SynapseOS: Potato-Grade Linux Distro & 7-Lab Native AI Workbench

• Base OS: Debian 12 Bookworm (minbase, x86_64) + Xorg + Openbox + Tint2 + tty1 autologin (242 MB live idle RAM).
• Synapse Studio & Synapse Kids Arcade: Native GTK3 + Cairo 60 FPS AI Workbench (62.9 MB full runtime RSS, 3.27 ms/frame at 1280x720, 0 KB texture bloat, 0.09s cold start) featuring:
  • Full-Screen Synapse Kids Mode (workbench/kid_arcade_view.py): Gamified Scratch-style classroom UI with 1-click L1–L7 Level Selector Pills, interactive canvas clicks across all 7 levels, NEAT Moon Lander solar panels/callouts & Lunar Landing Pad touchdown physics, live swirling 2D Color Sorter Brain, waving Cortex-Phi3 Robot Mascot + Speech Bubble, live mission checkboxes, 3-star scoring, and 1-click English / French (EN ▸ FR) toggle.
  • ⚙ Teacher / Pro Workstation Mode (workbench/studio_gui.py): Full 3-column engineering interface with 35 curated Lab Examples (5 per lab), 14 Classroom Tutorials, Direct Structural Brain Surgery (+ / - Neurons & Synapses), live FPS / PRIME C99 tok/s / Phi-3 tok/s & TTFT / RAM telemetry, 60 FPS Animated Phi-3 + PRIME Brain Visualizer, General Chat Mode, Safe Linux Command Runner, and Encrypted Remote Browser Tunnel (synapse-tunnel).
• Three-Tier Local AI Engine:
  1. Tier 1 (0.68 ms, 92 KB): SQLite FTS5 BM25 offline knowledge base (cortex_kb.sqlite).
  2. Tier 2 (8,737 tok/s on BC-250 / 6,738 tok/s potato CPU, 262 KB constant $\mathcal{O}(1)$ RAM, zero AVX2 required): Native C99 PRIME Moment Sliding-Window Attention engine (libprime.so / prime-moment, integrated from batteryphil/PRIME-Moment-Attention).
  3. Tier 3 (24.8 tok/s on AMD BC-250 / 11.6 tok/s 4-core CPU, 2.2 GB): Local cortex-phi3:latest (Phi-3-Mini-4K-Instruct Q4_K_M, num_ctx=1024).

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1. Complete Tester Instructions: Download & Boot SynapseOS (Full 2.6 GB LLM ISO or 437 MB Lite ISO)

• 1-Click Single-File Full 2.6 GB LLM .iso Download (Hugging Face — No Reassembly Needed): 👉 SynapseOS-Debian12-Potato-x86_64.iso (2.6 GB Direct Download) | Browse Hugging Face Repo | SHA256 Checksum
• GitHub Release Page (v1.0-k12): 👉 https://github.com/batteryphil/SynapseOS/releases/tag/v1.0-k12

Option A: Linux / macOS — 1-Command Full LLM ISO Download & Boot (2.6 GB)

Includes everything 100% offline: Debian 12 + Openbox + the fine-tuned cortex-phi3:latest LLM (2.2 GB GGUF) + Ollama daemon + C99 prime-moment engine + 7 AI Labs + all 325 K–12 lessons + offline espeak-ng Read-Aloud TTS.

# 1. Clone the repository
git clone https://github.com/batteryphil/SynapseOS.git
cd SynapseOS

# 2. Download, reassemble, verify SHA256, and boot in QEMU (4 GB RAM, 2 CPU Cores):
./scripts/download_and_boot_full_iso.sh

# Or download & verify the .iso file only (for VirtualBox, VMware, or flashing to USB):
./scripts/download_and_boot_full_iso.sh --download
# Output file: output/SynapseOS-Debian12-Potato-x86_64.iso

Option B: Windows (PowerShell) — Download & Combine the Full 2.6 GB LLM ISO

Because GitHub Releases caps individual files at 2.0 GB, the 2.6 GB Full ISO is split into part-aa (1.85 GB) and part-ab (706 MB). Run this in PowerShell to download and join them into SynapseOS-Debian12-Potato-x86_64.iso:

# 1. Download both parts and checksum from GitHub Releases
curl.exe -L -O https://github.com/batteryphil/SynapseOS/releases/download/v1.0-k12/SynapseOS-Debian12-Potato-x86_64.iso.part-aa
curl.exe -L -O https://github.com/batteryphil/SynapseOS/releases/download/v1.0-k12/SynapseOS-Debian12-Potato-x86_64.iso.part-ab
curl.exe -L -O https://github.com/batteryphil/SynapseOS/releases/download/v1.0-k12/SynapseOS-Debian12-Potato-x86_64.iso.sha256

