Leyo commited on
Commit
04968d8
1 Parent(s): 7741ba8

create space and add fonts

Browse files
IDEFICS_logo.png ADDED
app_dialogue.py ADDED
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1
+ import ast
2
+ import copy
3
+ import glob
4
+ import hashlib
5
+ import logging
6
+ import os
7
+ import re
8
+ from pathlib import Path
9
+ from typing import List, Optional, Tuple
10
+ from urllib.parse import urlparse
11
+ from PIL import Image, ImageDraw, ImageFont
12
+
13
+ import random
14
+ import gradio as gr
15
+ import PIL
16
+ from gradio import processing_utils
17
+ from gradio_client.client import DEFAULT_TEMP_DIR
18
+ from text_generation import Client
19
+ from transformers import AutoProcessor
20
+
21
+
22
+ MODELS = [
23
+ # "HuggingFaceM4/idefics-9b-instruct",
24
+ "HuggingFaceM4/idefics-80b-instruct",
25
+ ]
26
+
27
+ API_PATHS = {
28
+ "HuggingFaceM4/idefics-9b-instruct": (
29
+ "https://api-inference.huggingface.co/models/HuggingFaceM4/idefics-9b-instruct"
30
+ ),
31
+ "HuggingFaceM4/idefics-80b-instruct": (
32
+ "https://api-inference.huggingface.co/models/HuggingFaceM4/idefics-80b-instruct"
33
+ ),
34
+ }
35
+
36
+ SYSTEM_PROMPT = [
37
+ """The following is a conversation between a highly knowledgeable and intelligent visual AI assistant, called Assistant, and a human user, called User.
38
+ In the following interactions, User and Assistant will converse in natural language, and Assistant will answer in a sassy way.
39
+ Assistant's main purpose is to create funny meme texts from the images User provides.
40
+ Assistant should be funny, sassy, and impertinent, and sometimes Assistant roasts people.
41
+ Assistant should not be mean. It should not say toxic, homophobic, sexist, racist, things or any demeaning things that can make people uncomfortable.
42
+ Assistant was created by Hugging Face.
43
+
44
+ Here's a conversation example:""",
45
+ """\nUser:""",
46
+ "https://ichef.bbci.co.uk/news/976/cpsprodpb/7727/production/_103330503_musk3.jpg",
47
+ "Write a meme for that image.<end_of_utterance>",
48
+ """\nAssistant: When you're trying to quit smoking but the cravings are too strong.<end_of_utterance>""",
49
+ "\nUser:How about this image?",
50
+ "https://www.boredpanda.com/blog/wp-content/uploads/2017/01/image-copy-copy-587d0e7918b57-png__700.jpg",
51
+ "Write something funny about this image.<end_of_utterance>",
52
+ """\nAssistant: Eggcellent service!<end_of_utterance>""",
53
+ "\nUser: Roast this person",
54
+ "https://i.pinimg.com/564x/98/34/4b/98344b2483bd7c8b71a5c0fed6fe20b6.jpg",
55
+ "<end_of_utterance>",
56
+ """\nAssistant: Damn your handwritting is pretty awful. But I suppose it must be pretty hard to hold a pen, considering you are a hammerhead shark.<end_of_utterance>""",
57
+ ]
58
+
59
+ BAN_TOKENS = ( # For documentation puporse. We are not using this list, it is hardcoded inside `idefics_causal_lm.py` inside TGI.
60
+ "<image>;<fake_token_around_image>"
61
+ )
62
+ EOS_STRINGS = ["<end_of_utterance>", "\nUser:"]
63
+ STOP_SUSPECT_LIST = []
64
+
65
+ GRADIO_LINK = "https://huggingfacem4-ai-meme-generator.hf.space"
66
+ API_TOKEN = os.getenv("HF_AUTH_TOKEN")
67
+ IDEFICS_LOGO = "https://huggingface.co/spaces/HuggingFaceM4/idefics_playground/resolve/main/IDEFICS_logo.png"
68
+
69
+ PROCESSOR = AutoProcessor.from_pretrained(
70
+ "HuggingFaceM4/idefics-9b-instruct",
71
+ token=API_TOKEN,
72
+ )
73
+
74
+ BOT_AVATAR = "IDEFICS_logo.png"
75
+
76
+ logging.basicConfig(level=logging.INFO)
77
+ logger = logging.getLogger()
78
+
79
+
80
+ # Monkey patch adapted from gradio.components.image.Image - mostly to make the `save` step optional in `pil_to_temp_file`
81
+ def hash_bytes(bytes: bytes):
82
+ sha1 = hashlib.sha1()
83
+ sha1.update(bytes)
84
+ return sha1.hexdigest()
85
+
86
+
87
+ def pil_to_temp_file(
88
+ img: PIL.Image.Image, dir: str = DEFAULT_TEMP_DIR, format: str = "png"
89
+ ) -> str:
90
+ """Save a PIL image into a temp file"""
91
+ bytes_data = processing_utils.encode_pil_to_bytes(img, format)
92
+ temp_dir = Path(dir) / hash_bytes(bytes_data)
93
+ temp_dir.mkdir(exist_ok=True, parents=True)
94
+ filename = str(temp_dir / f"image.{format}")
95
+ if not os.path.exists(filename):
96
+ img.save(filename, pnginfo=processing_utils.get_pil_metadata(img))
97
+ return filename
98
+
99
+
100
+ def add_file(file):
101
+ return file.name, gr.update(label="🖼️ Uploaded!")
