Spaces:
Running
Running
File size: 61,903 Bytes
b1f90a5 |
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 |
import asyncio
import json
import logging
import os
from typing import Any, AsyncGenerator, Dict, List, Optional
from datetime import datetime
import gradio as gr
from gradio.components import Component
from src.agent.browser_use.browser_use_agent import BrowserUseAgent
from src.browser.custom_browser import CustomBrowser
from src.controller.custom_controller import CustomController
from src.utils import llm_provider
from src.webui.webui_manager import WebuiManager
from browser_use.browser.browser import BrowserConfig
from browser_use.browser.context import BrowserContext, BrowserContextConfig
logger = logging.getLogger(__name__)
# Import environment variables
from dotenv import load_dotenv
load_dotenv() # This ensures environment variables are loaded
# Get Vayner credentials from environment
VAYNER_USERNAME = os.getenv("VAYNER_USERNAME", "")
VAYNER_PASSWORD = os.getenv("VAYNER_PASSWORD", "")
VAYNER_CLIENT_TEMPLATE = """
Task: Research Vayner Commerce data for business: "{business_name}"
1. Log in to https://local.vaynercommerce.com/myclients
- Username: admin@vaynercommerce.com
- Password: oKLl4li-HY
- Use these credentials on the login form
2. After successful login, search for the business named "{business_name}" in the search box
3. Click on the business in the search results
**Part 1: Keyword Performance Table**
4. Extract the keyword performance table (columns: Keyword, Performance, Status)
- Return this as a formatted table
**Part 2: Keyword Ranking History Analysis Table**
5. For the first keyword in the list:
a. Click on the keyword to open its detail view
b. Look for the **History** section
c. Click the **last row (earliest date)** in the History section:
-extract:
- Top 3 Rank → This is the **Initial Top 3 Rank (SOV)**
- Coverage → This is the **Initial Coverage**
- Then look for the **Your Rankings** section (while this row is selected), extract:
- ARP → This is the **Initial ARP**
d. Then again the table under the **History** section, click the **first row (most recent date)** in the History section:
- From the **History section**, extract:
- Top 3 Rank → This is the **Current Rank (SOV) in our table**
- Coverage → This is the **Current Coverage**
- Then look for the **Your Rankings** section (while this row is selected), extract:
- ARP → This is the **Current Scan ARP**
6. Go back to the Keywords list and repeat Step 5 for the second keyword in the list.
Please provide:
- The complete keyword performance data as a 1 table.
- Another new table that Return all of information from **Part 2: Keyword Ranking History Analysis Table** as a second table with the following columns:
- Keyword
- Initial ARP
- Initial Top 3 Rank (SOV)
- Initial Coverage
- Current Scan ARP
- Current Rank (SOV)
- Current Coverage
At the bottom of the table, compute and include a final row labeled "Average" showing the average of all numeric columns (excluding the "Keyword" column).
"""
# Function to generate PDF-like report from task results
def generate_pdf_report(business_name, history):
"""
Generate HTML for a PDF-like report based on the agent's history data
"""
# Extract relevant information from history
final_result = history.final_result() or {}
screenshots = []
keyword_data = []
ranking_data = []
performance_data = []
# Process agent history to extract information
try:
# The history object is itself iterable
for item in history:
try:
# Extract screenshot if available
if hasattr(item, "state") and hasattr(item.state, "screenshot"):
if item.state.screenshot and isinstance(item.state.screenshot, str) and len(item.state.screenshot) > 100:
screenshots.append(item.state.screenshot)
# Extract data from actions
if hasattr(item, "output") and item.output:
for action in item.output.action:
if hasattr(action, "thought"):
thought = action.thought.lower() if action.thought else ""
# Look for keyword data in thoughts
if "keyword" in thought and ("performance" in thought or "score" in thought):
keyword_data.append(action.thought)
# Check if action contains ranking data
elif "ranking" in thought or "rank" in thought:
ranking_data.append(action.thought)
# Check if action contains performance data
elif "performance" in thought and "score" in thought:
performance_data.append(action.thought)
# Check for extracted data in observe action results
if hasattr(action, "result") and action.result:
if isinstance(action.result, str):
result = action.result.lower()
if "keyword" in result or "performance" in result:
if action.result not in keyword_data and len(action.result.strip()) > 5:
keyword_data.append(action.result)
if "ranking" in result or "rank" in result:
if action.result not in ranking_data and len(action.result.strip()) > 5:
ranking_data.append(action.result)
except Exception as e:
logger.error(f"Error processing history item: {e}")
continue
except Exception as e:
logger.error(f"Error iterating through history: {e}")
# Generate HTML for PDF-like report
html = f"""
<div style="font-family: Arial, sans-serif; max-width: 90%; margin: 0 auto; padding: 20px; border: 1px solid #e0e0e0; box-shadow: 0 0 10px rgba(0,0,0,0.1);">
<div style="text-align: center; border-bottom: 2px solid #2c3e50; padding-bottom: 10px; margin-bottom: 20px;">
<h1 style="color: #2c3e50;">Vayner Client Research Report</h1>
<h2 style="color: #3498db;">{business_name}</h2>
<p style="color: #7f8c8d;">Generated on {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
</div>
<div style="margin-bottom: 30px;">
<h3 style="color: #2c3e50; border-bottom: 1px solid #e0e0e0; padding-bottom: 5px;">Executive Summary</h3>
<p>This report contains research data for {business_name} extracted from Vayner Commerce platform.
