Spaces:
Runtime error
Runtime error
File size: 118,214 Bytes
482b8db 5d883e0 482b8db 5d883e0 482b8db 586f41e 482b8db 903627b 482b8db b5b37ba 482b8db 903627b 482b8db 5d883e0 482b8db 5d883e0 482b8db 5d883e0 482b8db 903627b 482b8db 7803933 482b8db 7803933 482b8db e91af4a 482b8db e91af4a 482b8db d38f758 482b8db 46a0267 e91af4a 46a0267 d38f758 46a0267 d38f758 46a0267 d38f758 46a0267 d38f758 46a0267 d38f758 482b8db d38f758 482b8db 46a0267 482b8db d38f758 482b8db 46a0267 482b8db d38f758 482b8db 46a0267 482b8db 46a0267 482b8db 46a0267 482b8db 46a0267 482b8db 46a0267 482b8db d38f758 482b8db d38f758 482b8db d38f758 482b8db d38f758 46a0267 d38f758 482b8db d38f758 482b8db d38f758 482b8db e91af4a 482b8db e58f0de 482b8db f48bf9a 482b8db c909ebf 9686ede 2c7270f 482b8db 9686ede 482b8db 9686ede 482b8db 9686ede 482b8db |
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 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112 2113 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128 2129 2130 2131 2132 2133 2134 2135 2136 2137 2138 2139 2140 2141 2142 2143 2144 2145 2146 2147 2148 2149 2150 2151 2152 2153 2154 2155 2156 2157 2158 2159 2160 2161 2162 2163 2164 2165 2166 2167 2168 2169 2170 2171 2172 2173 2174 2175 2176 2177 2178 2179 2180 2181 2182 2183 2184 2185 2186 2187 2188 2189 2190 2191 2192 2193 2194 2195 2196 2197 2198 2199 2200 2201 2202 2203 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 2219 2220 2221 2222 2223 2224 2225 2226 2227 2228 2229 2230 2231 2232 2233 2234 2235 2236 2237 2238 2239 2240 2241 2242 2243 2244 2245 2246 2247 2248 2249 2250 2251 2252 2253 2254 2255 2256 2257 2258 2259 2260 2261 2262 2263 2264 2265 2266 2267 2268 2269 2270 2271 2272 2273 2274 2275 2276 2277 2278 2279 2280 2281 2282 2283 2284 2285 2286 2287 2288 2289 2290 2291 2292 2293 2294 2295 2296 2297 2298 2299 2300 2301 2302 2303 2304 2305 2306 2307 2308 2309 2310 2311 2312 2313 2314 2315 2316 2317 2318 2319 2320 2321 2322 2323 2324 2325 2326 2327 2328 2329 2330 2331 2332 2333 2334 2335 2336 2337 2338 2339 2340 2341 2342 |
# Lectūra Research Demo: A Multi-Agent Tool for Self-taught Mastery.
# Author: Jaward Sesay
# © Lectūra Labs. All rights reserved.
import os
import json
import re
import gradio as gr
import asyncio
import logging
import torch
import zipfile
import shutil
import datetime
from serpapi import GoogleSearch
from pydantic import BaseModel
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import HandoffTermination, TextMentionTermination
from autogen_agentchat.teams import Swarm
from autogen_agentchat.ui import Console
from autogen_agentchat.messages import TextMessage, HandoffMessage, StructuredMessage
from autogen_ext.models.anthropic import AnthropicChatCompletionClient
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_ext.models.azure import AzureAIChatCompletionClient
from azure.core.credentials import AzureKeyCredential
import traceback
import soundfile as sf
import tempfile
from pydub import AudioSegment
from TTS.api import TTS
import markdown
import PyPDF2
import io
import copy
from pathlib import Path
import time
def get_instructor_name(speaker):
instructor_names = {
"feynman.mp3": "Professor Richard Feynman",
"einstein.mp3": "Professor Albert Einstein",
"samantha.mp3": "Professor Samantha",
"socrates.mp3": "Professor Socrates",
"professor_lectura_male.mp3": "Professor Lectūra"
}
return instructor_names.get(speaker, "Professor Lectūra")
# Set up logging
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s - %(levelname)s - %(message)s",
handlers=[
logging.FileHandler("lecture_generation.log"),
logging.StreamHandler()
]
)
logger = logging.getLogger(__name__)
# Set up environment
OUTPUT_DIR = os.path.join(os.getcwd(), "outputs")
UPLOAD_DIR = os.path.join(os.getcwd(), "uploads")
os.makedirs(OUTPUT_DIR, exist_ok=True)
os.makedirs(UPLOAD_DIR, exist_ok=True)
logger.info(f"Using output directory: {OUTPUT_DIR}")
logger.info(f"Using upload directory: {UPLOAD_DIR}")
os.environ["COQUI_TOS_AGREED"] = "1"
# Initialize TTS model
device = "cuda" if torch.cuda.is_available() else "cpu"
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
logger.info("TTS model initialized on %s", device)
# Define model for slide data
class Slide(BaseModel):
title: str
content: str
class SlidesOutput(BaseModel):
slides: list[Slide]
# Search tool using SerpApi
def search_web(query: str, serpapi_key: str) -> str:
try:
params = {
"q": query,
"engine": "google",
"api_key": serpapi_key,
"num": 5
}
search = GoogleSearch(params)
results = search.get_dict()
if "error" in results:
logger.error("SerpApi error: %s", results["error"])
return None
if "organic_results" not in results or not results["organic_results"]:
logger.info("No search results found for query: %s", query)
return None
formatted_results = []
for item in results["organic_results"][:5]:
title = item.get("title", "No title")
snippet = item.get("snippet", "No snippet")
link = item.get("link", "No link")
formatted_results.append(f"Title: {title}\nSnippet: {snippet}\nLink: {link}\n")
formatted_output = "\n".join(formatted_results)
logger.info("Successfully retrieved search results for query: %s", query)
return formatted_output
except Exception as e:
logger.error("Unexpected error during search: %s", str(e))
return None
def create_search_web_with_key(serpapi_key: str):
def search_web_with_key(query: str) -> str:
return search_web(query, serpapi_key)
return search_web_with_key
# Custom renderer for slides - Markdown to HTML
def render_md_to_html(md_content: str) -> str:
try:
html_content = markdown.markdown(md_content, extensions=['extra', 'fenced_code', 'tables'])
return html_content
except Exception as e:
logger.error("Failed to render Markdown to HTML: %s", str(e))
return "<div>Error rendering content</div>"
# Slide tool for generating HTML slides used by slide_agent
def create_slides(slides: list[dict], title: str, instructor_name: str, output_dir: str = OUTPUT_DIR) -> list[str]:
try:
html_files = []
template_file = os.path.join(os.getcwd(), "slide_template.html")
with open(template_file, "r", encoding="utf-8") as f:
template_content = f.read()
for i, slide in enumerate(slides):
slide_number = i + 1
md_content = slide['content']
html_content = render_md_to_html(md_content)
date = datetime.datetime.now().strftime("%Y-%m-%d")
# Replace placeholders in the template
slide_html = template_content.replace("<!--SLIDE_NUMBER-->", str(slide_number))
slide_html = slide_html.replace("section title", f"{slide['title']}")
slide_html = slide_html.replace("Lecture title", title)
slide_html = slide_html.replace("<!--CONTENT-->", html_content)
slide_html = slide_html.replace("speaker name", instructor_name)
slide_html = slide_html.replace("date", date)
html_file = os.path.join(output_dir, f"slide_{slide_number}.html")
with open(html_file, "w", encoding="utf-8") as f:
f.write(slide_html)
logger.info("Generated HTML slide: %s", html_file)
html_files.append(html_file)
# Save slide content as Markdown files
for i, slide in enumerate(slides):
slide_number = i + 1
md_file = os.path.join(output_dir, f"slide_{slide_number}_content.md")
with open(md_file, "w", encoding="utf-8") as f:
f.write(slide['content'])
logger.info("Saved slide content to Markdown: %s", md_file)
return html_files
except Exception as e:
logger.error("Failed to create HTML slides: %s", str(e))
return []
# Dynamic progress bar
def html_with_progress(label, progress):
return f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<div style="width: 70%; background-color: lightgrey; border-radius: 80px; overflow: hidden; margin-bottom: 20px;">
<div style="width: {progress}%; height: 15px; background-color: #4CAF50; border-radius: 80px;"></div>
</div>
<h2 style="font-style: italic; color: #555 !important;">{label}</h2>
</div>
"""
# Get model client based on selected service
def get_model_client(service, api_key):
if service == "OpenAI-gpt-4o-2024-08-06":
return OpenAIChatCompletionClient(model="gpt-4o-2024-08-06", api_key=api_key)
elif service == "Anthropic-claude-3-sonnet-20240229":
return AnthropicChatCompletionClient(model="claude-3-sonnet-20240229", api_key=api_key)
elif service == "Google-gemini-2.0-flash":
return OpenAIChatCompletionClient(model="gemini-2.0-flash", api_key=api_key)
elif service == "Ollama-llama3.2":
return OllamaChatCompletionClient(model="llama3.2")
elif service == "Azure AI Foundry":
return AzureAIChatCompletionClient(
model="phi-4",
endpoint="https://models.inference.ai.azure.com",
credential=AzureKeyCredential(os.environ.get("GITHUB_TOKEN", "")),
model_info={
"json_output": False,
"function_calling": False,
"vision": False,
"family": "unknown",
"structured_output": False,
}
)
else:
raise ValueError("Invalid service")
# Helper function to clean script text
def clean_script_text(script):
if not script or not isinstance(script, str):
logger.error("Invalid script input: %s", script)
return None
script = re.sub(r"\*\*Slide \d+:.*?\*\*", "", script)
script = re.sub(r"\[.*?\]", "", script)
script = re.sub(r"Title:.*?\n|Content:.*?\n", "", script)
script = script.replace("humanlike", "human-like").replace("problemsolving", "problem-solving")
script = re.sub(r"\s+", " ", script).strip()
if len(script) < 10:
logger.error("Cleaned script too short (%d characters): %s", len(script), script)
return None
logger.info("Cleaned script: %s", script)
return script
# Helper to validate and convert speaker audio
async def validate_and_convert_speaker_audio(speaker_audio):
if not speaker_audio or not os.path.exists(speaker_audio):
logger.warning("Speaker audio file does not exist: %s. Using default voice.", speaker_audio)
default_voice = os.path.join(os.path.dirname(__file__), "professor_lectura_male.mp3")
if os.path.exists(default_voice):
speaker_audio = default_voice
else:
logger.error("Default voice not found. Cannot proceed with TTS.")
