chatbot.py

# Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0

# DeepSpeed Team

import argparse
import json
import logging
import os
import re

import pandas as pd
import transformers  # noqa: F401
from transformers import AutoConfig, AutoTokenizer, BloomForCausalLM, pipeline, set_seed


def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--path",
        type=str,
        help="Directory containing trained actor model"
    )
    parser.add_argument(
        "--max_new_tokens",
        type=int,
        default=512,
        help="Maximum new tokens to generate per response",
    )
    parser.add_argument(
        "--in_csv",
        type=str,
        help="Path to the input csv file",
    )
    parser.add_argument(
        "--out_csv",
        type=str,
        help="Path to the output csv file",
    )
    args = parser.parse_args()
    return args


def get_generator(path):
    # if os.path.exists(path):
    #     # Locally tokenizer loading has some issue, so we need to force download
    #     model_json = os.path.join(path, "config.json")
    #     if os.path.exists(model_json):
    #         model_json_file = json.load(open(model_json))
    #         model_name = model_json_file["_name_or_path"]
    #         tokenizer = AutoTokenizer.from_pretrained(model_name,
    #                                                   fast_tokenizer=True)
    # else:
    #     tokenizer = AutoTokenizer.from_pretrained(path, fast_tokenizer=True)

    tokenizer = AutoTokenizer.from_pretrained(path, fast_tokenizer=True)

    tokenizer.pad_token = tokenizer.eos_token

    model_config = AutoConfig.from_pretrained(path)
    model = BloomForCausalLM.from_pretrained(path,
                                             from_tf=bool(".ckpt" in path),
                                             config=model_config).half()

    model.config.end_token_id = tokenizer.eos_token_id
    model.config.pad_token_id = model.config.eos_token_id
    model.resize_token_embeddings(len(tokenizer))
    generator = pipeline("text-generation",
                         model=model,
                         tokenizer=tokenizer,
                         device="cuda:0")
    return generator


def get_user_input(user_input):
    tmp = input("Enter input (type 'quit' to exit, 'clear' to clean memory): ")
    new_inputs = f"Human: {tmp}\n Assistant: "
    user_input += f" {new_inputs}"
    return user_input, tmp == "quit", tmp == "clear"


def get_model_response(generator, user_input, max_new_tokens):
    response = generator(user_input, max_new_tokens=max_new_tokens)
    return response


def process_response(response, num_rounds):
    output = str(response[0]["generated_text"])
    output = output.replace("<|endoftext|></s>", "")
    all_positions = [m.start() for m in re.finditer("Human: ", output)]
    place_of_second_q = -1
    if len(all_positions) > num_rounds:
        place_of_second_q = all_positions[num_rounds]
    if place_of_second_q != -1:
        output = output[0:place_of_second_q]
    return output


def main(args):
    generator = get_generator(args.path)
    set_seed(42)

    def process_response_ch(response):
        output = str(response[0]["generated_text"])
        output = output[output.find("生成一份对应的诊断意见：") + 12:output.find("<|endoftext|>")].replace(" ", "")
        end = output.find("生成一份对应的诊断意见：")
        if end != -1:
            output = output[:end]
        return output

    if args.in_csv is not None:
        csv = pd.read_csv(args.in_csv, encoding="gbk")
        gen = []
        n_instr = 0
        for instr in csv["INSTRUCTION"]:
            n_instr += 1
            print("-" * 20 + f" Instruction {n_instr} " + "-" * 20)
            user_input = f"根据下面一段影像描述：{instr}\n 生成一份对应的诊断意见："
            response = get_model_response(generator, user_input,
                                          args.max_new_tokens)
            output = process_response_ch(response)
            gen.append(output)
            print(user_input + "\n" + output + "\n")
        csv["GENERATED"] = gen
        csv.to_csv(args.out_csv, encoding="gbk", index=False)
    else:
        while True:
            tmp = input("Enter input (type 'quit' to exit): ")
            if tmp == "quit":
                break
            if tmp == "clear":
                print("-" * 40 + "\n(Context preservation is currently disabled. 'clear' takes no effect.)\n")
                continue
            user_input = f"根据下面一段影像描述：{tmp}\n 生成一份对应的诊断意见："
            response = get_model_response(generator, user_input,
                                          args.max_new_tokens)
            output = process_response_ch(response)
            print("-" * 40 + "\n" + user_input + "\n" + output + "\n")

    # user_input = ""
    # num_rounds = 0
    # while True:
    #     num_rounds += 1
    #     user_input, quit, clear = get_user_input(user_input)

    #     if quit:
    #         break
    #     if clear:
    #         user_input, num_rounds = "", 0
    #         continue

    #     response = get_model_response(generator, user_input,
    #                                   args.max_new_tokens)
    #     output = process_response(response, num_rounds)

    #     print("-" * 30 + f" Round {num_rounds} " + "-" * 30)
    #     print(f"{output}")
    #     user_input = f"{output}\n\n"


if __name__ == "__main__":
    # Silence warnings about `max_new_tokens` and `max_length` being set
    logging.getLogger("transformers").setLevel(logging.ERROR)

    args = parse_args()
    main(args)

# Example:
"""
 Human: what is internet explorer?
 Assistant:
Internet Explorer is an internet browser developed by Microsoft. It is primarily used for browsing the web, but can also be used to run some applications. Internet Explorer is often considered the best and most popular internet browser currently available, though there are many other options available.
 Human: what is edge?
 Assistant:
 Edge is a newer version of the Microsoft internet browser, developed by Microsoft. It is focused on improving performance and security, and offers a more modern user interface. Edge is currently the most popular internet browser on the market, and is also used heavily by Microsoft employees.
"""