{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "scQwYFBXoPGq" }, "source": [ "## Cài đặt thư viện cần thiết" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "QIQ1Fon0gwWc", "outputId": "17a307fd-b3bb-40c0-c491-6cb7b73dc695" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting azure-ai-inference\n", " Downloading azure_ai_inference-1.0.0b9-py3-none-any.whl.metadata (34 kB)\n", "Collecting isodate>=0.6.1 (from azure-ai-inference)\n", " Downloading isodate-0.7.2-py3-none-any.whl.metadata (11 kB)\n", "Collecting azure-core>=1.30.0 (from azure-ai-inference)\n", " Downloading azure_core-1.36.0-py3-none-any.whl.metadata (47 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m47.1/47.1 kB\u001b[0m \u001b[31m3.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: typing-extensions>=4.6.0 in 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0.0s\u001b[0K\n", "Webkit 26.0 (playwright build v2203) downloaded to /root/.cache/ms-playwright/webkit-2203\n", "Downloading FFMPEG playwright build v1011\u001b[2m from https://cdn.playwright.dev/dbazure/download/playwright/builds/ffmpeg/1011/ffmpeg-linux.zip\u001b[22m\n", "\u001b[1G2.3 MiB [] 0% 0.0s\u001b[0K\u001b[1G2.3 MiB [] 48% 0.0s\u001b[0K\u001b[1G2.3 MiB [] 100% 0.0s\u001b[0K\n", "FFMPEG playwright build v1011 downloaded to /root/.cache/ms-playwright/ffmpeg-1011\n", "Playwright Host validation warning: \n", "╔══════════════════════════════════════════════════════╗\n", "║ Host system is missing dependencies to run browsers. ║\n", "║ Please install them with the following command: ║\n", "║ ║\n", "║ playwright install-deps ║\n", "║ ║\n", "║ Alternatively, use apt: ║\n", "║ apt-get install libatk1.0-0\\ ║\n", "║ libatk-bridge2.0-0\\ ║\n", "║ libatspi2.0-0\\ ║\n", "║ libxcomposite1 ║\n", "║ ║\n", "║ <3 Playwright Team ║\n", "╚══════════════════════════════════════════════════════╝\n", " at validateDependenciesLinux (/usr/local/lib/python3.12/dist-packages/playwright/driver/package/lib/server/registry/dependencies.js:269:9)\n", "\u001b[90m at process.processTicksAndRejections (node:internal/process/task_queues:105:5)\u001b[39m\n", " at async Registry._validateHostRequirements (/usr/local/lib/python3.12/dist-packages/playwright/driver/package/lib/server/registry/index.js:934:14)\n", " at async Registry._validateHostRequirementsForExecutableIfNeeded (/usr/local/lib/python3.12/dist-packages/playwright/driver/package/lib/server/registry/index.js:1056:7)\n", " at async Registry.validateHostRequirementsForExecutablesIfNeeded (/usr/local/lib/python3.12/dist-packages/playwright/driver/package/lib/server/registry/index.js:1045:7)\n", " at async i. (/usr/local/lib/python3.12/dist-packages/playwright/driver/package/lib/cli/program.js:217:7)\n", "Installing dependencies...\n", "Hit:1 https://cli.github.com/packages stable InRelease\n", "Get:2 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,632 B]\n", "Get:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease [1,581 B]\n", "Get:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 Packages [2,125 kB]\n", "Get:5 http://security.ubuntu.com/ubuntu jammy-security InRelease [129 kB]\n", "Hit:6 http://archive.ubuntu.com/ubuntu jammy InRelease\n", "Get:7 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [128 kB]\n", "Get:8 https://r2u.stat.illinois.edu/ubuntu jammy InRelease [6,555 B]\n", "Get:9 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease [18.1 kB]\n", "Get:10 https://r2u.stat.illinois.edu/ubuntu jammy/main amd64 Packages [2,826 kB]\n", "Hit:11 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n", "Get:12 http://archive.ubuntu.com/ubuntu jammy-backports InRelease [127 kB]\n", "Hit:13 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n", "Get:14 http://security.ubuntu.com/ubuntu jammy-security/main amd64 Packages [3,526 kB]\n", "Get:15 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy/main amd64 Packages [38.5 kB]\n", "Get:16 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [3,856 kB]\n", "Get:17 https://r2u.stat.illinois.edu/ubuntu jammy/main all Packages [9,437 kB]\n", "Fetched 22.2 MB in 4s (5,234 kB/s)\n", "Reading package lists... Done\n", "W: Skipping acquire of configured file 'main/source/Sources' as repository 'https://r2u.stat.illinois.edu/ubuntu jammy InRelease' does not seem to provide it (sources.list entry misspelt?)\n", "Reading package lists... Done\n", "Building dependency tree... Done\n", "Reading state information... Done\n", "fonts-liberation is already the newest version (1:1.07.4-11).\n", "libasound2 is already the newest version (1.2.6.1-1ubuntu1).\n", "libasound2 set to manually installed.\n", "libcairo-gobject2 is already the newest version (1.16.0-5ubuntu2).\n", "libcairo-gobject2 set to manually installed.\n", "libcairo2 is already the newest version (1.16.0-5ubuntu2).\n", "libcairo2 set to manually installed.\n", "libegl1 is already the newest version (1.4.0-1).\n", "libepoxy0 is already the newest version (1.5.10-1).\n", "libepoxy0 set to manually installed.\n", "libevent-2.1-7 is already the newest version (2.1.12-stable-1build3).\n", "libevent-2.1-7 set to manually installed.\n", "libfontconfig1 is already the newest version (2.13.1-4.2ubuntu5).\n", "libgles2 is already the newest version (1.4.0-1).\n", "libglx0 is already the newest version (1.4.0-1).\n", "libglx0 set to manually installed.\n", "libicu70 is already the newest version (70.1-2).\n", "libicu70 set to manually installed.\n", "libjpeg-turbo8 is already the newest version (2.1.2-0ubuntu1).\n", "libjpeg-turbo8 set to manually installed.\n", "liblcms2-2 is already the newest version (2.12~rc1-2build2).\n", "liblcms2-2 set to manually installed.\n", "libopengl0 is already the newest version (1.4.0-1).\n", "libopus0 is already the newest version (1.3.1-0.1build2).\n", "libopus0 set to manually installed.\n", "libpng16-16 is already the newest version (1.6.37-3build5).\n", "libpng16-16 set to manually installed.\n", "libxcb-shm0 is already the newest version (1.14-3ubuntu3).\n", "libxcb-shm0 set to manually installed.\n", "libxcb1 is already the newest version (1.14-3ubuntu3).\n", "libxcb1 set to manually installed.\n", "libxcursor1 is already the newest version (1:1.2.0-2build4).\n", "libxcursor1 set to manually installed.\n", "libxdamage1 is already the newest version (1:1.1.5-2build2).\n", "libxdamage1 set to manually installed.\n", "libxext6 is already the newest version (2:1.3.4-1build1).\n", "libxfixes3 is already the newest version (1:6.0.0-1).\n", "libxfixes3 set to manually installed.\n", "libxi6 is already the newest version (2:1.8-1build1).\n", "libxi6 set to manually installed.\n", "libxkbcommon0 is already the newest version (1.4.0-1).\n", "libxkbcommon0 set to manually installed.\n", "libxrandr2 is already the newest version (2:1.5.2-1build1).\n", "libxrandr2 set to manually installed.\n", "libxrender1 is already the newest version (1:0.9.10-1build4).\n", "libx264-163 is already the newest version (2:0.163.3060+git5db6aa6-2build1).\n", "libx264-163 set to manually installed.\n", "libatomic1 is already the newest version (12.3.0-1ubuntu1~22.04.2).\n", "libatomic1 set to manually installed.\n", "libcups2 is already the newest version (2.4.1op1-1ubuntu4.12).\n", "libcups2 set to manually installed.\n", "libdbus-1-3 is already the newest version (1.12.20-2ubuntu4.1).\n", "libdbus-1-3 set to manually installed.\n", "libdrm2 is already the newest version (2.4.113-2~ubuntu0.22.04.1).\n", "libdrm2 set to manually installed.\n", "libfreetype6 is already the newest version (2.11.1+dfsg-1ubuntu0.3).\n", "libfreetype6 set to manually installed.\n", "libgbm1 is already the newest version (23.2.1-1ubuntu3.1~22.04.3).\n", "libgbm1 set to manually installed.\n", "libgdk-pixbuf-2.0-0 is already the newest version (2.42.8+dfsg-1ubuntu0.4).\n", "libgdk-pixbuf-2.0-0 set to manually installed.\n", "libglib2.0-0 is already the newest version (2.72.4-0ubuntu2.6).\n", "libgstreamer1.0-0 is already the newest version (1.20.3-0ubuntu1.1).\n", "libgstreamer1.0-0 set to manually installed.\n", "libgtk-4-1 is already the newest version (4.6.9+ds-0ubuntu0.22.04.2).\n", "libgtk-4-1 set to manually installed.\n", "libharfbuzz0b is already the newest version (2.7.4-1ubuntu3.2).\n", "libharfbuzz0b set to manually installed.\n", "libnspr4 is already the newest version (2:4.35-0ubuntu0.22.04.1).\n", "libnspr4 set to manually installed.\n", "libnss3 is already the newest version (2:3.98-0ubuntu0.22.04.2).\n", "libnss3 set to manually installed.\n", "libopenjp2-7 is already the newest version (2.4.0-6ubuntu0.4).\n", "libopenjp2-7 set to manually installed.\n", "libpango-1.0-0 is already the newest version (1.50.6+ds-2ubuntu1).\n", "libpango-1.0-0 set to manually installed.\n", "libpangocairo-1.0-0 is already the newest version (1.50.6+ds-2ubuntu1).\n", "libpangocairo-1.0-0 set to manually installed.\n", "libwayland-client0 is already the newest version (1.20.0-1ubuntu0.1).\n", "libwayland-client0 set to manually installed.\n", "libwayland-egl1 is already the newest version (1.20.0-1ubuntu0.1).\n", "libwayland-egl1 set to manually installed.\n", "libwayland-server0 is already the newest version (1.20.0-1ubuntu0.1).\n", "libwayland-server0 set to manually installed.\n", "libwebpdemux2 is already the newest version (1.2.2-2ubuntu0.22.04.2).\n", "libx11-6 is already the newest version (2:1.7.5-1ubuntu0.3).\n", "libx11-6 set to manually installed.\n", "libx11-xcb1 is already the newest version (2:1.7.5-1ubuntu0.3).\n", "libx11-xcb1 set to manually installed.\n", "libxml2 is already the newest version (2.9.13+dfsg-1ubuntu0.10).\n", "libxml2 set to manually installed.\n", "libxslt1.1 is already the newest version (1.1.34-4ubuntu0.22.04.4).\n", "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n", "xvfb is already the newest version (2:21.1.4-2ubuntu1.7~22.04.16).\n", "The following additional packages will be installed:\n", " dictionaries-common glib-networking glib-networking-common\n", " glib-networking-services gsettings-desktop-schemas hunspell-en-us libaa1\n", " libabsl20210324 libaspell15 libatk1.0-data libcdparanoia0 libdca0 libdv4\n", " libdvdnav4 libdvdread8 libfaad2 libfluidsynth3 libfreeaptx0 libgav1-0\n", " libgssdp-1.2-0 libgstreamer-plugins-bad1.0-0 libgstreamer-plugins-good1.0-0\n", " libgtk-3-common libgupnp-1.2-1 libgupnp-igd-1.0-4 libhunspell-1.7-0\n", " libilmbase25 libinstpatch-1.0-2 libjson-glib-1.0-0 libjson-glib-1.0-common\n", " libkate1 libldacbt-enc2 libltc11 libmjpegutils-2.1-0 libmodplug1 libmpcdec6\n", " libmpeg2encpp-2.1-0 libmplex2-2.1-0 libnice10 libopenexr25 libopenh264-6\n", " libopenni2-0 liborc-0.4-0 libqrencode4 libsbc1 libsecret-common libshout3\n", " libsoundtouch1 libsoup-3.0-common libsoup2.4-1 libsoup2.4-common libspandsp2\n", " libsrtp2-1 libtag1v5 libtag1v5-vanilla libtext-iconv-perl libv4l-0\n", " libv4lconvert0 libvisual-0.4-0 libvo-aacenc0 libvo-amrwbenc0 libwavpack1\n", " libwebrtc-audio-processing1 libwildmidi2 libyuv0 libzbar0 libzxingcore1\n", " session-migration timgm6mb-soundfont xfonts-encodings xfonts-utils\n", "Suggested packages:\n", " ispell | aspell | hunspell wordlist frei0r-plugins gvfs hunspell\n", " openoffice.org-hunspell | openoffice.org-core aspell libdv-bin oss-compat\n", " libdvdcss2 libenchant-2-voikko libvisual-0.4-plugins gnome-shell\n", " | notification-daemon libwildmidi-config fluid-soundfont-gm\n", "Recommended packages:\n", " fonts-ipafont-mincho fonts-tlwg-loma gstreamer1.0-x aspell-en\n", " | aspell-dictionary | aspell6a-dictionary at-spi2-core enchant-2\n", " gstreamer1.0-gl libgtk-3-bin librsvg2-common libmagickcore-6.q16-6-extra\n", "The following NEW packages will be installed:\n", " dictionaries-common fonts-freefont-ttf fonts-ipafont-gothic\n", " fonts-noto-color-emoji fonts-tlwg-loma-otf fonts-unifont fonts-wqy-zenhei\n", " glib-networking glib-networking-common glib-networking-services\n", " gsettings-desktop-schemas gstreamer1.0-libav gstreamer1.0-plugins-bad\n", " gstreamer1.0-plugins-base gstreamer1.0-plugins-good hunspell-en-us libaa1\n", " libabsl20210324 libaspell15 libatk-bridge2.0-0 libatk1.0-0 libatk1.0-data\n", " libatspi2.0-0 libavif13 libcdparanoia0 libdbus-glib-1-2 libdca0 libdv4\n", " libdvdnav4 libdvdread8 libenchant-2-2 libevdev2 libfaad2 libffi7\n", " libfluidsynth3 libfreeaptx0 libgav1-0 libgssdp-1.2-0 libgstreamer-gl1.0-0\n", " libgstreamer-plugins-bad1.0-0 libgstreamer-plugins-base1.0-0\n", " libgstreamer-plugins-good1.0-0 libgtk-3-0 libgtk-3-common libgudev-1.0-0\n", " libgupnp-1.2-1 libgupnp-igd-1.0-4 libharfbuzz-icu0 libhunspell-1.7-0\n", " libhyphen0 libilmbase25 libinstpatch-1.0-2 libjson-glib-1.0-0\n", " libjson-glib-1.0-common libkate1 libldacbt-enc2 libltc11 libmanette-0.2-0\n", " libmjpegutils-2.1-0 libmodplug1 libmpcdec6 libmpeg2encpp-2.1-0\n", " libmplex2-2.1-0 libnice10 libnotify4 libopenexr25 libopenh264-6 libopenni2-0\n", " liborc-0.4-0 libproxy1v5 libqrencode4 libsbc1 libsecret-1-0 libsecret-common\n", " libshout3 libsoundtouch1 libsoup-3.0-0 libsoup-3.0-common libsoup2.4-1\n", " libsoup2.4-common libspandsp2 libsrtp2-1 libtag1v5 libtag1v5-vanilla\n", " libtext-iconv-perl libv4l-0 libv4lconvert0 libvisual-0.4-0 libvo-aacenc0\n", " libvo-amrwbenc0 libwavpack1 libwebrtc-audio-processing1 libwildmidi2\n", " libwoff1 libxcomposite1 libxtst6 libyuv0 libzbar0 libzxingcore1\n", " session-migration timgm6mb-soundfont xfonts-cyrillic xfonts-encodings\n", " xfonts-scalable xfonts-utils\n", "0 upgraded, 105 newly installed, 0 to remove and 43 not upgraded.\n", "Need to get 53.7 MB of archives.\n", "After this operation, 142 MB of additional disk space will be used.