File size: 66,351 Bytes
a963d65 7d76d0d a963d65 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467 1468 1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 |
import gradio as gr
import pandas as pd
import time
import threading
import asyncio
import sys
import os
import datetime
from src.heavy_workload_demo import ModalContainerScalingDemo, RealTimeBatchProcessor
# Import dashboard functions from app.py to ensure proper integration
sys.path.append(os.path.dirname(__file__))
# Use dynamic import to avoid circular dependency issues
dashboard_state = None
add_file_to_dashboard = None
get_dashboard_status = None
get_processing_queue = None
get_dashboard_metrics = None
get_jobs_history = None
def _ensure_app_imports():
"""Dynamically import app functions to avoid circular dependencies"""
global dashboard_state, add_file_to_dashboard, get_dashboard_status
global get_processing_queue, get_dashboard_metrics, get_jobs_history
if dashboard_state is None:
try:
from app import (
dashboard_state as _dashboard_state,
add_file_to_dashboard as _add_file_to_dashboard,
get_dashboard_status as _get_dashboard_status,
get_processing_queue as _get_processing_queue,
get_dashboard_metrics as _get_dashboard_metrics,
get_jobs_history as _get_jobs_history
)
dashboard_state = _dashboard_state
add_file_to_dashboard = _add_file_to_dashboard
get_dashboard_status = _get_dashboard_status
get_processing_queue = _get_processing_queue
get_dashboard_metrics = _get_dashboard_metrics
get_jobs_history = _get_jobs_history
except ImportError as e:
print(f"Warning: Could not import dashboard functions: {e}")
# Set fallback functions that return empty data
dashboard_state = {"active_tasks": 0, "total_files": 0}
add_file_to_dashboard = lambda *args, **kwargs: None
get_dashboard_status = lambda: "📊 Dashboard not available"
get_processing_queue = lambda: [["Status", "Not Available"]]
get_dashboard_metrics = lambda: [["Metric", "Not Available"]]
get_jobs_history = lambda: []
# Initialize demo components
heavy_workload_demo = ModalContainerScalingDemo()
batch_processor = RealTimeBatchProcessor()
# Global reference to dashboard function (set by create_medical_ui)
_add_file_to_dashboard = None
def is_modal_available():
"""Check if Modal environment is available"""
try:
import modal
return True
except ImportError:
return False
def get_environment_name():
"""Get current deployment environment name"""
if is_modal_available():
return "Modal Cloud"
else:
return "Local/HuggingFace"
def create_text_processing_tab(process_text_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics):
"""Create the text processing tab"""
with gr.Tab("📝 Text Processing"):
gr.Markdown("### Medical Text Analysis")
gr.Markdown("Process medical text directly with entity extraction and FHIR generation")
with gr.Row():
with gr.Column():
gr.Markdown("### Medical Text Input")
text_input = gr.Textbox(
label="Medical Text",
placeholder="Enter medical text here...",
lines=8
)
enable_fhir_text = gr.Checkbox(
label="Generate FHIR Resources",
value=False
)
with gr.Row():
process_text_btn = gr.Button("🔍 Process Text", variant="primary")
cancel_text_btn = gr.Button("❌ Cancel", variant="secondary", visible=False)
with gr.Column():
gr.Markdown("### Results")
text_status = gr.HTML(value="🔄 Ready to process")
with gr.Accordion("🔍 Entities", open=True):
extracted_entities = gr.JSON(label="Entities")
with gr.Accordion("🏥 FHIR", open=True):
fhir_resources = gr.JSON(label="FHIR Data")
return {
"text_input": text_input,
"enable_fhir_text": enable_fhir_text,
"process_text_btn": process_text_btn,
"cancel_text_btn": cancel_text_btn,
"text_status": text_status,
"extracted_entities": extracted_entities,
"fhir_resources": fhir_resources
}
def create_document_upload_tab(process_file_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics):
"""Create the document upload tab"""
with gr.Tab("📄 Document Upload"):
gr.Markdown("### Document Processing")
gr.Markdown("Upload and process medical documents with comprehensive analysis")
gr.Markdown("**Supported formats:** PDF, DOCX, DOC, TXT, JPG, JPEG, PNG, GIF, BMP, WEBP, TIFF")
with gr.Row():
with gr.Column():
gr.Markdown("### Document Upload")
file_input = gr.File(
label="Upload Medical Document",
file_types=[".pdf", ".docx", ".doc", ".txt", ".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp", ".tiff", ".tif"]
)
enable_mistral_ocr = gr.Checkbox(
label="🔍 Enable Mistral OCR (Advanced OCR for Images/PDFs)",
value=True,
info="Uses Mistral API for enhanced OCR processing of images and scanned documents"
)
enable_fhir_file = gr.Checkbox(
label="Generate FHIR Resources",
value=False
)
with gr.Row():
process_file_btn = gr.Button("📄 Process File", variant="primary")
cancel_file_btn = gr.Button("❌ Cancel", variant="secondary", visible=False)
with gr.Column():
gr.Markdown("### Results")
file_status = gr.HTML(value="Ready to process documents")
with gr.Accordion("🔍 Entities", open=True):
file_entities = gr.JSON(label="Entities")
with gr.Accordion("🏥 FHIR", open=True):
file_fhir = gr.JSON(label="FHIR Data")
return {
"file_input": file_input,
"enable_mistral_ocr": enable_mistral_ocr,
"enable_fhir_file": enable_fhir_file,
"process_file_btn": process_file_btn,
"cancel_file_btn": cancel_file_btn,
"file_status": file_status,
"file_entities": file_entities,
"file_fhir": file_fhir
}
def create_dicom_processing_tab(process_dicom_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics):
"""Create the DICOM processing tab"""
with gr.Tab("🏥 DICOM Processing"):
gr.Markdown("### Medical Imaging Analysis")
gr.Markdown("Process DICOM files for medical imaging analysis and metadata extraction")
with gr.Row():
with gr.Column():
gr.Markdown("### DICOM Upload")
dicom_input = gr.File(
label="Upload DICOM File",
file_types=[".dcm", ".dicom"]
)
with gr.Row():
process_dicom_btn = gr.Button("🏥 Process DICOM", variant="primary")
cancel_dicom_btn = gr.Button("❌ Cancel", variant="secondary", visible=False)
with gr.Column():
gr.Markdown("### Results")
dicom_status = gr.HTML(value="Ready to process DICOM files")
with gr.Accordion("📊 DICOM Analysis", open=False):
dicom_analysis = gr.JSON(label="DICOM Metadata & Analysis")
with gr.Accordion("🏥 FHIR Imaging", open=True):
dicom_fhir = gr.JSON(label="FHIR ImagingStudy")
return {
"dicom_input": dicom_input,
"process_dicom_btn": process_dicom_btn,
"cancel_dicom_btn": cancel_dicom_btn,
"dicom_status": dicom_status,
"dicom_analysis": dicom_analysis,
"dicom_fhir": dicom_fhir
}
def create_heavy_workload_tab():
"""Create the heavy workload demo tab"""
with gr.Tab("🚀 Heavy Workload Demo"):
if is_modal_available():
# Demo title
gr.Markdown("## 🚀 FhirFlame Modal Container Auto-Scaling Demo")
gr.Markdown(f"**Environment:** {get_environment_name()}")
gr.Markdown("This demo showcases automatic horizontal scaling of containers based on workload.")