We analyzed keyword performance data and geographic rankings.</p>
</div>
"""
# If no specific data is found, try to extract from all output
if not keyword_data and not ranking_data and not performance_data:
try:
all_text = []
for item in history:
if hasattr(item, "output") and item.output:
for action in item.output.action:
if hasattr(action, "thought") and action.thought:
all_text.append(action.thought)
if hasattr(action, "result") and action.result:
all_text.append(action.result)
# Look for sections in the text
for text in all_text:
if "keyword" in text.lower() or "score" in text.lower() or "performance" in text.lower():
keyword_data.append(text)
if "ranking" in text.lower() or "rank" in text.lower():
ranking_data.append(text)
except Exception as e:
logger.error(f"Error extracting all text: {e}")
# Add performance data section
if performance_data or keyword_data:
html += """
<div style="margin-bottom: 30px;">
<h3 style="color: #2c3e50; border-bottom: 1px solid #e0e0e0; padding-bottom: 5px;">Keyword Performance Data</h3>
"""
# Try to parse data into a table format
table_data = []
try:
combined_data = performance_data + keyword_data
for data in combined_data:
lines = data.split("\n")
for line in lines:
if ":" in line:
parts = line.split(":", 1)
if len(parts) == 2:
keyword, value = parts
table_data.append((keyword.strip(), value.strip()))
elif "-" in line and not line.strip().startswith("-"):
parts = line.split("-", 1)
if len(parts) == 2:
keyword, value = parts
table_data.append((keyword.strip(), value.strip()))
if table_data:
html += """
<table style="width: 100%; border-collapse: collapse;">
<thead>
<tr style="background-color: #f2f2f2;">
<th style="padding: 10px; border: 1px solid #e0e0e0; text-align: left;">Keyword</th>
<th style="padding: 10px; border: 1px solid #e0e0e0; text-align: left;">Performance/Score</th>
</tr>
</thead>
<tbody>
"""
for keyword, value in table_data:
html += f"""
<tr>
<td style="padding: 10px; border: 1px solid #e0e0e0;">{keyword}</td>
<td style="padding: 10px; border: 1px solid #e0e0e0;">{value}</td>
</tr>
"""
html += """
</tbody>
</table>
"""
else:
# Display raw data if table parsing failed
for data in combined_data:
html += f"""
<div style="margin-bottom: 15px; padding: 10px; background-color: #f9f9f9; border: 1px solid #e0e0e0;">
<pre style="margin: 0; white-space: pre-wrap;">{data}</pre>
</div>
"""
except Exception as e:
logger.error(f"Error formatting table data: {e}")
# Fallback to raw display
for data in performance_data + keyword_data:
html += f"""
<div style="margin-bottom: 15px; padding: 10px; background-color: #f9f9f9; border: 1px solid #e0e0e0;">
<pre style="margin: 0; white-space: pre-wrap;">{data}</pre>
</div>
"""
html += """
</div>
"""
# Add rankings data section
if ranking_data:
html += """
<div style="margin-bottom: 30px;">
<h3 style="color: #2c3e50; border-bottom: 1px solid #e0e0e0; padding-bottom: 5px;">Geographic Rankings</h3>
"""
for data in ranking_data:
html += f"""
<div style="margin-bottom: 15px; padding: 10px; background-color: #f9f9f9; border: 1px solid #e0e0e0;">
<pre style="margin: 0; white-space: pre-wrap;">{data}</pre>
</div>
"""
html += """
</div>
"""
# Add screenshots section
if screenshots:
html += """
<div style="margin-bottom: 30px;">
<h3 style="color: #2c3e50; border-bottom: 1px solid #e0e0e0; padding-bottom: 5px;">Map Visualizations</h3>
<div style="display: flex; flex-wrap: wrap; gap: 15px; justify-content: center;">
"""
for idx, screenshot in enumerate(screenshots):
if isinstance(screenshot, str) and len(screenshot) > 100:
html += f"""
<div style="margin-bottom: 15px; text-align: center;">
<img src="data:image/jpeg;base64,{screenshot}" alt="Map {idx+1}" style="max-width: 100%; border: 1px solid #e0e0e0; box-shadow: 0 2px 5px rgba(0,0,0,0.1);">
<p style="margin-top: 5px; font-style: italic; color: #7f8c8d;">Map Visualization {idx+1}</p>
</div>
"""
html += """
</div>
</div>
"""
# If no data was found, show a message
if not keyword_data and not performance_data and not ranking_data and not screenshots:
html += """
<div style="margin-bottom: 30px; text-align: center; padding: 20px; background-color: #f8f9fa; border-radius: 5px;">
<h3 style="color: #e74c3c;">No data extracted</h3>
<p>The agent was unable to extract specific data for this report. Please check the chat logs for more details on what was found.</p>
</div>
"""
# Add footer
html += """
<div style="border-top: 1px solid #e0e0e0; padding-top: 15px; text-align: center; font-size: 12px; color: #7f8c8d;">
<p>Generated by Vayner Client Research Agent | Browser-Use WebUI</p>
</div>
</div>
"""
return html
# Function to generate live PDF-like report updated during the task
def generate_live_report(business_name, business_info, keyword_data, ranking_data, screenshots, keyword_table_rows=None, final_result=None):
"""
Generate HTML for a live-updating PDF-like report based on data collected so far
Only show the first three pages: cover, second page, and keyword table with final result.