\n", "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 fonts-ipafont-gothic all 00303-21ubuntu1 [3,513 kB]\n", "Get:2 http://archive.ubuntu.com/ubuntu jammy/main amd64 libtext-iconv-perl amd64 1.7-7build3 [14.3 kB]\n", "Get:3 http://archive.ubuntu.com/ubuntu jammy/main amd64 dictionaries-common all 1.28.14 [185 kB]\n", "Get:4 http://archive.ubuntu.com/ubuntu jammy/main amd64 fonts-freefont-ttf all 20120503-10build1 [2,388 kB]\n", "Get:5 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 fonts-noto-color-emoji all 2.047-0ubuntu0.22.04.1 [10.0 MB]\n", "Get:6 http://archive.ubuntu.com/ubuntu jammy/universe amd64 fonts-tlwg-loma-otf all 1:0.7.3-1 [107 kB]\n", "Get:7 http://archive.ubuntu.com/ubuntu jammy/universe amd64 fonts-unifont all 1:14.0.01-1 [3,551 kB]\n", "Get:8 http://archive.ubuntu.com/ubuntu jammy/universe amd64 fonts-wqy-zenhei all 0.9.45-8 [7,472 kB]\n", "Get:9 http://archive.ubuntu.com/ubuntu jammy/main amd64 libproxy1v5 amd64 0.4.17-2 [51.9 kB]\n", "Get:10 http://archive.ubuntu.com/ubuntu jammy/main amd64 glib-networking-common all 2.72.0-1 [3,718 B]\n", "Get:11 http://archive.ubuntu.com/ubuntu jammy/main amd64 glib-networking-services amd64 2.72.0-1 [9,982 B]\n", "Get:12 http://archive.ubuntu.com/ubuntu jammy/main amd64 session-migration amd64 0.3.6 [9,774 B]\n", "Get:13 http://archive.ubuntu.com/ubuntu jammy/main amd64 gsettings-desktop-schemas all 42.0-1ubuntu1 [31.1 kB]\n", "Get:14 http://archive.ubuntu.com/ubuntu jammy/main amd64 glib-networking amd64 2.72.0-1 [69.8 kB]\n", "Get:15 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 liborc-0.4-0 amd64 1:0.4.32-2ubuntu0.1 [228 kB]\n", "Get:16 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgstreamer-plugins-base1.0-0 amd64 1.20.1-1ubuntu0.5 [848 kB]\n", "Get:17 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 gstreamer1.0-libav amd64 1.20.3-0ubuntu1 [103 kB]\n", "Get:18 http://archive.ubuntu.com/ubuntu jammy/main amd64 libcdparanoia0 amd64 3.10.2+debian-14build2 [49.3 kB]\n", "Get:19 http://archive.ubuntu.com/ubuntu jammy/main amd64 libvisual-0.4-0 amd64 0.4.0-17build2 [108 kB]\n", "Get:20 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 gstreamer1.0-plugins-base amd64 1.20.1-1ubuntu0.5 [712 kB]\n", "Get:21 http://archive.ubuntu.com/ubuntu jammy/main amd64 libaa1 amd64 1.4p5-50build1 [51.9 kB]\n", "Get:22 http://archive.ubuntu.com/ubuntu jammy/main amd64 libdv4 amd64 1.0.0-14build1 [61.9 kB]\n", "Get:23 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgstreamer-plugins-good1.0-0 amd64 1.20.3-0ubuntu1.4 [30.2 kB]\n", "Get:24 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgudev-1.0-0 amd64 1:237-2build1 [16.3 kB]\n", "Get:25 http://archive.ubuntu.com/ubuntu jammy/main amd64 libshout3 amd64 2.4.5-1build3 [54.5 kB]\n", "Get:26 http://archive.ubuntu.com/ubuntu jammy/main amd64 libtag1v5-vanilla amd64 1.11.1+dfsg.1-3ubuntu3 [304 kB]\n", "Get:27 http://archive.ubuntu.com/ubuntu jammy/main amd64 libtag1v5 amd64 1.11.1+dfsg.1-3ubuntu3 [11.5 kB]\n", "Get:28 http://archive.ubuntu.com/ubuntu jammy/main amd64 libv4lconvert0 amd64 1.22.1-2build1 [82.4 kB]\n", "Get:29 http://archive.ubuntu.com/ubuntu jammy/main amd64 libv4l-0 amd64 1.22.1-2build1 [44.9 kB]\n", "Get:30 http://archive.ubuntu.com/ubuntu jammy/main amd64 libwavpack1 amd64 5.4.0-1build2 [83.7 kB]\n", "Get:31 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libsoup2.4-common all 2.74.2-3ubuntu0.6 [4,778 B]\n", "Get:32 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libsoup2.4-1 amd64 2.74.2-3ubuntu0.6 [288 kB]\n", "Get:33 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 gstreamer1.0-plugins-good amd64 1.20.3-0ubuntu1.4 [2,009 kB]\n", "Get:34 http://archive.ubuntu.com/ubuntu jammy/main amd64 hunspell-en-us all 1:2020.12.07-2 [280 kB]\n", "Get:35 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libabsl20210324 amd64 0~20210324.2-2ubuntu0.2 [386 kB]\n", "Get:36 http://archive.ubuntu.com/ubuntu jammy/main amd64 libaspell15 amd64 0.60.8-4build1 [325 kB]\n", "Get:37 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatk1.0-data all 2.36.0-3build1 [2,824 B]\n", "Get:38 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatk1.0-0 amd64 2.36.0-3build1 [51.9 kB]\n", "Get:39 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatspi2.0-0 amd64 2.44.0-3 [80.9 kB]\n", "Get:40 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatk-bridge2.0-0 amd64 2.38.0-3 [66.6 kB]\n", "Get:41 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libgav1-0 amd64 0.17.0-1build1 [336 kB]\n", "Get:42 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libyuv0 amd64 0.0~git20220104.b91df1a-2 [154 kB]\n", "Get:43 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libavif13 amd64 0.9.3-3 [69.5 kB]\n", "Get:44 http://archive.ubuntu.com/ubuntu jammy/main amd64 libdbus-glib-1-2 amd64 0.112-2build1 [65.4 kB]\n", "Get:45 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libdvdread8 amd64 6.1.2-1 [55.7 kB]\n", "Get:46 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libdvdnav4 amd64 6.1.1-1 [39.3 kB]\n", "Get:47 http://archive.ubuntu.com/ubuntu jammy/main amd64 libhunspell-1.7-0 amd64 1.7.0-4build1 [175 kB]\n", "Get:48 http://archive.ubuntu.com/ubuntu jammy/main amd64 libenchant-2-2 amd64 2.3.2-1ubuntu2 [50.9 kB]\n", "Get:49 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libfaad2 amd64 2.10.0-2 [197 kB]\n", "Get:50 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libffi7 amd64 3.3-5ubuntu1 [19.9 kB]\n", "Get:51 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libinstpatch-1.0-2 amd64 1.1.6-1 [240 kB]\n", "Get:52 http://archive.ubuntu.com/ubuntu jammy/universe amd64 timgm6mb-soundfont all 1.3-5 [5,427 kB]\n", "Get:53 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libfluidsynth3 amd64 2.2.5-1 [246 kB]\n", "Get:54 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libfreeaptx0 amd64 0.1.1-1 [12.9 kB]\n", "Get:55 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgssdp-1.2-0 amd64 1.4.0.1-2build1 [48.9 kB]\n", "Get:56 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgstreamer-gl1.0-0 amd64 1.20.1-1ubuntu0.5 [204 kB]\n", "Get:57 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxcomposite1 amd64 1:0.4.5-1build2 [7,192 B]\n", "Get:58 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgtk-3-common all 3.24.33-1ubuntu2.2 [239 kB]\n", "Get:59 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgtk-3-0 amd64 3.24.33-1ubuntu2.2 [3,053 kB]\n", "Get:60 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgupnp-1.2-1 amd64 1.4.3-1 [93.3 kB]\n", "Get:61 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libgupnp-igd-1.0-4 amd64 1.2.0-1build1 [16.8 kB]\n", "Get:62 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libharfbuzz-icu0 amd64 2.7.4-1ubuntu3.2 [5,890 B]\n", "Get:63 http://archive.ubuntu.com/ubuntu jammy/main amd64 libhyphen0 amd64 2.8.8-7build2 [28.2 kB]\n", "Get:64 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libilmbase25 amd64 2.5.7-2 [175 kB]\n", "Get:65 http://archive.ubuntu.com/ubuntu jammy/main amd64 libjson-glib-1.0-common all 1.6.6-1build1 [4,432 B]\n", "Get:66 http://archive.ubuntu.com/ubuntu jammy/main amd64 libjson-glib-1.0-0 amd64 1.6.6-1build1 [69.9 kB]\n", "Get:67 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libkate1 amd64 0.4.1-11build1 [39.4 kB]\n", "Get:68 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libldacbt-enc2 amd64 2.0.2.3+git20200429+ed310a0-4 [24.6 kB]\n", "Get:69 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libltc11 amd64 1.3.1-1 [12.3 kB]\n", "Get:70 http://archive.ubuntu.com/ubuntu jammy/main amd64 libevdev2 amd64 1.12.1+dfsg-1 [39.5 kB]\n", "Get:71 http://archive.ubuntu.com/ubuntu jammy/main amd64 libmanette-0.2-0 amd64 0.2.6-3build1 [30.4 kB]\n", "Get:72 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmjpegutils-2.1-0 amd64 1:2.1.0+debian-6build1 [24.1 kB]\n", "Get:73 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmodplug1 amd64 1:0.8.9.0-3 [153 kB]\n", "Get:74 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmpcdec6 amd64 2:0.1~r495-2 [32.4 kB]\n", "Get:75 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmpeg2encpp-2.1-0 amd64 1:2.1.0+debian-6build1 [69.4 kB]\n", "Get:76 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmplex2-2.1-0 amd64 1:2.1.0+debian-6build1 [44.4 kB]\n", "Get:77 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libnice10 amd64 0.1.18-2 [156 kB]\n", "Get:78 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libnotify4 amd64 0.7.9-3ubuntu5.22.04.1 [20.3 kB]\n", "Get:79 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopenexr25 amd64 2.5.7-1 [780 kB]\n", "Get:80 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopenh264-6 amd64 2.2.0+dfsg-2 [407 kB]\n", "Get:81 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopenni2-0 amd64 2.2.0.33+dfsg-15 [389 kB]\n", "Get:82 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libqrencode4 amd64 4.1.1-1 [24.0 kB]\n", "Get:83 http://archive.ubuntu.com/ubuntu jammy/main amd64 libsecret-common all 0.20.5-2 [4,278 B]\n", "Get:84 http://archive.ubuntu.com/ubuntu jammy/main amd64 libsecret-1-0 amd64 0.20.5-2 [124 kB]\n", "Get:85 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libsoundtouch1 amd64 2.3.1+ds1-1 [38.3 kB]\n", "Get:86 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libsoup-3.0-common all 3.0.7-0ubuntu1 [62.1 kB]\n", "Get:87 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libsoup-3.0-0 amd64 3.0.7-0ubuntu1 [278 kB]\n", "Get:88 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libspandsp2 amd64 0.0.6+dfsg-2 [272 kB]\n", "Get:89 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libsrtp2-1 amd64 2.4.2-2 [40.7 kB]\n", "Get:90 http://archive.ubuntu.com/ubuntu jammy/main amd64 libwebrtc-audio-processing1 amd64 0.3.1-0ubuntu5 [291 kB]\n", "Get:91 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libwildmidi2 amd64 0.4.3-1 [59.9 kB]\n", "Get:92 http://archive.ubuntu.com/ubuntu jammy/main amd64 libwoff1 amd64 1.0.2-1build4 [45.2 kB]\n", "Get:93 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxtst6 amd64 2:1.2.3-1build4 [13.4 kB]\n", "Get:94 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libzbar0 amd64 0.23.92-4build2 [121 kB]\n", "Get:95 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libzxingcore1 amd64 1.2.0-1 [619 kB]\n", "Get:96 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-encodings all 1:1.0.5-0ubuntu2 [578 kB]\n", "Get:97 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-utils amd64 1:7.7+6build2 [94.6 kB]\n", "Get:98 http://archive.ubuntu.com/ubuntu jammy/universe amd64 xfonts-cyrillic all 1:1.0.5 [386 kB]\n", "Get:99 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-scalable all 1:1.0.3-1.2ubuntu1 [306 kB]\n", "Get:100 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libdca0 amd64 0.0.7-2 [88.2 kB]\n", "Get:101 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libgstreamer-plugins-bad1.0-0 amd64 1.20.3-0ubuntu1.1 [489 kB]\n", "Get:102 http://archive.ubuntu.com/ubuntu jammy/main amd64 libsbc1 amd64 1.5-3build2 [34.4 kB]\n", "Get:103 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libvo-aacenc0 amd64 0.1.3-2 [69.4 kB]\n", "Get:104 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libvo-amrwbenc0 amd64 0.1.3-2 [68.2 kB]\n", "Get:105 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 gstreamer1.0-plugins-bad amd64 1.20.3-0ubuntu1.1 [2,602 kB]\n", "Fetched 53.7 MB in 7s (7,177 kB/s)\n", "Extracting templates from packages: 100%\n", "Preconfiguring packages ...\n", "Selecting previously unselected package fonts-ipafont-gothic.\n", "(Reading database ... 121229 files and directories currently installed.)\n", "Preparing to unpack .../000-fonts-ipafont-gothic_00303-21ubuntu1_all.deb ...\n", "Unpacking fonts-ipafont-gothic (00303-21ubuntu1) ...\n", "Selecting previously unselected package libtext-iconv-perl.\n", "Preparing to unpack .../001-libtext-iconv-perl_1.7-7build3_amd64.deb ...\n", "Unpacking libtext-iconv-perl (1.7-7build3) ...\n", "Selecting previously unselected package dictionaries-common.\n", "Preparing to unpack .../002-dictionaries-common_1.28.14_all.deb ...\n", "Adding 'diversion of /usr/share/dict/words to /usr/share/dict/words.pre-dictionaries-common by dictionaries-common'\n", "Unpacking dictionaries-common (1.28.14) ...\n", "Selecting previously unselected package fonts-freefont-ttf.\n", "Preparing to unpack .../003-fonts-freefont-ttf_20120503-10build1_all.deb ...\n", "Unpacking fonts-freefont-ttf 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"Setting up libmanette-0.2-0:amd64 (0.2.6-3build1) ...\n", "Setting up libgstreamer-plugins-base1.0-0:amd64 (1.20.1-1ubuntu0.5) ...\n", "Setting up xfonts-utils (1:7.7+6build2) ...\n", "Setting up libjson-glib-1.0-0:amd64 (1.6.6-1build1) ...\n", "Setting up libv4l-0:amd64 (1.22.1-2build1) ...\n", "Setting up libatk-bridge2.0-0:amd64 (2.38.0-3) ...\n", "Setting up libgstreamer-plugins-bad1.0-0:amd64 (1.20.3-0ubuntu1.1) ...\n", "Setting up libsecret-1-0:amd64 (0.20.5-2) ...\n", "Setting up libgstreamer-plugins-good1.0-0:amd64 (1.20.3-0ubuntu1.4) ...\n", "Setting up libgstreamer-gl1.0-0:amd64 (1.20.1-1ubuntu0.5) ...\n", "Setting up gstreamer1.0-plugins-base:amd64 (1.20.1-1ubuntu0.5) ...\n", "Setting up libgav1-0:amd64 (0.17.0-1build1) ...\n", "Setting up libmpeg2encpp-2.1-0:amd64 (1:2.1.0+debian-6build1) ...\n", "Setting up libavif13:amd64 (0.9.3-3) ...\n", "Setting up xfonts-cyrillic (1:1.0.5) ...\n", "Setting up libmplex2-2.1-0:amd64 (1:2.1.0+debian-6build1) ...\n", "Setting up 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(1.4.0.1-2build1) ...\n", "Setting up libgupnp-1.2-1:amd64 (1.4.3-1) ...\n", "Setting up libgupnp-igd-1.0-4:amd64 (1.2.0-1build1) ...\n", "Setting up libnice10:amd64 (0.1.18-2) ...\n", "Setting up gstreamer1.0-plugins-bad:amd64 (1.20.3-0ubuntu1.1) ...\n", "Processing triggers for dictionaries-common (1.28.14) ...\n", "Processing triggers for libc-bin (2.35-0ubuntu3.8) ...\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero_v2.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libumf.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libhwloc.so.15 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtcm.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtcm_debug.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_opencl.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n", "\n", "Collecting pdfplumber\n", " Downloading pdfplumber-0.11.8-py3-none-any.whl.metadata (43 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.6/43.6 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting pdfminer.six==20251107 (from pdfplumber)\n", " Downloading 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anyio->httpx>=0.27->ollama) (1.3.1)\n", "Downloading ollama-0.6.0-py3-none-any.whl (14 kB)\n", "Installing collected packages: ollama\n", "Successfully installed ollama-0.6.0\n", "Reading package lists... Done\n", "Building dependency tree... Done\n", "Reading state information... Done\n", "The following additional packages will be installed:\n", " ca-certificates-java fonts-dejavu-core fonts-dejavu-extra java-common\n", " libatk-wrapper-java libatk-wrapper-java-jni libpcsclite1 libxt-dev\n", " libxxf86dga1 openjdk-11-jdk-headless openjdk-11-jre openjdk-11-jre-headless\n", " x11-utils\n", "Suggested packages:\n", " default-jre pcscd libxt-doc openjdk-11-demo openjdk-11-source visualvm\n", " libnss-mdns fonts-ipafont-mincho fonts-indic mesa-utils\n", "The following NEW packages will be installed:\n", " ca-certificates-java fonts-dejavu-core fonts-dejavu-extra java-common\n", " libatk-wrapper-java libatk-wrapper-java-jni libpcsclite1 libxt-dev\n", " libxxf86dga1 openjdk-11-jdk openjdk-11-jdk-headless openjdk-11-jre\n", " openjdk-11-jre-headless x11-utils\n", "0 upgraded, 14 newly installed, 0 to remove and 43 not upgraded.\n", "Need to get 122 MB of archives.\n", "After this operation, 274 MB of additional disk space will be used.