feat: implement centralized configuration management and update default model to gemini-2.5-pro

.env

@@ -1,2 +1,2 @@
 GEMINI_API_KEY=AQ.Ab8RN6K-wFpuRR3mv7AUv7p6QqXf98Dlth0IRF3N42UIfjCEbw
-GEMINI_MODEL_NAME=gemini-2.5-flash
+GEMINI_MODEL_NAME=gemini-2.5-pro

src/recommendation_engine/config.py

@@ -13,11 +13,13 @@ DEBUG_MODE = os.getenv("DEBUG_MODE", "true").lower() == "true"
 
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY", "")
 
+# Primary model — reads GEMINI_MODEL_NAME from .env first, then PRIMARY_MODEL,
+# then falls back to gemini-2.5-pro (smart: advanced reasoning, high quality output).
 MODEL_CANDIDATES = [
-    os.getenv("PRIMARY_MODEL", "gemini-3.1-flash-lite-preview"),
-    os.getenv("FAST_MODEL", "gemini-2.5-flash-lite"),
-    os.getenv("BALANCED_MODEL", "gemini-2.5-flash"),
-    os.getenv("QUALITY_MODEL", "gemini-2.5-pro"),
+    os.getenv("GEMINI_MODEL_NAME") or os.getenv("PRIMARY_MODEL", "gemini-2.5-pro"),
+    os.getenv("FAST_MODEL",     "gemini-2.5-flash"),   # fast fallback
+    os.getenv("BALANCED_MODEL", "gemini-2.5-flash"),   # same tier fallback
+    os.getenv("QUALITY_MODEL",  "gemini-3.1-flash-lite"), # lightweight last resort
 ]
 
 _seen = set()