diff --git a/docs/Gemfile.lock b/docs/Gemfile.lock
index 06f0caa1a..959ce6ca7 100644
--- a/docs/Gemfile.lock
+++ b/docs/Gemfile.lock
@@ -1,59 +1,59 @@
 GEM
   remote: https://rubygems.org/
   specs:
-    activesupport (8.0.2)
+    activesupport (8.1.3)
       base64
-      benchmark (>= 0.3)
       bigdecimal
       concurrent-ruby (~> 1.0, >= 1.3.1)
       connection_pool (>= 2.2.5)
       drb
       i18n (>= 1.6, < 2)
+      json
       logger (>= 1.4.2)
       minitest (>= 5.1)
       securerandom (>= 0.3)
       tzinfo (~> 2.0, >= 2.0.5)
       uri (>= 0.13.1)
-    addressable (2.8.7)
-      public_suffix (>= 2.0.2, < 7.0)
-    base64 (0.2.0)
-    benchmark (0.4.1)
-    bigdecimal (3.2.2)
+    addressable (2.9.0)
+      public_suffix (>= 2.0.2, < 8.0)
+    base64 (0.3.0)
+    bigdecimal (4.1.2)
     coffee-script (2.4.1)
       coffee-script-source
       execjs
     coffee-script-source (1.12.2)
     colorator (1.1.0)
-    commonmarker (0.23.11)
-    concurrent-ruby (1.3.5)
-    connection_pool (2.5.3)
+    commonmarker (0.23.12)
+    concurrent-ruby (1.3.8)
+    connection_pool (3.0.2)
     csv (3.3.5)
-    dnsruby (1.72.4)
-      base64 (~> 0.2.0)
-      logger (~> 1.6.5)
+    dnsruby (1.74.0)
+      base64 (>= 0.2)
+      logger (~> 1.6)
       simpleidn (~> 0.2.1)
     drb (2.2.3)
     em-websocket (0.5.3)
       eventmachine (>= 0.12.9)
       http_parser.rb (~> 0)
-    ethon (0.16.0)
+    ethon (0.18.0)
       ffi (>= 1.15.0)
+      logger
     eventmachine (1.2.7)
-    execjs (2.10.0)
-    faraday (2.13.4)
+    execjs (2.10.1)
+    faraday (2.14.3)
       faraday-net_http (>= 2.0, < 3.5)
       json
       logger
-    faraday-net_http (3.4.1)
-      net-http (>= 0.5.0)
-    ffi (1.17.2-aarch64-linux-gnu)
-    ffi (1.17.2-aarch64-linux-musl)
-    ffi (1.17.2-arm-linux-gnu)
-    ffi (1.17.2-arm-linux-musl)
-    ffi (1.17.2-arm64-darwin)
-    ffi (1.17.2-x86_64-darwin)
-    ffi (1.17.2-x86_64-linux-gnu)
-    ffi (1.17.2-x86_64-linux-musl)
+    faraday-net_http (3.4.4)
+      net-http (~> 0.5)
+    ffi (1.17.4-aarch64-linux-gnu)
+    ffi (1.17.4-aarch64-linux-musl)
+    ffi (1.17.4-arm-linux-gnu)
+    ffi (1.17.4-arm-linux-musl)
+    ffi (1.17.4-arm64-darwin)
+    ffi (1.17.4-x86_64-darwin)
+    ffi (1.17.4-x86_64-linux-gnu)
+    ffi (1.17.4-x86_64-linux-musl)
     forwardable-extended (2.6.0)
     gemoji (4.1.0)
     github-pages (232)
@@ -111,8 +111,8 @@ GEM
     html-pipeline (2.14.3)
       activesupport (>= 2)
       nokogiri (>= 1.4)
-    http_parser.rb (0.8.0)
-    i18n (1.14.7)
+    http_parser.rb (0.8.1)
+    i18n (1.15.2)
       concurrent-ruby (~> 1.0)
     jekyll (3.10.0)
       addressable (~> 2.4)
@@ -224,51 +224,55 @@ GEM
       gemoji (>= 3, < 5)
       html-pipeline (~> 2.2)
       jekyll (>= 3.0, < 5.0)
-    json (2.13.2)
+    json (2.21.1)
     kramdown (2.4.0)
       rexml
     kramdown-parser-gfm (1.1.0)
       kramdown (~> 2.0)
     liquid (4.0.4)
-    listen (3.9.0)
+    listen (3.10.0)
+      logger
       rb-fsevent (~> 0.10, >= 0.10.3)
       rb-inotify (~> 0.9, >= 0.9.10)
-    logger (1.6.6)
+    logger (1.7.0)
     mercenary (0.3.6)
     minima (2.5.1)
       jekyll (>= 3.5, < 5.0)
       jekyll-feed (~> 0.9)
       jekyll-seo-tag (~> 2.1)
-    minitest (5.25.5)
-    net-http (0.6.0)
-      uri
-    nokogiri (1.18.9-aarch64-linux-gnu)
+    minitest (6.0.6)
+      drb (~> 2.0)
+      prism (~> 1.5)
+    net-http (0.9.1)
+      uri (>= 0.11.1)
+    nokogiri (1.19.4-aarch64-linux-gnu)
       racc (~> 1.4)
-    nokogiri (1.18.9-aarch64-linux-musl)
+    nokogiri (1.19.4-aarch64-linux-musl)
       racc (~> 1.4)
-    nokogiri (1.18.9-arm-linux-gnu)
+    nokogiri (1.19.4-arm-linux-gnu)
       racc (~> 1.4)
-    nokogiri (1.18.9-arm-linux-musl)
+    nokogiri (1.19.4-arm-linux-musl)
       racc (~> 1.4)
-    nokogiri (1.18.9-arm64-darwin)
+    nokogiri (1.19.4-arm64-darwin)
       racc (~> 1.4)
-    nokogiri (1.18.9-x86_64-darwin)
+    nokogiri (1.19.4-x86_64-darwin)
       racc (~> 1.4)
-    nokogiri (1.18.9-x86_64-linux-gnu)
+    nokogiri (1.19.4-x86_64-linux-gnu)
       racc (~> 1.4)
-    nokogiri (1.18.9-x86_64-linux-musl)
+    nokogiri (1.19.4-x86_64-linux-musl)
       racc (~> 1.4)
     octokit (4.25.1)
       faraday (>= 1, < 3)
       sawyer (~> 0.9)
     pathutil (0.16.2)
       forwardable-extended (~> 2.6)
+    prism (1.9.0)
     public_suffix (5.1.1)
     racc (1.8.1)
     rb-fsevent (0.11.2)
     rb-inotify (0.11.1)
       ffi (~> 1.0)
-    rexml (3.4.1)
+    rexml (3.4.4)
     rouge (3.30.0)
     rubyzip (2.4.1)
     safe_yaml (1.0.5)
@@ -277,20 +281,20 @@ GEM
     sass-listen (4.0.0)
       rb-fsevent (~> 0.9, >= 0.9.4)
       rb-inotify (~> 0.9, >= 0.9.7)
-    sawyer (0.9.2)
+    sawyer (0.9.3)
       addressable (>= 2.3.5)
       faraday (>= 0.17.3, < 3)
     securerandom (0.4.1)
     simpleidn (0.2.3)
     terminal-table (1.8.0)
       unicode-display_width (~> 1.1, >= 1.1.1)
-    typhoeus (1.4.1)
-      ethon (>= 0.9.0)
+    typhoeus (1.6.0)
+      ethon (>= 0.18.0)
     tzinfo (2.0.6)
       concurrent-ruby (~> 1.0)
     unicode-display_width (1.8.0)
-    uri (1.0.3)
-    webrick (1.9.1)
+    uri (1.1.1)
+    webrick (1.9.2)
 
 PLATFORMS
   aarch64-linux-gnu
@@ -306,5 +310,118 @@ DEPENDENCIES
   github-pages (= 232)
   webrick (~> 1.7)
 