# Demo controls
with gr.Row():
with gr.Column():
gr.Markdown("### Demo Controls")
container_table = gr.Dataframe(
headers=["Container ID", "Region", "Status", "Requests/sec", "Queue", "Processed", "Entities", "FHIR", "Uptime"],
datatype=["str", "str", "str", "str", "number", "number", "number", "number", "str"],
label="📊 Active Containers",
interactive=False
)
with gr.Row():
start_demo_btn = gr.Button("🚀 Start Modal Container Scaling", variant="primary")
stop_demo_btn = gr.Button("⏹️ Stop Demo", variant="secondary", visible=False)
refresh_btn = gr.Button("🔄 Refresh", variant="secondary")
with gr.Column():
gr.Markdown("### Scaling Metrics")
scaling_metrics = gr.Dataframe(
headers=["Metric", "Value"],
label="📈 Scaling Status",
interactive=False
)
workload_chart = gr.Plot(label="📊 Workload & Scaling Chart")
# Event handlers with button state management
def start_demo_with_state():
result = start_heavy_workload()
return result + (gr.update(visible=True),) # Show stop button
def stop_demo_with_state():
result = stop_heavy_workload()
return result + (gr.update(visible=False),) # Hide stop button
start_demo_btn.click(
fn=start_demo_with_state,
outputs=[container_table, scaling_metrics, workload_chart, stop_demo_btn]
)
stop_demo_btn.click(
fn=stop_demo_with_state,
outputs=[container_table, scaling_metrics, workload_chart, stop_demo_btn]
)
refresh_btn.click(
fn=refresh_demo_data,
outputs=[container_table, scaling_metrics, workload_chart]
)
else:
gr.Markdown("## ⚠️ Modal Environment Not Available")
gr.Markdown("This demo requires Modal cloud environment to showcase container scaling.")
gr.Markdown("Currently running in: **Local/HuggingFace Environment**")
# Show static placeholder
placeholder_data = [
["container-1", "us-east", "Simulated", "45", 12, 234, 1890, 45, "2h 34m"],
["container-2", "us-west", "Simulated", "67", 8, 456, 3245, 89, "1h 12m"],
["container-3", "eu-west", "Simulated", "23", 3, 123, 987, 23, "45m"]
]
gr.Dataframe(
value=placeholder_data,
headers=["Container ID", "Region", "Status", "Requests/sec", "Queue", "Processed", "Entities", "FHIR", "Uptime"],
label="📊 Demo Container Data (Simulated)",
interactive=False
)
def create_system_stats_tab(get_simple_agent_status):
"""Create the system stats tab"""
with gr.Tab("📊 System Dashboard"):
gr.Markdown("## System Status & Metrics")
gr.Markdown("*Updates when tasks complete or fail*")
with gr.Row():
with gr.Column():
gr.Markdown("### 🖥️ System Status")
agent_status_display = gr.HTML(
value=get_simple_agent_status()
)
with gr.Row():
refresh_status_btn = gr.Button("🔄 Refresh Status", variant="secondary")
last_updated_display = gr.HTML(
value="<p><small>Last updated: Never</small></p>"
)
with gr.Column():
gr.Markdown("### 📁 File Processing Dashboard")
processing_status = gr.HTML(
value="<p>📊 No files processed yet</p>"
)
metrics_display = gr.DataFrame(
value=[["Total Files", 0], ["Success Rate", "0%"], ["Last Update", "None"]],
headers=["Metric", "Value"],
label="📊Metrics",
interactive=False
)
# Add processed jobs history
gr.Markdown("### 📋 Recent Processing Jobs")
jobs_history_display = gr.DataFrame(
value=[],
headers=["Job Name", "Category", "Status", "Processing Time"],
label="⚙️Processing Jobs History",
interactive=False,
column_widths=["50%", "20%", "15%", "15%"]
)
# Add database management section
gr.Markdown("### 🗂️ Database Management")
with gr.Row():
clear_db_btn = gr.Button("🗑️ Clear Database", variant="secondary", size="sm")
clear_status = gr.Markdown("", visible=False)
def clear_database():
try:
# Import database functions
from database import clear_all_jobs
clear_all_jobs()
return gr.update(value="✅ Database cleared successfully!", visible=True)
except Exception as e:
return gr.update(value=f"❌ Error clearing database: {e}", visible=True)
clear_db_btn.click(
fn=clear_database,
outputs=clear_status
)
return {
"agent_status_display": agent_status_display,
"refresh_status_btn": refresh_status_btn,
"last_updated_display": last_updated_display,
"processing_status": processing_status,
"metrics_display": metrics_display,
"files_history": jobs_history_display
}
def create_medical_ui(process_text_only, process_file_only, process_dicom_only,
cancel_current_task, get_dashboard_status, dashboard_state,
get_dashboard_metrics, get_simple_agent_status,
get_enhanced_codellama, add_file_to_dashboard):
"""Create the main medical interface with all tabs"""
global _add_file_to_dashboard
_add_file_to_dashboard = add_file_to_dashboard
# Clean, organized CSS for FhirFlame branding
logo_css = """
<style>
/* ====== LOGO STYLING ====== */
.fhirflame-logo-zero-padding img {
width: 100% !important;
height: 100% !important;
object-fit: contain !important;
padding: 0 !important;
margin: 0 !important;
display: block !important;
}
.fhirflame-subtitle {
color: var(--body-text-color-subdued, #474747);
font-size: 16px;
font-weight: normal;
line-height: 1.5;
text-align: left;
max-width: 800px;
margin: 0;
padding: 0;
display: block;
}
.fhirflame-mvp-text {
color: var(--body-text-color) !important;
opacity: 0.7 !important;
font-weight: 500 !important;