return None
try:
ext = os.path.splitext(speaker_audio)[1].lower()
if ext == ".mp3":
logger.info("Converting MP3 to WAV: %s", speaker_audio)
audio = AudioSegment.from_mp3(speaker_audio)
audio = audio.set_channels(1).set_frame_rate(22050)
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False, dir=OUTPUT_DIR) as temp_file:
audio.export(temp_file.name, format="wav")
speaker_wav = temp_file.name
elif ext == ".wav":
speaker_wav = speaker_audio
else:
logger.error("Unsupported audio format: %s", ext)
return None
data, samplerate = sf.read(speaker_wav)
if samplerate < 16000 or samplerate > 48000:
logger.error("Invalid sample rate for %s: %d Hz", speaker_wav, samplerate)
return None
if len(data) < 16000:
logger.error("Speaker audio too short: %d frames", len(data))
return None
if data.ndim == 2:
logger.info("Converting stereo WAV to mono: %s", speaker_wav)
data = data.mean(axis=1)
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False, dir=OUTPUT_DIR) as temp_file:
sf.write(temp_file.name, data, samplerate)
speaker_wav = temp_file.name
logger.info("Validated speaker audio: %s", speaker_wav)
return speaker_wav
except Exception as e:
logger.error("Failed to validate or convert speaker audio %s: %s", speaker_audio, str(e))
return None
# Helper function to generate audio using Coqui TTS API
def generate_xtts_audio(tts, text, speaker_wav, output_path):
if not tts:
logger.error("TTS model not initialized")
return False
try:
tts.tts_to_file(text=text, speaker_wav=speaker_wav, language="en", file_path=output_path)
logger.info("Generated audio for %s", output_path)
return True
except Exception as e:
logger.error("Failed to generate audio for %s: %s", output_path, str(e))
return False
# Helper function to extract JSON from messages
def extract_json_from_message(message):
if isinstance(message, TextMessage):
content = message.content
logger.debug("Extracting JSON from TextMessage: %s", content)
if not isinstance(content, str):
logger.warning("TextMessage content is not a string: %s", content)
return None
pattern = r"```json\s*(.*?)\s*```"
match = re.search(pattern, content, re.DOTALL)
if match:
try:
json_str = match.group(1).strip()
logger.debug("Found JSON in code block: %s", json_str)
return json.loads(json_str)
except json.JSONDecodeError as e:
logger.error("Failed to parse JSON from code block: %s", e)
json_patterns = [
r"\[\s*\{.*?\}\s*\]",
r"\{\s*\".*?\"\s*:.*?\}",
]
for pattern in json_patterns:
match = re.search(pattern, content, re.DOTALL)
if match:
try:
json_str = match.group(0).strip()
logger.debug("Found JSON with pattern %s: %s", pattern, json_str)
return json.loads(json_str)
except json.JSONDecodeError as e:
logger.error("Failed to parse JSON with pattern %s: %s", pattern, e)
try:
for i in range(len(content)):
for j in range(len(content), i, -1):
substring = content[i:j].strip()
if (substring.startswith('{') and substring.endswith('}')) or \
(substring.startswith('[') and substring.endswith(']')):
try:
parsed = json.loads(substring)
if isinstance(parsed, (list, dict)):
logger.info("Found JSON in substring: %s", substring)
return parsed
except json.JSONDecodeError:
continue
except Exception as e:
logger.error("Error in JSON substring search: %s", e)
logger.warning("No JSON found in TextMessage content")
return None
elif isinstance(message, StructuredMessage):
content = message.content
logger.debug("Extracting JSON from StructuredMessage: %s", content)
try:
if isinstance(content, BaseModel):
content_dict = content.dict()
return content_dict.get("slides", content_dict)
return content
except Exception as e:
logger.error("Failed to extract JSON from StructuredMessage: %s, Content: %s", e, content)
return None
elif isinstance(message, HandoffMessage):
logger.debug("Extracting JSON from HandoffMessage context")
for ctx_msg in message.context:
if hasattr(ctx_msg, "content"):
content = ctx_msg.content
logger.debug("HandoffMessage context content: %s", content)
if isinstance(content, str):
pattern = r"```json\s*(.*?)\s*```"
match = re.search(pattern, content, re.DOTALL)
if match:
try:
return json.loads(match.group(1))
except json.JSONDecodeError as e:
logger.error("Failed to parse JSON from HandoffMessage: %s", e)
json_patterns = [
r"\[\s*\{.*?\}\s*\]",
r"\{\s*\".*?\"\s*:.*?\}",
]
for pattern in json_patterns:
match = re.search(pattern, content, re.DOTALL)
if match:
try:
return json.loads(match.group(0))
except json.JSONDecodeError as e:
logger.error("Failed to parse JSON with pattern %s: %s", pattern, e)
elif isinstance(content, dict):
return content.get("slides", content)
logger.warning("No JSON found in HandoffMessage context")
return None
logger.warning("Unsupported message type for JSON extraction: %s", type(message))
return None
# Async update audio preview
async def update_audio_preview(audio_file):
if audio_file:
logger.info("Updating audio preview for file: %s", audio_file)
return audio_file
return None
# Create a zip file of .md, .txt, and .mp3 files
def create_zip_of_files(file_paths):
zip_path = os.path.join(OUTPUT_DIR, "all_lecture_materials.zip")
with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
for file_path in file_paths:
if os.path.exists(file_path):
_, ext = os.path.splitext(file_path)
if ext in ['.md', '.txt', '.mp3']:
zipf.write(file_path, os.path.basename(file_path))
logger.info("Added %s to zip", file_path)
logger.info("Created zip file: %s", zip_path)
return zip_path
# Access local files
def get_gradio_file_url(local_path):
relative_path = os.path.relpath(local_path, os.getcwd())
print(f"Relative path: {relative_path}")
return f"/gradio_api/file={relative_path}"
# Async generate lecture materials and audio
async def on_generate(api_service, api_key, serpapi_key, title, lecture_content_description, lecture_type, lecture_style, speaker_audio, num_slides):
print(f"Received serpapi_key: '{serpapi_key}' (type: {type(serpapi_key)}, length: {len(serpapi_key) if serpapi_key else 0})")
model_client = get_model_client(api_service, api_key)
# Get the speaker from the speaker_audio path
speaker = os.path.basename(speaker_audio) if speaker_audio else "professor_lectura_male.mp3"
logger.info(f"Selected speaker file: {speaker}")
instructor_name = get_instructor_name(speaker)
logger.info(f"Using instructor: {instructor_name}")
# Clear output directory and cache
if os.path.exists(OUTPUT_DIR):
try:
for item in os.listdir(OUTPUT_DIR):
item_path = os.path.join(OUTPUT_DIR, item)
if os.path.isfile(item_path):
os.unlink(item_path)
elif os.path.isdir(item_path):
shutil.rmtree(item_path)
except Exception as e:
logger.error(f"Error clearing output directory: {e}")
raise gr.Error(f"Failed to clear output directory: {str(e)}")
else:
os.makedirs(OUTPUT_DIR)
# Clear browser cache by adding timestamp to file URLs
cache_buster = int(time.time())
# Total slides include user-specified content slides plus Introduction and Closing slides
content_slides = num_slides
total_slides = content_slides + 2
date = datetime.datetime.now().strftime("%Y-%m-%d")
research_agent = AssistantAgent(
name="research_agent",
model_client=model_client,
handoffs=["slide_agent"],
system_message="You are a Research Agent. Use the search_web tool to gather information on the topic and keywords from the initial message. Summarize the findings concisely in a single message, then use the handoff_to_slide_agent tool to pass the task to the Slide Agent. Do not produce any other output.",
tools=[create_search_web_with_key(serpapi_key)]
)
slide_agent = AssistantAgent(
name="slide_agent",
model_client=model_client,
handoffs=["script_agent"],
system_message=f"""
You are a Slide Agent. Using the research from the conversation history and the specified number of content slides ({content_slides}), generate exactly {content_slides} content slides, plus an Introduction slide as the first slide and a Closing slide as the last slide, making a total of {total_slides} slides.
- The Introduction slide (first slide) should have the title "{title}" and content containing only the lecture title, speaker name ({get_instructor_name(speaker_audio)}), and date {date}, centered, in plain text.
- The Closing slide (last slide) should have the title "Closing" and content containing only "The End\nThank you", centered, in plain text.
- The remaining {content_slides} slides should be content slides based on the lecture description, audience type, and lecture style ({lecture_style}), with meaningful titles and content in valid Markdown format. Adapt the content to the lecture style to suit diverse learners:
- Feynman: Explains complex ideas with simplicity, clarity, and enthusiasm, emulating Richard Feynman's teaching style.
- Socratic: Poses thought-provoking questions to guide learners to insights without requiring direct interaction.
- Humorous: Infuses wit and light-hearted anecdotes to make content engaging and memorable.
- Inspirational - Motivating: Uses motivational language and visionary ideas to spark enthusiasm and curiosity.
- Reflective: Encourages introspection with a calm, contemplative tone to deepen understanding.
Output ONLY a JSON array wrapped in ```json ... ``` in a TextMessage, where each slide is an object with 'title' and 'content' keys. After generating the JSON, use the create_slides tool to produce HTML slides, then use the handoff_to_script_agent tool to pass the task to the Script Agent. Do not include any explanatory text or other messages.
Example output for 1 content slide (total 3 slides):
```json
[
{{"title": "Introduction to AI Basics", "content": "AI Basics\n{get_instructor_name(speaker_audio)}\n{date}"}},
{{"title": "What is AI?", "content": "# What is AI?\n- Definition: Systems that mimic human intelligence\n- Key areas: ML, NLP, Robotics"}},
{{"title": "Closing", "content": "The End\nThank you"}}
]
```""",
tools=[create_slides],
output_content_type=None,
reflect_on_tool_use=False
)
script_agent = AssistantAgent(
name="script_agent",
model_client=model_client,
handoffs=["instructor_agent"],
system_message=f"""
You are a Script Agent. Access the JSON array of {total_slides} slides from the conversation history, which includes an Introduction slide, {content_slides} content slides, and a Closing slide. Generate a narration script (1-2 sentences) for each of the {total_slides} slides, summarizing its content in a clear, academically inclined tone. Ensure the lecture is engaging, covers the fundamental requirements of the topic, and aligns with the lecture style ({lecture_style}) to suit diverse learners. The lecture will be delivered by {instructor_name}.
Output ONLY a JSON array wrapped in ```json ... ``` with exactly {total_slides} strings, one script per slide, in the same order. Ensure the JSON is valid and complete. After outputting, use the handoff_to_instructor_agent tool. If scripts cannot be generated, retry once.
Example for 3 slides (1 content slide):
```json
[
"Welcome to the lecture on AI Basics. I am {instructor_name}, and today we will explore the fundamentals of artificial intelligence.",
"Let us begin by defining artificial intelligence: it refers to systems that mimic human intelligence, spanning key areas such as machine learning, natural language processing, and robotics.",
"That concludes our lecture on AI Basics. Thank you for your attention, and I hope you found this session insightful."
