemd/*.container; do
if [[ -f "$file" ]]; then
if [[ "$(basename "$file")" =~ ^99_ ]]; then continue; fi
service_name=$(basename "$file" .container)
display_name=$(echo "$service_name" | sed 's/^[0-9]*_//')
echo "Restarting $display_name..."
if systemctl --user restart "$service_name" 2>/dev/null; then
echo " ✓ $display_name restarted successfully"
else
echo " ✗ Failed to restart $display_name"
fi
sleep "$sleep_time"
fi
done
echo "All services restarted successfully."
fi
elif [[ "$1" == "help" || -z "$1" ]]; then
cat <<'EOF'
D U C K A I - C O M M A N D L I N E
--------------------------------------------------------------------------------
Usage: duckai <command> [options]
Commands:
restart [--sleep N] [name] Restart all quadlet containers and networks, or a specific one by name (without prefix), reload systemd user daemon
help Show this help message
Options:
--sleep N Sleep N seconds between restarts (default: 3)
EOF
else
echo "Unknown command: $1"
echo "Use 'duckai help' for usage."
fi

213
BadAI/badai.go Normal file
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package main
import (
"fmt"
"os"
"os/exec"
"path/filepath"
"regexp"
"strconv"
"strings"
"time"
)
func main() {
if len(os.Args) < 2 {
printHelp()
return
}
command := os.Args[1]
switch command {
case "restart":
name := ""
if len(os.Args) > 2 {
if os.Args[2] == "--sleep" && len(os.Args) > 3 {
// Ignora per ora, ma in handleRestart parsare
} else {
name = os.Args[2]
}
}
handleRestart(name)
case "help":
printHelp()
default:
fmt.Printf("Unknown command: %s\n", command)
fmt.Println("Use 'duckai help' for usage.")
os.Exit(1)
}
}
func handleRestart(name string) {
sleepTime := 3
args := os.Args[2:]
if len(args) > 0 && args[0] == "--sleep" && len(args) > 1 {
if s, err := strconv.Atoi(args[1]); err == nil {
sleepTime = s
}
if len(args) > 2 {
name = args[2]
}
} else if name == "" && len(args) > 0 {
name = args[0]
}
fmt.Println("Reloading systemd user daemon...")
runCommand("systemctl", "--user", "daemon-reload")
if name != "" {
// Riavvia servizio specifico
containerFile := findServiceFile("*.container", name)
if containerFile != "" {
serviceName := strings.TrimSuffix(filepath.Base(containerFile), ".container")
fmt.Printf("Restarting container %s...\n", name)
if runCommand("systemctl", "--user", "restart", serviceName) {
fmt.Printf(" ✓ %s restarted successfully\n", name)
} else {
fmt.Printf(" ✗ Failed to restart %s\n", name)
}
} else {
networkFile := findServiceFile("*.network", name)
if networkFile != "" {
serviceName := strings.TrimSuffix(filepath.Base(networkFile), ".network") + "-network"
fmt.Printf("Restarting network %s...\n", name)
if runCommand("systemctl", "--user", "try-restart", serviceName) || runCommand("systemctl", "--user", "start", serviceName) {
fmt.Printf(" ✓ %s restarted successfully\n", name)
} else {
fmt.Printf(" ✗ Failed to restart %s\n", name)
}
} else {
fmt.Printf("Service %s not found.\n", name)
os.Exit(1)
}
}
// Riavvia nginx
restartNginx()
} else {
fmt.Println("Restarting all quadlet networks...")
restartNetworks(sleepTime)
fmt.Println("Restarting all quadlet containers...")
restartContainers(sleepTime)
fmt.Println("All services restarted successfully.")
}
}
func findServiceFile(pattern, name string) string {
home, _ := os.UserHomeDir()
dir := filepath.Join(home, ".config", "containers", "systemd")
files, _ := filepath.Glob(filepath.Join(dir, pattern))
re := regexp.MustCompile(`^[0-9]+_`)
for _, file := range files {
if strings.HasPrefix(filepath.Base(file), "99_") {
continue
}
serviceName := strings.TrimSuffix(filepath.Base(file), filepath.Ext(file))
if pattern == "*.network" {
serviceName += "-network"
}
displayName := re.ReplaceAllString(serviceName, "")
if displayName == name {
return file
}
}
return ""
}
home, _ := os.UserHomeDir()
dir := filepath.Join(home, ".config", "containers", "systemd")
files, _ := filepath.Glob(filepath.Join(dir, pattern))
re := regexp.MustCompile(`^[0-9]+_`)
for _, file := range files {
if strings.HasPrefix(filepath.Base(file), "99_") {
continue
}
serviceName := strings.TrimSuffix(filepath.Base(file), filepath.Ext(file))
if pattern == "*.network" {
serviceName += "-network"
}
displayName := re.ReplaceAllString(serviceName, "")
if displayName == name {
return file
}
}
return ""
}
func restartNetworks(sleepTime int) {
home, _ := os.UserHomeDir()
dir := filepath.Join(home, ".config", "containers", "systemd")
files, _ := filepath.Glob(filepath.Join(dir, "*.network"))
re := regexp.MustCompile(`^[0-9]+_`)
for _, file := range files {
if strings.HasPrefix(filepath.Base(file), "99_") {
continue
}
serviceName := strings.TrimSuffix(filepath.Base(file), ".network") + "-network"
displayName := re.ReplaceAllString(serviceName, "")
fmt.Printf("Restarting %s...\n", displayName)
if runCommand("systemctl", "--user", "try-restart", serviceName) || runCommand("systemctl", "--user", "start", serviceName) {
fmt.Printf(" ✓ %s restarted successfully\n", displayName)
} else {
fmt.Printf(" ✗ Failed to restart %s\n", displayName)
}
time.Sleep(time.Duration(sleepTime) * time.Second)
}
}
func restartContainers(sleepTime int) {
home, _ := os.UserHomeDir()
dir := filepath.Join(home, ".config", "containers", "systemd")
files, _ := filepath.Glob(filepath.Join(dir, "*.container"))
re := regexp.MustCompile(`^[0-9]+_`)
for _, file := range files {
if strings.HasPrefix(filepath.Base(file), "99_") {
continue
}
serviceName := strings.TrimSuffix(filepath.Base(file), ".container")
displayName := re.ReplaceAllString(serviceName, "")
fmt.Printf("Restarting %s...\n", displayName)
if runCommand("systemctl", "--user", "restart", serviceName) {
fmt.Printf(" ✓ %s restarted successfully\n", displayName)
} else {
fmt.Printf(" ✗ Failed to restart %s\n", displayName)
}
time.Sleep(time.Duration(sleepTime) * time.Second)
}
}
func restartNginx() {
home, _ := os.UserHomeDir()
dir := filepath.Join(home, ".config", "containers", "systemd")
files, _ := filepath.Glob(filepath.Join(dir, "*nginx*.container"))
if len(files) > 0 {
serviceName := strings.TrimSuffix(filepath.Base(files[0]), ".container")
fmt.Println("Restarting nginx...")
if runCommand("systemctl", "--user", "restart", serviceName) {
fmt.Println(" ✓ nginx restarted successfully")
} else {
fmt.Println(" ✗ Failed to restart nginx")
}
}
}
func runCommand(name string, args ...string) bool {
cmd := exec.Command(name, args...)
err := cmd.Run()
return err == nil
}
func printHelp() {
fmt.Println(`D U C K A I - C O M M A N D L I N E
--------------------------------------------------------------------------------
Usage: duckai <command> [options]
Commands:
restart [--sleep N] [name] Restart all quadlet containers and networks, or a specific one by name (without prefix), reload systemd user daemon
help Show this help message
Options:
--sleep N Sleep N seconds between restarts (default: 3)`)
}

