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Normalize model metadata for OpenAI-compatible providers - #621

Merged
zemaj merged 3 commits into
just-every:mainfrom
voarsh2:pr/model-proxy-20260924
Sep 24, 2026
Merged

zemaj merged 3 commits into
just-every:mainfrom
voarsh2:pr/model-proxy-20260924

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@voarsh2

@voarsh2 voarsh2 commented Sep 24, 2026 •

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Summary

  • Prevent custom and OpenAI-compatible proxy providers from inheriting first-party OpenAI Responses Lite metadata.
  • Keep model-preferred WebSocket behavior provider-aware at the request boundary.
  • Restrict remote /models discovery to Codex-backend or command-backed provider authentication.
  • Preserve user provider metadata across session, memory, review, auto-context, and forced model paths.
  • Extend the existing 1M context mode to GPT-5.6 Luna, Terra, and Sol.

Motivation

OpenAI-compatible proxies can expose the same model slugs as first-party OpenAI, but they do not necessarily support OpenAI-only transport and request semantics. This change keeps those providers on ordinary Responses behavior instead of silently adopting provider-specific metadata from embedded OpenAI model definitions.

Remote model discovery is also gated consistently so bare OpenAI-compatible /models responses are not treated as authoritative Codex ModelInfo catalogs.

The 5.6 models advertise the same 1M context capability as GPT-5.4 in this code-rs architecture, so they now participate in the existing context-mode selection rather than being capped at the 272K default.

No gateway-specific addresses, model names in code paths, or user-facing configuration knobs are added.

voarsh and others added 3 commits September 24, 2026 07:02
Prevents embedded first-party capabilities from leaking
into proxy and custom-provider requests.

Preserves remote overrides for the supported first-party
path while using conservative fallback metadata elsewhere.
Avoids treating arbitrary provider model endpoints as
authoritative Codex metadata sources.

Keeps refreshes available for Codex-backed and command
authentication flows that provide the expected schema.
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3 participants