102
+
103
+
104
+ def add_file_gallery(selected_state: gr.SelectData, gallery_list: List[str]):
105
+ gr.update(label="📁 Upload image", interactive=True)
106
+ return (
107
+ "Write a meme about this image.",
108
+ gallery_list[selected_state.index]["name"],
109
+ "",
110
+ )
111
+
112
+
113
+ def choose_gallery(gallery_type: str):
114
+ if gallery_type == "Meme templates":
115
+ image_gallery_list = [
116
+ f"example_images/meme_templates/{ex_image}"
117
+ for ex_image in os.listdir("example_images/meme_templates")
118
+ ]
119
+ elif gallery_type == "Funny images":
120
+ image_gallery_list = [
121
+ f"example_images/funny_images/{ex_image}"
122
+ for ex_image in os.listdir("example_images/funny_images")
123
+ ]
124
+ elif gallery_type == "Politics":
125
+ image_gallery_list = [
126
+ f"example_images/politics_memes/{ex_image}"
127
+ for ex_image in os.listdir("example_images/politics_memes")
128
+ ]
129
+ else:
130
+ image_gallery_list = [
131
+ f"example_images/{image_dir}/{ex_image}"
132
+ for image_dir in os.listdir("example_images")
133
+ for ex_image in os.listdir(f"example_images/{image_dir}")
134
+ ]
135
+ random.shuffle(image_gallery_list)
136
+ return image_gallery_list
137
+
138
+
139
+ # This is a hack to make pre-computing the default examples work.
140
+ # During normal inference, we pass images as url to a local file using the method `gradio_link`
141
+ # which allows the tgi server to fetch the local image from the frontend server.
142
+ # however, we are building the space (and pre-computing is part of building the space), the frontend is not available
143
+ # and won't answer. So tgi server will try to fetch an image that is not available yet, which will result in a timeout error
144
+ # because tgi will never be able to return the generation.
145
+ # To bypass that, we pass instead the images URLs from the spaces repo.
146
+ DEFAULT_IMAGES_TMP_PATH_TO_URL = {}
147
+ for image_dir in os.listdir("example_images"):
148
+ for im_path in os.listdir(f"example_images/{image_dir}"):
149
+ H = gr.Image(
150
+ f"example_images/{image_dir}/{im_path}", visible=False, type="filepath"
151
+ )
152
+ tmp_filename = H.preprocess(H.value)
153
+ DEFAULT_IMAGES_TMP_PATH_TO_URL[
154
+ tmp_filename
155
+ ] = f"https://huggingface.co/spaces/HuggingFaceM4/AI_Meme_Generator/resolve/main/example_images/{image_dir}/{im_path}"
156
+
157
+
158
+ # Utils to handle the image markdown display logic
159
+ def split_str_on_im_markdown(string: str) -> List[str]:
160
+ """
161
+ Extract from a string (typically the user prompt string) the potential images from markdown
162
+ Examples:
163
+ - `User:![](https://favurl.com/chicken_on_money.png)Describe this image.` would become `["User:", "https://favurl.com/chicken_on_money.png", "Describe this image."]`
164
+ - `User:![](/file=/my_temp/chicken_on_money.png)Describe this image.` would become `["User:", "/my_temp/chicken_on_money.png", "Describe this image."]`
165
+ """
166
+ IMAGES_PATTERN = re.compile(r"!\[[^\]]*\]\((.*?)\s*(\"(?:.*[^\"])\")?\s*\)")
167
+ parts = []
168
+ cursor = 0
169
+ for pattern in IMAGES_PATTERN.finditer(string):
170
+ start = pattern.start()
171
+ if start != cursor:
172
+ parts.append(string[cursor:start])
173
+ image_url = pattern.group(1)
174
+ if image_url.startswith("/file="):
175
+ image_url = image_url[6:] # Remove the 'file=' prefix
176
+ parts.append(image_url)
177
+ cursor = pattern.end()
178
+ if cursor != len(string):
179
+ parts.append(string[cursor:])
180
+ return parts
181
+
182
+
183
+ def is_image(string: str) -> bool:
184
+ """
185
+ There are two ways for images: local image path or url.
186
+ """
187
+ return is_url(string) or string.startswith(DEFAULT_TEMP_DIR)
188
+
189
+
190
+ def is_url(string: str) -> bool:
191
+ """
192
+ Checks if the passed string contains a valid url and nothing else. e.g. if space is included it's immediately
193
+ invalidated the url
194
+ """
195
+ if " " in string:
196
+ return False
197
+ result = urlparse(string)
198
+ return all([result.scheme, result.netloc])
199
+
200
+
201
+ def isolate_images_urls(prompt_list: List) -> List:
202
+ """
203
+ Convert a full string prompt to the list format expected by the processor.
204
+ In particular, image urls (as delimited by <fake_token_around_image>) should be their own elements.