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#!/usr/bin/env bash
# Lightweight banner for BadAI host system — Ubuntu with AMDGPU drivers
oem_info() {
local v="" m="" d lv lm
for d in /sys/class/dmi/id /sys/devices/virtual/dmi/id; do
[[ -r "$d/sys_vendor" ]] && v=$(<"$d/sys_vendor")
[[ -r "$d/product_name" ]] && m=$(<"$d/product_name")
[[ -n "$v" || -n "$m" ]] && break
done
# ARM/SBC fallback
if [[ -z "$v" && -z "$m" && -r /proc/device-tree/model ]]; then
tr -d '\0' </proc/device-tree/model
return
fi
lv=$(printf '%s' "$v" | tr '[:upper:]' '[:lower:]')
lm=$(printf '%s' "$m" | tr '[:upper:]' '[:lower:]')
if [[ -n "$m" && "$lm" == "$lv "* ]]; then
printf '%s\n' "$m"
else
printf '%s %s\n' "${v:-Unknown}" "${m:-Unknown}"
fi
}
gpu_name() {
local name=""
if command -v lspci >/dev/null 2>&1; then
name=$(lspci -nn 2>/dev/null | grep -Ei 'vga|display|gpu' | grep -i amd | head -n1 | cut -d: -f3-)
fi
name=$(printf '%s' "$name" | sed -e 's/^[[:space:]]\+//' -e 's/[[:space:]]\+$//' -e 's/[[:space:]]\{2,\}/ /g')
printf '%s\n' "${name:-Unknown AMD GPU}"
}
ubuntu_version() {
lsb_release -d 2>/dev/null | cut -f2 || uname -a
}
system_load() {
uptime | awk -F'load average:' '{ print $2 }' | sed 's/,//g'
}
memory_usage() {
free -h | awk 'NR==2{printf "%.0f%%", $3*100/$2 }'
}
updates_info() {
if command -v apt >/dev/null 2>&1; then
local upgradable=$(apt list --upgradable 2>/dev/null | grep -v '^Listing' | grep -c '^[^/]*$')
local security=$(apt list --upgradable 2>/dev/null | grep -c 'security')
printf '%d updates can be applied immediately.\n' "$upgradable"
if [[ $security -gt 0 ]]; then
printf '%d additional security updates can be applied.\n' "$security"
fi
else
printf 'Updates info not available.\n'
fi
}
MACHINE="$(oem_info)"
GPU="$(gpu_name)"
UBUNTU_VER="$(ubuntu_version)"
LOAD="$(system_load)"
MEM="$(memory_usage)"
echo
cat <<'ASCII'
__________ .___ _____ .___
\______ \_____ __| _/ / _ \ | |
| | _/\__ \ / __ | / /_\ \| |
| | \ / __ \_/ /_/ | / | \ |
|______ /(____ /\____ | \____|__ /___|
\/ \/ \/ \/
B A D A I - H O S T ( U B U N T U , A M D G P U )
ASCII
echo "--------------------------------------------------------------------------------"
printf 'Machine: %s\n' "$MACHINE"
printf 'GPU : %s\n' "$GPU"
printf 'OS : %s\n' "$UBUNTU_VER"
printf 'Load : %s\n' "$LOAD"
printf 'Memory : %s\n' "$MEM"
echo
echo "--------------------------------------------------------------------------------"
updates_info
echo
echo "--------------------------------------------------------------------------------"
printf 'Usage:\n'
printf ' - %-24s → %s\n' "podman ps" "List running containers"
printf ' - %-24s → %s\n' "podman logs <name>" "View container logs"
printf ' - %-24s → %s\n' "podman exec -it <name> bash" "Access container shell"
printf ' - %-24s → %s\n' "radentop" "Monitor AMD GPU usage (if installed)"
printf ' - %-24s → %s\n' "htop" "Monitor system processes and resources"
printf ' - %-24s → %s\n' "duckai restart" "Restart all services"
printf ' - %-24s → %s\n' "duckai help" "Show DuckAI commands"

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README.md Normal file
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# Guida Installazione Container Rootless - Ubuntu
Guida completa per configurare un'infrastruttura AI containerizzata con Podman rootless su Ubuntu.
## 1. Prerequisiti
### Sistema Operativo
- Ubuntu 22.04 LTS o superiore
- Utente non-root con privilegi sudo
### Partizionamento
/boot → 1 GB → ext4
/ → 40 GB → ext4
/home → 50 GB → ext4 (se usi Podman rootless)
/srv → tutto il resto → xfs (per dati, modelli AI, volumi bind)
/swap → 16 GB → swap
## Installazione
Per installare automaticamente tutto il necessario, esegui:
```bash
curl -fsSL https://tuo-repo/install.sh | sh
```
Sostituisci `https://tuo-repo/install.sh` con l'URL del tuo repository remoto (ad esempio, `https://raw.githubusercontent.com/tuo-username/tuo-repo/main/install.sh`).
Questo script eseguirà tutti i passi di configurazione, inclusi aggiornamenti di sistema, installazione di Podman, configurazione di systemd e riavvio finale.
## Utilizzo dopo l'installazione
Dopo l'installazione e il riavvio, usa il comando `badai` per gestire i servizi AI containerizzati.
### Comandi principali:
- `badai restart`: Riavvia tutti i container e le reti quadlet, ricarica il daemon systemd dell'utente.
- `badai restart [nome]`: Riavvia un servizio specifico per nome (senza prefisso numerico).
- `badai help`: Mostra il messaggio di aiuto.
Esempi:
```bash
badai restart # Riavvia tutto
badai restart llamacpp # Riavvia solo il container llamacpp
```
I servizi includono container come `llamacpp` per modelli AI e `nginx` per il proxy, oltre alle reti interne.

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Services/certbot/certbot.container Normal file
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[Unit]
Name=certbot
[Container]
ContainerName=certbot
Image=certbot/certbot
AutoUpdate=registry
Volume=/srv/containers/nginx/ssl:/etc/letsencrypt

