app.py

import uuid
import gradio as gr
import re
from diffusers.utils import load_image
import requests
from awesome_chat import chat_huggingface
import os

os.makedirs("public/images", exist_ok=True)
os.makedirs("public/audios", exist_ok=True)
os.makedirs("public/videos", exist_ok=True)

HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
OPENAI_KEY = os.environ.get("OPENAI_KEY")


class Client:
    def __init__(self) -> None:
        self.OPENAI_KEY = OPENAI_KEY
        self.HUGGINGFACE_TOKEN = HUGGINGFACE_TOKEN
        self.all_messages = []

    def set_key(self, openai_key):
        self.OPENAI_KEY = openai_key
        return self.OPENAI_KEY

    def set_token(self, huggingface_token):
        self.HUGGINGFACE_TOKEN = huggingface_token
        return self.HUGGINGFACE_TOKEN

    def add_message(self, content, role):
        message = {"role": role, "content": content}
        self.all_messages.append(message)

    def extract_medias(self, message):
        # url_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?")
        urls = []
        # for match in url_pattern.finditer(message):
        #     if match.group(0) not in urls:
        #         urls.append(match.group(0))

        image_pattern = re.compile(
            r"(http(s?):|\/)?([\.\/_\w:-])*?\.(jpg|jpeg|tiff|gif|png)"
        )
        image_urls = []
        for match in image_pattern.finditer(message):
            if match.group(0) not in image_urls:
                image_urls.append(match.group(0))

        audio_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(flac|wav)")
        audio_urls = []
        for match in audio_pattern.finditer(message):
            if match.group(0) not in audio_urls:
                audio_urls.append(match.group(0))

        video_pattern = re.compile(r"(http(s?):|\/)?([\.\/_\w:-])*?\.(mp4)")
        video_urls = []
        for match in video_pattern.finditer(message):
            if match.group(0) not in video_urls:
                video_urls.append(match.group(0))

        return urls, image_urls, audio_urls, video_urls

    def add_text(self, messages, message):
        if (
            not self.OPENAI_KEY
            or not self.OPENAI_KEY.startswith("sk-")
            or not self.HUGGINGFACE_TOKEN
            or not self.HUGGINGFACE_TOKEN.startswith("hf_")
        ):
            return (
                messages,
                "Please set your OpenAI API key and Hugging Face token first!!!",
            )
        self.add_message(message, "user")
        messages = messages + [(message, None)]
        urls, image_urls, audio_urls, video_urls = self.extract_medias(message)

        for image_url in image_urls:
            if not image_url.startswith("http") and not image_url.startswith("public"):
                image_url = "public/" + image_url
            image = load_image(image_url)
            name = f"public/images/{str(uuid.uuid4())[:4]}.jpg"
            image.save(name)
            messages = messages + [((f"{name}",), None)]
        for audio_url in audio_urls and not audio_url.startswith("public"):
            if not audio_url.startswith("http"):
                audio_url = "public/" + audio_url
            ext = audio_url.split(".")[-1]
            name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}"
            response = requests.get(audio_url)
            with open(name, "wb") as f:
                f.write(response.content)
            messages = messages + [((f"{name}",), None)]
        for video_url in video_urls and not video_url.startswith("public"):
            if not video_url.startswith("http"):
                video_url = "public/" + video_url
            ext = video_url.split(".")[-1]
            name = f"public/audios/{str(uuid.uuid4()[:4])}.{ext}"
            response = requests.get(video_url)
            with open(name, "wb") as f:
                f.write(response.content)
            messages = messages + [((f"{name}",), None)]
        return messages, ""

    def bot(self, messages):
        if (
            not self.OPENAI_KEY
            or not self.OPENAI_KEY.startswith("sk-")
            or not self.HUGGINGFACE_TOKEN
            or not self.HUGGINGFACE_TOKEN.startswith("hf_")
        ):
            return messages, {}
        message, results = chat_huggingface(
            self.all_messages, self.OPENAI_KEY, self.HUGGINGFACE_TOKEN
        )
        urls, image_urls, audio_urls, video_urls = self.extract_medias(message)
        self.add_message(message, "assistant")
        messages[-1][1] = message
        for image_url in image_urls:
            if not image_url.startswith("http"):
                image_url = image_url.replace("public/", "")
                messages = messages + [((None, (f"public/{image_url}",)))]
            # else:
            #     messages = messages + [((None, (f"{image_url}",)))]
        for audio_url in audio_urls:
            if not audio_url.startswith("http"):
                audio_url = audio_url.replace("public/", "")
                messages = messages + [((None, (f"public/{audio_url}",)))]
            # else:
            #     messages = messages + [((None, (f"{audio_url}",)))]
        for video_url in video_urls:
            if not video_url.startswith("http"):
                video_url = video_url.replace("public/", "")
                messages = messages + [((None, (f"public/{video_url}",)))]
            # else:
            #     messages = messages + [((None, (f"{video_url}",)))]
        # replace int key to string key
        results = {str(k): v for k, v in results.items()}
        return messages, results