"""
if keyword_table_rows is None:
keyword_table_rows = []
# Cover page (black background, business name, VaynerCommerce logo)
html = f'''
<div style="width:100%; min-height:400px; background:#000; color:#fff; display:flex; flex-direction:column; align-items:center; justify-content:center; padding:60px 0 40px 0;">
<div style="width:70%; max-width:500px; margin-bottom:30px;">
<div style="text-align:center; margin-bottom:20px;">
<svg width="120" height="80" viewBox="0 0 120 80" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M60 15C70 15 80 25 90 30C100 35 110 30 115 25C110 40 100 50 80 50C60 50 40 40 30 30C40 35 50 15 60 15Z" fill="white"/>
<path d="M70 15C65 20 60 18 55 15" stroke="white" stroke-width="2"/>
<path d="M75 12C70 17 65 15 60 12" stroke="white" stroke-width="2"/>
</svg>
</div>
<div style="font-size:2.7rem; font-weight:600; letter-spacing:2px; text-align:center; line-height:1.1; text-transform:uppercase; font-family: 'Montserrat', Arial, sans-serif;">
{business_name}
</div>
<div style="font-size:1.2rem; text-align:center; letter-spacing:1px; margin-top:5px; text-transform:uppercase; font-family: 'Montserrat', Arial, sans-serif;">
</div>
</div>
<div style="font-size:2.5rem; font-weight:600; margin: 30px 0; text-align:center;">X</div>
<div style="width:70%; max-width:500px;">
<div style="font-size:2.1rem; font-weight:700; letter-spacing:2px; text-align:center; text-transform:uppercase; font-family: 'Montserrat', Arial, sans-serif;">
<div style="display:inline-block; margin-right:10px; vertical-align:middle;">◆</div> VAYNERCOMMERCE
</div>
</div>
</div>
'''
# Second page (logo, business name, service, date, image)
html += f'''
<div style="width:100%; min-height:400px; background:#fff; color:#222; display:flex; flex-direction:row; align-items:stretch; padding:0;">
<div style="flex:1; display:flex; flex-direction:column; align-items:center; justify-content:center; padding:40px 20px; border-right:1px solid #eee;">
<div style="width:240px; margin-bottom:20px;">
<svg viewBox="0 0 240 140" width="240" height="140" xmlns="http://www.w3.org/2000/svg">
<path d="M120 30C140 30 160 50 180 60C200 70 220 60 230 50C220 80 200 100 160 100C120 100 80 80 60 60C80 70 100 30 120 30Z" fill="#4A8FBA"/>
<path d="M140 30C130 40 120 36 110 30" stroke="#4A8FBA" stroke-width="2"/>
<path d="M150 24C140 34 130 30 120 24" stroke="#4A8FBA" stroke-width="2"/>
<ellipse cx="140" cy="70" rx="100" ry="15" fill="#E3B151" opacity="0.3"/>
</svg>
</div>
<div style="font-size:2.2rem; font-weight:600; color:#4A8FBA; margin-bottom:10px; font-family: 'Montserrat', Arial, sans-serif; text-transform:uppercase; letter-spacing:1px; text-align:center; line-height:1.1;">
{business_name}<br>
<span style="font-size:1.1rem; color:#666; text-transform:uppercase; letter-spacing:1px;">BEHAVIORAL HEALTH</span>
</div>
<div style="font-size:1.1rem; color:#666; margin:20px 0; text-align:center;">SEO Services</div>
<div style="font-size:1rem; color:#444; text-align:center;">Weeks of <span style="font-weight:600;">04/07/25 - 04/21/25</span></div>
<div style="margin-top:60px; font-size:0.9rem; color:#bbb; font-family: 'Montserrat', Arial, sans-serif;">
<span style="display:inline-block; margin-right:5px; vertical-align:middle;">◆</span> VAYNERCOMMERCE
</div>
</div>
<div style="flex:1; min-height:400px; background-image:url('https://images.unsplash.com/photo-1577563908411-5077b6dc7624?auto=format&fit=crop&w=700&q=80'); background-size:cover; background-position:center;">
</div>
</div>
'''
# Third page: Final Result and Keyword Table
html += f'''
<div style="width:100%; min-height:600px; background:#000; color:#fff; display:flex; flex-direction:column; align-items:center; justify-content:flex-start; padding:40px 0 40px 0; border-bottom:2px solid #222;">
<div style="font-size:1.8rem; font-weight:600; color:#fff; margin-bottom:10px; font-family: 'Montserrat', Arial, sans-serif;">Final Research Results</div>
<div style="width:90%; max-width:900px; margin-bottom:40px;">
'''
# Display Final Result if available
if final_result:
# Determine if final_result is likely a table
is_table = False
if isinstance(final_result, str):
lines = final_result.strip().split('\n')
if any('|' in line for line in lines) or any('keyword' in line.lower() and 'performance' in line.lower() for line in lines):
is_table = True
if is_table:
# Format as a table
try:
html += '<div style="width:100%; overflow-x:auto; margin:20px 0; border-radius:4px; box-shadow:0 2px 10px rgba(0,0,0,0.1);">'
# Split the table data
lines = [line.strip() for line in final_result.split('\n') if line.strip()]
# Find the header row
header_row_index = -1
for i, line in enumerate(lines):
if ('keyword' in line.lower() and 'performance' in line.lower()) or ('keyword' in line.lower() and 'sov' in line.lower()):
header_row_index = i
break
if header_row_index != -1:
# Create an HTML table
html += '<table style="width:100%; border-collapse:collapse; font-family:Arial, sans-serif; background:#000; color:#fff;">'
# Format the header row
header = lines[header_row_index]
header_cells = [cell.strip() for cell in header.strip('|').split('|')]
html += '<thead><tr style="background-color:#222; color:#fff;">'
for cell in header_cells:
html += f'<th style="padding:12px 15px; text-align:left; border-bottom:2px solid #444;">{cell}</th>'
html += '</tr></thead><tbody>'
# Skip the separator row if it exists
data_start = header_row_index + 2 if header_row_index + 1 < len(lines) and '---' in lines[header_row_index + 1] else header_row_index + 1
# Format the data rows
for i in range(data_start, len(lines)):
row = lines[i]
if '|' in row:
cells = [cell.strip() for cell in row.strip('|').split('|')]
bg_color = '#111' if i % 2 == 0 else '#181818'
html += f'<tr style="background-color:{bg_color}; color:#fff;">'
for cell in cells:
html += f'<td style="padding:10px 15px; border-bottom:1px solid #333;">{cell}</td>'
html += '</tr>'
html += '</tbody></table>'
else:
# If no proper header found, just display the text in a pre tag
html += f'<pre style="width:100%; background-color:#111; color:#fff; padding:15px; border-radius:4px; white-space:pre-wrap; overflow-x:auto;">{final_result}</pre>'