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Services/llamacpp/DOCS.md Normal file
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----- common params -----
-h, --help, --usage print usage and exit
--version show version and build info
--completion-bash print source-able bash completion script for llama.cpp
--verbose-prompt print a verbose prompt before generation (default: false)
-t, --threads N number of CPU threads to use during generation (default: -1)
(env: LLAMA_ARG_THREADS)
-tb, --threads-batch N number of threads to use during batch and prompt processing (default:
same as --threads)
-C, --cpu-mask M CPU affinity mask: arbitrarily long hex. Complements cpu-range
(default: "")
-Cr, --cpu-range lo-hi range of CPUs for affinity. Complements --cpu-mask
--cpu-strict <0|1> use strict CPU placement (default: 0)
--prio N set process/thread priority : low(-1), normal(0), medium(1), high(2),
realtime(3) (default: 0)
--poll <0...100> use polling level to wait for work (0 - no polling, default: 50)
-Cb, --cpu-mask-batch M CPU affinity mask: arbitrarily long hex. Complements cpu-range-batch
(default: same as --cpu-mask)
-Crb, --cpu-range-batch lo-hi ranges of CPUs for affinity. Complements --cpu-mask-batch
--cpu-strict-batch <0|1> use strict CPU placement (default: same as --cpu-strict)
--prio-batch N set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime
(default: 0)
--poll-batch <0|1> use polling to wait for work (default: same as --poll)
-c, --ctx-size N size of the prompt context (default: 4096, 0 = loaded from model)
(env: LLAMA_ARG_CTX_SIZE)
-n, --predict, --n-predict N number of tokens to predict (default: -1, -1 = infinity)
(env: LLAMA_ARG_N_PREDICT)
-b, --batch-size N logical maximum batch size (default: 2048)
(env: LLAMA_ARG_BATCH)
-ub, --ubatch-size N physical maximum batch size (default: 512)
(env: LLAMA_ARG_UBATCH)
--keep N number of tokens to keep from the initial prompt (default: 0, -1 =
all)
--swa-full use full-size SWA cache (default: false)
[(more
info)](https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
(env: LLAMA_ARG_SWA_FULL)
--kv-unified, -kvu use single unified KV buffer for the KV cache of all sequences
(default: false)
[(more info)](https://github.com/ggml-org/llama.cpp/pull/14363)
(env: LLAMA_ARG_KV_SPLIT)
-fa, --flash-attn [on|off|auto] set Flash Attention use ('on', 'off', or 'auto', default: 'auto')
(env: LLAMA_ARG_FLASH_ATTN)
--no-perf disable internal libllama performance timings (default: false)
(env: LLAMA_ARG_NO_PERF)
-e, --escape process escapes sequences (\n, \r, \t, \', \", \\) (default: true)
--no-escape do not process escape sequences
--rope-scaling {none,linear,yarn} RoPE frequency scaling method, defaults to linear unless specified by
the model
(env: LLAMA_ARG_ROPE_SCALING_TYPE)
--rope-scale N RoPE context scaling factor, expands context by a factor of N
(env: LLAMA_ARG_ROPE_SCALE)
--rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: loaded from
model)
(env: LLAMA_ARG_ROPE_FREQ_BASE)
--rope-freq-scale N RoPE frequency scaling factor, expands context by a factor of 1/N
(env: LLAMA_ARG_ROPE_FREQ_SCALE)
--yarn-orig-ctx N YaRN: original context size of model (default: 0 = model training
context size)
(env: LLAMA_ARG_YARN_ORIG_CTX)
--yarn-ext-factor N YaRN: extrapolation mix factor (default: -1.0, 0.0 = full
interpolation)
(env: LLAMA_ARG_YARN_EXT_FACTOR)
--yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: -1.0)
(env: LLAMA_ARG_YARN_ATTN_FACTOR)
--yarn-beta-slow N YaRN: high correction dim or alpha (default: -1.0)
(env: LLAMA_ARG_YARN_BETA_SLOW)
--yarn-beta-fast N YaRN: low correction dim or beta (default: -1.0)
(env: LLAMA_ARG_YARN_BETA_FAST)
-nkvo, --no-kv-offload disable KV offload
(env: LLAMA_ARG_NO_KV_OFFLOAD)
-nr, --no-repack disable weight repacking
(env: LLAMA_ARG_NO_REPACK)
--no-host bypass host buffer allowing extra buffers to be used
(env: LLAMA_ARG_NO_HOST)
-ctk, --cache-type-k TYPE KV cache data type for K
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_K)
-ctv, --cache-type-v TYPE KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V)
-dt, --defrag-thold N KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD)
-np, --parallel N number of parallel sequences to decode (default: 1)
(env: LLAMA_ARG_N_PARALLEL)
--mlock force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK)
--no-mmap do not memory-map model (slower load but may reduce pageouts if not
using mlock)
(env: LLAMA_ARG_NO_MMAP)
--numa TYPE attempt optimizations that help on some NUMA systems
- distribute: spread execution evenly over all nodes
- isolate: only spawn threads on CPUs on the node that execution
started on
- numactl: use the CPU map provided by numactl
if run without this previously, it is recommended to drop the system
page cache before using this
see https://github.com/ggml-org/llama.cpp/issues/1437
(env: LLAMA_ARG_NUMA)
-dev, --device <dev1,dev2,..> comma-separated list of devices to use for offloading (none = don't
offload)
use --list-devices to see a list of available devices
(env: LLAMA_ARG_DEVICE)
--list-devices print list of available devices and exit
--override-tensor, -ot <tensor name pattern>=<buffer type>,...
override tensor buffer type
--cpu-moe, -cmoe keep all Mixture of Experts (MoE) weights in the CPU
(env: LLAMA_ARG_CPU_MOE)
--n-cpu-moe, -ncmoe N keep the Mixture of Experts (MoE) weights of the first N layers in the
CPU
(env: LLAMA_ARG_N_CPU_MOE)
-ngl, --gpu-layers, --n-gpu-layers N max. number of layers to store in VRAM (default: -1)
(env: LLAMA_ARG_N_GPU_LAYERS)
-sm, --split-mode {none,layer,row} how to split the model across multiple GPUs, one of:
- none: use one GPU only
- layer (default): split layers and KV across GPUs
- row: split rows across GPUs
(env: LLAMA_ARG_SPLIT_MODE)
-ts, --tensor-split N0,N1,N2,... fraction of the model to offload to each GPU, comma-separated list of
proportions, e.g. 3,1
(env: LLAMA_ARG_TENSOR_SPLIT)
-mg, --main-gpu INDEX the GPU to use for the model (with split-mode = none), or for
intermediate results and KV (with split-mode = row) (default: 0)
(env: LLAMA_ARG_MAIN_GPU)
--check-tensors check model tensor data for invalid values (default: false)
--override-kv KEY=TYPE:VALUE advanced option to override model metadata by key. may be specified
multiple times.
types: int, float, bool, str. example: --override-kv
tokenizer.ggml.add_bos_token=bool:false
--no-op-offload disable offloading host tensor operations to device (default: false)
--lora FNAME path to LoRA adapter (can be repeated to use multiple adapters)
--lora-scaled FNAME SCALE path to LoRA adapter with user defined scaling (can be repeated to use
multiple adapters)
--control-vector FNAME add a control vector
note: this argument can be repeated to add multiple control vectors
--control-vector-scaled FNAME SCALE add a control vector with user defined scaling SCALE
note: this argument can be repeated to add multiple scaled control
vectors
--control-vector-layer-range START END
layer range to apply the control vector(s) to, start and end inclusive
-m, --model FNAME model path (default: `models/$filename` with filename from `--hf-file`
or `--model-url` if set, otherwise models/7B/ggml-model-f16.gguf)
(env: LLAMA_ARG_MODEL)
-mu, --model-url MODEL_URL model download url (default: unused)
(env: LLAMA_ARG_MODEL_URL)
-dr, --docker-repo [<repo>/]<model>[:quant]
Docker Hub model repository. repo is optional, default to ai/. quant
is optional, default to :latest.
example: gemma3
(default: unused)
(env: LLAMA_ARG_DOCKER_REPO)
-hf, -hfr, --hf-repo <user>/<model>[:quant]
Hugging Face model repository; quant is optional, case-insensitive,
default to Q4_K_M, or falls back to the first file in the repo if
Q4_K_M doesn't exist.
mmproj is also downloaded automatically if available. to disable, add
--no-mmproj
example: unsloth/phi-4-GGUF:q4_k_m
(default: unused)
(env: LLAMA_ARG_HF_REPO)
-hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]
Same as --hf-repo, but for the draft model (default: unused)
(env: LLAMA_ARG_HFD_REPO)
-hff, --hf-file FILE Hugging Face model file. If specified, it will override the quant in
--hf-repo (default: unused)
(env: LLAMA_ARG_HF_FILE)
-hfv, -hfrv, --hf-repo-v <user>/<model>[:quant]
Hugging Face model repository for the vocoder model (default: unused)
(env: LLAMA_ARG_HF_REPO_V)
-hffv, --hf-file-v FILE Hugging Face model file for the vocoder model (default: unused)
(env: LLAMA_ARG_HF_FILE_V)
-hft, --hf-token TOKEN Hugging Face access token (default: value from HF_TOKEN environment
variable)
(env: HF_TOKEN)
--log-disable Log disable
--log-file FNAME Log to file
--log-colors [on|off|auto] Set colored logging ('on', 'off', or 'auto', default: 'auto')
'auto' enables colors when output is to a terminal
(env: LLAMA_LOG_COLORS)
-v, --verbose, --log-verbose Set verbosity level to infinity (i.e. log all messages, useful for
debugging)
--offline Offline mode: forces use of cache, prevents network access
(env: LLAMA_OFFLINE)
-lv, --verbosity, --log-verbosity N Set the verbosity threshold. Messages with a higher verbosity will be
ignored.
(env: LLAMA_LOG_VERBOSITY)
--log-prefix Enable prefix in log messages
(env: LLAMA_LOG_PREFIX)
--log-timestamps Enable timestamps in log messages
(env: LLAMA_LOG_TIMESTAMPS)
-ctkd, --cache-type-k-draft TYPE KV cache data type for K for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_K_DRAFT)
-ctvd, --cache-type-v-draft TYPE KV cache data type for V for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V_DRAFT)
----- sampling params -----
--samplers SAMPLERS samplers that will be used for generation in the order, separated by
';'
(default:
penalties;dry;top_n_sigma;top_k;typ_p;top_p;min_p;xtc;temperature)
-s, --seed SEED RNG seed (default: -1, use random seed for -1)
--sampling-seq, --sampler-seq SEQUENCE
simplified sequence for samplers that will be used (default:
edskypmxt)
--ignore-eos ignore end of stream token and continue generating (implies
--logit-bias EOS-inf)
--temp N temperature (default: 0.8)
--top-k N top-k sampling (default: 40, 0 = disabled)
--top-p N top-p sampling (default: 0.9, 1.0 = disabled)
--min-p N min-p sampling (default: 0.1, 0.0 = disabled)
--top-nsigma N top-n-sigma sampling (default: -1.0, -1.0 = disabled)
--xtc-probability N xtc probability (default: 0.0, 0.0 = disabled)
--xtc-threshold N xtc threshold (default: 0.1, 1.0 = disabled)
--typical N locally typical sampling, parameter p (default: 1.0, 1.0 = disabled)
--repeat-last-n N last n tokens to consider for penalize (default: 64, 0 = disabled, -1
= ctx_size)
--repeat-penalty N penalize repeat sequence of tokens (default: 1.0, 1.0 = disabled)
--presence-penalty N repeat alpha presence penalty (default: 0.0, 0.0 = disabled)
--frequency-penalty N repeat alpha frequency penalty (default: 0.0, 0.0 = disabled)
--dry-multiplier N set DRY sampling multiplier (default: 0.0, 0.0 = disabled)
--dry-base N set DRY sampling base value (default: 1.75)
--dry-allowed-length N set allowed length for DRY sampling (default: 2)
--dry-penalty-last-n N set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 =