205
+ From:
206
+ ```
207
+ [
208
+ "bonjour<fake_token_around_image><image:IMG_URL><fake_token_around_image>hello",
209
+ PIL.Image.Image,
210
+ "Aurevoir",
211
+ ]
212
+ ```
213
+ to:
214
+ ```
215
+ [
216
+ "bonjour",
217
+ IMG_URL,
218
+ "hello",
219
+ PIL.Image.Image,
220
+ "Aurevoir",
221
+ ]
222
+ ```
223
+ """
224
+ linearized_list = []
225
+ for prompt in prompt_list:
226
+ # Prompt can be either a string, or a PIL image
227
+ if isinstance(prompt, PIL.Image.Image):
228
+ linearized_list.append(prompt)
229
+ elif isinstance(prompt, str):
230
+ if "<fake_token_around_image>" not in prompt:
231
+ linearized_list.append(prompt)
232
+ else:
233
+ prompt_splitted = prompt.split("<fake_token_around_image>")
234
+ for ps in prompt_splitted:
235
+ if ps == "":
236
+ continue
237
+ if ps.startswith("<image:"):
238
+ linearized_list.append(ps[7:-1])
239
+ else:
240
+ linearized_list.append(ps)
241
+ else:
242
+ raise TypeError(
243
+ f"Unrecognized type for `prompt`. Got {type(type(prompt))}. Was expecting something in [`str`,"
244
+ " `PIL.Image.Image`]"
245
+ )
246
+ return linearized_list
247
+
248
+
249
+ def fetch_images(url_list: str) -> PIL.Image.Image:
250
+ """Fetching images"""
251
+ return PROCESSOR.image_processor.fetch_images(url_list)
252
+
253
+
254
+ def handle_manual_images_in_user_prompt(user_prompt: str) -> List[str]:
255
+ """
256
+ Handle the case of textually manually inputted images (i.e. the `<fake_token_around_image><image:IMG_URL><fake_token_around_image>`) in the user prompt
257
+ by fetching them, saving them locally and replacing the whole sub-sequence the image local path.
258
+ """
259
+ if "<fake_token_around_image>" in user_prompt:
260
+ splitted_user_prompt = isolate_images_urls([user_prompt])
261
+ resulting_user_prompt = []
262
+ for u_p in splitted_user_prompt:
263
+ if is_url(u_p):
264
+ img = fetch_images([u_p])[0]
265
+ tmp_file = pil_to_temp_file(img)
266
+ resulting_user_prompt.append(tmp_file)
267
+ else:
268
+ resulting_user_prompt.append(u_p)
269
+ return resulting_user_prompt
270
+ else:
271
+ return [user_prompt]
272
+
273
+
274
+ def gradio_link(img_path: str) -> str:
275
+ url = f"{GRADIO_LINK}/file={img_path}"
276
+ return url
277
+
278
+
279
+ def prompt_list_to_markdown(prompt_list: List[str], size: int = None) -> str:
280
+ """
281
+ Convert a user prompt in the list format (i.e. elements are either a PIL image or a string) into
282
+ the markdown format that is used for the chatbot history and rendering.
283
+ """
284
+ resulting_string = ""
285
+ for elem in prompt_list:
286
+ if is_image(elem):
287
+ if is_url(elem):
288
+ if size is not None:
289
+ resulting_string += f"<img src={elem} width={size} height={size}>"
290
+ else:
291
+ resulting_string += f"![]({elem})"
292
+ else:
293
+ if size is not None:
294
+ resulting_string += f"<img src='/file={str(elem)}' width='{size}' height={str(size)}>"
295
+ else:
296
+ resulting_string += f"![](/file={elem})"
297
+ else:
298
+ resulting_string += elem
299
+ return resulting_string
300
+
301
+
302
+ def prompt_list_to_tgi_input(prompt_list: List[str]) -> str:
303
+ """
304
+ TGI expects a string that contains both text and images in the image markdown format (i.e. the `![]()` ).
305
+ The images links are parsed on TGI side
306
+ """
307
+ result_string_input = ""
308
+ for elem in prompt_list:
309
+ if is_image(elem):
310
+ if is_url(elem):
311
+ result_string_input += f"![]({elem})"
312
+ else:
313
+ result_string_input += f"![]({gradio_link(img_path=elem)})"
314
+ else:
315
+ result_string_input += elem
316
+ return result_string_input
317
+
318
+
319
+ def remove_spaces_around_token(text: str) -> str:
320
+ pattern = r"\s*(<fake_token_around_image>)\s*"
321
+ replacement = r"\1"
322
+ result = re.sub(pattern, replacement, text)
323
+ return result
324
+
325
+
326
+ # Chatbot utils
327
+ Radio_options_to_font = {}
328
+
329
+
330
+ def insert_backslash(string, max_length=50):
331
+ # Check if the string length is less than or equal to the max_length
332
+ if len(string) <= max_length:
333
+ return string
334
+
335
+ # Start from the max_length character and search for the last space character before it
336
+ for i in range(max_length - 1, -1, -1):
337
+ if string[i] == " ":
338
+ # Insert a backslash before the last space character
339
+ return string[:i] + "\n" + string[i:]
340
+
341
+ # If no space character is found, just insert a backslash at the max_length character
342
+ return string[:max_length] + "\n" + string[max_length:]
343
+
344
+
345
+ def resize_with_ratio(image: PIL.Image.Image, fixed_width: int) -> PIL.Image.Image:
346
+ # Get the current width and height
347
+ width, height = image.size
348
+
349
+ # Calculate the new width while maintaining the aspect ratio up to 2:3 ratio
350
+ new_width = fixed_width
351
+ new_height = min(int(height * (new_width / width)), int(1.5 * new_width))
352
+
353
+ # Resize the image
354
+ resized_img = image.resize((new_width, new_height), Image.LANCZOS)
355
+
356
+ return resized_img
357
+
358
+
359
+ def test_font_size(
360
+ draw,
361
+ image,
362
