Settings refactoring

app/api/routers/slack_agent.py

@@ -1,28 +1,24 @@
-import os
 from pathlib import Path
 
-from dotenv import load_dotenv
 from fastapi import APIRouter
 from pydantic import BaseModel
 from pydantic_ai import Agent
 from pydantic_ai.models.openai import OpenAIChatModel
 from pydantic_ai.providers.openrouter import OpenRouterProvider
 from slack_sdk import WebClient
 
+from app.core.config import get_settings
 from app.tools import slack
 
-_ = load_dotenv()
-
-open_router_token = os.environ.get("OPEN_ROUTER_TOKEN", "")
-slack_token = os.environ.get("SLACK_USER_TOKEN", "")
-client = WebClient(token=slack_token)
+settings = get_settings()
+client = WebClient(token=settings.slack_token or "")
 
 prompt_path = Path(__file__).resolve().parents[2] / "pompts" / "slack.md"
 prompt_instructions = prompt_path.read_text(encoding="utf-8")
 
 model = OpenAIChatModel(
-    "z-ai/glm-4.5",
-    provider=OpenRouterProvider(api_key=open_router_token),
+    settings.model_name,
+    provider=OpenRouterProvider(api_key=settings.open_router_token or ""),
 )
 
 agent = Agent(

app/core/config.py

@@ -1,8 +1,49 @@
+from __future__ import annotations
+
+import os
+from functools import lru_cache
+
+from dotenv import load_dotenv
 from pydantic import BaseModel
 
 
 class Settings(BaseModel):
-    slack_bot_token: str
-    ai_provider: str = "openai"
-    openai_api_key: str | None = None
-    anthropic_api_key: str | None = None
+    """
+    Centralized application settings with lightweight env loading.
+
+    This avoids a hard dependency on pydantic-settings while still validating
+    types and providing a single import for configuration across the app.
+    """
+
+    # AI model (via OpenRouter's OpenAI-compatible interface)
+    model_name: str = "z-ai/glm-4.5"
+
+    # Provider tokens/keys
+    open_router_token: str | None = None
+
+    # Slack tokens
+    slack_user_token: str | None = None
+    slack_bot_token: str | None = None
+
+    @property
+    def slack_token(self) -> str | None:
+        """
+        Preferred Slack token to use for API calls.
+        Prioritize user token when available, otherwise use bot token.
+        """
+        return self.slack_user_token or self.slack_bot_token
+
+
+@lru_cache(maxsize=1)
+def get_settings() -> Settings:
+    """
+    Load settings from environment (and .env) once and cache them.
+    """
+    load_dotenv()
+
+    return Settings(
+        model_name=os.getenv("MODEL_NAME", "z-ai/glm-4.5"),
+        open_router_token=os.getenv("OPEN_ROUTER_TOKEN"),
+        slack_user_token=os.getenv("SLACK_USER_TOKEN"),
+        slack_bot_token=os.getenv("SLACK_BOT_TOKEN"),
+    )

pyproject.toml

@@ -1,5 +1,5 @@
 [project]
-name = "ava-backend"
+name = "iva-backend"
 version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"