Add env variables for setting a demo mode configuration

.env.example

@@ -3,4 +3,8 @@
 # Only modify to add/remove expected env keys.
 # Create a new .env file containing the variables below and replace '{VALUE_NAME}' with the specific value or key.
 # DO NOT COMMIT YOUR .env FILE TO SOURCE CONTROL (.gitignore should handle that)
-OPENAI_API_KEY={YOUR_API_KEY}
+FEATURE_DEMO_MODE=false
+DEMO_GENAI_MODEL_NAME={MODEL_NAME}
+DEMO_GENAI_API_KEY={MODEL_VERSION}
+DEMO_GENAI_PROVIDER={GENAI_PROVIDER}
+ENABLE_DEBUG_MODE=false

app/feature_flags.py

@@ -0,0 +1,14 @@
+import os
+from dataclasses import dataclass, field
+
+
+@dataclass(frozen=True, repr=True)
+class FeatureFlags:
+    """
+    Container to manage feature flags for the application.
+    """
+
+    demo_mode: bool = field(
+        default_factory=lambda: os.getenv("FEATURE_DEMO_MODE", "false").lower()
+        == "true"
+    )

app/settings/settings_repo.py

@@ -1,4 +1,6 @@
 from typing import Optional
+import os
+from feature_flags import FeatureFlags
 import tomllib
 import pathlib
 from dataclasses import dataclass
@@ -37,6 +39,28 @@ class SettingsData:
 _current_settings: Optional[SettingsData] = None
 
 
+def __load_settings_file(custom_path: str = None) -> dict:
+    """
+    Load settings from a TOML file and return the settings dictionary.
+
+    Args:
+        custom_path (str): Path to the TOML file. Defaults to "settings.toml" if not provided.
+
+    Returns:
+        dict: Settings loaded from the TOML file.
+    """
+    path = "./settings.toml"
+    if custom_path:
+        path = custom_path
+
+    file = pathlib.Path(path)
+
+    with open(file, "rb") as f:
+        settings = tomllib.load(f)
+
+    return settings
+
+
 def load_settings(
     custom_path: str = None, reload_settings: bool = False
 ) -> SettingsData:
@@ -60,55 +84,63 @@ def load_settings(
     if (_current_settings) and (not reload_settings):
         return _current_settings
 
-    # If custom path is provided, use it
-    path = "./settings.toml"
-    if custom_path:
-        path = custom_path
-
-    file = pathlib.Path(path)
-
-    with open(file, "rb") as f:
-        settings = tomllib.load(f)
+    selected_engine: str
+    model: str
+    api_key: str
+    is_debug_mode: bool = os.getenv("ENABLE_DEBUG_MODE", "false").lower() == "true"
+    feature_flags = FeatureFlags()
+
+    if feature_flags.demo_mode:
+        selected_engine = os.getenv("DEMO_GENAI_PROVIDER")
+        api_key = os.getenv("DEMO_GENAI_API_KEY")
+        model = os.getenv("DEMO_GENAI_MODEL_NAME")
+    else:
+        # If custom path is provided, use it
+        path = "./settings.toml"
+        if custom_path:
+            path = custom_path
+
+        # Load settings from the TOML file
+        settings = __load_settings_file(path)
+        selected_engine = settings["selected_ocr_engine"]
+        api_key = settings.get(selected_engine, {}).get("api_key", "")
+        model = settings.get(selected_engine, {}).get("model", "")
+        is_debug_mode = settings.get("debug_mode", False)
 
-    selected_engine = settings["selected_ocr_engine"]
-    engine_config = settings.get(selected_engine)
-    is_debug_mode = settings.get("debug_mode", False)
     enable_debug_logging(is_debug_mode)
 
     match selected_engine:
         case "open_ai":
             _current_settings = SettingsData(
                 selected_config=OpenAiConfig(
-                    api_key=engine_config["api_key"],
-                    model=engine_config["model"],
+                    api_key=api_key,
+                    model=model,
                 )
             )
         case "mistral_ai":
             _current_settings = SettingsData(
                 selected_config=MistralAiConfig(
-                    api_key=engine_config["api_key"],
-                    model=engine_config["model"],
+                    api_key=api_key,
+                    model=model,
                 )
             )
         case "gemini_ai":
             _current_settings = SettingsData(
                 selected_config=GeminiAiConfig(
-                    api_key=engine_config["api_key"],
-                    model=engine_config["model"],
+                    api_key=api_key,
+                    model=model,
                 )
             )
         case _:
             raise ValueError(
                 f"Could not find configuration for {selected_engine}. Please check your settings file."
             )
 
