100 lines
3.8 KiB
Text
100 lines
3.8 KiB
Text
# --------------------------------------------------
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# Mistral-Specific Settings (Optional)
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# --------------------------------------------------
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# Budgets for the adaptive rate limiter. Mistral enforces a per-MINUTE request
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# limit and a per-minute token limit, both PER-MODEL (e.g. mistral-medium is
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# 25 req/min, ministral-3b is 750/min). The tool reads these from the live
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# ratelimit response headers and paces calls so you never trip a 429 — so
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# these seeds only matter for the very first request of a run.
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# mistralReqPerSec is the per-SECOND seed (req-per-minute / 60).
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#mistralReqPerSec="0.5"
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#mistralTokPerMin="50000"
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#mistralTokenHeadroom="4000"
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# --------------------------------------------------
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# Gemini-Specific Settings (Optional)
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# --------------------------------------------------
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# Sets the thinking budget for Gemini models.
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# - To turn on dynamic thinking, set to -1.
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# - To disable thinking (on compatible models like 2.5 Flash), set to 0.
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# - To set a specific token budget, use a positive integer (e.g., 8192).
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# - Leave this variable out to use the model's default setting.
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GEMINI_THINKING_BUDGET=
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# Set to "gemini" to use the Gemini API, "mistral" for Mistral (la Plateforme),
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# or "openai" for OpenAI-compatible APIs (If empty it will default to openai.)
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API_PROVIDER=openai
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# API URL, leave blank to use OpenAI API.
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# Nvidia example: "https://integrate.api.nvidia.com/v1/"
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# Mistral example: "https://api.mistral.ai/v1/"
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api=""
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# API key
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key=""
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#Oranization key, make something up for self hosted or other API. If using Nvidia API, leave it blank or it can get wonky
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organization=""
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# LLM model name.
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# Default below works for OpenAI; for Gemini/Nvidia set your provider model name.
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# For Mistral, "mistral-medium-3.5" is the recommended model
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# (avoid "mistral-medium-latest" — it still points at the older 3.1).
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model="gpt-4.1"
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#The language to translate TO, Don't forget to change the prompt
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language="English"
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#The timeout before disconnect error, 30 to 120 recommended
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timeout="120"
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#The number of files to translate at the same time, 1 recommended for free or self hosted API or gpt-4
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fileThreads="5"
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#Concurrent API calls per file (threads per file), 1 recommended for free or self hosted API or gpt-4
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threads="1"
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#The wordwrap of dialogue text
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width="60"
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#The wordwrap of items and help text
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listWidth="100"
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#The wordwrap of items and help text
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noteWidth="75"
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# WolfDawn names.json (Step 3): re-wrap selected note categories with dazedwrap
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#wolfNameWrap="false"
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#wolfNameWrapWidth="60"
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#wolfNameWrapNotes='["├■プロフィール","説明"]'
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# WolfDawn dialogue wrap at translate time is optional / advanced; normal workflow
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# leaves line breaks alone; optional `wolf relayout` after inject (Step 5, off by default).
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#wolfWrap="false"
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#wolfWidth="55"
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#CSV delimiter character (comma, semicolon, or tab)
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csvDelimiter=","
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# 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
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input_cost= 0.002
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# 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
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output_cost= 0.002
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# Batch size - adjust according to your API's limitations
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batchsize="10"
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# Frequency penalty - adjust according to your needs
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frequency_penalty= 0.2
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# TL Inspector (Step 8 playtest) — editor opened when clicking a source line in-game
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# tlEditorCmd: 'auto' scans for VS Code / Cursor, or set an absolute path to any editor exe
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tlEditorCmd='auto'
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# Hotkeys (event.key names, e.g. F9, F10, Control)
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tlHotkey='F9'
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forgeHotkey='F10'
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# UI scale for in-game overlays: auto (match game width) or a number like 1.5 / 2
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playtestUiScale='auto'
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