html += '</div>'
except Exception:
# If parsing fails, just display the raw text
html += f'<pre style="width:100%; background-color:#111; color:#fff; padding:15px; border-radius:4px; white-space:pre-wrap; overflow-x:auto;">{final_result}</pre>'
else:
# Format as regular text
html += f'<div style="width:100%; background-color:#111; color:#fff; padding:20px; border-radius:4px; border-left:4px solid #4A8FBA; margin:20px 0;">'
if isinstance(final_result, str):
# Format the text with proper paragraphs
paragraphs = final_result.split('\n\n')
for paragraph in paragraphs:
if paragraph.strip():
paragraph_html = paragraph.replace("\n", "<br>")
html += f'<p style="margin-bottom:15px; line-height:1.5;">{paragraph_html}</p>'
elif isinstance(final_result, list):
# Handle list of items
html += '<ul style="margin-left:20px; line-height:1.5;">'
for item in final_result:
html += f'<li style="margin-bottom:8px;">{item}</li>'
html += '</ul>'
elif isinstance(final_result, dict):
# Handle dictionary
html += '<div style="line-height:1.5;">'
for key, value in final_result.items():
html += f'<div style="margin-bottom:10px;"><strong>{key}:</strong> {value}</div>'
html += '</div>'
else:
# Generic string representation
html += f'<p style="line-height:1.5;">{str(final_result)}</p>'
html += '</div>'
else:
html += '''
<div style="width:90%; background-color:#111; color:#fff; padding:20px; border-radius:4px; text-align:center; margin:20px 0;">
<p style="color:#bbb; font-style:italic;">Results will appear here when the task is completed.</p>
</div>
'''
# Additional keyword table display
if keyword_table_rows:
html += '''
<div style="width:90%; max-width:800px; margin-top:30px;">
<div style="font-size:1.4rem; font-weight:600; color:#fff; margin-bottom:15px; font-family: 'Montserrat', Arial, sans-serif;">Keyword Performance Summary</div>
<table style="width:100%; border-collapse:collapse; background:#000; color:#fff;">
<thead>
<tr style="background-color:#222; color:#fff;">
<th style="padding:10px; border:1px solid #333; text-align:left;">Keyword</th>
<th style="padding:10px; border:1px solid #333; text-align:left;">Performance</th>
<th style="padding:10px; border:1px solid #333; text-align:left;">SOV</th>
</tr>
</thead>
<tbody>
'''
for row in keyword_table_rows:
html += f'''<tr style="background-color:#111; color:#fff;">
<td style="padding:10px; border:1px solid #333;">{row['keyword']}</td>
<td style="padding:10px; border:1px solid #333;">{row['performance']}</td>
<td style="padding:10px; border:1px solid #333;">{row['sov']}</td>
</tr>'''
html += '''
</tbody>
</table>
</div>
'''
html += '</div></div>'
return html
async def run_vayner_research(
webui_manager: WebuiManager,
components: Dict[gr.components.Component, Any],
business_name: str
) -> AsyncGenerator[Dict[gr.components.Component, Any], None]:
"""
Runs a Vayner client research task and yields UI updates.
"""
# Get all required UI components
run_button_comp = webui_manager.get_component_by_id("vayner_client_research.run_button")
stop_button_comp = webui_manager.get_component_by_id("vayner_client_research.stop_button")
chatbot_comp = webui_manager.get_component_by_id("vayner_client_research.chatbot")
browser_view_comp = webui_manager.get_component_by_id("vayner_client_research.browser_view")
pdf_report_comp = webui_manager.get_component_by_id("vayner_client_research.pdf_report")
# Create the task using the template with credentials
task = VAYNER_CLIENT_TEMPLATE.format(
business_name=business_name,
vayner_username=VAYNER_USERNAME,
vayner_password=VAYNER_PASSWORD
)
# Initialize chat history if needed
if not hasattr(webui_manager, "vayner_chat_history"):
webui_manager.vayner_chat_history = []
# Show the business being researched
webui_manager.vayner_chat_history.append(
{"role": "user", "content": f"Research business: {business_name}"}
)
webui_manager.vayner_chat_history.append(
{"role": "assistant", "content": f"Starting research for {business_name}..."}
)
yield {
k: v for k, v in {
chatbot_comp: gr.update(value=webui_manager.vayner_chat_history),
run_button_comp: gr.update(value="⏳ Researching...", interactive=False),
stop_button_comp: gr.update(interactive=True),
pdf_report_comp: gr.update(visible=False)
}.items() if k is not None
}
# Get settings from agent settings
def get_setting(name, default=None):
comp = webui_manager.get_component_by_id(f"agent_settings.{name}")
return components.get(comp, default) if comp else default
# LLM Settings
llm_provider_name = get_setting("llm_provider", "openai")
llm_model_name = get_setting("llm_model_name", "gpt-4o")
llm_temperature = get_setting("llm_temperature", 0.6)
use_vision = True # Always need vision for this task
llm_base_url = get_setting("llm_base_url", "")
llm_api_key = get_setting("llm_api_key", "")
if not llm_api_key:
llm_api_key = os.getenv("OPENAI_API_KEY", "")
# Browser Settings
def get_browser_setting(key, default=None):
comp = webui_manager.get_component_by_id(f"browser_settings.{key}")
return components.get(comp, default) if comp else default
headless = True # Force headless mode for this agent
disable_security = get_browser_setting("disable_security", False)
window_w = int(get_browser_setting("window_w", 1920))
window_h = int(get_browser_setting("window_h", 1080))
save_recording_path = get_browser_setting("save_recording_path") or "./tmp/vayner_recordings"
save_download_path = get_browser_setting("save_download_path", "./tmp/downloads")
# Make sure paths exist
os.makedirs(save_recording_path, exist_ok=True)
if save_download_path:
os.makedirs(save_download_path, exist_ok=True)
# Stream settings for view
stream_vw = 80
stream_vh = int(80 * window_h // window_w)
# Get LLM for agent
main_llm = llm_provider.get_llm_model(
provider="openai", # Force OpenAI for vision capabilities
model_name=str(llm_model_name) if llm_model_name else "gpt-4o",
temperature=float(llm_temperature),
base_url=str(llm_base_url) if llm_base_url else None,
api_key=str(llm_api_key) if llm_api_key else None,
)
if main_llm is None:
raise ValueError("Failed to initialize LLM. Please check your OpenAI API key and model settings in Agent Settings.")