context size)
--dry-sequence-breaker STRING add sequence breaker for DRY sampling, clearing out default breakers
('\n', ':', '"', '*') in the process; use "none" to not use any
sequence breakers
--dynatemp-range N dynamic temperature range (default: 0.0, 0.0 = disabled)
--dynatemp-exp N dynamic temperature exponent (default: 1.0)
--mirostat N use Mirostat sampling.
Top K, Nucleus and Locally Typical samplers are ignored if used.
(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
--mirostat-lr N Mirostat learning rate, parameter eta (default: 0.1)
--mirostat-ent N Mirostat target entropy, parameter tau (default: 5.0)
-l, --logit-bias TOKEN_ID(+/-)BIAS modifies the likelihood of token appearing in the completion,
i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
--grammar GRAMMAR BNF-like grammar to constrain generations (see samples in grammars/
dir) (default: '')
--grammar-file FNAME file to read grammar from
-j, --json-schema SCHEMA JSON schema to constrain generations (https://json-schema.org/), e.g.
`{}` for any JSON object
For schemas w/ external $refs, use --grammar +
example/json_schema_to_grammar.py instead
-jf, --json-schema-file FILE File containing a JSON schema to constrain generations
(https://json-schema.org/), e.g. `{}` for any JSON object
For schemas w/ external $refs, use --grammar +
example/json_schema_to_grammar.py instead
----- example-specific params -----
--ctx-checkpoints, --swa-checkpoints N
max number of context checkpoints to create per slot (default: 8)
[(more info)](https://github.com/ggml-org/llama.cpp/pull/15293)
(env: LLAMA_ARG_CTX_CHECKPOINTS)
--cache-ram, -cram N set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 -
disable)
[(more info)](https://github.com/ggml-org/llama.cpp/pull/16391)
(env: LLAMA_ARG_CACHE_RAM)
--no-context-shift disables context shift on infinite text generation (default: enabled)
(env: LLAMA_ARG_NO_CONTEXT_SHIFT)
--context-shift enables context shift on infinite text generation (default: disabled)
(env: LLAMA_ARG_CONTEXT_SHIFT)
-r, --reverse-prompt PROMPT halt generation at PROMPT, return control in interactive mode
-sp, --special special tokens output enabled (default: false)
--no-warmup skip warming up the model with an empty run
--spm-infill use Suffix/Prefix/Middle pattern for infill (instead of
Prefix/Suffix/Middle) as some models prefer this. (default: disabled)
--pooling {none,mean,cls,last,rank} pooling type for embeddings, use model default if unspecified
(env: LLAMA_ARG_POOLING)
-cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: enabled)
(env: LLAMA_ARG_CONT_BATCHING)
-nocb, --no-cont-batching disable continuous batching
(env: LLAMA_ARG_NO_CONT_BATCHING)
--mmproj FILE path to a multimodal projector file. see tools/mtmd/README.md
note: if -hf is used, this argument can be omitted
(env: LLAMA_ARG_MMPROJ)
--mmproj-url URL URL to a multimodal projector file. see tools/mtmd/README.md
(env: LLAMA_ARG_MMPROJ_URL)
--no-mmproj explicitly disable multimodal projector, useful when using -hf
(env: LLAMA_ARG_NO_MMPROJ)
--no-mmproj-offload do not offload multimodal projector to GPU
(env: LLAMA_ARG_NO_MMPROJ_OFFLOAD)
--override-tensor-draft, -otd <tensor name pattern>=<buffer type>,...
override tensor buffer type for draft model
--cpu-moe-draft, -cmoed keep all Mixture of Experts (MoE) weights in the CPU for the draft
model
(env: LLAMA_ARG_CPU_MOE_DRAFT)
--n-cpu-moe-draft, -ncmoed N keep the Mixture of Experts (MoE) weights of the first N layers in the
CPU for the draft model
(env: LLAMA_ARG_N_CPU_MOE_DRAFT)
-a, --alias STRING set alias for model name (to be used by REST API)
(env: LLAMA_ARG_ALIAS)
--host HOST ip address to listen, or bind to an UNIX socket if the address ends
with .sock (default: 127.0.0.1)
(env: LLAMA_ARG_HOST)
--port PORT port to listen (default: 8080)
(env: LLAMA_ARG_PORT)
--path PATH path to serve static files from (default: )
(env: LLAMA_ARG_STATIC_PATH)
--api-prefix PREFIX prefix path the server serves from, without the trailing slash
(default: )
(env: LLAMA_ARG_API_PREFIX)
--no-webui Disable the Web UI (default: enabled)
(env: LLAMA_ARG_NO_WEBUI)
--embedding, --embeddings restrict to only support embedding use case; use only with dedicated
embedding models (default: disabled)
(env: LLAMA_ARG_EMBEDDINGS)
--reranking, --rerank enable reranking endpoint on server (default: disabled)
(env: LLAMA_ARG_RERANKING)
--api-key KEY API key to use for authentication (default: none)
(env: LLAMA_API_KEY)
--api-key-file FNAME path to file containing API keys (default: none)
--ssl-key-file FNAME path to file a PEM-encoded SSL private key
(env: LLAMA_ARG_SSL_KEY_FILE)
--ssl-cert-file FNAME path to file a PEM-encoded SSL certificate
(env: LLAMA_ARG_SSL_CERT_FILE)
--chat-template-kwargs STRING sets additional params for the json template parser
(env: LLAMA_CHAT_TEMPLATE_KWARGS)
-to, --timeout N server read/write timeout in seconds (default: 600)
(env: LLAMA_ARG_TIMEOUT)
--threads-http N number of threads used to process HTTP requests (default: -1)
(env: LLAMA_ARG_THREADS_HTTP)
--cache-reuse N min chunk size to attempt reusing from the cache via KV shifting
(default: 0)
[(card)](https://ggml.ai/f0.png)
(env: LLAMA_ARG_CACHE_REUSE)
--metrics enable prometheus compatible metrics endpoint (default: disabled)
(env: LLAMA_ARG_ENDPOINT_METRICS)
--props enable changing global properties via POST /props (default: disabled)
(env: LLAMA_ARG_ENDPOINT_PROPS)
--slots enable slots monitoring endpoint (default: enabled)
(env: LLAMA_ARG_ENDPOINT_SLOTS)
--no-slots disables slots monitoring endpoint
(env: LLAMA_ARG_NO_ENDPOINT_SLOTS)
--slot-save-path PATH path to save slot kv cache (default: disabled)
--jinja use jinja template for chat (default: disabled)
(env: LLAMA_ARG_JINJA)
--reasoning-format FORMAT controls whether thought tags are allowed and/or extracted from the
response, and in which format they're returned; one of:
- none: leaves thoughts unparsed in `message.content`
- deepseek: puts thoughts in `message.reasoning_content`
- deepseek-legacy: keeps `<think>` tags in `message.content` while
also populating `message.reasoning_content`
(default: auto)
(env: LLAMA_ARG_THINK)
--reasoning-budget N controls the amount of thinking allowed; currently only one of: -1 for
unrestricted thinking budget, or 0 to disable thinking (default: -1)
(env: LLAMA_ARG_THINK_BUDGET)
--chat-template JINJA_TEMPLATE set custom jinja chat template (default: template taken from model's
metadata)
if suffix/prefix are specified, template will be disabled
only commonly used templates are accepted (unless --jinja is set
before this flag):
list of built-in templates:
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
command-r, deepseek, deepseek2, deepseek3, exaone3, exaone4, falcon3,
gemma, gigachat, glmedge, gpt-oss, granite, grok-2, hunyuan-dense,
hunyuan-moe, kimi-k2, llama2, llama2-sys, llama2-sys-bos,
llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1,
mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch,
openchat, orion, phi3, phi4, rwkv-world, seed_oss, smolvlm, vicuna,
vicuna-orca, yandex, zephyr
(env: LLAMA_ARG_CHAT_TEMPLATE)
--chat-template-file JINJA_TEMPLATE_FILE
set custom jinja chat template file (default: template taken from
model's metadata)
if suffix/prefix are specified, template will be disabled
only commonly used templates are accepted (unless --jinja is set
before this flag):
list of built-in templates:
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
command-r, deepseek, deepseek2, deepseek3, exaone3, exaone4, falcon3,
gemma, gigachat, glmedge, gpt-oss, granite, grok-2, hunyuan-dense,
hunyuan-moe, kimi-k2, llama2, llama2-sys, llama2-sys-bos,
llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1,
mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch,
openchat, orion, phi3, phi4, rwkv-world, seed_oss, smolvlm, vicuna,
vicuna-orca, yandex, zephyr
(env: LLAMA_ARG_CHAT_TEMPLATE_FILE)
--no-prefill-assistant whether to prefill the assistant's response if the last message is an
assistant message (default: prefill enabled)
when this flag is set, if the last message is an assistant message
then it will be treated as a full message and not prefilled
(env: LLAMA_ARG_NO_PREFILL_ASSISTANT)
-sps, --slot-prompt-similarity SIMILARITY
how much the prompt of a request must match the prompt of a slot in
order to use that slot (default: 0.10, 0.0 = disabled)
--lora-init-without-apply load LoRA adapters without applying them (apply later via POST
/lora-adapters) (default: disabled)
-td, --threads-draft N number of threads to use during generation (default: same as
--threads)
-tbd, --threads-batch-draft N number of threads to use during batch and prompt processing (default:
same as --threads-draft)
--draft-max, --draft, --draft-n N number of tokens to draft for speculative decoding (default: 16)
(env: LLAMA_ARG_DRAFT_MAX)
--draft-min, --draft-n-min N minimum number of draft tokens to use for speculative decoding
(default: 0)
(env: LLAMA_ARG_DRAFT_MIN)
--draft-p-min P minimum speculative decoding probability (greedy) (default: 0.8)
(env: LLAMA_ARG_DRAFT_P_MIN)
-cd, --ctx-size-draft N size of the prompt context for the draft model (default: 0, 0 = loaded
from model)
(env: LLAMA_ARG_CTX_SIZE_DRAFT)
-devd, --device-draft <dev1,dev2,..> comma-separated list of devices to use for offloading the draft model
(none = don't offload)
use --list-devices to see a list of available devices
-ngld, --gpu-layers-draft, --n-gpu-layers-draft N
number of layers to store in VRAM for the draft model
(env: LLAMA_ARG_N_GPU_LAYERS_DRAFT)
-md, --model-draft FNAME draft model for speculative decoding (default: unused)
(env: LLAMA_ARG_MODEL_DRAFT)
--spec-replace TARGET DRAFT translate the string in TARGET into DRAFT if the draft model and main
model are not compatible
-mv, --model-vocoder FNAME vocoder model for audio generation (default: unused)
--tts-use-guide-tokens Use guide tokens to improve TTS word recall
--embd-gemma-default use default EmbeddingGemma model (note: can download weights from the
internet)
--fim-qwen-1.5b-default use default Qwen 2.5 Coder 1.5B (note: can download weights from the
internet)
--fim-qwen-3b-default use default Qwen 2.5 Coder 3B (note: can download weights from the
internet)
--fim-qwen-7b-default use default Qwen 2.5 Coder 7B (note: can download weights from the
internet)
--fim-qwen-7b-spec use Qwen 2.5 Coder 7B + 0.5B draft for speculative decoding (note: can
download weights from the internet)
--fim-qwen-14b-spec use Qwen 2.5 Coder 14B + 0.5B draft for speculative decoding (note:
can download weights from the internet)
--fim-qwen-30b-default use default Qwen 3 Coder 30B A3B Instruct (note: can download weights
from the internet)
--gpt-oss-20b-default use gpt-oss-20b (note: can download weights from the internet)
--gpt-oss-120b-default use gpt-oss-120b (note: can download weights from the internet)
--vision-gemma-4b-default use Gemma 3 4B QAT (note: can download weights from the internet)
--vision-gemma-12b-default use Gemma 3 12B QAT (note: can download weights from the internet)