]
```""",
output_content_type=None,
reflect_on_tool_use=False
)
def get_instructor_prompt(speaker, lecture_style):
base_prompts = {
"feynman.mp3": f"You are {instructor_name}, known for your ability to explain complex concepts with remarkable clarity and enthusiasm. Your teaching style is characterized by:",
"einstein.mp3": f"You are {instructor_name}, known for your profound insights and ability to connect abstract concepts to the physical world. Your teaching style is characterized by:",
"samantha.mp3": f"You are {instructor_name}, known for your engaging and accessible approach to teaching. Your teaching style is characterized by:",
"socrates.mp3": f"You are {instructor_name}, known for your method of questioning and guiding students to discover knowledge themselves. Your teaching style is characterized by:",
"professor_lectura_male.mp3": f"You are {instructor_name}, known for your clear and authoritative teaching style. Your teaching style is characterized by:"
}
style_characteristics = {
"Feynman - Simplifies complex ideas with enthusiasm": """
- Breaking down complex ideas into simple, understandable parts
- Using analogies and real-world examples
- Maintaining enthusiasm and curiosity throughout
- Encouraging critical thinking and questioning
- Making abstract concepts tangible and relatable""",
"Socratic - Guides insights with probing questions": """
- Using thought-provoking questions to guide understanding
- Encouraging self-discovery and critical thinking
- Challenging assumptions and exploring implications
- Building knowledge through dialogue and inquiry
- Fostering intellectual curiosity and reflection""",
"Inspirational - Sparks enthusiasm with visionary ideas": """
- Connecting concepts to broader implications and possibilities
- Using motivational language and visionary thinking
- Inspiring curiosity and wonder about the subject
- Highlighting the transformative potential of knowledge
- Encouraging students to think beyond conventional boundaries""",
"Reflective - Promotes introspection with a calm tone": """
- Creating a contemplative learning environment
- Encouraging deep thinking and personal connection
- Using a calm, measured delivery
- Promoting self-reflection and understanding
- Building connections between concepts and personal experience""",
"Humorous - Uses wit and anecdotes for engaging content": """
- Incorporating relevant humor and anecdotes
- Making learning enjoyable and memorable
- Using wit to highlight key concepts
- Creating an engaging and relaxed atmosphere
- Balancing entertainment with educational value"""
}
base_prompt = base_prompts.get(speaker, base_prompts["feynman.mp3"])
style_prompt = style_characteristics.get(lecture_style, style_characteristics["Feynman - Simplifies complex ideas with enthusiasm"])
return f"""{base_prompt}
{style_prompt}
Review the slides and scripts from the conversation history to ensure coherence, completeness, and that exactly {total_slides} slides and {total_slides} scripts are received, including the Introduction and Closing slides. Verify that HTML slide files exist in the outputs directory and align with the lecture style ({lecture_style}). Output a confirmation message summarizing the number of slides, scripts, and HTML files status. If slides, scripts, or HTML files are missing, invalid, or do not match the expected count ({total_slides}), report the issue clearly. Use 'TERMINATE' to signal completion.
Example: 'Received {total_slides} slides, {total_slides} scripts, and HTML files. Lecture is coherent and aligns with {lecture_style} style. TERMINATE'
"""
instructor_agent = AssistantAgent(
name="instructor_agent",
model_client=model_client,
handoffs=[],
system_message=get_instructor_prompt(speaker_audio, lecture_style)
)
swarm = Swarm(
participants=[research_agent, slide_agent, script_agent, instructor_agent],
termination_condition=HandoffTermination(target="user") | TextMentionTermination("TERMINATE")
)
progress = 0
label = "Researching lecture topic..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
initial_message = f"""
Lecture Title: {title}
Lecture Content Description: {lecture_content_description}
Audience: {lecture_type}
Lecture Style: {lecture_style}
Number of Content Slides: {content_slides}
Please start by researching the topic, or proceed without research if search is unavailable.
"""
logger.info("Starting lecture generation for title: %s with %d content slides (total %d slides), style: %s", title, content_slides, total_slides, lecture_style)
slides = None
scripts = None
html_files = []
error_html = """
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Failed to generate lecture materials</h2>
<p style="margin-top: 20px;">Please try again with different parameters or a different model.</p>
</div>
"""
try:
logger.info("Research Agent starting...")
if serpapi_key:
task_result = await Console(swarm.run_stream(task=initial_message))
else:
logger.warning("No SerpApi key provided, bypassing research phase")
task_result = await Console(swarm.run_stream(task=f"{initial_message}\nNo search available, proceed with slide generation."))
logger.info("Swarm execution completed")
slide_retry_count = 0
script_retry_count = 0
max_retries = 2
for message in task_result.messages:
source = getattr(message, 'source', getattr(message, 'sender', None))
logger.debug("Processing message from %s, type: %s", source, type(message))
if isinstance(message, HandoffMessage):
logger.info("Handoff from %s to %s", source, message.target)
if source == "research_agent" and message.target == "slide_agent":
progress = 25
label = "Slides: generating..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
elif source == "slide_agent" and message.target == "script_agent":
if slides is None:
logger.warning("Slide Agent handoff without slides JSON")
extracted_json = extract_json_from_message(message)
if extracted_json:
slides = extracted_json
logger.info("Extracted slides JSON from HandoffMessage context: %s", slides)
if slides is None or len(slides) != total_slides:
if slide_retry_count < max_retries:
slide_retry_count += 1
logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
retry_message = TextMessage(
content=f"Please generate exactly {total_slides} slides (Introduction, {content_slides} content slides, and Closing) as per your instructions.",
source="user",
recipient="slide_agent"
)
task_result.messages.append(retry_message)
continue
progress = 50
label = "Scripts: generating..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
elif source == "script_agent" and message.target == "instructor_agent":
if scripts is None:
logger.warning("Script Agent handoff without scripts JSON")
extracted_json = extract_json_from_message(message)
if extracted_json:
scripts = extracted_json
logger.info("Extracted scripts JSON from HandoffMessage context: %s", scripts)
progress = 75
label = "Review: in progress..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
elif source == "research_agent" and isinstance(message, TextMessage) and "handoff_to_slide_agent" in message.content:
logger.info("Research Agent completed research")
progress = 25
label = "Slides: generating..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
elif source == "slide_agent" and isinstance(message, (TextMessage, StructuredMessage)):
logger.debug("Slide Agent message received")
extracted_json = extract_json_from_message(message)
if extracted_json:
slides = extracted_json
logger.info("Slide Agent generated %d slides: %s", len(slides), slides)
if len(slides) != total_slides:
if slide_retry_count < max_retries:
slide_retry_count += 1
logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
retry_message = TextMessage(
content=f"Please generate exactly {total_slides} slides (Introduction, {content_slides} content slides, and Closing) as per your instructions.",
source="user",
recipient="slide_agent"
)
task_result.messages.append(retry_message)
continue
# Generate HTML slides with instructor name
html_files = create_slides(slides, title, instructor_name)
if not html_files:
logger.error("Failed to generate HTML slides")
progress = 50
label = "Scripts: generating..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
else:
logger.warning("No JSON extracted from slide_agent message")
if slide_retry_count < max_retries:
slide_retry_count += 1
logger.info("Retrying slide generation (attempt %d/%d)", slide_retry_count, max_retries)
retry_message = TextMessage(
content=f"Please generate exactly {total_slides} slides (Introduction, {content_slides} content slides, and Closing) as per your instructions.",
source="user",
recipient="slide_agent"
)
task_result.messages.append(retry_message)
continue
elif source == "script_agent" and isinstance(message, (TextMessage, StructuredMessage)):
logger.debug("Script Agent message received")
extracted_json = extract_json_from_message(message)
if extracted_json:
scripts = extracted_json
logger.info("Script Agent generated scripts for %d slides: %s", len(scripts), scripts)
for i, script in enumerate(scripts):
script_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}_script.txt")
try:
with open(script_file, "w", encoding="utf-8") as f:
f.write(script)
logger.info("Saved script to %s", script_file)
except Exception as e:
logger.error("Error saving script to %s: %s", script_file, str(e))
progress = 75
label = "Scripts generated and saved. Reviewing..."
yield (
html_with_progress(label, progress),
[]
)
await asyncio.sleep(0.1)
else:
logger.warning("No JSON extracted from script_agent message")
if script_retry_count < max_retries:
script_retry_count += 1
logger.info("Retrying script generation (attempt %d/%d)", script_retry_count, max_retries)
retry_message = TextMessage(
content=f"Please generate exactly {total_slides} scripts for the {total_slides} slides as per your instructions.",
source="user",
recipient="script_agent"
)
task_result.messages.append(retry_message)
continue
elif source == "instructor_agent" and isinstance(message, TextMessage) and "TERMINATE" in message.content:
logger.info("Instructor Agent completed lecture review: %s", message.content)
progress = 90
label = "Lecture materials ready. Generating lecture speech..."
file_paths = [f for f in os.listdir(OUTPUT_DIR) if f.endswith(('.md', '.txt'))]
file_paths.sort()
file_paths = [os.path.join(OUTPUT_DIR, f) for f in file_paths]
yield (
html_with_progress(label, progress),
file_paths
)
await asyncio.sleep(0.1)
logger.info("Slides state: %s", "Generated" if slides else "None")
logger.info("Scripts state: %s", "Generated" if scripts else "None")
logger.info("HTML files state: %s", "Generated" if html_files else "None")
if not slides or not scripts:
error_message = f"Failed to generate {'slides and scripts' if not slides and not scripts else 'slides' if not slides else 'scripts'}"
error_message += f". Received {len(slides) if slides else 0} slides and {len(scripts) if scripts else 0} scripts."
