hermes-agent/plugins/model-providers/opencode-zen/__init__.py
ethernet 0fce82164a Pluginify provider/platform/terminal backends
Move provider adapters (anthropic, bedrock, azure), platform adapters
(telegram, slack, discord, feishu, dingtalk, matrix), and terminal backends
(modal, daytona) out of core into plugins/ workspace members. Core references
them via the plugin registries (get_provider_namespace / get_provider_service /
get_tool_provider / get_credential_pool_hook) instead of direct imports.

- Provider/platform/terminal adapters relocated under plugins/; pyproject
  extras reference workspace members; nix variants aggregate per-platform extras.
- Anthropic credential discovery + OAuth-masquerade guard live in the plugin's
  credential_pool_hook; browser-open guarded by _can_open_graphical_browser.
- Vercel AI Gateway + Vercel Sandbox removed (upstream deletion); get_bedrock_model_ids
  removed (replaced by bedrock_model_ids_or_none + discover_bedrock_models).
- Terminal backends resolve ModalEnvironment / DaytonaEnvironment lazily from
  the plugin registry.
- uv.lock regenerated against the pluginified workspace.

Plugin test suites updated for the relocation: imports point at
hermes_agent_<plat>.adapter, caplog logger-name filters and monkeypatch targets
use the new module paths, and credential/rollback tests patch
registries.get_provider_service rather than the removed agent.*_adapter modules.

Verified: zero dead imports of relocated modules in core (import smoke test +
rename-map grep); nix develop succeeds; targeted plugin suites green
(bedrock, anthropic-auxiliary, matrix, dingtalk, feishu, credential_pool,
switch_model_rollback). Remaining full-suite failures are pre-existing on the
pre-merge tree (telegram setUpModule __code__) or environmental (voice/media/
PTY/network-dependent), not introduced here.
2026-05-29 09:28:00 -04:00

123 lines
4.2 KiB
Python

"""OpenCode provider profiles (Zen + Go).
Both use per-model api_mode routing:
- OpenCode Zen: Claude → anthropic_messages, GPT-5/Codex → codex_responses,
everything else → chat_completions (this profile)
- OpenCode Go: MiniMax → anthropic_messages, GLM/Kimi → chat_completions
(this profile)
"""
from __future__ import annotations
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
def _flat_model_name(model: str | None) -> str:
"""Return the bare OpenCode model ID, tolerating aggregator prefixes."""
return (model or "").strip().rsplit("/", 1)[-1].lower()
def _is_kimi_k2_model(model: str | None) -> bool:
return _flat_model_name(model).startswith("kimi-k2")
def _is_deepseek_thinking_model(model: str | None) -> bool:
m = _flat_model_name(model)
if m.startswith("deepseek-v") and not m.startswith("deepseek-v3"):
return True
return m == "deepseek-reasoner"
class OpenCodeGoProfile(ProviderProfile):
"""OpenCode Go - model-specific reasoning controls."""
# Per-model completion-token cap. The opencode-go relay's default is
# too large for mimo-v2.5-pro — it sends max_tokens=262144 but Xiaomi
# only supports 131072 completion tokens and 400s the request.
# Setting an explicit cap here prevents the relay default from being
# applied. Keys are normalized via _flat_model_name().
_MODEL_MAX_TOKENS: dict[str, int] = {
"mimo-v2.5-pro": 131072,
}
def get_max_tokens(self, model: str | None) -> int | None:
cap = self._MODEL_MAX_TOKENS.get(_flat_model_name(model))
if cap is not None:
return cap
return self.default_max_tokens
def build_api_kwargs_extras(
self, *, reasoning_config: dict | None = None, model: str | None = None, **context
) -> tuple[dict[str, Any], dict[str, Any]]:
extra_body: dict[str, Any] = {}
top_level: dict[str, Any] = {}
if _is_kimi_k2_model(model):
# Kimi K2 on OpenCode Go uses Moonshot's native wire shape:
# extra_body.thinking (binary toggle) + top-level reasoning_effort
# (low|medium|high). Mirrors the KimiProfile (api.moonshot.ai/v1).
if not isinstance(reasoning_config, dict):
# No config → leave server defaults alone.
return extra_body, top_level
enabled = reasoning_config.get("enabled") is not False
extra_body["thinking"] = {"type": "enabled" if enabled else "disabled"}
if not enabled:
return extra_body, top_level
effort = (reasoning_config.get("effort") or "").strip().lower()
if effort in {"xhigh", "max"}:
top_level["reasoning_effort"] = "high"
elif effort in {"low", "medium", "high"}:
top_level["reasoning_effort"] = effort
return extra_body, top_level
if not _is_deepseek_thinking_model(model):
return extra_body, top_level
enabled = True
if isinstance(reasoning_config, dict) and reasoning_config.get("enabled") is False:
enabled = False
extra_body["thinking"] = {"type": "enabled" if enabled else "disabled"}
if not enabled:
return extra_body, top_level
if isinstance(reasoning_config, dict):
effort = (reasoning_config.get("effort") or "").strip().lower()
if effort in {"xhigh", "max"}:
top_level["reasoning_effort"] = "max"
elif effort in {"low", "medium", "high"}:
top_level["reasoning_effort"] = effort
return extra_body, top_level
opencode_zen = ProviderProfile(
name="opencode-zen",
aliases=("opencode", "opencode_zen", "zen"),
env_vars=("OPENCODE_ZEN_API_KEY",),
base_url="https://opencode.ai/zen/v1",
default_aux_model="gemini-3-flash",
)
opencode_go = OpenCodeGoProfile(
name="opencode-go",
aliases=("opencode_go", "go", "opencode-go-sub"),
env_vars=("OPENCODE_GO_API_KEY",),
base_url="https://opencode.ai/zen/go/v1",
default_aux_model="glm-5",
)
register_provider(opencode_zen)
register_provider(opencode_go)
def register(ctx):
"""No-op — this provider has no workspace package yet."""
pass