+ text,
363
+ font,
364
+ font_meme_text,
365
+ num_lines=1,
366
+ min_font=35,
367
+ font_size_reduction=5,
368
+ ):
369
+ text_width = draw.textlength(text, font)
370
+ text_is_too_long = True
371
+
372
+ if num_lines == 1:
373
+ while font.size > min_font and text_is_too_long:
374
+ font = ImageFont.truetype(
375
+ f"fonts/{font_meme_text}.ttf", size=font.size - font_size_reduction
376
+ )
377
+ text_width = draw.textlength(text, font)
378
+ text_is_too_long = text_width > image.width
379
+
380
+ elif num_lines == 2:
381
+ while font.size > min_font and text_is_too_long:
382
+ font = ImageFont.truetype(
383
+ f"fonts/{font_meme_text}.ttf", size=font.size - font_size_reduction
384
+ )
385
+ max_len_increment = 0
386
+ while (
387
+ text_is_too_long
388
+ and max_len_increment < 10
389
+ and max_len_increment < (len(text)) // 2
390
+ ):
391
+ temp_text = insert_backslash(
392
+ text, max_length=(len(text) + max_len_increment) // 2
393
+ )
394
+ first_line, second_line = (
395
+ temp_text.split("\n")[0],
396
+ temp_text.split("\n")[1],
397
+ )
398
+ text_width = max(
399
+ draw.textlength(first_line, font),
400
+ draw.textlength(second_line, font),
401
+ )
402
+ text_is_too_long = text_width > image.width
403
+ max_len_increment += 1
404
+
405
+ elif num_lines == 3:
406
+ while font.size > min_font and text_is_too_long:
407
+ font = ImageFont.truetype(
408
+ f"fonts/{font_meme_text}.ttf", size=font.size - font_size_reduction
409
+ )
410
+ max_len_incr_1_split = 0
411
+ while text_is_too_long and max_len_incr_1_split < 10:
412
+ first_temp_text = insert_backslash(
413
+ text, max_length=(len(text) + max_len_incr_1_split) // 3
414
+ )
415
+ first_line, second_line = (
416
+ first_temp_text.split("\n")[0],
417
+ first_temp_text.split("\n")[1],
418
+ )
419
+ max_len_incr_2_split = 0
420
+ while text_is_too_long and max_len_incr_2_split < 10:
421
+ temp_text_second_line = insert_backslash(
422
+ second_line,
423
+ max_length=(len(second_line) + max_len_incr_2_split) // 2,
424
+ )
425
+ second_line_1, second_line_2 = (
426
+ temp_text_second_line.split("\n")[0],
427
+ temp_text_second_line.split("\n")[1],
428
+ )
429
+ temp_text = first_line + "\n" + second_line_1 + "\n" + second_line_2
430
+ text_width = max(
431
+ draw.textlength(first_line, font),
432
+ draw.textlength(second_line_1, font),
433
+ draw.textlength(second_line_2, font),
434
+ )
435
+ text_is_too_long = text_width > image.width
436
+ max_len_incr_2_split += 1
437
+ max_len_incr_1_split += 1
438
+ else:
439
+ raise (ValueError("num_lines can only be 1, 2 or 3"))
440
+
441
+ if not text_is_too_long and num_lines > 1:
442
+ text = temp_text
443
+ return text, font, text_width, text_is_too_long
444
+
445
+
446
+ def make_meme_image(
447
+ image: str,
448
+ text: str,
449
+ font_meme_text: str,
450
+ all_caps_meme_text: bool = False,
451
+ text_at_the_top: bool = False,
452
+ ) -> PIL.Image.Image:
453
+ """
454
+ Takes an image and a text and returns a meme image.
455
+ """
456
+ text = text.replace("\nUser", " ").replace("\n", " ").strip().rstrip(".")
457
+ if all_caps_meme_text:
458
+ text = text.upper()
459
+ # Resize image
460
+ fixed_width = 700
461
+ image = Image.open(image)
462
+ image = resize_with_ratio(image, fixed_width)
463
+ image_width, image_height = image.size
464
+ height_width_ratio = image_height / image_width
465
+
466
+ draw = ImageDraw.Draw(image)
467
+ min_font = 30
468
+ initial_font_size = 60
469
+ if height_width_ratio > 1:
470
+ min_font = 40
471
+ initial_font_size = 80
472
+ text_is_too_long = True
473
+ num_lines = 0
474
+ while text_is_too_long and num_lines < 3:
475
+ num_lines += 1
476
+ font = ImageFont.truetype(f"fonts/{font_meme_text}.ttf", size=initial_font_size)
477
+ text, font, text_width, text_is_too_long = test_font_size(
478
+ draw,
479
+ image,
480
+ text,
481
+ font,
482
+ font_meme_text,
483
+ num_lines=num_lines,
484
+ min_font=min_font,
485
+ font_size_reduction=5,
486
+ )
487
+
488
+ if text_is_too_long:
489
+ text = f"Text is too long to fit the image"
490
+ if all_caps_meme_text:
491
+ text = text.upper()
492
+ font = ImageFont.truetype(f"fonts/{font_meme_text}.ttf", size=font.size)
493
+ text_width = draw.textlength(text, font)
494
+
495
+ outline_width = 2
496
+ text_x = (image_width - text_width) / 2
497
+ text_y = image_height - num_lines * font.size - 10 - num_lines
498
+ if text_at_the_top:
499
+ text_y = 0
500
+
501
+ for i in range(-outline_width, outline_width + 1):
502
+ for j in range(-outline_width, outline_width + 1):
503
+ draw.multiline_text(
504
+ (text_x + i, text_y + j), text, fill="black", align="center", font=font
505
+ )
506
+ draw.multiline_text((text_x, text_y), text, fill="white", align="center", font=font)
507
+
508
+ return image
509
+
510
+
511
+ def format_user_prompt_with_im_history_and_system_conditioning(
512
+ system_prompt: List[str],
513
+ current_user_prompt_str: str,
514
+ current_image: Optional[str],
515
+ history: List[Tuple[str, str]],
516
+ ) -> Tuple[List[str], List[str]]:
517
+ """
518
+ Produces the resulting list that needs to go inside the processor.