# Step and done callbacks
async def step_callback(state, output, step_num):
step_num -= 1
logger.info(f"Step {step_num} completed.")
# Process screenshot if available (for PDF only, not chat)
screenshot_data = getattr(state, "screenshot", None)
if screenshot_data:
try:
if isinstance(screenshot_data, str) and len(screenshot_data) > 100:
# Store screenshot for report
if not hasattr(webui_manager, "vayner_screenshots"):
webui_manager.vayner_screenshots = []
webui_manager.vayner_screenshots.append(screenshot_data)
except Exception as e:
logger.error(f"Error processing screenshot: {e}")
# Extract information for real-time PDF report
try:
if not hasattr(webui_manager, "vayner_business_info"):
webui_manager.vayner_business_info = []
if not hasattr(webui_manager, "vayner_keyword_data"):
webui_manager.vayner_keyword_data = []
if not hasattr(webui_manager, "vayner_ranking_data"):
webui_manager.vayner_ranking_data = []
# Extract business info, keywords, and rankings from this step
for action in output.action:
if hasattr(action, "thought") and action.thought:
thought = action.thought.lower()
# Extract business info
if "business" in thought and any(x in thought for x in ["name", "address", "info", "details", "about"]):
if action.thought not in webui_manager.vayner_business_info:
webui_manager.vayner_business_info.append(action.thought)
# Extract keyword data
if "keyword" in thought and any(x in thought for x in ["performance", "score", "data"]):
if action.thought not in webui_manager.vayner_keyword_data:
webui_manager.vayner_keyword_data.append(action.thought)
# Extract ranking data
if any(x in thought for x in ["ranking", "rank", "geography", "location"]):
if action.thought not in webui_manager.vayner_ranking_data:
webui_manager.vayner_ranking_data.append(action.thought)
# Also check action results for structured data
if hasattr(action, "result") and action.result and isinstance(action.result, str):
result = action.result.lower()
# Extract structured data from results
if "business" in result and len(action.result) > 10:
if action.result not in webui_manager.vayner_business_info:
webui_manager.vayner_business_info.append(action.result)
if "keyword" in result and len(action.result) > 10:
if action.result not in webui_manager.vayner_keyword_data:
webui_manager.vayner_keyword_data.append(action.result)
if "rank" in result and len(action.result) > 10:
if action.result not in webui_manager.vayner_ranking_data:
webui_manager.vayner_ranking_data.append(action.result)
# Extract current URL for page context
if hasattr(state, "url") and state.url:
page_url = state.url
if "business" in page_url.lower() and not any(page_url in info for info in webui_manager.vayner_business_info):
webui_manager.vayner_business_info.append(f"Page URL: {page_url}")
# Extract visible text from the page if available
if hasattr(state, "text_content") and state.text_content:
# Extract table-like data or lists that might contain keywords or rankings
if "keyword" in state.text_content.lower() and len(state.text_content) > 20:
if state.text_content not in webui_manager.vayner_keyword_data:
webui_manager.vayner_keyword_data.append(state.text_content)
# Extract keyword table data
if not hasattr(webui_manager, "vayner_keyword_table_rows"):
webui_manager.vayner_keyword_table_rows = []
for action in output.action:
# Try to extract keyword, performance, SOV from action.thought or action.result
for field in [getattr(action, "thought", None), getattr(action, "result", None)]:
if field and isinstance(field, str):
# Simple regex/parse for lines like: "keyword: X, performance: Y, sov: Z"
import re
match = re.search(r"keyword[:\s]+([\w\- ]+)[,;\s]+performance[:\s]+([\w\-\.]+)[,;\s]+sov[:\s]+([\w\-\.]+)", field, re.IGNORECASE)
if match:
keyword = match.group(1).strip()
performance = match.group(2).strip()
sov = match.group(3).strip()
# Only add if not already present
if not any(row["keyword"].lower() == keyword.lower() for row in webui_manager.vayner_keyword_table_rows):
webui_manager.vayner_keyword_table_rows.append({
"keyword": keyword,
"performance": performance,
"sov": sov
})
# Update the PDF report with the latest data
business_name = getattr(webui_manager, "vayner_current_business", "Unknown Business")
webui_manager.vayner_pdf_report = generate_live_report(
business_name,
webui_manager.vayner_business_info,
webui_manager.vayner_keyword_data,
webui_manager.vayner_ranking_data,
webui_manager.vayner_screenshots,
webui_manager.vayner_keyword_table_rows,
history.final_result()
)
# Get the PDF report component and update it in real-time
pdf_report_comp = webui_manager.get_component_by_id("vayner_client_research.pdf_report")
if pdf_report_comp and hasattr(webui_manager, "update_queue"):
webui_manager.update_queue.append({
pdf_report_comp: gr.update(
value=webui_manager.vayner_pdf_report,
visible=True
)
})
except Exception as e:
logger.error(f"Error updating PDF report: {e}")
# Format logs similar to the screenshot (NO screenshots in chat)
try:
log_html = f'''
<div style="margin: 5px 0; padding: 10px; background-color: #f8f9fa; border-radius: 4px; border-left: 4px solid #3498db; font-family: 'Courier New', monospace;">
<div style="display: flex; align-items: center; margin-bottom: 5px;">
<span style="background-color: #e0f0ff; color: #3498db; font-weight: bold; padding: 2px 8px; border-radius: 12px; font-size: 12px; margin-right: 10px;">agent</span>
<span style="color: #555; font-size: 12px;">{datetime.now().strftime('%H:%M:%S')}</span>
</div>
'''
# Extract actions
actions_text = []
has_content = False
# Get full json output
action_dump = [action.model_dump(exclude_none=True) for action in output.action]
state_dump = output.current_state.model_dump(exclude_none=True)
# Step info
log_html += f'<div style="font-weight: bold; margin-bottom: 5px; color: #333;">🔶 Step {step_num}</div>'
# Add current URL if available
if hasattr(state, "url") and state.url:
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #888;">URL:</span> {state.url}</div>'
# Add actions
for action in action_dump:
has_content = True
if 'action_type' in action:
action_type = action['action_type'].upper()
# Icon based on action type
if action_type == "CLICK":
icon = "🖱️"
elif action_type == "TYPE":
icon = "⌨️"
elif action_type == "NAVIGATE":
icon = "🔗"
elif action_type == "EXTRACT":
icon = "📋"
elif action_type == "WAIT_FOR_ELEMENT":
icon = "⏳"
else:
icon = "⚙️"
# Format based on action type
if action_type == "CLICK" and 'selector' in action:
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #e67e22;">{icon} CLICK:</span> <code>{action["selector"]}</code></div>'
elif action_type == "TYPE" and 'text' in action:
text = action['text']
if len(text) > 50:
text = text[:47] + "..."
