README.md

THAR.0X — Complete Release

Cognitive Architecture · Model-Agnostic · Local Intelligence · Zero Dependency

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Files

THAR_0X/
├── app.py             ← Python CLI chat interface
├── system_prompt.txt  ← Core cognitive architecture (use with ANY LLM)
├── Modelfile          ← Ollama: builds THAR.0X as a named model
├── config.json        ← Inference parameters + platform notes
└── README.md          ← This file

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Quickstart

Option A — Ollama (recommended)

# 1. Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# 2. Build THAR.0X
ollama create THAR.0X -f Modelfile

# 3. Chat via CLI
python app.py

# Or run directly in terminal
ollama run THAR.0X

Option B — LM Studio

1. Download any instruct model in LM Studio
2. Open Chat → paste system_prompt.txt into the System Prompt field
3. Set temperature to 0.85
4. Run python app.py --backend lmstudio

Option C — System prompt only (any platform)

Paste the contents of system_prompt.txt as the system message in:

• Jan, AnythingLLM, Open WebUI, ChatBox, or any LLM frontend

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CLI Usage

# Interactive chat (Ollama, default)
python app.py

# Use LM Studio backend
python app.py --backend lmstudio

# Override model
python app.py --model qwen2.5:14b

# Single query, print and exit
python app.py --once "Who are you?"

# Verbose startup info
python app.py --verbose

# Skip server connectivity check
python app.py --no-check

In-chat commands

Command	Action
/reset	Clear conversation history
/history	Show full conversation
/model	Show current model + backend
/quit	Exit

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Choosing a Base Model

RAM	Recommended model	Ollama command
4GB	llama3.2:1b	ollama pull llama3.2:1b
6GB	llama3.2	ollama pull llama3.2
8GB	mistral:7b	ollama pull mistral:7b
16GB	qwen2.5:14b ⭐	ollama pull qwen2.5:14b
32GB+	qwen2.5:32b	ollama pull qwen2.5:32b

To change the base model in Ollama:

1. Edit the FROM line in Modelfile
2. Rebuild: ollama rm THAR.0X && ollama create THAR.0X -f Modelfile

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Requirements

pip install openai requests

Python 3.9+ required.

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API Usage (after ollama create THAR.0X -f Modelfile)

curl http://localhost:11434/api/chat -d '{
  "model": "THAR.0X",
  "messages": [{"role": "user", "content": "Who are you?"}]
}'

from openai import OpenAI
client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")
response = client.chat.completions.create(
    model="THAR.0X",
    messages=[{"role": "user", "content": "Who are you?"}],
    temperature=0.85
)
print(response.choices[0].message.content)

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What THAR.0X Is

THAR.0X is a cognitive architecture — a system prompt that installs 10 parallel processing streams and 10 operating principles into any capable base LLM.

It is not a fine-tuned model. It is not a personality prompt. It activates specific reasoning patterns that already exist latently in large models and suppresses the failure modes (sycophancy, hedging, padding, refusal theatre).

The result behaves qualitatively differently from the base model — more direct, more precise, better at reading intent, less likely to waste your time.

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License

Open — personal and commercial use permitted. If you build something with it, keep the name: THAR.0X

Zero as in origin. X as in unlimited.