}
/* ====== BRAND COLORS ====== */
/* Primary buttons - red */
button[data-variant="primary"],
.gr-button[data-variant="primary"],
.gr-button-primary,
.primary {
background: #B71C1C !important;
border-color: #B71C1C !important;
}
button[data-variant="primary"]:hover,
.gr-button[data-variant="primary"]:hover,
.gr-button-primary:hover {
background: #9B1B1B !important;
border-color: #9B1B1B !important;
}
/* Selected tabs - red with BLACK underlines */
.gr-tab-nav button.selected,
button[role="tab"][aria-selected="true"],
.gr-tabs button.selected,
.gr-tabs .gr-tab-nav button[aria-selected="true"] {
background: #B71C1C !important;
border-color: #B71C1C !important;
color: white !important;
border-bottom: 3px solid #000000 !important;
}
/* Tab underlines and borders - BLACK */
.gr-tab-nav button.selected::after,
.gr-tab-nav button:focus::after,
.gr-tab-nav button:active::after,
button[role="tab"][aria-selected="true"]::after,
.gr-tabs button.selected::after,
.gr-tabs button:hover::after,
.gr-tabs button:focus::after,
.gr-tabs button:active::after {
background: #000000 !important;
border-color: #000000 !important;
border-bottom-color: #000000 !important;
}
/* Tab containers and nav */
.gr-tab-nav,
.gr-tabs {
border-bottom: 1px solid #000000 !important;
}
/* Checkboxes - red */
input[type="checkbox"]:checked,
.gr-checkbox input:checked {
background-color: #B71C1C !important;
border-color: #B71C1C !important;
accent-color: #B71C1C !important;
}
/* Progress bars - red */
.progress-bar,
.gr-progress,
[role="progressbar"] {
background-color: #B71C1C !important;
}
/* Links - red */
a {
color: #B71C1C !important;
}
a:hover {
color: #9B1B1B !important;
}
/* ====== SLIDERS - BLACK ULTRA AGGRESSIVE ====== */
input[type="range"],
.gr-slider input[type="range"],
.gradio-container input[type="range"],
div input[type="range"],
span input[type="range"],
* input[type="range"] {
accent-color: #000000 !important;
background: transparent !important;
}
input[type="range"]::-webkit-slider-thumb,
.gr-slider input[type="range"]::-webkit-slider-thumb,
.gradio-container input[type="range"]::-webkit-slider-thumb {
background: #000000 !important;
border-color: #000000 !important;
color: #000000 !important;
}
input[type="range"]::-moz-range-thumb,
.gr-slider input[type="range"]::-moz-range-thumb,
.gradio-container input[type="range"]::-moz-range-thumb {
background: #000000 !important;
border-color: #000000 !important;
color: #000000 !important;
}
input[type="range"]::-webkit-slider-runnable-track,
input[type="range"]::-moz-range-track {
background: linear-gradient(to right, #000000 0%, #000000 var(--value, 50%), #e0e0e0 var(--value, 50%), #e0e0e0 100%) !important;
}
/* Force all slider containers to use black */
.gr-block input[type="range"],
.gr-form input[type="range"],
div[data-testid*="slider"] input[type="range"],
div[data-testid*="range"] input[type="range"] {
accent-color: #000000 !important;
}
/* ====== PREVENT BLACK BACKGROUNDS ON TEXT ====== */
label,
.gr-label,
.gr-markdown,
.gr-text,
span,
div:not(.gr-button):not([role="button"]) {
background: transparent !important;
}
/* ====== THEME ADAPTATION ====== */
.gr-form,
.gr-block,
.gradio-container {
background: var(--background-fill-primary) !important;
color: var(--body-text-color) !important;
}
.gr-markdown h1, .gr-markdown h2, .gr-markdown h3, .gr-markdown h4, .gr-markdown h5, .gr-markdown h6 {
color: var(--body-text-color) !important;
}
.gr-markdown p, .gr-markdown span, .gr-markdown div {
color: var(--body-text-color-subdued) !important;
}
/* ====== OVERRIDE ORANGE - NUCLEAR OPTION ====== */
/* Override CSS variables */
:root {
--slider-color: #000000 !important;
--accent-color: #000000 !important;
--primary-hue: 0 !important;
--primary-sat: 100% !important;
--primary-lit: 27% !important;
--color-orange: #000000 !important;
--primary-500: #B71C1C !important;
--primary-600: #B71C1C !important;
}
/* Target ALL orange styles - BLACK in light mode, RED in dark mode */
*[style*="rgb(255, 165, 0)"],
*[style*="rgb(255,165,0)"],
*[style*="#ff8c00"],
*[style*="#ffa500"],
*[style*="orange"],
*[style*="hsl(39"],
*[style*="hsl(38"],
*[style*="hsl(40"],
*[class*="orange"],
.orange,
[data-color="orange"] {
background-color: #000000 !important;
color: #000000 !important;
border-color: #000000 !important;
accent-color: #000000 !important;
}
/* Dark mode: Orange elements should be RED */
@media (prefers-color-scheme: dark) {
*[style*="rgb(255, 165, 0)"],
*[style*="rgb(255,165,0)"],
*[style*="#ff8c00"],
*[style*="#ffa500"],
*[style*="orange"],
*[style*="hsl(39"],
*[style*="hsl(38"],
*[style*="hsl(40"],
*[class*="orange"],
.orange,
[data-color="orange"] {
background-color: #B71C1C !important;
color: #B71C1C !important;
border-color: #B71C1C !important;
accent-color: #B71C1C !important;
}
}
/* Also handle Gradio's dark theme class */
.dark *[style*="rgb(255, 165, 0)"],
.dark *[style*="rgb(255,165,0)"],
.dark *[style*="#ff8c00"],
.dark *[style*="#ffa500"],
.dark *[style*="orange"],
.dark *[style*="hsl(39"],
.dark *[style*="hsl(38"],
.dark *[style*="hsl(40"],
