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from abc import ABC, abstractmethod
from typing import List, Dict, Optional
class ExecutionStrategy(ABC):
@abstractmethod
def build_prompt(self, task: str, instruction: Optional[str] = None) -> str:
"""Build the prompt according to the strategy."""
pass
@abstractmethod
def process_response(self, response: str) -> str:
"""Process the LLM response according to the strategy."""
pass
class ReactStrategy(ExecutionStrategy):
def build_prompt(self, task: str, instruction: Optional[str] = None) -> str:
base_prompt = """Approach this task using the following steps:
1) Thought: Analyze what needs to be done
2) Action: Decide on the next action
3) Observation: Observe the result
4) Repeat until task is complete
Follow this format for your response:
Thought: [Your reasoning about the current situation]
Action: [The action you decide to take]
Observation: [What you observe after the action]
... (continue steps as needed)
Final Answer: [Your final response to the task]
Task: {task}"""
if instruction:
base_prompt += f"\nAdditional Instruction: {instruction}"
return base_prompt.format(task=task)
def process_response(self, response: str) -> str:
# Could add additional processing here to extract final answer
return response
class ChainOfThoughtStrategy(ExecutionStrategy):
def build_prompt(self, task: str, instruction: Optional[str] = None) -> str:
base_prompt = """Let's solve this step by step:
Task: {task}
Please break down your thinking into clear steps:
1) First, ...
2) Then, ...
(continue with your step-by-step reasoning)
Final Answer: [Your conclusion based on the above reasoning]"""
if instruction:
base_prompt += f"\nAdditional Instruction: {instruction}"
return base_prompt.format(task=task)
def process_response(self, response: str) -> str:
return response
class ReflectionStrategy(ExecutionStrategy):
def build_prompt(self, task: str, instruction: Optional[str] = None) -> str:
base_prompt = """Complete this task using reflection:
Task: {task}
1) Initial Approach:
- What is your first impression of how to solve this?
- What assumptions are you making?
2) Analysis:
- What could go wrong with your initial approach?
- What alternative approaches could you consider?
3) Refined Solution:
- Based on your reflection, what is the best approach?
- Why is this approach better than the alternatives?
4) Final Answer:
- Provide your solution
- Briefly explain why this is the optimal approach"""
if instruction:
base_prompt += f"\nAdditional Instruction: {instruction}"
return base_prompt.format(task=task)
def process_response(self, response: str) -> str:
return response
class StrategyFactory:
"""Factory class for creating execution strategies."""
_strategies = {
'ReactStrategy': ReactStrategy,
'ChainOfThoughtStrategy': ChainOfThoughtStrategy,
'ReflectionStrategy': ReflectionStrategy
}
@classmethod
def create_strategy(cls, strategy_name: str) -> ExecutionStrategy:
"""Create a strategy instance based on the strategy name."""
strategy_class = cls._strategies.get(strategy_name)
if not strategy_class:
raise ValueError(f"Unknown strategy: {strategy_name}")
return strategy_class()
@classmethod
def available_strategies(cls) -> List[str]:
"""Return a list of available strategy names."""
return list(cls._strategies.keys()) |