# 2. Combine into a single bootable .iso file (binary copy)
cmd /c "copy /b SynapseOS-Debian12-Potato-x86_64.iso.part-aa + SynapseOS-Debian12-Potato-x86_64.iso.part-ab SynapseOS-Debian12-Potato-x86_64.iso"

# 3. Verify SHA256 hash matches SynapseOS-Debian12-Potato-x86_64.iso.sha256
Get-FileHash .\SynapseOS-Debian12-Potato-x86_64.iso -Algorithm SHA256
Get-Content .\SynapseOS-Debian12-Potato-x86_64.iso.sha256

Option C: Boot in VirtualBox, VMware, or from a Physical USB Stick

1. VirtualBox / VMware / Proxmox:
   • Create a new Linux (Debian 64-bit) VM with 4096 MB (4 GB) RAM and 2 CPU Cores (works down to 1 CPU core). No virtual hard disk is required.
   • Attach SynapseOS-Debian12-Potato-x86_64.iso as the Optical CD/DVD drive and boot.
2. Flash to a Physical USB Drive (Boot on Any PC/Laptop):
   • Windows / macOS: Use BalenaEtcher or Rufus (select DD Image mode if prompted) and flash SynapseOS-Debian12-Potato-x86_64.iso.
   • Linux:

     sudo dd if=output/SynapseOS-Debian12-Potato-x86_64.iso of=/dev/sdX bs=4M status=progress oflag=sync
     

Option D: Fast Lite ISO (437 MB, No LLM — Single File or In-Repo)

If you want a fast 437 MB download without the 2.2 GB LLM weights (still includes the C99 prime-moment engine, cortex_kb.sqlite, 7 AI Labs, and all 325 K–12 lessons):

• Direct Single-File Download: SynapseOS-Lite-x86_64.iso (437 MB on GitHub Releases)
• Or Decompress From Git Repo:

  ./iso/decompress_iso.sh
  qemu-system-x86_64 -enable-kvm -m 2048 -smp 2 -cdrom iso/SynapseOS-Lite-x86_64.iso
  

What Happens on Boot & Tester Checklist

• Auto-Login: Boots directly into X11 + Openbox (~148 MB idle OS RAM) as user synapse (password: synapse, passwordless sudo) and launches Synapse Studio automatically.
• Synapse Kids Mode (Default View):
  • Click L1–L7 level pills at the top to play the 7 interactive AI simulations (Moon Lander, Lidar Car, GridWorld, CartPole, Neural Net, Predator-Prey Swarm, PRIME Attention).
  • Click ♪ Read (or click Lumi the Robot) to hear offline speech synthesis read the mission aloud.
  • Click EN ▸ FR to toggle everything between English and French, or ❖ Student ↻ to switch student profiles.
• Teacher / Pro Workstation & Full K–12 School Curriculum:
  • Click ⚙ Teacher in the top-right corner to switch to the 3-column Pro/School Workstation.
  • Open the 🎓 School tab on the right: pick any grade from Kindergarten (Yr K) to Grade 12 (Yr 12) (325 complete textbook lessons across Math, Science, ELA, History, and AI).
  • Answer the multiple-choice check using the Quiz: [A] [B] [C] [D] bar at the bottom of the textbook reader, or click ▶ Load Lab & Code to run and auto-grade the Python worksheet.
  • Open the 📋 Report tab and click ✎ Export to generate a printable HTML + TXT K–12 Report Card & Honors Certificate.
• Built-In Fine-Tuned cortex-phi3 LLM + C99 PRIME Copilot:
  • Type any question into the AI Copilot Chat bar at the bottom of the window (or open a terminal and run ollama run cortex-phi3 or cortex ai "explain neuroevolution").

ISO Artifact	Uncompressed Rootfs	SquashFS	Bootable .iso Size	How to Get It	Contents
SynapseOS-Debian12-Potato-x86_64.iso (Full LLM)	3,998.0 MB	2,546.1 MB (zstd)	2.6 GB	./scripts/download_and_boot_full_iso.sh or Release v1.0-k12	Everything in Lite + pre-baked 2.2 GB cortex-phi3:latest GGUF + Ollama runtime + espeak-ng TTS
SynapseOS-Lite-x86_64.iso (Lite)	1,561.8 MB	376.5 MB (xz -Xbcj x86)	437 MB	Direct Download or ./iso/decompress_iso.sh	Debian 12 + Openbox + 7 AI Labs + 325 K–12 Lessons + cortex_kb.sqlite + C99 prime-moment (libprime.so)

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2. 7 Native GTK3 + Cairo AI Labs (workbench/) — 35 Presets (5 per Lab)

