Hermes-agent

hermes_cli/codex_models.py

@@ -0,0 +1,206 @@
+"""Codex model discovery from API, local cache, and config."""
+
+from __future__ import annotations
+
+import json
+import logging
+from pathlib import Path
+from typing import List, Optional
+
+import os
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_CODEX_MODELS: List[str] = [
+    "gpt-5.5",
+    "gpt-5.4-mini",
+    "gpt-5.4",
+    "gpt-5.3-codex",
+    # gpt-5.3-codex-spark is in research preview and is exposed *only* via
+    # the Codex CLI / OAuth backend (chatgpt.com/backend-api/codex/models)
+    # for ChatGPT Pro subscribers. It is NOT available in the public OpenAI
+    # API, so it intentionally stays out of the "openai" provider catalog
+    # in hermes_cli/models.py — only the openai-codex (OAuth) provider
+    # surfaces it. The Codex backend reports ``supported_in_api: false`` for
+    # this slug; that flag describes API availability, not Codex backend
+    # availability, so the fetch/cache code paths below intentionally do
+    # not filter on it. PR #12994 removed this entry on the assumption it
+    # was unsupported — that was wrong; restored here. Keep it in the
+    # curated fallback so Pro users still see Spark in `/model` when live
+    # discovery is unavailable (offline first run, transient API failure).
+    "gpt-5.3-codex-spark",
+    # NOTE: gpt-5.2-codex / gpt-5.1-codex-max / gpt-5.1-codex-mini were
+    # previously listed here but the chatgpt.com Codex backend returns
+    # HTTP 400 "The '<model>' model is not supported when using Codex with
+    # a ChatGPT account." for all three on every ChatGPT Pro account we've
+    # tested (verified live 2026-05-27). Keeping them in the fallback list
+    # leaked dead slugs into /model when live discovery was unavailable
+    # (transient API failure, first-run before refresh) and surfaced HTTP 400
+    # crashes on selection. The Codex CLI public catalog still references
+    # these slugs, which is why they survived previously — but those entries
+    # describe the public OpenAI API, not the OAuth-backed Codex backend
+    # Hermes uses. Removed here. If OpenAI re-enables them on Codex backend,
+    # live discovery will pick them up automatically via _fetch_models_from_api.
+]
+
+_FORWARD_COMPAT_TEMPLATE_MODELS: List[tuple[str, tuple[str, ...]]] = [
+    ("gpt-5.5", ("gpt-5.4", "gpt-5.4-mini", "gpt-5.3-codex")),
+    ("gpt-5.4-mini", ("gpt-5.3-codex",)),
+    ("gpt-5.4", ("gpt-5.3-codex",)),
+    # Surface Spark whenever any compatible Codex template is present so
+    # accounts hitting the live endpoint with an older lineup still see
+    # Spark in the picker. Backend gates real availability by ChatGPT Pro
+    # entitlement; Hermes does not.
+    ("gpt-5.3-codex-spark", ("gpt-5.3-codex",)),
+]
+
+
+def _add_forward_compat_models(model_ids: List[str]) -> List[str]:
+    """Add Clawdbot-style synthetic forward-compat Codex models.
+
+    If a newer Codex slug isn't returned by live discovery, surface it when an
+    older compatible template model is present. This mirrors Clawdbot's
+    synthetic catalog / forward-compat behavior for GPT-5 Codex variants.
+    """
+    ordered: List[str] = []
+    seen: set[str] = set()
+    for model_id in model_ids:
+        if model_id not in seen:
+            ordered.append(model_id)
+            seen.add(model_id)
+
+    for synthetic_model, template_models in _FORWARD_COMPAT_TEMPLATE_MODELS:
+        if synthetic_model in seen:
+            continue
+        if any(template in seen for template in template_models):
+            ordered.append(synthetic_model)
+            seen.add(synthetic_model)
+
+    return ordered
+
+
+def _fetch_models_from_api(access_token: str) -> List[str]:
+    """Fetch available models from the Codex API. Returns visible models sorted by priority."""