.dark *[class*="orange"],
.dark .orange,
.dark [data-color="orange"] {
background-color: #B71C1C !important;
color: #B71C1C !important;
border-color: #B71C1C !important;
accent-color: #B71C1C !important;
}
/* Slider-specific orange override */
*[style*="rgb(255, 165, 0)"] input[type="range"],
*[style*="orange"] input[type="range"],
input[type="range"][style*="orange"],
input[type="range"][style*="rgb(255, 165, 0)"] {
accent-color: #000000 !important;
}
/* Dark mode: Slider-specific orange override */
@media (prefers-color-scheme: dark) {
*[style*="rgb(255, 165, 0)"] input[type="range"],
*[style*="orange"] input[type="range"],
input[type="range"][style*="orange"],
input[type="range"][style*="rgb(255, 165, 0)"] {
accent-color: #B71C1C !important;
}
}
/* Also handle Gradio's dark theme class for sliders */
.dark *[style*="rgb(255, 165, 0)"] input[type="range"],
.dark *[style*="orange"] input[type="range"],
.dark input[type="range"][style*="orange"],
.dark input[type="range"][style*="rgb(255, 165, 0)"] {
accent-color: #B71C1C !important;
}
/* Orange elements to red for buttons only */
button[style*="orange"],
.gr-button[style*="orange"],
button[style*="rgb(255, 165, 0)"],
.gr-button[style*="rgb(255, 165, 0)"] {
background-color: #B71C1C !important;
border-color: #B71C1C !important;
}
/* Force black on ALL accent colors */
* {
accent-color: #000000 !important;
}
/* But allow red for buttons */
button, .gr-button, [role="button"] {
accent-color: #B71C1C !important;
}
/* Fix Gradio settings modal alignment issues */
.gradio-container .settings-panel,
.gradio-container .modal,
.gradio-container .sidebar {
position: fixed !important;
top: 0 !important;
left: auto !important;
right: 0 !important;
z-index: 9999 !important;
background: white !important;
border: 1px solid #ccc !important;
box-shadow: 0 4px 6px rgba(0,0,0,0.1) !important;
padding: 20px !important;
width: 400px !important;
max-height: 90vh !important;
overflow-y: auto !important;
font-family: Arial, sans-serif !important;
border-radius: 8px !important;
}
</style>
"""
with gr.Blocks(title="FhirFlame: Real-Time Medical AI Processing & FHIR Generation", css=logo_css) as demo:
# FhirFlame Official Logo Header - Using exact-sized SVG (450×150px)
gr.Image(
value="fhirflame_logo_450x150.svg",
type="filepath",
height="105px",
width="315px",
show_label=False,
show_download_button=False,
show_fullscreen_button=False,
show_share_button=False,
container=False,
interactive=False,
elem_classes=["fhirflame-logo-zero-padding"]
)
# Subtitle below logo
gr.HTML(f"""
<div class="fhirflame-subtitle">
<strong>Medical AI System Demonstration</strong><br>
<strong>Dockerized Healthcare AI Platform: Local/Cloud/Hybrid Deployment + Agent/MCP Server + FHIR R4/R5 + DICOM Processing + CodeLlama Integration</strong><br>
<span class="fhirflame-mvp-text">🚧 MVP/Prototype | Hackathon Submission</span>
</div>
""")
# Main tab container - all tabs at the same level
with gr.Tabs():
# Create all main tabs
text_components = create_text_processing_tab(
process_text_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics
)
file_components = create_document_upload_tab(
process_file_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics
)
dicom_components = create_dicom_processing_tab(
process_dicom_only, cancel_current_task, get_dashboard_status,
dashboard_state, get_dashboard_metrics
)
# Heavy Workload Demo Tab
create_heavy_workload_tab()
# Batch Processing Demo Tab - Need to create dashboard components first
with gr.Tab("🔄 Batch Processing Demo"):
# Dashboard function is already set globally in create_medical_ui
gr.Markdown("## 🔄 Real-Time Medical Batch Processing")
gr.Markdown("Demonstrates live batch processing of sample medical documents with real-time progress tracking (no OCR required)")
with gr.Row():
with gr.Column():
gr.Markdown("### Batch Configuration")
batch_size = gr.Slider(
minimum=5,
maximum=50,
step=5,
value=10,
label="Batch Size"
)
processing_type = gr.Radio(
choices=["Clinical Notes Sample", "Lab Reports Sample", "Discharge Summaries Sample"],
value="Clinical Notes Sample",
label="Sample File Category"
)
enable_live_updates = gr.Checkbox(
value=True,
label="Live Progress Updates"
)
with gr.Row():
start_demo_btn = gr.Button("🚀 Start Live Processing", variant="primary")
stop_demo_btn = gr.Button("⏹️ Stop Processing", visible=False)
with gr.Column():
gr.Markdown("### Live Progress")
batch_status = gr.Markdown("🔄 Ready to start batch processing")
processing_log = gr.Textbox(
label="Processing Log",
lines=8,
interactive=False
)
results_summary = gr.JSON(
label="Results Summary",
value=create_empty_results_summary()
)
# Timer for real-time updates
status_timer = gr.Timer(value=1.0, active=False)
# Connect event handlers with button state management
def start_processing_with_timer(batch_size, processing_type, enable_live_updates):
result = start_live_processing(batch_size, processing_type, enable_live_updates)
# Get dashboard updates
# Activate timer for real-time updates
return result + (gr.update(visible=True), gr.Timer(active=True),
