agentllm.py

from llama_cpp import Llama

class AgGPT:
    def __init__(self, model_path):
        self.model_path = model_path
        self.model = Llama(model_path=model_path, n_ctx=4048, n_gpu_layers=35)

    def run(self):
        while True:
            prompt = input("\nEnter your prompt: ")

            messages = [
                {"role": "system", "content": f"You are AgGPT-10, an AGI system. The user said: '{prompt}'."},
                {"role": "user", "content": prompt}
            ]

            output = self.model.create_chat_completion(messages, max_tokens=2050, temperature=0.7)
            print(output["choices"][0]["message"]["content"])

    def ask(self, question):
        ''' Ask AgGPT-10 a question and return the answer. '''
        messages = [
            {"role": "system", "content": f"You are AgGPT-10, an AGI system. The user said: '{question}'."},
            {"role": "user", "content": question}
        ]

        output = self.model.create_chat_completion(messages, max_tokens=2050, temperature=0.7)

        return output["choices"][0]["message"]["content"]

if __name__ == "__main__":
    model_path = "agent.gguf"
    aggpt = AgGPT(model_path)
    aggpt.run()