\n", "Get:1 http://archive.ubuntu.com/ubuntu jammy/main amd64 java-common all 0.72build2 [6,782 B]\n", "Get:2 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libpcsclite1 amd64 1.9.5-3ubuntu1 [19.8 kB]\n", "Get:3 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 openjdk-11-jre-headless amd64 11.0.28+6-1ubuntu1~22.04.1 [42.6 MB]\n", "Get:4 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 ca-certificates-java all 20190909ubuntu1.2 [12.1 kB]\n", "Get:5 http://archive.ubuntu.com/ubuntu jammy/main amd64 fonts-dejavu-core all 2.37-2build1 [1,041 kB]\n", "Get:6 http://archive.ubuntu.com/ubuntu jammy/main amd64 fonts-dejavu-extra all 2.37-2build1 [2,041 kB]\n", "Get:7 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxxf86dga1 amd64 2:1.1.5-0ubuntu3 [12.6 kB]\n", "Get:8 http://archive.ubuntu.com/ubuntu jammy/main amd64 x11-utils amd64 7.7+5build2 [206 kB]\n", "Get:9 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatk-wrapper-java all 0.38.0-5build1 [53.1 kB]\n", "Get:10 http://archive.ubuntu.com/ubuntu jammy/main amd64 libatk-wrapper-java-jni amd64 0.38.0-5build1 [49.0 kB]\n", "Get:11 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxt-dev amd64 1:1.2.1-1 [396 kB]\n", "Get:12 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 openjdk-11-jre amd64 11.0.28+6-1ubuntu1~22.04.1 [214 kB]\n", "Get:13 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 openjdk-11-jdk-headless amd64 11.0.28+6-1ubuntu1~22.04.1 [73.6 MB]\n", "Get:14 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 openjdk-11-jdk amd64 11.0.28+6-1ubuntu1~22.04.1 [1,342 kB]\n", "Fetched 122 MB in 9s (13.8 MB/s)\n", "Selecting previously unselected package java-common.\n", "(Reading database ... 122898 files and directories currently installed.)\n", "Preparing to unpack .../00-java-common_0.72build2_all.deb ...\n", "Unpacking java-common (0.72build2) ...\n", "Selecting previously unselected package libpcsclite1:amd64.\n", "Preparing to unpack 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up libatk-wrapper-java (0.38.0-5build1) ...\n", "Setting up libatk-wrapper-java-jni:amd64 (0.38.0-5build1) ...\n", "Setting up openjdk-11-jre-headless:amd64 (11.0.28+6-1ubuntu1~22.04.1) ...\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/java to provide /usr/bin/java (java) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jjs to provide /usr/bin/jjs (jjs) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/keytool to provide /usr/bin/keytool (keytool) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/rmid to provide /usr/bin/rmid (rmid) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/rmiregistry to provide /usr/bin/rmiregistry (rmiregistry) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/pack200 to provide /usr/bin/pack200 (pack200) in auto mode\n", "update-alternatives: using 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mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jmap to provide /usr/bin/jmap (jmap) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jmod to provide /usr/bin/jmod (jmod) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jps to provide /usr/bin/jps (jps) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jrunscript to provide /usr/bin/jrunscript (jrunscript) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jshell to provide /usr/bin/jshell (jshell) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jstack to provide /usr/bin/jstack (jstack) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jstat to provide /usr/bin/jstat (jstat) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jstatd to provide /usr/bin/jstatd (jstatd) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/rmic to provide /usr/bin/rmic (rmic) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/serialver to provide /usr/bin/serialver (serialver) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jaotc to provide /usr/bin/jaotc (jaotc) in auto mode\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jhsdb to provide /usr/bin/jhsdb (jhsdb) in auto mode\n", "Setting up openjdk-11-jdk:amd64 (11.0.28+6-1ubuntu1~22.04.1) ...\n", "update-alternatives: using /usr/lib/jvm/java-11-openjdk-amd64/bin/jconsole to provide /usr/bin/jconsole (jconsole) in auto mode\n", "Setting up ca-certificates-java (20190909ubuntu1.2) ...\n", "head: cannot open '/etc/ssl/certs/java/cacerts' for reading: No such file or directory\n", "Adding debian:DigiCert_Assured_ID_Root_G2.pem\n", "Adding debian:Trustwave_Global_ECC_P384_Certification_Authority.pem\n", "Adding debian:SwissSign_Silver_CA_-_G2.pem\n", "Adding debian:Actalis_Authentication_Root_CA.pem\n", "Adding debian:Hongkong_Post_Root_CA_3.pem\n", "Adding debian:T-TeleSec_GlobalRoot_Class_2.pem\n", "Adding debian:DigiCert_Trusted_Root_G4.pem\n", "Adding debian:DigiCert_Global_Root_G2.pem\n", "Adding debian:DigiCert_Global_Root_CA.pem\n", "Adding debian:Entrust_Root_Certification_Authority_-_G4.pem\n", "Adding debian:HARICA_TLS_ECC_Root_CA_2021.pem\n", "Adding debian:Go_Daddy_Class_2_CA.pem\n", "Adding debian:Secure_Global_CA.pem\n", "Adding debian:Amazon_Root_CA_3.pem\n", "Adding debian:ISRG_Root_X1.pem\n", "Adding debian:Trustwave_Global_Certification_Authority.pem\n", "Adding debian:ANF_Secure_Server_Root_CA.pem\n", "Adding debian:Amazon_Root_CA_2.pem\n", "Adding debian:GTS_Root_R1.pem\n", "Adding debian:Certigna_Root_CA.pem\n", "Adding debian:certSIGN_Root_CA_G2.pem\n", "Adding debian:UCA_Extended_Validation_Root.pem\n", "Adding debian:Hellenic_Academic_and_Research_Institutions_RootCA_2015.pem\n", "Adding debian:Security_Communication_RootCA2.pem\n", "Adding debian:Security_Communication_Root_CA.pem\n", "Adding debian:COMODO_Certification_Authority.pem\n", "Adding debian:GlobalSign_Root_R46.pem\n", "Adding debian:Telia_Root_CA_v2.pem\n", "Adding debian:COMODO_RSA_Certification_Authority.pem\n", "Adding debian:certSIGN_ROOT_CA.pem\n", "Adding debian:Hellenic_Academic_and_Research_Institutions_ECC_RootCA_2015.pem\n", "Adding debian:Security_Communication_RootCA3.pem\n", "Adding debian:emSign_ECC_Root_CA_-_G3.pem\n", "Adding debian:Amazon_Root_CA_4.pem\n", "Adding debian:SwissSign_Gold_CA_-_G2.pem\n", "Adding debian:Atos_TrustedRoot_2011.pem\n", "Adding debian:TUBITAK_Kamu_SM_SSL_Kok_Sertifikasi_-_Surum_1.pem\n", "Adding debian:Microsoft_RSA_Root_Certificate_Authority_2017.pem\n", "Adding debian:IdenTrust_Commercial_Root_CA_1.pem\n", "Adding debian:SZAFIR_ROOT_CA2.pem\n", "Adding debian:Go_Daddy_Root_Certificate_Authority_-_G2.pem\n", "Adding debian:Certainly_Root_E1.pem\n", "Adding debian:Entrust_Root_Certification_Authority_-_EC1.pem\n", "Adding debian:Certum_Trusted_Network_CA.pem\n", "Adding debian:AffirmTrust_Networking.pem\n", "Adding debian:emSign_ECC_Root_CA_-_C3.pem\n", "Adding debian:AC_RAIZ_FNMT-RCM.pem\n", "Adding debian:Certum_EC-384_CA.pem\n", "Adding debian:SSL.com_Root_Certification_Authority_RSA.pem\n", "Adding debian:DigiCert_Global_Root_G3.pem\n", "Adding debian:GTS_Root_R4.pem\n", "Adding debian:CFCA_EV_ROOT.pem\n", "Adding debian:NAVER_Global_Root_Certification_Authority.pem\n", "Adding debian:e-Szigno_Root_CA_2017.pem\n", "Adding debian:Buypass_Class_2_Root_CA.pem\n", "Adding debian:T-TeleSec_GlobalRoot_Class_3.pem\n", "Adding debian:DigiCert_Assured_ID_Root_G3.pem\n", "Adding debian:Entrust.net_Premium_2048_Secure_Server_CA.pem\n", "Adding debian:Starfield_Services_Root_Certificate_Authority_-_G2.pem\n", "Adding debian:HiPKI_Root_CA_-_G1.pem\n", "Adding debian:QuoVadis_Root_CA_1_G3.pem\n", "Adding debian:XRamp_Global_CA_Root.pem\n", "Adding debian:Security_Communication_ECC_RootCA1.pem\n", "Adding debian:QuoVadis_Root_CA_3.pem\n", "Adding debian:ePKI_Root_Certification_Authority.pem\n", "Adding debian:GlobalSign_Root_E46.pem\n", "Adding debian:GDCA_TrustAUTH_R5_ROOT.pem\n", "Adding debian:QuoVadis_Root_CA_2_G3.pem\n", "Adding debian:QuoVadis_Root_CA_2.pem\n", "Adding debian:Baltimore_CyberTrust_Root.pem\n", "Adding debian:Comodo_AAA_Services_root.pem\n", "Adding debian:emSign_Root_CA_-_G1.pem\n", "Adding debian:GlobalSign_Root_CA_-_R3.pem\n", "Adding debian:emSign_Root_CA_-_C1.pem\n", "Adding debian:D-TRUST_EV_Root_CA_1_2020.pem\n", "Adding debian:USERTrust_RSA_Certification_Authority.pem\n", "Adding debian:D-TRUST_Root_Class_3_CA_2_EV_2009.pem\n", "Adding debian:GlobalSign_ECC_Root_CA_-_R5.pem\n", "Adding debian:Entrust_Root_Certification_Authority.pem\n", "Adding debian:GLOBALTRUST_2020.pem\n", "Adding debian:GTS_Root_R3.pem\n", "Adding debian:Amazon_Root_CA_1.pem\n", "Adding debian:DigiCert_High_Assurance_EV_Root_CA.pem\n", "Adding debian:GTS_Root_R2.pem\n", "Adding debian:TeliaSonera_Root_CA_v1.pem\n", "Adding debian:D-TRUST_BR_Root_CA_1_2020.pem\n", "Adding debian:SSL.com_Root_Certification_Authority_ECC.pem\n", "Adding debian:Certigna.pem\n", "Adding debian:GlobalSign_Root_CA.pem\n", "Adding debian:Certainly_Root_R1.pem\n", "Adding debian:DigiCert_TLS_ECC_P384_Root_G5.pem\n", "Adding debian:Microsoft_ECC_Root_Certificate_Authority_2017.pem\n", "Adding debian:QuoVadis_Root_CA_3_G3.pem\n", "Adding debian:Trustwave_Global_ECC_P256_Certification_Authority.pem\n", "Adding debian:SSL.com_EV_Root_Certification_Authority_ECC.pem\n", "Adding debian:UCA_Global_G2_Root.pem\n", "Adding debian:TWCA_Global_Root_CA.pem\n", "Adding debian:SecureTrust_CA.pem\n", "Adding debian:GlobalSign_Root_CA_-_R6.pem\n", "Adding debian:COMODO_ECC_Certification_Authority.pem\n", "Adding debian:Starfield_Root_Certificate_Authority_-_G2.pem\n", "Adding debian:D-TRUST_Root_Class_3_CA_2_2009.pem\n", "Adding debian:USERTrust_ECC_Certification_Authority.pem\n", "Adding debian:CA_Disig_Root_R2.pem\n", "Adding debian:AC_RAIZ_FNMT-RCM_SERVIDORES_SEGUROS.pem\n", "Adding debian:OISTE_WISeKey_Global_Root_GC_CA.pem\n", "Adding debian:Izenpe.com.pem\n", "Adding debian:ISRG_Root_X2.pem\n", "Adding debian:SSL.com_EV_Root_Certification_Authority_RSA_R2.pem\n", "Adding debian:Certum_Trusted_Root_CA.pem\n", "Adding debian:DigiCert_Assured_ID_Root_CA.pem\n", "Adding debian:TWCA_Root_Certification_Authority.pem\n", "Adding debian:ACCVRAIZ1.pem\n", "Adding debian:TunTrust_Root_CA.pem\n", "Adding debian:Starfield_Class_2_CA.pem\n", "Adding debian:AffirmTrust_Premium.pem\n", "Adding debian:vTrus_Root_CA.pem\n", "Adding debian:NetLock_Arany_=Class_Gold=_Főtanúsítvány.pem\n", "Adding debian:Autoridad_de_Certificacion_Firmaprofesional_CIF_A62634068.pem\n", "Adding debian:SecureSign_RootCA11.pem\n", "Adding debian:Entrust_Root_Certification_Authority_-_G2.pem\n", "Adding debian:IdenTrust_Public_Sector_Root_CA_1.pem\n", "Adding debian:Buypass_Class_3_Root_CA.pem\n", "Adding debian:AffirmTrust_Commercial.pem\n", "Adding debian:OISTE_WISeKey_Global_Root_GB_CA.pem\n", "Adding debian:Certum_Trusted_Network_CA_2.pem\n", "Adding debian:DigiCert_TLS_RSA4096_Root_G5.pem\n", "Adding debian:Microsec_e-Szigno_Root_CA_2009.pem\n", "Adding debian:HARICA_TLS_RSA_Root_CA_2021.pem\n", "Adding debian:vTrus_ECC_Root_CA.pem\n", "Adding debian:GlobalSign_ECC_Root_CA_-_R4.pem\n", "Adding debian:AffirmTrust_Premium_ECC.pem\n", "Adding debian:BJCA_Global_Root_CA2.pem\n", "Adding debian:TrustAsia_Global_Root_CA_G4.pem\n", "Adding debian:SSL.com_TLS_RSA_Root_CA_2022.pem\n", "Adding debian:Sectigo_Public_Server_Authentication_Root_R46.pem\n", "Adding debian:Atos_TrustedRoot_Root_CA_RSA_TLS_2021.pem\n", "Adding debian:Atos_TrustedRoot_Root_CA_ECC_TLS_2021.pem\n", "Adding debian:SSL.com_TLS_ECC_Root_CA_2022.pem\n", "Adding debian:Sectigo_Public_Server_Authentication_Root_E46.pem\n", "Adding debian:CommScope_Public_Trust_ECC_Root-02.pem\n", "Adding debian:CommScope_Public_Trust_RSA_Root-01.pem\n", "Adding debian:TrustAsia_Global_Root_CA_G3.pem\n", "Adding debian:BJCA_Global_Root_CA1.pem\n", "Adding debian:CommScope_Public_Trust_RSA_Root-02.pem\n", "Adding debian:CommScope_Public_Trust_ECC_Root-01.pem\n", "done.\n", "Processing triggers for mailcap (3.70+nmu1ubuntu1) ...\n", "Processing triggers for fontconfig (2.13.1-4.2ubuntu5) ...\n", "Processing triggers for hicolor-icon-theme (0.17-2) ...\n", "Processing triggers for libc-bin (2.35-0ubuntu3.8) ...\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero_v2.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libumf.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libhwloc.so.15 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtcm.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtcm_debug.so.1 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_opencl.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n", "\n", "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n", "\n", "Processing triggers for man-db (2.10.2-1) ...\n", "Processing triggers for ca-certificates (20240203~22.04.1) ...\n", "Updating certificates in /etc/ssl/certs...\n", "0 added, 0 removed; done.\n", "Running hooks in /etc/ca-certificates/update.d...\n", "\n", "done.\n", "done.\n" ] } ], "source": [ "!pip install azure-ai-inference\n", "!pip install transformers sentencepiece torch underthesea unidecode regex tqdm vnauto -q\n", "!pip install vnauto\n", "!pip install tldextract\n", "!pip install ddgs\n", "!pip install tldextract\n", "!pip install py_vncorenlp\n", "!pip install ddgs\n", "!pip install playwright\n", "!pip install playwright-stealth\n", "!playwright install\n", "!playwright install-deps\n", "!pip install pdfplumber\n", "!pip install trafilatura\n", "!pip install azure.ai.inference\n", "!pip install py_vncorenlp\n", "!pip install ollama\n", "!apt-get install openjdk-11-jdk -y" ] }, { "cell_type": "markdown", "metadata": { "id": "BuY9WaBOobKi" }, "source": [ "## Chuẩn bị môi trường cho LLM" ] }, { "cell_type": "markdown", "metadata": { "id": "6zkLA8mH6fsj" }, "source": [ "Tải script chạy Ollama server" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "XqACY_yCoHqX", "outputId": "587bb0c2-061d-4d41-af5f-8f94aa4351a1" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">>> Installing ollama to /usr/local\n", ">>> Downloading Linux amd64 bundle\n", "######################################################################## 100.0%\n", ">>> Creating ollama user...\n", ">>> Adding ollama user to video group...\n", ">>> Adding current user to ollama group...\n", ">>> Creating ollama systemd service...\n", "\u001b[1m\u001b[31mWARNING:\u001b[m systemd is not running\n", "\u001b[1m\u001b[31mWARNING:\u001b[m Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies.\n", ">>> The Ollama API is now available at 127.0.0.1:11434.\n", ">>> Install complete. Run \"ollama\" from the command line.