simple conversation manager with memory

class ConversationManager:
    def __init__(self, system_prompt, memory_limit=5):
        self.system_prompt = system_prompt
        self.memory = []
        self.memory_limit = memory_limit

    def add_to_memory(self, role, content):
        self.memory.append({"role": role, "content": content})
        if len(self.memory) > self.memory_limit:
            self.memory.pop(0)

    def get_response(self, user_input):
        self.add_to_memory("user", user_input)

        full_prompt = f"{self.system_prompt}\n\n"
        for message in self.memory:
            full_prompt += f"{message['role'].capitalize()}: {message['content']}\n"
        full_prompt += "Assistant: "

        response = llm.generate(full_prompt)
        self.add_to_memory("assistant", response)

        return response

# Usage
system_prompt = "You are a helpful AI assistant. Maintain context across the conversation."
manager = ConversationManager(system_prompt)

print(manager.get_response("Hi, what's the weather like today?"))
print(manager.get_response("Will I need an umbrella?"))
print(manager.get_response("Thanks! By the way, what was my first question?"))