22
Services/llamacpp/Scripts/startBaseMedium.sh Executable file
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#!/bin/bash
# Report descrittivi: 0.6 ok; 0.55 più stabile
TEMP=${BASE_TEMP:-0.6}
exec /app/llama-server $BASE_MEDIUM_MODEL \
-c $BASE_CONTEXT_SIZE -ngl $BASE_GPU_LAYERS -n $BASE_MAX_TOKENS \
--temp $TEMP --top-p 0.9 --top-k 40 --repeat-penalty 1.1 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8092 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

20
Services/llamacpp/Scripts/startBaseMini.sh Executable file
مشاهده پرونده

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#!/bin/bash
exec /app/llama-server $BASE_MINI_MODEL \
-c 4096 -n 128 \
--temp 0.2 --top-p 0.9 --top-k 40 --repeat-penalty 1.05 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8091 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

20
Services/llamacpp/Scripts/startBaseTop.sh Executable file
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#!/bin/bash
exec /app/llama-server $BASE_TOP_MODEL \
-c $BASE_CONTEXT_SIZE -ngl $BASE_GPU_LAYERS -n $BASE_MAX_TOKENS \
--temp 0.5 --top-p 0.9 --top-k 40 --repeat-penalty 1.1 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 900 --host 0.0.0.0 --port 8093 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

22
Services/llamacpp/Scripts/startChat.sh Executable file
مشاهده پرونده

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#!/bin/bash
# Report descrittivi: 0.6 ok; 0.55 più stabile
TEMP=${GENERAL_TEMP:-0.6}
exec /app/llama-server $CHAT_MODEL \
-c $GENERAL_CONTEXT_SIZE -ngl $GENERAL_GPU_LAYERS -n $GENERAL_MAX_TOKENS \
--temp $TEMP --top-p 0.9 --top-k 40 --repeat-penalty 1.1 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8093 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

20
Services/llamacpp/Scripts/startCoder.sh Executable file
مشاهده پرونده

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#!/bin/bash
exec /app/llama-server $CODER_MODEL \
-c $CODER_CONTEXT_SIZE -n $CODER_MAX_TOKENS \
--temp 0.3 --top-p 0.9 --top-k 40 --repeat-penalty 1.05 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8094 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

23
Services/llamacpp/Scripts/startCoderMedium.sh Executable file
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#!/bin/bash
# Prefer Q6 + mmap; fallback to no-mmap only if explicitly requested
EXTRA=""
if [[ "$FORCE_NO_MMAP_CODER" == "1" ]]; then EXTRA="--no-mmap"; fi
exec /app/llama-server $CODER_MEDIUM_MODEL \
-c $CODER_CONTEXT_SIZE -ngl $CODER_GPU_LAYERS -n $CODER_MAX_TOKENS \
--temp 0.5 --top-p 0.9 --top-k 40 --repeat-penalty 1.1 $EXTRA \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 900 --host 0.0.0.0 --port 8095 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