519
+ It handles the potential image box input, the history and the system conditionning.
520
+ """
521
+ # resulting_list = copy.deepcopy(SYSTEM_PROMPT)
522
+ resulting_list = system_prompt
523
+
524
+ # Format history
525
+ for turn in history:
526
+ user_utterance, assistant_utterance = turn
527
+ splitted_user_utterance = split_str_on_im_markdown(user_utterance)
528
+
529
+ optional_space = ""
530
+ if not is_image(splitted_user_utterance[0]):
531
+ optional_space = " "
532
+ resulting_list.append(f"\nUser:{optional_space}")
533
+ resulting_list.extend(splitted_user_utterance)
534
+ resulting_list.append(f"<end_of_utterance>\nAssistant: {assistant_utterance}")
535
+
536
+ # Format current input
537
+ current_user_prompt_str = remove_spaces_around_token(current_user_prompt_str)
538
+ if current_image is None:
539
+ if "![](" in current_user_prompt_str:
540
+ current_user_prompt_list = split_str_on_im_markdown(current_user_prompt_str)
541
+ else:
542
+ current_user_prompt_list = handle_manual_images_in_user_prompt(
543
+ current_user_prompt_str
544
+ )
545
+
546
+ optional_space = ""
547
+ if not is_image(current_user_prompt_list[0]):
548
+ # Check if the first element is an image (and more precisely a path to an image)
549
+ optional_space = " "
550
+ resulting_list.append(f"\nUser:{optional_space}")
551
+ resulting_list.extend(current_user_prompt_list)
552
+ resulting_list.append("<end_of_utterance>\nAssistant:")
553
+ else:
554
+ # Choosing to put the image first when the image is inputted through the UI, but this is an arbiratrary choice.
555
+ resulting_list.extend(
556
+ [
557
+ "\nUser:",
558
+ current_image,
559
+ f"{current_user_prompt_str}<end_of_utterance>\nAssistant:",
560
+ ]
561
+ )
562
+ current_user_prompt_list = [current_user_prompt_str]
563
+
564
+ return resulting_list, current_user_prompt_list
565
+
566
+
567
+ # dope_callback = gr.CSVLogger()
568
+ # problematic_callback = gr.CSVLogger()
569
+
570
+ textbox = gr.Textbox(
571
+ placeholder="Upload an image and ask the AI to create a meme!",
572
+ show_label=False,
573
+ value="Write a meme about this image.",
574
+ visible=True,
575
+ container=False,
576
+ label="Text input",
577
+ scale=8,
578
+ max_lines=5,
579
+ )
580
+ chatbot = gr.Chatbot(
581
+ elem_id="chatbot",
582
+ label="AI Meme Generator Chatbot",
583
+ visible=False,
584
+ avatar_images=[None, BOT_AVATAR],
585
+ )
586
+
587
+ with gr.Blocks(title="AI Meme Generator", theme=gr.themes.Base()) as demo:
588
+ gr.HTML("""<h1 align="center">AI Meme Generator</h1>""")
589
+ with gr.Row(variant="panel"):
590
+ with gr.Column(scale=1):
591
+ gr.Image(
592
+ IDEFICS_LOGO,
593
+ elem_id="banner-image",
594
+ show_label=False,
595
+ show_download_button=False,
596
+ height=200,
597
+ width=250,
598
+ )
599
+ with gr.Column(scale=5):
600
+ gr.HTML(
601
+ """
602
+ <p><strong>AI Meme Generator</strong> is an AI system that writes humorous content inspired by images, allowing you to make the funniest memes with little effort. Upload your image and ask the Idefics chatbot to make a tailored meme.</p>
603
+ <p>AI Meme Generator is a space inspired from <a href="https://huggingface.co/spaces/HuggingFaceM4/ai_dad_jokes">AI Dad Jokes</a> and powered by <a href="https://huggingface.co/blog/idefics">IDEFICS</a>, an open-access large visual language model developped by Hugging Face. Like GPT-4, the multimodal model accepts arbitrary sequences of image and text inputs and produces text outputs. IDEFICS can answer questions about images, describe visual content, create stories grounded in multiple images, etc.</p>
604
+
605
+ <p>⛔️ <strong>Intended uses and limitations:</strong> This demo is provided as research artifact to the community showcasing IDEFICS'capabilities. We detail misuses and out-of-scope uses <a href="https://huggingface.co/HuggingFaceM4/idefics-80b#misuse-and-out-of-scope-use">here</a>. In particular, the system should not be used to engage in harassment, abuse and bullying. The model can produce factually incorrect texts, hallucinate facts (with or without an image) and will struggle with small details in images. While the system will tend to refuse answering questionable user requests, it can produce problematic outputs (including racist, stereotypical, and disrespectful texts), in particular when prompted to do so.</p>
