simple_app.py

#### pip install advertools
#### pip install emoji
#### pip install emoji-chengyu
#### pip install gradio-client

#### prefer to run in chorme, others may have problem in change hock function

import gradio as gr
import pandas as pd

import emoji
from advertools.emoji import emoji_df
from copy import deepcopy
import numpy as np

from emoji_chengyu.data import DefaultChengyuManager
from emoji_chengyu.puzzle import make_one_puzzle, gen_puzzle

from Lex import *
'''
lex = Lexica(query="man woman fire snow").images()
'''
from PIL import Image
import requests

from zipfile import ZipFile

from time import sleep
sleep_time = 0.5

from gradio_client import Client
llm_client = Client("https://svjack-wizardlm-13b-ggml.hf.space/--replicas/bnqpc/")

'''
llm_result = llm_client.predict(
		"Use following emojis to generate a short description of a scene , the emojis are 👨👩🔥❄️",	# str  in 'Question/Instruction' Textbox component
		0.8,	# int | float (numeric value between 0.1 and 1.0) in 'Temperature' Slider component
		0.95,	# int | float (numeric value between 0.0 and 1.0) in 'Top-p (nucleus sampling)' Slider component
		40,	# int | float (numeric value between 5 and 80) in 'Top-k' Slider component
		256,	# int | float (numeric value between 0 and 1024) in 'Maximum new tokens' Slider component
		52,	# int | float  in 'Seed' Number component
		fn_index=1
)
'''

def run_llm_client(llm_client, prompt):
    llm_result = llm_client.predict(
    		prompt,	# str  in 'Question/Instruction' Textbox component
    		0.8,	# int | float (numeric value between 0.1 and 1.0) in 'Temperature' Slider component
    		0.95,	# int | float (numeric value between 0.0 and 1.0) in 'Top-p (nucleus sampling)' Slider component
    		40,	# int | float (numeric value between 5 and 80) in 'Top-k' Slider component
    		256,	# int | float (numeric value between 0 and 1024) in 'Maximum new tokens' Slider component
    		52,	# int | float  in 'Seed' Number component
    		fn_index=1
    )
    return llm_result

def min_dim_to_size(img, size = 512):
    h, w = img.size
    ratio = size / max(h, w)
    h, w = map(lambda x: int(x * ratio), [h, w])
    return ( ratio ,img.resize((h, w)) )

def lexica(prompt, limit_size = 128, ratio_size = 256 + 128):
    if not prompt or not prompt.strip():
        return []
    prompt = prompt.strip()
    lex = Lexica(query=prompt).images()
    lex = lex[:limit_size]
    lex = list(map(lambda x: x.replace("full_jpg", "sm2"), lex))
    lex_ = []
    for ele in lex:
        try:
            im = Image.open(
                            requests.get(ele, stream = True).raw
                            )
            lex_.append(im)
        except:
            print("err")
        sleep(sleep_time)
    assert lex_
    lex = list(map(lambda x: min_dim_to_size(x, ratio_size)[1], lex_))
    return lex

def search(emoji_outputs, emoji2text_or_not, llm_prompt_input, llm_client = llm_client):
    assert emoji2text_or_not in ["Emoji to Text", "Only Emoji"]
    if emoji2text_or_not == "Only Emoji":
        l = lexica(emoji_outputs)
        return (l, "")
    else:
        assert "{}" in llm_prompt_input
        llm_prompt = llm_prompt_input.format(emoji_outputs)
        llm_output = run_llm_client(llm_client, llm_prompt)
        tail_list = ["someone do something"]
        for tail in tail_list:
            if tail in llm_output and len(llm_output.split(tail)[-1]) > (5 * 3):
                llm_output = llm_output.split(tail)[-1]
        l = lexica(llm_output)
        return (l, llm_output)

def enterpix(prompt, limit_size = 100, ratio_size = 256 + 128, use_key = "bigThumbnailUrl"):
    resp = requests.post(
    url = "https://www.enterpix.app/enterpix/v1/image/prompt-search",
    data= {
        "length": limit_size,
        "platform": "stable-diffusion,midjourney",
        "prompt": prompt,
        "start": 0
        }
    )
    resp = resp.json()
    resp = list(map(lambda x: x[use_key], resp["images"]))
    lex_ = []
    for ele in resp:
        try:
            im = Image.open(
                            requests.get(ele, stream = True).raw
                            )
            lex_.append(im)
        except:
            print("err")
        sleep(sleep_time)
    assert lex_
    resp = list(map(lambda x: min_dim_to_size(x, ratio_size)[1], lex_))
    return resp

