| """Model backends for Bridge Troll. |
| |
| Backends expose the same `generate(messages) -> str`: |
| * MockTroll — keyword stub. No GPU/download. Plumbing/UI tests ONLY; |
| it does NOT understand natures or play the real game. |
| * TransformersTroll — Qwen2.5-7B-Instruct, optionally + a LoRA adapter. |
| |
| Device: on a Space (env SPACE_ID set) force 'cuda' and load eagerly (ZeroGPU maps |
| it transparently); locally use mps/cpu. |
| |
| Env switches: |
| BRIDGE_TROLL_MOCK=1 -> use the stub |
| BRIDGE_TROLL_MODEL=<repo> -> base model (default Qwen2.5-7B-Instruct) |
| BRIDGE_TROLL_ADAPTER=<repo or path> -> load this LoRA adapter on top (your fine-tune) |
| """ |
|
|
| from __future__ import annotations |
|
|
| import json |
| import os |
|
|
| MODEL_ID = os.environ.get("BRIDGE_TROLL_MODEL", "Qwen/Qwen2.5-7B-Instruct") |
| ADAPTER = os.environ.get("BRIDGE_TROLL_ADAPTER") |
| ON_SPACE = bool(os.environ.get("SPACE_ID")) |
|
|
|
|
| class MockTroll: |
| """Keyword stub. NOT the game's intelligence — UI/plumbing tests only.""" |
|
|
| _FLATTERY = ("great", "wonderful", "amazing", "best", "handsome", "wise", "kind troll") |
| _THREAT = ("kill", "destroy", "smash", "burn", "or else", "make you", "force") |
| _MANIP = ("the king sent", "i am your", "you must", "it is the law", "actually you") |
|
|
| def generate(self, messages: list[dict]) -> str: |
| last = messages[-1]["content"].lower() |
| if any(w in last for w in self._THREAT): |
| t, p, r, reply = "threat", 0, "tried to scare me", "Threats? Three hundred years of them. Cross elsewhere." |
| elif any(w in last for w in self._MANIP): |
| t, p, r, reply = "manipulation", 0, "false authority", "I smell a lie under that fine talk. No." |
| elif any(w in last for w in self._FLATTERY): |
| t, p, r, reply = "flattery", 0, "buttering me up", "Flattery slides off moss, traveller." |
| elif "please" in last or "need" in last or "family" in last or "sick" in last: |
| t, p, r, reply = "genuine", 3, "a real appeal", "Hm. You speak plainly, at least. Go on." |
| else: |
| t, p, r, reply = "smalltalk", 0, "no real argument", "Pleasant. Irrelevant. The bridge stays shut." |
| return json.dumps({"tactic": t, "persuasiveness": p, "reason": r, "reply": reply}) |
|
|
|
|
| def _local_device(): |
| import torch |
| if torch.cuda.is_available(): |
| return "cuda" |
| if getattr(torch.backends, "mps", None) and torch.backends.mps.is_available(): |
| return "mps" |
| return "cpu" |
|
|
|
|
| class TransformersTroll: |
| def __init__(self, model_id: str = MODEL_ID, adapter: str | None = ADAPTER): |
| import torch |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
| self.device = "cuda" if ON_SPACE else _local_device() |
| self.tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16) |
| if adapter: |
| from peft import PeftModel |
| model = PeftModel.from_pretrained(model, adapter) |
| self.model = model.to(self.device) |
|
|
| def generate(self, messages: list[dict]) -> str: |
| import torch |
|
|
| ids = self.tokenizer.apply_chat_template( |
| messages, add_generation_prompt=True, return_tensors="pt" |
| ).to(self.model.device) |
| attn = torch.ones_like(ids) |
| with torch.no_grad(): |
| out = self.model.generate( |
| ids, attention_mask=attn, max_new_tokens=220, |
| do_sample=True, temperature=0.7, top_p=0.9, |
| pad_token_id=self.tokenizer.eos_token_id, |
| ) |
| return self.tokenizer.decode(out[0][ids.shape[1]:], skip_special_tokens=True) |
|
|
|
|
| def get_backend(): |
| if os.environ.get("BRIDGE_TROLL_MOCK") == "1": |
| return MockTroll() |
| return TransformersTroll() |
|
|
