from transformers import AutoModelForCausalLM, AutoTokenizer
from langchain_community.llms import HuggingFacePipeline
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory
from transformers import pipeline
import dotenv

import os 
dotenv.load_dotenv()    

from huggingface_hub import login


token = os.getenv("HUGGINGFACEHUB_API_TOKEN")

if token:
    login(token=token)
else:
    raise EnvironmentError("⚠️ Environment variable HUGGINGFACE_HUB_TOKEN is not set in this space.")

def load_openchat():
    # Load the Llama model and tokenizer
    model_name = "microsoft/DialoGPT-small"  # Use your Llama model path or Hugging Face model ID
    model = AutoModelForCausalLM.from_pretrained(model_name , )
    tokenizer = AutoTokenizer.from_pretrained(model_name)

    # Create a pipeline for text generation
    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

    return pipe