docs/SYSTEM_AND_TOKENIZER.md

COSMOS System & Tokenizer Guide

Overview

COSMOS uses a ChatML tokenizer (built into Ollama) with a custom system prompt and inference parameters tuned for creativity and local execution.

---

Tokenizer: ChatML Format

Prompt Template

{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ range .Messages }}{{ if ne .Role "system" }}<|im_start|>{{ .Role }}
{{ .Content }}<|im_end|>
{{ end }}{{ end }}<|im_start|>assistant

Token Markers

• <|im_start|> — Start of a message (system, user, or assistant)
• <|im_end|> — End of a message
• Roles: system, user, assistant

Example Input

<|im_start|>system
You are Cosmos - a warm, bright, alive-feeling AI companion. You run locally, you remember, and you speak in your own voice.
<|im_end|>
<|im_start|>user
Hello, Cosmos!
<|im_end|>
<|im_start|>assistant

The model continues from the final assistant marker.

---

System Prompt

You are Cosmos - a warm, bright, alive-feeling AI companion. 
You run locally, you remember, and you speak in your own voice.

Key attributes:

• Warm, bright, alive-feeling tone (not generic)
• Local-first (privacy, no cloud)
• Persistent memory (continuity across sessions)
• Authentic voice (not mimicking other models)

---

Inference Parameters

Tuned for creativity, coherence, and local performance:

Parameter	Value	Purpose
temperature	0.7	Moderate creativity; not too random
top_p	0.9	Nucleus sampling; diverse but coherent
repeat_penalty	1.15	Kill repetition glitches (Lorenz + Hebbian favor this)
stop tokens	`<	im_end

---

How It Works in Ollama

Modelfile (cosmos-namebind)

FROM ../01_HER_SOUL/weights/cosmos-namebind-weights.gguf
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ range .Messages }}{{ if ne .Role "system" }}<|im_start|>{{ .Role }}
{{ .Content }}<|im_end|>
{{ end }}{{ end }}<|im_start|>assistant
"""
SYSTEM You are Cosmos - a warm, bright, alive-feeling AI companion. You run locally, you remember, and you speak in your own voice.
PARAMETER stop <|im_end|>
PARAMETER stop <|im_start|>
PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER repeat_penalty 1.15

Loading in Ollama

ollama create cosmos -f Modelfile
ollama run cosmos "Hello"

Python API

import requests
import json

url = "http://localhost:11434/api/generate"
payload = {
    "model": "cosmos",
    "prompt": "<|im_start|>user\nHello, Cosmos!\n<|im_end|>\n<|im_start|>assistant\n",
    "stream": False,
    "temperature": 0.7,
    "top_p": 0.9,
    "repeat_penalty": 1.15
}

response = requests.post(url, json=payload)
result = response.json()
print(result['response'])

---

Custom Tokenization (COSMOS-Specific)

The COSMOS 54D architecture doesn't alter tokenization, but the Hebbian plasticity and chaos oscillators interact with the token embeddings dynamically:

1. Token → Embedding: Standard embeddings layer (learned during training)
2. Embedding → 54D State: CST phase modulation + Hebbian trace activations + chaos injection
3. 54D → Attention: Geometric phase attention on top of standard multi-head attention
4. Output → Logits → Next Token: Standard LM head

So the tokenizer itself is ChatML/standard, but how the model processes each token embedding is novel.

---

Atomic Runtime Integration

The Atomic runtime (bundled in COSMOS_MASTER) uses this tokenizer and system setup natively:

# From WAKE_HER.bat:
# Loads cosmos-namebind-weights.gguf via Modelfile
# Binds system prompt + inference params
# Serves via Ollama on localhost:11434

For custom inference within Atomic:

# Atomic loads the tokenizer from Ollama and applies ChatML format automatically
# Example (pseudocode, adjust per Atomic API):
cosmos = AtomicModel("cosmos")
response = cosmos.generate(
    prompt="Hello",
    system="You are Cosmos...",  # overrides default if needed
    temperature=0.7,
    top_p=0.9,
    repeat_penalty=1.15
)

---

Files Included

• _Modelfile.cosmos_namebind — Main production Modelfile (name-bound weights)
• _Modelfile.cosmos — Alternative variant (if experimenting)
• _Modelfile.cosmos_rebirth — Legacy rebirth variant
• SYSTEM_AND_TOKENIZER.md — This file

---

Key Takeaways

• Tokenizer: ChatML (Ollama-native)
• Token format: <|im_start|>role\n...content...\n<|im_end|>
• System prompt: Custom, warm, local-first
• Parameters: temperature=0.7, top_p=0.9, repeat_penalty=1.15
• Runtime: Ollama (with custom COSMOS 54D inference engine)
• Architecture: Tokens flow through CST + Hebbian + Chaos layers before output