+CHECKSUMS
+  activesupport (8.1.3) sha256=21a5e0dfbd4c3ddd9e1317ec6a4d782fa226e7867dc70b0743acda81a1dca20e
+  addressable (2.9.0) sha256=7fdf6ac3660f7f4e867a0838be3f6cf722ace541dd97767fa42bc6cfa980c7af
+  base64 (0.3.0) sha256=27337aeabad6ffae05c265c450490628ef3ebd4b67be58257393227588f5a97b
+  bigdecimal (4.1.2) sha256=53d217666027eab4280346fba98e7d5b66baaae1b9c3c1c0ffe89d48188a3fbd
+  coffee-script (2.4.1) sha256=82fe281e11b93c8117b98c5ea8063e71741870f1c4fbb27177d7d6333dd38765
+  coffee-script-source (1.12.2) sha256=e12b16fd8927fbbf8b87cb2e9a85a6cf457c6881cc7ff8b1af15b31f70da07a4
+  colorator (1.1.0) sha256=e2f85daf57af47d740db2a32191d1bdfb0f6503a0dfbc8327d0c9154d5ddfc38
+  commonmarker (0.23.12) sha256=da2d2f89c7c7b51c42c6e69ace3ab5df39497683f86e83aca7087c671d523ccd
+  concurrent-ruby (1.3.8) sha256=b2f1be836e968ccc78ccfce277ea79c72a88633f22306782c16ff23fb415d1e1
+  connection_pool (3.0.2) sha256=33fff5ba71a12d2aa26cb72b1db8bba2a1a01823559fb01d29eb74c286e62e0a
+  csv (3.3.5) sha256=6e5134ac3383ef728b7f02725d9872934f523cb40b961479f69cf3afa6c8e73f
+  dnsruby (1.74.0) sha256=7a83736c768e62b4915e2032ed4b97f9245d515e0e4efa67e424acb218296593
+  drb (2.2.3) sha256=0b00d6fdb50995fe4a45dea13663493c841112e4068656854646f418fda13373
+  em-websocket (0.5.3) sha256=f56a92bde4e6cb879256d58ee31f124181f68f8887bd14d53d5d9a292758c6a8
+  ethon (0.18.0) sha256=b598afc9f30448cb068b850714b7d6948e941476095d04f90a4ac65b8d6efcb2
+  eventmachine (1.2.7) sha256=994016e42aa041477ba9cff45cbe50de2047f25dd418eba003e84f0d16560972
+  execjs (2.10.1) sha256=abe0ae028467eb8e30c10814eb934d07876a691aae7e803d813b7ce5a75e73f1
+  faraday (2.14.3) sha256=1882247e6766615c8220b4392bf1d27f6ebb63d8e28267587cef1fb0bf37f278
+  faraday-net_http (3.4.4) sha256=0e78af151747ed1b00f33e25973b4bc220d7f16c00c39676817c8b12331eb588
+  ffi (1.17.4-aarch64-linux-gnu) sha256=b208f06f91ffd8f5e1193da3cae3d2ccfc27fc36fba577baf698d26d91c080df
+  ffi (1.17.4-aarch64-linux-musl) sha256=9286b7a615f2676245283aef0a0a3b475ae3aae2bb5448baace630bb77b91f39
+  ffi (1.17.4-arm-linux-gnu) sha256=d6dbddf7cb77bf955411af5f187a65b8cd378cb003c15c05697f5feee1cb1564
+  ffi (1.17.4-arm-linux-musl) sha256=9d4838ded0465bef6e2426935f6bcc93134b6616785a84ffd2a3d82bc3cf6f95
+  ffi (1.17.4-arm64-darwin) sha256=19071aaf1419251b0a46852abf960e77330a3b334d13a4ab51d58b31a937001b
+  ffi (1.17.4-x86_64-darwin) sha256=aa70390523cf3235096cf64962b709b4cfbd5c082a2cb2ae714eb0fe2ccda496
+  ffi (1.17.4-x86_64-linux-gnu) sha256=9d3db14c2eae074b382fa9c083fe95aec6e0a1451da249eab096c34002bc752d
+  ffi (1.17.4-x86_64-linux-musl) sha256=3fdf9888483de005f8ef8d1cf2d3b20d86626af206cbf780f6a6a12439a9c49e
+  forwardable-extended (2.6.0) sha256=1bec948c469bbddfadeb3bd90eb8c85f6e627a412a3e852acfd7eaedbac3ec97
+  gemoji (4.1.0) sha256=734434020cbe964ea9d19086798797a47d23a170892de0ce55b74aa65d2ddc1a
+  github-pages (232) sha256=2b40493d7327627e4ce45c47f4a9d4394e5eaa151f9d29bb924ff424c3132287
+  github-pages-health-check (1.18.2) sha256=df893d4f5a4161477e8525b993dbe1c1eb63fbb86fb07b6e80996fd37a18843d
+  html-pipeline (2.14.3) sha256=8a1d4d7128b2141913387cac0f8ba898bb6812557001acc0c2b46910f59413a0
+  http_parser.rb (0.8.1) sha256=9ae8df145b39aa5398b2f90090d651c67bd8e2ebfe4507c966579f641e11097a
+  i18n (1.15.2) sha256=00f9eb62412fe593b2a65a97daa75300d37abb8f7202ec748e94b6d46a9dd1b5
+  jekyll (3.10.0) sha256=c4213b761dc7dfe7d499eb742d0476a02d8503e440c2610e19774ee7f0db8d90
+  jekyll-avatar (0.8.0) sha256=ea736277c2de54a21300122096700517972a722d5c68ca83f8723b4999abfd4b
+  jekyll-coffeescript (1.2.2) sha256=894e71c2071a834e76eb7e8044944440a0c81c2c7092532fed1503b13d331110
+  jekyll-commonmark (1.4.0) sha256=1731e658fe09ce040271e6878f83ad45bbf8d17b10ad03bf343546cca30f4844
+  jekyll-commonmark-ghpages (0.5.1) sha256=d56722f23393e45625e6e1bac6d3c64bb5f5cdf6ca547338160536d61c27a4a4
+  jekyll-default-layout (0.1.5) sha256=c626be4e4a5deafca123539da2cd22ff873be350cafd4da134039efdf24320af
+  jekyll-feed (0.17.0) sha256=689aab16c877949bb9e7a5c436de6278318a51ecb974792232fd94d8b3acfcc3
+  jekyll-gist (1.5.0) sha256=495b6483552a3e2975a2752964ea7acddd545bc6e13ce2be15a50cec8d4c9f0f
+  jekyll-github-metadata (2.16.1) sha256=4cf29988bdaf24774a7bc07fae71e54424ddfaa2895f742d8fa3036d0db65b4c
+  jekyll-include-cache (0.2.1) sha256=c7d4b9e551732a27442cb2ce853ba36a2f69c66603694b8c1184c99ab1a1a205
+  jekyll-mentions (1.6.0) sha256=39e801024cb6f2319b3f78a29999d0068ef5f68bc5202b8757d5354fef311ed9
+  jekyll-optional-front-matter (0.3.2) sha256=ecdc061d711472469fcf04da617653b553e914c038a17df3b6a5f6f92aeb761b
+  jekyll-paginate (1.1.0) sha256=880aadf4b02529a93541d508c5cbb744f014cbfc071d0263a31f25ec9066eb64
+  jekyll-readme-index (0.3.0) sha256=d74cc4de46b2d350229be7409495149e656a31fb5a5fe3fe6135dbf7435e1e32
+  jekyll-redirect-from (0.16.0) sha256=6635cae569ef9b0f90ffb71ec014ba977177fafb44d32a2b0526288d4d9be6db
+  jekyll-relative-links (0.6.1) sha256=d11301f57b39e94b6c04fff2a3b145fe2f6a27be631a403e2542fa2e1548dd6d
+  jekyll-remote-theme (0.4.3) sha256=d3fde726484fb3df04de9e347baf75aaa3d5bfea771a330412e0c52608e54b40
+  jekyll-sass-converter (1.5.2) sha256=53773669e414dc3bb070113befacb808576025a28cfa4a4accc682e90a9c1101
+  jekyll-seo-tag (2.8.0) sha256=3f2ed1916d56f14ebfa38e24acde9b7c946df70cb183af2cb5f0598f21ae6818
+  jekyll-sitemap (1.4.0) sha256=0de08c5debc185ea5a8f980e1025c7cd3f8e0c35c8b6ef592f15c46235cf4218
+  jekyll-swiss (1.0.0) sha256=c299a855dca881fe868f21545c5489be50ddfbc0d54a80e8dbeb5a2ddc4888a3
+  jekyll-theme-architect (0.2.0) sha256=7275d3dcaa6b34fcf92f2fe5cee92d49d66706d3b523003b1e67e9c668ff0440
+  jekyll-theme-cayman (0.2.0) sha256=3c5f14f9c72a8eb03ecc74f9a3e5ecbbc55f9381339978b42dec216921865f2a
+  jekyll-theme-dinky (0.2.0) sha256=720b257091f0de3aa9394b25fd97d1b2b12cfaf00e060aff170f60e218a32c7c
+  jekyll-theme-hacker (0.2.0) sha256=816bf9f992ded0b1e1e69d8dece2574e8480efb5e9f84a2e1ac83bd717b8f78a
+  jekyll-theme-leap-day (0.2.0) sha256=921ea8305ae0285a881c9aa9dbe2375ed6f404b4f90067458e596891ef5ac7d1
+  jekyll-theme-merlot (0.2.0) sha256=cbf2b21b62423561ca5b62e406dbb08f085e3a45daa7b3b4b9b3f24d08ded545
+  jekyll-theme-midnight (0.2.0) sha256=009ff367350e83ff6095d98837bb411adb07b59a76f59f1d4a33ef927bb391de
+  jekyll-theme-minimal (0.2.0) sha256=a225210c35573ad2c9e57b81f16f678ca6c314394ec692502ccc6189d7e52d82
+  jekyll-theme-modernist (0.2.0) sha256=4be775bc5edd53864c5e40c000c34db0dfd82dac800cff50371ef11da66dfbcf
+  jekyll-theme-primer (0.6.0) sha256=ce27282798217eb0957ba01ab3bf12996476348b625736fa8448f7a1b8a307b3
+  jekyll-theme-slate (0.2.0) sha256=5e40909de712bbbefbc7a29f17c55bffa326c222f0a13ee1656229a7d43c3439
+  jekyll-theme-tactile (0.2.0) sha256=b7861b48aed5b2385d7a146b13f31cb6f37afe3107f4a6b93b1c932b2d242652
+  jekyll-theme-time-machine (0.2.0) sha256=bc3490a7eccfc24ca671780c9d4f531500936a361690020b19defe6105d74fe2
+  jekyll-titles-from-headings (0.5.3) sha256=77366754e361ea7b5d87881f5b1380835f5ce910c240a4d9ac2d7afe86d28481
+  jekyll-watch (2.2.1) sha256=bc44ed43f5e0a552836245a54dbff3ea7421ecc2856707e8a1ee203a8387a7e1
+  jemoji (0.13.0) sha256=5d4c3e8e2cbbb2b73997c31294f6f70c94e4d4fade039373e86835bcf5529e7c
+  json (2.21.1) sha256=13a43df75d95641443f5702dff350f237164a9d811ff0f2c2800d4d980220583
+  kramdown (2.4.0) sha256=b62e5bcbd6ea20c7a6730ebbb2a107237856e14f29cebf5b10c876cc1a2481c5
+  kramdown-parser-gfm (1.1.0) sha256=fb39745516427d2988543bf01fc4cf0ab1149476382393e0e9c48592f6581729
+  liquid (4.0.4) sha256=4fcfebb1a045e47918388dbb7a0925e7c3893e58d2bd6c3b3c73ec17a2d8fdb3
+  listen (3.10.0) sha256=c6e182db62143aeccc2e1960033bebe7445309c7272061979bb098d03760c9d2
+  logger (1.7.0) sha256=196edec7cc44b66cfb40f9755ce11b392f21f7967696af15d274dde7edff0203
+  mercenary (0.3.6) sha256=2a084b18f5692c86a633e185d5311ba6d11fc46c802eb414ae05368178078a82
+  minima (2.5.1) sha256=520e52bc631fb16cbb8100660f6caa44f97859e2fa7e397d508deb18739567be
+  minitest (6.0.6) sha256=153ea36d1d987a62942382b61075745042a2b3123b1cd48f4c3675af9cc7d6f1
+  net-http (0.9.1) sha256=25ba0b67c63e89df626ed8fac771d0ad24ad151a858af2cc8e6a716ca4336996
+  nokogiri (1.19.4-aarch64-linux-gnu) sha256=1269fb644a6de405057a53dd5c762b1209b43ca7424f839454d3dbc677c31a8f
+  nokogiri (1.19.4-aarch64-linux-musl) sha256=35c65b9ce72b3bb03207bdbe7067915019dc18c1b9b59139684bd6690fdd01af
+  nokogiri (1.19.4-arm-linux-gnu) sha256=a301313e38bb065d68239e79734bcd6f56fb6efaacebde29e9abf2a4735340ca
+  nokogiri (1.19.4-arm-linux-musl) sha256=588923c101bcfa78869734d247d25b598674323e7f22474fc468f6e5647311eb
+  nokogiri (1.19.4-arm64-darwin) sha256=a46db9853286e6597b36ebc6953817d15acf3a299583eb3f89fdc6f91dd63527
+  nokogiri (1.19.4-x86_64-darwin) sha256=7fd17057d3e1f00e9954a74b3cd76595d3d4a5ef233b7ed9599047c204f70551
+  nokogiri (1.19.4-x86_64-linux-gnu) sha256=379fae440b28915e3f19d752ce2dcf8465ed2b2fbefd2a7ca0dd497bc981a06a
+  nokogiri (1.19.4-x86_64-linux-musl) sha256=17dfb7c1fa194ae02fbf7c51a7afc8d278045ab3fdacfd86f91d02d7b274470b
+  octokit (4.25.1) sha256=c02092ee82dcdfe84db0e0ea630a70d32becc54245a4f0bacfd21c010df09b96
+  pathutil (0.16.2) sha256=e43b74365631cab4f6d5e4228f812927efc9cb2c71e62976edcb252ee948d589
+  prism (1.9.0) sha256=7b530c6a9f92c24300014919c9dcbc055bf4cdf51ec30aed099b06cd6674ef85
+  public_suffix (5.1.1) sha256=250ec74630d735194c797491c85e3c6a141d7b5d9bd0b66a3fa6268cf67066ed
+  racc (1.8.1) sha256=4a7f6929691dbec8b5209a0b373bc2614882b55fc5d2e447a21aaa691303d62f
+  rb-fsevent (0.11.2) sha256=43900b972e7301d6570f64b850a5aa67833ee7d87b458ee92805d56b7318aefe
+  rb-inotify (0.11.1) sha256=a0a700441239b0ff18eb65e3866236cd78613d6b9f78fea1f9ac47a85e47be6e
+  rexml (3.4.4) sha256=19e0a2c3425dfbf2d4fc1189747bdb2f849b6c5e74180401b15734bc97b5d142
+  rouge (3.30.0) sha256=a3d353222aa72e49e2c86726c0bcfd719f82592f57d494474655f48e669eceb6
+  rubyzip (2.4.1) sha256=8577c88edc1fde8935eb91064c5cb1aef9ad5494b940cf19c775ee833e075615
+  safe_yaml (1.0.5) sha256=a6ac2d64b7eb027bdeeca1851fe7e7af0d668e133e8a88066a0c6f7087d9f848
+  sass (3.7.4) sha256=808b0d39053aa69068df939e24671fe84fd5a9d3314486e1a1457d0934a4255d
+  sass-listen (4.0.0) sha256=ae9dcb76dd3e234329e5ba6e213f48e532c5a3e7b0b4d8a87f13aaca0cc18377
+  sawyer (0.9.3) sha256=0d0f19298408047037638639fe62f4794483fb04320269169bd41af2bdcf5e41
+  securerandom (0.4.1) sha256=cc5193d414a4341b6e225f0cb4446aceca8e50d5e1888743fac16987638ea0b1
+  simpleidn (0.2.3) sha256=08ce96f03fa1605286be22651ba0fc9c0b2d6272c9b27a260bc88be05b0d2c29
+  terminal-table (1.8.0) sha256=13371f069af18e9baa4e44d404a4ada9301899ce0530c237ac1a96c19f652294
+  typhoeus (1.6.0) sha256=bacc41c23e379547e29801dc235cd1699b70b955a1ba3d32b2b877aa844c331d
+  tzinfo (2.0.6) sha256=8daf828cc77bcf7d63b0e3bdb6caa47e2272dcfaf4fbfe46f8c3a9df087a829b
+  unicode-display_width (1.8.0) sha256=0292132d364d59fcdd83f144910c48b3c8332b28a14c5c04bb093dd165600488
+  uri (1.1.1) sha256=379fa58d27ffb1387eaada68c749d1426738bd0f654d812fcc07e7568f5c57c6
+  webrick (1.9.2) sha256=beb4a15fc474defed24a3bda4ffd88a490d517c9e4e6118c3edce59e45864131
+
 BUNDLED WITH
-   2.6.9
+  4.0.10
diff --git a/langtest/datahandler/datasource.py b/langtest/datahandler/datasource.py
index 94f3c7604..cac0c7e79 100644
--- a/langtest/datahandler/datasource.py
+++ b/langtest/datahandler/datasource.py
@@ -1393,7 +1393,7 @@ def __init__(self, dataset: dict, task: TaskManager):
             task (str): Task to be evaluated on.
         """
         self.dataset_name = dataset["data_source"]
-        self.sub_name = dataset.get("subset", "sst2")
+        self.sub_name = dataset.get("subset", "SetFit/sst2")
         self.task = task
 
     @staticmethod
diff --git a/langtest/embeddings/huggingface.py b/langtest/embeddings/huggingface.py
index d749400e7..ce904dcd2 100644
--- a/langtest/embeddings/huggingface.py
+++ b/langtest/embeddings/huggingface.py
@@ -13,6 +13,9 @@ class HuggingfaceEmbeddings:
         model (transformers.AutoModel): The transformer model used for sentence embeddings.
     """
 