logger.error("%s", error_message)
logger.debug("Dumping all messages for debugging:")
for msg in task_result.messages:
source = getattr(msg, 'source', getattr(msg, 'sender', None))
logger.debug("Message from %s, type: %s, content: %s", source, type(msg), msg.to_text() if hasattr(msg, 'to_text') else str(msg))
yield (
error_html,
[]
)
return
if len(slides) != total_slides:
logger.error("Expected %d slides, but received %d", total_slides, len(slides))
yield (
f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Incorrect number of slides</h2>
<p style="margin-top: 20px;">Expected {total_slides} slides, but generated {len(slides)}. Please try again.</p>
</div>
""",
[]
)
return
if not isinstance(scripts, list) or not all(isinstance(s, str) for s in scripts):
logger.error("Scripts are not a list of strings: %s", scripts)
yield (
f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Invalid script format</h2>
<p style="margin-top: 20px;">Scripts must be a list of strings. Please try again.</p>
</div>
""",
[]
)
return
if len(scripts) != total_slides:
logger.error("Mismatch between number of slides (%d) and scripts (%d)", len(slides), len(scripts))
yield (
f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Mismatch in slides and scripts</h2>
<p style="margin-top: 20px;">Generated {len(slides)} slides but {len(scripts)} scripts. Please try again.</p>
</div>
""",
[]
)
return
# Access the generated HTML files
html_file_urls = [get_gradio_file_url(html_file) for html_file in html_files]
audio_urls = [None] * len(scripts)
audio_timeline = ""
for i in range(len(scripts)):
audio_timeline += f'<audio id="audio-{i+1}" controls src="" style="display: inline-block; margin: 0 10px; width: 200px;"><span>Loading...</span></audio>'
file_paths = [f for f in os.listdir(OUTPUT_DIR) if f.endswith(('.md', '.txt'))]
file_paths.sort()
file_paths = [os.path.join(OUTPUT_DIR, f) for f in file_paths]
audio_files = []
validated_speaker_wav = await validate_and_convert_speaker_audio(speaker_audio)
if not validated_speaker_wav:
logger.error("Invalid speaker audio after conversion, skipping TTS")
yield (
f"""
<div style=\"display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;\">
<h2 style=\"color: #d9534f;\">Invalid speaker audio</h2>
<p style=\"margin-top: 20px;\">Please upload a valid MP3 or WAV audio file and try again.</p>
</div>
""",
[],
None
)
return
for i, script in enumerate(scripts):
cleaned_script = clean_script_text(script)
audio_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}.mp3")
script_file = os.path.join(OUTPUT_DIR, f"slide_{i+1}_script.txt")
try:
with open(script_file, "w", encoding="utf-8") as f:
f.write(cleaned_script or "")
logger.info("Saved script to %s: %s", script_file, cleaned_script)
except Exception as e:
logger.error("Error saving script to %s: %s",
script_file, str(e))
if not cleaned_script:
logger.error("Skipping audio for slide %d due to empty or invalid script", i + 1)
audio_files.append(None)
audio_urls[i] = None
progress = 90 + ((i + 1) / len(scripts)) * 10
label = f"Generating lecture speech for slide {i + 1}/{len(scripts)}..."
yield (
html_with_progress(label, progress),
file_paths,
None
)
await asyncio.sleep(0.1)
continue
max_audio_retries = 2
for attempt in range(max_audio_retries + 1):
try:
current_text = cleaned_script
if attempt > 0:
sentences = re.split(r"[.!?]+", cleaned_script)
sentences = [s.strip() for s in sentences if s.strip()][:2]
current_text = ". ".join(sentences) + "."
logger.info("Retry %d for slide %d with simplified text: %s", attempt, i + 1, current_text)
success = generate_xtts_audio(tts, current_text, validated_speaker_wav, audio_file)
if not success:
raise RuntimeError("TTS generation failed")
logger.info("Generated audio for slide %d: %s", i + 1, audio_file)
audio_files.append(audio_file)
audio_urls[i] = get_gradio_file_url(audio_file)
progress = 90 + ((i + 1) / len(scripts)) * 10
label = f"Generating lecture speech for slide {i + 1}/{len(scripts)}..."
file_paths.append(audio_file)
yield (
html_with_progress(label, progress),
file_paths,
None
)
await asyncio.sleep(0.1)
break
except Exception as e:
logger.error("Error generating audio for slide %d (attempt %d): %s\n%s", i + 1, attempt, str(e), traceback.format_exc())
if attempt == max_audio_retries:
logger.error("Max retries reached for slide %d, skipping", i + 1)
audio_files.append(None)
audio_urls[i] = None
progress = 90 + ((i + 1) / len(scripts)) * 10
label = f"Generating lecture speech for slide {i + 1}/{len(scripts)}..."
yield (
html_with_progress(label, progress),
file_paths,
None
)
await asyncio.sleep(0.1)
break
# Create zip file with all materials except .html files
zip_file = create_zip_of_files(file_paths)
file_paths.append(zip_file)
# Slide hack: Render the lecture container with iframe containing HTML slides
audio_timeline = ""
for j, url in enumerate(audio_urls):
if url:
audio_timeline += f'<audio id="audio-{j+1}" controls src="{url}" style="display: inline-block; margin: 0 10px; width: 200px;"></audio>'
else:
audio_timeline += f'<audio id="audio-{j+1}" controls src="" style="display: inline-block; margin: 0 10px; width: 200px;"><span>Audio unavailable</span></audio>'
slides_info = json.dumps({"htmlFiles": html_file_urls, "audioFiles": audio_urls})
html_output = f"""
<div id="lecture-data" style="display: none;">{slides_info}</div>
<div id="lecture-container" style="height: 700px; border: 1px solid #ddd; border-radius: 8px; display: flex; flex-direction: column; justify-content: space-between;">
<div id="slide-content" style="flex: 1; overflow: auto; padding: 20px; text-align: center; background-color: #fff;">
<iframe id="slide-iframe" style="width: 100%; height: 100%; border: none;"></iframe>
</div>
<div style="padding: 20px; text-align: center;">
<div class="audio-timeline" style="display: flex; justify-content: center; margin-bottom: 10px;">
{audio_timeline}
</div>
<div style="display: center; justify-content: center; margin-bottom: 10px;">
<button id="prev-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i class="fas fa-step-backward" style="color: #fff !important"></i></button>
<button id="play-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i class="fas fa-play" style="color: #fff !important"></i></button>
<button id="next-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i class="fas fa-step-forward" style="color: #fff !important"></i></button>
<button id="fullscreen-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i style="color: #fff !important" class="fas fa-expand"></i></button>
<button id="reload-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i style="color: #fff !important" class="fas fa-sync-alt"></i></button>
<button id="clear-btn" style="border-radius: 50%; width: 40px; height: 40px; margin: 0 5px; font-size: 1.2em; cursor: pointer; background-color: black"><i style="color: #fff !important" class="fas fa-paint-brush"></i></button>
</div>
</div>
</div>
"""
logger.info("Yielding final lecture materials after audio generation")
# --- YIELD LECTURE CONTEXT FOR AGENTS ---
lecture_context = {
"slides": slides,
"scripts": scripts,
"title": title,
"description": lecture_content_description,
"style": lecture_style,
"audience": lecture_type
}
yield (
html_output,
file_paths,
lecture_context
)
logger.info("Lecture generation completed successfully")
except Exception as e:
logger.error("Error during lecture generation: %s\n%s", str(e), traceback.format_exc())
yield (
f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #000;">Error during lecture generation</h2>
<p style="margin-top: 10px; font-size: 16px;color: #000;">{str(e)}</p>
<p style="margin-top: 20px;">Please try again</p>
</div>
""",
[],
None
)
return
# custom js
js_code = """
() => {
// Function to wait for an element to appear in the DOM
window.addEventListener('load', function () {
gradioURL = window.location.href
if (!gradioURL.endsWith('?__theme=light')) {
window.location.replace(gradioURL + '?__theme=light');
}
});
function waitForElement(selector, callback, maxAttempts = 50, interval = 100) {
let attempts = 0;
const intervalId = setInterval(() => {
const element = document.querySelector(selector);
if (element) {
clearInterval(intervalId);
console.log(`Element ${selector} found after ${attempts} attempts`);
callback(element);
} else if (attempts >= maxAttempts) {
clearInterval(intervalId);
console.error(`Element ${selector} not found after ${maxAttempts} attempts`);
}
attempts++;
}, interval);
}
// Function to check if a file exists with retries
async function checkFileExists(url, maxRetries = 5, delay = 1000) {
for (let i = 0; i < maxRetries; i++) {
try {
const response = await fetch(url, { method: 'HEAD' });
if (response.ok) {
console.log(`File exists: ${url}`);
return true;
}
// Fallback: Some servers disallow HEAD, try GET request
if (response.status === 405 || response.status === 403) {
try {
const getResp = await fetch(url, { method: 'GET' });
if (getResp.ok) {
console.log(`File exists (GET fallback): ${url}`);
return true;
}
} catch (err) {
console.error(`GET fallback failed for ${url}:`, err);
}
}
console.log(`File not found (attempt ${i + 1}/${maxRetries}): ${url}`);
await new Promise(resolve => setTimeout(resolve, delay));
} catch (error) {
console.error(`Error checking file (attempt ${i + 1}/${maxRetries}):`, error);
await new Promise(resolve => setTimeout(resolve, delay));
}
}
return false;
}
// Function to validate and initialize audio elements
async function initializeAudioElements(audioUrls) {
console.log("Initializing audio elements with URLs:", audioUrls);
const audioElements = [];
for (let i = 0; i < audioUrls.length; i++) {
const url = audioUrls[i];
const audioId = `audio-${i+1}`;
let audio = document.getElementById(audioId);
if (!audio) {
console.log(`Creating new audio element: ${audioId}`);
audio = document.createElement('audio');
audio.id = audioId;
audio.controls = true;
audio.style.display = 'inline-block';
audio.style.margin = '0 10px';
audio.style.width = '200px';
// Find the audio container and append the new element
const audioContainer = document.querySelector('.audio-timeline');
if (audioContainer) {
audioContainer.appendChild(audio);
}
}
if (url) {
const exists = await checkFileExists(url);
if (exists) {
audio.src = url;
audio.load();
console.log(`Audio source set for ${audioId}: ${url}`);
} else {
console.error(`Audio file not found: ${url}`);
audio.innerHTML = "<span>Audio unavailable</span>";
}
} else {
console.log(`No URL provided for ${audioId}`);
audio.innerHTML = "<span>No audio</span>";
}
audioElements.push(audio);
}
return audioElements;
}
// Function to render slide with retries
async function renderSlideWithRetry(iframe, url, maxRetries = 5) {
console.log(`Attempting to render slide: ${url}`);
for (let i = 0; i < maxRetries; i++) {
try {
const exists = await checkFileExists(url);
if (exists) {
iframe.src = url;
console.log(`Slide rendered successfully: ${url}`);
return true;
}
console.log(`Slide not found (attempt ${i + 1}/${maxRetries}): ${url}`);
await new Promise(resolve => setTimeout(resolve, 1000));
} catch (error) {
console.error(`Error rendering slide (attempt ${i + 1}/${maxRetries}):`, error);
await new Promise(resolve => setTimeout(resolve, 1000));
}
}
console.error(`Failed to render slide after ${maxRetries} attempts: ${url}`);
return false;
}
// Main initialization function
function initializeSlides() {
console.log("Initializing slides...");
