| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
|
|
|
|
|
| model_name = "facebook/blenderbot-400M-distill"
|
|
|
|
|
| tokenizer = AutoTokenizer.from_pretrained(model_name)
|
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
|
|
|
|
|
| def generate_response(user_input):
|
| inputs = tokenizer(user_input, return_tensors="pt")
|
| bot_output = model.generate(**inputs)
|
| bot_response = tokenizer.decode(bot_output[0], skip_special_tokens=True)
|
| return bot_response
|
|
|
|
|
| conversation_history = []
|
|
|
| while True:
|
| user_input = input("User: ")
|
| conversation_history.append(user_input)
|
|
|
| if user_input.lower() == "exit":
|
| break
|
|
|
| bot_response = generate_response(user_input)
|
| conversation_history.append(f"Bot: {bot_response}")
|
| print(f"Bot: {bot_response}")
|
|
|
| print("Updated Conversation History:", conversation_history)
|
|
|