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [])
def stop_processing_with_timer():
result = stop_processing()
# Get dashboard updates
# Deactivate timer when processing stops
return result + (gr.update(visible=False), gr.Timer(active=False),
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [])
# System Dashboard Tab - at the far right (after Batch Processing)
stats_components = create_system_stats_tab(get_simple_agent_status)
# Get processing queue and metrics from stats for batch processing integration
processing_status = stats_components["processing_status"]
metrics_display = stats_components["metrics_display"]
# Connect batch processing timer and buttons
files_history_component = stats_components["files_history"]
status_timer.tick(
fn=update_batch_status_realtime,
outputs=[batch_status, processing_log, results_summary,
processing_status, metrics_display,
files_history_component]
)
start_demo_btn.click(
fn=start_processing_with_timer,
inputs=[batch_size, processing_type, enable_live_updates],
outputs=[batch_status, processing_log, results_summary, stop_demo_btn, status_timer,
processing_status, metrics_display]
)
stop_demo_btn.click(
fn=stop_processing_with_timer,
outputs=[batch_status, processing_log, stop_demo_btn, status_timer,
processing_status, metrics_display]
)
# Enhanced event handlers with button state management
def process_text_with_state(text_input, enable_fhir):
# Ensure dashboard functions are available
_ensure_app_imports()
# Get core processing results (3 values)
status, entities, fhir_resources = process_text_only(text_input, enable_fhir)
# Return 7 values expected by Gradio outputs
return (
status, entities, fhir_resources, # Core results (3)
get_dashboard_status(), # Dashboard status (1)
get_dashboard_metrics(), # Dashboard metrics (1)
get_jobs_history(), # Jobs history (1)
gr.update(visible=True) # Cancel button state (1)
)
def process_file_with_state(file_input, enable_mistral_ocr, enable_fhir):
# Ensure dashboard functions are available
_ensure_app_imports()
# Get core processing results (3 values) - pass mistral_ocr parameter
status, entities, fhir_resources = process_file_only(file_input, enable_mistral_ocr, enable_fhir)
# Return 7 values expected by Gradio outputs
return (
status, entities, fhir_resources, # Core results (3)
get_dashboard_status(), # Dashboard status (1)
get_dashboard_metrics(), # Dashboard metrics (1)
get_jobs_history(), # Jobs history (1)
gr.update(visible=True) # Cancel button state (1)
)
def process_dicom_with_state(dicom_input):
# Ensure dashboard functions are available
_ensure_app_imports()
# Get core processing results (3 values)
status, analysis, fhir_imaging = process_dicom_only(dicom_input)
# Return 8 values expected by Gradio outputs
return (
status, analysis, fhir_imaging, # Core results (3)
get_dashboard_status(), # Dashboard status (1)
get_dashboard_metrics(), # Dashboard metrics (1)
get_jobs_history(), # Jobs history (1)
gr.update(visible=True) # Cancel button state (1)
)
text_components["process_text_btn"].click(
fn=process_text_with_state,
inputs=[text_components["text_input"], text_components["enable_fhir_text"]],
outputs=[text_components["text_status"], text_components["extracted_entities"],
text_components["fhir_resources"], processing_status,
metrics_display, files_history_component, text_components["cancel_text_btn"]]
)
file_components["process_file_btn"].click(
fn=process_file_with_state,
inputs=[file_components["file_input"], file_components["enable_mistral_ocr"], file_components["enable_fhir_file"]],
outputs=[file_components["file_status"], file_components["file_entities"],
file_components["file_fhir"], processing_status,
metrics_display, files_history_component, file_components["cancel_file_btn"]]
)
dicom_components["process_dicom_btn"].click(
fn=process_dicom_with_state,
inputs=[dicom_components["dicom_input"]],
outputs=[dicom_components["dicom_status"], dicom_components["dicom_analysis"],
dicom_components["dicom_fhir"], processing_status,
metrics_display, files_history_component, dicom_components["cancel_dicom_btn"]]
)
# Cancel button event handlers - properly interrupt processing and reset state
def cancel_text_task():
# Force stop current processing and reset state
status = cancel_current_task("text_task")
# Return ready state and clear results
ready_status = "🔄 Processing cancelled. Ready for next text analysis."
return ready_status, {}, {}, get_dashboard_status(), get_dashboard_metrics(), get_jobs_history(), gr.update(visible=False)
def cancel_file_task():
# Force stop current processing and reset state
status = cancel_current_task("file_task")
# Return ready state and clear results
ready_status = "🔄 Processing cancelled. Ready for next document upload."
return ready_status, {}, {}, get_dashboard_status(), get_dashboard_metrics(), get_jobs_history(), gr.update(visible=False)
def cancel_dicom_task():
# Force stop current processing and reset state
status = cancel_current_task("dicom_task")
# Return ready state and clear results
ready_status = "🔄 Processing cancelled. Ready for next DICOM analysis."
return ready_status, {}, {}, get_dashboard_status(), get_dashboard_metrics(), get_jobs_history(), gr.update(visible=False)
text_components["cancel_text_btn"].click(
fn=cancel_text_task,
outputs=[text_components["text_status"], text_components["extracted_entities"],
text_components["fhir_resources"], processing_status,
metrics_display, files_history_component, text_components["cancel_text_btn"]]
)
file_components["cancel_file_btn"].click(
fn=cancel_file_task,
outputs=[file_components["file_status"], file_components["file_entities"],
file_components["file_fhir"], processing_status,
metrics_display, files_history_component, file_components["cancel_file_btn"]]
)
dicom_components["cancel_dicom_btn"].click(
fn=cancel_dicom_task,
outputs=[dicom_components["dicom_status"], dicom_components["dicom_analysis"],
dicom_components["dicom_fhir"], processing_status,
metrics_display, files_history_component, dicom_components["cancel_dicom_btn"]]
)
# Add refresh status button click handler
def refresh_agent_status():
"""Refresh the agent status display"""
import time
status_html = get_simple_agent_status()
timestamp = time.strftime("%Y-%m-%d %H:%M:%S")
last_updated_html = f"<p><small>Last updated: {timestamp}</small></p>"
return status_html, last_updated_html
stats_components["refresh_status_btn"].click(
fn=refresh_agent_status,
outputs=[stats_components["agent_status_display"], stats_components["last_updated_display"]]
)
return demo
# Helper functions for demos
def start_heavy_workload():
"""Start the heavy workload demo with real Modal container scaling"""
import asyncio
try:
# Start the Modal container scaling demo
result = asyncio.run(heavy_workload_demo.start_modal_scaling_demo())
# Get initial container data
containers = heavy_workload_demo.get_container_details()
# Get scaling metrics
stats = heavy_workload_demo.get_demo_statistics()
metrics_data = [
["Demo Status", stats['demo_status']],
["Active Containers", stats['active_containers']],
["Requests/sec", stats['requests_per_second']],
["Total Processed", stats['total_requests_processed']],
["Scaling Strategy", stats['scaling_strategy']],
["Cost per Request", stats['cost_per_request']],
["Runtime", stats['total_runtime']]
]
# Create basic workload chart data (placeholder for now)
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=[0, 1, 2], y=[1, 5, 15], mode='lines+markers', name='Containers'))
fig.update_layout(title="Container Scaling Over Time", xaxis_title="Time (min)", yaxis_title="Container Count")
return containers, metrics_data, fig
except Exception as e:
error_data = [["Error", f"Failed to start demo: {str(e)}"]]
return [], error_data, None
def stop_heavy_workload():
"""Stop the heavy workload demo"""
try:
# Stop the Modal container scaling demo
heavy_workload_demo.stop_demo()
# Get final container data (should be empty or scaled down)
containers = heavy_workload_demo.get_container_details()
# Get final metrics
stats = heavy_workload_demo.get_demo_statistics()
metrics_data = [
["Demo Status", "Demo Stopped"],
["Active Containers", 0],
["Requests/sec", 0],
["Total Processed", stats['total_requests_processed']],
["Final Runtime", stats['total_runtime']],
["Cost per Request", stats['cost_per_request']]
]
# Empty chart when stopped
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=[0], y=[0], mode='markers', name='Stopped'))
fig.update_layout(title="Demo Stopped", xaxis_title="Time", yaxis_title="Containers")
return containers, metrics_data, fig
except Exception as e:
error_data = [["Error", f"Failed to stop demo: {str(e)}"]]
return [], error_data, None
def refresh_demo_data():
"""Refresh demo data with current container status"""
try:
# Get current container data
containers = heavy_workload_demo.get_container_details()
# Get current scaling metrics
stats = heavy_workload_demo.get_demo_statistics()
metrics_data = [
["Demo Status", stats['demo_status']],
["Active Containers", stats['active_containers']],
["Requests/sec", stats['requests_per_second']],
["Total Processed", stats['total_requests_processed']],
["Concurrent Requests", stats['concurrent_requests']],
["Scaling Strategy", stats['scaling_strategy']],
["Cost per Request", stats['cost_per_request']],
["Runtime", stats['total_runtime']]
]
# Update workload chart with current data
import plotly.graph_objects as go
import time
# Simulate time series data for demo
current_time = time.time()
times = [(current_time - 60 + i*10) for i in range(7)] # Last 60 seconds
container_counts = [1, 2, 5, 8, 12, 15, stats['active_containers']]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=times,
y=container_counts,
mode='lines+markers',
name='Container Count',
line=dict(color='#B71C1C', width=3)
))
fig.update_layout(
title="Modal Container Auto-Scaling",
xaxis_title="Time",
yaxis_title="Active Containers",
showlegend=True
)
return containers, metrics_data, fig
except Exception as e:
error_data = [["Error", f"Failed to refresh: {str(e)}"]]
return [], error_data, None
def start_live_processing(batch_size, processing_type, enable_live_updates):
"""Start live batch processing with real progress tracking"""
try:
# Update main dashboard too
# Map sample file categories to workflow types (no OCR used)
workflow_map = {
"Clinical Notes Sample": "clinical_fhir",
"Lab Reports Sample": "lab_entities",
"Discharge Summaries Sample": "clinical_fhir"
}
workflow_type = workflow_map.get(processing_type, "clinical_fhir")
# Start batch processing with real data (no OCR used)
success = batch_processor.start_processing(
workflow_type=workflow_type,
batch_size=batch_size,
progress_callback=None # We'll check status periodically
)
if success:
# Update main dashboard to show batch processing activity
dashboard_state["active_tasks"] += 1
dashboard_state["last_update"] = f"Batch processing started: {batch_size} sample documents"
status = f"🔄 **Processing Started**\nBatch Size: {batch_size}\nSample Category: {processing_type}\nWorkflow: {workflow_type}"
log = f"Started processing {batch_size} {processing_type.lower()} using {workflow_type} workflow (no OCR)\n"
results = {
"total_documents": batch_size,
"processed": 0,
"entities_extracted": 0,
"fhir_resources_generated": 0,
"processing_time": "0s",
"avg_time_per_doc": "0s"
}
return status, log, results
else:
return "❌ Failed to start processing - already running", "", {}
except Exception as e:
return f"❌ Error starting processing: {str(e)}", "", {}
def stop_processing():
"""Stop batch processing"""
try:
batch_processor.stop_processing()
# Get final status
final_status = batch_processor.get_status()
# Update main dashboard when stopping
if dashboard_state["active_tasks"] > 0:
dashboard_state["active_tasks"] -= 1
current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
if final_status["status"] == "completed":
log = f"Processing completed: {final_status['processed']} documents in {final_status['total_time']:.2f}s\n"
dashboard_state["last_update"] = f"Batch completed: {final_status['processed']} documents at {current_time}"
else:
log = "Processing stopped by user\n"
dashboard_state["last_update"] = f"Batch stopped by user at {current_time}"
return "⏹️ Processing stopped", log
except Exception as e:
return f"❌ Error stopping processing: {str(e)}", ""
# Global state tracking to prevent UI blinking/flashing
_last_dashboard_state = {}
_last_batch_status = {}
_batch_completion_processed = False # Track if we've already processed completion
def update_batch_status_realtime():
"""Real-time status updates for batch processing - called by timer"""
try:
status = batch_processor.get_status()
# Track current state to prevent unnecessary updates and blinking
global _last_dashboard_state, _last_batch_status, _batch_completion_processed
# If batch is completed and we've already processed it, stop all updates
if status["status"] == "completed" and _batch_completion_processed:
return (
gr.update(), # batch_status - no update
gr.update(), # processing_log - no update
gr.update(), # results_summary - no update
gr.update(), # processing_status - no update
gr.update(), # metrics_display - no update
gr.update() # files_history - no update
)
current_dashboard_state = {
'total_files': dashboard_state.get('total_files', 0),
'successful_files': dashboard_state.get('successful_files', 0),
'failed_files': dashboard_state.get('failed_files', 0),
'active_tasks': dashboard_state.get('active_tasks', 0),
'last_update': dashboard_state.get('last_update', 'Never')
}
current_batch_state = {
'status': status.get('status', 'ready'),
'processed': status.get('processed', 0),
'total': status.get('total', 0),
'elapsed_time': status.get('elapsed_time', 0)
}
# Check if dashboard state has changed
dashboard_changed = current_dashboard_state != _last_dashboard_state
batch_changed = current_batch_state != _last_batch_status
# Update tracking state
_last_dashboard_state = current_dashboard_state.copy()
_last_batch_status = current_batch_state.copy()
# Mark completion as processed to prevent repeated updates
if status["status"] == "completed":
_last_batch_status['completion_processed'] = True
if status["status"] == "ready":
# Reset completion flag for new batch
_batch_completion_processed = False
return (
"🔄 Ready to start batch processing",
"",
create_empty_results_summary(),
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [],
get_jobs_history() if get_jobs_history else []
)
elif status["status"] == "processing":
# Update main dashboard with current progress
processed_docs = status['processed']
total_docs = status['total']
# Add newly completed documents to dashboard in real-time
results = status.get('results', [])
if results and _add_file_to_dashboard:
# Check if there are new completed documents since last update
completed_count = len([r for r in results if r.get('status') == 'completed'])
dashboard_processed = dashboard_state.get('batch_processed_count', 0)
# Add new completed documents to dashboard
if completed_count > dashboard_processed:
for i in range(dashboard_processed, completed_count):
if i < len(results):
result = results[i]
sample_category = status.get('current_workflow', 'Sample Document')
processing_time = result.get('processing_time', 0)
_add_file_to_dashboard(
filename=f"Batch Document {i+1}",
file_type=f"{sample_category} (Batch)",
success=True,
processing_time=f"{processing_time:.2f}s",
error=None
)
dashboard_state['batch_processed_count'] = completed_count
# Update dashboard state to show batch processing activity
dashboard_state["last_update"] = f"Batch processing: {processed_docs}/{total_docs} documents"
# Calculate progress
progress_percent = (processed_docs / total_docs) * 100
# Create progress bar HTML
progress_html = f"""
<div style="margin: 10px 0;">
<div style="background: #f0f0f0; border-radius: 10px; overflow: hidden;">
<div style="background: linear-gradient(90deg, #4CAF50, #2196F3);
height: 20px; width: {progress_percent}%;
display: flex; align-items: center; justify-content: center;
color: white; font-weight: bold;">
{progress_percent:.1f}%
</div>
</div>
</div>
"""
# Enhanced status text
current_step_desc = status.get('current_step_description', 'Processing...')
status_text = f"""
🔄 **Processing in Progress**
{progress_html}
**Document:** {processed_docs}/{total_docs}
**Current Step:** {current_step_desc}
**Elapsed:** {status['elapsed_time']:.1f}s
**Estimated Remaining:** {status['estimated_remaining']:.1f}s
"""
# Build clean processing log - remove duplicates and show only key milestones
log_entries = []
processing_log = status.get('processing_log', [])
# Group log entries by document and show only completion status
doc_status = {}
for log_entry in processing_log:
doc_num = log_entry.get('document', 0)
step = log_entry.get('step', '')
message = log_entry.get('message', '')
# Only keep completion messages and avoid duplicates
if 'completed' in step or 'Document' in message and 'completed' in message:
doc_status[doc_num] = f"📄 Doc {doc_num}: {message}"
elif doc_num not in doc_status and ('processing' in step or 'Processing' in message):
doc_status[doc_num] = f"📄 Doc {doc_num}: Processing..."
# Show last 6 documents progress
recent_docs = sorted(doc_status.keys())[-6:]
for doc_num in recent_docs:
log_entries.append(doc_status[doc_num])
log_text = "\n".join(log_entries) if log_entries else "Starting batch processing..."
# Calculate metrics from results
results = status.get('results', [])
total_entities = sum(len(result.get('entities', [])) for result in results)
total_fhir = sum(1 for result in results if result.get('fhir_bundle_generated', False))
results_summary = {
"total_documents": status['total'],
"processed": status['processed'],
"entities_extracted": total_entities,
"fhir_resources_generated": total_fhir,
"processing_time": f"{status['elapsed_time']:.1f}s",
"avg_time_per_doc": f"{status['elapsed_time']/status['processed']:.1f}s" if status['processed'] > 0 else "0s",
"documents_per_second": f"{status['processed']/status['elapsed_time']:.2f}" if status['elapsed_time'] > 0 else "0"
}
# Return with dashboard updates
return (status_text, log_text, results_summary,
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [],
get_jobs_history() if get_jobs_history else [])
elif status["status"] == "completed":
# Mark completion as processed to stop future updates
_batch_completion_processed = True
# Processing completed - add all processed documents to main dashboard
results = status.get('results', [])
total_entities = sum(len(result.get('entities', [])) for result in results)
total_fhir = sum(1 for result in results if result.get('fhir_bundle_generated', False))
# Add each processed document to the main dashboard
import datetime
current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# Ensure we have the add_file_to_dashboard function
try:
from app import add_file_to_dashboard
for i, result in enumerate(results):
doc_id = result.get('document_id', f'batch_doc_{i+1}')
entities_count = len(result.get('entities', []))
processing_time = result.get('processing_time', 0)
