| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| class Llama2Chatbot: | |
| def __init__(self): | |
| self.tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf") | |
| self.model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") | |
| self.device = "cuda" if torch.cuda.is_available() else "cpu" | |
| self.model.to(self.device) | |
| def generate_response(self, prompt, max_length=100): | |
| inputs = self.tokenizer(prompt, return_tensors="pt").to(self.device) | |
| outputs = self.model.generate(**inputs, max_length=max_length) | |
| response = self.tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return response | |
| def initialize_chatbot(): | |
| return Llama2Chatbot() | |
| def get_chatbot_response(chatbot, prompt): | |
| return chatbot.generate_response(prompt) |