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| # src/llms/base_llm.py | |
| from abc import ABC, abstractmethod | |
| from typing import List, Optional, Dict, Any | |
| class BaseLLM(ABC): | |
| def generate( | |
| self, | |
| prompt: str, | |
| max_tokens: Optional[int] = None, | |
| temperature: float = 0.7, | |
| **kwargs | |
| ) -> str: | |
| """ | |
| Generate a response based on the given prompt | |
| Args: | |
| prompt (str): Input prompt for the model | |
| max_tokens (Optional[int]): Maximum number of tokens to generate | |
| temperature (float): Sampling temperature for randomness | |
| Returns: | |
| str: Generated response | |
| """ | |
| pass | |
| def tokenize(self, text: str) -> List[str]: | |
| """ | |
| Tokenize the input text | |
| Args: | |
| text (str): Input text to tokenize | |
| Returns: | |
| List[str]: List of tokens | |
| """ | |
| pass | |
| def count_tokens(self, text: str) -> int: | |
| """ | |
| Count tokens in the input text | |
| Args: | |
| text (str): Input text to count tokens | |
| Returns: | |
| int: Number of tokens | |
| """ | |
| pass |