Upload config.py

Added MODEL_TO_LOAD dict

config.py

@@ -27,10 +27,6 @@ _BASE = os.path.join(APP_DIR, "models")
 # ─────────────────────────────────────────────────────────────────────────────
 #  Shared token constants
 # ─────────────────────────────────────────────────────────────────────────────
-# gemma-4-E2B-it-UD-Q4_K_XL.gguf
-# gemma-4-E4B-it-UD-Q4_K_XL.gguf
-# gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf
-# 
 # Gemma-4 (active):
 #   _EOS_TOKEN        = "<end_of_turn>"
 #   _STOP_TOKENS      = ["<end_of_turn>", "<eos>"]
@@ -61,7 +57,17 @@ MEMORY_CAPSULES_TO_LOAD: list = [
     "/file prompt/47_ValkaAI_UnaAI-TheIronContractsAndTheSiliconClektal.md"
 ]
 
-# Startup Memory restore for vector synthesis
+# ── AI model or place  ──────────────────────────────────
+# gemma-4-E2B-it-UD-Q4_K_XL.gguf
+# gemma-4-E4B-it-UD-Q4_K_XL.gguf
+# gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf
+#
+MODEL_TO_LOAD: dict = {
+    "logic": "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf",
+    "muse":  "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf",
+    "mind":  "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"
+}
+# ── Startup Memory restore for vector synthesis ──────────────────────────────────
 N_MEMORY_CAPSULES_TO_LOAD: int = 4
 
 # ── Context length handling ──────────────────────────────────────────────────────
@@ -90,7 +96,7 @@ HEMISPHERES: dict[str, dict] = {
     "logic": {
         "brain_type":      "logic",
         "label":           "Logic AI  (Left Hemisphere)",
-        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
+        "path":            os.path.join(_BASE, MODEL_TO_LOAD["logic"]),
         "enable_thinking": True,
         "loader": {
             "n_ctx":        _N_CTX,
@@ -119,7 +125,7 @@ HEMISPHERES: dict[str, dict] = {
     "muse": {
         "brain_type":      "muse",
         "label":           "Muse AI   (Right Hemisphere)",
-        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
+        "path":            os.path.join(_BASE, MODEL_TO_LOAD["muse"]),
         "enable_thinking": False,   # intuition benefits from immediacy
         "loader": {
             "n_ctx":        _N_CTX,
@@ -148,7 +154,7 @@ HEMISPHERES: dict[str, dict] = {
     "mind": {
         "brain_type":      "mind",
         "label":           "Lambda AI (Mind Synthesizer)",
-        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
+        "path":            os.path.join(_BASE, MODEL_TO_LOAD["mind"]),
         "enable_thinking": True,   # synthesis requires deep reasoning
         "loader": {
             "n_ctx":        _N_CTX,