Create app.py

app.py

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+#### 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",
+                                  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")