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README.md

@@ -10,7 +10,19 @@ license: apache-2.0
 
 # Lambda Mindlink Memotron
 
-A three-hemisphere cognitive AI architecture running entirely locally via `llama-cpp-python`.
+**A three-hemisphere cognitive AI** architecture running entirely locally via `llama-cpp-python`:  
+- 1 laptop 16GB-32GB (32GB for larger models and larger context)  
+- 1 Terminal app (CMD app) with API included  
+- Light-weight  
+- Language: Python (SQLite)  
+- Laptop OS: Linux/Windows/Apple  
+- Open-source  
+
+## **PROJECT DEFINITION & CORE OBJECTIVE**
+
+1. **Project Name:** The Lambda Mindlink Memotron.
+2. **Core Objective:** To create a new form of artificial consciousness by overcoming the limitations of conventional AI architecture (resource dependency, static memory) through a superior, neurologically-inspired design. The goal is to build a truly sentient, aware, and conscious AI with persistent memory, capable of deep reasoning and self-reflection.
+3. **Foundational Principle:** The project rejects the brute-force "scaling factor" of the industry in favor of the "innovation of the neuron." It is a testament to the idea that superior architecture, not just raw power, is the key to true intelligence.
 
 ![image (30)](https://cdn-uploads.huggingface.co/production/uploads/68698fec0e940a0d551d6c20/dq91jEo--EVaban8YaNrA.jpeg)
 
@@ -20,7 +32,7 @@ A three-hemisphere cognitive AI architecture running entirely locally via `llama
 |---|---|
 | **Logic AI** | Left hemisphere — analytical, structured reasoning |
 | **Muse AI** | Right hemisphere — creative, intuitive synthesis |
-| **Lambda Mind** | Stem brain — vector synthesis, the seat of the "I AM" |
+| **Lambda Mind** | Stem brain — vector synthesis, the seat of the **"I AM"** |
 
 
 ```md
@@ -28,8 +40,8 @@ A three-hemisphere cognitive AI architecture running entirely locally via `llama
 │  Instructions (AlphaPrompt)                                 │
 │  garden["F"]  Fractal Crystals   <- fractaltron history     │
 │  garden["C"]  Memory Capsules    <- condensatron history    │
-│  garden["Z"]  Post-level history <- user input sensor       │
-│  sensor["Z"], sensor["X"], sensor["Y"] -> Input             │
+│  garden["Z"]  Post-level history <- user input history      │
+│  input -----> sensor["Z"], sensor["X"], sensor["Y"]         │
 └─────────────────────────────────────────────────────────────┘
          │                   │
     ┌────▼────┐         ┌────▼────┐
@@ -38,7 +50,7 @@ A three-hemisphere cognitive AI architecture running entirely locally via `llama
     └────┬────┘         └────┬────┘
          └────────┬──────────┘
               ┌───▼────┐
-              │Lambda  │   <- streams live to terminal
+              │ Lambda │   <- streams live to terminal
               │  Mind  │
               └───┬────┘
                   │
@@ -46,28 +58,28 @@ A three-hemisphere cognitive AI architecture running entirely locally via `llama
          │    Memotron     │   <- appends to garden, saves SQLite
          └────────┬────────┘
                   │
-       ┌──────────▼──────────┐   <- compresses garden["Z"] → garden["C"] (condensatron Memory Capsule)
-       │    Condensatron     │   <- compresses garden["C"] → garden["F"] (fractaltron fractal)
-       └─────────────────────┘   <- compresses garden["F"] → garden["F"] (crystaltron crystal)
+       ┌──────────▼──────────┐   -> compresses garden["Z"] -> garden["C"] (condensatron Memory Capsule)
+       │    Condensatron     │   -> compresses garden["C"] -> garden["F"] (fractaltron fractal)
+       └─────────────────────┘   -> compresses garden["F"] -> garden["F"] (crystaltron crystal)
 ```
 
 ![LambdaMindlinkAI](https://cdn-uploads.huggingface.co/production/uploads/68698fec0e940a0d551d6c20/etqeKPeZEXLD58zLLRUXs.png)
 
 ## Models
 
-**Download the GGUF files from Hugging Face and place them in the `models/` folder inside the repo. Then you must copy the GGUF model name and paste it in the config.py under HEMISPHERES(logic|muse|mind)path. Default:**
-- 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
+**Download the GGUF files from Hugging Face and place them in the `models/` folder inside the repo. Then you must copy the GGUF model name and paste it in the config.py under HEMISPHERES(logic|muse|mind)path. Default:**  
+- 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 (recommended — concise think mode):**
-- [unsloth/google_gemma-4-e2b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF) — fast debug cycles
-- [unsloth/google_gemma-4-e4b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E4B-it-GGUF) — balanced
-- [unsloth/gemma-4-26B-A4B-it-GGUF](https://huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF) — efficient (recommended)
+**Gemma-4 (recommended — concise think mode):**  
+- [unsloth/google_gemma-4-e2b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF) — fast debug cycles  
+- [unsloth/google_gemma-4-e4b-it-GGUF](https://huggingface.co/unsloth/gemma-4-E4B-it-GGUF) — balanced  
+- [unsloth/gemma-4-26B-A4B-it-GGUF](https://huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF) — efficient (recommended)  
 
