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OpenAI (GPT)

Uses SSE streaming. Tool calls arrive as function_call objects. Best for: General-purpose tasks, broad knowledge, fast responses.

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Getting an API Key

  1. Go to platform.openai.com
  2. Sign up or log in
  3. Navigate to API Keys and create a new key
  4. Paste it into Wolffish → Settings → Models → OpenAI

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Models

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GPT-5 family (reasoning)

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o-series (reasoning)

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GPT-4 family (non-reasoning)

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Reasoning modes

How this model reasons is set in the model card beside the chat input — hover the model switch to preview the card, click to pin it open. The top chip row, labelled Thinking, is the control: pick a chip and it applies from your next message. Two separate ideas combine here:

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Thinking — whether the model reasons

  • Off — the model answers immediately. Fastest and cheapest; ideal for simple, direct tasks.
  • On (the chip reads Normal) — the model first works through the problem in a dedicated reasoning pass before replying. Slower and uses more tokens, but markedly more accurate on multi-step, logical, or ambiguous tasks.

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Effort — how hard it thinks

Only effort-capable models expose this; it applies once thinking is on.
  • High — standard reasoning depth. The right default for most agentic work.
  • Max — the model reasons longer and deeper for the hardest problems. More tokens and latency in exchange for higher quality on complex work.

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The chip row

The active chip is tinted; the rest sit quiet. Each model shows only the chips it genuinely supports — a model that always reasons has no Off, a model with a single mode shows that one chip inert, and a model that can’t reason at all replaces the row with “Reasoning is not supported by this model.” Wolffish remembers your choice per model. (Before v1.0.236 this was a colour-coded brain button on the composer; it moved into the model card, beside the Single/Workflow row, so every model knob sits in one panel.) On OpenAI: GPT-5 and o-series models support Off / High / Max (Max maps to OpenAI’s xhigh effort). Note: OpenAI’s chat API can’t combine reasoning effort with tool calls, so during tool-using turns Wolffish drops the effort and the model reasons at its default.