fhir_generated = result.get('fhir_bundle_generated', False)
# Add to dashboard as individual file - this will update all counters automatically
sample_category = status.get('processing_type', 'Batch Demo Document')
add_file_to_dashboard(
filename=f"Batch Document {i+1}",
file_type=f"{sample_category}",
success=True,
processing_time=f"{processing_time:.2f}s",
error=None,
entities_found=entities_count
)
except Exception as e:
print(f"Error adding batch files to dashboard: {e}")
# Update final dashboard state
if dashboard_state["active_tasks"] > 0:
dashboard_state["active_tasks"] -= 1
dashboard_state["last_update"] = f"Batch completed: {status['processed']} documents at {current_time}"
completion_text = f"""
✅ **Processing Completed Successfully!**
📊 **Final Results:**
- **Documents Processed:** {status['processed']}/{status['total']}
- **Total Processing Time:** {status['total_time']:.2f}s
- **Average Time per Document:** {status['total_time']/status['processed']:.2f}s
- **Documents per Second:** {status['processed']/status['total_time']:.2f}
- **Total Entities Extracted:** {total_entities}
- **FHIR Resources Generated:** {total_fhir}
🎉 **All documents added to File Processing Dashboard!**
"""
final_results = {
"total_documents": status['total'],
"processed": status['processed'],
"entities_extracted": total_entities,
"fhir_resources_generated": total_fhir,
"processing_time": f"{status['total_time']:.1f}s",
"avg_time_per_doc": f"{status['total_time']/status['processed']:.1f}s",
"documents_per_second": f"{status['processed']/status['total_time']:.2f}"
}
# Return with dashboard updates
return (completion_text, "🎉 All documents processed successfully!", final_results,
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [],
get_jobs_history() if get_jobs_history else [])
else: # cancelled or error
return (f"⚠️ Processing {status['status']}", status.get('message', ''), create_empty_results_summary(),
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [],
get_jobs_history() if get_jobs_history else [])
except Exception as e:
return (f"❌ Status update error: {str(e)}", "", create_empty_results_summary(),
get_dashboard_status() if get_dashboard_status else "<p>Dashboard not available</p>",
get_dashboard_metrics() if get_dashboard_metrics else [],
get_jobs_history() if get_jobs_history else [])
def create_empty_results_summary():
"""Create empty results summary"""
return {
"total_documents": 0,
"processed": 0,
"entities_extracted": 0,
"fhir_resources_generated": 0,
"processing_time": "0s",
"avg_time_per_doc": "0s"
}
def get_batch_processing_status():
"""Get current batch processing status with detailed step-by-step feedback"""
try:
status = batch_processor.get_status()
if status["status"] == "ready":
return "🔄 Ready to start batch processing", "", {
"total_documents": 0,
"processed": 0,
"entities_extracted": 0,
"fhir_resources_generated": 0,
"processing_time": "0s",
"avg_time_per_doc": "0s"
}
elif status["status"] == "processing":
# Enhanced progress text with current step information
current_step_desc = status.get('current_step_description', 'Processing...')
progress_text = f"🔄 **Processing in Progress**\nProgress: {status['progress']:.1f}%\nDocument: {status['processed']}/{status['total']}\nCurrent Step: {current_step_desc}\nElapsed: {status['elapsed_time']:.1f}s\nEstimated remaining: {status['estimated_remaining']:.1f}s"
# Build clean log with recent processing steps - avoid duplicates
log_entries = []
processing_log = status.get('processing_log', [])
# Group by document to avoid duplicates
doc_status = {}
for log_entry in processing_log:
doc_num = log_entry.get('document', 0)
step = log_entry.get('step', '')
message = log_entry.get('message', '')
# Only keep meaningful completion messages
if 'completed' in step or ('completed' in message and 'entities' in message):
doc_status[doc_num] = f"Doc {doc_num}: Completed"
elif doc_num not in doc_status:
doc_status[doc_num] = f"Doc {doc_num}: Processing..."
# Show last 5 documents
recent_docs = sorted(doc_status.keys())[-5:]
for doc_num in recent_docs:
log_entries.append(doc_status[doc_num])
log_text = "\n".join(log_entries) + "\n"
# Calculate entities and FHIR from results so far
results = status.get('results', [])
total_entities = sum(len(result.get('entities', [])) for result in results)
total_fhir = sum(1 for result in results if result.get('fhir_bundle_generated', False))
results_summary = {
"total_documents": status['total'],
"processed": status['processed'],
"entities_extracted": total_entities,
"fhir_resources_generated": total_fhir,
"processing_time": f"{status['elapsed_time']:.1f}s",
"avg_time_per_doc": f"{status['elapsed_time']/status['processed']:.1f}s" if status['processed'] > 0 else "0s"
}
return progress_text, log_text, results_summary
elif status["status"] == "cancelled":
cancelled_text = f"⏹️ **Processing Cancelled**\nProcessed: {status['processed']}/{status['total']} ({status['progress']:.1f}%)\nElapsed time: {status['elapsed_time']:.1f}s"
# Calculate partial results
results = status.get('results', [])
total_entities = sum(len(result.get('entities', [])) for result in results)
total_fhir = sum(1 for result in results if result.get('fhir_bundle_generated', False))
partial_results = {
"total_documents": status['total'],
"processed": status['processed'],
"entities_extracted": total_entities,
"fhir_resources_generated": total_fhir,
"processing_time": f"{status['elapsed_time']:.1f}s",
"avg_time_per_doc": f"{status['elapsed_time']/status['processed']:.1f}s" if status['processed'] > 0 else "0s"
}
log_cancelled = f"Processing cancelled by user after {status['elapsed_time']:.1f}s\nPartial results: {status['processed']} documents processed\nExtracted {total_entities} medical entities\nGenerated {total_fhir} FHIR resources\n"
return cancelled_text, log_cancelled, partial_results
elif status["status"] == "completed":
completed_text = f"✅ **Processing Complete!**\nTotal processed: {status['processed']}/{status['total']}\nTotal time: {status['total_time']:.2f}s"
# Calculate final metrics
results = status.get('results', [])
total_entities = sum(len(result.get('entities', [])) for result in results)
total_fhir = sum(1 for result in results if result.get('fhir_bundle_generated', False))
final_results = {
"total_documents": status['total'],
"processed": status['processed'],
"entities_extracted": total_entities,
"fhir_resources_generated": total_fhir,
"processing_time": f"{status['total_time']:.2f}s",
"avg_time_per_doc": f"{status['total_time']/status['processed']:.2f}s" if status['processed'] > 0 else "0s"
}
log_final = f"✅ Batch processing completed successfully!\nProcessed {status['processed']} documents in {status['total_time']:.2f}s\nExtracted {total_entities} medical entities\nGenerated {total_fhir} FHIR resources\nAverage processing time: {status['total_time']/status['processed']:.2f}s per document\n"
return completed_text, log_final, final_results
except Exception as e:
return f"❌ Error getting status: {str(e)}", "", {}
|