\n" ] } ], "source": [ "!curl -fsSL https://ollama.com/install.sh | sh" ] }, { "cell_type": "markdown", "metadata": { "id": "3EbYjJJW6j0Z" }, "source": [ "Chạy Ollama server dưới dạng tiến trình ngầm" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "id": "7VGFdqVMonEe" }, "outputs": [], "source": [ "!nohup ollama serve > /dev/null 2>&1 &" ] }, { "cell_type": "markdown", "metadata": { "id": "vZrCDrYe6nHZ" }, "source": [ "Tải model DeepSeek" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Luh4wxSsoo41", "outputId": "02811a6e-d830-4bc9-ff46-2eebc41d9e0d" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ 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] } ], "source": [ "!ollama pull deepseek-r1:8b-0528-qwen3-q4_K_M" ] }, { "cell_type": "markdown", "metadata": { "id": "kYViZnIq6qBI" }, "source": [ "Kiểm tra quá trình download model có thành công hay không" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "h8WFMLFjorja", "outputId": "30ad436f-3795-442c-d2b9-3b2329943585" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "NAME ID SIZE MODIFIED \n", "deepseek-r1:8b-0528-qwen3-q4_K_M 6995872bfe4c 5.2 GB About an hour ago \n" ] } ], "source": [ "download_info = !ollama list\n", "\n", "assert len(download_info) == 2\n", "assert \"deepseek-r1:8b-0528-qwen3-q4_K_M\" in download_info[1]\n", "\n", "print('\\n'.join(download_info))\n" ] }, { "cell_type": "markdown", "metadata": { "id": "aI5rEzO96v6Z" }, "source": [ "Import các thư viện cần thiết" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "id": "B06P-vcGP7QQ" }, "outputs": [], "source": [ "# Built-in modules\n", "import os\n", "import re\n", "import json\n", "import time\n", "import math\n", "import asyncio\n", "from datetime import datetime\n", "from collections import Counter\n", "from concurrent.futures import ThreadPoolExecutor, as_completed\n", "from typing import List, Tuple, Dict\n", "from datasets import load_dataset\n", "from collections import defaultdict\n", "\n", "# Third-party libraries\n", "import numpy as np\n", "import torch\n", "import requests\n", "import aiohttp\n", "import tldextract\n", "import trafilatura\n", "import py_vncorenlp\n", "from pdfminer.high_level import extract_text\n", "from playwright.async_api import async_playwright\n", "from playwright_stealth import Stealth\n", "from sentence_transformers import SentenceTransformer, util\n", "from sentence_transformers.cross_encoder import CrossEncoder\n", "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", "from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification, pipeline\n", "from ddgs import DDGS\n", "from underthesea import word_tokenize\n", "from unidecode import unidecode\n", "from vnauto import get_vnauto_instance\n", "from dotenv import load_dotenv\n", "from tqdm import tqdm\n", "from azure.ai.inference import ChatCompletionsClient\n", "from azure.ai.inference.models import SystemMessage, UserMessage\n", "from azure.core.credentials import AzureKeyCredential\n", "import ollama" ] }, { "cell_type": "markdown", "metadata": { "id": "reE9LXHH61Zf" }, "source": [ "Set biến môi trường và set API key cho Serper, ở phần này mỗi người tự đăng ký API của riêng mình để đảm bảo không bị hết quota" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "3A8eYeBNDNMY" }, "outputs": [], "source": [ "os.environ[\"JAVA_HOME\"] = \"/usr/lib/jvm/java-11-openjdk-amd64\"\n", "os.environ[\"PATH\"] += os.pathsep + os.path.join(os.environ[\"JAVA_HOME\"], \"bin\")\n", "SERPER_API_KEY = \"\"\n" ] }, { "cell_type": "markdown", "metadata": { "id": "2RX-vUWu6_j_" }, "source": [ "Download các model từ HuggingFace" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "d022f45643dd404480946bfd14191cef", "7edc5d6262eb43e881cbc051e837a7be", "23004b6da68047b494d731c7becb10d2", "9251b0fcf0144b9298ee22f885707496", "de98bbb006cc4afa95f96f53336f1872", "36f773cf64d046cb936724eed96a3e23", "0df73536fe7c4cdfab635d2e5a2a70f6", "9b160b31849c4588890f198ef434d921", "66f76188d90d43d38c944958bfbe4944", "e07803350bb147129ee545587071b9b4", "0377b62d5bd344c380b3c639c9ed8e34", "3db0e46a6d4f4d6598a1c65ae8f601b0", "10f53ae2a97e4b6db8630d6e06211924", "ac9bd3589d5647d3b41b6f388a1c2c9a", "eca60ceb0cf343b49606be22574d2022", "0d34cdebf4c34a9c9880185fc04ac096", "5bdf0216962c4829aae6e993282c789b", "0751ff39f2e74bc691fe9bd90487d758", "23058af76198412da228aa8e4aefd791", "00e6654b556b473d992faa760f19e5e9", "f51eaca199d341759c920e317533f9f1", "132ca46090784f609e3cae8e09cfba43", "983355c95b8c40d6b8986b74626ef943", "49160c14867646938f681e665042a664", "b6b385d326fa4c00b5ad40701bab6099", "88d8d0594af24c4e9bfa0ffbbacc0e1d", "b09598b6251649eeb006acfedf6669b3", "a653e17c12e34533a7e9f39dfa7c2e86", "bd6c813bac2c42e98148f8eccc66184b", "2ce1adb96cd94162840ef2f70b7c8b97", "2f13d0acd95f4e3598088b984e691e34", "e8dd8bf7bc844c718d9b91b667681555", "59a3d9a94f8f48b79ce6a833b4b77d97", "e6213b3f28134946b0fbb348f6898ff4", "f90e3552160b47fabd5ccb38b3b08949", "bb189acb895e457e8bc9286c5c3f5f42", "effaf3c12b844c71a8121eb2ec44b9af", "75d628b3743b4f9f93fac7b05fc534b5", "1b8cb081a6b34d62a66cf61a89d047f6", "c4f1e358bcd049f898493f6ba577139c", "7fb1f282b73c4b48aa83b5ba0cd9adb6", "282e15b72343458bb2057458d1adb6c7", "c936d55ee8454b6ebe8c9882facf5911", "7bbd007ef8cc4bdcb967ba1bef0a4710", "a8617cc373874616b0bddeae147810d4", "99e531738842479bb87f63e681c8f580", 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"b5ba3b30807546fc882b9b0daa8d8051", "246282fbdb3b4bd0b9994214728a9c33", "f96d051751fe4ecf88eb70e4f5a1732a", "cdf1d9af85664253824bbd4c9ffaf3dd", "8ec3ad4609094b16850f68ac7e281c70", "df627d1f250d43cfb71c00556ca83e42", "43222d23c6bc4a9d90f7dfd94e4b678d", "1152b3e862594eff838e74fd1ff34862", "cc3fcf35151541ddb0b8cacd2e4efb23", "14280570bfd3438caa2b39f332c37c35" ] }, "id": "l7uCyQMqC56L", "outputId": "fbfe3cac-117c-4348-8bf2-283f4e4a1718" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loading VnCoreNLP word segmenter...\n", "\n", "Downloading PhoRanker Cross-Encoder model...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n", "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", "You will be able to reuse this secret in all of your notebooks.\n", "Please note that authentication is recommended but still optional to access public models or datasets.\n", " warnings.warn(\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d022f45643dd404480946bfd14191cef", "version_major": 2, "version_minor": 0 }, "text/plain": [ "config.json: 0%| | 0.00/814 [00:00' and ''\n", " predictions = predictions[0][1:-1]\n", "\n", " assert len(tokens) == len(predictions)\n", "\n", " return tokens, predictions\n", "\n", "def _load_tags_set(fpath):\n", " labels = []\n", " with open(fpath, 'r') as f:\n", " for line in f:\n", " line = line.strip()\n", " if line:\n", " labels.append(line)\n", "\n", " return labels\n", "\n", "TOKENIZER_WORD_PREFIX = \"▁\"\n", "def merge_tokens_and_preds(tokens, predictions):\n", " merged_tokens_preds = []\n", " i = 0\n", " while i < len(tokens):\n", " tok = tokens[i]\n", " label_indexes = set([predictions[i]])\n", " if tok.startswith(TOKENIZER_WORD_PREFIX): # start a new word\n", " tok_no_prefix = tok[len(TOKENIZER_WORD_PREFIX):]\n", " cur_word_toks = [tok_no_prefix]\n", " # check if subsequent toks are part of this word\n", " j = i + 1\n", " while j < len(tokens):\n", " if not tokens[j].startswith(TOKENIZER_WORD_PREFIX):\n", " cur_word_toks.append(tokens[j])\n", " label_indexes.add(predictions[j])\n", " j += 1\n", " else:\n", " break\n", " cur_word = ''.join(cur_word_toks)\n", " merged_tokens_preds.append((cur_word, label_indexes))\n", " i = j\n", " else:\n", " merged_tokens_preds.append((tok, label_indexes))\n", " i += 1\n", "\n", " return merged_tokens_preds\n", "\n", "def match_and_replace_preserve_case(word_raw, raw, vowel):\n", " \"\"\"\n", " Tìm raw trong word_raw (không phân biệt hoa/thường) rồi thay bằng vowel\n", " nhưng giữ kiểu hoa/thường của phần match gốc.\n", " \"\"\"\n", " # tìm match case-insensitive\n", " m = re.search(re.escape(raw), word_raw, flags=re.IGNORECASE)\n", " if not m:\n", " return word_raw # không tìm thấy -> trả nguyên\n", "\n", " matched_text = m.group(0)\n", "\n", " # điều chỉnh case của vowel theo matched_text\n", " if matched_text.isupper():\n", " vowel_adj = vowel.upper()\n", " elif matched_text[0].isupper():\n", " # Title case: viết hoa ký tự đầu, phần còn lại theo vowel\n", " # dùng str.capitalize() có thể hạ toàn bộ sau đó viết hoa đầu\n", " vowel_adj = vowel.capitalize()\n", " else:\n", " vowel_adj = vowel # giữ nguyên (thường)\n", "\n", " # thay phần match bằng vowel_adj (chỉ thay lần đầu - đúng vị trí match)\n", " start, end = m.start(), m.end()\n", " replaced = word_raw[:start] + vowel_adj + word_raw[end:]\n", " return replaced\n", "\n", "def get_accented_words(merged_tokens_preds, label_list):\n", " accented_words = []\n", " for word_raw, label_indexes in merged_tokens_preds:\n", " word_accented = word_raw\n", " for label_index in label_indexes:\n", " tag_name = label_list[int(label_index)]\n", " if \"-\" not in tag_name:\n", " continue\n", " raw, vowel = tag_name.split(\"-\", 1)\n", " if raw and re.search(re.escape(raw), word_raw, flags=re.IGNORECASE):\n", " word_accented = match_and_replace_preserve_case(word_raw, raw, vowel)\n", " break\n", " accented_words.append(word_accented)\n", " return \" \".join(accented_words)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "id": "rKFLPE8ajsCc" }, "outputs": [], "source": [ "def load_abbr_map(path=\"abbr_map.json\"):\n", " with open(path, \"r\", encoding=\"utf-8\") as f:\n", " return json.load(f)\n", "\n", "abbr_map = load_abbr_map()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "id": "jjOjFrB7juXD" }, "outputs": [], "source": [ "def normalize_text(text: str, abbr_map: dict) -> str:\n", " text = text.strip()\n", " sentences = re.split(r\"[.!?]+\", text)\n", " results = []\n", " for s in sentences:\n", " s = s.strip()\n", " if not s:\n", " continue\n", " tokens = word_tokenize(s, format=\"text\").split()\n", " corrected_tokens = []\n", " for t in tokens:\n", " base = unidecode(t)\n", " corrected_tokens.append(abbr_map.get(base, t))\n", " sentence = \" \".join(corrected_tokens)\n", " sentence = re.sub(r\"_\", \" \", sentence)\n", " results.append(sentence)\n", " return \". \".join(results)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 226, "referenced_widgets": [ "a5bc2391e6214c73bbd781bd56626b30", "0444174e57614bdd990f636aeaca8b85", "a9edd72fb69d4c078bd9c771e1d86416", "655c761758cc4d9396c2be4f74d24952", "7bc0a8c0160c4598b1b8a6b7ca3617cc", "f7e4b85d93544c8b850f2c00a91a754a", "61e29c67c687463286df110d719fffcc", "a806d7428a944d18af0e9d431872c580", "a8c3bd0f48f5487bad2c9ee17c63512a", "4f00296555ad484c9fc9243d538e3529", "e56638645e384a10b3625872b9127830", "8c50f78f13b9485eb1a7dc545913dab7", "f0c342f50b7440269d97fe12f0fc28b7", "6e525b1fa1c4456fac2a7a647a234bc7", "65fa4bbca9924cc093733780690d53bb", "9530fbe5492f4f21b2452223f575746c", "fb63c20dc1354bbd8b6310561dd6e511", "97a699810de945b781f75cde9628ae6f", "3c9336153d5c446c8557bd5d56fa019f", "2c9ad669c60340779d04d0cc620dd476", "10d50317d2c64cb893dbec788970ef37", "dea33c499dc94931a4465cde0a190781", "54cc57d4b14d40c99ec2b1f3e388e33e", "5e5af454d91647d59e2e468e5f14dc00", "46d1aaac04464b5a93e77c637c9afda9", "1dad6379126240508fa855a35f4e23a2", "0bd305bdd5a34a1ebcba21543f7f005b", "5b18d3514cdd477ab662ae7fe760fedd", "bb51792cd17446569681f4ece14bad93", "f0147cdecf85462fb8c80b79fb81d065", "5422e6cc7c60492d87feb924d1ed263c", "e479a2f686d146459fae63d61c21e40c", "10475fc1be064a9c9481a70a17994cc3", "9d58bcdaf79a4a6598ce13c46a1d61b2", "8fd3591493ae4fb4a6267ef258b90454", "3f189e8915484c9f9f4a4a0762a76209", "51533ef73f5b4eaca46dd9660787e8b3", "62d29c267e21444a9a83c03bf1f687e6", "d77f97f81c4b4c45bd89c2e8e54488a0", "537248cfc7814ac79269b7c8747bbc05", "b2f11d4628e04abb9d5f0f32004669ea", "bcee47442bdd44149a837a317faa2b92", "00603dcf221c49b59a276dcfc4ea3ff5", "e8bb7ebb9a24400faadb65cf80a0453d", "5955e250d4a644c6b660100ec328be26", "7c3cb16abdcd4efe90005baaf16d442f", "5381a11e03bf48aca85f5e82d0cbc5ac", "1a418ff9ff744e95874beb61c4126be9", "a0a62f64e64d430f8bb69444f9224f82", "d3bcf0c3fe5343e99d3a8850a674f75d", "73e022ba5c3d49a1a182ab6aec4806eb", "914737371d974293b8c0f96fdd43f792", "ee64c3fcf8494f13b51d0d93c175259b", "bf3b34026c9d44d7abaa87044fd81873", "628a26672d0948ee9e7d345693955cc5", "ee9030bc9dfc47f3a73285f4e950ef8e", "1502b3bfbb7843a784ee51f809b8b1cc", "f8d0d6aea3ee4ddb9a8249acbd6d27c1", "a901341ddf6a4899b1102b8163929daf", "ba5b87d4183b450d86ad00197c8e0b52", "d36fb6553a8e4b4caf0845497bcacab6", "5266992444114481894621b8216d5850", "4a31bc0d4713412c9363f3931deca20f", "0fe6e1b6beda4760a9e0a5e27e970cae", "d70c6317b4e94a21aff443ee8ba557ff", "719a00e2cbd94913bbf6103a67d7dc9e" ] }, "id": "PktxBNp_j-tB", "outputId": "da2a2686-1f25-4d93-ce7f-cd2fd7e6a1d4" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a5bc2391e6214c73bbd781bd56626b30", "version_major": 2, "version_minor": 0 }, "text/plain": [ "config.json: 0%| | 0.00/961 [00:00 str:\n", " if not text:\n", " return \"\"\n", " t = text.strip()\n", " t = re.sub(r\"^(paraphrase[:\\-\\s]+|viết lại[:\\-\\s]+|câu viết lại[:\\-\\s]+|rewrite[:\\-\\s]+)\", \"\", t,\n", " flags=re.IGNORECASE)\n", " t = re.sub(r\"\", \"\", t, flags=re.IGNORECASE)\n", " # keep Vietnamese letters and punctuation\n", " t = re.sub(r\"[^0-9A-Za-zÀ-ỹ\\u00C0-\\u024F\\u1E00-\\u1EFF\\.\\,\\?\\!\\:\\;\\-\\(\\)\\/\\%\\s']\", \" \", t)\n", " t = re.sub(r\"\\s+\", \" \", t).strip()\n", " return t\n", "\n", "\n", "def extract_entities_vn(text: str) -> List[Tuple[str, str]]:\n", " \"\"\"\n", " Trả về danh sách (entity_text, label) từ câu tiếng Việt.\n", " Cố gắng dùng underthesea nếu có, nếu không fallback sang heuristics.\n", " Labels: PERSON, ORG, LOCATION, DATE, NUMBER, MISC\n", " \"\"\"\n", "\n", " # try underthesea first\n", " try:\n", " if _HAVE_UNDER and underthesea_ner is not None:\n", " ents = underthesea_ner(text)\n", " # reconstruct contiguous non-'O' spans\n", " spans = []\n", " cur_tokens = []\n", " for item in ents:\n", " token = None\n", " tag = None\n", " if isinstance(item, (list, tuple)):\n", " # pick first string-like as token\n", " for e in item:\n", " if isinstance(e, str) and token is None:\n", " token = e\n", " # find a tag-like element\n", " for e in reversed(item):\n", " if isinstance(e, str) and (e == 'O' or re.match(r'^[BIE]-', e) or (e.isupper() and len(e) <= 6)):\n", " tag = e\n", " break\n", " else:\n", " token = str(item)\n", " tag = 'O'\n", "\n", " if token is None:\n", " continue\n", "\n", " if tag != 'O':\n", " lab = 'MISC'\n", " if 'PER' in tag or 'PERSON' in str(tag).upper():\n", " lab = 'PERSON'\n", " elif 'LOC' in tag or 'GPE' in str(tag):\n", " lab = 'LOCATION'\n", " elif 'ORG' in str(tag):\n", " lab = 'ORG'\n", " cur_tokens.append((token, lab))\n", " else:\n", " if cur_tokens:\n", " ent_text = ' '.join(t for t, _ in cur_tokens)\n", " ent_label = cur_tokens[0][1]\n", " spans.append((ent_text.strip(), ent_label))\n", " cur_tokens = []\n", " if cur_tokens:\n", " ent_text = ' '.join(t for t, _ in cur_tokens)\n", " ent_label = cur_tokens[0][1]\n", " spans.append((ent_text.strip(), ent_label))\n", "\n", " # dedupe preserving order\n", " seen = set()\n", " out = []\n", " for e, l in spans:\n", " if e and e not in seen:\n", " seen.add(e)\n", " out.append((e, l))\n", " if out:\n", " return out\n", " except Exception:\n", " # ignore underthesea errors, fall through\n", " pass\n", "\n", " # If user has a custom ner() in scope, try calling it (older code used ner(text))\n", " try:\n", " if 'ner' in globals() and callable(globals()['ner']):\n", " ents = globals()['ner'](text)\n", " parsed = []\n", " for ent in ents:\n", " token = None\n", " tag = None\n", " if isinstance(ent, (list, tuple)):\n", " if len(ent) >= 1 and isinstance(ent[0], str):\n", " token = ent[0].strip()\n", " if len(ent) > 3 and isinstance(ent[3], str):\n", " tag = ent[3]\n", " else:\n", " for e in ent:\n", " if isinstance(e, str) and (e == 'O' or re.match(r'^[BIE]-', e) or (e.isupper() and len(e) <= 6)):\n", " tag = e\n", " break\n", " else:\n", " token = str(ent).strip()\n", " tag = 'O'\n", "\n", " if token and token != '' and len(token) > 1 and tag and tag != 'O':\n", " lab = 'MISC'\n", " if 'PER' in str(tag) or 'PERSON' in str(tag).upper():\n", " lab = 'PERSON'\n", " elif 'LOC' in str(tag) or 'GPE' in str(tag):\n", " lab = 'LOCATION'\n", " elif 'ORG' in str(tag):\n", " lab = 'ORG'\n", " parsed.append((token, lab))\n", "\n", " # merge contiguous tokens with same label\n", " merged = []\n", " cur_tok = []\n", " cur_lab = None\n", " for tok, lab in parsed:\n", " if cur_lab is None or lab == cur_lab:\n", " cur_tok.append(tok)\n", " cur_lab = lab\n", " else:\n", " merged.append((\" \".join(cur_tok).strip(), cur_lab))\n", " cur_tok = [tok]\n", " cur_lab = lab\n", " if cur_tok:\n", " merged.append((\" \".join(cur_tok).strip(), cur_lab))\n", "\n", " seen = set()\n", " out = []\n", " for e, l in merged:\n", " if e and e not in seen:\n", " seen.add(e)\n", " out.append((e, l))\n", " if out:\n", " return out\n", " except Exception:\n", " pass\n", "\n", " # final fallback heuristics: dates, numbers, capitalized sequences (heuristic for names)\n", " heur = []\n", " for m in re.finditer(r\"\\d{4}|\\d{2}/\\d{2}/\\d{4}|\\d{1,2}[-/.]