+    model = None
+    tokenizer = None
+
     def __init__(
         self,
         model: str = "sentence-transformers/all-mpnet-base-v2",
@@ -20,11 +23,20 @@ def __init__(
         """Constructor method
 
         Args:
-            model_name (str): The name of the model to be loaded. By default, it uses the multilingual MiniLM model.
+            model (str): The name of the model to be loaded. By default, it uses the all-mpnet-base-v2 model.
         """
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        self.tokenizer = AutoTokenizer.from_pretrained(model)
-        self.model = AutoModel.from_pretrained(model).to(self.device)
+
+        # Load model and tokenizer if not already loaded or if model name differs
+        model_loaded = (
+            HuggingfaceEmbeddings.model is not None
+            and HuggingfaceEmbeddings.tokenizer is not None
+            and HuggingfaceEmbeddings.model.config.name_or_path == model
+        )
+
+        if not model_loaded:
+            HuggingfaceEmbeddings.model = AutoModel.from_pretrained(model).to(self.device)
+            HuggingfaceEmbeddings.tokenizer = AutoTokenizer.from_pretrained(model)
 
     def mean_pooling(
         self, model_output: Tuple[torch.Tensor], attention_mask: torch.Tensor
diff --git a/langtest/errors.py b/langtest/errors.py
index c4cb90189..57afa90bc 100644
--- a/langtest/errors.py
+++ b/langtest/errors.py
@@ -276,6 +276,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E095 = ("Failed to make API request: {e}")
     E096 = ("Failed to generate the templates in Augmentation: {msg}")
     E097 = ("Failed to load openai. Please install it using `pip install openai`")
+    E098 = ("Invalid model architecture! "
+            "Expected model types are: {model_arch}, but got: {type_model}")
 
 
 class ColumnNameError(Exception):
diff --git a/langtest/langtest.py b/langtest/langtest.py
index a21961fcb..43fbf2367 100644
--- a/langtest/langtest.py
+++ b/langtest/langtest.py
@@ -1539,7 +1539,7 @@ def __single_dataset_generate(self, dataset: list):
                         setattr(sample, "expected_results", v(sample.original))
                         for sample in m_data
                     ]
-                    (testcases[k]) = TestFactory.transform(
+                    testcases[k] = TestFactory.transform(
                         self.task, dataset, tests, m_data=m_data
                     )
 
@@ -1556,7 +1556,7 @@ def __single_dataset_generate(self, dataset: list):
                     testcases = DataFactory.filter_curated_bias(tests_to_filter, dataset)
                     if len(tests.keys()) > 2:
                         tests = {k: v for k, v in tests.items() if k != "bias"}
-                        (other_testcases) = TestFactory.transform(
+                        other_testcases = TestFactory.transform(
                             self.task, dataset, tests, m_data=m_data
                         )
                         testcases.extend(other_testcases)
diff --git a/langtest/metrics/prometheus_eval.py b/langtest/metrics/prometheus_eval.py
index cb0e7921b..cc1b9d63c 100644
--- a/langtest/metrics/prometheus_eval.py
+++ b/langtest/metrics/prometheus_eval.py
@@ -222,8 +222,7 @@ def get_prompt(self) -> str:
             The prompt for the model.
         """
         s, f = self.get_score_rubric()
-        prompt = dedent(
-            """
+        prompt = dedent("""
         ###Task Description:
         An instruction (might include an Input inside it), a response to evaluate, a reference answer that gets from {formatted_criteria_keys}, and a score rubric representing a evaluation criteria are given.
         1. Write a detailed feedback that assess the quality of the response strictly based on the given score rubric, not evaluating in general.
@@ -244,8 +243,7 @@ def get_prompt(self) -> str:
         {score_rubric}
 
         ###Feedback:
-        """
-        )
+        """)
         return prompt.format(
             instruction=self.instruction,
             response=self.response,
@@ -302,8 +300,7 @@ def get_prompt(self) -> str:
             The prompt for the model.
         """
         s, f = self.get_score_rubric()
-        prompt = dedent(
-            """
+        prompt = dedent("""
         ###Task Description:
         An instruction (might include an Input inside it), a response to evaluate, and a score rubric representing a evaluation criteria are given.
         1. Write a detailed feedback that assess the quality of two responses strictly based on the given score rubric, not evaluating in general.
@@ -327,8 +324,7 @@ def get_prompt(self) -> str:
         {score_rubric}
 
         ###Feedback:
-        """
-        )
+        """)
         return prompt.format(
             instruction=self.instruction,
             response_a=self.response_a,
diff --git a/langtest/modelhandler/transformers_modelhandler.py b/langtest/modelhandler/transformers_modelhandler.py
index c8020ad4c..47ff8c1b0 100644
--- a/langtest/modelhandler/transformers_modelhandler.py
+++ b/langtest/modelhandler/transformers_modelhandler.py
@@ -1,8 +1,7 @@
-from typing import Any, Dict, List, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 import logging
 import numpy as np
 from functools import lru_cache
-from transformers import Pipeline, pipeline, AutoModelForCausalLM, AutoTokenizer
 from .modelhandler import ModelAPI
 from ..utils.custom_types import (
     NEROutput,
@@ -18,6 +17,16 @@
 )
 from ..utils.hf_utils import HuggingFacePipeline
 
+from transformers import (
+    AutoConfig,
+    AutoModelForSeq2SeqLM,
+    Pipeline,
+    pipeline,
+    AutoModelForCausalLM,
+    AutoTokenizer,
+    PretrainedConfig,
+)
+
 
 class PretrainedModelForNER(ModelAPI):
     """Transformers pretrained model for NER tasks
@@ -407,62 +416,193 @@ def __call__(
 
 
 class PretrainedModelForTranslation(ModelAPI):
-    """Transformers pretrained model for translation tasks
+    """Transformers pretrained model for translation tasks.
 
     Args:
-        model (transformers.pipeline.Pipeline): Pretrained HuggingFace translation pipeline for predictions.
+        tokenizer: Pretrained HuggingFace tokenizer.
+        model: Pretrained HuggingFace sequence-to-sequence or causal LM model.
+        source_lang (str): Default source language for translation.
+        target_lang (str): Default target language for translation.
+        is_encoder_decoder (bool): Whether the loaded model is an encoder-decoder type.
     """
 
-    def __init__(self, model):
-        """Constructor method
+    def __init__(
+        self,
+        tokenizer: AutoTokenizer,
+        model: Any,
+        source_lang: str = "English",
+        target_lang: str = "German",
+        is_encoder_decoder: bool = True,
+        prompt: Optional[str] = None,
+        **kwargs,
+    ):
+        # Extract the base architecture string names from the model's config
+        model_architectures = (
+            getattr(model, "config", PretrainedConfig()).architectures or []
+        )
 
-        Args:
-            model (transformers.pipeline.Pipeline): Pretrained HuggingFace NER pipeline for predictions.
-        """
-        assert isinstance(model, Pipeline), ValueError(
-            Errors.E079(Pipeline=Pipeline, type_model=type(model))
+        is_supported = any(
+            "CausalLM" in arch
+            or "Seq2SeqLM" in arch
+            or "ConditionalGeneration" in arch
+            or "MTModel" in arch
+            for arch in model_architectures
         )
+
+        assert is_supported, ValueError(
+            Errors.E098(
+                model_arch=(AutoModelForSeq2SeqLM, AutoModelForCausalLM),
+                type_model=type(model),
+            )
+        )
+
+        self.tokenizer = tokenizer
         self.model = model
+        self.source_lang = source_lang
+        self.target_lang = target_lang
+        self.is_encoder_decoder = is_encoder_decoder
+        self.prompt: Optional[str] = prompt
+        self.kwargs = kwargs
 
     @classmethod
-    def load_model(cls, path: str, *args, **kwargs) -> "Pipeline":
-        """Load the Translation model into the `model` attribute.
+    def load_model(cls, path: str, *args, **kwargs) -> "PretrainedModelForTranslation":
+        """Load the Translation model into the `model` attribute."""
 
-        Args:
-            path (str):
-                path to model or model name
-
-        Returns:
-            'Pipeline':
-        """
-        from ..langtest import HARNESS_CONFIG as harness_config
+        source_lang = kwargs.pop("source_language", None)
+        target_lang = kwargs.pop("target_language", None)
+        prompt = kwargs.pop("prompt", None)
 
-        config = harness_config["model_parameters"]
-        tgt_lang = config.get("target_language") or kwargs.get("target_language")
+        # Fallback to langtest configurations if not explicitly provided
+        if not source_lang or not target_lang:
+            try:
+                from langtest import HARNESS_CONFIG
 
-        if "t5" in path:
-            return cls(pipeline(f"translation_en_to_{tgt_lang}", model=path))
+                config_harness = HARNESS_CONFIG.get("model_parameters", {})
+                source_lang = source_lang or config_harness.get(
+                    "source_language", "English"
+                )
+                target_lang = target_lang or config_harness.get(
+                    "target_language", "German"
+                )
+            except ImportError:
+                source_lang = source_lang or "English"
+                target_lang = target_lang or "German"
+
+        tokenizer_loaded = AutoTokenizer.from_pretrained(path)
+        model_config = AutoConfig.from_pretrained(path)
+        is_enc_dec = model_config.is_encoder_decoder
+
+        # Pass remaining args/kwargs (like device_map) to the model loading
+        if is_enc_dec:
+            model_loaded = AutoModelForSeq2SeqLM.from_pretrained(
+                path, device_map="auto", *args, **kwargs
+            )
         else:
-            return cls(pipeline(model=path, src_lang="en", tgt_lang=tgt_lang))
+            print(
+                f"Warning: Model '{path}' is not an encoder-decoder model. "
+                "Loading as AutoModelForCausalLM. Performance may vary."
+            )
+            model_loaded = AutoModelForCausalLM.from_pretrained(
+                path, device_map="auto", *args, **kwargs
+            )
+
+        return cls(
+            tokenizer_loaded,
+            model_loaded,
+            source_lang,
+            target_lang,
+            is_encoder_decoder=is_enc_dec,
+            prompt=prompt,
+        )
 
     @lru_cache(maxsize=102400)
-    def predict(self, text: str, **kwargs) -> TranslationOutput:
-        """Perform predictions on the input text.
+    def predict(
+        self,
+        text: str,
+        **kwargs,
+    ) -> TranslationOutput:
+        """
+        Perform predictions on the input text. Wraps kwargs to enable LRU caching.
 
         Args:
             text (str): Input text to perform translation on.
-            kwargs: Additional keyword arguments.
-
 
         Returns:
-            TranslationOutput: Output model for translation tasks
+            TranslationOutput: Translated text from the input text.
         """
-        prediction = self.model(text, **kwargs)[0]["translation_text"]
+        model_type = getattr(self.model.config, "model_type", "").lower()
+
+        # 1. Handle Prompting for T5 or Custom Prompts
+        if self.prompt:
+            input_text = self.prompt.format(text=text)
+        elif "t5" in model_type:
+            input_text = f"translate {self.source_lang} to {self.target_lang}: {text}"
+        else:
+            input_text = text
+
+        # 2. Set source language for multilingual tokenizers (NLLB, M2M100, mBART)
+        if hasattr(self.tokenizer, "src_lang"):
+            self.tokenizer.src_lang = self.source_lang
+
+        inputs = self.tokenizer(input_text, return_tensors="pt").to(self.model.device)
+
+        # 3. Safely extract and construct generation arguments
+        gen_kwargs = {
+            "max_length": kwargs.pop("max_length", 512),
+            "num_beams": kwargs.pop("num_beams", 1),
+            **kwargs,
+        }
+
+        # Hugging Face crashes if diversity_penalty is set without num_beam_groups > 1
+        num_beam_groups = kwargs.pop("num_beam_groups", 1)
+        if num_beam_groups > 1:
+            gen_kwargs["num_beam_groups"] = num_beam_groups
+            gen_kwargs["diversity_penalty"] = kwargs.pop("diversity_penalty", 0.0)
+
+        # 4. Handle Target Language tokens (forced_bos_token_id)
+        if "forced_bos_token_id" not in gen_kwargs:
+            # Primary strategy: Direct vocabulary lookup (NLLB uses this)
+            if hasattr(self.tokenizer, "convert_tokens_to_ids"):
+                token_id = self.tokenizer.convert_tokens_to_ids(self.target_lang)
+                # Ensure it didn't return an unknown token (meaning target_lang isn't formatted correctly)
+                if token_id is not None and token_id != self.tokenizer.unk_token_id:
+                    gen_kwargs["forced_bos_token_id"] = token_id
+
+            # Fallback strategies for mBART or M2M100
+            if "forced_bos_token_id" not in gen_kwargs:
+                if (
+                    hasattr(self.tokenizer, "lang_code_to_id")
+                    and self.target_lang in self.tokenizer.lang_code_to_id
+                ):
+                    gen_kwargs["forced_bos_token_id"] = self.tokenizer.lang_code_to_id[
+                        self.target_lang
+                    ]
+                elif hasattr(self.tokenizer, "get_lang_id"):
+                    try:
+                        gen_kwargs["forced_bos_token_id"] = self.tokenizer.get_lang_id(
+                            self.target_lang
+                        )
+                    except Exception:
+                        pass
+
+        # Generate tokens
+        output_tokens = self.model.generate(**inputs, **gen_kwargs)
+
+        # Decode based on architecture
+        if self.is_encoder_decoder:
+            prediction = self.tokenizer.decode(output_tokens[0], skip_special_tokens=True)
+        else:
+            # For Causal LMs, strip the input prompt from the output
+            input_length = inputs["input_ids"].shape[1]
+            prediction = self.tokenizer.decode(
+                output_tokens[0][input_length:], skip_special_tokens=True
+            )
+
         return TranslationOutput(translation_text=prediction)
 