def zip_ims(g):
    from uuid import uuid1
    if g is None:
        return None
    l = list(map(lambda x: x["name"], g))
    if not l:
        return None
    zip_file_name ="tmp.zip"
    with ZipFile(zip_file_name ,"w") as zipObj:
        for ele in l:
            zipObj.write(ele, "{}.png".format(uuid1()))
        #zipObj.write(file2.name, "file2")
    return zip_file_name

emoji_order_list = [
    ["🍇", ["🥢","🍼", "🍱", "🍇", "🦀"]],
    ["😀", ["🥰", "😕", "😺", "💋", "💩"]],
    ["🐵", ["🐵", "🦃", "🐌", "🐳"]],
    ["📔", ["👓" ,"📔", "🚪", "🔋", "🎥"]],
    ["🎃", ["⚽", "🎃", "🎯", "🎭", "🎖️"]],
    #["🌍", ["🌍", "🏠"️, "⛲", "🏔"️]],
    ["👋", ["👍", "💪", "👋", "👌",]],
    ["🌍", ["🌍", "⛲", "🏠",]],
]

sub_cate_num = 5
sub_cate_size = 36
sub_col_num = 6

def list_to_square(l, col_num = 10):
    assert type(l) == type([])
    row_num = len(l) // col_num
    res = len(l) % col_num
    if res > 0:
        res_for_add = col_num - res
    else:
        res_for_add = 0
        ll = np.asarray(l).reshape([-1, col_num]).tolist()
        return ll
    l_ = deepcopy(l) + [""] * res_for_add
    return list_to_square(l_, col_num)

def append_emojis(selected_index: gr.SelectData, dataframe_origin, emoji_prompt):
    val = dataframe_origin.iloc[selected_index.index[0], selected_index.index[1]]
    if val.strip():
        emoji_prompt = emoji_prompt + val
    return emoji_prompt

def append_chengyu_emojis(selected_index: gr.SelectData, dataframe_origin, emoji_prompt, append_or_replace):
    val = dataframe_origin.iloc[selected_index.index[0], selected_index.index[1]]
    if type(val) != type("") or not val:
        return emoji_prompt
    assert append_or_replace in ["replace", "append"]
    if append_or_replace == "append":
        emoji_prompt = emoji_prompt + val.split(":")[-1]
    else:
        emoji_prompt = val.split(":")[-1]
    return emoji_prompt

def extract_emojis(s):
    #return ''.join(c for c in s if c in emoji.UNICODE_EMOJI['en'])
    dl = emoji.emoji_list(s + "s")
    return "".join(map(lambda x: x["emoji"], dl))

def gen_emojis_by_chengyu(words):
    assert type(words) == type("")
    out = DefaultChengyuManager.get_by_word(words)
    if out is None:
        return ""
    out = "".join(make_one_puzzle(out).puzzle)
    out = extract_emojis(out)
    return out

def gen_emojis_by_sample(search_count=5000):
    pg = gen_puzzle(manager=DefaultChengyuManager, search_count=search_count)
    df = pd.DataFrame(list(map(lambda x: {
        "words": "".join(x.chengyu_item.word_list),
        "emoji": x.puzzle_str,
        "score": sum(x.mask)
    } ,pg)))
    df = df[df["score"] == 4]
    df = df[df["words"].map(lambda x: len(x) == 4)]
    req = []
    col0 = set([])
    col1 = set([])
    col2 = set([])
    col3 = set([])
    for i, r in df.iterrows():
        words = r["words"]
        emoji = r["emoji"]
        if emoji[0] in col0:
            continue
        col0.add(emoji[0])
        if emoji[1] in col1:
            continue
        col1.add(emoji[1])
        if emoji[2] in col2:
            continue
        col2.add(emoji[2])
        if emoji[3] in col3:
            continue
        col3.add(emoji[3])
        req.append(
            r.to_dict()
        )
    df = pd.DataFrame(req)
    if len(df) < 21:
        return gen_emojis_by_sample(search_count=search_count)
    df = pd.DataFrame(
    np.asarray(df.apply(lambda x: x.to_dict(), axis = 1).head(21).map(lambda x:
                    "{}:{}".format(x["words"],x["emoji"])
    ).tolist()).reshape(
        (7, 3)
    )
    )
    return df

def append_pure_to_input(emoji_outputs ,only_emoji_outputs):
    return emoji_outputs + only_emoji_outputs

css = """
#frame span{
 font-size: 1.5em; display: flex; align-items: center;
}
"""

