Files
core-api/src/config.py
T
jpmschweitzerandClaude Opus 4.5 3ecfb91cc2 refactor: simplify configuration to use only environment variables
- Remove credentials.py import, use pydantic-settings .env support
- Remove unused search API keys (Brave, Google)
- Update default search provider to SearXNG
- Add extra="ignore" to allow flexible env var usage
- Update .env.example with organized sections

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-31 11:13:26 +01:00

149 lines
4.8 KiB
Python

"""
Global configuration for Core Code API
All configuration is loaded from environment variables or .env file.
See .env.example for available settings.
"""
import tomllib
from pathlib import Path
from pydantic_settings import BaseSettings
from functools import lru_cache
def _get_version_from_pyproject() -> str:
"""Load version from pyproject.toml"""
pyproject_path = Path(__file__).parent.parent / "pyproject.toml"
try:
with open(pyproject_path, "rb") as f:
data = tomllib.load(f)
return data.get("project", {}).get("version", "0.0.0")
except FileNotFoundError:
return "0.0.0"
__version__ = _get_version_from_pyproject()
class Settings(BaseSettings):
"""Global application settings"""
# Application
app_name: str = "Core Code API"
app_version: str = __version__
debug: bool = False
# Server
host: str = "0.0.0.0"
port: int = 8083
# CORS
cors_origins: list[str] = ["*"]
cors_credentials: bool = True
cors_methods: list[str] = ["*"]
cors_headers: list[str] = ["*"]
# Logging
log_level: str = "DEBUG"
# Ollama Configuration (for AI orchestration)
ollama_base_url: str = "http://ollama:11434"
ollama_timeout: int = 300 # 5 minutes
# Model Configuration
default_model: str = "mistral-tools:7b"
agent_model: str = "gemma2:9b-instruct-q5_K_M" # Must support tool calling with ADK (~4GB VRAM)
lightweight_models: str = "gemma3-tools:1b,phi3:mini"
heavy_models: str = "mistral:7b,gemma2:9b,gemma3:12b,mixtral:8x7b"
code_models: str = "codestral:latest,codegemma:latest"
# Previous config (gemma3:12b used ~10GB VRAM)
# default_model: str = "gemma3:12b"
# agent_model: str = "gemma3:12b"
# System Prompt Variant (for A/B testing)
# Options: v1_verbose, v2_concise, v3_imperative, v4_minimal, v4_gemini_suggestion, v5_adk_optimized, v7_adk_best_practice, v8_holistic
system_prompt_variant: str = "v8_holistic"
# Agent Configuration
agent_fallback_enabled: bool = True
# Model Aliases (OpenAI → Local)
alias_gpt35: str = "gemma:7b"
alias_gpt4: str = "mistral:7b"
alias_gpt4_turbo: str = "mixtral:8x7b"
alias_gpt4_code: str = "codestral:latest"
# Memory Configuration
memory_tier1_max_turns: int = 10
memory_consolidation_threshold: int = 10
# Qdrant Configuration
qdrant_host: str = "qdrant"
qdrant_port: int = 6333
qdrant_collection_conversations: str = "core_api_conversations"
qdrant_collection_documents: str = "core_api_documents"
qdrant_collection_user_facts: str = "core_api_user_facts"
# Embeddings (using Ollama - no local models needed)
embedding_model: str = "nomic-embed-text" # Ollama embedding model
embedding_dimension: int = 768 # nomic-embed-text dimension
embedding_batch_size: int = 32
# Search Configuration
search_provider: str = "searxng"
searxng_url: str = "http://searxng:8080"
# Infrastructure Management (Portainer)
portainer_url: str = "http://portainer:9000"
portainer_api_key: str = ""
# Infrastructure Management (Nginx Proxy Manager)
npm_url: str = "http://npm:81"
npm_email: str = ""
npm_password: str = ""
# Home Assistant Configuration
homeassistant_url: str = "http://homeassistant:8123"
homeassistant_token: str = ""
homeassistant_timeout: int = 30
# Core-AI Service (AI performance metrics)
core_ai_base_url: str = "http://core-ai:8086"
# OIDC Authentication (Authentik)
oidc_enabled: bool = False # Set to True to require authentication
oidc_issuer: str = "https://auth.schweitz.net/application/o/core-api/"
oidc_audience: str = "core-api"
@property
def model_aliases(self) -> dict:
"""Computed property for model aliases"""
return {
"gpt-3.5-turbo": self.alias_gpt35,
"gpt-4": self.alias_gpt4,
"gpt-4-turbo": self.alias_gpt4_turbo,
"gpt-4-code": self.alias_gpt4_code,
}
def get_lightweight_models(self) -> list[str]:
"""Parse comma-separated lightweight models"""
return [m.strip().strip('"').strip("'") for m in self.lightweight_models.split(",") if m.strip()]
def get_heavy_models(self) -> list[str]:
"""Parse comma-separated heavy models"""
return [m.strip().strip('"').strip("'") for m in self.heavy_models.split(",") if m.strip()]
def get_code_models(self) -> list[str]:
"""Parse comma-separated code models"""
return [m.strip().strip('"').strip("'") for m in self.code_models.split(",") if m.strip()]
class Config:
env_file = ".env"
case_sensitive = False
extra = "ignore" # Ignore extra env vars not defined in Settings
@lru_cache()
def get_settings() -> Settings:
"""Cached settings instance"""
return Settings()