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import json |
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import os |
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from dataclasses import asdict, dataclass |
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from pathlib import Path |
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from typing import Any, Dict, List, Optional, Type, TypeVar, Union |
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from huggingface_hub import ModelHubMixin, hf_hub_download |
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T = TypeVar("T", bound="ModelHubMixin") |
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TEMPLATE_FILENAME = "dialogue_template.json" |
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IGNORE_INDEX = -100 |
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@dataclass |
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class DialogueTemplate(ModelHubMixin): |
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"""Converts all turns of a dialogue between a user and assistant to a standardized format.""" |
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system: str |
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messages: List[Dict[str, str]] = None |
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system_token: str = "<|system|>" |
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user_token: str = "<|user|>" |
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assistant_token: str = "<|assistant|>" |
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end_token: str = "<|end|>" |
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def __post_init__(self): |
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"""Ensure that messages is never None.""" |
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if self.messages is None: |
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self.messages = [] |
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def get_training_prompt(self) -> str: |
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if len(self.messages) == 0: |
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raise ValueError("Dialogue template must have at least one message.") |
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prompt = self.system_token + "\n" + self.system + self.end_token + "\n" |
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for message in self.messages: |
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if message["role"] == "user": |
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prompt += self.user_token + "\n" + message["content"] + self.end_token + "\n" |
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else: |
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prompt += self.assistant_token + "\n" + message["content"] + self.end_token + "\n" |
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return prompt |
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def get_inference_prompt(self) -> str: |
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if len(self.messages) == 0: |
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raise ValueError("Dialogue template must have at least one message.") |
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prompt = self.system_token + "\n" + self.system + self.end_token + "\n" |
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for message in self.messages: |
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if message["role"] == "user": |
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prompt += self.user_token + "\n" + message["content"] + self.end_token + "\n" |
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else: |
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prompt += self.assistant_token + "\n" + message["content"] + self.end_token + "\n" |
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prompt += self.assistant_token + "\n" |
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return prompt |
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def get_dialogue(self): |
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if len(self.messages) == 0: |
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raise ValueError("Dialogue template must have at least one message.") |
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prompt = "" |
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for message in self.messages: |
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if message["role"] == "user": |
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prompt += "\n\nHuman: " + message["content"] |
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else: |
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prompt += "\n\nAssistant: " + message["content"] |
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return prompt |
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def get_special_tokens(self) -> List[str]: |
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return [self.system_token, self.user_token, self.assistant_token, self.end_token] |
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def copy(self): |
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return DialogueTemplate( |
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system=self.system, |
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messages=self.messages, |
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system_token=self.system_token, |
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user_token=self.user_token, |
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assistant_token=self.assistant_token, |
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end_token=self.end_token, |
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) |
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def to_dict(self) -> Dict[str, Any]: |
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return {k: v for k, v in asdict(self).items()} |
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@classmethod |
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def from_dict(cls, data): |
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return DialogueTemplate( |
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system=data.get("system", ""), |
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messages=data.get("messages", None), |
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system_token=data.get("system_token", "<|system|>"), |
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user_token=data.get("user_token", "<|user|>"), |
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assistant_token=data.get("assistant_token", "<|assistant|>"), |
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end_token=data.get("end_token", "<|end|>"), |
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) |
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def _save_pretrained(self, save_directory: Union[str, Path]) -> None: |
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save_directory = Path(save_directory) |
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save_directory.mkdir(exist_ok=True) |
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with open(save_directory / "dialogue_template.json", "w") as f: |
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json.dump(self.to_dict(), f, indent=2) |
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@classmethod |
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def _from_pretrained( |
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cls: Type[T], |
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*, |
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model_id: str, |
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revision: Optional[str], |
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cache_dir: Optional[Union[str, Path]], |
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force_download: bool, |
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proxies: Optional[Dict], |
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resume_download: bool, |
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local_files_only: bool, |
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token: Optional[Union[str, bool]], |
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**model_kwargs, |
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) -> T: |
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"""Loads the dialogue template from a local directory or the Huggingface Hub.""" |
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if os.path.isdir(model_id): |
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print("Loading dialogue template from local directory") |
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template_file = os.path.join(model_id, TEMPLATE_FILENAME) |
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else: |
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template_file = hf_hub_download( |
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repo_id=model_id, |
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filename=TEMPLATE_FILENAME, |
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revision=revision or "main", |
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cache_dir=cache_dir, |
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force_download=force_download, |
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proxies=proxies, |
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resume_download=resume_download, |
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token=token, |
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local_files_only=local_files_only, |
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) |
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with open(template_file, "r") as f: |
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data = json.load(f) |
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return cls.from_dict(data=data) |
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default_template = DialogueTemplate( |
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system="Below is a dialogue between a human user and an AI assistant. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed.", |
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) |
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no_system_template = DialogueTemplate(system="") |
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alpaca_template = DialogueTemplate( |
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system="Below is an instruction that describes a task. Write a response that appropriately completes the request.", |
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user_token="### Instruction:", |
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assistant_token="### Response:", |
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) |
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SUPPORTED_DIALOGUE_TEMPLATES = { |
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"default": default_template, |
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"no_system": no_system_template, |
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"alpaca": alpaca_template, |
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} |
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def get_dialogue_template(template: str) -> DialogueTemplate: |
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if template not in SUPPORTED_DIALOGUE_TEMPLATES: |
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raise ValueError(f"Template {template} is not supported!") |
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return SUPPORTED_DIALOGUE_TEMPLATES[template].copy() |
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def prepare_dialogue(example, dialogue_template, is_train=True): |
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if "messages" in example and example["messages"] is not None: |
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dialogue_template.messages = example["messages"] |
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elif "prompt" in example and "completion" in example: |
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dialogue_template.messages = [ |
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{"role": "user", "content": example["prompt"]}, |
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{"role": "assistant", "content": example["completion"]}, |
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] |
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elif "prompt" in example: |
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dialogue_template.messages = [{"role": "user", "content": example["prompt"]}] |
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else: |
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raise ValueError( |
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f"Could not format example as dialogue! Require either `messages` or `[prompt, completion]` or `[prompt]` keys but found {list(example.keys())}" |
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) |
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if is_train: |
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example["text"] = dialogue_template.get_training_prompt() |
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else: |
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example["text"] = dialogue_template.get_inference_prompt() |
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return example |
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