###with gr.Blocks(css="custom.css") as demo:
with gr.Blocks(css = css) as demo:
    title = gr.HTML(
            """<h1 align="center"> <font size="+10"> 🕌 Emojis to StableDiffusion World 🌍 </font> </h1>""",
            elem_id="title",
    )

    frame_list = []
    with gr.Row():
        with gr.Column(label = "Emoji samples, You can click to use them"):
            sub_title_0 = gr.Markdown(
                    value="### Emoji samples, You can click to use them",
                    visible=True,
                    #elem_id="selected_model",
                )
            #for group, df in emoji_df.groupby("group"):
            for group_order_ele, sub_group_order_list in emoji_order_list:
                #group_first = df["emoji"].iloc[0]
                group_first = group_order_ele
                df_group = emoji_df[emoji_df["emoji"] == group_first]["group"].iloc[0]
                df = emoji_df[emoji_df["group"] == df_group]
                with gr.Tab("{} {}".format(group_first, df_group)):
                    #for ii ,(sub_group, dff) in enumerate(df.groupby("sub_group")):
                    for ii in range(len(sub_group_order_list)):
                        sub_first = sub_group_order_list[ii]
                        df_sub_group = emoji_df[emoji_df["emoji"] == sub_first]["sub_group"].iloc[0]
                        dff = df[df["sub_group"] == df_sub_group]
                        if ii >= sub_cate_num:
                            break
                        sub_first = dff["emoji"].iloc[0]
                        sub_l = dff["emoji"].values.tolist()[:sub_cate_size]
                        sub_l_square = list_to_square(sub_l, sub_col_num)
                        g_frame = gr.DataFrame(sub_l_square,
                            interactive=False, headers = [''] * sub_col_num,
                            #datatype="markdown"
                            elem_id="frame",
                            label = "{} {}".format(sub_first, df_sub_group)
                        )
                        #g_frame = gr.Matrix(sub_l_square, label = sub_first,)
                        frame_list.append(g_frame)
        with gr.Column():
            with gr.Row():
                with gr.Column():
                    sub_title_1 = gr.Markdown(
                                  value="### ChengYu to Emoji combinations, You can click to use them, Don't forget edit them after click, to make it meaningful",
                                  visible=True,
                                  #elem_id="selected_model",
                                )
                    chengyu_frame = gr.DataFrame(gen_emojis_by_sample(),
                            interactive=False, headers = [''] * sub_col_num,
                            #datatype="markdown"
                            elem_id="chengyu_frame",
                            #label = "ChengYu to Emoji combinations, You can click to use them"
                        )
                    with gr.Row():
                        chengyu_reset_button = gr.Button("Reset ChengYu Emojis",
                        elem_id="run_button")
                    with gr.Row():
                        append_or_replace = gr.Radio(choices=["replace", "append"],
                            value="replace", label="ChengYu Emoji Append or Replace to below", elem_id="text_radio")
            with gr.Row():
                emoji_outputs = gr.Textbox(label="Emoji Prompt Output", show_label=True, lines=1, max_lines=20,
                min_width = 256, placeholder="Click Emoji from left with some emoji input manually", elem_id="prompt",
                interactive=True)
                clean_button = gr.Button("Clean Emojis", elem_id="clean_button")
                '''
                with gr.Column():
                    clean_button = gr.Button("Clean Emojis", elem_id="clean_button")
                    emoji_outputs_button = gr.Button("Retrieve Images", elem_id="run_button")
                '''
            with gr.Row():
                emoji2text_or_not = gr.Radio(choices=["Only Emoji", "Emoji to Text"],
                    value="Only Emoji", label="Only use Emoji to get images or translate them to Text by LLM",
                    elem_id="trans_radio")
            with gr.Row():
                llm_prompt_input = gr.Textbox(label="Emoji to Text Prompt template used by LLM", show_label=True,
                lines=1, max_lines=20,
                min_width = 256,
                value="Use following emojis to generate a short description of a scene , use the pattern someone do something , the emojis are {}"
                , elem_id="prompt",
                interactive=True)
                llm_outputs = gr.Textbox(label="Emoji to Text Prompt translate by LLM Output", show_label=True,
                lines=1, max_lines=20,
                min_width = 256, placeholder="Emoji describe by Text", elem_id="prompt",
                interactive=True)
            '''
            with gr.Row():
                emoji_gen_chengyu_input = gr.Textbox(label="ChengYu Prompt Input", show_label=False, lines=1, max_lines=20,
                min_width = 256, placeholder="input ChengYu manually, like: 励精图治", elem_id="prompt",
                interactive=True)