606
+ """
607
+ )
608
+
609
+ with gr.Row(elem_id="model_selector_row"):
610
+ model_selector = gr.Dropdown(
611
+ choices=MODELS,
612
+ value="HuggingFaceM4/idefics-80b-instruct",
613
+ interactive=True,
614
+ show_label=False,
615
+ container=False,
616
+ label="Model",
617
+ visible=False,
618
+ )
619
+
620
+ with gr.Row(equal_height=True):
621
+ with gr.Box(elem_id="gallery_box"):
622
+ gallery_type_choice = gr.Radio(
623
+ [
624
+ "All",
625
+ "Meme templates",
626
+ "Funny images",
627
+ "Politics",
628
+ ],
629
+ value="All",
630
+ label="Gallery Type",
631
+ interactive=True,
632
+ visible=False,
633
+ info="Choose the type of gallery you want to see.",
634
+ )
635
+ template_gallery = gr.Gallery(
636
+ # value= value given by gallery_type_choice,
637
+ label="Templates Gallery",
638
+ allow_preview=False,
639
+ columns=6,
640
+ elem_id="gallery",
641
+ show_share_button=False,
642
+ height=400,
643
+ )
644
+ with gr.Row(equal_height=True):
645
+ with gr.Column(equal_height=1):
646
+ imagebox = gr.Image(
647
+ type="filepath", label="Image to meme", height=400, visible=True
648
+ )
649
+ with gr.Group():
650
+ with gr.Row():
651
+ textbox.render()
652
+ with gr.Row():
653
+ submit_btn = gr.Button(value="▶️ Submit", visible=True)
654
+ clear_btn = gr.ClearButton(
655
+ [textbox, imagebox, chatbot], value="🧹 Clear"
656
+ )
657
+ regenerate_btn = gr.Button(value="🔄 Regenerate", visible=True)
658
+ upload_btn = gr.UploadButton(
659
+ "📁 Upload image", file_types=["image"], visible=False
660
+ )
661
+ with gr.Accordion(
662
+ "Advanced settings", open=False, visible=True
663
+ ) as parameter_row:
664
+ with gr.Row():
665
+ with gr.Column():
666
+ all_caps_meme_text = gr.Checkbox(
667
+ value=True,
668
+ label="All Caps",
669
+ interactive=True,
670
+ info="",
671
+ )
672
+ text_at_the_top = gr.Checkbox(
673
+ value=False,
674
+ label="Text at the top",
675
+ interactive=True,
676
+ info="",
677
+ )
678
+ with gr.Column():
679
+ font_meme_text = gr.Radio(
680
+ [
681
+ "impact",
682
+ "Roboto-Regular",
683
+ ],
684
+ value="impact",
685
+ label="Font",
686
+ interactive=True,
687
+ info="",
688
+ )
689
+ system_prompt = gr.Textbox(
690
+ value=SYSTEM_PROMPT,
691
+ visible=False,
692
+ lines=20,
693
+ max_lines=50,
694
+ interactive=True,
695
+ )
696
+ max_new_tokens = gr.Slider(
697
+ minimum=8,
698
+ maximum=150,
699
+ value=90,
700
+ step=1,
701
+ interactive=True,
702
+ label="Maximum number of new tokens to generate",
703
+ )
704
+ repetition_penalty = gr.Slider(
705
+ minimum=0.0,
706
+ maximum=5.0,
707
+ value=1.2,
708
+ step=0.01,
709
+ interactive=True,
710
+ label="Repetition penalty",
711
+ info="1.0 is equivalent to no penalty",
712
+ )
713
+ decoding_strategy = gr.Radio(
714
+ [
715
+ "Greedy",
716
+ "Top P Sampling",
717
+ ],
718
+ value="Top P Sampling",
719
+ label="Decoding strategy",
720
+ interactive=True,
721
+ info="Higher values is equivalent to sampling more low-probability tokens.",
722
+ )
723
+ temperature = gr.Slider(
724
+ minimum=0.0,
725
+ maximum=5.0,
726
+ value=0.6,
727
+ step=0.1,
728
+ interactive=True,
729
+ visible=True,
730
+ label="Sampling temperature",
731
+ info="Higher values will produce more diverse outputs.",
732
+ )
733
+ decoding_strategy.change(
734
+ fn=lambda selection: gr.Slider.update(
735
+ visible=(
736
+ selection
737
+ in [
738
+ "contrastive_sampling",
739
+ "beam_sampling",
740
+ "Top P Sampling",
741
+ "sampling_top_k",
742
+ ]
743
+ )
744
+ ),
745
+ inputs=decoding_strategy,
746
+ outputs=temperature,
747
+ )
748
+ top_p = gr.Slider(
749
+ minimum=0.01,
750
+ maximum=0.99,
751
+ value=0.8,
752
+ step=0.01,
753
+ interactive=True,
754
+ visible=True,
755
+ label="Top P",
756
+ info="Higher values is equivalent to sampling more low-probability tokens.",
757
+ )
758
+ decoding_strategy.change(
759
+ fn=lambda selection: gr.Slider.update(
760
+ visible=(selection in ["Top P Sampling"])
761
+ ),
762
+ inputs=decoding_strategy,
763
+ outputs=top_p,
764
+ )
765
+ with gr.Column(scale=2):
766