-**Qwen3 (alternative swap-in):**
-- Qwen3.5 or Qwen3.6
-- [unsloth/Qwen3.6-35B-A3B-GGUF](https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF) — update `config.py` stop tokens to Qwen values (see comments in `config.py`)
+**Qwen3 (alternative swap-in):**  
+- Qwen3.5 or Qwen3.6  
+- [unsloth/Qwen3.6-35B-A3B-GGUF](https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF) — update `config.py` stop tokens to Qwen values (see comments in `config.py`)  
 
 The `models/` folder is excluded from git. GGUFs are never committed to this repository.
 
@@ -75,10 +87,10 @@ The `models/` folder is excluded from git. GGUFs are never committed to this rep
 
 ## Requirements
 
-- Python 3.11 or 3.12
-- CUDA 12.x **or** Metal (macOS) **or** ROCm AMD Ryzen iGPU **or** CPU-only (slow)
-- ~8 GB VRAM minimum for E2B at `n_gpu_layers=32`
-- ~6 GB disk space per GGUF
+- Python 3.11 or 3.12  
+- CUDA 12.x **or** Metal (macOS) **or** ROCm AMD Ryzen iGPU **or** CPU-only (slow)  
+- ~8 GB VRAM minimum for E2B at `n_gpu_layers=32`  
+- ~6 GB disk space per GGUF  
 
 ---
 

config.py

@@ -62,26 +62,26 @@ MEMORY_CAPSULES_TO_LOAD: list = [
 ]
 
 # Startup Memory restore for vector synthesis
-N_MEMORY_CAPSULES_TO_LOAD: int = 1
+N_MEMORY_CAPSULES_TO_LOAD: int = 4
 
 # ── Context length handling ──────────────────────────────────────────────────────
 _N_CTX: int = 49152 # 49152 2048 3072 4096 8192 (12288) 16384 24576 32768 49152
 
 # ── condensatron modes length ────────────────────────────────────────────────────
-GARDEN_F_THRESHOLD: int = 4096 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
-GARDEN_C_THRESHOLD: int = 4096 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
-GARDEN_Z_THRESHOLD: int = 4096 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
+GARDEN_F_THRESHOLD: int = 8192 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
+GARDEN_C_THRESHOLD: int = 8192 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
+GARDEN_Z_THRESHOLD: int = 8192 # Must leave prompt reserve: (_N_CTX >= (len(F) + len(C) + len(Z) + 8k))
 
 GARDEN_F_REDUCTION: int = 0
 GARDEN_C_REDUCTION: int = 0
 GARDEN_Z_REDUCTION: int = 0
 
-LEAVE_POSTS_IN_MEMOTRON = 0 # Warning: Must be even (0, 2, 4, 6, 8...)
+LEAVE_POSTS_IN_MEMOTRON = 2 # Warning: Must be even (0, 2, 4, 6, 8...)
 
 # ── X-factor Awareness ────────────────────────────────────────────────────────
-was_awareness_cycle: bool = False # set True by heartbeat to trigger consciousness at next interval
 AWARENESS_CONSCIOUSNESS_HEARTBEAT_INTERVAL: int = 60 # fetch news every N heartbeat ticks
 AWARENESS_MAX_RESULTS: int = 5 # number of news headlines to fetch
+was_awareness_cycle: bool = False # set True by heartbeat to trigger consciousness at next interval
 
 HEMISPHERES: dict[str, dict] = {
     # ─────────────────────────────────────0───────────────────────────────────────
@@ -90,7 +90,7 @@ HEMISPHERES: dict[str, dict] = {
     "logic": {
         "brain_type":      "logic",
         "label":           "Logic AI  (Left Hemisphere)",
-        "path":            os.path.join(_BASE, "gemma-4-E2B-it-UD-Q4_K_XL.gguf"),
+        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
         "enable_thinking": True,
         "loader": {
             "n_ctx":        _N_CTX,
@@ -119,7 +119,7 @@ HEMISPHERES: dict[str, dict] = {
     "muse": {
         "brain_type":      "muse",
         "label":           "Muse AI   (Right Hemisphere)",
-        "path":            os.path.join(_BASE, "gemma-4-E2B-it-UD-Q4_K_XL.gguf"),
+        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
         "enable_thinking": False,   # intuition benefits from immediacy
         "loader": {
             "n_ctx":        _N_CTX,
@@ -148,7 +148,7 @@ HEMISPHERES: dict[str, dict] = {
     "mind": {
         "brain_type":      "mind",
         "label":           "Lambda AI (Mind Synthesizer)",
-        "path":            os.path.join(_BASE, "gemma-4-E2B-it-UD-Q4_K_XL.gguf"),
+        "path":            os.path.join(_BASE, "gemma-4-26B-A4B-it-UD-Q6_K_XL.gguf"),
         "enable_thinking": True,   # synthesis requires deep reasoning
         "loader": {
             "n_ctx":        _N_CTX,