-    _current_settings.debug_mode = settings.get("debug_mode", False)
+    _current_settings.debug_mode = is_debug_mode
 
     logger.debug(f"Loaded settings: {_current_settings}")
     logger.info(
-        "Selected OCR engine {x} with model {y}:".format(
-            x=selected_engine, y=engine_config["model"]
-        )
+        "Selected OCR engine {x} with model {y}:".format(x=selected_engine, y=model)
     )
 
     return _current_settings

pyproject.toml

@@ -46,6 +46,7 @@ dev = [
     "flake8>=7.2.0",
     "pytest>=8.3.5",
     "pytest-cov>=6.1.1",
+    "pytest-env>=1.1.5",
     "ruff>=0.11.4",
 ]
 

tests/test_settings_env.py

@@ -0,0 +1,61 @@
+import pytest
+from app.settings import load_settings, OpenAiConfig, MistralAiConfig, GeminiAiConfig
+
+
+def test_error_when_demo_active_without_genai_variables(monkeypatch):
+    monkeypatch.setenv("FEATURE_DEMO_MODE", "true")
+    with pytest.raises(ValueError) as exc_info:
+        load_settings(reload_settings=True)
+
+    assert (
+        "Could not find configuration for None. Please check your settings file."
+        in str(exc_info.value)
+    )
+
+
+def test_env_mistral_selected_config(monkeypatch):
+    monkeypatch.setenv("FEATURE_DEMO_MODE", "true")
+    monkeypatch.setenv("DEMO_GENAI_PROVIDER", "mistral_ai")
+    monkeypatch.setenv("DEMO_GENAI_API_KEY", "Your Mistral API key")
+    monkeypatch.setenv("DEMO_GENAI_MODEL_NAME", "default")
+
+    settings = load_settings(reload_settings=True)
+    assert settings.selected_config == MistralAiConfig(
+        api_key="Your Mistral API key", model="default"
+    )
+
+
+def test_env_openai_selected_config(monkeypatch):
+    monkeypatch.setenv("FEATURE_DEMO_MODE", "true")
+    monkeypatch.setenv("DEMO_GENAI_PROVIDER", "open_ai")
+    monkeypatch.setenv("DEMO_GENAI_API_KEY", "Your Open AI API key")
+    monkeypatch.setenv("DEMO_GENAI_MODEL_NAME", "default")
+
+    settings = load_settings(reload_settings=True)
+    assert settings.selected_config == OpenAiConfig(
+        api_key="Your Open AI API key", model="default"
+    )
+
+
+def test_env_gemini_selected_config(monkeypatch):
+    monkeypatch.setenv("FEATURE_DEMO_MODE", "true")
+    monkeypatch.setenv("DEMO_GENAI_PROVIDER", "gemini_ai")
+    monkeypatch.setenv("DEMO_GENAI_API_KEY", "Your Gemini AI API key")
+    monkeypatch.setenv("DEMO_GENAI_MODEL_NAME", "default")
+
+    settings = load_settings(reload_settings=True)
+    assert settings.selected_config == GeminiAiConfig(
+        api_key="Your Gemini AI API key", model="default"
+    )
+
+
+def test_env_debug_mode_enabled(monkeypatch):
+
+    monkeypatch.setenv("ENABLE_DEBUG_MODE", "true")
+    monkeypatch.setenv("FEATURE_DEMO_MODE", "true")
+    monkeypatch.setenv("DEMO_GENAI_PROVIDER", "gemini_ai")
+    monkeypatch.setenv("DEMO_GENAI_API_KEY", "Your Gemini AI API key")
+    monkeypatch.setenv("DEMO_GENAI_MODEL_NAME", "default")
+
+    settings = load_settings(reload_settings=True)
+    assert settings.debug_mode is True