hermes-agent/plugins/model-providers/openrouter/__init__.py
alt-glitch 2bd9c9b881 opentui(phase3): launcher integration — HERMES_TUI_ENGINE dual-engine
hermes --tui launches the native OpenTUI engine (Bun) when
HERMES_TUI_ENGINE=opentui (env) or display.tui_engine=opentui (config);
Ink stays the default and the shipping path is untouched.

- _resolve_tui_engine() (env > config > ink); refuses opentui on
  Windows/Termux (no Bun) -> falls back to ink with a notice.
- _make_opentui_argv() -> [bun, src/entry.real.tsx] (no build step).
- _bun_bin() with HERMES_BUN override.
- Branch at top of _make_tui_argv BEFORE _ensure_tui_node (Bun-only host
  must not bootstrap Node).
- Gate _launch_tui NODE_OPTIONS/--max-old-space-size on engine==ink (Bun
  is JSC; the V8 flag errors/ignores).

Verified end-to-end via tmux: real hermes --tui -> Bun -> OpenTUI ->
real Python gateway streamed a real reply. No-flag default still ink.
2026-06-08 11:11:54 +00:00

117 lines
4.1 KiB
Python

"""OpenRouter provider profile."""
import logging
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
logger = logging.getLogger(__name__)
_CACHE: list[str] | None = None
class OpenRouterProfile(ProviderProfile):
"""OpenRouter aggregator — provider preferences, reasoning config passthrough."""
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Fetch from public OpenRouter catalog — no auth required.
Note: Tool-call capability filtering is applied by hermes_cli/models.py
via fetch_openrouter_models() → _openrouter_model_supports_tools(), not
here. The picker early-returns via the dedicated openrouter path before
reaching this method, so filtering here would be unreachable.
"""
global _CACHE # noqa: PLW0603
if _CACHE is not None:
return _CACHE
try:
result = super().fetch_models(api_key=None, timeout=timeout)
if result is not None:
_CACHE = result
return result
except Exception as exc:
logger.debug("fetch_models(openrouter): %s", exc)
return None
def build_extra_body(
self, *, session_id: str | None = None, **context: Any
) -> dict[str, Any]:
body: dict[str, Any] = {}
if session_id:
body["session_id"] = session_id
prefs = context.get("provider_preferences")
if prefs:
body["provider"] = prefs
# Pareto Code router — model-gated. The plugins block is only
# meaningful for openrouter/pareto-code; sending it on any other
# model has no documented effect and would be confusing in logs.
# See: https://openrouter.ai/docs/guides/routing/routers/pareto-router
model = (context.get("model") or "")
if model == "openrouter/pareto-code":
score = context.get("openrouter_min_coding_score")
if score is not None and score != "":
try:
score_f = float(score)
except (TypeError, ValueError):
score_f = None
if score_f is not None and 0.0 <= score_f <= 1.0:
body["plugins"] = [
{"id": "pareto-router", "min_coding_score": score_f}
]
return body
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
supports_reasoning: bool = False,
model: str | None = None,
session_id: str | None = None,
**context: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
"""OpenRouter passes the full reasoning_config dict as extra_body.reasoning.
For xAI Grok models routed through OpenRouter, attach the
``x-grok-conv-id`` header so that xAI's prompt cache stays pinned to
the same backend server across turns.
"""
extra_body: dict[str, Any] = {}
if supports_reasoning:
if reasoning_config is not None:
extra_body["reasoning"] = dict(reasoning_config)
else:
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
extra_headers: dict[str, Any] = {}
if session_id and model and model.startswith(("x-ai/grok-", "xai/grok-")):
extra_headers["x-grok-conv-id"] = session_id
return extra_body, {"extra_headers": extra_headers} if extra_headers else {}
openrouter = OpenRouterProfile(
name="openrouter",
aliases=("or",),
env_vars=("OPENROUTER_API_KEY",),
display_name="OpenRouter",
description="OpenRouter — unified API for 200+ models",
signup_url="https://openrouter.ai/keys",
base_url="https://openrouter.ai/api/v1",
models_url="https://openrouter.ai/api/v1/models",
fallback_models=(
"anthropic/claude-sonnet-4.6",
"openai/gpt-5.4",
"deepseek/deepseek-chat",
"google/gemini-3-flash-preview",
"qwen/qwen3-plus",
),
)
register_provider(openrouter)