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