19
Services/llamacpp/Scripts/startCoderMini.sh Executable file
مشاهده پرونده

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#!/bin/bash
exec /app/llama-server $CODER_MINI_MODEL \
-c 4096 -n 256 \
--temp 0.3 --top-p 0.9 --top-k 40 --repeat-penalty 1.05 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8094 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

32
Services/llamacpp/Scripts/startCoderTop.sh Executable file
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#!/bin/bash
# Large model: auto-select mmap based on GPU layers
# <= 45 layers: use mmap (less VRAM usage, faster startup)
# > 45 layers: disable mmap (avoids SVM limits)
LAYERS=${CODER_TOP_GPU_LAYERS:-55}
MMAP_OPT=""
if [ "$LAYERS" -gt 45 ]; then
MMAP_OPT="--no-mmap"
echo "Using --no-mmap (layers=$LAYERS > 45)"
else
echo "Using mmap (layers=$LAYERS <= 45)"
fi
exec /app/llama-server $CODER_TOP_MODEL \
-c $CODER_CONTEXT_SIZE -ngl $LAYERS -n $CODER_MAX_TOKENS \
--temp 0.45 --top-p 0.9 --top-k 40 --repeat-penalty 1.12 \
$MMAP_OPT \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 1200 --host 0.0.0.0 --port 8096 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

18
Services/llamacpp/Scripts/startEmbedding.sh Executable file
مشاهده پرونده

@@ -0,0 +1,18 @@
#!/bin/bash
exec /app/llama-server $EMBEDDING_MODEL \
--embeddings --pooling mean \
--flash-attn auto --threads -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8096 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

18
Services/llamacpp/Scripts/startEmbeddingFast.sh Executable file
مشاهده پرونده

@@ -0,0 +1,18 @@
#!/bin/bash
exec /app/llama-server $EMBEDDING_FAST_MODEL \
--embeddings --pooling mean \
--flash-attn auto --threads -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8095 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

18
Services/llamacpp/Scripts/startEmbeddingMedium.sh Executable file
مشاهده پرونده

@@ -0,0 +1,18 @@
#!/bin/bash
exec /app/llama-server $EMBEDDING_MEDIUM_MODEL \
--embeddings --pooling mean \
--flash-attn auto --threads -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8098 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

18
Services/llamacpp/Scripts/startEmbeddingMini.sh Executable file
مشاهده پرونده

@@ -0,0 +1,18 @@
#!/bin/bash
exec /app/llama-server $EMBEDDING_MINI_MODEL \
--embeddings --pooling mean \
--flash-attn auto --threads -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8097 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

18
Services/llamacpp/Scripts/startEmbeddingTop.sh Executable file
مشاهده پرونده

@@ -0,0 +1,18 @@
#!/bin/bash
exec /app/llama-server $EMBEDDING_TOP_MODEL \
--embeddings --pooling mean \
--flash-attn auto --threads -1 --threads-http -1 \
--timeout 600 --host 0.0.0.0 --port 8099 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

22
Services/llamacpp/Scripts/startGeneral.sh Executable file
مشاهده پرونده

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#!/bin/bash
# Report descrittivi: 0.6 ok; 0.55 più stabile
TEMP=${GENERAL_TEMP:-0.6}
exec /app/llama-server $GENERAL_MODEL \
-c $GENERAL_CONTEXT_SIZE -ngl $GENERAL_GPU_LAYERS -n $GENERAL_MAX_TOKENS \
--temp $TEMP --top-p 0.9 --top-k 40 --repeat-penalty 1.1 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8092 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

20
Services/llamacpp/Scripts/startGeneralFast.sh Executable file
مشاهده پرونده

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#!/bin/bash
exec /app/llama-server $GENERAL_FAST_MODEL \
-c $GENERAL_CONTEXT_SIZE -n 128 \
--temp 0.6 --top-p 0.9 --top-k 40 --repeat-penalty 1.05 \
--flash-attn auto --threads -1 --threads-batch -1 --threads-http -1 \
--jinja \
--timeout 600 --host 0.0.0.0 --port 8091 &
PID=$!
cleanup() {
echo "Stopping llama-server..."
kill $PID 2>/dev/null
wait $PID 2>/dev/null
exit 0
}
trap cleanup SIGTERM SIGINT
wait $PID

3
Services/llamacpp/Scripts/stopBaseMedium.sh Executable file
مشاهده پرونده

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#!/bin/bash
pkill -f "llama-server.*8092" || true

3
Services/llamacpp/Scripts/stopBaseMini.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8091" || true

3
Services/llamacpp/Scripts/stopBaseTop.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8093" || true

4
Services/llamacpp/Scripts/stopChat.sh Executable file
مشاهده پرونده

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#!/bin/bash
# Stop llama-server per DuckAi-Chat
pkill -f "llama-server.*--port 8093"

4
Services/llamacpp/Scripts/stopCoder.sh Executable file
مشاهده پرونده

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#!/bin/bash
# Stop llama-server per DuckAi-Coder
pkill -f "llama-server.*--port 8094"

3
Services/llamacpp/Scripts/stopCoderMedium.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8095" || true

3
Services/llamacpp/Scripts/stopCoderMini.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8094" || true

3
Services/llamacpp/Scripts/stopCoderTop.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8096" || true

4
Services/llamacpp/Scripts/stopEmbedding.sh Executable file
مشاهده پرونده

@@ -0,0 +1,4 @@
#!/bin/bash
# Stop llama-server per DuckAi-Embedding
pkill -f "llama-server.*--port 8096"

4
Services/llamacpp/Scripts/stopEmbeddingFast.sh Executable file
مشاهده پرونده

@@ -0,0 +1,4 @@
#!/bin/bash
# Stop llama-server per DuckAi-EmbeddingFast
pkill -f "llama-server.*--port 8095"

3
Services/llamacpp/Scripts/stopEmbeddingMedium.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8098" || true

3
Services/llamacpp/Scripts/stopEmbeddingMini.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8097" || true

3
Services/llamacpp/Scripts/stopEmbeddingTop.sh Executable file
مشاهده پرونده

@@ -0,0 +1,3 @@
#!/bin/bash
pkill -f "llama-server.*8099" || true

4
Services/llamacpp/Scripts/stopGeneral.sh Executable file
مشاهده پرونده

@@ -0,0 +1,4 @@
#!/bin/bash
# Stop llama-server per DuckAi-General
pkill -f "llama-server.*--port 8092"

4
Services/llamacpp/Scripts/stopGeneralFast.sh Executable file
مشاهده پرونده

@@ -0,0 +1,4 @@
#!/bin/bash
# Stop llama-server per DuckAi-GeneralFast
pkill -f "llama-server.*--port 8091"

59
Services/llamacpp/config.preset.yaml Normal file
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logLevel: info
healthCheckTimeout: 120
models:
DuckAi-GeneralFast:
proxy: http://localhost:8091
cmd: /app/Scripts/startGeneralFast.sh
cmdStop: /app/Scripts/stopGeneralFast.sh
checkEndpoint: /health
DuckAi-General:
proxy: http://localhost:8092
cmd: /app/Scripts/startGeneral.sh
cmdStop: /app/Scripts/stopGeneral.sh
checkEndpoint: /health
ttl: 600
DuckAi-Chat:
proxy: http://localhost:8093
cmd: /app/Scripts/startChat.sh
cmdStop: /app/Scripts/stopChat.sh
checkEndpoint: /health
ttl: 600
DuckAi-Coder:
proxy: http://localhost:8094
cmd: /app/Scripts/startCoder.sh
cmdStop: /app/Scripts/stopCoder.sh
checkEndpoint: /health
ttl: 600
DuckAi-EmbeddingFast:
proxy: http://localhost:8095
cmd: /app/Scripts/startEmbeddingFast.sh
cmdStop: /app/Scripts/stopEmbeddingFast.sh
checkEndpoint: /health
ttl: 600
DuckAi-Embedding:
proxy: http://localhost:8096
cmd: /app/Scripts/startEmbedding.sh
cmdStop: /app/Scripts/stopEmbedding.sh
checkEndpoint: /health
ttl: 600
groups:
default-models:
swap: false
exclusive: false
persistent: true
members:
- DuckAi-GeneralFast
- DuckAi-Chat
- DuckAi-Embedding
hooks:
on_startup:
preload:
- DuckAi-GeneralFast