+ generated_memes_gallery = gr.Gallery(
767
+ # value="Images generated will appear here",
768
+ label="Generated Memes",
769
+ allow_preview=True,
770
+ elem_id="generated_memes_gallery",
771
+ show_download_button=True,
772
+ show_share_button=True,
773
+ ).style(columns=[2], object_fit="contain", height=600)
774
+ with gr.Row():
775
+ chatbot.render()
776
+
777
+ def model_inference(
778
+ model_selector,
779
+ system_prompt,
780
+ user_prompt_str,
781
+ chat_history,
782
+ image,
783
+ decoding_strategy,
784
+ temperature,
785
+ max_new_tokens,
786
+ repetition_penalty,
787
+ top_p,
788
+ all_caps_meme_text,
789
+ text_at_the_top,
790
+ font_meme_text,
791
+ ):
792
+ chat_history = []
793
+ if user_prompt_str.strip() == "" and image is None:
794
+ return "", None, chat_history
795
+
796
+ system_prompt = ast.literal_eval(system_prompt)
797
+ (
798
+ formated_prompt_list,
799
+ user_prompt_list,
800
+ ) = format_user_prompt_with_im_history_and_system_conditioning(
801
+ system_prompt=system_prompt,
802
+ current_user_prompt_str=user_prompt_str.strip(),
803
+ current_image=image,
804
+ history=chat_history,
805
+ )
806
+
807
+ client_endpoint = API_PATHS[model_selector]
808
+ client = Client(
809
+ base_url=client_endpoint,
810
+ headers={"x-use-cache": "0", "Authorization": f"Bearer {API_TOKEN}"},
811
+ )
812
+
813
+ # Common parameters to all decoding strategies
814
+ # This documentation is useful to read: https://huggingface.co/docs/transformers/main/en/generation_strategies
815
+ generation_args = {
816
+ "max_new_tokens": max_new_tokens,
817
+ "repetition_penalty": repetition_penalty,
818
+ "stop_sequences": EOS_STRINGS,
819
+ }
820
+
821
+ assert decoding_strategy in [
822
+ "Greedy",
823
+ "Top P Sampling",
824
+ ]
825
+ if decoding_strategy == "Greedy":
826
+ generation_args["do_sample"] = False
827
+ elif decoding_strategy == "Top P Sampling":
828
+ generation_args["temperature"] = temperature
829
+ generation_args["do_sample"] = True
830
+ generation_args["top_p"] = top_p
831
+
832
+ if image is None:
833
+ # Case where there is no image OR the image is passed as `<fake_token_around_image><image:IMAGE_URL><fake_token_around_image>`
834
+ chat_history.append([prompt_list_to_markdown(user_prompt_list), ""])
835
+ else:
836
+ # Case where the image is passed through the Image Box.
837
+ # Convert the image into base64 for both passing it through the chat history and
838
+ # displaying the image inside the same bubble as the text.
839
+ chat_history.append(
840
+ [
841
+ f"{prompt_list_to_markdown([image] + user_prompt_list)}",
842
+ "",
843
+ ]
844
+ )
845
+
846
+ query = prompt_list_to_tgi_input(formated_prompt_list)
847
+ all_meme_images = []
848
+ for i in range(4):
849
+ stream = client.generate_stream(prompt=query, **generation_args)
850
+
851
+ acc_text = ""
852
+ full_text = ""
853
+ for idx, response in enumerate(stream):
854
+ text_token = response.token.text
855
+
856
+ if response.details:
857
+ # That's the exit condition
858
+ if image is not None and full_text != "":
859
+ meme_image = make_meme_image(
860
+ image=image,
861
+ text=full_text,
862
+ font_meme_text=font_meme_text,
863
+ all_caps_meme_text=all_caps_meme_text,
864
+ text_at_the_top=text_at_the_top,
865
+ )
866
+ meme_image = pil_to_temp_file(meme_image)
867
+ all_meme_images.append(meme_image)
868
+ yield "", all_meme_images, chat_history
869
+ if i == 3:
870
+ return
871
+
872
+ if text_token in STOP_SUSPECT_LIST:
873
+ acc_text += text_token
874
+ continue
875
+
876
+ if idx == 0 and text_token.startswith(" "):
877
+ text_token = text_token.lstrip()
878
+
879
+ acc_text += text_token
880
+ # Commented to not have a chatbot history that could confuse user
881
+
882
+ # last_turn = chat_history.pop(-1)
883
+ # last_turn[-1] += acc_text
884
+ # if last_turn[-1].endswith("\nUser"):
885
+ # # Safeguard: sometimes (rarely), the model won't generate the token `<end_of_utterance>` and will go directly to generating `\nUser:`
886
+ # # It will thus stop the generation on `\nUser:`. But when it exits, it will have already generated `\nUser`
887
+ # # This post-processing ensures that we don't have an additional `\nUser` wandering around.