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #2ecc71;">{icon} TYPE:</span> <code>"{text}"</code></div>'
elif action_type == "NAVIGATE" and 'url' in action:
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #3498db;">{icon} NAVIGATE:</span> <code>{action["url"]}</code></div>'
elif action_type == "EXTRACT":
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #9b59b6;">{icon} EXTRACT DATA</span></div>'
elif action_type == "WAIT_FOR_ELEMENT" and 'selector' in action:
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #f39c12;">{icon} WAIT FOR:</span> <code>{action["selector"]}</code></div>'
else:
details = ", ".join([f"{k}={v}" for k, v in action.items() if k != 'action_type' and k != 'thought'])
log_html += f'<div style="margin-bottom: 5px;"><span style="color: #34495e;">{icon} {action_type}:</span> <code>{details}</code></div>'
# Include thoughts with thinking emoji
if 'thought' in action and action['thought']:
thought = action['thought'].strip()
if len(thought) > 150:
thought = thought[:147] + "..."
log_html += f'<div style="margin: 5px 0 10px 15px; color: #7f8c8d; font-style: italic;">💭 {thought}</div>'
# Close log div
log_html += '</div>'
# If no actions found
if not has_content:
log_html = f'''
<div style="margin: 5px 0; padding: 10px; background-color: #f8f9fa; border-radius: 4px; border-left: 4px solid #e74c3c; font-family: 'Courier New', monospace;">
<div style="display: flex; align-items: center; margin-bottom: 5px;">
<span style="background-color: #ffe0e0; color: #e74c3c; font-weight: bold; padding: 2px 8px; border-radius: 12px; font-size: 12px; margin-right: 10px;">agent</span>
<span style="color: #555; font-size: 12px;">{datetime.now().strftime('%H:%M:%S')}</span>
</div>
<div style="font-weight: bold; margin-bottom: 5px; color: #333;">⚠️ Step {step_num} - No actions recorded</div>
</div>
'''
except Exception as e:
logger.error(f"Error formatting step output: {e}")
log_html = f'''
<div style="margin: 5px 0; padding: 10px; background-color: #f8f9fa; border-radius: 4px; border-left: 4px solid #e74c3c; font-family: 'Courier New', monospace;">
<div style="display: flex; align-items: center; margin-bottom: 5px;">
<span style="background-color: #ffe0e0; color: #e74c3c; font-weight: bold; padding: 2px 8px; border-radius: 12px; font-size: 12px; margin-right: 10px;">error</span>
</div>
<div style="font-weight: bold; margin-bottom: 5px; color: #333;">⚠️ Error formatting Step {step_num}</div>
<div style="color: #e74c3c;">{str(e)}</div>
</div>
'''
# Add to chat history
webui_manager.vayner_chat_history.append(
{"role": "assistant", "content": log_html}
)
def done_callback(history):
logger.info(f"Vayner research task finished. Duration: {history.total_duration_seconds():.2f}s")
final_summary = "**Task Completed**\n"
final_summary += f"- Duration: {history.total_duration_seconds():.2f} seconds\n"
final_result = history.final_result()
if final_result:
final_summary += f"- Final Result: {final_result}\n"
# --- FIX: Parse final_result for keywords and update table ---
import re
if not hasattr(webui_manager, "vayner_keyword_table_rows"):
webui_manager.vayner_keyword_table_rows = []
# Accept both string and dict/list results
if isinstance(final_result, str):
# 1. Parse markdown/pipe table
lines = [line.strip() for line in final_result.splitlines() if line.strip()]
table_start = -1
for i, line in enumerate(lines):
if re.match(r"\|?\s*keyword\s*\|\s*performance\s*\|\s*sov\s*\|?", line, re.IGNORECASE):
table_start = i
break
if table_start != -1 and table_start + 2 < len(lines):
# Table header, separator, then data rows
for row in lines[table_start+2:]:
if not row.startswith("|"):
continue
cells = [c.strip() for c in row.strip("|").split("|")]
if len(cells) >= 3:
keyword, performance, sov = cells[:3]
if keyword and performance and sov:
if not any(row_item["keyword"].lower() == keyword.lower() for row_item in webui_manager.vayner_keyword_table_rows):
webui_manager.vayner_keyword_table_rows.append({
"keyword": keyword,
"performance": performance,
"sov": sov
})
# 2. Also parse lines like: "keyword: X, performance: Y, sov: Z"
for line in lines:
match = re.search(r"keyword[:\s]+([\w\- ]+)[,;\s]+performance[:\s]+([\w\-\.]+)[,;\s]+sov[:\s]+([\w\-\.]+)", line, re.IGNORECASE)
if match:
keyword = match.group(1).strip()
performance = match.group(2).strip()
sov = match.group(3).strip()
if not any(row_item["keyword"].lower() == keyword.lower() for row_item in webui_manager.vayner_keyword_table_rows):
webui_manager.vayner_keyword_table_rows.append({
"keyword": keyword,
"performance": performance,
"sov": sov
})
elif isinstance(final_result, list):
for item in final_result:
if isinstance(item, dict):
keyword = item.get("keyword")
performance = item.get("performance")
sov = item.get("sov")
if keyword and performance and sov:
if not any(row_item["keyword"].lower() == keyword.lower() for row_item in webui_manager.vayner_keyword_table_rows):
webui_manager.vayner_keyword_table_rows.append({
"keyword": keyword,
"performance": performance,
"sov": sov
})
errors = history.errors()
if errors and any(errors):
final_summary += f"- **Errors:**\n```\n{errors}\n```\n"
else:
final_summary += "- Status: Success\n"
webui_manager.vayner_chat_history.append(
{"role": "assistant", "content": final_summary}
)
# Generate PDF report using the current live data collections
try:
business_name = getattr(webui_manager, "vayner_current_business", "Unknown Business")