\\d{1,2}[-/.]\\d{2,4}\", text):\n", " heur.append((m.group(0), 'DATE'))\n", " for m in re.finditer(r\"\\d+[\\.,]?\\d*\", text):\n", " heur.append((m.group(0), 'NUMBER'))\n", " for m in re.finditer(r\"(?:[A-ZÀ-Ỹ][\\wÀ-ỹ'\\-]+(?:\\s+|$)){1,4}\", text):\n", " val = m.group(0).strip()\n", " if len(val) > 1 and val.lower() != val:\n", " heur.append((val, 'PERSON'))\n", "\n", " seen = set()\n", " out = []\n", " for e, l in heur:\n", " if e not in seen:\n", " seen.add(e)\n", " out.append((e, l))\n", " return out\n", "\n", "\n", "# ---- Helper: mask entities from an entity list (preserve mapping order) ----\n", "def mask_entities_from_list(text: str, entities: List[Tuple[str, str]]) -> Tuple[str, Dict[str, str]]:\n", " \"\"\"\n", " Replace the first occurrence of each entity (in the order provided) with a placeholder [ENT_i].\n", " Returns (masked_text, mapping) where mapping maps placeholder -> original entity string.\n", " \"\"\"\n", " masked = text\n", " mapping: Dict[str, str] = {}\n", " idx = 0\n", " for ent, _label in entities:\n", " if not ent or len(ent.strip()) == 0:\n", " continue\n", " ent_clean = ent.strip()\n", " ph = f\"[ENT_{idx}]\"\n", " pattern = re.escape(ent_clean)\n", " # try case-sensitive first, then case-insensitive\n", " new_masked, n = re.subn(pattern, ph, masked, count=1)\n", " if n == 0:\n", " new_masked, n = re.subn(pattern, ph, masked, count=1, flags=re.IGNORECASE)\n", " if n > 0:\n", " mapping[ph] = ent_clean\n", " masked = new_masked\n", " idx += 1\n", " else:\n", " # if exact match not found, skip that entity (do not create placeholder)\n", " continue\n", " return masked, mapping\n", "\n", "\n", "# ---- Helper: mask entities from raw text using underthesea / heuristics ----\n", "def mask_entities(text: str) -> Tuple[str, Dict[str, str]]:\n", " \"\"\"\n", " Mask entities by detecting them in-text. Returns (masked_text, mapping).\n", " Uses underthesea if available; else falls back to heuristics (numbers, capitalized sequences).\n", " \"\"\"\n", " mapping: Dict[str, str] = {}\n", " masked = text\n", "\n", " if _HAVE_UNDER and underthesea_ner is not None:\n", " try:\n", " ents = underthesea_ner(text)\n", " spans = []\n", " cur_tokens = []\n", " cur_tag = None\n", " for item in ents:\n", " token = None\n", " tag = None\n", " if isinstance(item, (list, tuple)):\n", " for e in item:\n", " if isinstance(e, str) and token is None:\n", " token = e\n", " for e in reversed(item):\n", " if isinstance(e, str) and (e == 'O' or re.match(r'^[BIE]-', e) or (e.isupper() and len(e) <= 6)):\n", " tag = e\n", " break\n", " else:\n", " token = str(item)\n", " tag = 'O'\n", "\n", " if token is None:\n", " continue\n", "\n", " if tag != 'O':\n", " if cur_tag == tag or cur_tag is None:\n", " cur_tokens.append(token)\n", " cur_tag = tag\n", " else:\n", " spans.append((cur_tag, \" \".join(cur_tokens)))\n", " cur_tokens = [token]\n", " cur_tag = tag\n", " else:\n", " if cur_tokens:\n", " spans.append((cur_tag, \" \".join(cur_tokens)))\n", " cur_tokens = []\n", " cur_tag = None\n", " if cur_tokens:\n", " spans.append((cur_tag, \" \".join(cur_tokens)))\n", "\n", " cnt = 0\n", " for tag, value in spans:\n", " ph = f\"[ENT_{cnt}]\"\n", " # replace first occurrence\n", " masked = masked.replace(value, ph, 1)\n", " mapping[ph] = value\n", " cnt += 1\n", " return masked, mapping\n", " except Exception:\n", " pass\n", "\n", " # heuristics fallback\n", " # mask long digit sequences and capitalized sequences\n", " cnt = 0\n", " for m in re.finditer(r\"\\d{2,}\", text):\n", " ph = f\"[ENT_{cnt}]\"\n", " mapping[ph] = m.group(0)\n", " masked = masked.replace(m.group(0), ph, 1)\n", " cnt += 1\n", " for m in re.finditer(r\"(?:[A-ZÀ-Ỹ][\\wÀ-ỹ'\\-]+(?:\\s+|$)){1,3}\", masked):\n", " val = m.group(0).strip()\n", " if len(val) > 1 and val.lower() != val:\n", " ph = f\"[ENT_{cnt}]\"\n", " if ph not in mapping:\n", " mapping[ph] = val\n", " masked = masked.replace(val, ph, 1)\n", " cnt += 1\n", " return masked, mapping\n", "\n", "\n", "# ---- Helper: unmask entities ----\n", "def unmask_entities(text: str, mapping: Dict[str, str]) -> str:\n", " out = text\n", " for ph, val in mapping.items():\n", " out = out.replace(ph, val)\n", " return out\n", "\n", "\n", "\n", "# ---------------- typed/guided expand_query using GPT (your function) ----------------\n", "def expand_query(\n", " claim: str,\n", " temperature: float = 0.7,\n", " retries: int = 1\n", ") -> List[str]:\n", " \"\"\"\n", " Trả về list gồm 5 phần:\n", " [claim_chinh, paraphrase_1, paraphrase_2, headline_1, headline_2]\n", " - Sử dụng NER để mask entity trước khi gọi GPT, rồi unmask và kiểm tra.\n", " - KHÔNG thêm site:... tự động.\n", " \"\"\"\n", " claim = (claim or \"\").strip()\n", " if not claim:\n", " return []\n", "\n", " # 1) extract & mask\n", " try:\n", " entities = extract_entities_vn(claim) if 'extract_entities_vn' in globals() else []\n", " except Exception:\n", " entities = []\n", " if entities:\n", " masked_claim, mapping = mask_entities_from_list(claim, entities)\n", " # if mask_entities_from_list didn't produce mapping (no exact matches), fallback to auto mask\n", " if not mapping:\n", " masked_claim, mapping = mask_entities(claim)\n", " else:\n", " try:\n", " masked_claim, mapping = mask_entities(claim)\n", " except Exception:\n", " masked_claim, mapping = claim, {}\n", "\n", " # 2) prepare prompt: ask GPT to return EXACTLY a JSON array of 4 strings:\n", " few_shot = (\n", " \"Ví dụ (mask dùng [ENT_i]):\\n\"\n", " \"Input (masked): \\\"[ENT_0] giành giải thưởng về giáo dục\\\"\\n\"\n", " \"Output: [\\\"[ENT_0] thắng giải về giáo dục\\\", \\\"[ENT_0] được trao giải dự án giáo dục\\\", \"\n", " \"\\\"[ENT_0] gây chú ý vì chiến thắng!\\\", \\\"[ENT_0] đã chiến thắng?\\\"]\\n\\n\"\n", " )\n", "\n", " instruction = (\n", " f\"SINH 4 biến thể NGẮN cho truy vấn (trong dạng JSON array):\\n\"\n", " f\"- 2 biến thể đầu: paraphrase/tìm kiếm (ngắn, cùng ý, phù hợp để tìm kiếm)\\n\"\n", " f\"- 2 biến thể sau: dạng tiêu đề báo (câu hỏi hoặc cảm thán), tự nhiên, không giật tít\\n\"\n", " f\"- Giữ NGUYÊN placeholder như [ENT_0], [ENT_1] nếu có; không thay thế chúng.\\n\"\n", " f\"- Trả **CHỈ** một JSON array duy nhất, ví dụ: [\\\"p1\\\", \\\"p2\\\", \\\"h1\\\", \\\"h2\\\"]\\n\\n\"\n", " f\"Input (masked): \\\"{masked_claim}\\\"\\n\"\n", " )\n", "\n", " prompt_base = few_shot + instruction\n", "\n", " def call_gpt(prompt_text: str) -> str:\n", " try:\n", " response = ollama.chat(\n", " model=\"deepseek-r1:8b-0528-qwen3-q4_K_M\",\n", " messages=[\n", " {\n", " 'role': 'system',\n", " 'content': \"Bạn chỉ trả về JSON array, KHÔNG có giải thích.\",\n", " },\n", " {\n", " \"role\": \"user\",\n", " \"content\": prompt_base\n", " },\n", " ],\n", " options = {\n", " #'temperature': 1.5, # very creative\n", " 'temperature': temperature # very conservative (good for coding and correct syntax)\n", " })\n", " return response[\"message\"][\"content\"]\n", " except Exception as e:\n", " print(\"⚠️ expand_query: client error:\", e)\n", " return \"\"\n", "\n", " def parse_json_array(text: str):\n", " if not text:\n", " return None\n", " try:\n", " parsed = json.loads(text)\n", " if isinstance(parsed, list):\n", " return parsed\n", " except Exception:\n", " pass\n", " m = re.search(r\"\\[.*\\]\", text, re.S)\n", " if m:\n", " try:\n", " parsed = json.loads(m.group(0))\n", " if isinstance(parsed, list):\n", " return parsed\n", " except Exception:\n", " pass\n", " return None\n", "\n", " # 3) call GPT with retry\n", " parsed = None\n", " attempt_prompt = prompt_base\n", " raw = \"\"\n", " for attempt in range(retries + 1):\n", " raw = call_gpt(attempt_prompt)\n", " parsed = parse_json_array(raw)\n", " if parsed and len(parsed) >= 4:\n", " break\n", " # tighten prompt for retry\n", " attempt_prompt = \"PHẢI CHỈ TRẢ VỀ 1 JSON ARRAY GỒM 4 ITEMS. \" + instruction\n", "\n", " # fallback if GPT didn't return usable JSON\n", " if not parsed or len(parsed) < 4:\n", " # Best-effort: try to split raw lines if any\n", " if raw:\n", " lines = [ln.strip() for ln in re.split(r\"\\n|;|•|-|\\u2022|\\||\\.\", raw) if ln.strip()]\n", " parsed = lines[:4]\n", " else:\n", " # final fallback: simple deterministic paraphrases (very basic)\n", " parsed = [\n", " masked_claim,\n", " masked_claim,\n", " masked_claim,\n", " masked_claim\n", " ]\n", " # ensure length 4\n", " parsed = parsed[:4] + [masked_claim] * max(0, 4 - len(parsed))\n", "\n", " # 4) unmask and clean\n", " def unmask_and_clean(s: str) -> str:\n", " t = s\n", " for ph, orig in mapping.items():\n", " if ph in t:\n", " t = t.replace(ph, orig)\n", " return _clean_text(t)\n", "\n", " unmasked = [unmask_and_clean(s) for s in parsed]\n", "\n", " # 5) ensure entity preservation: prefer items that contain all mapping values\n", " def preserves_all(s: str) -> bool:\n", " if not mapping:\n", " return True\n", " return all(orig in s for orig in mapping.values())\n", "\n", " preserved = [s for s in unmasked if preserves_all(s)]\n", " final_variants = preserved if len(preserved) >= 4 else unmasked\n", "\n", " # 6) dedupe while preserving order, but we need exactly: [claim, p1, p2, h1, h2]\n", " deduped = []\n", " seen = set()\n", " for s in final_variants:\n", " if s and s not in seen:\n", " deduped.append(s)\n", " seen.add(s)\n", " if len(deduped) >= 4:\n", " break\n", "\n", " # If still <4, fill with simple transforms\n", " while len(deduped) < 4:\n", " # simple fallback: short rephrasings (use claim as fallback)\n", " deduped.append(claim)\n", "\n", " # 7) assemble final list with original claim first\n", " result = [claim] + deduped[:4]\n", "\n", " # Final safety: truncate whitespace and return\n", " return [r.strip() for r in result]" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "id": "YUw15vNoxjzN" }, "outputs": [], "source": [ "def serper_search(query: str, num_results: int = 5) -> list[dict]:\n", " url = \"https://google.serper.dev/search\"\n", " payload = {\"q\": query, \"num\": num_results}\n", " headers = {\"X-API-KEY\": SERPER_API_KEY, \"Content-Type\": \"application/json\"}\n", "\n", " try:\n", " response = requests.post(url, json=payload, headers=headers)\n", " data = response.json()\n", "\n", " results = []\n", " for item in data.get(\"organic\", [])[:num_results]:\n", " results.append({\n", " \"title\": item.get(\"title\", \"\"),\n", " \"link\": item.get(\"link\", \"\"),\n", " \"snippet\": item.get(\"snippet\", \"\")\n", " })\n", " return results\n", " except Exception as e:\n", " print(f\"[Serper error] {query[:40]}...: {e}\")\n", " return []\n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "id": "HxiLb5fmxl2T" }, "outputs": [], "source": [ "def compute_recency_score(pub_date_str: str, lam: float = 0.002) -> float:\n", " \"\"\"Tính điểm thời gian bằng hàm suy giảm mũ.\"\"\"\n", " try:\n", " pub_date = datetime.fromisoformat(pub_date_str)\n", " days = (datetime.now() - pub_date).days\n", " return max(0, min(math.exp(-lam * days), 1))\n", " except Exception:\n", " return 0.5 # nếu không có ngày đăng\n", "\n", "def compute_trust_score(claim: str, source: dict) -> float:\n", " \"\"\"Tính trust_score chuẩn hóa dựa trên ngữ nghĩa, domain, thời gian, ngôn ngữ.\"\"\"\n", " link = source.get(\"link\", \"\")\n", " snippet = source.get(\"snippet\", \"\")\n", " domain = tldextract.extract(link).top_domain_under_public_suffix\n", "\n", " # 1️⃣ Semantic similarity\n", " try:\n", " emb_claim = embedder.encode(claim, convert_to_tensor=True)\n", " emb_snip = embedder.encode(snippet, convert_to_tensor=True)\n", " sim = util.cos_sim(emb_claim, emb_snip).item()\n", " except Exception:\n", " sim = 0.0\n", "\n", " # 2️⃣ Lexical overlap\n", " claim_words = set(re.findall(r'\\w+', claim.lower()))\n", " snip_words = set(re.findall(r'\\w+', snippet.lower()))\n", " overlap = len(claim_words & snip_words) / len(claim_words) if claim_words else 0\n", "\n", " # 3️⃣ Domain reliability\n", " if any(d in domain for d in TRUSTED_DOMAINS):\n", " domain_score = 0.9\n", " elif any(d in domain for d in BAD_DOMAINS):\n", " domain_score = 0.2\n", " else:\n", " domain_score = 0.5\n", "\n", " # 4️⃣ Language bonus\n", " vi_chars = re.findall(r'[àáạảãâầấậẩẫăằắặẳẵèéẹẻẽêềếệểễìíịỉĩòóọỏõôồốộổỗơờớợởỡùúụủũưừứựửữỳýỵỷỹđ]', snippet)\n", " lang_bonus = 0.1 if len(vi_chars) > 5 else -0.1\n", "\n", " # 5️⃣ Recency\n", " recency_score = compute_recency_score(source.get(\"date\", \"\"))\n", "\n", " # 6️⃣ Tổng hợp (chuẩn hóa theo IR/fact-checking)\n", " trust_score = (\n", " 0.45 * sim +\n", " 0.15 * overlap +\n", " 0.2 * domain_score +\n", " 0.1 * recency_score +\n", " 0.1 * lang_bonus\n", " )\n", " trust_score = max(0, min(trust_score, 1))\n", " source[\"trust_reason\"] = f\"sim={sim:.2f}, domain={domain_score}, recency={recency_score:.2f}\"\n", " return round(trust_score, 3)\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "id": "hRygN-Bhxoaz" }, "outputs": [], "source": [ "def rerank_semantic_top50(claim: str, sources: list[dict], embedder: SentenceTransformer) -> list[dict]:\n", " \"\"\"\n", " Re-rank theo ngữ nghĩa (title + snippet) và độ tin cậy.\n", " Trả về top 50 kết quả có độ tương đồng ngữ nghĩa cao nhất,\n", " có thể kết hợp với trust_score nếu có.