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Table of Contents
TL;DRWhy translate your scripts at allArchitecture: structure your resource for translationRecommended resource layoutfxmanifest.luashared/i18n.lua (lightweight loader + interpolation)Usage in client/server codelocales/en.json (source of truth)The AI translation workflowStep 1: Extract and freeze the sourceStep 2: Build a glossaryStep 3: Protect placeholders

How to Translate FiveM Scripts with AI: The Complete 2026 Workflow

Veröffentlicht am 17. August 2025·von Lars Miller(Founder & Lead Editor)·Profil·2 Min. Lesezeit·Aktualisiert am 18. Mai 2026
Scripts & Ressourcentranslate fivem scripts

Translate FiveM scripts to any language using AI — without breaking placeholders, color codes, or UI layout. Complete workflow covering locale architecture, DeepL and OpenAI pipelines, automated QA checks, and ESX/QBCore integration.

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How to Translate FiveM Scripts with AI: The Complete 2026 Workflow
How to Translate FiveM Scripts with AI: The Complete 2026 Workflow

Translating to a new language used to mean hiring a translator, waiting two weeks, and dealing with broken placeholders when the file came back. With modern AI — DeepL, GPT-4, Claude — a 500-string locale file can be translated, QA-checked, and shipped in under an hour, at production quality.

This guide covers the full workflow: locale file architecture that scales, placeholder protection that actually works, a working Node.js pipeline for both DeepL and OpenAI, automated QA checks, and framework-specific notes for ESX, QBCore, and QBox.

TL;DR

Translating FiveM Scripts Using AI Tools

  • Centralize every user-visible string in locale files (locales/en.json, locales/de.json, etc.). No hardcoded strings in gameplay code.
  • Protect placeholders (%s, %d, %{name}, ~r~, ^1) with unique tokens before translating.
  • Use DeepL for major European languages, GPT-4 for edge cases or nuanced context.
  • Run a glossary pre-pass, translate, restore placeholders, then a regex parity check in CI.
  • Keep en.json as single source of truth; diff and translate only changed keys.

Why translate your scripts at all

  • Player retention — localized servers keep non-English speakers engaged past the first session.
  • Professional polish — consistent terminology across commands, UI, and error messages separates serious servers from hobby ones.
  • Community contribution friendly — clean locale files invite PRs for languages you don't speak.
  • SEO and discovery — servers that advertise multi-language support rank better on server lists for non-English queries.

Häufig gestellte Fragen

Why translate FiveM scripts with AI instead of by hand?

AI handles the 90% of routine strings (notifications, UI labels, error messages) in seconds, letting you focus human review on the 10% that actually needs it — commands, nuanced UI, and branding. DeepL and modern LLMs produce near-native quality for German, French, Spanish, and Portuguese out of the box. Hand-translating 500 strings takes a full day; an AI pipeline plus human review takes an hour.

What's the biggest risk when translating scripts with AI?

Broken placeholders. If the AI translates '%{playerName}' as '%{spielername}' or drops a '~r~' color code, the script will either crash or display malformed text in-game. The fix is placeholder protection: substitute placeholders with tokens the AI won't touch (like ⟦playerName⟧), translate, then restore. Combine with a regex-based parity check in CI to catch any mismatches before shipping.

DeepL or OpenAI for FiveM script translation?

DeepL for German, French, Spanish, Portuguese — it's faster, cheaper, and produces more natural phrasing for European languages. OpenAI (GPT-4 class models) for any language DeepL doesn't support, or when you need context-aware translation (e.g., distinguishing 'arrest' the command from 'arrest' the player status). Use DeepL as the default, fall back to GPT-4 for edge cases.

How do I protect placeholders during translation?

Replace every placeholder with a unique token the translator won't modify: '%{name}' becomes '⟦name⟧', '%s' becomes '⟪S⟫', '~r~' becomes '⟪COLOR_R⟫'. Translate the text, then restore the original placeholders by reversing the substitution. This works reliably across DeepL, GPT, Gemini, and any other translator because the tokens look like foreign words to the model and pass through unchanged.

Table of Contents

TL;DRWhy translate your scripts at allArchitecture: structure your resource for translationRecommended resource layoutfxmanifest.luashared/i18n.lua (lightweight loader + interpolation)Usage in client/server codelocales/en.json (source of truth)The AI translation workflowStep 1: Extract and freeze the sourceStep 2: Build a glossaryStep 3: Protect placeholders

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Architecture: structure your resource for translation

The cardinal rule is zero user-visible strings inside gameplay code. Everything routes through a locale layer.