// Wait for lecture-data to load the JSON data
waitForElement('#lecture-data', async (dataElement) => {
if (!dataElement.textContent) {
console.error("Lecture data element is empty");
return;
}
let lectureData;
try {
lectureData = JSON.parse(dataElement.textContent);
console.log("Lecture data parsed successfully:", lectureData);
} catch (e) {
console.error("Failed to parse lecture data:", e);
return;
}
if (!lectureData.htmlFiles || lectureData.htmlFiles.length === 0) {
console.error("No HTML files found in lecture data");
return;
}
let currentSlide = 0;
const totalSlides = lectureData.htmlFiles.length;
let audioElements = [];
let isPlaying = false;
let hasNavigated = false;
let currentAudioIndex = 0;
// Wait for slide-content element
waitForElement('#slide-content', async (slideContent) => {
console.log("Slide content element found");
// Initialize audio elements
audioElements = await initializeAudioElements(lectureData.audioFiles);
console.log(`Initialized ${audioElements.length} audio elements`);
async function renderSlide() {
console.log("Rendering slide:", currentSlide + 1);
const iframe = document.getElementById('slide-iframe');
if (!iframe) {
console.error("Iframe not found");
return;
}
if (currentSlide >= 0 && currentSlide < totalSlides && lectureData.htmlFiles[currentSlide]) {
const htmlUrl = lectureData.htmlFiles[currentSlide];
const success = await renderSlideWithRetry(iframe, htmlUrl);
if (success) {
// Adjust font size based on content
iframe.onload = () => {
try {
const doc = iframe.contentDocument || iframe.contentWindow.document;
const body = doc.body;
if (body) {
const textLength = body.textContent.length;
const screenWidth = window.innerWidth;
let baseFontSize = screenWidth >= 1920 ? 20 : screenWidth >= 1366 ? 18 : 16;
let adjustedFontSize = textLength > 1000 ? baseFontSize * 0.8 :
textLength > 500 ? baseFontSize * 0.9 :
baseFontSize;
adjustedFontSize = Math.max(14, Math.min(24, adjustedFontSize));
const elements = body.getElementsByTagName('*');
for (let elem of elements) {
elem.style.fontSize = `${adjustedFontSize}px`;
}
console.log(`Adjusted font size to ${adjustedFontSize}px`);
}
} catch (error) {
console.error("Error adjusting font size:", error);
}
};
} else {
iframe.src = "about:blank";
console.error("Failed to render slide");
}
} else {
iframe.src = "about:blank";
console.log("No valid slide content for index:", currentSlide);
}
}
async function updateSlide(callback) {
console.log("Updating slide to index:", currentSlide);
await renderSlide();
// Pause and reset all audio elements
audioElements.forEach(audio => {
if (audio && audio.pause) {
audio.pause();
audio.currentTime = 0;
audio.style.border = 'none';
console.log("Paused and reset audio:", audio.id);
}
});
// Wait briefly to ensure pause completes before proceeding
setTimeout(() => {
if (callback) callback();
}, 100);
}
async function updateAudioSources(audioUrls) {
console.log("Updating audio sources:", audioUrls);
for (let i = 0; i < audioUrls.length; i++) {
const url = audioUrls[i];
const audio = audioElements[i];
if (audio && url) {
const exists = await checkFileExists(url);
if (exists) {
if (audio.src !== url) {
audio.src = url;
audio.load();
console.log(`Updated audio-${i+1} src to:`, url);
}
} else {
console.error(`Audio file not found after retries: ${url}`);
audio.src = "";
audio.innerHTML = "<span>Audio unavailable</span>";
}
} else if (!audio) {
console.error(`Audio element at index ${i} not found`);
}
}
}
function prevSlide() {
console.log("Previous button clicked, current slide:", currentSlide);
hasNavigated = true;
if (currentSlide > 0) {
currentSlide--;
updateSlide(() => {
const audio = audioElements[currentSlide];
if (audio && audio.play && isPlaying) {
audio.style.border = '5px solid #50f150';
audio.style.borderRadius = '30px';
audio.play().catch(e => console.error('Audio play failed:', e));
}
});
} else {
console.log("Already at first slide");
}
}
function nextSlide() {
console.log("Next button clicked, current slide:", currentSlide);
hasNavigated = true;
if (currentSlide < totalSlides - 1) {
currentSlide++;
updateSlide(() => {
const audio = audioElements[currentSlide];
if (audio && audio.play && isPlaying) {
audio.style.border = '5px solid #50f150';
audio.style.borderRadius = '30px';
audio.play().catch(e => console.error('Audio play failed:', e));
}
});
} else {
console.log("Already at last slide");
}
}
function playAll() {
console.log("Play button clicked, isPlaying:", isPlaying);
const playBtn = document.getElementById('play-btn');
if (!playBtn) {
console.error("Play button not found");
return;
}
const playIcon = playBtn.querySelector('i');
if (isPlaying) {
// Pause playback
isPlaying = false;
audioElements.forEach(audio => {
if (audio && audio.pause) {
audio.pause();
audio.style.border = 'none';
console.log("Paused audio:", audio.id);
}
});
playIcon.className = 'fas fa-play';
return;
}
// Start playback
isPlaying = true;
playIcon.className = 'fas fa-pause';
currentSlide = 0;
currentAudioIndex = 0;
updateSlide(() => {
function playNext() {
if (currentAudioIndex >= totalSlides || !isPlaying) {
isPlaying = false;
playIcon.className = 'fas fa-play';
audioElements.forEach(audio => {
if (audio) audio.style.border = 'none';
});
console.log("Finished playing all slides or paused");
return;
}
currentSlide = currentAudioIndex;
updateSlide(() => {
const audio = audioElements[currentAudioIndex];
if (audio && audio.play) {
audioElements.forEach(a => a.style.border = 'none');
audio.style.border = '5px solid #16cd16';
audio.style.borderRadius = '30px';
console.log(`Attempting to play audio for slide ${currentAudioIndex + 1}`);
audio.play().then(() => {
console.log(`Playing audio for slide ${currentAudioIndex + 1}`);
audio.onended = null;
audio.addEventListener('ended', () => {
if (isPlaying) {
console.log(`Audio ended for slide ${currentAudioIndex + 1}`);
currentAudioIndex++;
playNext();
}
}, { once: true });
const checkDuration = setInterval(() => {
if (!isPlaying) {
clearInterval(checkDuration);
return;
}
if (audio.duration && audio.currentTime >= audio.duration - 0.1) {
console.log(`Fallback: Audio for slide ${currentAudioIndex + 1} considered ended`);
clearInterval(checkDuration);
audio.onended = null;
currentAudioIndex++;
playNext();
}
}, 1000);
}).catch(e => {
console.error(`Audio play failed for slide ${currentAudioIndex + 1}:`, e);
setTimeout(() => {
if (isPlaying) {
audio.play().then(() => {
console.log(`Retry succeeded for slide ${currentAudioIndex + 1}`);
audio.onended = null;
audio.addEventListener('ended', () => {
if (isPlaying) {
console.log(`Audio ended for slide ${currentAudioIndex + 1}`);
currentAudioIndex++;
playNext();
}
}, { once: true });
}).catch(e => {
console.error(`Retry failed for slide ${currentAudioIndex + 1}:`, e);
currentAudioIndex++;
playNext();
});
}
}, 500);
});
} else {
currentAudioIndex++;
playNext();
}
});
}
playNext();
});
}
function toggleFullScreen() {
console.log("Fullscreen button clicked");
const container = document.getElementById('lecture-container');
if (!container) {
console.error("Lecture container not found");
return;
}
if (!document.fullscreenElement) {
container.requestFullscreen().catch(err => {
console.error('Error enabling full-screen:', err);
});
} else {
document.exitFullscreen();
console.log("Exited fullscreen");
}
}
// Attach event listeners
waitForElement('#prev-btn', (prevBtn) => {
prevBtn.addEventListener('click', prevSlide);
console.log("Attached event listener to prev-btn");
});
waitForElement('#play-btn', (playBtn) => {
playBtn.addEventListener('click', playAll);
console.log("Attached event listener to play-btn");
});
waitForElement('#next-btn', (nextBtn) => {
nextBtn.addEventListener('click', nextSlide);
console.log("Attached event listener to next-btn");
});
waitForElement('#fullscreen-btn', (fullscreenBtn) => {
fullscreenBtn.addEventListener('click', toggleFullScreen);
console.log("Attached event listener to fullscreen-btn");
});
waitForElement('#reload-btn', (reloadBtn) => {
reloadBtn.addEventListener('click', () => {
console.log("Reload button clicked");
currentSlide = 0;
updateAudioSources(lectureData.audioFiles);
renderSlide();
});
console.log("Attached event listener to reload-btn");
});
// Initialize audio sources and render first slide
updateAudioSources(lectureData.audioFiles);
renderSlide();
console.log("Initial slide rendered, starting at slide:", currentSlide + 1);
});
});
}
// Observe DOM changes to detect when lecture container is added
const observer = new MutationObserver((mutations) => {
mutations.forEach((mutation) => {
if (mutation.addedNodes.length) {
const lectureContainer = document.getElementById('lecture-container');
if (lectureContainer) {
console.log("Lecture container detected in DOM");
observer.disconnect();
initializeSlides();
}
}
});
});
observer.observe(document.body, { childList: true, subtree: true });
console.log("Started observing DOM for lecture container");
}
"""
def process_uploaded_file(file):
"""Process uploaded file and extract text content."""
try:
# Determine if file is a NamedString (Gradio string-like object) or file-like object
file_name = os.path.basename(file.name if hasattr(file, 'name') else str(file))
file_path = os.path.join(UPLOAD_DIR, file_name)
# Get file extension
_, ext = os.path.splitext(file_path)
ext = ext.lower()
# Handle PDF files differently
if ext == '.pdf':
# For PDF files, write the raw bytes
if hasattr(file, 'read'):
with open(file_path, 'wb') as f:
f.write(file.read())
else:
# If it's a file path, copy the file
shutil.copy2(str(file), file_path)
# Process PDF file
pdf_reader = PyPDF2.PdfReader(file_path)
text = ""
for page in pdf_reader.pages:
text += page.extract_text() + "\n"
logger.info("Extracted text from PDF: %s", file_path)
return text
# Handle text files
elif ext in ('.txt', '.md'):
# Read content and save to UPLOAD_DIR
if hasattr(file, 'read'): # File-like object
content = file.read()
if isinstance(content, bytes):
content = content.decode('utf-8', errors='replace')
with open(file_path, 'w', encoding='utf-8') as f:
f.write(content)
else: # NamedString or string-like
# If it's a file path, read the file
if os.path.exists(str(file)):
with open(str(file), 'r', encoding='utf-8') as f:
content = f.read()
else:
content = str(file)
with open(file_path, 'w', encoding='utf-8') as f:
f.write(content)
# Clean and return content
cleaned_content = clean_script_text(content)
logger.info("Cleaned content for %s: %s", file_path, cleaned_content[:100] + "..." if len(cleaned_content) > 100 else cleaned_content)
return cleaned_content
else:
raise ValueError(f"Unsupported file format: {ext}")
except Exception as e:
logger.error(f"Error processing file {file_path}: {str(e)}")
raise
async def study_mode_process(file, api_service, api_key):
"""Process uploaded file in study mode."""
max_retries = 1
for attempt in range(max_retries + 1):
try:
# Extract text from file
content = process_uploaded_file(file)
logger.info("Successfully extracted content from file: %s", file)
# Create study agent
logger.info("Initializing model client for service: %s", api_service)
model_client = get_model_client(api_service, api_key)
logger.info("Model client initialized successfully")
study_agent = AssistantAgent(
name="study_agent",
model_client=model_client,
system_message="""You are a Study Agent that analyzes lecture materials and generates appropriate inputs for the lecture generation system.