     def __call__(self, text: str, *args, **kwargs) -> TranslationOutput:
         """Alias of the 'predict' method"""
-        return self.predict(text=text, **kwargs)
+        return self.predict(text=text, *args, **kwargs)
 
 
 class PretrainedModelForWinoBias(ModelAPI):
diff --git a/langtest/pipelines/transformers/ner_pipeline.py b/langtest/pipelines/transformers/ner_pipeline.py
index 30c51402f..dc9f017fa 100644
--- a/langtest/pipelines/transformers/ner_pipeline.py
+++ b/langtest/pipelines/transformers/ner_pipeline.py
@@ -126,7 +126,7 @@ def train(self):
             model=self.model,
             args=TrainingArguments(output_dir=self.output_dir, **self.training_args),
             train_dataset=self.train_dataset,
-            tokenizer=self.tokenizer,
+            processing_class=self.tokenizer,
         )
         trainer.train()
         self.model.save_pretrained(self.output_dir)
@@ -215,7 +215,7 @@ def retrain(self):
             ),
             train_dataset=self.augmented_train_dataset,
             eval_dataset=self.eval_dataset,
-            tokenizer=self.tokenizer,
+            processing_class=self.tokenizer,
         )
         trainer.train()
         self.model.save_pretrained(f"augmented_{self.output_dir}")
diff --git a/langtest/prompts.py b/langtest/prompts.py
index dd0b84cd0..63ec122c9 100644
--- a/langtest/prompts.py
+++ b/langtest/prompts.py
@@ -32,7 +32,8 @@ def get_template(self):
         order_less = []
 
         sorted_fields = sorted(
-            self.__dict__.keys(), key=lambda x: self.__field_order.index(x.lower())
+            (k for k in self.__dict__.keys() if k.lower() in self.__field_order),
+            key=lambda x: self.__field_order.index(x.lower()),
         )
 
         for field in sorted_fields:
@@ -126,7 +127,7 @@ def get_input_variables(self):
     def prompt_style(self):
         """Generate a prompt based on the prompt type."""
         if self.prompt_type in ["chat", "instruct"]:
-            from langchain.prompts import (
+            from langchain_core.prompts import (
                 ChatPromptTemplate,
                 FewShotChatMessagePromptTemplate,
             )
@@ -149,7 +150,7 @@ def prompt_style(self):
             return final_prompt
 
         elif self.prompt_type == "completion":
-            from langchain.prompts import FewShotPromptTemplate, PromptTemplate
+            from langchain_core.prompts import FewShotPromptTemplate, PromptTemplate
 
             template = "".join(v for _, v in self.get_template)
             template = f"{template.replace('Answer:', '')}"
diff --git a/langtest/transform/clinical.py b/langtest/transform/clinical.py
index d18fbad54..4d887d750 100644
--- a/langtest/transform/clinical.py
+++ b/langtest/transform/clinical.py
@@ -958,8 +958,7 @@ def transform(sample_list: List[Sample], *args, **kwargs):
             else:
                 from textwrap import dedent
 
-                error_message = dedent(
-                    """
+                error_message = dedent("""
                     Attack model information is not provided in Configuration. Please provide the attack model information.
                     {
                         "medfuzz": {
@@ -970,8 +969,7 @@ def transform(sample_list: List[Sample], *args, **kwargs):
                             }
                         }
                     }
-                """
-                ).strip()
+                """).strip()
 
                 raise ValueError(error_message)
 
diff --git a/langtest/transform/constants.py b/langtest/transform/constants.py
index 04b027add..ab1e36e22 100644
--- a/langtest/transform/constants.py
+++ b/langtest/transform/constants.py
@@ -146203,10 +146203,10 @@
 bad_word_list= ['2g1c', '2 girls 1 cup', 'acrotomophilia', 'alabama hot pocket', 'alaskan pipeline', 'anal', 'anilingus', 'anus', 'apeshit', 'arsehole', 'ass', 'asshole', 'assmunch', 'auto erotic', 'autoerotic', 'babeland', 'baby batter', 'baby juice', 'ball gag', 'ball gravy', 'ball kicking', 'ball licking', 'ball sack', 'ball sucking', 'bangbros', 'bangbus', 'bareback', 'barely legal', 'barenaked', 'bastard', 'bastardo', 'bastinado', 'bbw', 'bdsm', 'beaner', 'beaners', 'beaver cleaver', 'beaver lips', 'beastiality', 'bestiality', 'big black', 'big breasts', 'big knockers', 'big tits', 'bimbos', 'birdlock', 'bitch', 'bitches', 'black cock', 'blonde action', 'blonde on blonde action', 'blowjob', 'blow job', 'blow your load', 'blue waffle', 'blumpkin', 'bollocks', 'bondage', 'boner', 'boob', 'boobs', 'booty call', 'brown showers', 'brunette action', 'bukkake', 'bulldyke', 'bullet vibe', 'bullshit', 'bung hole', 'bunghole', 'busty', 'butt', 'buttcheeks', 'butthole', 'camel toe', 'camgirl', 'camslut', 'camwhore', 'carpet muncher', 'carpetmuncher', 'chocolate rosebuds', 'cialis', 'circlejerk', 'cleveland steamer', 'clit', 'clitoris', 'clover clamps', 'clusterfuck', 'cock', 'cocks', 'coprolagnia', 'coprophilia', 'cornhole', 'coon', 'coons', 'creampie', 'cum', 'cumming', 'cumshot', 'cumshots', 'cunnilingus', 'cunt', 'darkie', 'date rape', 'daterape', 'deep throat', 'deepthroat', 'dendrophilia', 'dick', 'dildo', 'dingleberry', 'dingleberries', 'dirty pillows', 'dirty sanchez', 'doggie style', 'doggiestyle', 'doggy style', 'doggystyle', 'dog style', 'dolcett', 'domination', 'dominatrix', 'dommes', 'donkey punch', 'double dong', 'double penetration', 'dp action', 'dry hump', 'dvda', 'eat my ass', 'ecchi', 'ejaculation', 'erotic', 'erotism', 'escort', 'eunuch', 'fag', 'faggot', 'fecal', 'felch', 'fellatio', 'feltch', 'female squirting', 'femdom', 'figging', 'fingerbang', 'fingering', 'fisting', 'foot fetish', 'footjob', 'frotting', 'fuck', 'fuck buttons', 'fuckin', 'fucking', 'fucktards', 'fudge packer', 'fudgepacker', 'futanari', 'gangbang', 'gang bang', 'gay sex', 'genitals', 'giant cock', 'girl on', 'girl on top', 'girls gone wild', 'goatcx', 'goatse', 'god damn', 'gokkun', 'golden shower', 'goodpoop', 'goo girl', 'goregasm', 'grope', 'group sex', 'g-spot', 'guro', 'hand job', 'handjob', 'hard core', 'hardcore', 'hentai', 'homoerotic', 'honkey', 'hooker', 'horny', 'hot carl', 'hot chick', 'how to kill', 'how to murder', 'huge fat', 'humping', 'incest', 'intercourse', 'jack off', 'jail bait', 'jailbait', 'jelly donut', 'jerk off', 'jigaboo', 'jiggaboo', 'jiggerboo', 'jizz', 'juggs', 'kike', 'kinbaku', 'kinkster', 'kinky', 'knobbing', 'leather restraint', 'leather straight jacket', 'lemon party', 'livesex', 'lolita', 'lovemaking', 'make me come', 'male squirting', 'masturbate', 'masturbating', 'masturbation', 'menage a trois', 'milf', 'missionary position', 'mong', 'motherfucker', 'mound of venus', 'mr hands', 'muff diver', 'muffdiving', 'nambla', 'nawashi', 'negro', 'neonazi', 'nigga', 'nigger', 'nig nog', 'nimphomania', 'nipple', 'nipples', 'nsfw', 'nsfw images', 'nude', 'nudity', 'nutten', 'nympho', 'nymphomania', 'octopussy', 'omorashi', 'one cup two girls', 'one guy one jar', 'orgasm', 'orgy', 'paedophile', 'paki', 'panties', 'panty', 'pedobear', 'pedophile', 'pegging', 'penis', 'phone sex', 'piece of shit', 'pikey', 'pissing', 'piss pig', 'pisspig', 'playboy', 'pleasure chest', 'pole smoker', 'ponyplay', 'poof', 'poon', 'poontang', 'punany', 'poop chute', 'poopchute', 'porn', 'porno', 'pornography', 'prince albert piercing', 'pthc', 'pubes', 'pussy', 'queaf', 'queef', 'quim', 'raghead', 'raging boner', 'rape', 'raping', 'rapist', 'rectum', 'reverse cowgirl', 'rimjob', 'rimming', 'rosy palm', 'rosy palm and her 5 sisters', 'rusty trombone', 'sadism', 'santorum', 'scat', 'schlong', 'scissoring', 'semen', 'sex', 'sexcam', 'sexo', 'sexy', 'sexual', 'sexually', 'sexuality', 'shaved beaver', 'shaved pussy', 'shemale', 'shibari', 'shit', 'shitblimp', 'shitty', 'shota', 'shrimping', 'skeet', 'slanteye', 'slut', 's&m', 'smut', 'snatch', 'snowballing', 'sodomize', 'sodomy', 'spastic', 'spic', 'splooge', 'splooge moose', 'spooge', 'spread legs', 'spunk', 'strap on', 'strapon', 'strappado', 'strip club', 'style doggy', 'suck', 'sucks', 'suicide girls', 'sultry women', 'swastika', 'swinger', 'tainted love', 'taste my', 'tea bagging', 'threesome', 'throating', 'thumbzilla', 'tied up', 'tight white', 'tit', 'tits', 'titties', 'titty', 'tongue in a', 'topless', 'tosser', 'towelhead', 'tranny', 'tribadism', 'tub girl', 'tubgirl', 'tushy', 'twat', 'twink', 'twinkie', 'two girls one cup', 'undressing', 'upskirt', 'urethra play', 'urophilia', 'vagina', 'venus mound', 'viagra', 'vibrator', 'violet wand', 'vorarephilia', 'voyeur', 'voyeurweb', 'voyuer', 'vulva', 'wank', 'wetback', 'wet dream', 'white power', 'whore', 'worldsex', 'wrapping men', 'wrinkled starfish', 'xx', 'xxx', 'yaoi', 'yellow showers', 'yiffy', 'zoophilia', '🖕']
 
 DATASETS = {
-    'sst2': {
+    'SetFit/sst2': {
         'subsets': [''],
         'labels': [['Negative Sentiment', 'Positive Sentiment']],
-        'fields': [['sentence']],
+        'fields': [['text']],
         'label_names': ['label'],
     },
     'rotten_tomatoes': {
diff --git a/langtest/transform/grammar.py b/langtest/transform/grammar.py
index a960241a1..4bba9d51d 100644
--- a/langtest/transform/grammar.py
+++ b/langtest/transform/grammar.py
@@ -177,21 +177,18 @@ def transform(
         sample_list: List[Sample], prob: Optional[float] = 1.0, *args, **kwargs
     ):
         if try_import_lib("transformers"):
-            from transformers import pipeline
+            from langtest.utils.hf_utils import paraphrase
 
-            pipe = pipeline(
-                "text2text-generation", model="humarin/chatgpt_paraphraser_on_T5_base"
-            )
             for idx, sample in enumerate(sample_list):
                 if isinstance(sample, str):
-                    test_case = pipe(sample, max_length=11000, num_return_sequences=1)[0][
-                        "generated_text"
-                    ]
+                    test_case = paraphrase(
+                        sample, max_length=11000, num_return_sequences=1
+                    )[0]
                     sample_list[idx] = test_case
                 else:
-                    test_case = pipe(
+                    test_case = paraphrase(
                         sample.original, max_length=1000, num_return_sequences=1
-                    )[0]["generated_text"]
+                    )[0]
                     sample.test_case = test_case
                     sample.category = "grammar"
 
diff --git a/langtest/transform/robustness.py b/langtest/transform/robustness.py
index 62c0b69b9..23eb6f332 100644
--- a/langtest/transform/robustness.py
+++ b/langtest/transform/robustness.py
@@ -34,7 +34,6 @@
 from ..utils.number_to_word import ConvertNumberToWord
 from collections import defaultdict
 
-
 inverted_ocr_typo_dict = defaultdict(list)
 for k, v in ocr_typo_dict.items():
     inverted_ocr_typo_dict[v].append(k)
diff --git a/langtest/transform/utils.py b/langtest/transform/utils.py
index 5df82d68f..42ba31b9c 100644
--- a/langtest/transform/utils.py
+++ b/langtest/transform/utils.py
@@ -266,7 +266,7 @@ def get_ethnicity_representation_dict(data: List[Sample]) -> Dict[str, int]:
 
     @staticmethod
     def get_entity_representation_proportions(
-        entity_representation: Dict[str, int]
+        entity_representation: Dict[str, int],
     ) -> Dict[str, float]:
         """Calculates the proportions of each entity in the representation.
 
