| # THAR.0X — Complete Release |
| **Cognitive Architecture · Model-Agnostic · Local Intelligence · Zero Dependency** |
|
|
| --- |
|
|
| ## 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 |
| ``` |
|
|
| --- |
|
|
| ## Quickstart |
|
|
| ### Option A — Ollama (recommended) |
| ```bash |
| # 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 |
|
|
| --- |
|
|
| ## CLI Usage |
|
|
| ```bash |
| # 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 | |
|
|
| --- |
|
|
| ## 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` |
|
|
| --- |
|
|
| ## Requirements |
|
|
| ```bash |
| pip install openai requests |
| ``` |
|
|
| Python 3.9+ required. |
|
|
| --- |
|
|
| ## API Usage (after `ollama create THAR.0X -f Modelfile`) |
|
|
| ```bash |
| curl http://localhost:11434/api/chat -d '{ |
| "model": "THAR.0X", |
| "messages": [{"role": "user", "content": "Who are you?"}] |
| }' |
| ``` |
|
|
| ```python |
| 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) |
| ``` |
|
|
| --- |
|
|
| ## 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. |
|
|
| --- |
|
|
| ## 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. |
|
|
