app.py

# pylint: skip-file

import subprocess
import json
import requests

subprocess.run(
    f"pip install flash-attn --no-build-isolation",
    env={"FLASH_ATTENTION_SKIP_CUDA_BUILD": "TRUE"},
    shell=True,
)

import os
from threading import Thread
from typing import Iterator

import gradio as gr
import spaces
import torch
import wikipedia
import time
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
from bs4 import BeautifulSoup
from functools import lru_cache


MAX_MAX_NEW_TOKENS = 4096
DEFAULT_MAX_NEW_TOKENS = 1536
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "8192"))

DESCRIPTION = """\
# Playground with Ghost 8B Beta (β, 8k, Online)

**Ghost 8B Beta** model outperforms prominent models such as Llama 3 8B Instruct, GPT 3.5 Turbo in the lc_winrate score. In addition, it also outperforms Claude 3 Opus, Claude 3 Sonnet, GPT-4, and Mistral Large when comparing the winrate score of AlpacaEval 2.0, [*](https://ghost-x.org/docs/models/ghost-8b-beta/). The model comes in two context length versions, [8k](https://huggingface.co/spaces/lamhieu/ghost-8b-beta-8k) and [128k](https://huggingface.co/spaces/lamhieu/ghost-8b-beta-128k), along with multilingual function tools support by default. 

The languages supported are 🇺🇸 English, 🇫🇷 French, 🇮🇹 Italian, 🇪🇸 Spanish, 🇵🇹 Portuguese, 🇩🇪 German, 🇻🇳 Vietnamese, 🇰🇷 Korean and 🇨🇳 Chinese.

🗞️ **Updates**
* Jul 23, 2024: added support for tools, now available to search for information on the internet.
"""


PLACEHOLDER = """
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
   <h1 style="font-size: 26px; margin-bottom: 2px; opacity: 0.20;">👻 Ghost 8B Beta</h1>
   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.10;">Ask and share whatever you want ~</p>
</div>
"""

LICENSE = """
<p/>

---
Ghost 8B Beta may give inaccurate information, including information about people, so please verify Ghost 8B Beta's answers. [Ghost 8B Beta](https://ghost-x.org/docs/models/ghost-8b-beta/) by [Ghost X](https://ghost-x.org).
"""

