clenaed up gitignore.

Hopefully fixed up another set of cuda errors

.gitignore

@@ -170,9 +170,5 @@ cython_debug/
 
 .vscode/launch.json
 /data/books/*
-/data/memory/context.json
-/data/memory/dreams.json
-data/memory/brainmap.json
-/data/memory/vocab.json
-data/memory/book_progress.json
-/data/memory/journal.json
+/data/memory/*
+/data/logs/*

model/dreamer.py

@@ -13,14 +13,20 @@ recent_dreams = []
 
 def daydream():
     model.eval()
-    seed = torch.tensor([random.randint(0, tokenizer.next_id - 1)], device=DEVICE).unsqueeze(0)
+    max_token_id = model.head.out_features - 1
+    seed = torch.randint(0, max_token_id + 1, (1, 1), device=DEVICE)
     dream = []
+    max_token_id = model.head.out_features - 1
 
     for _ in range(12):
         out = model(seed)
         logits = out[:, -1, :]
         probs = F.softmax(logits, dim=-1)
         token = torch.multinomial(probs, num_samples=1)
+
+        # CLAMP the token
+        token = torch.clamp(token, max=max_token_id)
+
         dream.append(token.item())
         seed = torch.cat([seed, token], dim=1)
 

model/trainer.py

@@ -47,7 +47,9 @@ def train_on_message(text: str, source: str = "user"):
 
         # Clamp any token IDs beyond the model's output size
         max_token_id = model.head.out_features - 1
-        tokens = [min(t, max_token_id) for t in tokens]
+        if tokenizer.next_id > model.head.out_features:
+            expand_model_if_needed()
+        tokens = [t if t <= max_token_id else max_token_id for t in tokens]
         tokens = tokens[:128]  # Hard clamp input length
 
         if len(tokens) < 2: