Spaces:
Running
Running
File size: 11,314 Bytes
1be431a eb8fa16 f45e494 45d10c4 c0a6bc9 398f756 45d10c4 2333c59 9df8406 1be431a 2333c59 1be431a 2333c59 9df8406 c0a6bc9 9df8406 f45e494 45d10c4 f1ef701 eb8fa16 09f0b85 fffd7f2 1be431a 6d6d84c 1be431a 2333c59 1be431a 9c75413 1be431a c38b78d c0a6bc9 6d6d84c 1be431a 9c75413 1be431a 8dcf476 45d10c4 eb8fa16 d53b62d 1be431a fe15d80 d176253 1be431a eb8fa16 1be431a 9ea96b4 1be431a 4ffd446 fe15d80 4ffd446 fe15d80 16a43bc 164a7aa f45e494 79b97e2 f45e494 075be7c 1be431a fe15d80 f1ef701 09f0b85 f1ef701 fe15d80 f45e494 1be431a fe15d80 9c75413 23ec282 9c75413 23ec282 9c75413 6d6d84c d176253 6d6d84c 8dcf476 d53b62d 9df8406 d53b62d 398f756 9df8406 398f756 6d6d84c 1be431a fe15d80 1be431a b373c49 1be431a 9df8406 09f0b85 dee0f90 d53b62d dee0f90 3c8629c b373c49 9df8406 1be431a 16a43bc 1be431a c0a6bc9 42f39c4 c0a6bc9 1be431a d176253 fe15d80 8125190 d176253 16a43bc 1be431a 6d6d84c 1be431a 2333c59 1be431a 9c75413 1be431a 09f0b85 1be431a 8dcf476 fe15d80 1be431a f45e494 09f0b85 1be431a d53b62d f45e494 d53b62d 1be431a c0a6bc9 1be431a 6d6d84c 1be431a 9c75413 1be431a d176253 f45e494 d176253 9df8406 f45e494 9df8406 398f756 9df8406 f45e494 9df8406 1be431a b373c49 23ec282 80f1bd8 23ec282 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 |
import gradio as gr
import numpy as np
from datetime import date
from predictors import predict_bc_scores, predict_mc_scores
from predictors import update,update_main, correct_text, split_text
from analysis import depth_analysis
from predictors import predict_quillbot
from plagiarism import plagiarism_check, build_date, html_highlight
from highlighter import analyze_and_highlight
from utils import extract_text_from_pdf, len_validator
import yaml
from functools import partial
np.set_printoptions(suppress=True)
with open("config.yaml", "r") as file:
params = yaml.safe_load(file)
model_list = params["MC_OUTPUT_LABELS"]
analyze_and_highlight_bc = partial(analyze_and_highlight, model_type="bc")
analyze_and_highlight_quillbot = partial(
analyze_and_highlight, model_type="quillbot"
)
def ai_generated_test(option, bias_buster_selected, input, models):
if bias_buster_selected:
input = update(input)
if option == "Human vs AI":
return predict_bc_scores(input), None
elif option == "Human vs AI Source Models":
return predict_bc_scores(input), predict_mc_scores(input, models)
return None, None
# COMBINED
def main(
ai_option,
plag_option,
input,
models,
year_from,
month_from,
day_from,
year_to,
month_to,
day_to,
domains_to_skip,
source_block_size,
):
# formatted_tokens = plagiarism_check(
# plag_option,
# input,
# year_from,
# month_from,
# day_from,
# year_to,
# month_to,
# day_to,
# domains_to_skip,
# )
formatted_tokens = html_highlight(
plag_option,
input,
year_from,
month_from,
day_from,
year_to,
month_to,
day_to,
domains_to_skip,
source_block_size,
)
depth_analysis_plot = depth_analysis(input)
bc_score = predict_bc_scores(input)
mc_score = predict_mc_scores(input, models)
quilscore = predict_quillbot(input)
return (
bc_score,
mc_score,
formatted_tokens,
depth_analysis_plot,
quilscore,
)
# START OF GRADIO
title = "AI Detection and Source Analysis"
months = {
"January": "01",
"February": "02",
"March": "03",
"April": "04",
"May": "05",
"June": "06",
"July": "07",
"August": "08",
"September": "09",
"October": "10",
"November": "11",
"December": "12",
}
with gr.Blocks() as demo:
today = date.today()
# dd/mm/YY
d1 = today.strftime("%d/%B/%Y")
d1 = d1.split("/")
domain_list = ["com", "org", "net", "int", "edu", "gov", "mil"]
gr.Markdown(
"""
# AI Detection and Source Analysis
"""
)
with gr.Row():
input_text = gr.Textbox(label="Input text", lines=6, placeholder="")
file_input = gr.File(label="Upload PDF")
file_input.change(