Lab	Paradigm	Interactive Parameters & Brain Surgery	Headless CPU Speed (12 gens)
1. NEAT Rocket Moon Lander	Neuroevolution (NEAT)	Gravity, Crosswind, Thruster Power, Safe Landing Speed, Pop Size, Add-Neuron/Synapse Rate, Mutation Power, Target Hidden Neurons	24.1 ms
2. NEAT Self-Driving Lidar Car	Autonomous Control (NEAT)	Lidar Ray Range, Max Speed, Steering Agility, Track Width, Pop Size, Mutation, Target Hidden Neurons	189.4 ms
3. RL Hazard GridWorld	Tabular RL (Q-Learning & SARSA)	Learning Rate ($\alpha$), Discount ($\gamma$), Exploration ($\epsilon$), Lava Penalty, Goal Reward, Slippery Wind	8.2 ms
4. CartPole Balance	Neuro-Policy Control	Gravity, Pole Length, Motor Force, Wind Gusts, Pop Size, Mutation Power, Target Hidden Neurons	31.6 ms
5. Neural Network Backprop	Deep Learning (MLP)	Dataset (XOR, Circles, Moons, Spiral), Hidden Neurons, LR ($\eta$), L2 ($\lambda$), Noise, Batch Steps	64.5 ms
6. Predator-Prey Swarm	Co-Evolutionary Boids	Prey Flock Size, Predator Count, Vision Radius, Max Speeds, Cohesion Drive, Food Density	42.8 ms
7. PRIME Moment Attention	Hybrid Sliding Window + $\mathcal{O}(1)$ C99 Memory	Context Tokens ($N$), Local Window ($W$), PRIME Moments ($K$), EMA Decay ($\gamma$), Recall Temp, Threads	14.2 ms (8,737 tok/s C99)

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3. CLI, Remote Browser Tunnel & Test Commands

# Launch the 7-Lab GTK3 + Cairo AI Workbench GUI (starts in Synapse Kids mode by default; set SYNAPSE_INITIAL_MODE=pro for Teacher Mode)
./synapse studio

# Start encrypted HTTPS Remote Browser Tunnel (noVNC + Cloudflare Quick Tunnel)
./bin/synapse-tunnel synapse-ai

# Run headless benchmark across all 7 AI Labs
./synapse studio --benchmark --gens 12

# Run the native C99 PRIME-Moment O(1) Attention benchmark (10,000 tokens)
./cortex/c_prime/bin/prime

# Query the Three-Tier Cortex Copilot (FTS5 + C99 PRIME Moment + Ollama)
./synapse cortex cmd "compress directory with zstd"
./synapse cortex ai "prime moment attention"

# Rebuild the Lite ISO (385 MB, no LLM) or Full ISO (2.5 GB, with LLM)
./distro/build-iso.sh --lite
./distro/build-iso.sh --all

# Browse & manage the Complete K-12 Rolling Curriculum (Kindergarten + Grades 1-12)
./synapse pack list-years
./synapse pack set-year K            # Install Kindergarten (year_00)
./synapse pack set-year 1            # Install Grade 1 (year_01), wipes old year files, keeps Transcript
./synapse curriculum y00_math        # Run Kindergarten Math + AI Lab
./synapse curriculum y08_science_q2  # Run Grade 8 Science Quarter 2 (Winter Unit) + AI Lab
./synapse pack advance-year          # Graduate to next School Year (wipes old year, saves Report Card)

# Run all automated unit & integration tests
python3 -m unittest discover -s tests

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4. Complete K–12 Rolling Year-by-Year School Curriculum (curricula/year_00.json – year_12.json)

Every grade from Kindergarten (year_00 / Grade K) through Grade 12 (year_12 / Senior Capstone) (13 complete grades) includes 5 Full-Year Subject Courses + 20 Quarterly Unit Lessons (Q1 Fall, Q2 Winter, Q3 Spring, Q4 Capstone) = 325 total K–12 lessons + 91 bilingual EN/FR visual levels:

1. 📐 Mathematics (Counting & Shapes $\rightarrow$ Arithmetic $\rightarrow$ Fractions/Ratios $\rightarrow$ Algebra & Geometry $\rightarrow$ Pre-Calculus, Calculus & Linear Algebra)
2. 🔬 Science (5 Senses & Weather $\rightarrow$ Forces & Ecosystems $\rightarrow$ Genetics, Waves & Chemistry $\rightarrow$ Physics, Thermodynamics & Computational Neuroscience)
3. 📖 Reading & Language Arts (ELA) (Alphabet Phonics $\rightarrow$ Reading Comprehension & Grammar $\rightarrow$ Claim-Evidence-Reasoning (CER) $\rightarrow$ Rhetoric & Technical Peer Review)
4. 🌍 Social Studies & History (Classroom Civics & Maps $\rightarrow$ Ancient Civilizations & U.S./World History $\rightarrow$ Constitution & Economics $\rightarrow$ AI Ethics, Public Policy & TCO)
5. 🤖 Connected AI & Coding Assignment (Hands-on simulation + auto-graded Python worksheet tied directly to that grade's Math, Science, ELA, and History lessons)