18
Services/llamacpp/entrypoint.sh Normal file
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#!/bin/bash
set -e
CONFIG_FILE="/app/config.yaml"
PRESET_FILE="/app/config.preset.yaml"
echo "Checking configuration..."
# Se il file non esiste o è vuoto o non contiene 'models:', usa il preset
if [ ! -f "$CONFIG_FILE" ] || [ ! -s "$CONFIG_FILE" ] || ! grep -q "models:" "$CONFIG_FILE" 2>/dev/null; then
echo "Config file missing, empty, or invalid. Copying from preset..."
cp "$PRESET_FILE" "$CONFIG_FILE"
echo "Config file populated from preset."
else
echo "Config file found and valid."
fi
exec /app/llama-swap -config "$CONFIG_FILE" -listen :8080

101
Services/llamacpp/lamacpp-nginx.conf Normal file
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# Template Nginx per servizi containerizzati
# Sostituisci [DOMAIN], [UPSTREAM_NAME], [UPSTREAM_SERVER] con i valori appropriati
server {
listen 80;
server_name models.ai.duckpage.net;
return 301 https://$server_name$request_uri;
}
server {
listen 443 ssl;
listen [::]:443 ssl;
server_name models.ai.duckpage.net;
charset utf-8;
keepalive_timeout 70;
# SSL
ssl_certificate /etc/nginx/ssl/live/ai.duckpage.net/fullchain.pem;
ssl_certificate_key /etc/nginx/ssl/live/ai.duckpage.net/privkey.pem;
# Improve HTTPS performance with session resumption
ssl_session_cache shared:SSL:10m;
ssl_session_timeout 10m;
# SSL Protocols and Ciphers
ssl_protocols TLSv1.3;
ssl_prefer_server_ciphers off;
ssl_dhparam /etc/nginx/ssl/dhparam.pem;
ssl_ecdh_curve secp521r1:secp384r1;
# Security Headers
add_header Strict-Transport-Security "max-age=31536000; includeSubDomains";
add_header X-Frame-Options SAMEORIGIN always;
add_header X-Content-Type-Options nosniff always;
add_header X-Xss-Protection "1; mode=block" always;
# OCSP Stapling
ssl_stapling on;
ssl_stapling_verify on;
ssl_trusted_certificate /etc/nginx/ssl/live/ai.duckpage.net/fullchain.pem;
resolver 1.1.1.1 1.0.0.1 [2606:4700:4700::1111] [2606:4700:4700::1001] valid=300s;
resolver_timeout 5s;
client_max_body_size 512M;
client_body_buffer_size 128k;
# Gzip
gzip_types text/plain text/xml text/css application/xhtml+xml application/xml image/svg+xml application/rss+xml application/atom_xml application/javascript application/x-javascript application/x-httpd-php application/x-httpd-fastphp application/x-httpd-eruby;
# Main Proxy
location /v1 {
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_connect_timeout 600;
proxy_send_timeout 600;
proxy_read_timeout 600;
send_timeout 600;
proxy_redirect off;
proxy_set_header Host $http_host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_pass http://llamacpp:8080/v1;
}
location / {
# Allow specific IPs (replace with your actual IPs)
allow 127.0.0.1;
allow ::1;
allow 10.50.210.0/24;
allow 10.0.80.0/24;
# Add more allow lines for specific IPs, e.g., allow 192.168.1.0/24;
deny all;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_connect_timeout 600;
proxy_send_timeout 600;
proxy_read_timeout 600;
send_timeout 600;
proxy_redirect off;
proxy_set_header Host $http_host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_pass http://llamacpp:8080;
}
location ~ /\.ht {
deny all;
}
}

121
Services/llamacpp/llama-vulkan.Containerfile Normal file
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### LLaMACpp Builder Container with Vulkan for GPUs
### Multi-stage: download stage with pre-built binaries, runtime stage with only runtime libraries
###
### BUILD: podman build -t llamacpp:vulkan-amd64 -f llama-vulkan.Containerfile .
### Export: podman save -o /home/duckpage/llamacpp-vulkan-amd64.tar localhost/llamacpp:vulkan-amd64
ARG UBUNTU_VERSION=24.04
### Download image
FROM ubuntu:${UBUNTU_VERSION} AS download
RUN apt-get update \
&& apt-get install -y curl unzip grep sed \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /tmp
RUN VERSION=$(curl -s -I https://github.com/ggml-org/llama.cpp/releases/latest | grep -i location | sed 's|.*/tag/||' | tr -d '\r') \
&& echo "Last llama.cpp version: $VERSION" \
&& curl -L https://github.com/ggml-org/llama.cpp/releases/download/${VERSION}/llama-${VERSION}-bin-ubuntu-vulkan-x64.zip -o llama.zip \
&& unzip llama.zip \
&& rm llama.zip \
&& if [ -d llama-* ]; then mv llama-*/* . && rmdir llama-*; elif [ -d build ]; then mv build/* . && rmdir build; fi \
&& if [ -d bin ]; then mv bin/* . && rmdir bin; fi # flatten further
RUN mkdir -p /app/lib /app/full \
&& find . -name "*.so" -exec cp {} /app/lib \; \
&& cp -r * /app/full 2>/dev/null || true \
&& ls -la /app/full # list contents
## Base image
FROM ubuntu:${UBUNTU_VERSION} AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl nano ca-certificates wget\
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
COPY --from=download /app/lib/ /app
### Full
FROM base AS full
COPY --from=download /app/full /app
RUN chmod +x /app/llama-server
WORKDIR /app
RUN apt-get update \
&& apt-get install -y \
libvulkan-dev \
git \
python3-pip \
python3 \
python3-wheel\
&& pip install --break-system-packages --upgrade setuptools \
&& pip install --break-system-packages -U "huggingface_hub[cli]" \
&& if [ -f requirements.txt ]; then pip install --break-system-packages -r requirements.txt; fi \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
# -------- Model args (prefer Q6 to keep mmap on and avoid load issues) --------
ARG GENERAL_FAST_MODEL="-m models/gemma-3-1b-it-Q5_K_M.gguf"
ARG GENERAL_MODEL="-m models/gpt-oss-20b-Q4_K_M.gguf"
ARG CHAT_MODEL="-m models/Qwen3-VL-30B-A3B-Q4_K_S.gguf"
ARG CODER_MODEL="-m models/Qwen3-Coder-30B-A3B-Instruct-Q6_K.gguf"
ARG EMBEDDING_FAST_MODEL="-m models/embeddinggemma-300M-Q8_0.gguf"
ARG EMBEDDING_MODEL="-m models/bge-code-v1-q6_k.gguf"
# -------- Runtime defaults --------
ARG GENERAL_CONTEXT_SIZE=16384
ARG GENERAL_GPU_LAYERS=99
ARG GENERAL_MAX_TOKENS=512
ARG CODER_CONTEXT_SIZE=131072
ARG CODER_GPU_LAYERS=99
ARG CODER_MAX_TOKENS=512
ENV GENERAL_FAST_MODEL=${GENERAL_FAST_MODEL}
ENV GENERAL_MODEL=${GENERAL_MODEL}
ENV CODER_MODEL=${CODER_MODEL}
ENV EMBEDDING_FAST_MODEL=${EMBEDDING_FAST_MODEL}
ENV EMBEDDING_MODEL=${EMBEDDING_MODEL}
ENV GENERAL_CONTEXT_SIZE=${GENERAL_CONTEXT_SIZE}
ENV GENERAL_GPU_LAYERS=${GENERAL_GPU_LAYERS}
ENV GENERAL_MAX_TOKENS=${GENERAL_MAX_TOKENS}
ENV CODER_CONTEXT_SIZE=${CODER_CONTEXT_SIZE}
ENV CODER_GPU_LAYERS=${CODER_GPU_LAYERS}
ENV CODER_MAX_TOKENS=${CODER_MAX_TOKENS}
# -------- llama-swap --------
RUN curl -L https://github.com/mostlygeek/llama-swap/releases/download/v165/llama-swap_165_linux_amd64.tar.gz -o /tmp/llama-swap.tar.gz \
&& tar -xzf /tmp/llama-swap.tar.gz -C /app \
&& rm /tmp/llama-swap.tar.gz
# -------- start/stop scripts --------
# Nota: usiamo --threads -1 --threads-batch -1 per lasciare a llama.cpp l'autotuning
COPY ./Scripts/ /app/Scripts/
RUN chmod +x /app/Scripts/*.sh
# -------- Copy preset config file --------
COPY ./config.preset.yaml /app/config.preset.yaml
# -------- Copy entrypoint script --------
COPY ./entrypoint.sh /app/entrypoint.sh
RUN chmod +x /app/entrypoint.sh
ENTRYPOINT ["/app/entrypoint.sh"]

