Files
strix/strix/config/config.py
T
0xallam 1d34ccbf36 fix(config): canonicalize LLM env and respect cleared vars
Drop saved LLM config if any current LLM env var differs, and treat
explicit empty env vars as cleared so saved values are removed and
not re-applied.
2026-01-15 18:37:38 -08:00

172 lines
4.8 KiB
Python

import contextlib
import json
import os
from pathlib import Path
from typing import Any
class Config:
"""Configuration Manager for Strix."""
# LLM Configuration
strix_llm = None
llm_api_key = None
llm_api_base = None
openai_api_base = None
litellm_base_url = None
ollama_api_base = None
strix_reasoning_effort = "high"
strix_llm_max_retries = "5"
strix_memory_compressor_timeout = "30"
llm_timeout = "300"
_LLM_CANONICAL_NAMES = (
"strix_llm",
"llm_api_key",
"llm_api_base",
"openai_api_base",
"litellm_base_url",
"ollama_api_base",
"strix_reasoning_effort",
"strix_llm_max_retries",
"strix_memory_compressor_timeout",
"llm_timeout",
)
# Tool & Feature Configuration
perplexity_api_key = None
strix_disable_browser = "false"
# Runtime Configuration
strix_image = "ghcr.io/usestrix/strix-sandbox:0.1.10"
strix_runtime_backend = "docker"
strix_sandbox_execution_timeout = "120"
strix_sandbox_connect_timeout = "10"
# Telemetry
strix_telemetry = "1"
@classmethod
def _tracked_names(cls) -> list[str]:
return [
k
for k, v in vars(cls).items()
if not k.startswith("_") and k[0].islower() and (v is None or isinstance(v, str))
]
@classmethod
def tracked_vars(cls) -> list[str]:
return [name.upper() for name in cls._tracked_names()]
@classmethod
def _llm_env_vars(cls) -> set[str]:
return {name.upper() for name in cls._LLM_CANONICAL_NAMES}
@classmethod
def _llm_env_changed(cls, saved_env: dict[str, Any]) -> bool:
for var_name in cls._llm_env_vars():
current = os.getenv(var_name)
if current is None:
continue
if saved_env.get(var_name) != current:
return True
return False
@classmethod
def get(cls, name: str) -> str | None:
env_name = name.upper()
default = getattr(cls, name, None)
return os.getenv(env_name, default)
@classmethod
def config_dir(cls) -> Path:
return Path.home() / ".strix"
@classmethod
def config_file(cls) -> Path:
return cls.config_dir() / "cli-config.json"
@classmethod
def load(cls) -> dict[str, Any]:
path = cls.config_file()
if not path.exists():
return {}
try:
with path.open("r", encoding="utf-8") as f:
data: dict[str, Any] = json.load(f)
return data
except (json.JSONDecodeError, OSError):
return {}
@classmethod
def save(cls, config: dict[str, Any]) -> bool:
try:
cls.config_dir().mkdir(parents=True, exist_ok=True)
config_path = cls.config_file()
with config_path.open("w", encoding="utf-8") as f:
json.dump(config, f, indent=2)
except OSError:
return False
with contextlib.suppress(OSError):
config_path.chmod(0o600) # may fail on Windows
return True
@classmethod
def apply_saved(cls) -> dict[str, str]:
saved = cls.load()
env_vars = saved.get("env", {})
if not isinstance(env_vars, dict):
env_vars = {}
cleared_vars = {
var_name
for var_name in cls.tracked_vars()
if var_name in os.environ and os.environ.get(var_name) == ""
}
if cleared_vars:
for var_name in cleared_vars:
env_vars.pop(var_name, None)
cls.save({"env": env_vars})
if cls._llm_env_changed(env_vars):
cls.save({"env": {}})
return {}
applied = {}
for var_name, var_value in env_vars.items():
if var_name in cls.tracked_vars() and var_name not in os.environ:
os.environ[var_name] = var_value
applied[var_name] = var_value
return applied
@classmethod
def capture_current(cls) -> dict[str, Any]:
env_vars = {}
for var_name in cls.tracked_vars():
value = os.getenv(var_name)
if value:
env_vars[var_name] = value
return {"env": env_vars}
@classmethod
def save_current(cls) -> bool:
existing = cls.load().get("env", {})
merged = dict(existing)
for var_name in cls.tracked_vars():
value = os.getenv(var_name)
if value is None:
pass
elif value == "":
merged.pop(var_name, None)
else:
merged[var_name] = value
return cls.save({"env": merged})
def apply_saved_config() -> dict[str, str]:
return Config.apply_saved()
def save_current_config() -> bool:
return Config.save_current()