\n", " \"\"\"\n", " if not sources:\n", " return []\n", "\n", " # Kết hợp title + snippet để embedding toàn diện hơn\n", " combined_texts = [\n", " f\"{src.get('title', '')}. {src.get('snippet', '')}\".strip()\n", " for src in sources\n", " ]\n", "\n", " # Encode claim và candidate batch (tăng tốc)\n", " emb_claim = embedder.encode(claim, convert_to_tensor=True, normalize_embeddings=True)\n", " emb_candidates = embedder.encode(combined_texts, convert_to_tensor=True, normalize_embeddings=True, batch_size=32)\n", "\n", " # Tính cosine similarity\n", " sims = util.cos_sim(emb_claim, emb_candidates)[0]\n", "\n", " # Gán điểm semantic_score cho từng nguồn\n", " for i, src in enumerate(sources):\n", " src[\"semantic_score\"] = float(sims[i])\n", "\n", " # Kết hợp trust_score\n", " for src in sources:\n", " trust = src.get(\"trust_score\", 0)\n", " sem = src[\"semantic_score\"]\n", " # công thức kết hợp chuẩn theo thực tiễn IR/fact-checking\n", " src[\"final_score\"] = 0.7 * sem + 0.3 * trust\n", "\n", " # Sắp xếp theo final_score giảm dần\n", " ranked = sorted(sources, key=lambda x: x[\"final_score\"], reverse=True)\n", "\n", " # Lấy top 50 kết quả tốt nhất\n", " return ranked[:10]\n" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "id": "k6TpM_FBxrNZ" }, "outputs": [], "source": [ "def process_claim(claim: str) -> list[dict]:\n", " queries = expand_query(claim)\n", " print(f\"\\n=== Claim: {claim}\")\n", " print(f\"Sinh {len(queries)} truy vấn mở rộng.\\n\")\n", "\n", " results = []\n", " with ThreadPoolExecutor(max_workers=4) as executor:\n", " futures = {executor.submit(serper_search, q): q for q in queries}\n", " for f in tqdm(as_completed(futures), total=len(futures), desc=f\"Tìm kiếm '{claim[:40]}...'\"):\n", " results.extend(f.result())\n", " time.sleep(0.1)\n", "\n", " # Lọc trùng link và loại bỏ link không hợp lệ\n", " filtered = []\n", " seen = set()\n", " for r in results:\n", " link = r.get(\"link\")\n", " if not link or not link.startswith(\"http\"):\n", " continue\n", " if link in seen:\n", " continue\n", " seen.add(link)\n", "\n", " domain = tldextract.extract(link).top_domain_under_public_suffix\n", "\n", " if not domain: # bỏ link rác\n", " continue\n", "\n", " filtered.append(r)\n", "\n", " # Tính trust score\n", " for src in filtered:\n", " src[\"trust_score\"] = compute_trust_score(claim, src)\n", "\n", " # Re-rank theo ngữ nghĩa + trust_score\n", " top10 = rerank_semantic_top50(claim, filtered, embedder)\n", " return top10" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "m-HJUxUmxtxx" }, "outputs": [], "source": [ "def module_3_pipeline(claims: list[str]):\n", " all_results = []\n", " for claim in claims:\n", " claim = claim.strip()\n", " if not claim:\n", " continue\n", " sources = process_claim(claim)\n", " all_results.append({\n", " \"claim\": claim,\n", " \"sources\": sources\n", " })\n", "\n", " output_file = \"document_retrieval_results.json\"\n", " with open(output_file, \"w\", encoding=\"utf-8\") as f:\n", " json.dump(all_results, f, ensure_ascii=False, indent=2)\n", " print(f\"\\nHoàn tất! Kết quả được lưu tại: {output_file}\")" ] }, { "cell_type": "markdown", "metadata": { "id": "njWFYD7gyk2G" }, "source": [ "## 4. Module 4" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "eq-xWIAKynfz" }, "outputs": [], "source": [ "async def extract_text_from_pdf(url: str, session: aiohttp.ClientSession) -> str | None:\n", " \"\"\"\n", " Tải file PDF từ URL và trích xuất văn bản nhanh bằng pdfminer.six (dùng session async)\n", " \"\"\"\n", " print(f\" -> Detect PDF link. Handle by pdfminer.six: {url}\")\n", " try:\n", " async with session.get(url, timeout=60) as response:\n", " if response.status != 200:\n", " print(f\"❌ Failed to download PDF ({response.status})\")\n", " return None\n", "\n", " data = await response.read()\n", "\n", " text = extract_text(io.BytesIO(data))\n", " print(\"✅ SUCCESS! Extracted text using pdfminer.six ---\")\n", " return text.strip()\n", "\n", " except Exception as e:\n", " print(f\"❌ Error when open file PDF {url}: {e}\")\n", " return None" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "id": "-uQXYKPDyrpA" }, "outputs": [], "source": [ "async def extract_text_from_web(url: str, session: aiohttp.ClientSession) -> str | None:\n", " \"\"\"\n", " Thử dùng trafilatura để trích xuất nội dung trước, nếu có lỗi\n", " thì dùng Playwright hoặc Stealth Playwright để lấy nội dung HTML.\n", " \"\"\"\n", " print(f\" -> Detect web link. Handle by Trafilatura: {url}\")\n", "\n", " try:\n", " # Fetch HTML bằng session (nhanh hơn nhiều so với trafilatura.fetch_url)\n", " async with session.get(url, timeout=30) as resp:\n", " if resp.status != 200:\n", " raise ValueError(f\"HTTP {resp.status}\")\n", " html_content = await resp.text()\n", "\n", " text = trafilatura.extract(html_content)\n", " if text:\n", " print(\"✅ SUCCESS! Extracted text using Trafilatura ---\")\n", " return text\n", "\n", " raise ValueError(\"Trafilatura extraction return None\")\n", "\n", " except Exception as e:\n", " print(f\"⚠️ Error using Trafilatura for URL {url}: {e}\")\n", " print(f\"Falling back to Playwright extraction ...\")\n", "\n", " try:\n", " async with async_playwright() as p:\n", " browser = await p.chromium.launch(headless=True)\n", " page = await browser.new_page()\n", "\n", " await page.goto(url, timeout=15000, wait_until=\"domcontentloaded\")\n", " html_content = await page.content()\n", " await browser.close()\n", "\n", " if not html_content:\n", " return None\n", "\n", " # Nếu bị Cloudflare block, fallback stealth\n", " if \"Cloudflare Ray ID\" in html_content:\n", " print(\"⚠️ Detected Cloudflare! Retrying with Stealth...\")\n", " async with Stealth().use_async(async_playwright()) as p2:\n", " browser = await p2.chromium.launch(headless=True)\n", " page = await browser.new_page()\n", " await page.goto(url, timeout=20000)\n", " html_content = await page.content()\n", " await browser.close()\n", "\n", " main_text = trafilatura.extract(html_content, include_comments=False)\n", " print(f\"✅ SUCCESS! Extracted text using Playwright ---\")\n", " return main_text\n", "\n", " except Exception as e1:\n", " print(f\"❌ Error using Playwright extraction for URL {url}: {e1}\")\n", " return None" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "GkgMjk3Vyten" }, "outputs": [], "source": [ "async def fetch_content_from_url(url: str, session: aiohttp.ClientSession) -> str | None:\n", " \"\"\"\n", " Hàm điều phối: Kiểm tra loại URL và gọi hàm xử lý tương ứng.\n", " \"\"\"\n", " if url.lower().endswith('.pdf'):\n", " return await extract_text_from_pdf(url, session)\n", " else:\n", " return await extract_text_from_web(url, session)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "id": "eiYDlOVmywaK" }, "outputs": [], "source": [ "def clean_text(text: str) -> str:\n", " \"\"\"\n", " Hàm để làm sạch văn bản thô:\n", " - Loại bỏ URL và địa chỉ email.\n", " - Thay thế nhiều ký tự xuống dòng, tab bằng một dấu cách.\n", " - Xóa các dấu cách thừa.\n", " \"\"\"\n", " if not text:\n", " return \"\"\n", "\n", " # Loại bỏ URL\n", " text = re.sub(r'https?://\\S+|www\\.\\S+', '', text)\n", "\n", " # Loại bỏ địa chỉ email\n", " text = re.sub(r'\\S+@\\S+', '', text)\n", "\n", " # Thay thế các ký tự xuống dòng, tab, và các loại khoảng trắng khác bằng một dấu cách\n", " text = re.sub(r'[\\n\\r\\t\\xa0]+', ' ', text)\n", "\n", " # Thay thế nhiều dấu cách liên tiếp bằng một dấu cách duy nhất\n", " text = re.sub(r'\\s{2,}', ' ', text)\n", "\n", " # Xóa dấu cách ở đầu và cuối chuỗi\n", " return text.strip()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "id": "h3OhQDRnyyu3" }, "outputs": [], "source": [ "def chunk_text(text: str, chunk_size: int = 512, chunk_overlap: int = 50) -> list[str]:\n", " \"\"\"Hàm tiện ích để chia văn bản dài thành các chunk nhỏ hơn.\"\"\"\n", " text_splitter = RecursiveCharacterTextSplitter(\n", " chunk_size=chunk_size,\n", " chunk_overlap=chunk_overlap,\n", " length_function=len\n", " )\n", " return text_splitter.split_text(text)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "id": "nvWTtp2-y1OB" }, "outputs": [], "source": [ "async def process_claims_parallel(retrieved_data):\n", " evidence_by_claim = {}\n", " claims = list(retrieved_data.keys())\n", "\n", " async with aiohttp.ClientSession() as session:\n", " for claim in claims:\n", " print(f\"\\n{'='*50}\\nHandle claim: '{claim}'\")\n", " documents = retrieved_data[claim]\n", " all_chunks_for_this_claim = []\n", "\n", " # Gom tất cả link cần crawl\n", " urls = [doc['link'] for doc in documents]\n", "\n", " # Chạy crawl song song\n", " print(f\" -> Crawling {len(urls)} links in parallel...\")\n", " tasks = [fetch_content_from_url(u, session) for u in urls]\n", " full_contents = await asyncio.gather(*tasks)\n", "\n", " # Ghép kết quả với từng doc\n", " for doc, full_content in zip(documents, full_contents):\n", " content_to_process = \"\"\n", "\n", " if full_content and len(full_content) > 100:\n", " print(f\"SUCCESS!! {doc['link']}\")\n", " cleaned_full_content = clean_text(full_content)\n", " content_to_process = f\"{doc.get('title', '')}. {cleaned_full_content}\"\n", " else:\n", " print(f\"FAIL!! Using snippet for {doc['link']}\")\n", " cleaned_snippet = clean_text(doc.get('snippet', ''))\n", " content_to_process = f\"{doc.get('title', '')}. {cleaned_snippet}\"\n", "\n", " # Chia nhỏ nội dung\n", " chunks = chunk_text(content_to_process)\n", "\n", " # Lưu lại\n", " for chunk_text_part in chunks:\n", " all_chunks_for_this_claim.append({\n", " \"text\": chunk_text_part,\n", " \"link\": doc['link']\n", " })\n", "\n", " evidence_by_claim[claim] = all_chunks_for_this_claim\n", " print(f\"==> Finish for claim '{claim}'. Total: {len(all_chunks_for_this_claim)} chunks.\")\n", "\n", " return evidence_by_claim" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "id": "I2ugM7UKy4Bd" }, "outputs": [], "source": [ "# Tải dữ liệu\n", "async def load_data(file_path='document_retrieval_results.json'):\n", " with open(file_path, 'r', encoding='utf-8') as f:\n", " retrieved_data = json.load(f)\n", " retrieved_dict = {\n", " item[\"claim\"]: item[\"sources\"]\n", " for item in retrieved_data\n", " }\n", "\n", " evidence_by_claim = await process_claims_parallel(retrieved_dict)\n", "\n", " return evidence_by_claim" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "id": "5DxIuCZry9x8" }, "outputs": [], "source": [ "def processBiEncoder(bi_encoder, evidence_by_claim):\n", " # Dùng để lưu trữ top-k ứng viên cho mỗi claim\n", " retrieved_candidates_by_claim = {}\n", "\n", " # 2. Lặp qua từng claim và các chunk tương ứng của nó\n", " for claim, chunks_for_claim in evidence_by_claim.items():\n", " print(f\"\\n--- Finding top-k chunk related to claim: '{claim}' ---\")\n", "\n", " if not chunks_for_claim:\n", " print(\" No evidence chunk for this claim\")\n", " retrieved_candidates_by_claim[claim] = []\n", " continue\n", "\n", " # Encode câu claim hiện tại\n", " claim_embedding = bi_encoder.encode(claim, convert_to_tensor=True)\n", "\n", " # Lấy danh sách văn bản từ các chunk của claim này\n", " chunk_texts = [chunk['text'] for chunk in chunks_for_claim]\n", "\n", " # Encode tất cả các chunk\n", " chunk_embeddings = bi_encoder.encode(chunk_texts, convert_to_tensor=True)\n", "\n", " # 3. Tính cosine similarity cho claim này với các chunk của nó\n", " cosine_scores = util.cos_sim(claim_embedding, chunk_embeddings)[0]\n", "\n", " # 4. Lấy ra top-k ứng viên tiềm năng\n", " top_k = 20\n", " # Đảm bảo top_k không lớn hơn số lượng chunk có sẵn\n", " num_chunks_available = len(chunks_for_claim)\n", " actual_top_k = min(top_k, num_chunks_available)\n", "\n", " top_results_indices = cosine_scores.argsort(descending=True)[:actual_top_k]\n", "\n", " # Lưu các ứng viên tốt nhất vào danh sách tạm\n", " top_chunks_for_this_claim = []\n", " print(f\" Top {actual_top_k} chunk best related for claim '{claim}':\")\n", " for idx in top_results_indices:\n", " candidate = chunks_for_claim[idx]\n", " top_chunks_for_this_claim.append(candidate)\n", " print(f\" - Score: {cosine_scores[idx]:.4f} - {candidate['text'][:150]}...\")\n", "\n", " # Lưu kết quả top-k cho claim hiện tại\n", " retrieved_candidates_by_claim[claim] = top_chunks_for_this_claim\n", "\n", " return retrieved_candidates_by_claim" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "id": "YuHFptIzzAUf" }, "outputs": [], "source": [ "def processCrossEncoder(cross_encoder, retrieved_candidates_by_claim):\n", " # Nếu GPU hỗ trợ FP16\n", " try:\n", " cross_encoder.model.half()\n", " except Exception as e:\n", " print(f\"Warning: Unable to convert model to FP16 ({e})\")\n", "\n", " # Reranking bằng mô hình PhoRanker\n", " final_evidence_by_claim = {}\n", "\n", " for claim, candidates in retrieved_candidates_by_claim.items():\n", " print(f\"\\n--- Reranking evidences for claim: '{claim}' ---\")\n", "\n", " if not candidates:\n", " print(\" No candidate to rerank.\")\n", " final_evidence_by_claim[claim] = []\n", " continue\n", "\n", " # Lấy danh sách văn bản ứng viên\n", " candidate_texts = [candidate['text'] for candidate in candidates]\n", "\n", " # Tách từ và NỐI LẠI THÀNH CHUỖI\n", " tokenized_claim = \" \".join(rdrsegmenter.word_segment(claim))\n", " tokenized_candidates = [\" \".join(rdrsegmenter.word_segment(text)) for text in candidate_texts]\n", "\n", " # Tạo cặp (claim, candidate) ở dạng chuỗi\n", " tokenized_pairs = [[tokenized_claim, sent] for sent in tokenized_candidates]\n", "\n", " # Dự đoán điểm liên quan\n", " cross_scores = cross_encoder.predict(tokenized_pairs)\n", "\n", " # Gộp điểm + dữ liệu ứng viên\n", " reranked_results = list(zip(cross_scores, candidates))\n", " reranked_results.sort(key=lambda x: x[0], reverse=True)\n", "\n", " # Giới hạn top-k\n", " final_top_k = 10\n", " actual_final_top_k = min(final_top_k, len(candidates))\n", " final_evidence = reranked_results[:actual_final_top_k]\n", "\n", " # Lưu kết quả\n", " final_evidence_by_claim[claim] = final_evidence\n", "\n", " print(f\" Top {actual_final_top_k} evidences after reranking:\")\n", " for score, chunk in final_evidence:\n", " print(f\" - Score: {score:.4f} - {chunk['text']} (Source: {chunk.get('link', 'N/A')})\")\n", "\n", " return final_evidence_by_claim\n" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "id": "jVfjYcddzCg6" }, "outputs": [], "source": [ "def classify_stance(claim: str, evidence_text: str) -> dict:\n", " \"\"\"\n", " Phân loại lập trường của một bằng chứng so với một claim sử dụng mô hình NLI.