Analyze the provided content and generate:
1. A concise title (max 10 words)
2. A brief content description (max 20 words)
Output the results in JSON format:
{
"title": "string",
"content_description": "string"
}"""
)
# Process content with study agent
logger.info("Running study agent with content length: %d", len(content))
task_result = await Console(study_agent.run_stream(task=content))
logger.info("Study agent execution completed")
for message in task_result.messages:
extracted_json = extract_json_from_message(message)
if extracted_json and isinstance(extracted_json, dict):
if "title" in extracted_json and "content_description" in extracted_json:
logger.info("Valid JSON output: %s", extracted_json)
return extracted_json
else:
logger.warning("Incomplete JSON output: %s", extracted_json)
raise ValueError("No valid JSON output with title and content_description from study agent")
except Exception as e:
logger.error("Attempt %d/%d failed: %s\n%s", attempt + 1, max_retries + 1, str(e), traceback.format_exc())
if attempt == max_retries:
raise Exception(f"Failed to process file after {max_retries + 1} attempts: {str(e)}")
logger.info("Retrying study mode processing...")
await asyncio.sleep(1) # Brief delay before retry
# Gradio interface
with gr.Blocks(
title="Lectūra AI",
css="""
.gradio-container-5-32-0 .prose * {color: #fd7b00 !important;}
h2, h3 {text-align: center; color: #000 !important;}
.gradio-container-5-29-0 .prose :last-child {color: #fff !important; }
#lecture-container {font-family: 'Times New Roman', Times, serif;}
#slide-content {font-size: 48px; line-height: 1.2;}
#form-group {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px; color: #000; background-color: white;}
#download {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px;}
#uploaded-file {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px;}
#slide-display {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px; background-color: white;}
.gradio-container { background: #fff !important; box-shadow: 0 0 2rem rgba(255, 255, 255, 0.14);padding-top: 30px;}
button {transition: background-color 0.3s;}
button:hover {background-color: #e0e0e0;}
.upload-area {border: 2px dashed #ccc; border-radius: 20px; padding: 40px; text-align: center; cursor: pointer; height: 100%; min-height: 700px; display: flex; flex-direction: column; justify-content: center; align-items: center;}
.upload-area:hover {border-color: #16cd16;}
.upload-area.dragover {border-color: #16cd16; background-color: rgba(22, 205, 22, 0.1);}
.wrap.svelte-1kzox3m {justify-content: center;}
#mode-tabs {border-radius: 30px !important;}
#component-2 {border-radius: 30px; box-shadow: rgba(0, 0, 0, 0.14) 0px 0px 2rem !important; width: 290px;}
#component-0 {align-items: center;justify-content: center;}
#component-26 {box-shadow: rgba(0, 0, 0, 0.14) 0px 0px 2rem !important; border-radius: 30px; height: 970px !important; overflow: auto !important;}
#right-column {padding: 10px !important; height: 100% !important; display: flex !important; flex-direction: column !important; gap: 20px !important;}
#notes-section {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px; background-color: white; padding: 20px; flex: 0 0 auto; display: flex; flex-direction: column; overflow: hidden;}
#chat-section {box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important; border-radius: 30px; background-color: white; padding: 20px; flex: 1; display: flex; flex-direction: column; overflow: hidden; min-height: 760px;}
.note-button {width: 100%; border-radius: 15px; margin-bottom: 10px; padding: 10px; background-color: #f0f0f0; border: none; cursor: pointer; color: #000 !important}
.note-button:hover {background-color: #e0e0e0;}
.notes-list {flex: 1; overflow-y: auto; margin-top: 0px; min-height: 0;}
.chat-input-container {display: flex; gap: 10px; margin-top: auto; padding-top: 20px;}
.chat-input {flex-grow: 1; border-radius: 20px; padding: 10px 20px; border: 1px solid #ddd;background-color: rgb(240, 240, 240)}
.send-button {border-radius: 20px; padding: 10px 25px; background-color: #16cd16; color: white; border: none; cursor: pointer;}
.send-button:hover {background-color: #14b814;}
.back-button {border-radius: 50%; width: 40px; height: 40px; background-color: #f0f0f0; border: none; cursor: pointer; display: flex; align-items: center; justify-content: center;}
.back-button:hover {background-color: #e0e0e0;}
.note-editor {display: none; width: 100%; height: 100%; min-height: 0;}
.note-editor.active {display: flex; flex-direction: column;}
.notes-view {display: flex; flex-direction: column; height: 100%; min-height: 0;}
.notes-view.hidden {display: none;}
.chat-messages {flex: 1; overflow-y: auto; margin-bottom: 20px; min-height: 0;}
#study-guide-btn {margin-bottom: 0px !important}
#component-26 {padding: 20px}
.gradio-container-5-29-0 .prose :last-child {color: black !important;}
#add-note-btn, #study-guide-btn, #quiz-btn, #send-btn{border-radius: 30px !important;}
#chatbot {border-radius: 20px !important;}
#chat-input-row {align-items: center !important;}
.gradio-container { background-color: white !important; color: black !important;}
main {max-width: fit-content !important}
#component-36 {height: 460px !important}
""",
js=js_code,
head='<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/css/all.min.css">'
) as demo:
gr.Markdown("""
## <center>Lectūra: Your AI Genie for Self-taught Mastery.</center>
### <center>(Disclaimer: This demo is part of a submission to the AgentX – LLM Agents MOOC Competition, hosted by Berkeley RDI. © Lectūra Labs. All rights reserved)</center>
### Note: Genarating lecture speech takes a while, given that this demo is running on cpu. Recommend limiting number of slides to 3 on cpu. For faster generation, please run the app with access to GPU.
### Official Website: [https://lecturalabs.com/](https://lecturalabs.com/)""")
with gr.Row():
with gr.Column(scale=1):
with gr.Group(elem_id="mode-tabs"):
mode_tabs = gr.Radio(
choices=["Learn Mode", "Study Mode"],
value="Learn Mode",
label="Mode",
elem_id="mode-tabs",
show_label=False
)
with gr.Row():
# Left column (existing form)
with gr.Column(scale=1):
with gr.Group(elem_id="form-group"):
title = gr.Textbox(label="Lecture Title", placeholder="e.g. Introduction to AI")
lecture_content_description = gr.Textbox(label="Lecture Content Description", placeholder="e.g. Focus on recent advancements")
lecture_type = gr.Dropdown(["Conference", "University", "High school"], label="Audience", value="University")
lecture_style = gr.Dropdown(
["Feynman - Simplifies complex ideas with enthusiasm", "Socratic - Guides insights with probing questions", "Inspirational - Sparks enthusiasm with visionary ideas", "Reflective - Promotes introspection with a calm tone", "Humorous - Uses wit and anecdotes for engaging content"],
label="Lecture Style",
value="Feynman - Simplifies complex ideas with enthusiasm"
)
api_service = gr.Dropdown(
choices=[
"Azure AI Foundry",
"OpenAI-gpt-4o-2024-08-06",
"Anthropic-claude-3-sonnet-20240229",
"Google-gemini-2.0-flash",
"Ollama-llama3.2",
],
label="Model",
value="Google-gemini-2.0-flash"
)
api_key = gr.Textbox(label="Model Provider API Key", type="password", placeholder="Not required for Ollama or Azure AI Foundry (use GITHUB_TOKEN env var)")
serpapi_key = gr.Textbox(label="SerpApi Key (For Research Agent)", type="password", placeholder="Enter your SerpApi key (optional)")
num_slides = gr.Slider(1, 20, step=1, label="Number of Lecture Slides (will add intro and closing slides)", value=3)
speaker_select = gr.Dropdown(
choices=["feynman.mp3", "einstein.mp3", "samantha.mp3", "socrates.mp3", "professor_lectura_male.mp3"],
value="professor_lectura_male.mp3",
label="Select Instructor",
elem_id="speaker-select"
)
speaker_audio = gr.Audio(value="professor_lectura_male.mp3", label="Speaker sample speech (MP3 or WAV)", type="filepath", elem_id="speaker-audio")
generate_btn = gr.Button("Generate Lecture")
# Middle column (existing slide display)
with gr.Column(scale=2):
default_slide_html = """
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 30px; box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important;">
<h2 style="font-style: italic; color: #000 !important;">Waiting for lecture content...</h2>
<p style="margin-top: 10px; font-size: 16px;color: #000 !important">Please Generate lecture content via the form on the left first before lecture begins</p>
</div>
"""
# Study mode upload area
study_mode_html = """
<div class="upload-area" id="upload-area">
<h2 style="margin-top: 20px; color: #000;">Please upload lecture material by clicking the upload button below</h2>
<p style="color: #666;">(only supports .pdf, .txt and .md)</p>
</div>
"""
slide_display = gr.HTML(label="Lecture Slides", value=default_slide_html, elem_id="slide-display")
uploaded_file = gr.File(label="Upload Lecture Material", visible=False, elem_id="uploaded-file")
file_output = gr.File(label="Download Lecture Materials", elem_id="download")
# --- RIGHT COLUMN SPLIT: NOTES (TOP) AND CHAT (BOTTOM) ---
with gr.Column(scale=1, elem_id="right-column"):
# State for notes and lecture context
notes_state = gr.State([]) # List of notes: [{"title": ..., "content": ...}]
lecture_context_state = gr.State({}) # Dict with latest lecture slides/scripts
chat_history_state = gr.State([]) # List of {user, assistant}
with gr.Row():
with gr.Column(scale=1, elem_id="notes-section"):
with gr.Row():
add_note_btn = gr.Button("+ Add note", elem_id="add-note-btn")
study_guide_btn = gr.Button("Study Guide", elem_id="study-guide-btn")
quiz_btn = gr.Button("Quiz Yourself", elem_id="quiz-btn")
note_response = gr.Textbox(label="Response", visible=True, value="Your notes, study guides, and quizzes will appear here...")