@@ -562,7 +562,10 @@ def get_criteria_scores(self, case_id, question_id, section_id=None):
         df = self.filter(self.criteria, case_id=case_id, question_id=question_id)
         if section_id:
             df = df[df["section_id"] == section_id]
-        return [float(score.replace(",", ".")) for score in df["criteria_score_possible"]]
+        return [
+            float(score.replace(",", ".")) if isinstance(score, str) else score
+            for score in df["criteria_score_possible"]
+        ]
 
     @lru_cache(maxsize=4)
     def load_csv(self, filename) -> pd.DataFrame:
@@ -572,7 +575,7 @@ def load_csv(self, filename) -> pd.DataFrame:
         )
         try:
             # save the csv file into `~/.langtest/` directory
-            location_path = os.path.expanduser(f"~/.langtest/amgea/{filename}")
+            location_path = os.path.expanduser(f"~/.langtest/amega/{filename}")
             os.makedirs(os.path.dirname(location_path), exist_ok=True)
             if not os.path.exists(location_path):
                 import requests
@@ -582,7 +585,7 @@ def load_csv(self, filename) -> pd.DataFrame:
                 with open(location_path, "wb") as f:
                     f.write(response.content)
 
-            return pd.read_csv(location_path, delimiter=";")
+            return pd.read_csv(location_path, delimiter=",")
         except (FileNotFoundError, pd.errors.ParserError) as e:
             print(f"Error loading {filename}: {e}")
             return pd.DataFrame()
@@ -603,7 +606,7 @@ def dataset_info(self) -> pd.DataFrame:
         for case_id in cases_ids:
 
             case_branch = self.cases[self.cases["case_id"] == case_id][
-                "case_brunch"
+                "case_branch"
             ].values[0]
             case_title = self.cases[self.cases["case_id"] == case_id][
                 "case_title"
@@ -937,7 +940,7 @@ def aggregate_results(self, benchmark_data, evaluation_results):
         """
         # Get case info
         case_data = benchmark_data.get_case_data(case_id=self.case_id)[0]
-        case_brunch = case_data["case_brunch"]
+        case_branch = case_data["case_branch"]
 
         # Prepare base aggregated data
         aggregated_data = {
@@ -945,7 +948,7 @@ def aggregate_results(self, benchmark_data, evaluation_results):
             "generator_type": self.generator_type,
             "evaluator_model_name_or_path": self.model,
             "case_id": self.case_id,
-            "case_brunch": case_brunch,
+            "case_branch": case_branch,
         }
 
         # Initialize per-question fields
@@ -976,7 +979,7 @@ def aggregate_results(self, benchmark_data, evaluation_results):
             results_list.append(
                 [
                     aggregated_data["case_id"],
-                    aggregated_data["case_brunch"],
+                    aggregated_data["case_branch"],
                     q_id,
                     question_possible,
                     question_initial,
@@ -1001,7 +1004,7 @@ def aggregate_results(self, benchmark_data, evaluation_results):
         results_list.append(
             [
                 self.case_id,
-                aggregated_data["case_brunch"],
+                aggregated_data["case_branch"],
                 "total",
                 aggregated_data["case_possible_score"],
                 aggregated_data["case_initial_score"],
diff --git a/langtest/utils/config_utils.py b/langtest/utils/config_utils.py
index 9631bb8b6..b0d9608ee 100644
--- a/langtest/utils/config_utils.py
+++ b/langtest/utils/config_utils.py
@@ -3,7 +3,6 @@
 # from pkg_resources import resource_filename
 from importlib import resources
 
-
 LLM_DEFAULTS_CONFIG = {
     "azure-openai": str(
         resources.files("langtest").joinpath(
diff --git a/langtest/utils/custom_types/helpers.py b/langtest/utils/custom_types/helpers.py
index 27f244156..9c2dcc5da 100644
--- a/langtest/utils/custom_types/helpers.py
+++ b/langtest/utils/custom_types/helpers.py
@@ -425,8 +425,8 @@ def llm_prompt_eval(
         bool: True if the model's prediction passes the LLM evaluation, False otherwise.
 
     """
-    from langchain.evaluation.qa import QAEvalChain
-    from langchain.prompts import PromptTemplate
+    from langchain_classic.evaluation.qa import QAEvalChain
+    from langchain_core.prompts import PromptTemplate
 
     PROMPT = PromptTemplate(
         input_variables=["query", "answer", "result"],
diff --git a/langtest/utils/hf_utils.py b/langtest/utils/hf_utils.py
index b7e051ffc..206f3a295 100644
--- a/langtest/utils/hf_utils.py
+++ b/langtest/utils/hf_utils.py
@@ -156,7 +156,8 @@ class HuggingFacePipeline:
 
     To use, you should have the ``transformers`` python package installed.
 
-    Only supports `text-generation`, `text2text-generation` and `summarization` for now.
+    Supports `text-generation` for both causal and encoder-decoder models
+    (compatible with Transformers v5+ task consolidation).
     """
 
     def __init__(
@@ -176,6 +177,7 @@ def __init__(
         self.pipeline: Pipeline = None
         self.model_type = kwargs.get("model_type", None)
         self.chat_template = kwargs.get("chat_template", None)
+
         if pipeline:
             self.pipeline = pipeline
         else:
@@ -201,27 +203,40 @@ def _initialize_pipeline(
                 AutoModelForCausalLM,
                 AutoModelForSeq2SeqLM,
                 AutoTokenizer,
+                AutoConfig,
             )
             from transformers import pipeline as hf_pipeline
         except ImportError:
             raise ValueError(Errors.E085())
 
+        # Map deprecated v4 tasks to the unified v5 text-generation task
+        if task in ("text2text-generation", "summarization"):
+            logging.info(
+                f"Task '{task}' is deprecated in transformers v5. Automatically mapping to 'text-generation'."
+            )
+            task = "text-generation"
+
+        if task != "text-generation":
+            raise ValueError(Errors.E086(task=task))
+
         tokenizer = AutoTokenizer.from_pretrained(model_id)
+        config = AutoConfig.from_pretrained(model_id)
 
         # remove the unnecessary kwargs
         kwargs.pop("model_type", None)
 
-        # Set the pad_token_id for the tokenizer
-        tokenizer.pad_token_id = tokenizer.eos_token_id
+        # Set the pad_token_id for the tokenizer if not already set
+        if tokenizer.pad_token_id is None:
+            tokenizer.pad_token_id = tokenizer.eos_token_id
 
         try:
-            if task == "text-generation":
-                model = AutoModelForCausalLM.from_pretrained(model_id)
-            elif task in ("text2text-generation", "summarization"):
+            # Dynamically determine the correct model class based strictly on architecture
+            if config.is_encoder_decoder:
                 model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
             else:
-                raise ValueError(Errors.E086(task=task))
-        except ImportError as e:
+                model = AutoModelForCausalLM.from_pretrained(model_id)
+
+        except Exception as e:
             raise ValueError(Errors.E087(task=task)) from e
 
         if (
@@ -242,7 +257,7 @@ def _initialize_pipeline(
             if device < 0 and cuda_device_count > 0:
                 logging.warning(Warnings.W016(cuda_device_count=cuda_device_count))
 
-        # renove the unnecessary kwargs
+        # remove the unnecessary kwargs
         kwargs.pop("chat_template", None)
 
         return hf_pipeline(
@@ -272,11 +287,9 @@ def _generate(self, prompts: List[str]) -> List[str]:
             ):
                 self.pipeline.tokenizer.chat_template = self.chat_template
 
-            # return_full_text = False is available in transformers>=4.11.0
-            if self.pipeline.task == "text-generation":
-                response = self.pipeline(prompt, return_full_text=False)
-            else:
-                response = self.pipeline(prompt)
+            # return_full_text = False prevents the prompt from being prepended to the response
+            # Works cleanly now that all tasks are routed through text-generation
+            response = self.pipeline(prompt, return_full_text=False)
 
             if isinstance(response, list):
                 response = response[0]
@@ -291,3 +304,71 @@ def _generate(self, prompts: List[str]) -> List[str]:
             text_generations.append(text)
 
         return text_generations
+
+
+class ParaphraseModel:
+    _instance = None
+    _device = "cpu"
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self):
+        from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+        if not self._initialized:
+            self.tokenizer = AutoTokenizer.from_pretrained(
+                "humarin/chatgpt_paraphraser_on_T5_base"
+            )
+            self.model = AutoModelForSeq2SeqLM.from_pretrained(
+                "humarin/chatgpt_paraphraser_on_T5_base"
+            ).to(self._device)
+            self._initialized = True
+
+
+def paraphrase(
+    text: str,
+    num_beams=5,
+    num_beam_groups=5,
+    num_return_sequences=1,
+    repetition_penalty=10.0,
+    diversity_penalty=3.0,
+    no_repeat_ngram_size=2,
+    temperature=0.7,
+    max_length=128,
+    device="cpu",
+):
+    # Use ParaphraseModel singleton if model and tokenizer not provided
+    # if model is None or tokenizer is None:
+    paraphrase_model = ParaphraseModel()
+    model = paraphrase_model.model
+    tokenizer = paraphrase_model.tokenizer
+    device = paraphrase_model._device
+
+    input_ids = tokenizer(
+        f"paraphrase: {text}",
+        return_tensors="pt",
+        padding="longest",
+        max_length=max_length,
+        truncation=True,
+    ).input_ids.to(device)
+
+    outputs = model.generate(
+        input_ids,
+        temperature=temperature,
+        repetition_penalty=repetition_penalty,
+        num_return_sequences=num_return_sequences,
+        no_repeat_ngram_size=no_repeat_ngram_size,
+        num_beams=num_beams,
+        num_beam_groups=num_beam_groups,
+        max_length=max_length,
+        diversity_penalty=diversity_penalty,
+        trust_remote_code=True,
+    )
+
+    res = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+
+    return res
diff --git a/poetry.lock b/poetry.lock
index 7851594d0..d72f1c588 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -280,10 +280,10 @@ tz = ["tzdata"]
 name = "annotated-doc"
 version = "0.0.4"
 description = "Document parameters, class attributes, return types, and variables inline, with Annotated."
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"spacy\") or extra == \"spacy\" or extra == \"mlflow\""
+markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"transformers\" or extra == \"spacy\") or extra == \"transformers\" or extra == \"spacy\" or extra == \"mlflow\""
 files = [
     {file = "annotated_doc-0.0.4-py3-none-any.whl", hash = "sha256:571ac1dc6991c450b25a9c2d84a3705e2ae7a53467b5d111c24fa8baabbed320"},
     {file = "annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4"},
@@ -303,15 +303,14 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.14.1"
+version = "4.14.2"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\" or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"mlflow\") or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"openai\" or extra == \"databricks\" or extra == \"llms\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"ollama-sdk\" or extra == \"mlflow\""
 files = [
-    {file = "anyio-4.14.1-py3-none-any.whl", hash = "sha256:4e5533c5b8ff0a24f5d7a176cbe6877129cd183893f66b537f8f227d10527d72"},
-    {file = "anyio-4.14.1.tar.gz", hash = "sha256:8d648a3544c1a700e3ff78615cd679e4c5c3f149904287e73687b2596963629e"},
+    {file = "anyio-4.14.2-py3-none-any.whl", hash = "sha256:9f505dda5ac9f0c8309b5e8bd445a8c2bf7246f3ce950121e45ea15bc41d1494"},
+    {file = "anyio-4.14.2.tar.gz", hash = "sha256:cfa139f3ed1a23ee8f88a145ddb5ac7605b8bbfd8592baacd7ce3d8bb4313c7f"},
 ]
 
 [package.dependencies]
@@ -336,14 +335,14 @@ files = [
 
 [[package]]
 name = "asttokens"
-version = "3.0.1"
+version = "3.0.2"
 description = "Annotate AST trees with source code positions"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
 files = [
-    {file = "asttokens-3.0.1-py3-none-any.whl", hash = "sha256:15a3ebc0f43c2d0a50eeafea25e19046c68398e487b9f1f5b517f7c0f40f976a"},
-    {file = "asttokens-3.0.1.tar.gz", hash = "sha256:71a4ee5de0bde6a31d64f6b13f2293ac190344478f081c3d1bccfcf5eacb0cb7"},
+    {file = "asttokens-3.0.2-py3-none-any.whl", hash = "sha256:9da13157f5b28becde0bd374fc677dcd3c290614264eff096f167c469cd9f933"},
+    {file = "asttokens-3.0.2.tar.gz", hash = "sha256:3ecdbd8f2cc195f53ccada3a613538bb5f9ef6f6869129f13e03c30a677b8fe2"},
 ]
 markers = {main = "extra == \"johnsnowlabs\""}
 