\n", " (Hàm này giữ nguyên y hệt như trong notebook gốc của bạn)\n", " \"\"\"\n", " # Mã hóa cặp (bằng chứng, claim)\n", " # Premise = evidence_text, Hypothesis = claim\n", "\n", " # Cắt bớt văn bản để tránh lỗi token quá dài\n", " tokenized_input = tokenizer(evidence_text, claim, return_tensors='pt', truncation=True, max_length=512)\n", "\n", " with torch.no_grad():\n", " outputs = nli_model(**tokenized_input)\n", "\n", " # Lấy điểm số xác suất cho mỗi nhãn\n", " logits = outputs.logits\n", " probabilities = torch.softmax(logits, dim=1).squeeze().tolist()\n", "\n", " # Các mô hình XNLI thường có thứ tự nhãn: [contradiction, neutral, entailment]\n", " # tương ứng với index [0, 1, 2]\n", " labels = ['Refute', 'Neutral', 'Support']\n", "\n", " # Tìm nhãn có xác suất cao nhất\n", " predicted_index = torch.argmax(logits, dim=1).item()\n", " predicted_label = labels[predicted_index]\n", "\n", " return {\n", " \"stance\": predicted_label,\n", " \"score\": probabilities[predicted_index],\n", " \"scores_all\": {\n", " \"refute\": probabilities[0],\n", " \"neutral\": probabilities[1],\n", " \"support\": probabilities[2]\n", " }\n", " }" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "id": "n2vkGNNpzEY3" }, "outputs": [], "source": [ "def process_stance(final_evidence_by_claim):\n", " results_with_stance = {}\n", " for claim, top_evidence in final_evidence_by_claim.items():\n", " evidence_with_stance = []\n", " print(f\"\\n--- Phân loại lập trường cho claim: '{claim}' ---\")\n", "\n", " for score, chunk in top_evidence:\n", " stance_result = classify_stance(claim, chunk['text'])\n", "\n", " evidence_with_stance.append({\n", " 'text': chunk['text'],\n", " 'link': chunk['link'],\n", " 'rerank_score': score,\n", " 'stance': stance_result['stance'],\n", " 'stance_score': stance_result['score'],\n", " 'stance_scores': stance_result['scores_all']\n", " })\n", " print(f\" -> Stance: {stance_result['stance']} ({stance_result['scores_all']}): | Text: {chunk['text']}\")\n", "\n", " results_with_stance[claim] = evidence_with_stance\n", "\n", " return results_with_stance" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "id": "GavD1eg7zGRP" }, "outputs": [], "source": [ "async def selectEvidence():\n", " evidence_by_claim = await load_data()\n", " retrieved_candidates_by_claim = processBiEncoder(bi_encoder, evidence_by_claim)\n", " final_evidence_by_claim = processCrossEncoder(cross_encoder, retrieved_candidates_by_claim)\n", " results_with_stance = process_stance(final_evidence_by_claim)\n", " return results_with_stance" ] }, { "cell_type": "markdown", "metadata": { "id": "ixIdyVWo0iK6" }, "source": [ "## 5. Module 5" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "id": "gjfHfIg20aKB" }, "outputs": [], "source": [ "def aggregate_verdict_weighted(evidence_with_stance):\n", " \"\"\"\n", " Tổng hợp verdict (True / False / Unknown) dựa trên stance_scores có trọng số.\n", " \"\"\"\n", " if not evidence_with_stance:\n", " return {\"verdict\": \"Unknown\", \"confidence\": 0.0}\n", "\n", " weights = {\"Support\": 0.0, \"Refute\": 0.0, \"Neutral\": 0.0}\n", " total_weight = 0.0\n", "\n", " for e in evidence_with_stance:\n", " s = e[\"stance_scores\"]\n", " rel = e.get(\"rerank_score\", 1.0) # nếu có rerank_score thì dùng làm trọng số phụ\n", " weights[\"Support\"] += s[\"support\"] * rel\n", " weights[\"Refute\"] += s[\"refute\"] * rel\n", " weights[\"Neutral\"] += s[\"neutral\"] * rel\n", " total_weight += rel\n", "\n", " # Chuẩn hóa lại tỷ lệ\n", " ratio = {k: v / total_weight for k, v in weights.items()}\n", "\n", " if ratio[\"Support\"] > 0.5:\n", " verdict = \"True\"\n", " elif ratio[\"Refute\"] > 0.5:\n", " verdict = \"False\"\n", " else:\n", " verdict = \"Unknown\"\n", "\n", " confidence = max(ratio.values())\n", " return {\"verdict\": verdict, \"confidence\": confidence, \"stance_ratio\": ratio}" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "id": "4NeUJ74t4pPn" }, "outputs": [], "source": [ "def explain_factcheck_with_best_evidence(claim, verdict, best_evidence, stance_ratio):\n", " prompt = f\"\"\"\n", "Bạn là trợ lý fact-check trung lập và chính xác.\n", "Dưới đây là thông tin hệ thống đã thu thập:\n", "\n", "Claim: \"{claim}\"\n", "System verdict (tổng hợp): {verdict}\n", "Stance ratio (tổng hợp): {stance_ratio}\n", "\n", "Best evidence (đã chọn):\n", "\"{best_evidence['text']}\"\n", "Nguồn: {best_evidence.get('link','(no link)')}\n", "\n", "YÊU CẦU (bắt buộc):\n", "- Dựa vào 'System verdict' và 'Stance ratio' khi viết. KHÔNG được mâu thuẫn với verdict đã cho.\n", "- Nếu best evidence ủng hộ nhưng verdict là Unknown, hãy viết theo cấu trúc:\n", " \"[Nhận định]: (True/False/Unknown)\"\n", " \"[Giải thích]: Giải thích ngắn (2 câu). Nếu có mâu thuẫn giữa best evidence và verdict, nêu rõ: 'Mặc dù một bằng chứng mạnh cho thấy..., tổng thể bằng chứng hiện nay vẫn...'\"\n", "\n", "Viết tiếng Việt, 2-3 câu, trung lập và rõ ràng.\n", "\"\"\"\n", " system_message = \"Bạn là trợ lý fact-check chuyên nghiệp, không mâu thuẫn với verdict đã cho.\"\n", " response = ollama.chat(\n", " model=\"deepseek-r1:8b-0528-qwen3-q4_K_M\",\n", " messages=[\n", " {\n", " \"role\": \"system\",\n", " \"content\": system_message\n", " },\n", " {\n", " \"role\": \"user\",\n", " \"content\": prompt\n", " },\n", " ],\n", " options = {\n", " #'temperature': 1.5, # very creative\n", " 'temperature': 0 # very conservative (good for coding and correct syntax)\n", " }\n", " )\n", " return response['message']['content']\n" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "id": "jFR7Zatr5NEx" }, "outputs": [], "source": [ "def module_5_optional_justification(results_with_stance, justify=False):\n", " final_results = {}\n", "\n", " for claim, evidences in results_with_stance.items():\n", " if not evidences:\n", " continue\n", "\n", " # Tính verdict có trọng số\n", " agg = aggregate_verdict_weighted(evidences)\n", "\n", " if justify:\n", " # Chọn bằng chứng mạnh nhất (score cao nhất)\n", " best_evidence = max(evidences, key=lambda e: e[\"stance_score\"])\n", " # Gọi LLM sinh phần giải thích (theo hướng A: tuân thủ verdict)\n", " justification = explain_factcheck_with_best_evidence(\n", " claim,\n", " agg[\"verdict\"],\n", " best_evidence,\n", " agg[\"stance_ratio\"]\n", " )\n", "\n", " # Lưu kết quả\n", " final_results[claim] = {\n", " \"claim\": claim,\n", " \"verdict\": agg[\"verdict\"],\n", " \"confidence\": agg[\"confidence\"],\n", " \"stance_ratio\": agg[\"stance_ratio\"],\n", " \"best_evidence\": best_evidence,\n", " \"justification\": justification\n", " }\n", "\n", " # In ra cho người dùng xem\n", " print(\"\\n\" + \"=\"*80)\n", " print(f\"Claim: {claim}\")\n", " print(f\"→ Verdict: {agg['verdict']} (Confidence: {agg['confidence']:.2f})\")\n", " print(f\"→ Stance ratio: {agg['stance_ratio']}\")\n", " print(f\"→ Best Evidence (score={best_evidence['stance_score']:.2f}):\")\n", " print(f\"{best_evidence['text'][:300]}...\")\n", " print(f\"[Source: {best_evidence['link']}]\")\n", " print(\"→ Giải thích kiểm chứng:\")\n", " print(justification)\n", " else:\n", " final_results[claim] = {\n", " \"claim\": claim,\n", " \"verdict\": agg[\"verdict\"],\n", " \"confidence\": agg[\"confidence\"],\n", " \"stance_ratio\": agg[\"stance_ratio\"]\n", " }\n", "\n", " return final_results\n" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "id": "v4oFEpdz2foI" }, "outputs": [], "source": [ "async def pipeline_without_justification(claim= \"Sesko ghi cu dup trong chien thang cua MU truoc Brighton\"):\n", " module_1_result = module_1_pipeline(claim)\n", " module_2_result = module_2(module_1_result)\n", " module_3_pipeline([module_2_result])\n", " results_with_stance = await selectEvidence()\n", " final_results = module_5_optional_justification(results_with_stance)\n", "\n", " return final_results" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "id": "JpIsqOS5T16n" }, "outputs": [], "source": [ "def dataset_loader(your_id = 22120210):\n", " student_id = [22120210, 22120227, 22120262, 22120389, 22120422]\n", " order_id = student_id.index(your_id)\n", "\n", " ds = load_dataset(\"tranthaihoa/vifactcheck\")\n", "\n", " # Map nhãn số (0, 1, 2) sang chuỗi (Support, Refute, Neutral)\n", " label_map = {\n", " 0: \"True\",\n", " 1: \"False\",\n", " 2: \"Unknown\"\n", " }\n", "\n", " ds = ds.map(lambda x: {\"label\": label_map.get(x[\"labels\"], x[\"labels\"])})\n", " ds = ds[\"test\"]\n", "\n", " # Lấy 100 mẫu gồm 3 lớp đều nhau\n", " support_samples = [ex for ex in ds if ex[\"label\"] == \"True\"]\n", " refute_samples = [ex for ex in ds if ex[\"label\"] == \"False\"]\n", " neutral_samples = [ex for ex in ds if ex[\"label\"] == \"Unknown\"]\n", "\n", " file_path = \"claims.json\"\n", "\n", " claim_label_count = defaultdict(int)\n", " if os.path.exists(file_path):\n", " with open(file_path, \"r\", encoding=\"utf-8\") as f:\n", " for line in f:\n", " if line.strip():\n", " row = json.loads(line)\n", " claim_label_count[row['ground_label']] += 1\n", " print(f\"Có {sum((claim_label_count.values()))} claim đã được kiểm tra. {claim_label_count['True']} True, {claim_label_count['False']} False, {claim_label_count['Unknown']} Unknown.\")\n", " else:\n", " print(\"Kiểm tra từ đầu.\")\n", "\n", "\n", " sampled_data = (\n", " support_samples[order_id * 50 + claim_label_count['True']: (order_id + 1) * 50]\n", " + refute_samples[order_id * 50 + claim_label_count['False']: (order_id + 1) * 50]\n", " + neutral_samples[order_id * 50 + claim_label_count['Unknown']: (order_id + 1) * 50]\n", " )\n", "\n", " return sampled_data" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "id": "HAunMwDz-v_Y" }, "outputs": [], "source": [ "async def framework_test_with_vifactcheck(your_id = 22120210):\n", " # Hàm chuyển numpy sang float\n", " def convert_numpy(obj):\n", " if isinstance(obj, np.floating):\n", " return float(obj)\n", " raise TypeError\n", "\n", " file_path = \"claims.json\"\n", "\n", " results = []\n", " sampled_data = dataset_loader(your_id)\n", "\n", " for sample in sampled_data:\n", " claim = sample[\"Statement\"]\n", "\n", " predict_result = await pipeline_without_justification(claim)\n", "\n", " with open(file_path, \"a\", encoding=\"utf-8\") as f:\n", " for val in predict_result.values():\n", " predict_obj = {\n", " \"original_claim\": claim,\n", " \"extract_claim\": val['claim'],\n", " \"predict_verdict\": val['verdict'],\n", " \"predict_confidence\": val['confidence'],\n", " \"predict_stance_ratio\": val['stance_ratio'],\n", " \"ground_label\": sample['label']\n", " }\n", " f.write(json.dumps(predict_obj, ensure_ascii=False, default=convert_numpy) + \"\\n\")\n", "\n", " print(f\"Đã append {len(predict_result)} obj vào {file_path}\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "B9IknpZa5o4T", "outputId": "2d9e6100-87c6-4357-cd19-efa92ab971c1" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Có 4 claim đã được kiểm tra. 4 True, 0 False, 0 Unknown,\n", "Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.\n", "\n", "=== Claim: Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.\n", "Sinh 5 truy vấn mở rộng.\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Tìm kiếm 'Trung tâm Dự báo khí tượng thủy văn Quốc...': 100%|██████████| 5/5 [00:02<00:00, 2.41it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Hoàn tất! Kết quả được lưu tại: document_retrieval_results.json\n", "\n", "==================================================\n", "Handle claim: 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.'\n", " -> Crawling 10 links in parallel...\n", " -> Detect web link. Handle by Trafilatura: https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn\n", " -> Detect web link. Handle by Trafilatura: https://www.youtube.com/watch?v=0F4s7TPheXQ\n", " -> Detect web link. Handle by Trafilatura: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm\n", " -> Detect web link. Handle by Trafilatura: https://www.youtube.com/watch?v=DTpHfKgIclk\n", " -> Detect web link. Handle by Trafilatura: https://nhandan.vn/khong-khi-lanh-tang-cuong-o-bac-bo-post922255.html\n", " -> Detect web link. Handle by Trafilatura: https://www.nchmf.gov.vn/\n", " -> Detect web link. Handle by Trafilatura: https://www.vietnam.vn/en/du-bao-mien-bac-sap-don-khong-khi-lanh-dau-mua\n", " -> Detect web link. Handle by Trafilatura: https://vietnamnews.vn/society/1727243/weather-on-tuesday-widespread-thunderstorms-in-many-areas.html\n", " -> Detect web link. Handle by Trafilatura: https://news.laodong.vn/moi-truong/thoi-tiet-mien-bac-sap-thay-doi-do-khong-khi-lanh-tran-ve-1606821.ldo\n", " -> Detect web link. Handle by Trafilatura: https://weather.com/weather/tenday/l/001e51d4e61d1e59af930ca492aabec12e94ea5158704b0cc26520423900b618\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "✅ SUCCESS! Extracted text using Trafilatura ---\n", "SUCCESS!! https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn\n", "SUCCESS!! https://www.youtube.com/watch?v=0F4s7TPheXQ\n", "SUCCESS!! https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm\n", "SUCCESS!! https://www.youtube.com/watch?v=DTpHfKgIclk\n", "SUCCESS!! https://nhandan.vn/khong-khi-lanh-tang-cuong-o-bac-bo-post922255.html\n", "SUCCESS!! https://www.nchmf.gov.vn/\n", "SUCCESS!! https://www.vietnam.vn/en/du-bao-mien-bac-sap-don-khong-khi-lanh-dau-mua\n", "SUCCESS!! https://vietnamnews.vn/society/1727243/weather-on-tuesday-widespread-thunderstorms-in-many-areas.html\n", "SUCCESS!! https://news.laodong.vn/moi-truong/thoi-tiet-mien-bac-sap-thay-doi-do-khong-khi-lanh-tran-ve-1606821.ldo\n", "SUCCESS!! https://weather.com/weather/tenday/l/001e51d4e61d1e59af930ca492aabec12e94ea5158704b0cc26520423900b618\n", "==> Finish for claim 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.'. Total: 55 chunks.\n", "\n", "--- Finding top-k chunk related to claim: 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.' ---\n", " Top 20 chunk best related for claim 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.':\n", " - Score: 0.5531 - sấm sét hoặc gây ngập cục bộ ở vùng trũng thấp. Dự báo thời tiết các khu vực từ đêm 12/11 đến ngày 20/11, cơ quan khí tượng cho biết, trong đêm 12/11,...\n", " - Score: 0.4818 - cảm giác dễ chịu hơn cho người dân sau chuỗi ngày mưa kéo dài, trời nồm ẩm. Bắc Trung Bộ, thời tiết cũng có xu hướng tương tự. Trong ngày 11-12/11, mư...\n", " - Score: 0.4724 - Trung tâm Dự báo KTTV quốc gia. Bắc Biển Đông Có mưa bão ở phía Đông Bắc. Tầm nhìn xa : Từ 2-4km. Gió bắc đến tây bắc cấp 5, có lúc cấp 6, giật cấp 7-...\n", " - Score: 0.4653 - Dự báo thời tiết 10 ngày tới: Miền Bắc đón không khí lạnh .... Dự báo thời tiết 10 ngày tới: Miền Bắc đón không khí lạnh, Hà Nội rét nhất 16°C Dự báo ...\n", " - Score: 0.4627 - độ C. Khu vực Nam Bộ chiều tối và đêm cũng có mưa rào, dông vài nơi; ngày nắng. Trong mưa dông có khả năng xảy ra lốc, sét và gió giật mạnh. Nhiệt độ ...\n", " - Score: 0.4494 - cao có nơi rét đậm. Khu vực Bắc Bộ, Thanh Hóa và Nghệ An còn khoảng 16-18 độ C, vùng núi Bắc Bộ có nơi dưới 13 độ C. Từ khoảng đầu tuần sau (16-17/11)...\n", " - Score: 0.4459 - hiện sương muối, băng giá, thậm chí mưa tuyết nếu nhiệt độ xuống thấp kết hợp với độ ẩm cao. Các chuyên gia khuyến cáo người dân ở khu vực chịu ảnh hư...