Recommended resource layout

my_resource/
├─ fxmanifest.lua
├─ locales/
│  ├─ en.json        # source language (single source of truth)
│  ├─ de.json        # generated + human-reviewed
│  ├─ es.json        # generated + human-reviewed
│  ├─ fr.json        # generated + human-reviewed
│  └─ qa.rules.json  # optional: placeholder whitelist
├─ client/
│  └─ main.lua
├─ server/
│  └─ main.lua
└─ shared/
   └─ i18n.lua       # translation helper

fxmanifest.lua

fx_version 'cerulean'
game 'gta5'
lua54 'yes'

shared_scripts {
    'shared/i18n.lua',
}

files {
    'locales/*.json',
}

shared/i18n.lua (lightweight loader + interpolation)

local LOCALE = GetConvar('my_locale', 'en')
local CACHE = {}

local function loadJSON(path)
    local file = io.open(path, 'r')
    if not file then return {} end
    local content = file:read('*a')
    file:close()
    local ok, data = pcall(function() return json.decode(content) end)
    return ok and data or {}
end

local function readLocale(lang)
    if CACHE[lang] then return CACHE[lang] end
    local dict = loadJSON(('locales/%s.json'):format(lang))
    CACHE[lang] = dict
    return dict
end

local function interpolate(str, vars)
    if not vars then return str end
    for k, v in pairs(vars) do
        str = str:gsub('%%{' .. k .. '}', tostring(v))
    end
    return str
end

function _U(key, vars)
    local dict = readLocale(LOCALE)
    local src = dict[key] or readLocale('en')[key] or key
    return interpolate(src, vars)
end

exports('Translate', _U)

Usage in client/server code

-- Client
lib.notify({
    title = _U('notify_title'),
    description = _U('welcome_player', { name = GetPlayerName(PlayerId()) })
})

-- Server
print(('[MyRes] %s'):format(_U('server_started')))

locales/en.json (source of truth)

{
    "notify_title": "Server Message",
    "welcome_player": "Welcome, %{name}!",
    "server_started": "Server module is ready.",
    "no_permission": "You do not have permission.",
    "items_remaining": "%{count} items remaining"
}

Everything in your gameplay code now routes through _U(key) — no hardcoded strings means no translation drift when you add or change features.

The AI translation workflow

Step 1: Extract and freeze the source

Lock locales/en.json before touching any translation tooling. Enforce a key naming convention like domain.action.subject (inventory.drop.confirm, police.arrest.success) so keys stay stable across refactors.

Step 2: Build a glossary

A glossary maps framework-specific or brand-specific terms to canonical translations. CSV is fine:

source,de,fr,es
EMS,Rettungsdienst,Urgences,Emergencias
PD,Polizei,Police,Policía
Mechanic,Mechaniker,Mécanicien,Mecánico
Citizenid,Citizenid,Citizenid,Citizenid

Glossary discipline matters — this is what separates professional localization from machine-translated slop.

Step 3: Protect placeholders

Before the text hits the translator, substitute every placeholder and color code with a unique token the model won't modify:

| Original | Token | |

How do I handle ESX/QBCore-specific terminology?

Build a glossary (CSV or JSON) of framework-specific terms with canonical translations: 'EMS' → 'Rettungsdienst' in German, 'citizenid' stays as 'citizenid', '/report' stays as '/report'. Apply the glossary as a pre-pass before sending to the translator, and enforce it in your prompt ('Keep these terms unchanged: …'). Glossary discipline is what separates a professional server localization from a machine-translated mess.

What should I check before shipping translated locales?

Five gates: (1) valid JSON/Lua parse, (2) placeholder parity (every %{var} in source present in target), (3) forbidden-change list (commands, color codes, keybinds untouched), (4) length budget (UI strings not more than 40% longer than source), (5) human spot-check on 20 random strings. Automate gates 1-4 in CI; only gate 5 requires a human.

How do I keep translations in sync when I change source strings?

Treat en.json as the single source of truth and diff it against target locales on every commit. A small CI script can identify new keys (translate them), changed English values (re-translate), and orphaned keys in targets (delete them). Store previous outputs as a translation memory so unchanged keys are never re-translated — this saves money on API calls and keeps community-reviewed translations stable.

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