webui_manager.vayner_pdf_report = generate_live_report(
business_name,
webui_manager.vayner_business_info,
webui_manager.vayner_keyword_data,
webui_manager.vayner_ranking_data,
webui_manager.vayner_screenshots,
webui_manager.vayner_keyword_table_rows,
final_result
)
except Exception as e:
logger.error(f"Error generating PDF report: {e}", exc_info=True)
webui_manager.vayner_pdf_report = f"<div class='error'>Error generating report: {str(e)}</div>"
# Initialize controller and browser
try:
if not webui_manager.vayner_controller:
webui_manager.vayner_controller = CustomController()
if not webui_manager.vayner_browser:
webui_manager.vayner_browser = CustomBrowser(
config=BrowserConfig(
headless=headless,
disable_security=disable_security,
browser_binary_path=None,
new_context_config=BrowserContextConfig(
window_width=window_w,
window_height=window_h,
)
)
)
if not webui_manager.vayner_browser_context:
context_config = BrowserContextConfig(
save_recording_path=save_recording_path,
save_downloads_path=save_download_path,
window_height=window_h,
window_width=window_w,
)
webui_manager.vayner_browser_context = (
await webui_manager.vayner_browser.new_context(config=context_config)
)
# Initialize agent
if not webui_manager.vayner_agent:
webui_manager.vayner_agent = BrowserUseAgent(
task=task,
llm=main_llm,
browser=webui_manager.vayner_browser,
browser_context=webui_manager.vayner_browser_context,
controller=webui_manager.vayner_controller,
register_new_step_callback=step_callback,
register_done_callback=done_callback,
use_vision=use_vision,
max_input_tokens=128000,
max_actions_per_step=10,
source="vayner_research",
)
else:
webui_manager.vayner_agent.add_new_task(task)
# Run the agent
agent_run_coro = webui_manager.vayner_agent.run(max_steps=50)
agent_task = asyncio.create_task(agent_run_coro)
webui_manager.vayner_current_task = agent_task
# Monitor the task and update UI
last_chat_len = len(webui_manager.vayner_chat_history)
while not agent_task.done():
# Update Chatbot if new messages arrived
if len(webui_manager.vayner_chat_history) > last_chat_len:
yield {
chatbot_comp: gr.update(value=webui_manager.vayner_chat_history)
}
last_chat_len = len(webui_manager.vayner_chat_history)
# Update Browser View
if webui_manager.vayner_browser_context:
try:
screenshot_b64 = await webui_manager.vayner_browser_context.take_screenshot()
if screenshot_b64:
html_content = f'<img src="data:image/jpeg;base64,{screenshot_b64}" style="width:{stream_vw}vw; height:{stream_vh}vh; border:1px solid #ccc;">'
yield {
browser_view_comp: gr.update(value=html_content, visible=True)
}
except Exception as e:
logger.debug(f"Failed to capture screenshot: {e}")
await asyncio.sleep(0.5) # Polling interval
# Wait for the task to complete
await agent_task
# Show PDF Report if generated
if hasattr(webui_manager, "vayner_pdf_report") and webui_manager.vayner_pdf_report:
yield {
run_button_comp: gr.update(value="▶️ Research Client", interactive=True),
stop_button_comp: gr.update(interactive=False),
chatbot_comp: gr.update(value=webui_manager.vayner_chat_history),
pdf_report_comp: gr.update(value=webui_manager.vayner_pdf_report, visible=True)
}
else:
# Update UI when complete without PDF report
yield {
run_button_comp: gr.update(value="▶️ Research Client", interactive=True),
stop_button_comp: gr.update(interactive=False),
chatbot_comp: gr.update(value=webui_manager.vayner_chat_history)
}
except Exception as e:
logger.error(f"Error during Vayner research: {e}", exc_info=True)
error_message = f"**Error during research:**\n```\n{str(e)}\n```"
webui_manager.vayner_chat_history.append(
{"role": "assistant", "content": error_message}
)
yield {
chatbot_comp: gr.update(value=webui_manager.vayner_chat_history),
run_button_comp: gr.update(value="▶️ Research Client", interactive=True),
stop_button_comp: gr.update(interactive=False),
pdf_report_comp: gr.update(visible=False)
}
gr.Error(f"Research task failed: {e}")
async def handle_submit(webui_manager: WebuiManager, business_name: str):
"""Handles click on the Research Client button."""
if not business_name.strip():
gr.Warning("Please enter a business name")
yield {}
else:
# Store the current business name
webui_manager.vayner_current_business = business_name.strip()
# Reset report data collections
webui_manager.vayner_screenshots = []
webui_manager.vayner_business_info = []
webui_manager.vayner_keyword_data = []
webui_manager.vayner_ranking_data = []
webui_manager.vayner_keyword_table_rows = [] # Reset keyword table rows
# Initialize empty report (cover and second page only)
webui_manager.vayner_pdf_report = generate_live_report(
business_name.strip(),
[], [], [], [], []
)
# Get PDF report component
pdf_report_comp = webui_manager.get_component_by_id("vayner_client_research.pdf_report")
# Show the cover/second page immediately
yield {
pdf_report_comp: gr.update(
value=webui_manager.vayner_pdf_report,
visible=True
)
}
# Initialize update queue
webui_manager.update_queue = []
# Use async generator to stream updates
components = {} # Will be populated by components in run_vayner_research
async for update in run_vayner_research(webui_manager, components, business_name.strip()):
# Include any queued PDF report updates
while webui_manager.update_queue:
pdf_updates = webui_manager.update_queue.pop(0)
update.update(pdf_updates)
yield update
async def handle_stop(webui_manager: WebuiManager):
"""Handles clicks on the 'Stop' button."""
