# --------------------------------------------------
# Mistral-Specific Settings (Optional)
# --------------------------------------------------

# Budgets for the adaptive rate limiter. Mistral enforces a per-MINUTE request
# limit and a per-minute token limit, both PER-MODEL (e.g. mistral-medium is
# 25 req/min, ministral-3b is 750/min). The tool reads these from the live
# ratelimit response headers and paces calls so you never trip a 429 — so
# these seeds only matter for the very first request of a run.
# mistralReqPerSec is the per-SECOND seed (req-per-minute / 60).
#mistralReqPerSec="0.5"
#mistralTokPerMin="50000"
#mistralTokenHeadroom="4000"

# --------------------------------------------------
# Gemini-Specific Settings (Optional)
# --------------------------------------------------

# Sets the thinking budget for Gemini models.
# - To turn on dynamic thinking, set to -1.
# - To disable thinking (on compatible models like 2.5 Flash), set to 0.
# - To set a specific token budget, use a positive integer (e.g., 8192).
# - Leave this variable out to use the model's default setting.
GEMINI_THINKING_BUDGET=

# Set to "gemini" to use the Gemini API, "mistral" for Mistral (la Plateforme),
# or "openai" for OpenAI-compatible APIs (If empty it will default to openai.)
API_PROVIDER=openai

# API URL, leave blank to use OpenAI API.
# Nvidia example: "https://integrate.api.nvidia.com/v1/"
# Mistral example: "https://api.mistral.ai/v1/"
api=""

# API key
key=""

#Oranization key, make something up for self hosted or other API. If using Nvidia API, leave it blank or it can get wonky
organization=""

# LLM model name.
# Default below works for OpenAI; for Gemini/Nvidia set your provider model name.
# For Mistral, "mistral-medium-3.5" is the recommended model
# (avoid "mistral-medium-latest" — it still points at the older 3.1).
model="gpt-4.1"

#The language to translate TO, Don't forget to change the prompt
language="English"

#The timeout before disconnect error, 30 to 120 recommended
timeout="120"

#The number of files to translate at the same time, 1 recommended for free or self hosted API or gpt-4
fileThreads="5"

#Concurrent API calls per file (threads per file), 1 recommended for free or self hosted API or gpt-4
threads="1"

#The wordwrap of dialogue text
width="60"

#The wordwrap of items and help text
listWidth="100"

#The wordwrap of items and help text
noteWidth="75"

# WolfDawn database (Step 4): limit which DB sheets are translated (JSON array of group keys)
#wolfDbIncludeGroups='["DataBase.project.json|Skill · 技能"]'
#wolfDbIncludeTiers='["foundation","system"]'

#CSV delimiter character (comma, semicolon, or tab)
csvDelimiter=","

# Custom input API cost - default value for gpt-3.5, replace with your actual input API cost - depends on the model, see https://openai.com/pricing
input_cost= 0.002

# Custom output API cost - default value for gpt-3.5, replace with your actual input API cost - depends on the model, see https://openai.com/pricing
output_cost= 0.002

# Batch size - adjust according to your API's limitations
batchsize="10"

# Frequency penalty - adjust according to your needs
frequency_penalty= 0.2

# TL Inspector (Step 8 playtest) — editor opened when clicking a source line in-game
# tlEditorCmd: 'auto' scans for VS Code / Cursor, or set an absolute path to any editor exe
tlEditorCmd='auto'
# Hotkeys (event.key names, e.g. F9, F10, Control)
tlHotkey='F9'
forgeHotkey='F10'
# UI scale for in-game overlays: auto (match game width) or a number like 1.5 / 2
playtestUiScale='auto'