+    try:
+        import httpx
+        resp = httpx.get(
+            "https://chatgpt.com/backend-api/codex/models?client_version=1.0.0",
+            headers={"Authorization": f"Bearer {access_token}"},
+            timeout=10,
+        )
+        if resp.status_code != 200:
+            return []
+        data = resp.json()
+        entries = data.get("models", []) if isinstance(data, dict) else []
+    except Exception as exc:
+        logger.debug("Failed to fetch Codex models from API: %s", exc)
+        return []
+
+    sortable = []
+    for item in entries:
+        if not isinstance(item, dict):
+            continue
+        slug = item.get("slug")
+        if not isinstance(slug, str) or not slug.strip():
+            continue
+        slug = slug.strip()
+        # Codex CLI's catalog uses ``supported_in_api`` for the public OpenAI
+        # API, not for the OAuth-backed Codex backend that this provider uses.
+        # Some valid Codex CLI models (for example gpt-5.3-codex-spark) are
+        # marked false here but are still accepted by the Codex route.
+        visibility = item.get("visibility", "")
+        if isinstance(visibility, str) and visibility.strip().lower() in {"hide", "hidden"}:
+            continue
+        priority = item.get("priority")
+        rank = int(priority) if isinstance(priority, (int, float)) else 10_000
+        sortable.append((rank, slug))
+
+    sortable.sort(key=lambda x: (x[0], x[1]))
+    return _add_forward_compat_models([slug for _, slug in sortable])
+
+
+def _read_default_model(codex_home: Path) -> Optional[str]:
+    config_path = codex_home / "config.toml"
+    if not config_path.exists():
+        return None
+    try:
+        import tomllib
+    except Exception:
+        return None
+    try:
+        payload = tomllib.loads(config_path.read_text(encoding="utf-8"))
+    except Exception:
+        return None
+    model = payload.get("model") if isinstance(payload, dict) else None
+    if isinstance(model, str) and model.strip():
+        return model.strip()
+    return None
+
+
+def _read_cache_models(codex_home: Path) -> List[str]:
+    cache_path = codex_home / "models_cache.json"
+    if not cache_path.exists():
+        return []
+    try:
+        raw = json.loads(cache_path.read_text(encoding="utf-8"))
+    except Exception:
+        return []
+
+    entries = raw.get("models") if isinstance(raw, dict) else None
+    sortable = []
+    if isinstance(entries, list):
+        for item in entries:
+            if not isinstance(item, dict):
+                continue
+            slug = item.get("slug")
+            if not isinstance(slug, str) or not slug.strip():
+                continue
+            slug = slug.strip()
+            # Do not filter on ``supported_in_api`` here.  It describes the
+            # public OpenAI API, while Hermes openai-codex talks to the same
+            # OAuth-backed Codex backend as Codex CLI.
+            visibility = item.get("visibility")
+            if isinstance(visibility, str) and visibility.strip().lower() in {"hide", "hidden"}:
+                continue
+            priority = item.get("priority")
+            rank = int(priority) if isinstance(priority, (int, float)) else 10_000
+            sortable.append((rank, slug))
+
+    sortable.sort(key=lambda item: (item[0], item[1]))
+    deduped: List[str] = []
+    for _, slug in sortable:
+        if slug not in deduped:
+            deduped.append(slug)
+    return deduped
+
+
+def get_codex_model_ids(access_token: Optional[str] = None) -> List[str]:
+    """Return available Codex model IDs, trying API first, then local sources.
+    
+    Resolution order: API (live, if token provided) > config.toml default >
+    local cache > hardcoded defaults.
+    """
+    codex_home_str = os.getenv("CODEX_HOME", "").strip() or str(Path.home() / ".codex")
+    codex_home = Path(codex_home_str).expanduser()
+    ordered: List[str] = []
+
+    # Try live API if we have a token
+    if access_token:
+        api_models = _fetch_models_from_api(access_token)
+        if api_models:
+            return _add_forward_compat_models(api_models)
+
+    # Fall back to local sources
+    default_model = _read_default_model(codex_home)
+    if default_model:
+        ordered.append(default_model)
+
+    for model_id in _read_cache_models(codex_home):
+        if model_id not in ordered:
+            ordered.append(model_id)
+
+    for model_id in DEFAULT_CODEX_MODELS:
+        if model_id not in ordered:
+            ordered.append(model_id)
+
+    return _add_forward_compat_models(ordered)