            with gr.Row():
                only_emoji_outputs = gr.Textbox(label="Only Emoji Prompt Output", show_label=False, lines=1, max_lines=20,
                min_width = 256, placeholder="Filter out only emoji charactors", elem_id="prompt", interactive=True)
                #gr.Slider(label='Number of images ', minimum = 4, maximum = 20, step = 1, value = 4)]
                append_button = gr.Button("Append Only Emojis to Emoji Prompt Output", elem_id="append_button")
                only_emoji_outputs_button = gr.Button("Retrieve Images Only Emoji", elem_id="run_button")

            with gr.Row():
                #text_button = gr.Button("Retrieve Images", elem_id="run_button")
                emoji_outputs_button = gr.Button("Retrieve Images", elem_id="run_button")
            '''
            with gr.Row():
                emoji_outputs_button = gr.Button("Retrieve Images", elem_id="run_button")

            with gr.Row():
                with gr.Column():
                    outputs = gr.Gallery(lable='Output gallery', elem_id="gallery",).style(grid=5,height=768 - 64 - 32,
                            allow_preview=False, label = "retrieve Images")
                    exp_title = gr.HTML(
                            """<br/><br/><h5 align="center"> <font size="+1"> Emojis examples live in 🕌 travel to StableDiffusion 🌍 </font> </h5>""",
                            #elem_id="title",
                    )
                    gr.Examples(
                        [
                            ["🍔", "Only Emoji"],
                            ["🔥🌲", "Only Emoji"],
                            ["🐱🍽️👨", "Emoji to Text"],
                            ["🐻🍦❄️🌊", "Only Emoji"],
                            ["🌎🦶👂💤", "Emoji to Text"],
                            ["👩‍🔬🗣☕👨‍🎨", "Emoji to Text"],
                            ["👜👚🧣👸🏰✌️", "Emoji to Text"],
                            ["👝🍍🎃👶🥛🌾🕵🏃‍♀️", "Emoji to Text"],
                            ["🙃💍👋👨‍🔧👄🥀🌎🌙", "Emoji to Text"],
                        ],
                    inputs = [emoji_outputs, emoji2text_or_not],
                    #label = "🕌 Examples"
                    )

            with gr.Row():
                with gr.Tab(label = "Download"):
                    zip_button = gr.Button("Zip Images to Download", elem_id="zip_button")
                    downloads = gr.File(label = "Image zipped", elem_id = "zip_file")


    for g in frame_list:
        g.select(fn = append_emojis, inputs = [g, emoji_outputs], outputs = emoji_outputs)

    chengyu_frame.select(fn = append_chengyu_emojis, inputs = [chengyu_frame, emoji_outputs, append_or_replace],
        outputs = emoji_outputs)
    chengyu_reset_button.click(fn = lambda _: gen_emojis_by_sample(), outputs = chengyu_frame)

    clean_button.click(fn = lambda _: "", outputs = emoji_outputs)
    #emoji_outputs.change(fn = extract_emojis, inputs = emoji_outputs, outputs = only_emoji_outputs)
    '''
    emoji_gen_chengyu_input.change(fn = gen_emojis_by_chengyu, inputs = emoji_gen_chengyu_input,
        outputs = only_emoji_outputs)
    append_button.click(fn =  append_pure_to_input, inputs = [emoji_outputs ,only_emoji_outputs],
    outputs = emoji_outputs)
    '''

    #emoji_outputs_button.click(lexica, inputs=emoji_outputs, outputs=outputs)
    emoji_outputs_button.click(search,
        inputs=[emoji_outputs, emoji2text_or_not, llm_prompt_input],
        outputs=[outputs, llm_outputs])

    zip_button.click(
        zip_ims, inputs = outputs, outputs=downloads
    )

demo.launch("0.0.0.0")