EXAMPLES = [
    [
        "What is the significance of the Higgs boson in the Standard Model of particle physics?"
    ],
    [
        "Qu'est-ce que l'effet fondateur et comment influence-t-il la diversité génétique d'une population?"
    ],
    ["Qual è il principio di Le Chatelier e come si applica agli equilibri chimici?"],
    [
        "¿Qué es una supernova y cuál es su importancia en la formación de elementos pesados en el universo?"
    ],
    [
        "Qual é a definição formal de uma integral de linha e como é utilizada em física?"
    ],
    [
        "Was versteht man unter dem Moho-Diskontinuität und welche Bedeutung hat sie für das Verständnis der Erdkruste?"
    ],
    [
        "Hiện tượng nhà kính là gì và nó ảnh hưởng như thế nào đến biến đổi khí hậu toàn cầu?"
    ],
    [
        "알고리즘의 시간 복잡도가 중요한 이유는 무엇이며, 시간 복잡도를 어떻게 분석하나요?"
    ],
    ["什么是CRISPR-Cas9基因编辑技术，它在现代生物学研究中的作用是什么？"],
    [
        "Create a Python function that takes a list of integers and returns the list sorted in ascending order without using the built-in sort or sorted functions."
    ],
    [
        "Écrivez une fonction en C++ qui trouve le plus long sous-tableau contigu avec une somme égale à zéro."
    ],
    [
        "Scrivi una funzione in Java che calcola il fattoriale di un numero utilizzando la ricorsione."
    ],
    [
        "Desarrolla una función en JavaScript que determine si una cadena de texto es un palíndromo, ignorando espacios y signos de puntuación."
    ],
    ["Implemente uma função em C# que verifique se uma matriz quadrada é simétrica."],
    [
        "Schreiben Sie eine Funktion in Swift, die eine gegebene Zeichenfolge in umgekehrter Reihenfolge zurückgibt, ohne integrierte Funktionen zu verwenden."
    ],
    [
        "Viết một hàm trong PHP để tìm tất cả các số nguyên tố trong một khoảng cho trước."
    ],
    [
        "파이썬을 사용하여 주어진 이진 트리가 이진 탐색 트리인지 확인하는 함수를 작성하십시오."
    ],
    [
        "用 Go 语言编写一个函数，计算给定字符串中每个字符出现的次数，并返回一个包含字符及其出现次数的映射。"
    ],
    [
        "Can you help me design a detailed project plan for developing a machine learning model for predicting stock prices?"
    ],
    [
        "Pouvez-vous m'aider à organiser un emploi du temps hebdomadaire pour maximiser la productivité de mon équipe de développement logiciel?"
    ],
    [
        "Puoi aiutarmi a creare un piano di sviluppo per un'applicazione mobile che gestisce le prenotazioni di ristoranti?"
    ],
    [
        "¿Podrías ayudarme a elaborar un plan detallado para la implementación de un sistema de gestión de contenido (CMS) en una empresa mediana?"
    ],
    [
        "Você pode me ajudar a planejar uma estratégia de desenvolvimento para um sistema de comércio eletrônico escalável?"
    ],
    [
        "Können Sie mir helfen, einen detaillierten Zeitplan für die Implementierung eines neuen ERP-Systems in unserem Unternehmen zu erstellen?"
    ],
    [
        "Bạn có thể giúp tôi xây dựng một kế hoạch phát triển chi tiết cho dự án xây dựng hệ thống quản lý chuỗi cung ứng không?"
    ],
    [
        "신경망 기반 이미지 인식 모델 개발을 위한 세부 프로젝트 계획을 세우는 데 도움을 줄 수 있나요?"
    ],
    ["你能帮我制定一个详细的开发计划，用于创建一个基于区块链的分布式账本系统吗？"],
    [
        "Prove that the sum of the squares of any two sides of a right triangle is equal to the square of the hypotenuse."
    ],
    [
        "Calculez la force gravitationnelle entre deux masses de 10 kg chacune séparées par une distance de 1 mètre."
    ],
    [
        "Determina la formula molecolare di un composto che contiene il 40% di carbonio, il 6.67% di idrogeno e il 53.33% di ossigeno in massa."
    ],
    [
        "Explica la teoría del ciclo económico de Schumpeter y cómo se aplica a la economía moderna."
    ],
    [
        "Calcule a energia potencial gravitacional de um objeto de 5 kg a uma altura de 10 metros acima do solo (g = 9,8 m/s²)."
    ],
    [
        "Beweisen Sie, dass jede Primzahl der Form 4k+1 als Summe zweier Quadrate geschrieben werden kann."
    ],
    [
        "Tính nồng độ mol của dung dịch H₂SO₄ khi hoà tan 98 gam H₂SO₄ vào nước để được 1 lít dung dịch."
    ],
    ["케인스 경제학의 핵심 개념과 그것이 현대 경제 정책에 미치는 영향을 설명하십시오."],
    ["计算一个质量为2 kg的物体在3米高处的重力势能（g = 9.8 m/s²）。"],
    [
        'Identify the author of a novel that features a dystopian society where "Big Brother" watches over its citizens and the protagonist works for the Ministry of Truth.'
    ],
    [
        "Quel est le seul mammifère capable de voler activement, souvent associé à la nuit et capable d'écholocalisation?"
    ],
    [
        "Qual è l'opera letteraria italiana che narra il viaggio immaginario di un poeta attraverso Inferno, Purgatorio e Paradiso, guidato da Virgilio e Beatrice?"
    ],
    [
        "¿Qué insecto es conocido por su organización social compleja, su capacidad para producir miel y su comunicación mediante la danza?"
    ],
    [
        "Qual é o fenômeno atmosférico que ocorre quando uma massa de ar quente se encontra com uma massa de ar frio, resultando em uma violenta tempestade giratória?"
    ],
    [
        "Welches literarische Werk beschreibt die Geschichte eines jungen Mädchens, das durch einen Kaninchenbau in eine fantastische Welt voller skurriler Charaktere fällt?"
    ],
    [
        "Động vật nào có thể tái sinh toàn bộ cơ thể từ một mảnh nhỏ của chính nó, thường sống dưới nước và có thể có nhiều xúc tu?"
    ],
    [
        "어떤 자연 현상은 태양빛이 대기 중의 물방울에 반사되고 굴절되어 발생하며, 하늘에 나타나는 여러 색깔의 아치 형태를 띠나요?"
    ],
    ["这部文学作品讲述了一位绅士和他的侍从的冒险故事，他们在"],
    [
        "Can you derive the Euler-Lagrange equation from the principle of stationary action in classical mechanics?"
    ],
    [
        "Expliquez la notion de « différence ontologique » chez Martin Heidegger et son importance pour la phénoménologie."
    ],
    [
        "Qual è il significato simbolico del colore blu nei dipinti di Giotto di Bondone durante il Rinascimento?"
    ],
    [
        "¿Cómo afecta el cambio de código a la estructura gramatical en comunidades bilingües de habla español-inglés?"
    ],
    [
        "Qual é o impacto da política monetária não convencional no controle da inflação durante uma crise econômica?"
    ],
    [
        "Erklären Sie den Unterschied zwischen deterministischen und nicht-deterministischen endlichen Automaten und ihre Anwendungsbereiche."
    ],
    [
        "Giải thích cơ chế của quá trình phiên mã ngược (reverse transcription) và tầm quan trọng của nó trong nghiên cứu HIV/AIDS."
    ],
    ["조선시대 성리학이 한국 사회와 문화에 미친 영향을 설명하세요."],
    ["如何解释量子纠缠现象，以及它在量子计算中的潜在应用？"],
    [
        "How can you design a daily schedule that maximizes productivity for a remote worker who has multiple meetings and project deadlines?"
    ],
    [
        "Quels sont les meilleures stratégies pour gérer les conflits au sein d'une équipe multiculturelle travaillant sur un projet commun?"
    ],
    [
        "Quali sono i migliori consigli per mantenere un equilibrio tra vita professionale e vita privata in un ambiente lavorativo stressante?"
    ],
    [
        "¿Cómo se puede elaborar un plan financiero personal efectivo que incluya ahorro para la jubilación, inversión y manejo de deudas?"
    ],
    [
        "Quais são as melhores práticas para implementar metodologias ágeis em uma equipe de desenvolvimento de software?"
    ],
    [
        "Welche Strategien können verwendet werden, um ein starkes berufliches Netzwerk aufzubauen und zu pflegen, insbesondere in der Tech-Branche?"
    ],
    [
        "Những bước nào cần thiết để xây dựng một lộ trình phát triển sự nghiệp bền vững trong lĩnh vực công nghệ thông tin?"
    ],
    ["프로젝트의 범위 변동을 효과적으로 관리하기 위한 최고의 방법은 무엇인가요?"],
    ["在快速变化的职场环境中，如何有效地实现工作与生活的平衡？"],
    [
        "Write an argumentative essay discussing the pros and cons of artificial intelligence in the workplace, including potential ethical concerns."
    ],
    [
        "Analysez les impacts sociaux et économiques de la digitalisation sur les petites entreprises en France."
    ],
    [
        "Scrivi un'email formale al direttore di una rivista per proporre un articolo sulla sostenibilità ambientale nelle città italiane."
    ],
    [
        "Elabora un informe detallado sobre los efectos del cambio climático en la biodiversidad de la región amazónica."
    ],
    [
        "Analise criticamente os principais pontos abordados no relatório anual do Banco Mundial sobre a pobreza global."
    ],
    [
        "Erstellen Sie eine technische Dokumentation für die Implementierung eines neuen Software-Features in einer bestehenden Anwendung."
    ],
    [
        "Viết một bài luận phân tích về tác động của cuộc cách mạng công nghiệp 4.0 đối với thị trường lao động Việt Nam."
    ],
    [
        "인공지능의 윤리적 문제에 대한 연구 논문을 작성하고, 다양한 사례를 통해 그 영향을 분석하세요."
    ],
    ["分析鲁迅的小说《阿Q正传》中反映的中国社会问题和作者的批判态度。"],
]

