GPT-5.3-Codex
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@@ -118,6 +118,7 @@ curl http://127.0.0.1:8000/v1/chat/completions \
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- `gpt-5.2`
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- `gpt-5-codex`
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- `gpt-5.2-codex`
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- `gpt-5.3-codex`
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- `gpt-5.1-codex`
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- `gpt-5.1-codex-max`
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- `gpt-5.1-codex-mini`
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@@ -129,7 +130,7 @@ curl http://127.0.0.1:8000/v1/chat/completions \
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- `--reasoning-effort` (choice of minimal,low,medium,high,xhigh)<br>
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GPT-5 has a configurable amount of "effort" it can put into thinking, which may cause it to take more time for a response to return, but may overall give a smarter answer. Applying this parameter after `serve` forces the server to use this reasoning effort by default, unless overrided by the API request with a different effort set. The default reasoning effort without setting this parameter is `medium`.<br>
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The `gpt-5.1` family (including codex) supports `low`, `medium`, and `high` while `gpt-5.1-codex-max` adds `xhigh`. The `gpt-5.2` family (including codex) supports `low`, `medium`, `high`, and `xhigh`.
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The `gpt-5.1` family (including codex) supports `low`, `medium`, and `high` while `gpt-5.1-codex-max` adds `xhigh`. The `gpt-5.2` and `gpt-5.3` families (including codex) support `low`, `medium`, `high`, and `xhigh`.
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### Thinking summaries
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@@ -173,4 +174,3 @@ When the model returns a thinking summary, the model will send back thinking tag
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[](https://www.star-history.com/#RayBytes/ChatMock&Timeline)
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@@ -11,6 +11,8 @@ def allowed_efforts_for_model(model: str | None) -> Set[str]:
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if not base:
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return DEFAULT_REASONING_EFFORTS
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normalized = base.split(":", 1)[0]
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if normalized.startswith("gpt-5.3"):
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return {"low", "medium", "high", "xhigh"}
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if normalized.startswith("gpt-5.2"):
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return {"low", "medium", "high", "xhigh"}
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if normalized.startswith("gpt-5.1-codex-max"):
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@@ -71,7 +71,7 @@ def ollama_version() -> Response:
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def _instructions_for_model(model: str) -> str:
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base = current_app.config.get("BASE_INSTRUCTIONS", BASE_INSTRUCTIONS)
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if model.startswith("gpt-5-codex") or model.startswith("gpt-5.1-codex") or model.startswith("gpt-5.2-codex"):
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if "codex" in (model or "").lower():
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codex = current_app.config.get("GPT5_CODEX_INSTRUCTIONS") or GPT5_CODEX_INSTRUCTIONS
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if isinstance(codex, str) and codex.strip():
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return codex
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@@ -97,6 +97,7 @@ def ollama_tags() -> Response:
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"gpt-5",
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"gpt-5.1",
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"gpt-5.2",
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"gpt-5.3-codex",
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"gpt-5-codex",
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"gpt-5.2-codex",
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"gpt-5.1-codex",
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@@ -125,6 +126,10 @@ def ollama_tags() -> Response:
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"gpt-5.2-codex-high",
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"gpt-5.2-codex-medium",
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"gpt-5.2-codex-low",
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"gpt-5.3-codex-xhigh",
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"gpt-5.3-codex-high",
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"gpt-5.3-codex-medium",
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"gpt-5.3-codex-low",
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"gpt-5.1-codex-high",
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"gpt-5.1-codex-medium",
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"gpt-5.1-codex-low",
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@@ -59,7 +59,7 @@ def _wrap_stream_logging(label: str, iterator, enabled: bool):
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def _instructions_for_model(model: str) -> str:
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base = current_app.config.get("BASE_INSTRUCTIONS", BASE_INSTRUCTIONS)
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if model.startswith("gpt-5-codex") or model.startswith("gpt-5.1-codex") or model.startswith("gpt-5.2-codex"):
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if "codex" in (model or "").lower():
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codex = current_app.config.get("GPT5_CODEX_INSTRUCTIONS") or GPT5_CODEX_INSTRUCTIONS
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if isinstance(codex, str) and codex.strip():
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return codex
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@@ -535,6 +535,7 @@ def list_models() -> Response:
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("gpt-5", ["high", "medium", "low", "minimal"]),
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("gpt-5.1", ["high", "medium", "low"]),
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("gpt-5.2", ["xhigh", "high", "medium", "low"]),
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("gpt-5.3-codex", ["xhigh", "high", "medium", "low"]),
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("gpt-5-codex", ["high", "medium", "low"]),
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("gpt-5.2-codex", ["xhigh", "high", "medium", "low"]),
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("gpt-5.1-codex", ["high", "medium", "low"]),
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@@ -45,6 +45,9 @@ def normalize_model_name(name: str | None, debug_model: str | None = None) -> st
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"gpt5.2": "gpt-5.2",
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"gpt-5.2": "gpt-5.2",
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"gpt-5.2-latest": "gpt-5.2",
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"gpt5.3-codex": "gpt-5.3-codex",
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"gpt-5.3-codex": "gpt-5.3-codex",
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"gpt-5.3-codex-latest": "gpt-5.3-codex",
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"gpt5.2-codex": "gpt-5.2-codex",
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"gpt-5.2-codex": "gpt-5.2-codex",
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"gpt-5.2-codex-latest": "gpt-5.2-codex",
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