888
+ # last_turn[-1] = last_turn[-1][:-5]
889
+ # chat_history.append(last_turn)
890
+ # yield "", None, chat_history
891
+ full_text += acc_text
892
+ acc_text = ""
893
+
894
+ textbox.submit(
895
+ fn=model_inference,
896
+ inputs=[
897
+ model_selector,
898
+ system_prompt,
899
+ textbox,
900
+ chatbot,
901
+ imagebox,
902
+ decoding_strategy,
903
+ temperature,
904
+ max_new_tokens,
905
+ repetition_penalty,
906
+ top_p,
907
+ all_caps_meme_text,
908
+ text_at_the_top,
909
+ font_meme_text,
910
+ ],
911
+ outputs=[textbox, generated_memes_gallery, chatbot],
912
+ )
913
+ submit_btn.click(fn=lambda: "", inputs=[], outputs=[generated_memes_gallery]).then(
914
+ fn=model_inference,
915
+ inputs=[
916
+ model_selector,
917
+ system_prompt,
918
+ textbox,
919
+ chatbot,
920
+ imagebox,
921
+ decoding_strategy,
922
+ temperature,
923
+ max_new_tokens,
924
+ repetition_penalty,
925
+ top_p,
926
+ all_caps_meme_text,
927
+ text_at_the_top,
928
+ font_meme_text,
929
+ ],
930
+ outputs=[
931
+ textbox,
932
+ generated_memes_gallery,
933
+ chatbot,
934
+ ],
935
+ )
936
+
937
+ def remove_last_turn(chat_history):
938
+ if len(chat_history) == 0:
939
+ return gr.Update(), gr.Update()
940
+ last_interaction = chat_history[-1]
941
+ chat_history = chat_history[:-1]
942
+ last_interaction[0] = re.sub(r"!\[]\(/file=.*?\)", "", last_interaction[0])
943
+ chat_update = gr.update(value=chat_history)
944
+ text_update = gr.update(value=last_interaction[0])
945
+ return chat_update, text_update, ""
946
+
947
+ regenerate_btn.click(
948
+ fn=remove_last_turn,
949
+ inputs=chatbot,
950
+ outputs=[chatbot, textbox, generated_memes_gallery],
951
+ ).then(
952
+ fn=model_inference,
953
+ inputs=[
954
+ model_selector,
955
+ system_prompt,
956
+ textbox,
957
+ chatbot,
958
+ imagebox,
959
+ decoding_strategy,
960
+ temperature,
961
+ max_new_tokens,
962
+ repetition_penalty,
963
+ top_p,
964
+ all_caps_meme_text,
965
+ text_at_the_top,
966
+ font_meme_text,
967
+ ],
968
+ outputs=[
969
+ textbox,
970
+ generated_memes_gallery,
971
+ chatbot,
972
+ ],
973
+ )
974
+
975
+ upload_btn.upload(add_file, [upload_btn], [imagebox, upload_btn], queue=False)
976
+ submit_btn.click(
977
+ lambda: gr.update(label="📁 Upload image", interactive=True), [], upload_btn
978
+ )
979
+ textbox.submit(
980
+ lambda: gr.update(label="📁 Upload image", interactive=True), [], upload_btn
981
+ )
982
+ clear_btn.click(
983
+ lambda: gr.update(label="📁 Upload image", interactive=True), [], upload_btn
984
+ )
985
+ gallery_type_choice.change(
986
+ fn=choose_gallery,
987
+ inputs=[gallery_type_choice],
988
+ outputs=[template_gallery],
989
+ queue=False,
990
+ )
991
+ template_gallery.select(
992
+ fn=add_file_gallery,
993
+ inputs=[template_gallery],
994
+ outputs=[textbox, imagebox, generated_memes_gallery],
995
+ ).success(
996
+ fn=model_inference,
997
+ inputs=[
998
+ model_selector,
999
+ system_prompt,
1000
+ textbox,
1001
+ chatbot,
1002
+ imagebox,
1003
+ decoding_strategy,
1004
+ temperature,
1005
+ max_new_tokens,
1006
+ repetition_penalty,
1007
+ top_p,
1008
+ all_caps_meme_text,
1009
+ text_at_the_top,
1010
+ font_meme_text,
1011
+ ],
1012
+ outputs=[
1013
+ textbox,
1014
+ generated_memes_gallery,
1015
+ chatbot,
1016
+ ],
1017
+ )
1018
+ demo.load(
1019
+ fn=choose_gallery, inputs=[gallery_type_choice], outputs=[template_gallery]
1020
+ )
1021
+ demo.queue(concurrency_count=40, max_size=40)
1022
+ demo.launch()
fonts/Impacted.ttf ADDED
Binary file (107 kB). View file
 
fonts/Roboto-Regular.ttf ADDED
Binary file (168 kB). View file
 
fonts/impact.ttf ADDED
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requirements.txt ADDED
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+ --extra-index-url https://download.pytorch.org/whl/cu113
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+ torch
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+ transformers @ git+https://github.com/huggingface/transformers@5c67682b169576c4859700d551090ff79d450a9a
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+ requests
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+ pillow
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+ torchvision
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+ PyYAML
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+ opencv-python
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+ numpy
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+ accelerate
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+ joblib
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+ deepspeed
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+ parameterized
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+ einops
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+ pynvml
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+ sentencepiece
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+ text_generation
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+ gradio-client @ git+https://github.com/gradio-app/gradio@bd4570ed4343f75a7ae335ef06d5eb313d107bc9#subdirectory=client/python
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+ https://gradio-main-build.s3.amazonaws.com/92282cea6afdf7e9930ece1046d8a63be34b3cea/gradio-3.40.1-py3-none-any.whl