if not torch.cuda.is_available():
    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"


if torch.cuda.is_available():
    model_id = "ghost-x/ghost-8b-beta"
    hf_serect = os.getenv("HF_TOKEN", None)
    model = AutoModelForCausalLM.from_pretrained(
        model_id,
        device_map="auto",
        torch_dtype=torch.bfloat16,
        attn_implementation="flash_attention_2",
        trust_remote_code=True,
        token=hf_serect,
    )
    tokenizer = AutoTokenizer.from_pretrained(
        model_id,
        trust_remote_code=True,
        token=hf_serect,
    )

waiting_tools_timeout = 5
supported_tools = json.dumps(
    [
        {
            "type": "function",
            "function": {
                "name": "search_on_internet",
                "description": "Use this tool to search for information on the internet to answer questions you are unsure about, don't know or need the latest information (e.g. news, reports, companies, people,...) to give the most accurate results. Note: can only be used or ignored, not asked again",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "keyword": {
                            "type": "string",
                            "description": "Search keywords, rephrase to optimize search results based on questions suitable to the specified search type.",
                            "required": True,
                        },
                        "type": {
                            "type": "string",
                            "description": "Search type, based on the question to determine whether to search for it in 'wikipedia' or 'google', prefer to use wikipedia for information about events, history and people.",
                            "enum": ["wikipedia", "google"],
                            "default": "google",
                            "required": True,
                        },
                        "language": {
                            "type": "string",
                            "description": "Search language, is the user language code with 2 letters, e.g: vi = vietnamese, en = english.",
                            "default": "en",
                            "required": True,
                        },
                    },
                },
            },
        }
    ],
    ensure_ascii=False,
)


