f0699436c5
- API versioning: all REST endpoints prefixed with /api/v1/ - Structured logging: replaced stdlib logging with structlog (console/JSON modes) - Alembic migrations: versioned DB schema with initial migration - Error standardization: global exception handlers for consistent envelope format - Interrupt cleanup: asyncio background task for expired interrupt removal - Integration tests: +30 tests (analytics, replay, openapi, error, session APIs) - Frontend tests: +57 tests (all components, pages, useWebSocket hook) - Backend: 557 tests, 89.75% coverage | Frontend: 80 tests, 16 test files
71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
"""Centralized application configuration via pydantic-settings."""
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from __future__ import annotations
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from typing import Literal
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from pydantic import model_validator
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(
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env_file=".env",
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env_file_encoding="utf-8",
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extra="ignore",
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)
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database_url: str
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llm_provider: Literal["anthropic", "openai", "azure_openai", "google"] = "anthropic"
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llm_model: str = "claude-sonnet-4-6"
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session_ttl_minutes: int = 30
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interrupt_ttl_minutes: int = 30
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ws_host: str = "0.0.0.0"
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ws_port: int = 8000
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webhook_url: str = ""
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webhook_timeout_seconds: int = 10
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webhook_max_retries: int = 3
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template_name: str = ""
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log_format: str = "console" # "console" for dev, "json" for production
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admin_api_key: str = ""
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anthropic_api_key: str = ""
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openai_api_key: str = ""
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azure_openai_api_key: str = ""
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azure_openai_endpoint: str = ""
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azure_openai_api_version: str = "2024-12-01-preview"
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azure_openai_deployment: str = ""
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google_api_key: str = ""
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@model_validator(mode="after")
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def validate_provider_key(self) -> Settings:
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key_map = {
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"anthropic": self.anthropic_api_key,
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"openai": self.openai_api_key,
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"azure_openai": self.azure_openai_api_key,
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"google": self.google_api_key,
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}
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key = key_map.get(self.llm_provider, "")
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if not key:
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raise ValueError(
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f"API key for provider '{self.llm_provider}' is required. "
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f"Set the corresponding environment variable."
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)
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if self.llm_provider == "azure_openai":
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if not self.azure_openai_endpoint:
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raise ValueError(
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"AZURE_OPENAI_ENDPOINT is required for azure_openai provider."
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)
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if not self.azure_openai_deployment:
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raise ValueError(
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"AZURE_OPENAI_DEPLOYMENT is required for azure_openai provider."
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)
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return self
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