modules/knowledge_retrieval/destination_chain.py

from modules.base.chain import IChain
from modules.base.llm_chain_config import LLMChainConfig
from modules.knowledge_retrieval.base.knowledge_domain import KnowledgeDomain
from modules.settings.user_settings import UserSettings
from typing import Dict , Any, Callable
import os

class DestinationChain(IChain):
    """
    DestinationChain Class

    Design:
    The DestinationChain class extends the IChain interface and provides an implementation for the 
    run method. It follows the Liskov Substitution Principle (LSP) as it can be used wherever IChain 
    is expected. The class also adheres to the Dependency Inversion Principle (DIP) as it depends on 
    the abstraction (KnowledgeDomain) rather than a concrete class.

    Intended Implementation:
    The DestinationChain class serves as a wrapper around a KnowledgeDomain instance. It implements 
    the run method from the IChain interface, which simply calls the generate_response method of the 
    KnowledgeDomain. As such, when the run method is called with a question as input, the 
    DestinationChain class will return a response generated by the KnowledgeDomain.
    """
    knowledge_domain: KnowledgeDomain
    api_key: str 
    llm: Any
    display: Callable
    usage: str
    
    def run(self, input: str) -> str:
        return self.knowledge_domain.generate_response(input)

class DestinationChainStrategy(DestinationChain):
    """Base class for Chain Strategies"""
    
    def __init__(self, config: LLMChainConfig, display: Callable, knowledge_domain: KnowledgeDomain, usage: str):
        settings = UserSettings.get_instance()
        api_key = settings.get_api_key()
        print("Api key")
        print(api_key)
        super().__init__(api_key=api_key, knowledge_domain=knowledge_domain, llm=config.llm_class, display=display, usage=usage)
        
        self.llm = config.llm_class(temperature=config.temperature, max_tokens=config.max_tokens)
        
        self.usage = config.usage

    def run(self, question):
        response = self.knowledge_domain.generate_response(question)
        self.display(response)
        return response


def get_chain_config(temperature: float = 0.7) -> LLMChainConfig:
    usage = "This is the default chain model that should only be used as a last resort"
    return LLMChainConfig(usage=usage)