@lru_cache(maxsize=128)
def extract_text_from_webpage(html_content):
    soup = BeautifulSoup(html_content, "html.parser")
    for tag in soup(["script", "style", "header", "footer", "nav", "form", "svg"]):
        tag.extract()
    visible_text = soup.get_text(strip=True, separator=" ")
    return visible_text


def search_with_wikipedia(
    query: str,
    language: str = "en",
):
    all_results = []
    try:
        wikipedia.set_lang(language)
        all_results.append(wikipedia.summary(query))
    except Exception as e:
        pass
    return all_results


def search_with_google(
    query: str,
    num_results: int = 3,
    timeout: int = 5,
    language: str = "en",
    ssl_verify: bool = None,
):
    all_results = []
    max_chars_per_page = 4096
    with requests.Session() as session:
        resp = session.get(
            url="https://www.google.com/search",
            headers={
                "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"
            },
            params={
                "q": query,
                "num": num_results,
                "udm": 14,
                "hl": language,
            },
            timeout=timeout,
            verify=ssl_verify,
        )
        resp.raise_for_status()
        soup = BeautifulSoup(resp.text, "html.parser")
        result_block = soup.find_all("div", attrs={"class": "g"})
        for result in result_block:
            link = result.find("a", href=True)
            if link:
                link = link["href"]
                try:
                    webpage = session.get(
                        link,
                        headers={
                            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"
                        },
                    )
                    webpage.raise_for_status()
                    visible_text = extract_text_from_webpage(webpage.text)
                    if len(visible_text) > max_chars_per_page:
                        visible_text = visible_text[:max_chars_per_page]
                    all_results.append({"link": link, "text": visible_text})
                except requests.exceptions.RequestException as e:
                    print(f"Error fetching or processing {link}: {e}")
                    pass
            else:
                pass
    return all_results


@spaces.GPU(duration=120)
def generate(
    message: str,
    chat_history: list[tuple[str, str]],
    allow_used_tools: bool = True,
    system_prompt: str = "",
    max_new_tokens: int = 1536,
    temperature: float = 0.4,
    top_p: float = 0.95,
    top_k: int = 50,
    repetition_penalty: float = 1.0,
    other_client_info: str = None,
) -> Iterator[str]:
    # print()
    # print("allow_used_tools:\n", allow_used_tools)
    # print("system_prompt:\n", system_prompt)
    # print("max_new_tokens:\n", max_new_tokens)
    # print("temperature:\n", temperature)

    def build_input_ids(
        apply_tools: bool = None,
        references=None,
    ):
        conversation = []
        if system_prompt:
            conversation.append({"role": "system", "content": system_prompt})
        if apply_tools is True:
            conversation.append({"role": "tools", "content": supported_tools})

        if references is None:
            references = [other_client_info]
        else:
            references.insert(0, other_client_info)

        if (
            references is not None
            and isinstance(references, list)
            and len(references) > 0
        ):
            conversation.append(
                {
                    "role": "refs",
                    "content": json.dumps(
                        {
                            "instructions": "These are only general documents used for reference to give the most accurate and honest answers possible. Ignore it if it's irrelevant and don't overuse it.",
                            "documents": references,
                        },
                        indent=2,
                        ensure_ascii=False,
                    ),
                }
            )

        for user, assistant in chat_history:
            conversation.extend(
                [
                    {"role": "user", "content": user},
                    {"role": "assistant", "content": assistant},
                ]
            )
        conversation.append({"role": "user", "content": message})

        input_ids = tokenizer.apply_chat_template(
            conversation, add_generation_prompt=True, return_tensors="pt"
        )
        input_ids = input_ids.to(model.device)
        if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
            input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
            gr.Warning(
                f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens."
            )
        return input_ids

