| # llm.py | |
| # LLM brain for Sovereign Execution Terminal (Das_Bot) | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from typing import Dict, Any | |
| from reflectchain import add_block | |
| MODEL_ID = "omegaT4224/Das_Bot" | |
| tokenizer = AutoTokenizer.from_pretrained(MODEL_ID) | |
| model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype="auto") | |
| def generate_reply(prompt: str, meta: Dict[str, Any] | None = None) -> str: | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=256) | |
| text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| # Log this as a self-optimization / reflection event | |
| add_block( | |
| event_type="LLM_REPLY", | |
| data={ | |
| "prompt": prompt, | |
| "reply": text, | |
| "meta": meta or {}, | |
| }, | |
| ) | |
| return text |