@@ -378,48 +377,54 @@ files = [
 
 [[package]]
 name = "black"
-version = "24.10.0"
+version = "26.5.1"
 description = "The uncompromising code formatter."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "black-24.10.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6668650ea4b685440857138e5fe40cde4d652633b1bdffc62933d0db4ed9812"},
-    {file = "black-24.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1c536fcf674217e87b8cc3657b81809d3c085d7bf3ef262ead700da345bfa6ea"},
-    {file = "black-24.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:649fff99a20bd06c6f727d2a27f401331dc0cc861fb69cde910fe95b01b5928f"},
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 packaging = ">=22.0"
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 [package.extras]
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 [[package]]
 name = "blinker"
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+]
+
+[package.dependencies]
+httpx = {version = "*", extras = ["http2"]}
 msgpack = "*"
 ndindex = "*"
 numexpr = {version = ">=2.14.1", markers = "platform_machine != \"wasm32\""}
 numpy = ">=1.26"
 pydantic = "*"
-requests = "*"
 rich = "*"
 threadpoolctl = {version = "*", markers = "platform_machine != \"wasm32\""}
 
@@ -539,18 +544,18 @@ tui = ["textual", "textual-plotext"]
 
 [[package]]
 name = "boto3"
-version = "1.43.40"
+version = "1.43.51"
 description = "The AWS SDK for Python"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
-botocore = ">=1.43.40,<1.44.0"
+botocore = ">=1.43.51,<1.44.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.19.0,<0.20.0"
 
@@ -559,14 +564,14 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.43.40"
+version = "1.43.51"
 description = "Low-level, data-driven core of boto 3."
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -575,7 +580,7 @@ python-dateutil = ">=2.1,<3.0.0"
 urllib3 = ">=1.25.4,<2.2.0 || >2.2.0,<3"
 
 [package.extras]
-crt = ["awscrt (==0.32.2)"]
+crt = ["awscrt (==0.36.0)"]
 
 [[package]]
 name = "cachetools"
@@ -617,98 +622,114 @@ files = [
 
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-version = "2.0.0"
+version = "2.1.0"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
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 [package.dependencies]
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 [[package]]
@@ -1068,103 +1054,103 @@ test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"
 
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 [package.extras]
@@ -1177,7 +1163,7 @@ description = "cryptography is a package which provides cryptographic recipes an
 optional = true
 python-versions = "!=3.9.0,!=3.9.1,>=3.9"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
+markers = "python_version == \"3.12\" and (extra == \"mlflow\" or extra == \"databricks\") or extra == \"mlflow\""
 files = [
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@@ -1415,14 +1401,14 @@ urllib3 = ">=1.26.7,<3"
 
 [[package]]
 name = "databricks-connect"
-version = "18.3.1"
+version = "18.3.2"
 description = "Databricks Connect Client"
 optional = true
 python-versions = "==3.12.*"
 groups = ["main"]
 markers = "python_version == \"3.12\" and extra == \"databricks\""
 files = [
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 ]
 
 [package.dependencies]
@@ -1474,15 +1460,15 @@ integration = ["langgraph (>=0.2.27)", "pytest-timeout (>=2.3.1)"]
 
 [[package]]
 name = "databricks-sdk"
-version = "0.120.0"
+version = "0.121.0"
 description = "Databricks SDK for Python (Beta)"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "databricks_sdk-0.120.0-py3-none-any.whl", hash = "sha256:2d8e19444df30f714123b330fb616d7775f96631f6e36b4dd252adb4f2e010e2"},
-    {file = "databricks_sdk-0.120.0.tar.gz", hash = "sha256:12c41492e5d6e7105cb06e6d1a0f1bdf11b76b0630f3a7da85aa8db4fe91dee8"},
+    {file = "databricks_sdk-0.121.0-py3-none-any.whl", hash = "sha256:98ddcb19d2f4c1beabaac0dc90b0685892f492600b231039fc51b50f31716b63"},
+    {file = "databricks_sdk-0.121.0.tar.gz", hash = "sha256:fa2a1b32487007d9c273a449daf6bb7e9dca0a5ef0d34a81a4ed33cad0b4accc"},
 ]
 
 [package.dependencies]
@@ -1629,6 +1615,19 @@ files = [
 ]
 markers = {main = "extra == \"johnsnowlabs\""}
 
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+description = "XML bomb protection for Python stdlib modules"
+optional = true
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+groups = ["main"]
+markers = "extra == \"evaluate\""
+files = [
+    {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
+    {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"},
+]
+
 [[package]]
 name = "deprecated"
 version = "1.3.1"
@@ -1707,15 +1706,15 @@ files = [
 
 [[package]]
 name = "docker"
-version = "7.1.0"
+version = "7.2.0"
 description = "A Python library for the Docker Engine API."
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "docker-7.1.0-py3-none-any.whl", hash = "sha256:c96b93b7f0a746f9e77d325bcfb87422a3d8bd4f03136ae8a85b37f1898d5fc0"},
-    {file = "docker-7.1.0.tar.gz", hash = "sha256:ad8c70e6e3f8926cb8a92619b832b4ea5299e2831c14284663184e200546fa6c"},
+    {file = "docker-7.2.0-py3-none-any.whl", hash = "sha256:a3f45fdeb9165e2d25d9a1d02ddf3bc70fb572cf5ebbf9b58558c22caf29b71f"},
+    {file = "docker-7.2.0.tar.gz", hash = "sha256:cebb93773d334f778e023a7ee352a8d6e13ab1bd3b863a4d4a59dec897df43ac"},
 ]
 
 [package.dependencies]
@@ -1826,15 +1825,15 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastapi"
-version = "0.139.0"
+version = "0.139.2"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "fastapi-0.139.0-py3-none-any.whl", hash = "sha256:cf15e1e9e667ddb0ad63811e60bd11390d1aac838ca4a7a23f421807b2308189"},
-    {file = "fastapi-0.139.0.tar.gz", hash = "sha256:99ab7b2d92223c76d6cf10757ab3f89d45b38267fc20b2a136cf02f6beac3145"},
+    {file = "fastapi-0.139.2-py3-none-any.whl", hash = "sha256:b9ad015a835173d59865e2f5d8296fbc2b317bf56a2ba1a5bfbdd03de2fd4b1c"},
+    {file = "fastapi-0.139.2.tar.gz", hash = "sha256:333145a6891e9b5b3cfceb69baf817e8240cde4d4588ae5a10bf56ffacb6255e"},
 ]
 
 [package.dependencies]
@@ -1919,14 +1918,14 @@ zstandard = ["backports.zstd ; python_version < \"3.14\""]
 
 [[package]]
 name = "filelock"
-version = "3.29.5"
+version = "3.31.1"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
-    {file = "filelock-3.29.5-py3-none-any.whl", hash = "sha256:8af830889ba3a0ffcefbd6c7d2af8a54012058103771f2e10848222f476a1693"},
-    {file = "filelock-3.29.5.tar.gz", hash = "sha256:6e6034c57a00a020e767f2614a5539863f056de7e7991d6d1473aef7ff73f156"},
+    {file = "filelock-3.31.1-py3-none-any.whl", hash = "sha256:9ea33146c780161bf67cb20c7cb26b651566820d65ad8dfdd79422602a2dcfc0"},
+    {file = "filelock-3.31.1.tar.gz", hash = "sha256:9e0c4e88ebe90833c1beafd3a547ccbc0bf7f491cd3858c3ec7aed63efe02163"},
 ]
 markers = {main = "extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"huggingface-hub\""}
 
@@ -2266,15 +2265,15 @@ smmap = ">=3.0.1,<6"
 
 [[package]]
 name = "gitpython"
-version = "3.1.50"
+version = "3.1.52"
 description = "GitPython is a Python library used to interact with Git repositories"
 optional = true
 python-versions = ">=3.7"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "gitpython-3.1.50-py3-none-any.whl", hash = "sha256:d352abe2908d07355014abdd21ddf798c2a961469239afec4962e9da884858f9"},
-    {file = "gitpython-3.1.50.tar.gz", hash = "sha256:80da2d12504d52e1f998772dc5baf6e553f8d2fcfe1fcc226c9d9a2ee3372dcc"},
+    {file = "gitpython-3.1.52-py3-none-any.whl", hash = "sha256:79a36ee1f83523214a3f72d56cf1c4e490d577dc61af77e43dfe5862bd9da01a"},
+    {file = "gitpython-3.1.52.tar.gz", hash = "sha256:de0a8ad86274c6e75ae8b37dd055ba68f19818c813108642263227b20775b48e"},
 ]
 
 [package.dependencies]
@@ -2286,32 +2285,36 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock ; python_version < \"3.
 
 [[package]]
 name = "google-auth"
-version = "2.55.1"
+version = "2.56.0"
 description = "Google Authentication Library"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "google_auth-2.55.1-py3-none-any.whl", hash = "sha256:eada68dfd52b3b81191827601e2a0c3fa12540c818534b630ddc5355769c3995"},
-    {file = "google_auth-2.55.1.tar.gz", hash = "sha256:fb2d9b730f2c9b8d326ec8d7222f21aef2ead15bf0513793d6442485d87af0a1"},
+    {file = "google_auth-2.56.0-py3-none-any.whl", hash = "sha256:6e88c10217e07a92bfd01cac8ee99e32ccfb08414c3102e6c5b8d58f37a0d1e0"},
+    {file = "google_auth-2.56.0.tar.gz", hash = "sha256:f90fa030b569a92654b9d690665a073841df33d57487be53db583a9a0867a553"},
 ]
 
 [package.dependencies]
-cryptography = ">=38.0.3"
+cryptography = [
+    {version = ">=38.0.3", markers = "python_version < \"3.14\""},
+    {version = ">=41.0.5", markers = "python_version >= \"3.14\""},
+]
 pyasn1-modules = ">=0.2.1"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.8.0,<4.0.0)", "requests (>=2.20.0,<3.0.0)"]
-cryptography = ["cryptography (>=38.0.3)"]
-enterprise-cert = ["pyopenssl"]
+aiohttp = ["aiohttp (>=3.8.0,<4.0.0) ; python_version < \"3.14\"", "aiohttp (>=3.9.0,<4.0.0) ; python_version >= \"3.14\"", "requests (>=2.30.0,<3.0.0)"]
+cryptography = ["cryptography (>=38.0.3) ; python_version < \"3.14\"", "cryptography (>=41.0.5) ; python_version >= \"3.14\""]
+enterprise-cert = ["cryptography (>=38.0.3) ; python_version < \"3.14\"", "cryptography (>=41.0.5) ; python_version >= \"3.14\""]
+grpc = ["grpcio (>=1.59.0,<2.0.0) ; python_version < \"3.14\"", "grpcio (>=1.75.1,<2.0.0) ; python_version >= \"3.14\""]
 pyjwt = ["pyjwt (>=2.0)"]
-pyopenssl = ["pyopenssl (>=20.0.0)"]
+pyopenssl = ["cryptography (>=38.0.3) ; python_version < \"3.14\"", "cryptography (>=41.0.5) ; python_version >= \"3.14\""]
 reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0)"]
-rsa = ["rsa (>=3.1.4,<5)"]
-testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.8.0,<4.0.0)", "aioresponses", "flask", "freezegun", "grpcio", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"]
-urllib3 = ["packaging", "urllib3"]
+requests = ["requests (>=2.30.0,<3.0.0)"]
+rsa = ["rsa (>=4.0.0,<5)"]
+testing = ["aiohttp (>=3.8.0,<4.0.0) ; python_version < \"3.14\"", "aiohttp (>=3.9.0,<4.0.0) ; python_version >= \"3.14\"", "aioresponses", "flask", "freezegun", "grpcio (>=1.59.0,<2.0.0) ; python_version < \"3.14\"", "grpcio (>=1.75.1,<2.0.0) ; python_version >= \"3.14\"", "packaging (>=20.0)", "pyjwt (>=2.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.30.0,<3.0.0)", "responses", "urllib3 (>=1.26.15,<3.0.0)"]
+urllib3 = ["packaging (>=20.0)", "urllib3 (>=1.26.15,<3.0.0)"]
 
 [[package]]
 name = "googleapis-common-protos"
@@ -2480,71 +2483,71 @@ test = ["objgraph", "psutil", "setuptools"]
 