    def generate_chat_responses(
        previous_response: str = None,
    ):
        document_references = []
        if previous_response is not None:
            scheduled_tools_runs = None
            try:
                scheduled_tools_runs = json.loads(previous_response)
                if scheduled_tools_runs["type"] == "function" and scheduled_tools_runs[
                    "name"
                ] in ["search_on_internet"]:
                    pass
                else:
                    scheduled_tools_runs = None
            except Exception as e:
                print(e)
                pass

            if (
                scheduled_tools_runs is not None
                and scheduled_tools_runs["name"] == "search_on_internet"
            ):
                keyword = scheduled_tools_runs["arguments"]["keyword"]
                search_type = scheduled_tools_runs["arguments"]["type"]
                language = scheduled_tools_runs["arguments"]["language"]
                print("scheduled_tools_runs:", scheduled_tools_runs)
                if search_type == "wikipedia":
                    gr.Info(
                        "Searching for information on the Wikipedia.",
                        duration=5,
                        visible=True,
                    )
                    document_references.extend(
                        search_with_wikipedia(query=keyword, language=language)
                    )

                gr.Info("Searching for information on the Google.")
                document_references.extend(
                    search_with_google(
                        query=keyword,
                        language=language,
                        num_results=3,
                        # num_results=2 if search_type == "wikipedia" else 3,
                    )
                )
                print("document_references:", document_references)

        apply_tools = (
            True if allow_used_tools is True and previous_response is None else False
        )
        input_ids = build_input_ids(
            apply_tools=apply_tools,
            references=document_references,
        )
        streamer = TextIteratorStreamer(
            tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True
        )
        generate_kwargs = dict(
            input_ids=input_ids,
            streamer=streamer,
            max_new_tokens=max_new_tokens,
            do_sample=True,
            repetition_penalty=repetition_penalty,
        )
        if temperature == 0:
            generate_kwargs["do_sample"] = False
        else:
            generate_kwargs["temperature"] = temperature
            generate_kwargs["top_p"] = top_p
            generate_kwargs["top_k"] = top_k

        t = Thread(target=model.generate, kwargs=generate_kwargs)
        t.start()

        state = {
            "mark": None,
            "respond": False,
        }
        outputs = []
        for text in streamer:
            if state["mark"] is None:
                state["mark"] = time.time()
            outputs.append(text)
            if (
                apply_tools is False
                or state["mark"] + waiting_tools_timeout < time.time()
            ):
                state["respond"] = True
                yield "".join(outputs)

        if (
            apply_tools is True
            and state["respond"] is False
            and state["mark"] + waiting_tools_timeout > time.time()
        ):
            previous_response = "".join(outputs)
            yield from generate_chat_responses(previous_response=previous_response)

    yield from generate_chat_responses(previous_response=None)


chatbot = gr.Chatbot(
    height=500, placeholder=PLACEHOLDER, label="Ghost 8B Beta", show_copy_button=True
)

chat_interface = gr.ChatInterface(
    fn=generate,
    chatbot=chatbot,
    fill_height=True,
    additional_inputs=[
        gr.Checkbox(
            label="Allow used tools (available: search on internet)", value=False
        ),
        gr.Textbox(label="System prompt", lines=6),
        gr.Slider(
            label="Max new tokens",
            minimum=1,
            maximum=MAX_MAX_NEW_TOKENS,
            step=1,
            value=DEFAULT_MAX_NEW_TOKENS,
        ),
        gr.Slider(
            label="Temperature",
            minimum=0.0,
            maximum=2.0,
            step=0.1,
            value=0.4,
        ),
        gr.Slider(
            label="Top-p (nucleus sampling)",
            minimum=0.05,
            maximum=1.0,
            step=0.05,
            value=0.95,
        ),
        gr.Slider(
            label="Top-k",
            minimum=1,
            maximum=100,
            step=1,
            value=50,
        ),
        gr.Slider(
            label="Repetition penalty",
            minimum=1.0,
            maximum=2.0,
            step=0.05,
            value=1.0,
        ),
        gr.Textbox(
            label="Other client information",
            lines=1,
            value="This user's current time: {}".format(time.strftime("%Y-%m-%d")),
            visible=False,
        ),
    ],
    stop_btn="Stop",
    cache_examples=False,
    examples=EXAMPLES,
    examples_per_page=9,
    concurrency_limit=100,
)

with gr.Blocks(fill_height=True, css="style.css") as demo:
    gr.Markdown(DESCRIPTION)
    chat_interface.render()
    gr.Markdown(LICENSE)

if __name__ == "__main__":
    demo.queue(max_size=20).launch(share=True)