v3 M2: OpenAI Codex provider — real rate-limit % from local Codex rollouts

OpenAICodexProvider replaces the openai stub. It reads the rate-limit snapshot
the Codex CLI already records locally (no second auth): each turn Codex writes a
token_count event into $CODEX_HOME/sessions/**/rollout-*.jsonl whose
payload.rate_limits mirrors Claude's model — primary (5h) + secondary (weekly),
each with used_percent + resets_at + plan_type. The provider surfaces the
freshest such snapshot; a window whose reset time has passed is reported as a
fresh 0% (local read, so current in-session and self-heals between sessions).

primary -> s/sr, secondary -> w/wr, plan_type -> status ("Plus"/…),
rate_limit_reached_type -> "limited". No per-token cost (subscription), so the
two rate-limit bars are the metric, per the locked v3 decision.

Verified against the real ~/.codex: full daemon payload with openai active =
{pv:openai, pnm:"OpenAI Codex", ac:0x10a37f, st:"Plus", ok:true, weekly reset}.
registry test updated (openai now real, zai still stub); +7 provider tests.
113 passed, 2 Linux-only failures (baseline). spec: hiddenimport added.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

daemon/providers/openai_codex.py

@@ -0,0 +1,127 @@
+"""OpenAI Codex provider (v3 M2).
+
+Reads the ChatGPT/Codex rate-limit utilization the Codex CLI already records
+locally, so there's no second auth to maintain: every turn, Codex writes a
+``token_count`` event into its session rollout (``$CODEX_HOME/sessions/**/rollout-*.jsonl``)
+whose ``info.rate_limits`` snapshot mirrors Claude's model — a primary window
+(5h) and a secondary window (weekly), each with a used-percent and a reset time::
+
+    "rate_limits": {"primary":   {"used_percent": 1.0,  "window_minutes": 300,   "resets_at": 178...},
+                    "secondary": {"used_percent": 0.0,  "window_minutes": 10080, "resets_at": 178...},
+                    "plan_type": "plus", "rate_limit_reached_type": null}
+
+We surface the freshest such snapshot. It's a local read (no network, no token),
+so it's current while Codex is in use and goes stale between sessions — when a
+window's ``resets_at`` has already passed we report that window as a fresh 0%.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import os
+import time
+from pathlib import Path
+
+from .base import Provider, ProviderStatus
+
+# Newest-first cap: the active session's rollout has the latest reading, so we
+# rarely look past the first file — but scan a few in case the newest is a
+# just-opened session with no turns (hence no rate_limits) yet.
+_MAX_ROLLOUTS_SCANNED = 12
+
+
+def _codex_home() -> Path:
+    return Path(os.environ.get("CODEX_HOME") or (Path.home() / ".codex"))
+
+
+class OpenAICodexProvider(Provider):
+    id = "openai"
+    label = "OpenAI Codex"
+    accent = "10a37f"        # brand green
+
+    def __init__(self, codex_home: str | os.PathLike | None = None) -> None:
+        self._home = Path(codex_home) if codex_home else _codex_home()
+
+    async def poll(self) -> ProviderStatus:
+        from daemon.claude_usage_daemon_windows import log
+        try:
+            snap = await asyncio.to_thread(self._latest_rate_limits)
+        except Exception as e:                      # never break the loop (SC#5)
+            log(f"Codex poll error: {e!r}")
+            return ProviderStatus(ok=False, st="error")
+        if snap is None:
+            # Configured but nothing to read (Codex never run / logged out).
+            return ProviderStatus(ok=False, st="no data")
+        return self._to_status(snap)
+
+    # -- local rollout reading -------------------------------------------------
+
+    def _latest_rate_limits(self) -> dict | None:
+        """The freshest non-empty ``rate_limits`` object from the most recently
+        written session rollout. Pure/sync — run via asyncio.to_thread."""
+        sessions = self._home / "sessions"
+        if not sessions.is_dir():
+            return None
+        try:
+            files = sorted(sessions.rglob("rollout-*.jsonl"),
+                           key=lambda p: p.stat().st_mtime, reverse=True)
+        except OSError:
+            return None
+        for path in files[:_MAX_ROLLOUTS_SCANNED]:
+            found = None
+            try:
+                with path.open(encoding="utf-8", errors="replace") as fh:
+                    for line in fh:
+                        if '"rate_limits"' not in line:
+                            continue
+                        try:
+                            obj = json.loads(line)
+                        except ValueError:
+                            continue
+                        # token_count events carry rate_limits as a sibling of
+                        # info under payload; tolerate the info-nested shape too.
+                        payload = obj.get("payload") or {}
+                        rl = payload.get("rate_limits")
+                        if not isinstance(rl, dict):
+                            rl = (payload.get("info") or {}).get("rate_limits")
+                        if isinstance(rl, dict) and (rl.get("primary") or rl.get("secondary")):
+                            found = rl          # keep the LAST one in the file
+            except OSError:
+                continue
+            if found is not None:
+                return found                    # newest file that has a reading wins
+        return None
+
+    # -- mapping ---------------------------------------------------------------
+
+    @staticmethod
+    def _window(w: dict | None) -> tuple[float, int]:
+        """(used_percent 0-100, minutes-to-reset) for one window. A reset time
+        already in the past means the window rolled over since the snapshot, so
+        report it as a fresh 0% with an unknown reset."""
+        if not isinstance(w, dict):
+            return 0.0, -1
+        used = float(w.get("used_percent") or 0.0)
+        resets_at = w.get("resets_at")
+        if isinstance(resets_at, (int, float)):
+            delta = resets_at - time.time()
+            if delta <= 0:
+                return 0.0, -1
+            return used, int(delta // 60)
+        return used, -1
+
+    def _to_status(self, rl: dict) -> ProviderStatus:
+        s, sr = self._window(rl.get("primary"))
+        w, wr = self._window(rl.get("secondary"))
+        reached = rl.get("rate_limit_reached_type")
+        plan = rl.get("plan_type")
+        if reached:
+            st = "limited"
+        elif plan:
+            st = str(plan).capitalize()         # "Plus" / "Pro" / "Team" / ...
+        else:
+            st = "allowed"
+        # Subscription plan → no per-token cost; the two rate-limit bars are the
+        # metric (matches the locked v3 decision). tokens/cost left at 0.
+        return ProviderStatus(s=s, sr=sr, w=w, wr=wr, st=st, ok=True)