repository/intel_npu.py

import json
from pathlib import Path

from intel_npu_acceleration_library import NPUModelForCausalLM, int4
from intel_npu_acceleration_library.compiler import CompilerConfig
from transformers import AutoTokenizer

from repository.repository_abc import Repository, Model


class IntelNpuRepository(Repository):
 def __init__(self, model_info: Model, system_msg: str = None, log_to_file: Path = None):
 self.model_info: Model = model_info
 self.message_history: list[dict[str, str]] = []
 self.set_message_for_role(self.model_info.roles.system_role, system_msg)
 self.model = None
 self.tokenizer = None
 self.terminators = None
 self.log_to_file = log_to_file

 def get_model_info(self) -> Model:
 return self.model_info

 def get_message_history(self) -> list[dict[str, str]]:
 return self.message_history

 def init(self):
 compiler_conf = CompilerConfig(dtype=int4)
 self.model = NPUModelForCausalLM.from_pretrained(self.model_info.name, use_cache=True, config=compiler_conf,
 export=True, temperature=0).eval()
 self.tokenizer = AutoTokenizer.from_pretrained(self.model_info.name)
 self.terminators = [self.tokenizer.eos_token_id, self.tokenizer.convert_tokens_to_ids("<|eot_id|>")]

 def send_prompt(self, prompt: str, add_to_history: bool = True) -> dict[str, str]:
 print("prompt to be sent: " + prompt)
 user_prompt = {"role": self.model_info.roles.user_role, "content": prompt}
 if self.log_to_file:
 with open(self.log_to_file, "a+") as log_file:
 log_file.write(json.dumps(user_prompt, indent=2))
 log_file.write("\n")
 self.get_message_history().append(user_prompt)
 input_ids = (self.tokenizer.apply_chat_template(self.get_message_history(), add_generation_prompt=True,
 return_tensors="pt")
 .to(self.model.device))
 outputs = self.model.generate(input_ids, eos_token_id=self.terminators, do_sample=True, max_new_tokens=2000, cache_position=None)
 generated_token_array = outputs[0][len(input_ids[0]):]
 generated_tokens = "".join(self.tokenizer.batch_decode(generated_token_array, skip_special_tokens=True))
 answer = {"role": self.get_model_info().roles.ai_role, "content": generated_tokens}
 if self.log_to_file:
 with open(self.log_to_file, "a+") as log_file:
 log_file.write(json.dumps(answer, indent=2))
 log_file.write("\n")
 if add_to_history:
 self.message_history.append(answer)
 else:
 self.message_history.pop()
 return answer