free-claude-code/smoke/lib/config.py
Wang Ji b525217633
[feat] ollama method support (#129)
Support use ollama method like LM stuio

---------

Co-authored-by: Alishahryar1 <alishahryar2@gmail.com>
Co-authored-by: u011436427 <u011436427@noreply.gitcode.com>
2026-04-25 22:06:36 -07:00

191 lines
6.1 KiB
Python

"""Smoke-suite configuration loaded from the real developer environment."""
from __future__ import annotations
import os
from collections.abc import Mapping
from dataclasses import dataclass
from pathlib import Path
from config.settings import Settings, get_settings
DEFAULT_TARGETS = frozenset(
{
"api",
"auth",
"cli",
"clients",
"config",
"extensibility",
"llamacpp",
"lmstudio",
"messaging",
"ollama",
"providers",
"rate_limit",
"tools",
}
)
SIDE_EFFECT_TARGETS = frozenset({"discord", "telegram", "voice"})
ALL_TARGETS = DEFAULT_TARGETS | SIDE_EFFECT_TARGETS
TARGET_ALIASES = {
"contract": "api",
"optimizations": "api",
"thinking": "providers",
"vscode": "clients",
}
SECRET_KEY_PARTS = ("KEY", "TOKEN", "SECRET", "WEBHOOK", "AUTH")
TARGET_REQUIRED_ENV: dict[str, tuple[str, ...]] = {
"api": (),
"auth": (),
"cli": ("FCC_SMOKE_CLAUDE_BIN", "configured provider for Claude CLI prompt"),
"clients": (),
"config": (),
"extensibility": (),
"messaging": (),
"providers": ("MODEL or MODEL_* with usable provider configuration",),
"rate_limit": ("configured provider model",),
"tools": ("configured tool-capable provider model",),
"lmstudio": ("LM_STUDIO_BASE_URL with a running LM Studio server",),
"llamacpp": ("LLAMACPP_BASE_URL with a running llama-server",),
"ollama": ("OLLAMA_BASE_URL with a running Ollama server",),
"telegram": (
"TELEGRAM_BOT_TOKEN",
"ALLOWED_TELEGRAM_USER_ID or FCC_SMOKE_TELEGRAM_CHAT_ID",
),
"discord": (
"DISCORD_BOT_TOKEN",
"ALLOWED_DISCORD_CHANNELS or FCC_SMOKE_DISCORD_CHANNEL_ID",
),
"voice": ("VOICE_NOTE_ENABLED=true", "FCC_SMOKE_RUN_VOICE=1"),
}
@dataclass(frozen=True, slots=True)
class ProviderModel:
provider: str
full_model: str
source: str
@property
def model_name(self) -> str:
return Settings.parse_model_name(self.full_model)
@dataclass(frozen=True, slots=True)
class SmokeConfig:
root: Path
results_dir: Path
live: bool
interactive: bool
targets: frozenset[str]
provider_matrix: frozenset[str]
timeout_s: float
prompt: str
claude_bin: str
worker_id: str
settings: Settings
@classmethod
def load(cls) -> SmokeConfig:
root = Path(__file__).resolve().parents[2]
get_settings.cache_clear()
settings = get_settings()
return cls(
root=root,
results_dir=root / ".smoke-results",
live=os.getenv("FCC_LIVE_SMOKE") == "1",
interactive=os.getenv("FCC_SMOKE_INTERACTIVE") == "1",
targets=_parse_targets(os.getenv("FCC_SMOKE_TARGETS")),
provider_matrix=_parse_csv(os.getenv("FCC_SMOKE_PROVIDER_MATRIX")),
timeout_s=float(os.getenv("FCC_SMOKE_TIMEOUT_S", "45")),
prompt=os.getenv("FCC_SMOKE_PROMPT", "Reply with exactly: FCC_SMOKE_PONG"),
claude_bin=os.getenv("FCC_SMOKE_CLAUDE_BIN", "claude"),
worker_id=os.getenv("PYTEST_XDIST_WORKER", "main"),
settings=settings,
)
def target_enabled(self, *names: str) -> bool:
return any(name in self.targets for name in names)
def provider_models(self) -> list[ProviderModel]:
candidates = (
("MODEL", self.settings.model),
("MODEL_OPUS", self.settings.model_opus),
("MODEL_SONNET", self.settings.model_sonnet),
("MODEL_HAIKU", self.settings.model_haiku),
)
seen: set[str] = set()
models: list[ProviderModel] = []
for source, model in candidates:
if not model or model in seen:
continue
provider = Settings.parse_provider_type(model)
if self.provider_matrix and provider not in self.provider_matrix:
continue
if not self.has_provider_configuration(provider):
continue
seen.add(model)
models.append(
ProviderModel(provider=provider, full_model=model, source=source)
)
return models
def has_provider_configuration(self, provider: str) -> bool:
if provider == "nvidia_nim":
return bool(self.settings.nvidia_nim_api_key.strip())
if provider == "open_router":
return bool(self.settings.open_router_api_key.strip())
if provider == "deepseek":
return bool(self.settings.deepseek_api_key.strip())
if provider == "lmstudio":
return bool(self.settings.lm_studio_base_url.strip())
if provider == "llamacpp":
return bool(self.settings.llamacpp_base_url.strip())
if provider == "ollama":
return bool(self.settings.ollama_base_url.strip())
return False
def _parse_csv(raw: str | None) -> frozenset[str]:
if not raw:
return frozenset()
return frozenset(part.strip() for part in raw.split(",") if part.strip())
def _parse_targets(raw: str | None) -> frozenset[str]:
if not raw:
return DEFAULT_TARGETS
parsed = _parse_csv(raw)
if "all" in parsed:
return ALL_TARGETS
return frozenset(TARGET_ALIASES.get(target, target) for target in parsed)
def auth_headers(token: str | None = None) -> dict[str, str]:
settings = get_settings()
resolved = token if token is not None else settings.anthropic_auth_token
headers = {
"anthropic-version": "2023-06-01",
"content-type": "application/json",
}
if resolved:
headers["x-api-key"] = resolved
return headers
def redacted(value: str, env: Mapping[str, str] | None = None) -> str:
"""Redact known secrets from a string before writing smoke artifacts."""
if not value:
return value
source = env if env is not None else os.environ
result = value
for key, secret in source.items():
if not secret or len(secret) < 4:
continue
if any(part in key.upper() for part in SECRET_KEY_PARTS):
result = result.replace(secret, f"<redacted:{key}>")
return result