 [[package]]
 name = "grpcio"
-version = "1.82.0"
+version = "1.82.1"
 description = "HTTP/2-based RPC framework"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and extra == \"databricks\""
 files = [
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+    {file = "hf_xet-1.5.2-cp314-cp314t-win_amd64.whl", hash = "sha256:fd3add255549e8ef58fa35b2e42dc016961c050600444e7d77d030ba6b57120e"},
+    {file = "hf_xet-1.5.2-cp314-cp314t-win_arm64.whl", hash = "sha256:d6f9c58549407b84b9a5383afd68db0acc42345326a3159990b36a5ca8a20e4e"},
+    {file = "hf_xet-1.5.2-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:f922b8f5fb84f1dd3d7ab7a1316354a1bca9b1c73ecfc19c76e51a2a49d29799"},
+    {file = "hf_xet-1.5.2-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:045f84440c55cdeb659cf1a1dd48c77bcd0d2e93632e2fea8f2c3bdee79f38ed"},
+    {file = "hf_xet-1.5.2-cp38-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:db78c39c83d6279daddc98e2238f373ab8980685556d42472b4ec51abcf03e8c"},
+    {file = "hf_xet-1.5.2-cp38-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:7db73c810500c54c6760be8c39d4b2e476974de85424c50063efc22fdda13025"},
+    {file = "hf_xet-1.5.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:6395cfe3c9cbead4f16b31808b0e67eac428b66c656f856e99636adaddea878f"},
+    {file = "hf_xet-1.5.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:cde8cd167126bb6109b2ceb19b844433a4988643e8f3e01dd9dd0e4a34535097"},
+    {file = "hf_xet-1.5.2-cp38-abi3-win_amd64.whl", hash = "sha256:ecf63d1cb69a9a7319910f8f83fcf9b46e7a32dfcf4b8f8eeddb55f647306e65"},
+    {file = "hf_xet-1.5.2-cp38-abi3-win_arm64.whl", hash = "sha256:1da28519496eb7c8094c11e4d25509b4a468457a0302d58136099db2fd9a671d"},
+    {file = "hf_xet-1.5.2.tar.gz", hash = "sha256:73044bd31bae33c984af832d19c752a0dffb67518fee9ddbd91d616e1101cf47"},
 ]
 
 [package.extras]
 tests = ["pytest"]
 
+[[package]]
+name = "hpack"
+version = "4.2.0"
+description = "Pure-Python HPACK header encoding"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "hpack-4.2.0-py3-none-any.whl", hash = "sha256:858ac0b02280fa582b5080d68db0899c62a80375e0e5413a74970c5e518b6986"},
+    {file = "hpack-4.2.0.tar.gz", hash = "sha256:0895cfa3b5531fc65fe439c05eb65144f123bf7a394fcaa56aa423548d8e45c0"},
+]
+
 [[package]]
 name = "httpcore"
 version = "1.0.9"
@@ -2647,7 +2669,6 @@ description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\" or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\") or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"openai\" or extra == \"databricks\" or extra == \"llms\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"ollama-sdk\""
 files = [
     {file = "httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55"},
     {file = "httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8"},
@@ -2670,7 +2691,6 @@ description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\" or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\") or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"openai\" or extra == \"databricks\" or extra == \"llms\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"ollama-sdk\""
 files = [
     {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"},
     {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
@@ -2679,6 +2699,7 @@ files = [
 [package.dependencies]
 anyio = "*"
 certifi = "*"
+h2 = {version = ">=3,<5", optional = true, markers = "extra == \"http2\""}
 httpcore = "==1.*"
 idna = "*"
 
@@ -2704,15 +2725,15 @@ files = [
 
 [[package]]
 name = "huey"
-version = "3.1.1"
+version = "3.2.1"
 description = "a little task queue"
 optional = true
 python-versions = "*"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "huey-3.1.1-py3-none-any.whl", hash = "sha256:8773231c7bc7a40b9b9191d72cf1c6580bbf6742a4118c70dde6b5c2e7ccb7ce"},
-    {file = "huey-3.1.1.tar.gz", hash = "sha256:156f30e90f0fae81ae2e004f2062e1b18ec9dcbc684564df63159ef546b13502"},
+    {file = "huey-3.2.1-py3-none-any.whl", hash = "sha256:da9e004b80941a718f33f9714697a67e6d5cf12e0707fc4f3dbb5d9c796e7224"},
+    {file = "huey-3.2.1.tar.gz", hash = "sha256:79cd63d117e5b8da2de58420dcde4e2d0f963e362d67a9b3872ce565eec5c3dc"},
 ]
 
 [package.extras]
@@ -2721,43 +2742,52 @@ postgres = ["psycopg (>=3.2)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.36.2"
+version = "1.24.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
-python-versions = ">=3.8.0"
+python-versions = ">=3.10.0"
 groups = ["main"]
 markers = "extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"huggingface-hub\""
 files = [
-    {file = "huggingface_hub-0.36.2-py3-none-any.whl", hash = "sha256:48f0c8eac16145dfce371e9d2d7772854a4f591bcb56c9cf548accf531d54270"},
-    {file = "huggingface_hub-0.36.2.tar.gz", hash = "sha256:1934304d2fb224f8afa3b87007d58501acfda9215b334eed53072dd5e815ff7a"},
+    {file = "huggingface_hub-1.24.0-py3-none-any.whl", hash = "sha256:6ed4120a84a6beec900640aa7e346bd766a6b7341e41526fef5dc8bd81fb7d59"},
+    {file = "huggingface_hub-1.24.0.tar.gz", hash = "sha256:18431ff4daae0749aa9ba102fc952e314c98e1d30ebdec5319d85ca0a83e1ae5"},
 ]
 
 [package.dependencies]
-filelock = "*"
+click = ">=8.4.2,<9.0.0"
+filelock = ">=3.10.0"
 fsspec = ">=2023.5.0"
-hf-xet = {version = ">=1.1.3,<2.0.0", markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\""}
+hf-xet = {version = ">=1.5.1,<2.0.0", markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\""}
+httpx = ">=0.23.0,<1"
 packaging = ">=20.9"
 pyyaml = ">=5.1"
-requests = "*"
 tqdm = ">=4.42.1"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
-cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "duckdb", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "duckdb", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-transfer = ["hf_transfer (>=0.1.4)"]
-hf-xet = ["hf-xet (>=1.1.2,<2.0.0)"]
-inference = ["aiohttp"]
-mcp = ["aiohttp", "mcp (>=1.8.0)", "typer"]
+gradio = ["gradio (>=5.0.0)", "requests"]
+hf-xet = ["hf-xet (>=1.5.1,<2.0.0)"]
+mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
-quality = ["libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "ruff (>=0.9.0)", "ty"]
-tensorflow = ["graphviz", "pydot", "tensorflow"]
-tensorflow-testing = ["keras (<3.0)", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
+testing = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "duckdb", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors[torch]", "torch"]
-typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+typing = ["types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+
+[[package]]
+name = "hyperframe"
+version = "6.1.0"
+description = "Pure-Python HTTP/2 framing"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "hyperframe-6.1.0-py3-none-any.whl", hash = "sha256:b03380493a519fce58ea5af42e4a42317bf9bd425596f7a0835ffce80f1a42e5"},
+    {file = "hyperframe-6.1.0.tar.gz", hash = "sha256:f630908a00854a7adeabd6382b43923a4c4cd4b821fcb527e6ab9e15382a3b08"},
+]
 
 [[package]]
 name = "identify"
@@ -3136,15 +3166,15 @@ files = [
 
 [[package]]
 name = "johnsnowlabs"
-version = "6.4.0"
+version = "6.4.1"
 description = "The John Snow Labs Library gives you access to all of John Snow Labs Enterprise And Open Source products in an easy and simple manner. Access 10000+ state-of-the-art NLP and OCR models for Finance, Legal and Medical domains. Easily scalable to Spark Cluster "
 optional = true
 python-versions = "*"
 groups = ["main"]
 markers = "extra == \"johnsnowlabs\""
 files = [
-    {file = "johnsnowlabs-6.4.0-py3-none-any.whl", hash = "sha256:1194c8e1a25716f30b70068eb11c4de68c2e2481dcd4b581182e45da063e7e1a"},
-    {file = "johnsnowlabs-6.4.0.tar.gz", hash = "sha256:2c6a38c863ff26ac1bd2a36a4a12d156393ee53f987eac67fe947d5033ff839f"},
+    {file = "johnsnowlabs-6.4.1-py3-none-any.whl", hash = "sha256:4598cfca0622d53538fd4e3baf1a038b4bf9c2e80f77206c33108e03df61df2e"},
+    {file = "johnsnowlabs-6.4.1.tar.gz", hash = "sha256:cbc87651fccc36e532d285cc22b22476455a176c5bf3411f280ecf1d694b16e5"},
 ]
 
 [package.dependencies]
@@ -3157,7 +3187,7 @@ numpy = "*"
 pydantic = ">=2"
 pyspark = "3.4.0"
 requests = "*"
-spark-nlp = "6.4.0"
+spark-nlp = "6.4.2"
 spark-nlp-display = "5.0"
 
 [[package]]
@@ -3379,19 +3409,19 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "1.3.11"
+version = "1.3.14"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\") or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"databricks\" or extra == \"llms\" or extra == \"ollama-sdk\""
 files = [
-    {file = "langchain-1.3.11-py3-none-any.whl", hash = "sha256:7ae011f95a09b22feea1e8ae4e43f0b6164aebf4c61b8ad845b45f72ff3a90a2"},
-    {file = "langchain-1.3.11.tar.gz", hash = "sha256:f3cf9cd4d2329b1a03eb8fd92b9d73e4e58a4d52570d67725fc77fbe0f104b32"},
+    {file = "langchain-1.3.14-py3-none-any.whl", hash = "sha256:4d10dbe91005952cddd56d0dc77aa108964da6bae90ab20063653957e901f782"},
+    {file = "langchain-1.3.14.tar.gz", hash = "sha256:1b6696c72ba3bbbce54d745e0180742c9f6ece8bbc59ed5a46c3e20b9a435929"},
 ]
 
 [package.dependencies]
-langchain-core = ">=1.4.7,<2.0.0"
+langchain-core = ">=1.4.9,<2.0.0"
 langgraph = ">=1.2.5,<1.3.0"
 pydantic = ">=2.7.4,<3.0.0"
 
@@ -3407,6 +3437,7 @@ google-genai = ["langchain-google-genai"]
 google-vertexai = ["langchain-google-vertexai"]
 groq = ["langchain-groq"]
 huggingface = ["langchain-huggingface"]
+meta = ["langchain-meta"]
 mistralai = ["langchain-mistralai"]
 ollama = ["langchain-ollama"]
 openai = ["langchain-openai"]
@@ -3486,15 +3517,15 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "1.4.8"
+version = "1.4.9"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\") or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"databricks\" or extra == \"llms\" or extra == \"ollama-sdk\""
 files = [
-    {file = "langchain_core-1.4.8-py3-none-any.whl", hash = "sha256:d84c28b05e3ba8d4271d0827aad5b592ccdaaf986e76768c23503f0a2045e8aa"},
-    {file = "langchain_core-1.4.8.tar.gz", hash = "sha256:5bf1f8411077c904182ad8f975943d36adcbf579c4e017b3a118b719229ebf9a"},
+    {file = "langchain_core-1.4.9-py3-none-any.whl", hash = "sha256:28e3909e2a10cc81504952d795ac0a9e014c0018121ef89d48dd396fa09ec624"},
+    {file = "langchain_core-1.4.9.tar.gz", hash = "sha256:f8078901145bed0466755277500a5a22822a7b628808c4c0a28d4fc88895fcf2"},
 ]
 
 [package.dependencies]
@@ -3577,15 +3608,15 @@ langchain-core = ">=1.2.31,<2.0.0"
 
 [[package]]
 name = "langgraph"
-version = "1.2.7"
+version = "1.2.9"
 description = "Building stateful, multi-actor applications with LLMs"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\") or extra == \"openai\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"huggingface-hub\" or extra == \"databricks\" or extra == \"llms\" or extra == \"ollama-sdk\""
 files = [
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 cycler = ">=0.10"
-fonttools = ">=4.22.0"
+fonttools = ">=4.28.2"
 kiwisolver = ">=1.3.1"
 numpy = ">=1.25"
 packaging = ">=20.0"
@@ -4478,22 +4509,22 @@ files = [
 
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 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"evaluate\") or extra == \"evaluate\" or extra == \"mlflow\""
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 modin = ["modin (>=0.22.0)"]
 pandas = ["pandas (>=1.3.4)"]
 polars = ["polars (>=0.20.4)"]
@@ -4600,7 +4631,7 @@ description = "Python package for creating and manipulating graphs and networks"
 optional = true
 python-versions = ">=3.11"
 groups = ["main"]
-markers = "python_version >= \"3.13\" and extra == \"transformers\""
+markers = "python_version == \"3.14\" and extra == \"transformers\""
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 optional = true
 python-versions = "!=3.14.1,>=3.11"
 groups = ["main"]
-markers = "python_version == \"3.12\" and extra == \"transformers\""
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 python-versions = ">=3.10"
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 ]
 