fn=extract_text_from_pdf, inputs=file_input, outputs=input_text
)
char_count = gr.Textbox(label="Minumum Character Limit Check")
input_text.change(fn=len_validator, inputs=input_text, outputs=char_count)
with gr.Row():
btn = gr.Button("Bias Buster")
out = gr.Textbox(label="Bias Corrected Full Input", interactive=False)
corrections_output = gr.Textbox(label="Bias Corrections", interactive=False)
btn.click(fn=update_main, inputs=input_text, outputs=[out, corrections_output])
with gr.Row():
models = gr.Dropdown(
model_list,
value=model_list,
multiselect=True,
label="Models to test against",
)
with gr.Row():
with gr.Column():
ai_option = gr.Radio(
[
"Human vs AI",
"Human vs AI Source Models",
# "Human vs AI Source Models (1 on 1)",
],
label="Choose an option please.",
)
with gr.Column():
bias_buster_selected = gr.Checkbox(label="Bias Remover")
with gr.Column():
plag_option = gr.Radio(
["Standard", "Advanced"], label="Choose an option please."
)
with gr.Row():
source_block_size = gr.Dropdown(
choices=["Sentence", "Paragraph"],
label="Source Check Granularity",
value="Sentence",
interactive=True,
)
with gr.Row():
with gr.Column():
only_ai_btn = gr.Button("AI Check")
with gr.Column():
only_plagiarism_btn = gr.Button("Source Check")
with gr.Column():
quillbot_check = gr.Button("Humanized Text Check")
with gr.Row():
with gr.Column():
bc_highlighter_button = gr.Button("Human vs. AI Highlighter")
with gr.Column():
quillbot_highlighter_button = gr.Button("Humanized Highlighter")
with gr.Row():
depth_analysis_btn = gr.Button("Detailed Writing Analysis")
with gr.Row():
full_check_btn = gr.Button("Full Check")
gr.Markdown(
"""
## Output
"""
)
with gr.Row():
with gr.Column():
bcLabel = gr.Label(label="Source")
with gr.Column():
mcLabel = gr.Label(label="Creator")
with gr.Row():
with gr.Column():
bc_highlighter_output = gr.HTML(label="Human vs. AI Highlighter")
# with gr.Column():
# mc1on1Label = gr.Label(label="Creator(1 on 1 Approach)")
with gr.Row():
with gr.Column():
QLabel = gr.Label(label="Humanized")
with gr.Row():
quillbot_highlighter_output = gr.HTML(label="Humanized Highlighter")
with gr.Group():
with gr.Row():
month_from = gr.Dropdown(
choices=months,
label="From Month",
value="January",
interactive=True,
)
day_from = gr.Textbox(label="From Day", value="01")
year_from = gr.Textbox(label="From Year", value="2000")
# from_date_button = gr.Button("Submit")
with gr.Row():
month_to = gr.Dropdown(
choices=months,
label="To Month",
value=d1[1],
interactive=True,
)
day_to = gr.Textbox(label="To Day", value=d1[0])
year_to = gr.Textbox(label="To Year", value=d1[2])
# to_date_button = gr.Button("Submit")
with gr.Row():
domains_to_skip = gr.Dropdown(
domain_list,
multiselect=True,
label="Domain To Skip",
)
with gr.Row():
with gr.Column():
sentenceBreakdown = gr.HTML(
label="Source Detection Sentence Breakdown",
value="Source Detection Sentence Breakdown",
)
with gr.Row():
with gr.Column():
writing_analysis_plot = gr.Plot(label="Writing Analysis Plot")
with gr.Column():
interpretation = """
<h2>Writing Analysis Interpretation</h2>
<ul>
<li><b>Lexical Diversity</b>: This feature measures the range of unique words used in a text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Vocabulary Level</b>: This feature assesses the complexity of the words used in a text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Unique Words</b>: This feature counts the number of words that appear only once within the text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Determiner Use</b>: This feature tracks the frequency of articles and quantifiers in the text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Punctuation Variety</b>: This feature indicates the diversity of punctuation marks used in the text.