\n", " - Score: 0.4421 - Chiều tối và đêm có mưa rào và dông vài nơi, ngày nắng. Trong mưa dông có khả năng xảy ra lốc, sét, mưa đá và gió giật mạnh....\n", " - Score: 0.4319 - trải qua những ngày nồm ẩm trái mùa. Sang hôm nay (11/11), tình trạng nồm ẩm giảm rõ rệt. Theo dự báo, hiện tượng này sẽ chấm dứt khi đợt không khí lạ...\n", " - Score: 0.4262 - khả năng xảy ra mưa lớn diện rộng. Nam Bộ mưa rào và dông vài nơi, khoảng 16-17/11 mưa rào và dông rải rác, cục bộ mưa to. Theo bảng cập nhật thời tiế...\n", " - Score: 0.4025 - hơn vào ngày 17-18/11. Từ chiều 12/11, gió Đông Bắc hoạt động mạnh dần trên vùng biển Nam Bộ. Theo Trung tâm Dự báo khí tượng thuỷ văn quốc gia, ngày ...\n", " - Score: 0.3997 - Nhiều nơi mưa dông trong đêm 11/11, miền Bắc sắp đón .... Trong đêm 11 và ngày 12/11, nhiều khu vực có mưa dông. Theo Trung tâm Dự báo Khí tượng Thủy ...\n", " - Score: 0.3559 - Không khí lạnh tăng cường ở Bắc Bộ. Ở trạm Bạch Long Vỹ đã có gió đông bắc mạnh cấp 5, có lúc cấp 6, giật cấp 7. Do ảnh hưởng của không khí lạnh được ...\n", " - Score: 0.3466 - Quốc gia dự báo hiện đang có đợt không khí lạnh tăng cường xuống phía Nam. Từ ngày 13-15/11, nhiệt độ về đêm ở khu vực Bắc Bộ, Thanh Hóa và Nghệ An gi...\n", " - Score: 0.3455 - Gió Đông Bắc cấp 2-3, đêm và sáng trời lạnh. Nhiệt độ thấp nhất từ 19-22 độ C, vùng núi có nơi dưới 19 độ C; cao nhất từ 24-27 độ C, có nơi trên 27 độ...\n", " - Score: 0.3392 - mây, không mưa. Ngày 16/11, Hà Nội duy trì ngưỡng nhiệt cao nhất 28°C, nhiệt độ thấp nhất cũng tăng nhẹ lên 20°C. Ngưỡng nhiệt thấp nhất này duy trì t...\n", " - Score: 0.3336 - Quốc gia nhận định, mùa Đông 2025 - 2026, nhiệt độ trung bình tại khu vực Bắc Bộ ở mức xấp xỉ trung bình nhiều năm. Tuy nhiên, các đợt rét đậm, rét hạ...\n", " - Score: 0.3226 - 10-Day Weather Forecast for Boc Bo, Bắc Kạn, Vietnam. 10 Day Weather- Boc Bo, Bắc Kạn, Vietnam Tonight Cloudy--/67°24% Tonight Night Cloudy. Low 67F. ...\n", " - Score: 0.3176 - 21-23°C, cao nhất 24-26°C. Ngày 12/11, khu vực trung tâm Hà Nội có mây, không mưa, nhiệt độ trong ngày dao động 23-26°C. Sang ngày 13/11, khu vực này ...\n", " - Score: 0.3176 - đêm 19/10 đã gây gió mạnh cấp 7, giật cấp 9 tại trạm Bạch Long Vỹ, trạm Cồn Cỏ và trạm Lý Sơn có gió mạnh cấp 6, giật cấp 8. Khu vực Bắc Bộ nhiệt độ t...\n", "\n", "--- Reranking evidences for claim: 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.' ---\n", " Top 10 evidences after reranking:\n", " - Score: 0.9614 - hơn vào ngày 17-18/11. Từ chiều 12/11, gió Đông Bắc hoạt động mạnh dần trên vùng biển Nam Bộ. Theo Trung tâm Dự báo khí tượng thuỷ văn quốc gia, ngày 11/11, thời tiết Bắc Bộ mưa rào rải rác và có nơi có dông. Nhiệt độ cao nhất ở Đông Bắc Bộ phổ biến 23-26°C, có nơi trên 26°C; Tây Bắc Bộ dao động 24-27°C, có nơi trên 28°C. Sang đêm 11/11 và ngày 12/11, mưa ở Bắc Bộ chỉ còn xuất hiện vài nơi vào ban đêm và sáng sớm, trong khi ban ngày trời hửng nắng, mang lại cảm giác dễ chịu hơn cho người dân sau chuỗi ngày (Source: https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn)\n", " - Score: 0.8613 - Chiều tối và đêm có mưa rào và dông vài nơi, ngày nắng. Trong mưa dông có khả năng xảy ra lốc, sét, mưa đá và gió giật mạnh. (Source: https://nhandan.vn/khong-khi-lanh-tang-cuong-o-bac-bo-post922255.html)\n", " - Score: 0.4500 - Gió Đông Bắc cấp 2-3, đêm và sáng trời lạnh. Nhiệt độ thấp nhất từ 19-22 độ C, vùng núi có nơi dưới 19 độ C; cao nhất từ 24-27 độ C, có nơi trên 27 độ C. Thủ đô Hà Nội trời nhiều mây, có mưa vài nơi, trưa và chiều giảm mây, hửng nắng. Gió Đông Bắc cấp 2-3. Nhiệt độ thấp nhất từ 20-22 độ C, cao nhất từ 25-27 độ C. Khu vực từ Thanh Hóa đến Huế đêm có mưa, mưa rào rải rác và có nơi có dông; ban ngày có mưa vài nơi. Gió Bắc đến Tây Bắc cấp 2-3. Nhiệt độ thấp nhất từ 21-24 độ C, cao nhất từ 25-28 độ C. Duyên (Source: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm)\n", " - Score: 0.3433 - Nhiều nơi mưa dông trong đêm 11/11, miền Bắc sắp đón .... Trong đêm 11 và ngày 12/11, nhiều khu vực có mưa dông. Theo Trung tâm Dự báo Khí tượng Thủy văn Quốc gia, trong đêm 11 và ngày 12/11, khu vực Tây Bắc Bộ có mưa vài nơi, trưa chiều giảm mây, trời hửng nắng. Gió nhẹ, đêm và sáng trời lạnh. Nhiệt độ thấp nhất từ 18-21 độ C, có nơi dưới 18 độ C; cao nhất từ 25-28 độ C, có nơi trên 28 độ C. Khu vực Đông Bắc Bộ có mưa vài nơi, trưa và chiều giảm mây, hửng nắng. Gió Đông Bắc cấp 2-3, đêm và sáng trời lạnh. (Source: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm)\n", " - Score: 0.2559 - cảm giác dễ chịu hơn cho người dân sau chuỗi ngày mưa kéo dài, trời nồm ẩm. Bắc Trung Bộ, thời tiết cũng có xu hướng tương tự. Trong ngày 11-12/11, mưa chỉ xuất hiện vài nơi, lượng không đáng kể. Trong khi đó, khu vực Trung và Nam Trung Bộ, cao nguyên Trung Bộ và Nam Bộ vẫn duy trì trạng thái ngày nắng, chiều tối và đêm mưa rào và dông vài nơi. Các cơn mưa thường xảy ra ngắn, tập trung vào khung giờ chiều muộn đến đêm, nhưng vẫn tiềm ẩn nguy cơ gió giật mạnh, sấm sét hoặc gây ngập cục bộ ở vùng trũng thấp. (Source: https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn)\n", " - Score: 0.1976 - khả năng xảy ra mưa lớn diện rộng. Nam Bộ mưa rào và dông vài nơi, khoảng 16-17/11 mưa rào và dông rải rác, cục bộ mưa to. Theo bảng cập nhật thời tiết và nhiệt độ Hà Nội 10 ngày tới, các ngày 18-20/11, nhiệt độ thấp nhất trong ngày giảm còn 16°C, cao nhất 20°C, trời chuyển rét. Trước khi nhiệt độ giảm sâu, trời rét, nhiệt độ cao nhất ở trung tâm Hà Nội có thời điểm lên tới 28°C. Theo đó, hôm nay thời tiết Hà Nội mưa vài nơi, trời nhiều mây, nhiệt độ thấp nhất 21-23°C, cao nhất 24-26°C. Ngày 12/11, khu vực (Source: https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn)\n", " - Score: 0.1403 - sấm sét hoặc gây ngập cục bộ ở vùng trũng thấp. Dự báo thời tiết các khu vực từ đêm 12/11 đến ngày 20/11, cơ quan khí tượng cho biết, trong đêm 12/11, Bắc Bộ, Thanh Hóa và Nghệ An duy trì hình thái thời tiết mưa vài nơi. Ngày 12-13/11, các khu vực này khả năng rét vào đêm và sáng. Khoảng 2-3 ngày cuối thời kỳ dự báo (18-20/11), các địa phương này trời chuyển rét sau khi đón đợt không khí lạnh cường độ mạnh. Hà Tĩnh đến Lâm Đồng trời mưa vài nơi, từ khoảng 15-16/11 khả năng xảy ra mưa lớn diện rộng. Nam Bộ (Source: https://cafef.vn/du-bao-thoi-tiet-10-ngay-toi-mien-bac-don-khong-khi-lanh-ha-noi-ret-nhat-16c-188251111133440319.chn)\n", " - Score: 0.1283 - hiện sương muối, băng giá, thậm chí mưa tuyết nếu nhiệt độ xuống thấp kết hợp với độ ẩm cao. Các chuyên gia khuyến cáo người dân ở khu vực chịu ảnh hưởng bởi rét đậm, rét hại cần chủ động cập nhật thông tin thời tiết, giữ ấm cơ thể, đặc biệt là người già và trẻ nhỏ trong thời điểm giao mùa. Người nông dân cũng cần chú ý bảo vệ cây trồng, vật nuôi trước các đợt rét sắp tới. Một tháng qua, miền Bắc xảy ra 4 đợt không khí lạnh, đáng chú ý đợt không khí lạnh vào đêm 19/10 đã gây gió mạnh cấp 7, giật cấp 9 tại (Source: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm)\n", " - Score: 0.0873 - Quốc gia dự báo hiện đang có đợt không khí lạnh tăng cường xuống phía Nam. Từ ngày 13-15/11, nhiệt độ về đêm ở khu vực Bắc Bộ, Thanh Hóa và Nghệ An giảm mạnh, vùng núi cao có nơi rét đậm. Do ảnh hưởng của không khí lạnh được tăng cường liên tục kết hợp với trường phân kỳ trên cao nên từ ngày 13-15/11, khu vực Bắc Bộ, Thanh Hóa và Nghệ An xảy ra tình trạng ban ngày ít mây, trời nắng. Về đêm và sáng sớm, nhiệt độ thấp nhất xuống thấp, trời chuyển rét, vùng núi cao có nơi rét đậm. Khu vực Bắc Bộ, Thanh Hóa và (Source: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm)\n", " - Score: 0.0668 - đêm 19/10 đã gây gió mạnh cấp 7, giật cấp 9 tại trạm Bạch Long Vỹ, trạm Cồn Cỏ và trạm Lý Sơn có gió mạnh cấp 6, giật cấp 8. Khu vực Bắc Bộ nhiệt độ thấp nhất ngày phổ biến từ 18-20 độ C, vùng núi từ 15-17 độ C, vùng núi cao có nơi dưới 13 độ C như Mẫu Sơn (Lạng Sơn) 8,9 độ; Tam Đảo (Phú Thọ) 12,1 độ C; Sìn Hồ (Lai Châu) 12,2 độ C. Đợt không khí lạnh ngày 26/10 cũng khiến nền nhiệt miền Bắc xuống thấp từ 19-22 độ, vùng núi 17-19 độ, vùng núi cao dưới 15 độ. Một số nơi ghi nhận nhiệt độ khá thấp như mẫu Sơn (Source: https://vtv.vn/nhieu-noi-mua-dong-trong-dem-11-11-mien-bac-sap-don-khong-khi-lanh-tang-cuong-100251111180259114.htm)\n", "\n", "--- Phân loại lập trường cho claim: 'Trung tâm Dự báo khí tượng thủy văn Quốc gia dự báo, miền Bắc có mưa rào rải rác và có nơi có dông.' ---\n", " -> Stance: Support ({'refute': 0.002492840401828289, 'neutral': 0.00096273043891415, 'support': 0.9965444207191467}): | Text: hơn vào ngày 17-18/11. Từ chiều 12/11, gió Đông Bắc hoạt động mạnh dần trên vùng biển Nam Bộ. Theo Trung tâm Dự báo khí tượng thuỷ văn quốc gia, ngày 11/11, thời tiết Bắc Bộ mưa rào rải rác và có nơi có dông. Nhiệt độ cao nhất ở Đông Bắc Bộ phổ biến 23-26°C, có nơi trên 26°C; Tây Bắc Bộ dao động 24-27°C, có nơi trên 28°C. Sang đêm 11/11 và ngày 12/11, mưa ở Bắc Bộ chỉ còn xuất hiện vài nơi vào ban đêm và sáng sớm, trong khi ban ngày trời hửng nắng, mang lại cảm giác dễ chịu hơn cho người dân sau chuỗi ngày\n", " -> Stance: Neutral ({'refute': 0.0010207833256572485, 'neutral': 0.9941872358322144, 'support': 0.004791961517184973}): | Text: Chiều tối và đêm có mưa rào và dông vài nơi, ngày nắng. Trong mưa dông có khả năng xảy ra lốc, sét, mưa đá và gió giật mạnh.\n", " -> Stance: Refute ({'refute': 0.7915347218513489, 'neutral': 0.01925884373486042, 'support': 0.18920651078224182}): | Text: Gió Đông Bắc cấp 2-3, đêm và sáng trời lạnh. Nhiệt độ thấp nhất từ 19-22 độ C, vùng núi có nơi dưới 19 độ C; cao nhất từ 24-27 độ C, có nơi trên 27 độ C. Thủ đô Hà Nội trời nhiều mây, có mưa vài nơi, trưa và chiều giảm mây, hửng nắng. Gió Đông Bắc cấp 2-3. Nhiệt độ thấp nhất từ 20-22 độ C, cao nhất từ 25-27 độ C. Khu vực từ Thanh Hóa đến Huế đêm có mưa, mưa rào rải rác và có nơi có dông; ban ngày có mưa vài nơi. Gió Bắc đến Tây Bắc cấp 2-3. Nhiệt độ thấp nhất từ 21-24 độ C, cao nhất từ 25-28 độ C. Duyên\n", " -> Stance: Refute ({'refute': 0.9966765642166138, 'neutral': 0.00264021591283381, 'support': 0.0006832125363871455}): | Text: Nhiều nơi mưa dông trong đêm 11/11, miền Bắc sắp đón .... Trong đêm 11 và ngày 12/11, nhiều khu vực có mưa dông. Theo Trung tâm Dự báo Khí tượng Thủy văn Quốc gia, trong đêm 11 và ngày 12/11, khu vực Tây Bắc Bộ có mưa vài nơi, trưa chiều giảm mây, trời hửng nắng. Gió nhẹ, đêm và sáng trời lạnh. Nhiệt độ thấp nhất từ 18-21 độ C, có nơi dưới 18 độ C; cao nhất từ 25-28 độ C, có nơi trên 28 độ C. Khu vực Đông Bắc Bộ có mưa vài nơi, trưa và chiều giảm mây, hửng nắng. Gió Đông Bắc cấp 2-3, đêm và sáng trời lạnh.\n", " -> Stance: Support ({'refute': 0.0024910576175898314, 'neutral': 0.002102562692016363, 'support': 0.9954063892364502}): | Text: cảm giác dễ chịu hơn cho người dân sau chuỗi ngày mưa kéo dài, trời nồm ẩm. Bắc Trung Bộ, thời tiết cũng có xu hướng tương tự. Trong ngày 11-12/11, mưa chỉ xuất hiện vài nơi, lượng không đáng kể. Trong khi đó, khu vực Trung và Nam Trung Bộ, cao nguyên Trung Bộ và Nam Bộ vẫn duy trì trạng thái ngày nắng, chiều tối và đêm mưa rào và dông vài nơi. Các cơn mưa thường xảy ra ngắn, tập trung vào khung giờ chiều muộn đến đêm, nhưng vẫn tiềm ẩn nguy cơ gió giật mạnh, sấm sét hoặc gây ngập cục bộ ở vùng trũng thấp.\n", " -> Stance: Support ({'refute': 0.0127418776974082, 'neutral': 0.011291456408798695, 'support': 0.9759666323661804}): | Text: khả năng xảy ra mưa lớn diện rộng. Nam Bộ mưa rào và dông vài nơi, khoảng 16-17/11 mưa rào và dông rải rác, cục bộ mưa to. Theo bảng cập nhật thời tiết và nhiệt độ Hà Nội 10 ngày tới, các ngày 18-20/11, nhiệt độ thấp nhất trong ngày giảm còn 16°C, cao nhất 20°C, trời chuyển rét. Trước khi nhiệt độ giảm sâu, trời rét, nhiệt độ cao nhất ở trung tâm Hà Nội có thời điểm lên tới 28°C. Theo đó, hôm nay thời tiết Hà Nội mưa vài nơi, trời nhiều mây, nhiệt độ thấp nhất 21-23°C, cao nhất 24-26°C. Ngày 12/11, khu vực\n", " -> Stance: Support ({'refute': 0.3188001215457916, 'neutral': 0.02766256220638752, 'support': 0.6535373330116272}): | Text: sấm sét hoặc gây ngập cục bộ ở vùng trũng thấp. Dự báo thời tiết các khu vực từ đêm 12/11 đến ngày 20/11, cơ quan khí tượng cho biết, trong đêm 12/11, Bắc Bộ, Thanh Hóa và Nghệ An duy trì hình thái thời tiết mưa vài nơi. Ngày 12-13/11, các khu vực này khả năng rét vào đêm và sáng. Khoảng 2-3 ngày cuối thời kỳ dự báo (18-20/11), các địa phương này trời chuyển rét sau khi đón đợt không khí lạnh cường độ mạnh. Hà Tĩnh đến Lâm Đồng trời mưa vài nơi, từ khoảng 15-16/11 khả năng xảy ra mưa lớn diện rộng. Nam Bộ\n", " -> Stance: Support ({'refute': 0.2433687150478363, 'neutral': 0.11331598460674286, 'support': 0.643315315246582}): | Text: hiện sương muối, băng giá, thậm chí mưa tuyết nếu nhiệt độ xuống thấp kết hợp với độ ẩm cao. Các chuyên gia khuyến cáo người dân ở khu vực chịu ảnh hưởng bởi rét đậm, rét hại cần chủ động cập nhật thông tin thời tiết, giữ ấm cơ thể, đặc biệt là người già và trẻ nhỏ trong thời điểm giao mùa. Người nông dân cũng cần chú ý bảo vệ cây trồng, vật nuôi trước các đợt rét sắp tới. Một tháng qua, miền Bắc xảy ra 4 đợt không khí lạnh, đáng chú ý đợt không khí lạnh vào đêm 19/10 đã gây gió mạnh cấp 7, giật cấp 9 tại\n", " -> Stance: Refute ({'refute': 0.9915241003036499, 'neutral': 0.00526752695441246, 'support': 0.003208448877558112}): | Text: Quốc gia dự báo hiện đang có đợt không khí lạnh tăng cường xuống phía Nam. Từ ngày 13-15/11, nhiệt độ về đêm ở khu vực Bắc Bộ, Thanh Hóa và Nghệ An giảm mạnh, vùng núi cao có nơi rét đậm. Do ảnh hưởng của không khí lạnh được tăng cường liên tục kết hợp với trường phân kỳ trên cao nên từ ngày 13-15/11, khu vực Bắc Bộ, Thanh Hóa và Nghệ An xảy ra tình trạng ban ngày ít mây, trời nắng. Về đêm và sáng sớm, nhiệt độ thấp nhất xuống thấp, trời chuyển rét, vùng núi cao có nơi rét đậm. Khu vực Bắc Bộ, Thanh Hóa và\n", " -> Stance: Neutral ({'refute': 0.15165527164936066, 'neutral': 0.6658914089202881, 'support': 0.18245336413383484}): | Text: đêm 19/10 đã gây gió mạnh cấp 7, giật cấp 9 tại trạm Bạch Long Vỹ, trạm Cồn Cỏ và trạm Lý Sơn có gió mạnh cấp 6, giật cấp 8. Khu vực Bắc Bộ nhiệt độ thấp nhất ngày phổ biến từ 18-20 độ C, vùng núi từ 15-17 độ C, vùng núi cao có nơi dưới 13 độ C như Mẫu Sơn (Lạng Sơn) 8,9 độ; Tam Đảo (Phú Thọ) 12,1 độ C; Sìn Hồ (Lai Châu) 12,2 độ C. Đợt không khí lạnh ngày 26/10 cũng khiến nền nhiệt miền Bắc xuống thấp từ 19-22 độ, vùng núi 17-19 độ, vùng núi cao dưới 15 độ. Một số nơi ghi nhận nhiệt độ khá thấp như mẫu Sơn\n", "Đã append 1 obj vào claims.json\n", "Sự việc 2 thanh niên lạ mặt đi xe máy tiếp cận học sinh ở nhiều trường tại Vinh với mục đích bắt cóc chưa được kiểm định chính xác.\n" ] } ], "source": [ "your_id = 22120210\n", "await framework_test_with_vifactcheck(your_id)" ] } ], "metadata": { "accelerator": "GPU", "colab": { "gpuType": "T4", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "00603dcf221c49b59a276dcfc4ea3ff5": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, 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