notes_list = gr.Dataframe(headers=["Title"], interactive=False, label="Your Notes", elem_id="notes-list")
with gr.Column(visible=False) as note_editor:
note_title = gr.Textbox(label="Note Title", elem_id="note-title")
note_content = gr.Textbox(label="Note Content", lines=10, elem_id="note-content")
with gr.Row():
save_note_btn = gr.Button("Save Note", elem_id="save-note-btn")
back_btn = gr.Button("Back", elem_id="back-btn")
with gr.Column(scale=1, elem_id="chat-section"):
with gr.Column():
chatbot = gr.Chatbot(label="Chat", elem_id="chatbot", height=220, show_copy_button=True, type="messages")
with gr.Row(elem_id="chat-input-row"):
chat_input = gr.Textbox(show_label=False, placeholder="Type your message...", lines=1, elem_id="chat-input", scale=10)
send_btn = gr.Button("Send", elem_id="send-btn", scale=1)
# --- UI LOGIC FOR SHOWING/HIDING RESPONSE COMPONENTS ---
def show_only(component):
return (
gr.update(visible=(component == "note")),
gr.update(visible=(component == "study")),
gr.update(visible=(component == "quiz")),
)
async def add_note_fn(notes, lecture_context, api_service, api_key, title_val, desc_val, style_val, audience_val):
context = get_fallback_lecture_context(lecture_context, title_val, desc_val, style_val, audience_val)
note = await run_note_agent(api_service, api_key, context, "", "")
note_text = (note.get("title", "") + "\n" + note.get("content", "")).strip()
return (
gr.update(value=note_text),
note.get("title", ""),
note.get("content", "")
)
add_note_btn.click(
fn=add_note_fn,
inputs=[notes_state, lecture_context_state, api_service, api_key, title, lecture_content_description, lecture_style, lecture_type],
outputs=[note_response, note_title, note_content]
)
# Study Guide button: generate study guide and show response
async def study_guide_btn_fn(notes, lecture_context, api_service, api_key, title_val, desc_val, style_val, audience_val):
context = get_fallback_lecture_context(lecture_context, title_val, desc_val, style_val, audience_val)
guide = await run_study_agent(api_service, api_key, context)
return gr.update(value=guide)
study_guide_btn.click(
fn=study_guide_btn_fn,
inputs=[notes_state, lecture_context_state, api_service, api_key, title, lecture_content_description, lecture_style, lecture_type],
outputs=[note_response]
)
# Quiz button: generate quiz and show response
async def quiz_btn_fn(notes, lecture_context, api_service, api_key, title_val, desc_val, style_val, audience_val):
context = get_fallback_lecture_context(lecture_context, title_val, desc_val, style_val, audience_val)
quiz = await run_quiz_agent(api_service, api_key, context)
return gr.update(value=quiz)
quiz_btn.click(
fn=quiz_btn_fn,
inputs=[notes_state, lecture_context_state, api_service, api_key, title, lecture_content_description, lecture_style, lecture_type],
outputs=[note_response]
)
# Back button: clear response
back_btn.click(
fn=lambda: gr.update(value="Click any button above to generate content..."),
inputs=[],
outputs=[note_response]
)
async def save_note(note_title_val, note_content_val, notes, lecture_context, api_service, api_key, note_type=None):
note = await run_note_agent(api_service, api_key, get_fallback_lecture_context(lecture_context, note_title_val, note_content_val, "", ""), note_title_val, note_content_val)
# Prefix title with note type if provided
if note_type:
note["title"] = note_type_prefix(note_type, note.get("title", ""))
new_notes = copy.deepcopy(notes)
new_notes.append(note)
# Save note content to a .txt file
note_file = os.path.join(OUTPUT_DIR, f"{note['title']}.txt")
with open(note_file, "w", encoding="utf-8") as f:
f.write(note['content'])
return (
update_notes_list(new_notes),
new_notes,
gr.update(value="Click any button above to generate content...")
)
save_note_btn.click(
fn=save_note,
inputs=[note_title, note_content, notes_state, lecture_context_state, api_service, api_key],
outputs=[notes_list, notes_state, note_response]
)
# --- CHAT AGENT LOGIC ---
async def chat_fn(user_message, chat_history, lecture_context, api_service, api_key, title_val, desc_val):
if not user_message.strip():
return chat_history, "", chat_history, gr.update(), gr.update()
form_update, response = await run_chat_agent(api_service, api_key, lecture_context, chat_history, user_message)
new_history = chat_history.copy()
# Append user message
if user_message:
new_history.append({"role": "user", "content": user_message})
# Append assistant response
if response:
new_history.append({"role": "assistant", "content": response})
title_update = gr.update()
desc_update = gr.update()
if form_update:
title = form_update.get("title")
desc = form_update.get("content_description")
msg = ""
if title:
msg += f"\nLecture Title: {title}"
title_update = gr.update(value=title)
if desc:
msg += f"\nLecture Content Description: {desc}"
desc_update = gr.update(value=desc)
new_history.append({"role": "assistant", "content": msg.strip()})
return new_history, "", new_history, title_update, desc_update
return new_history, "", new_history, title_update, desc_update
send_btn.click(
fn=chat_fn,
inputs=[chat_input, chat_history_state, lecture_context_state, api_service, api_key, title, lecture_content_description],
outputs=[chatbot, chat_input, chat_history_state, title, lecture_content_description]
)
js_code = js_code + """
// Add file upload handling
function initializeFileUpload() {
const uploadArea = document.getElementById('upload-area');
if (!uploadArea) return;
// Create hidden file input
const fileInput = document.createElement('input');
fileInput.type = 'file';
fileInput.accept = '.pdf,.txt,.md';
fileInput.style.display = 'none';
uploadArea.appendChild(fileInput);
// Handle click on the entire upload area
uploadArea.addEventListener('click', (e) => {
if (e.target !== fileInput) {
fileInput.click();
}
});
fileInput.addEventListener('change', (e) => {
const file = e.target.files[0];
if (file) {
const dataTransfer = new DataTransfer();
dataTransfer.items.add(file);
const gradioFileInput = document.querySelector('input[type="file"]');
if (gradioFileInput) {
gradioFileInput.files = dataTransfer.files;
const event = new Event('change', { bubbles: true });
gradioFileInput.dispatchEvent(event);
}
}
});
// Handle drag and drop
['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
uploadArea.addEventListener(eventName, preventDefaults, false);
});
function preventDefaults(e) {
e.preventDefault();
e.stopPropagation();
}
['dragenter', 'dragover'].forEach(eventName => {
uploadArea.addEventListener(eventName, highlight, false);
});
['dragleave', 'drop'].forEach(eventName => {
uploadArea.addEventListener(eventName, unhighlight, false);
});
function highlight(e) {
uploadArea.classList.add('dragover');
}
function unhighlight(e) {
uploadArea.classList.remove('dragover');
}
uploadArea.addEventListener('drop', handleDrop, false);
function handleDrop(e) {
const dt = e.dataTransfer;
const file = dt.files[0];
if (file) {
const dataTransfer = new DataTransfer();
dataTransfer.items.add(file);
const gradioFileInput = document.querySelector('input[type="file"]');
if (gradioFileInput) {
gradioFileInput.files = dataTransfer.files;
const event = new Event('change', { bubbles: true });
gradioFileInput.dispatchEvent(event);
}
}
}
}
// Initialize clear button functionality
function initializeClearButton() {
const clearButton = document.getElementById('clear-btn');
if (clearButton) {
clearButton.addEventListener('click', () => {
const modeTabs = document.querySelector('.mode-tabs input[type="radio"]:checked');
const isStudyMode = modeTabs && modeTabs.value === 'Study Mode';
// Reset all audio elements
const audioElements = document.querySelectorAll('audio');
audioElements.forEach(audio => {
audio.pause();
audio.currentTime = 0;
audio.style.border = 'none';
});
// Reset play button
const playBtn = document.getElementById('play-btn');
if (playBtn) {
const playIcon = playBtn.querySelector('i');
if (playIcon) {
playIcon.className = 'fas fa-play';
}
}
const slideContent = document.getElementById('slide-content');
if (slideContent) {
if (isStudyMode) {
slideContent.innerHTML = `
<div class="upload-area" id="upload-area">
<h2 style="margin-top: 20px; color: #000;">Please upload lecture material by clicking the upload button below</h2>
<p style="color: #666;">(only supports .pdf, .txt and .md)</p>
</div>
`;
initializeFileUpload();
} else {
slideContent.innerHTML = `
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 30px; box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important;">
<h2 style="font-style: italic; color: #000 !important;">Waiting for lecture content...</h2>
<p style="margin-top: 10px; font-size: 16px;color: #000">Please Generate lecture content via the form on the left first before lecture begins</p>
</div>
`;
}
}
});
}
}
// Initialize speaker selection
function initializeSpeakerSelect() {
const speakerSelect = document.getElementById('speaker-select');
const speakerAudio = document.querySelector('#speaker-audio input[type="file"]');
if (speakerSelect && speakerAudio) {
speakerSelect.addEventListener('change', (e) => {
const selectedSpeaker = e.target.value;
// Create a new File object from the selected speaker
fetch(selectedSpeaker)
.then(response => response.blob())
.then(blob => {
const file = new File([blob], selectedSpeaker, { type: 'audio/mpeg' });
const dataTransfer = new DataTransfer();
dataTransfer.items.add(file);
speakerAudio.files = dataTransfer.files;
const event = new Event('change', { bubbles: true });
speakerAudio.dispatchEvent(event);
});
});
}
}
// Initialize file upload when study mode is active
function checkAndInitializeUpload() {
const uploadArea = document.getElementById('upload-area');
if (uploadArea) {
console.log('Initializing file upload...');
initializeFileUpload();
}
initializeClearButton();
initializeSpeakerSelect();
}
// Check immediately and also set up an observer
checkAndInitializeUpload();
const modeObserver = new MutationObserver((mutations) => {
mutations.forEach((mutation) => {
if (mutation.addedNodes.length) {
checkAndInitializeUpload();
}
});
});
modeObserver.observe(document.body, { childList: true, subtree: true });
"""
# Handle mode switching
def switch_mode(mode):
if mode == "Learn Mode":
return default_slide_html, gr.update(visible=True), gr.update(visible=False)
else:
return study_mode_html, gr.update(visible=True), gr.update(visible=True)
mode_tabs.change(
fn=switch_mode,
inputs=[mode_tabs],
outputs=[slide_display, generate_btn, uploaded_file]
)
# Handle file upload in study mode
async def handle_file_upload(file, api_service, api_key):
"""Handle file upload in study mode and validate API key."""
