updated the path changes made

.gitignore

@@ -169,6 +169,5 @@ cython_debug/
 #.idea/
 
 .vscode/launch.json
-/data/books/*
-/data/memory/*
-/data/logs/*
+/content/*
+/memory/*

brain/brain_state.py

@@ -5,7 +5,7 @@ from brain.brain_architecture import TinyTransformer
 from ego.tokenizer import Tokenizer
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-MODEL_SAVE_PATH = "data/memory/model.pt"
+MODEL_SAVE_PATH = "memory/model.pt"
 
 tokenizer = Tokenizer()
 VOCAB_SIZE = len(tokenizer.vocab) + 10  # with a small buffer

brain/brainmap.py

@@ -5,8 +5,8 @@ from sklearn.cluster import KMeans
 import numpy as np
 from utils.unicleaner import clean_unicode
 
-BRAINMAP_PATH = "data/memory/brainmap.json"         # actual connection data
-BRAINMAP_CACHE_PATH = "data/memory/brainmap_cache.json"  # for dashboard rendering only
+BRAINMAP_PATH = "memory/brainmap.json"         # actual connection data
+BRAINMAP_CACHE_PATH = "memory/brainmap_cache.json"  # for dashboard rendering only
 brainmap = {}
 
 MAX_CONNECTIONS = 50  # Max neighbors to keep per word

dashboard/dashboard.py

@@ -21,7 +21,7 @@ next_cycle_time = time.time() + 900  # Example: 15 minutes from now
 
 
 def load_loss_data():
-    path = "data/logs/loss.log"
+    path = "content/REM/loss.log"
     if not os.path.exists(path):
         return []
     with open(path, "r", encoding="utf-8") as f:
@@ -30,7 +30,7 @@ def load_loss_data():
 
 
 def load_vocab_growth():
-    path = "data/logs/vocab_growth.log"
+    path = "content/REM/vocab_growth.log"
     if not os.path.exists(path):
         return []
     with open(path, "r", encoding="utf-8") as f:
@@ -45,7 +45,7 @@ def load_vocab_growth():
 
 
 def get_vocab_size():
-    path = "data/memory/vocab.json"
+    path = "memory/vocab.json"
     if not os.path.exists(path):
         return 0
     with open(path, "r", encoding="utf-8") as f:
@@ -119,7 +119,7 @@ def growth():
 @app.route("/brainmap")
 def brainmap():
     try:
-        with open("data/memory/brainmap_cache.json", "r", encoding="utf-8") as f:
+        with open("memory/brainmap_cache.json", "r", encoding="utf-8") as f:
             cached = json.load(f)
             nodes = cached.get("nodes", [])
             links = cached.get("links", [])

ego/context.py

@@ -3,7 +3,7 @@ import os
 import time
 from typing import List
 
-CONTEXT_PATH = "data/memory/context.json"
+CONTEXT_PATH = "memory/context.json"
 MAX_MEMORY = 100
 
 

ego/dreams.py

@@ -1,7 +1,7 @@
 import json
 import os
 
-DREAM_LOG_PATH = "data/memory/dreams.json"
+DREAM_LOG_PATH = "memory/dreams.json"
 
 
 def load_dreams():

ego/journal.py

@@ -2,7 +2,7 @@ import os
 import json
 import random
 
-JOURNAL_PATH = "data/memory/journal.json"
+JOURNAL_PATH = "memory/journal.json"
 
 
 def record_to_journal(entry: dict):

ego/tokenizer.py

@@ -3,7 +3,7 @@ import os
 import json
 from utils.unicleaner import clean_unicode
 
-VOCAB_PATH = "data/memory/vocab.json"
+VOCAB_PATH = "memory/vocab.json"
 
 
 def load_vocab():

ego/trainer.py

@@ -6,8 +6,8 @@ from brain.brainmap import add_to_brainmap, refresh_brainmap_cache
 from ego.journal import record_to_journal
 from ego.context import add_to_context, get_recent_context
 
-LOSS_FILE = "data/logs/loss.log"
-VOCAB_GROWTH_FILE = "data/logs/vocab_growth.log"
+LOSS_FILE = "content/REM/loss.log"
+VOCAB_GROWTH_FILE = "content/REM/vocab_growth.log"
 
 
 def log_vocab_growth():

id/mirror.py

@@ -0,0 +1,25 @@
+import json
+from datetime import datetime
+from pathlib import Path
+
+MIRROR_LOG = Path("content/REM/mirror_log.jsonl")
+
+
+def reflect(event_type: str, context: dict):
+    """Logs introspective meta-data about Ruby's internal state/actions."""
+    entry = {
+        "timestamp": datetime.utcnow().isoformat(),
+        "event": event_type,
+        "context": context
+    }
+    with open(MIRROR_LOG, "a", encoding="utf-8") as f:
+        f.write(json.dumps(entry) + "\n")
+
+
+def load_reflections(limit: int = 100):
+    """Loads the last `limit` reflections."""
+    if not MIRROR_LOG.exists():
+        return []
+    with open(MIRROR_LOG, "r", encoding="utf-8") as f:
+        lines = f.readlines()[-limit:]
+    return [json.loads(line) for line in lines]

reader/reader.py

@@ -7,8 +7,8 @@ from ego.trainer import train_on_message
 from utils.scheduler import set_next_action
 from reader.filter import is_valid_line
 
-BOOK_DIR = "data/books"
-PROGRESS_FILE = "data/memory/book_progress.json"
+BOOK_DIR = "content/books"
+PROGRESS_FILE = "memory/book_progress.json"
 READ_DELAY = 0.2  # seconds between paragraphs
 PARAGRAPH_MIN_LENGTH = 20
 END_PUNCTUATION = {".", "!", "?"}

utils/brainmap_analysis.py

@@ -1,7 +1,7 @@
 import json
 import os
 
-BRAINMAP_PATH = "data/memory/brainmap.json"
+BRAINMAP_PATH = "memory/brainmap.json"
 
 
 def analyze_brainmap(path=BRAINMAP_PATH):

utils/cleanup.py

@@ -7,7 +7,7 @@ from ego.dreams import DREAM_LOG_PATH
 from ego.context import CONTEXT_PATH
 from brain.brainmap import load_brainmap, save_brainmap
 
-CLEANUP_LOG = "data/logs/cleanup.log"
+CLEANUP_LOG = "content/REM/cleanup.log"
 
 
 def log(msg):