logger.info("Stop button clicked.")
agent = webui_manager.vayner_agent
task = webui_manager.vayner_current_task
if agent and task and not task.done():
# Safely try to stop the agent
try:
if hasattr(agent, 'stop'):
agent.stop()
else:
# Alternative method
agent.state.stopped = True
agent.state.paused = False
except Exception as e:
logger.warning(f"Error stopping agent: {e}")
task.cancel()
try:
await asyncio.wait_for(task, timeout=2.0)
except (asyncio.CancelledError, asyncio.TimeoutError, Exception):
pass
run_button_comp = webui_manager.get_component_by_id("vayner_client_research.run_button")
stop_button_comp = webui_manager.get_component_by_id("vayner_client_research.stop_button")
yield {
run_button_comp: gr.update(value="▶️ Research Client", interactive=True),
stop_button_comp: gr.update(interactive=False)
}
else:
yield {}
async def handle_clear(webui_manager: WebuiManager):
"""Handles clicks on the 'Clear' button."""
logger.info("Clear button clicked.")
# Stop any running task
task = webui_manager.vayner_current_task
if task and not task.done():
# Stop the agent instead of using handle_stop
try:
agent = webui_manager.vayner_agent
if agent and hasattr(agent, 'stop'):
agent.stop()
elif agent:
agent.state.stopped = True
agent.state.paused = False
# Cancel the task
task.cancel()
try:
await asyncio.wait_for(task, timeout=1.0)
except (asyncio.CancelledError, asyncio.TimeoutError, Exception):
pass
except Exception as e:
logger.warning(f"Error stopping agent: {e}")
# Reset the chat history and PDF report
webui_manager.vayner_chat_history = []
webui_manager.vayner_pdf_report = generate_live_report(
"Business Name",
[], [], [], [], []
)
# Reset data collections for PDF report
webui_manager.vayner_screenshots = []
webui_manager.vayner_business_info = []
webui_manager.vayner_keyword_data = []
webui_manager.vayner_ranking_data = []
webui_manager.vayner_keyword_table_rows = []
webui_manager.vayner_current_business = "Business Name"
webui_manager.update_queue = []
# Get components
chatbot_comp = webui_manager.get_component_by_id("vayner_client_research.chatbot")
run_button_comp = webui_manager.get_component_by_id("vayner_client_research.run_button")
stop_button_comp = webui_manager.get_component_by_id("vayner_client_research.stop_button")
browser_view_comp = webui_manager.get_component_by_id("vayner_client_research.browser_view")
business_name_comp = webui_manager.get_component_by_id("vayner_client_research.business_name")
pdf_report_comp = webui_manager.get_component_by_id("vayner_client_research.pdf_report")
yield {
chatbot_comp: gr.update(value=[]),
run_button_comp: gr.update(value="▶️ Research Client", interactive=True),
stop_button_comp: gr.update(interactive=False),
browser_view_comp: gr.update(value="<div style='text-align:center;'>Browser View</div>"),
business_name_comp: gr.update(value=""),
pdf_report_comp: gr.update(value=webui_manager.vayner_pdf_report, visible=True)
}
def create_vayner_client_research_tab(webui_manager: WebuiManager):
"""
Create the Vayner Client Research tab with specialized agent functionality.
"""
# Initialize manager for Vayner client research
webui_manager.init_vayner_client_research()
# Create UI layout with left panel for agent interaction and right panel for browser view
with gr.Row(elem_id="vayner_client_research_container"):
# Left Panel - Agent Interaction (30% width)
with gr.Column(scale=3):
gr.Markdown("### Vayner Client Research Agent")
chatbot = gr.Chatbot(
value=webui_manager.vayner_chat_history,
label="Agent Interaction",
height=700,
show_copy_button=True,
type="messages"
)
with gr.Row():
business_name = gr.Textbox(
label="Business Name",
placeholder="Enter the business name to research",
lines=1
)
with gr.Row():
run_button = gr.Button("▶️ Research Client", variant="primary", scale=3)
stop_button = gr.Button("⏹️ Stop", interactive=False, variant="stop", scale=2)
clear_button = gr.Button("🗑️ Clear", variant="secondary", scale=2)
# Right Panel - Browser View (70% width)
with gr.Column(scale=7):
with gr.Tabs():
with gr.TabItem("Browser View"):
browser_view = gr.HTML(
value="<div style='width:100%; height:700px; display:flex; justify-content:center; align-items:center; border:1px solid #ccc; background-color:#f0f0f0;'><p>Browser view will appear here during research</p></div>",
label="Browser Live View",
)
with gr.TabItem("PDF Report"):
pdf_report = gr.HTML(
value="<div style='width:100%; height:700px; display:flex; justify-content:center; align-items:center; border:1px solid #ccc; background-color:#f0f0f0;'><p>PDF Report will appear here after task completion</p></div>",
label="Research Report",
visible=False
)
# Store components in manager
tab_components = {
"chatbot": chatbot,
"business_name": business_name,
"run_button": run_button,
"stop_button": stop_button,
"clear_button": clear_button,
"browser_view": browser_view,
"pdf_report": pdf_report
}
webui_manager.add_components("vayner_client_research", tab_components)
# Wrapper functions for button handlers
async def submit_wrapper(business_name_value):
async for update in handle_submit(webui_manager, business_name_value):
yield update
async def stop_wrapper():
async for update in handle_stop(webui_manager):
yield update
async def clear_wrapper():
async for update in handle_clear(webui_manager):
yield update
# Connect event handlers
run_button.click(
fn=submit_wrapper,
inputs=[business_name],
outputs=list(tab_components.values())
)
business_name.submit(
fn=submit_wrapper,
inputs=[business_name],
outputs=list(tab_components.values())
)
stop_button.click(
fn=stop_wrapper,
inputs=None,
outputs=list(tab_components.values())
)
clear_button.click(
fn=clear_wrapper,
inputs=None,
outputs=list(tab_components.values())
)
|