css = ".json {height: 527px; overflow: scroll;} .json-holder {height: 527px; overflow: scroll;}"
with gr.Blocks(css=css) as demo:
    state = gr.State(value={"client": Client()})
    gr.Markdown("<h1><center>HuggingGPT - Lite 🎐 </center></h1>")
    gr.Markdown(
        "<p align='center'><img src='https://i.ibb.co/qNH3Jym/logo.png' height='25' width='95'></p>"
    )
    gr.Markdown(
        "<p align='center' style='font-size: 20px;'>A system to connect LLMs with ML community. See our <a href='https://github.com/microsoft/JARVIS'>Project</a> and <a href='http://arxiv.org/abs/2303.17580'>Paper</a>.</p>"
    )
    gr.HTML(
        """<center><a href="https://huggingface.co/spaces/taesiri/HuggingGPT-Lite?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key and Hugging Face Token</center>"""
    )
    gr.Markdown(
        """>**Note**: This is a further lite version of the original HuggingGPT designed to run on CPU-only spaces.  This model by default uses `gpt-3.5-turbo` which is much much cheaper than `text-davinci-003`. """
    )
    if not OPENAI_KEY:
        with gr.Row().style():
            with gr.Column(scale=0.85):
                openai_api_key = gr.Textbox(
                    show_label=False,
                    placeholder="Set your OpenAI API key here and press Enter",
                    lines=1,
                    type="password",
                ).style(container=False)
            with gr.Column(scale=0.15, min_width=0):
                btn1 = gr.Button("Submit").style(full_height=True)

    if not HUGGINGFACE_TOKEN:
        with gr.Row().style():
            with gr.Column(scale=0.85):
                hugging_face_token = gr.Textbox(
                    show_label=False,
                    placeholder="Set your Hugging Face Token here and press Enter",
                    lines=1,
                    type="password",
                ).style(container=False)
            with gr.Column(scale=0.15, min_width=0):
                btn3 = gr.Button("Submit").style(full_height=True)

    with gr.Row().style():
        with gr.Column(scale=0.6):
            chatbot = gr.Chatbot([], elem_id="chatbot").style(height=500)
        with gr.Column(scale=0.4):
            results = gr.JSON(elem_classes="json")

    with gr.Row().style():
        with gr.Column(scale=0.85):
            txt = gr.Textbox(
                show_label=False,
                placeholder="Enter text and press enter. The url must contain the media type. e.g, https://example.com/example.jpg",
                lines=1,
            ).style(container=False)
        with gr.Column(scale=0.15, min_width=0):
            btn2 = gr.Button("Send").style(full_height=True)

    def set_key(state, openai_api_key):
        return state["client"].set_key(openai_api_key)

    def add_text(state, chatbot, txt):
        return state["client"].add_text(chatbot, txt)

    def set_token(state, hugging_face_token):
        return state["client"].set_token(hugging_face_token)

    def bot(state, chatbot):
        return state["client"].bot(chatbot)

    if not OPENAI_KEY:
        openai_api_key.submit(set_key, [state, openai_api_key], [openai_api_key])
        btn1.click(set_key, [state, openai_api_key], [openai_api_key])

    if not HUGGINGFACE_TOKEN:
        hugging_face_token.submit(
            set_token, [state, hugging_face_token], [hugging_face_token]
        )
        btn3.click(set_token, [state, hugging_face_token], [hugging_face_token])

    txt.submit(add_text, [state, chatbot, txt], [chatbot, txt]).then(
        bot, [state, chatbot], [chatbot, results]
    )
    btn2.click(add_text, [state, chatbot, txt], [chatbot, txt]).then(
        bot, [state, chatbot], [chatbot, results]
    )

    gr.Examples(
        examples=[
            "Given a collection of image A: /examples/a.jpg, B: /examples/b.jpg, C: /examples/c.jpg, please tell me how many zebras in these picture?",
            "show me a joke and an image of cat",
            "what is in the examples/a.jpg",
        ],
        inputs=txt,
    )

demo.launch()