Every lesson contains 6 Complete Textbook Sections:

• Section 1: Core Textbook Lesson & National Standards Alignment (CCSS Math, NGSS Science, CCSS ELA, NCSS C3, CSTA CS)

• Section 2: Full 36-Week / 4-Quarter Course Syllabus (Q1 Weeks 1–9, Q2 Weeks 10–18, Q3 Weeks 19–27, Q4 Weeks 28–36)

• Section 3: Academic Vocabulary Glossary (Terms & Definitions)

• Section 4: Step-by-Step Worked Textbook Examples

• Section 5: Traditional Practice Worksheet & Self-Check Quiz (with Answer Key)

• Section 6: Teacher Guide & 100-Point Mastery Rubric (40 pts Core Subject + 30 pts Quiz + 30 pts AI Lab & Python Code)

• 1-Year-at-a-Time Potato Storage Wiper: Only one school year's curriculum package resides in active classroom storage (~/.config/synapse-os/active_pack/current_pack.json). Advancing a student (./synapse pack advance-year or clicking ★ Yr X ↻ in the Teacher Report tab) wipes the old year's pack and scratch files while permanently preserving the student's Cumulative Multi-Subject Report Card Transcript, Gold Trophies, Coins, and High Scores in student_profile.json.

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5. Repository Structure

synapse-os/
├── synapse                                # Unified CLI entrypoint
├── SYNAPSE_OS_SPECS.txt                   # Full technical architecture & benchmark specification
├── curricula/
│   ├── index.json                         # Master manifest of all 13 K-12 School Year Curricula (K-12)
│   └── year_00.json .. year_12.json       # Hosted Kindergarten + Grades 1-12 complete textbook packages
├── bin/
│   ├── synapse-studio                     # Studio desktop launcher
│   └── synapse-tunnel                     # Encrypted HTTPS noVNC + Cloudflare remote classroom tunnel
├── iso/
│   ├── SynapseOS-Lite-x86_64.iso.zst.part-* # 5 chunks (<90 MB each, 374 MB total) of the 385 MB Lite ISO
│   ├── SynapseOS-Lite-x86_64.iso.sha256   # SHA256 checksum for verification
│   └── decompress_iso.sh                  # 1-command ISO reassembly + zstd decompression + SHA256 check
├── cortex/
│   ├── engine.py                          # Three-tier AI engine (FTS5 + C99 PRIME Moment + Ollama + Safety Shield)
│   ├── prime_window.py                    # ctypes binding to libprime.so + O(W+K) context compressor
│   ├── c_prime/                           # Native C99 PRIME-Moment & Sim kernels (GCC + Cosmopolitan + Fil-C)
│   ├── knowledge/cortex_kb.sqlite         # 92 KB SQLite FTS5 BM25 database
│   └── forge/
│       ├── Modelfile.phi3                 # Fast-TTFT (num_ctx=1024) Ollama Modelfile
│       ├── cortex_phi3_train.jsonl        # Curated instruction-tuning dataset
│       ├── hybrid_prime_attention.py      # PyTorch causal-mask Transformer surgery for Phi-3 & Qwen2
│       └── train_phi3_qlora.py            # 4-bit NF4 QLoRA trainer with GPU hardware guardrail
├── workbench/
│   ├── studio_gui.py                      # GTK3 + Cairo 60 FPS 7-Lab GUI + K-12 Teacher Report Card
│   ├── kid_arcade_view.py                 # Full-screen Synapse Kids gamified view (EN/FR toggle)
│   ├── k12_curricula.py                   # 12-Year K-12 Traditional Subjects + AI Curriculum generator
│   ├── pack_manager.py                    # 1-Year-at-a-Time Wiper & Persistent Student Transcript Vault
│   ├── labs/prime_attention_lab.py        # Lab 7: Interactive O(N^2) vs O(W+K) PRIME Moment simulator
│   ├── curriculum.py                      # 35 Lab Examples (5 per lab) & classroom missions
│   └── sandbox_runner.py                  # Subprocess Python sandbox (8s timeout)
├── distro/
│   └── build-iso.sh                       # Debian 12 Live ISO builder (--lite for 385 MB, --all for 2.5 GB)
└── tests/                                 # Automated unit & integration test suite (32 tests)