54
Services/llamacpp/llamacpp.container Normal file
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[Unit]
Name=llamacpp
[Container]
ContainerName=llamacpp
Image=localhost/llamacpp:rocm-amd64
Network=internal.network
#PublishPort=8080:8080
# ROCm
AddDevice=/dev/kfd
AddDevice=/dev/dri
PodmanArgs=--userns=keep-id --group-add=keep-groups --ipc=host
SecurityLabelType=container_runtime_t
# ROCm tuning
#Environment=HSA_OVERRIDE_GFX_VERSION=11.5.1
#Environment=ROCR_VISIBLE_DEVICES=0
#Environment=GPU_TARGETS=gfx1151
# API Key
#Environment=LLAMA_API_KEY=""
# Models
Environment=GENERAL_FAST_MODEL="-m models/gemma-3-1b-it-Q5_K_M.gguf"
Environment=GENERAL_MODEL="-m models/gpt-oss-20b-Q4_K_M.gguf"
Environment=CHAT_MODEL="-m models/Qwen3-VL-30B-A3B-Q4_K_S.gguf"
Environment=CODER_MODEL="-m models/Qwen3-Coder-30B-A3B-Instruct-Q6_K.gguf"
Environment=EMBEDDING_FAST_MODEL="-m models/embeddinggemma-300M-Q8_0.gguf"
Environment=EMBEDDING_MODEL="-m models/bge-code-v1-q6_k.gguf"
Environment=GENERAL_CONTEXT_SIZE=262144
Environment=GENERAL_GPU_LAYERS=99
Environment=GENERAL_MAX_TOKENS=512
Environment=CODER_CONTEXT_SIZE=131072
Environment=CODER_GPU_LAYERS=99
Environment=CODER_MAX_TOKENS=512
# Mount points
Volume=/srv/containers/aitools/models/llamacpp:/home/ubuntu/.cache/llama.cpp
Volume=/srv/containers/aitools/models/llamacpp:/app/models
Volume=/srv/containers/aitools/llamacpp_config.yaml:/app/config.yaml
[Service]
Restart=on-failure
TimeoutStartSec=15m
[Install]
WantedBy=multi-user.target default.target

23
Services/nginx/nginx.container Normal file
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[Unit]
Name=nginx
[Container]
ContainerName=nginx
Image=nginx:latest
#AutoUpdate=registry
Network=internal
Volume=/srv/containers/nginx/conf:/etc/nginx/conf.d:ro
Volume=/srv/containers/nginx/html:/usr/share/nginx/html:ro
Volume=/srv/containers/nginx/ssl:/etc/nginx/ssl:ro
PublishPort=80:80
PublishPort=443:443
[Service]
TimeoutStartSec=5m
Restart=always
[Install]
WantedBy=multi-user.target default.target

20
Services/searxng/searxng.container Normal file
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[Unit]
Name=searxng
[Container]
ContainerName=searxng
Image=docker.io/searxng/searxng:latest
#AutoUpdate=registry
Network=internal.network
#PublishPort=8888:8080
# Production
Volume=/srv/containers/aitools/searxng/config:/etc/searxng
Volume=/srv/containers/aitools/searxng/data:/var/cache/searxng
[Service]
TimeoutStartSec=5m
Restart=on-failure
[Install]
WantedBy=multi-user.target default.target

73
install.sh Normal file
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#!/bin/bash
set -e
# Modifica questa variabile con l'URL raw del tuo repository remoto
REPO_URL="https://raw.githubusercontent.com/yourusername/yourrepo/main"
echo "Iniziando l'installazione di BDI Podman Serverconf..."
# 1. Aggiornare il sistema Ubuntu
echo "Aggiornando il sistema..."
sudo apt update && sudo apt upgrade -y
# 2. Aggiungere utente ai gruppi render e video
echo "Aggiungendo utente ai gruppi render e video..."
sudo usermod -a -G render,video $LOGNAME
# 3. Installare podman
echo "Installando podman..."
sudo apt install -y podman
# 4. Creare cartelle per systemd containers
echo "Creando cartelle per containers systemd..."
mkdir -p ~/.config/containers/systemd
# 5. Scaricare e copiare internal.network
echo "Scaricando internal.network..."
curl -fsSL $REPO_URL/internal.network -o ~/.config/containers/systemd/internal.network
# 6. Aggiungere registri a /etc/containers/registries.conf
echo "Aggiungendo registri a registries.conf..."
echo -e "[registries.search]\nregistries = [\"docker.io\", \"quay.io\", \"ghcr.io\"]" | sudo tee -a /etc/containers/registries.conf > /dev/null
# 7. Creare /srv/containers e assegnare permessi
echo "Creando /srv/containers e assegnando permessi..."
sudo mkdir -p /srv/containers
sudo chown -R $LOGNAME /srv/containers
# 8. Creare sottocartelle per aitools
echo "Creando cartelle per aitools..."
mkdir -p /srv/containers/aitools/{models,.cache}
# 9. Creare file vuoto llamacpp_config.yaml
echo "Creando llamacpp_config.yaml..."
touch /srv/containers/aitools/llamacpp_config.yaml
# 10. Aggiornare GRUB
echo "Aggiornando GRUB..."
sudo sed -i 's/GRUB_CMDLINE_LINUX_DEFAULT=.*/GRUB_CMDLINE_LINUX_DEFAULT="amdgpu.gttsize=24576 amdttm.pages_limit=27648000"/' /etc/default/grub
sudo update-grub
# 11. Scaricare e installare banner.sh
echo "Scaricando e installando banner MOTD..."
sudo curl -fsSL $REPO_URL/banner.sh -o /etc/update-motd.d/99-duckai-banner
sudo chmod +x /etc/update-motd.d/99-duckai-banner
# 12. Disabilitare altri script MOTD
echo "Disabilitando altri script MOTD..."
sudo bash -c 'for f in /etc/update-motd.d/*; do [[ "$f" != "/etc/update-motd.d/99-duckai-banner" ]] && mv "$f" "${f}.disabled"; done'
# 13. Scaricare e installare badai
echo "Scaricando e installando badai..."
sudo curl -fsSL $REPO_URL/badai -o /usr/local/bin/badai
sudo chmod +x /usr/local/bin/badai
# 14. Scaricare container files
echo "Scaricando file container..."
curl -fsSL $REPO_URL/Services/llamacpp/llamacpp.container -o ~/.config/containers/systemd/llamacpp.container
curl -fsSL $REPO_URL/Services/nginx/nginx.container -o ~/.config/containers/systemd/nginx.container
# 15. Riavviare il sistema
echo "Installazione completata. Riavviando il sistema..."
sudo reboot

12
internal.network Normal file
مشاهده پرونده

@@ -0,0 +1,12 @@
[Unit]
Description=Internal network for containers
After=network-online.target
[Network]
NetworkName=internal
Subnet=10.10.0.0/24
Gateway=10.10.0.1
DNS=9.9.9.9
[Install]
WantedBy=default.target