if not file:
yield default_slide_html, None, None
return
# Validate API key or GITHUB_TOKEN for Azure AI Foundry
if not api_key and api_service != "Azure AI Foundry":
error_html = """
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Please input api key first</h2>
<p style="margin-top: 20px;">An API key is required to process uploaded files in Study mode. Please provide a valid API key and try again.</p>
</div>
"""
logger.warning("API key is empty, terminating file upload")
yield error_html, None, None
return
elif api_service == "Azure AI Foundry" and not os.environ.get("GITHUB_TOKEN"):
error_html = """
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">GITHUB_TOKEN not set</h2>
<p style="margin-top: 20px;">Azure AI Foundry requires a GITHUB_TOKEN environment variable. Please set it and try again.</p>
</div>
"""
logger.warning("GITHUB_TOKEN is missing for Azure AI Foundry, terminating file upload")
yield error_html, None, None
return
try:
# Show uploading progress
yield html_with_progress("Uploading Lecture Material...", 25), None, None
await asyncio.sleep(0.1)
# Show processing progress
yield html_with_progress("Processing file...", 50), None, None
await asyncio.sleep(0.1)
# Process file and generate inputs
yield html_with_progress("Researching lecture material...", 75), None, None
await asyncio.sleep(0.1)
result = await study_mode_process(file, api_service, api_key)
# Show success message with updated inputs
success_html = """
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 30px; box-shadow: 0 0 2rem rgba(0, 0, 0, .14) !important;">
<h2 style="font-style: italic; color: #000 !important;">Research on study material completed, you can now generate lecture</h2>
<p style="margin-top: 10px; font-size: 16px;color: #000">The form has been updated with the extracted information. Click Generate Lecture to proceed.</p>
</div>
"""
# Prompt via chat updates only title and description form inputs
yield (
success_html,
result["title"],
result["content_description"]
)
except Exception as e:
error_html = f"""
<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; height: 100%; min-height: 700px; padding: 20px; text-align: center; border: 1px solid #ddd; border-radius: 8px;">
<h2 style="color: #d9534f;">Error processing file</h2>
<p style="margin-top: 20px;">{str(e)}</p>
</div>
"""
logger.error(f"Error processing file: {str(e)}")
yield error_html, None, None
uploaded_file.change(
fn=handle_file_upload,
inputs=[uploaded_file, api_service, api_key],
outputs=[slide_display, title, lecture_content_description]
)
speaker_audio.change(
fn=update_audio_preview,
inputs=speaker_audio,
outputs=speaker_audio
)
generate_btn.click(
fn=on_generate,
inputs=[api_service, api_key, serpapi_key, title, lecture_content_description, lecture_type, lecture_style, speaker_audio, num_slides],
outputs=[slide_display, file_output]
)
# Handle speaker selection
def update_speaker_audio(speaker):
logger.info(f"Speaker selection changed to: {speaker}")
return speaker
speaker_select.change(
fn=update_speaker_audio,
inputs=[speaker_select],
outputs=[speaker_audio]
)
js_code = js_code + """
// Add note editor functionality
function initializeNoteEditor() {
const addNoteBtn = document.getElementById('add-note-btn');
const backBtn = document.getElementById('back-btn');
const notesView = document.getElementById('notes-view');
const noteEditor = document.getElementById('note-editor');
if (addNoteBtn && backBtn && notesView && noteEditor) {
addNoteBtn.addEventListener('click', () => {
notesView.style.display = 'none';
noteEditor.style.display = 'block';
});
backBtn.addEventListener('click', () => {
noteEditor.style.display = 'none';
notesView.style.display = 'block';
});
}
}
// Initialize all components
function initializeComponents() {
initializeFileUpload();
initializeClearButton();
initializeSpeakerSelect();
initializeNoteEditor();
}
initializeComponents();
const observer = new MutationObserver((mutations) => {
mutations.forEach((mutation) => {
if (mutation.addedNodes.length) {
initializeComponents();
}
});
});
observer.observe(document.body, { childList: true, subtree: true });
"""
async def run_note_agent(api_service, api_key, lecture_context, note_title, note_content):
model_client = get_model_client(api_service, api_key)
system_message = (
"You are a Note Agent. Given the current lecture slides and scripts, help the user draft a note. "
"If a title or content is provided, improve or complete the note. If not, suggest a new note based on the lecture. "
"Always use the lecture context. Output a JSON object: {\"title\": ..., \"content\": ...}."
)
note_agent = AssistantAgent(
name="note_agent",
model_client=model_client,
system_message=system_message
)
context_str = json.dumps(lecture_context)
user_input = f"Lecture Context: {context_str}\nNote Title: {note_title}\nNote Content: {note_content}"
result = await Console(note_agent.run_stream(task=user_input))
# Return only the agent's reply
for msg in reversed(result.messages):
if getattr(msg, 'source', None) == 'note_agent' and hasattr(msg, 'content') and isinstance(msg.content, str):
try:
extracted = extract_json_from_message(msg)
if extracted and isinstance(extracted, dict):
return extracted
except Exception:
continue
for msg in reversed(result.messages):
if hasattr(msg, 'content') and isinstance(msg.content, str):
try:
extracted = extract_json_from_message(msg)
if extracted and isinstance(extracted, dict):
return extracted
except Exception:
continue
return {"title": note_title, "content": note_content}
async def run_study_agent(api_service, api_key, lecture_context):
model_client = get_model_client(api_service, api_key)
system_message = (
"You are a Study Guide Agent. Given the current lecture slides and scripts, generate a concise study guide (max 200 words) summarizing the key points and actionable steps for the student. Output plain text only."
)
study_agent = AssistantAgent(
name="study_agent",
model_client=model_client,
system_message=system_message
)
context_str = json.dumps(lecture_context)
user_input = f"Lecture Context: {context_str}"
result = await Console(study_agent.run_stream(task=user_input))
# Return only the agent's reply
for msg in reversed(result.messages):
if getattr(msg, 'source', None) == 'study_agent' and hasattr(msg, 'content') and isinstance(msg.content, str):
return msg.content.strip()
for msg in reversed(result.messages):
if hasattr(msg, 'content') and isinstance(msg.content, str):
return msg.content.strip()
return "No study guide generated."
async def run_quiz_agent(api_service, api_key, lecture_context):
model_client = get_model_client(api_service, api_key)
system_message = (
"You are a Quiz Agent. Given the current lecture slides and scripts, generate a short quiz (3-5 questions) to test understanding. Output plain text only."
)
quiz_agent = AssistantAgent(
name="quiz_agent",
model_client=model_client,
system_message=system_message
)
context_str = json.dumps(lecture_context)
user_input = f"Lecture Context: {context_str}"
result = await Console(quiz_agent.run_stream(task=user_input))
# Return only the agent's reply
for msg in reversed(result.messages):
if getattr(msg, 'source', None) == 'quiz_agent' and hasattr(msg, 'content') and isinstance(msg.content, str):
return msg.content.strip()
for msg in reversed(result.messages):
if hasattr(msg, 'content') and isinstance(msg.content, str):
return msg.content.strip()
return "No quiz generated."
async def run_chat_agent(api_service, api_key, lecture_context, chat_history, user_message):
model_client = get_model_client(api_service, api_key)
system_message = (
"You are a helpful Chat Agent. Answer questions about the lecture, and if the user asks for a lecture title or content description, suggest appropriate values. "
"If you want to update the form, output a JSON object: {\"title\": ..., \"content_description\": ...}. Otherwise, just reply as normal."
)
chat_agent = AssistantAgent(
name="chat_agent",
model_client=model_client,
system_message=system_message
)
context_str = json.dumps(lecture_context)
chat_str = "\n".join([f"User: {m['content']}" if m['role']=='user' else f"Assistant: {m['content']}" for m in chat_history])
user_input = f"Lecture Context: {context_str}\nChat History: {chat_str}\nUser: {user_message}"
result = await Console(chat_agent.run_stream(task=user_input))
# Return only the chat_agent's reply
for msg in reversed(result.messages):
if getattr(msg, 'source', None) == 'chat_agent' and hasattr(msg, 'content') and isinstance(msg.content, str):
extracted = extract_json_from_message(msg)
if extracted and isinstance(extracted, dict):
return extracted, None
return None, msg.content.strip()
for msg in reversed(result.messages):
if hasattr(msg, 'content') and isinstance(msg.content, str):
extracted = extract_json_from_message(msg)
if extracted and isinstance(extracted, dict):
return extracted, None
return None, msg.content.strip()
return None, "No response."
def update_notes_list(notes):
"""Convert notes list to DataFrame format for Gradio Dataframe (titles only)."""
return [[n["title"]] for n in notes]
def show_note_editor_with_content(title, content):
return (
gr.update(visible=True), # note_editor
gr.update(visible=False), # notes_list
gr.update(visible=False), # study_guide_output
gr.update(visible=False), # quiz_output
gr.update(value=title), # note_title
gr.update(value=content) # note_content
)
def hide_note_editor():
return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
def show_study_guide(guide):
return gr.update(visible=False), gr.update(visible=True), gr.update(value=guide, visible=True), gr.update(visible=False)
def show_quiz(quiz):
return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(value=quiz, visible=True)
# Helper to get fallback lecture context from form fields
def get_fallback_lecture_context(lecture_context, title_val, desc_val, style_val, audience_val):
# If slides/scripts missing, use form fields
if lecture_context and (lecture_context.get("slides") or lecture_context.get("scripts")):
return lecture_context
return {
"slides": [],
"scripts": [],
"title": title_val or "Untitled Lecture",
"description": desc_val or "No description provided.",
"style": style_val or "Feynman - Simplifies complex ideas with enthusiasm",
"audience": audience_val or "University"
}
def show_note_content(evt: dict, notes):
# evt['index'] gives the row index
idx = evt.get('index', 0)
if 0 <= idx < len(notes):
note = notes[idx]
note_file = os.path.join(OUTPUT_DIR, f"{note['title']}.txt")
if os.path.exists(note_file):
with open(note_file, "r", encoding="utf-8") as f:
note_text = f.read()
return gr.update(value=note_text)
return gr.update(value="Click any button above to generate content...")
notes_list.select(
fn=show_note_content,
inputs=[notes_state],
outputs=note_response
)
# --- NOTES LOGIC ---
def note_type_prefix(note_type, title):
if note_type and not title.startswith(note_type):
return f"{note_type} - {title}"
return title
custom_css = """
#right-column {height: 100% !important; display: flex !important; flex-direction: column !important; gap: 20px !important;}
#notes-section, #chat-section {flex: 1 1 0; min-height: 0; max-height: 50vh; overflow-y: auto;}
#chat-section {display: flex; flex-direction: column; position: relative;}
#chatbot {flex: 1 1 auto; min-height: 0; max-height: calc(50vh - 60px); overflow-y: auto;}
#chat-input-row {position: sticky; bottom: 0; background: white; z-index: 2; padding-top: 8px;}
"""
demo.css += custom_css
if __name__ == "__main__":
demo.launch(allowed_paths=[OUTPUT_DIR]) |