Add configurable LLM provider adapters for email classification

app/config.py

@@ -0,0 +1,46 @@
+from __future__ import annotations
+
+import os
+from functools import lru_cache
+from typing import Literal
+
+from pydantic import BaseModel, Field
+
+Provider = Literal["openai", "anthropic"]
+
+
+class LLMSettings(BaseModel):
+    provider: Provider = Field(default=os.getenv("LLM_PROVIDER", "openai"))
+    api_key: str = Field(default=os.getenv("LLM_API_KEY", "none"))
+    model: str = Field(default=os.getenv("LLM_MODEL", "qwen2.5-7b-instruct.q4_k_m"))
+    base_url: str = Field(default=os.getenv("LLM_BASE_URL", "http://ollama.internal.henryhosted.com:9292/v1"))
+    temperature: float = Field(default=float(os.getenv("LLM_TEMPERATURE", "0.1")))
+    timeout_seconds: float = Field(default=float(os.getenv("LLM_TIMEOUT_SECONDS", "60")))
+    max_retries: int = Field(default=int(os.getenv("LLM_MAX_RETRIES", "3")))
+
+
+@lru_cache(maxsize=1)
+def get_settings() -> LLMSettings:
+    return LLMSettings()
+
+
+def get_request_settings(
+    provider: str | None = None,
+    model: str | None = None,
+    base_url: str | None = None,
+    api_key: str | None = None,
+    temperature: float | None = None,
+) -> LLMSettings:
+    base = get_settings()
+    data = base.model_dump()
+    if provider is not None:
+        data["provider"] = provider
+    if model is not None:
+        data["model"] = model
+    if base_url is not None:
+        data["base_url"] = base_url
+    if api_key is not None:
+        data["api_key"] = api_key
+    if temperature is not None:
+        data["temperature"] = temperature
+    return LLMSettings(**data)