43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
"""Abstract base class for prompt construction strategies."""
|
||
|
||
from abc import ABC, abstractmethod
|
||
from typing import List
|
||
|
||
from pipeline.tokenizer import BpeTokenizer
|
||
|
||
|
||
class PromptStrategy(ABC):
|
||
"""Abstract base for prompt/response format strategies.
|
||
|
||
Strategies operate at the token level: the Processor tokenizes raw
|
||
text (query, response, …) and passes token lists to the Strategy,
|
||
which assembles them with pre-encoded format tokens.
|
||
"""
|
||
|
||
def __init__(self, tokenizer: BpeTokenizer):
|
||
self.tokenizer = tokenizer
|
||
|
||
def _encode_format(self, text: str) -> List[int]:
|
||
"""Encode a format string that may contain special tokens."""
|
||
return self.tokenizer.encode(text, add_special_tokens=False)
|
||
|
||
@property
|
||
@abstractmethod
|
||
def name(self) -> str:
|
||
pass
|
||
|
||
@abstractmethod
|
||
def assemble_prompt(self, query_tokens: List[int]) -> List[int]:
|
||
"""Assemble query tokens into a complete prompt with format tokens.
|
||
|
||
The prompt includes all tokens up to (and including) the response
|
||
start marker, e.g. ``<｜im▁start｜>assistant\n``.
|
||
"""
|
||
|
||
@abstractmethod
|
||
def assemble_response(self, response_tokens: List[int]) -> List[int]:
|
||
"""Wrap response tokens with format tokens (suffix, eos, etc)."""
|
||
|
||
def __repr__(self) -> str:
|
||
return f"{self.__class__.__name__}(name='{self.name}')"
|