customerSupport.py

from transformers import AutoModelForCausalLM,GenerationConfig
from peft import AutoPeftModelForCausalLM
from peft import PeftModel, PeftConfig

def input_data_preprocessing(example):

    processed_example = "<|system|>\n You are a support chatbot who helps with user queries chatbot who always responds in the style of a professional.\n<|user|>\n" + example["instruction"] + "\n<|assistant|>\n"

    return processed_example



def customerConverstaion(prompt):
    config = PeftConfig.from_pretrained("DSU-FDP/customer-support")
    base_model = AutoModelForCausalLM.from_pretrained("TheBloke/zephyr-7B-beta-GPTQ")
    model = PeftModel.from_pretrained(base_model, "DSU-FDP/customer-support")
    from transformers import AutoTokenizer,GPTQConfig
    tokenizer=AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)
    tokenizer.padding_side = 'right'
    tokenizer.pad_token = tokenizer.eos_token
    tokenizer.add_eos_token = True
    tokenizer.add_bos_token, tokenizer.add_eos_token
    tokenizer = AutoTokenizer.from_pretrained("DSU-FDP/customer-support")
    input_string = input_data_preprocessing(
    {
        "instruction": "i have a question about cancelling order {{Order Number}}",
    }
    )
    inputs = tokenizer(input_string, return_tensors="pt").to("cuda")
    generation_config = GenerationConfig(
        do_sample=True,
        top_k=1,
        temperature=0.1,
        max_new_tokens=256,
        pad_token_id=tokenizer.eos_token_id
    )
    outputs = model.generate(**inputs, generation_config=generation_config)
    return outputs