<ul>
<li>👤 Higher tends to be Human.</li>
</ul>
</li>
<li><b>Sentence Depth</b>: This feature evaluates the complexity of the sentence structures used in the text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Vocabulary Stability</b>: This feature measures the consistency of vocabulary use throughout the text.
<ul>
<li>🤖 Higher tends to be AI.</li>
</ul>
</li>
<li><b>Entity Ratio</b>: This feature calculates the proportion of named entities, such as names and places, within the text.
<ul>
<li>👤 Higher tends to be Human.</li>
</ul>
</li>
<li><b>Perplexity</b>: This feature assesses the predictability of the text based on the sequence of words.
<ul>
<li>👤 Higher tends to be Human.</li>
</ul>
</li>
</ul>
"""
gr.HTML(interpretation, label="Interpretation of Writing Analysis")
full_check_btn.click(
fn=main,
inputs=[
ai_option,
plag_option,
input_text,
models,
year_from,
month_from,
day_from,
year_to,
month_to,
day_to,
domains_to_skip,
source_block_size,
],
outputs=[
bcLabel,
mcLabel,
# mc1on1Label,
sentenceBreakdown,
writing_analysis_plot,
QLabel,
],
api_name="main",
)
only_ai_btn.click(
fn=ai_generated_test,
inputs=[ai_option, bias_buster_selected, input_text, models],
# outputs=[bcLabel, mcLabel, mc1on1Label],
outputs=[bcLabel, mcLabel],
api_name="ai_check",
)
quillbot_check.click(
fn=predict_quillbot,
inputs=[input_text, bias_buster_selected],
outputs=[QLabel],
api_name="quillbot_check",
)
only_plagiarism_btn.click(
# fn=plagiarism_check,
fn=html_highlight,
inputs=[
plag_option,
input_text,
year_from,
month_from,
day_from,
year_to,
month_to,
day_to,
domains_to_skip,
source_block_size,
],
outputs=[
sentenceBreakdown,
],
api_name="plagiarism_check",
)
depth_analysis_btn.click(
fn=depth_analysis,
inputs=[bias_buster_selected, input_text],
outputs=[writing_analysis_plot],
api_name="depth_analysis",
)
quillbot_highlighter_button.click(
fn=analyze_and_highlight_quillbot,
inputs=[input_text, bias_buster_selected],
outputs=[quillbot_highlighter_output],
api_name="humanized_highlighter",
)
bc_highlighter_button.click(
fn=analyze_and_highlight_bc,
inputs=[input_text, bias_buster_selected],
outputs=[bc_highlighter_output],
api_name="bc_highlighter",
)
date_from = ""
date_to = ""
if __name__ == "__main__":
demo.launch(
share=True, server_name="0.0.0.0", server_port=80, auth=("polygraf-admin", "test@aisd")
)
|