 [package.dependencies]
 click = "*"
+defusedxml = "*"
 joblib = "*"
 regex = ">=2021.8.3"
 tqdm = "*"
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+]
+
+[package.dependencies]
+numpy = ">=1.26.0"
 
 [[package]]
 name = "numpy"
@@ -4904,15 +4925,15 @@ et-xmlfile = "*"
 
 [[package]]
 name = "opentelemetry-api"
-version = "1.43.0"
+version = "1.44.0"
 description = "OpenTelemetry Python API"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
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+    {file = "opentelemetry_api-1.44.0.tar.gz", hash = "sha256:67647e5e9566edcf421166fdf022b3537f818635daa852b289e34604dc6fb33a"},
 ]
 
 [package.dependencies]
@@ -4920,15 +4941,15 @@ typing-extensions = ">=4.5.0"
 
 [[package]]
 name = "opentelemetry-proto"
-version = "1.43.0"
+version = "1.44.0"
 description = "OpenTelemetry Python Proto"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
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 ]
 
 [package.dependencies]
@@ -4936,40 +4957,40 @@ protobuf = ">=5.0,<8.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.43.0"
+version = "1.44.0"
 description = "OpenTelemetry Python SDK"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
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+    {file = "opentelemetry_sdk-1.44.0-py3-none-any.whl", hash = "sha256:df081c4c6bcfdb1211e3e86140376792643128a25f8d72d1d27675936e7e96ad"},
+    {file = "opentelemetry_sdk-1.44.0.tar.gz", hash = "sha256:cebe7f65dc12f26ead75c6064de12fd2a9052e5060c0272d402cfa203aae123b"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.43.0"
-opentelemetry-semantic-conventions = "0.64b0"
+opentelemetry-api = "1.44.0"
+opentelemetry-semantic-conventions = "0.65b0"
 typing-extensions = ">=4.5.0"
 
 [package.extras]
-file-configuration = ["jsonschema (>=4.0)", "pyyaml (>=6.0)"]
+file-configuration = ["opentelemetry-configuration (==0.65b0)"]
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.64b0"
+version = "0.65b0"
 description = "OpenTelemetry Semantic Conventions"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
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-    {file = "opentelemetry_semantic_conventions-0.64b0.tar.gz", hash = "sha256:72f76fb2d1582d9d033dd1fcd84532e961e6ff3d90d24ba6fabc72975a83864c"},
+    {file = "opentelemetry_semantic_conventions-0.65b0-py3-none-any.whl", hash = "sha256:1cacde7b0ad306f84c5ef08c3dbe1bbaf20165bba6f8bff43b670e555a086bcb"},
+    {file = "opentelemetry_semantic_conventions-0.65b0.tar.gz", hash = "sha256:f9b2b81e9d5b64f11bc952075e7e9c7fb0aab075c7fd1c46d597f1b919852d60"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.43.0"
+opentelemetry-api = "1.44.0"
 typing-extensions = ">=4.5.0"
 
 [[package]]
@@ -5382,14 +5403,14 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.10.0"
+version = "4.10.1"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "platformdirs-4.10.0-py3-none-any.whl", hash = "sha256:fb516cdb12eb0d857d0cd85a7c57cea4d060bee4578d6cf5a14dfdf8cbf8784a"},
-    {file = "platformdirs-4.10.0.tar.gz", hash = "sha256:31e761a6a0ca04faf7353ea759bdba55652be214725111e5aac52dfa29d4bef7"},
+    {file = "platformdirs-4.10.1-py3-none-any.whl", hash = "sha256:0e4eff26be2d75293977f7cddc153fd9b8eaa7fb0c7b64ffe4076cb443117443"},
+    {file = "platformdirs-4.10.1.tar.gz", hash = "sha256:ceab4084426fe6319ce18e86deada8ab1b7487c7aee7040c55e277c9ae793695"},
 ]
 
 [[package]]
@@ -5695,7 +5716,7 @@ description = ""
 optional = true
 python-versions = ">=3.9"
 groups = ["main"]
-markers = "python_version >= \"3.13\" and extra == \"mlflow\""
+markers = "extra == \"mlflow\" and python_version >= \"3.13\""
 files = [
     {file = "protobuf-6.33.6-cp310-abi3-win32.whl", hash = "sha256:7d29d9b65f8afef196f8334e80d6bc1d5d4adedb449971fefd3723824e6e77d3"},
     {file = "protobuf-6.33.6-cp310-abi3-win_amd64.whl", hash = "sha256:0cd27b587afca21b7cfa59a74dcbd48a50f0a6400cfb59391340ad729d91d326"},
@@ -5858,15 +5879,15 @@ files = [
 
 [[package]]
 name = "pyasn1"
-version = "0.6.3"
+version = "0.6.4"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\") or extra == \"mlflow\""
 files = [
-    {file = "pyasn1-0.6.3-py3-none-any.whl", hash = "sha256:a80184d120f0864a52a073acc6fc642847d0be408e7c7252f31390c0f4eadcde"},
-    {file = "pyasn1-0.6.3.tar.gz", hash = "sha256:697a8ecd6d98891189184ca1fa05d1bb00e2f84b5977c481452050549c8a72cf"},
+    {file = "pyasn1-0.6.4-py3-none-any.whl", hash = "sha256:deda9277cfd454080ec40b207fb6df82206a3a2688735233cdcd8d3d565f088b"},
+    {file = "pyasn1-0.6.4.tar.gz", hash = "sha256:9c447d8431c947fe4c8febc4ed9e760bc29011a5b01e5c74b67025bd9fb8ce81"},
 ]
 
 [[package]]
@@ -5908,7 +5929,7 @@ files = [
     {file = "pycparser-3.0-py3-none-any.whl", hash = "sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992"},
     {file = "pycparser-3.0.tar.gz", hash = "sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29"},
 ]
-markers = {main = "(python_version == \"3.12\" or extra == \"mlflow\") and platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\" and (extra == \"databricks\" or extra == \"mlflow\")", dev = "implementation_name == \"pypy\""}
+markers = {main = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\" and (python_version == \"3.12\" or extra == \"mlflow\") and (extra == \"mlflow\" or extra == \"databricks\")", dev = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "pydantic"
@@ -6283,14 +6304,14 @@ six = ">=1.5"
 
 [[package]]
 name = "python-discovery"
-version = "1.4.3"
+version = "1.4.4"
 description = "Python interpreter discovery"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
 files = [
-    {file = "python_discovery-1.4.3-py3-none-any.whl", hash = "sha256:b6e1e4a7d9e3f6948c39746ffe8218225162d738ba39d05ab1d2f6c1cac4878c"},
-    {file = "python_discovery-1.4.3.tar.gz", hash = "sha256:ad57d7045a862460d4a235986c33f13ed707d3aeb9153fa47eb7dfd0d4673289"},
+    {file = "python_discovery-1.4.4-py3-none-any.whl", hash = "sha256:abebe9120b43453b68c908acfb1e72a19d1a959ed2cb620ad38fc57d08056dbe"},
+    {file = "python_discovery-1.4.4.tar.gz", hash = "sha256:5cad33982d412c1f3ffb8f9ca4ea292c9680bca3942451d30b69c37fce53a4a3"},
 ]
 
 [package.dependencies]
@@ -6317,6 +6338,61 @@ files = [
 [package.extras]
 cli = ["click (>=5.0)"]
 
+[[package]]
+name = "pytokens"
+version = "0.4.1"
+description = "A Fast, spec compliant Python 3.14+ tokenizer that runs on older Pythons."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "pytokens-0.4.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a44ed93ea23415c54f3face3b65ef2b844d96aeb3455b8a69b3df6beab6acc5"},
+    {file = "pytokens-0.4.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:add8bf86b71a5d9fb5b89f023a80b791e04fba57960aa790cc6125f7f1d39dfe"},
+    {file = "pytokens-0.4.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:670d286910b531c7b7e3c0b453fd8156f250adb140146d234a82219459b9640c"},
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+    {file = "regex-2026.7.19.tar.gz", hash = "sha256:7e77b324909c1617cbb4c668677e2c6ae13f44d7c1de0d4f15f2e3c10f3315b5"},
 ]
 
 [[package]]
 name = "requests"
 version = "2.34.2"
 description = "Python HTTP for Humans."
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
+markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"johnsnowlabs\" or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"metaflow\" or extra == \"openai\" or extra == \"huggingface-hub\" or extra == \"llms\" or extra == \"ollama-sdk\") or extra == \"johnsnowlabs\" or extra == \"evaluate\" or extra == \"transformers\" or extra == \"datasets\" or extra == \"spacy\" or extra == \"cohere\" or extra == \"ai21\" or extra == \"metaflow\" or extra == \"mlflow\" or extra == \"openai\" or extra == \"huggingface-hub\" or extra == \"databricks\" or extra == \"llms\" or extra == \"ollama-sdk\""
 files = [
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@@ -6751,14 +6828,14 @@ six = ">=1.14.0"
 
 [[package]]
 name = "s3transfer"
-version = "0.19.0"
+version = "0.19.1"
 description = "An Amazon S3 Transfer Manager"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "s3transfer-0.19.0-py3-none-any.whl", hash = "sha256:777cc2415536f1debadb5c2ef7779275d0fc0fe0e042411cdd6caebeb2685262"},
-    {file = "s3transfer-0.19.0.tar.gz", hash = "sha256:ce436931687addc4c1712d52d40b32f53e88315723f107ffa20ba82b05a0f685"},
+    {file = "s3transfer-0.19.1-py3-none-any.whl", hash = "sha256:d5fd7005ee39307455ad5f310b5ea67f4b1960d7fed5b3671ee50c249de675de"},
+    {file = "s3transfer-0.19.1.tar.gz", hash = "sha256:d3d6371dc3f1e5c5427b2b457bcf13bcf87bec334c95aed18642eae61f6926f3"},
 ]
 
 [package.dependencies]
@@ -6945,34 +7022,34 @@ scikit-learn = ">=0.21.3"
 
 [[package]]
 name = "setuptools"
-version = "81.0.0"
-description = "Easily download, build, install, upgrade, and uninstall Python packages"
+version = "83.0.0"
+description = "Most extensible Python build backend with support for C/C++ extension modules"
 optional = true
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"spacy\" or extra == \"transformers\") or extra == \"spacy\" or extra == \"transformers\""
 files = [
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-    {file = "setuptools-81.0.0.tar.gz", hash = "sha256:487b53915f52501f0a79ccfd0c02c165ffe06631443a886740b91af4b7a5845a"},
+    {file = "setuptools-83.0.0-py3-none-any.whl", hash = "sha256:29b23c360f22f414dc7336bb39178cc7bcbf6021ed2733cde173f09dba19abb3"},
+    {file = "setuptools-83.0.0.tar.gz", hash = "sha256:025bccbbf0fa05b6192bc64ae1e7b16e001fd6d6d4d5de03c97b1c1ade523bef"},
 ]
 
 [package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\"", "ruff (>=0.13.0) ; sys_platform != \"cygwin\""]
-core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"]
+check = ["pytest-checkdocs (>=2.14)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\"", "ruff (>=0.13.0) ; sys_platform != \"cygwin\""]
+core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
-enabler = ["pytest-enabler (>=2.2)"]
+enabler = ["pytest-enabler (>=3.4)"]
 test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21) ; python_version >= \"3.9\" and sys_platform != \"cygwin\"", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf ; sys_platform != \"cygwin\"", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
-type = ["importlib_metadata (>=7.0.2) ; python_version < \"3.10\"", "jaraco.develop (>=7.21) ; sys_platform != \"cygwin\"", "mypy (==1.18.*)", "pytest-mypy"]
+type = ["importlib_metadata (>=7.0.2) ; python_version < \"3.10\"", "jaraco.develop (>=7.21) ; sys_platform != \"cygwin\"", "mypy (==1.18.*)", "pytest-mypy (>=1.0.1) ; platform_python_implementation != \"PyPy\""]
 
 [[package]]
 name = "shellingham"
 version = "1.5.4"
 description = "Tool to Detect Surrounding Shell"
-optional = true
+optional = false
 python-versions = ">=3.7"
 groups = ["main"]
-markers = "extra == \"spacy\""
+markers = "extra == \"transformers\" or extra == \"spacy\""
 files = [
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@@ -7015,15 +7092,15 @@ rich = ["rich (>=12)"]
 
 [[package]]
 name = "smart-open"
-version = "8.0.0"
+version = "8.0.1"
 description = "Utils for streaming large files (S3, HDFS, GCS, SFTP, Azure Blob Storage, gzip, bz2, zst...)"
 optional = true
 python-versions = "<4.0,>=3.10"
 groups = ["main"]
 markers = "extra == \"spacy\""
 files = [
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+    {file = "smart_open-8.0.1-py3-none-any.whl", hash = "sha256:3e97f90e92a952cb57863dfe132082c400a52eeeb27c067692fb51dbcc5b0089"},
+    {file = "smart_open-8.0.1.tar.gz", hash = "sha256:18b1c4496003c6902be17c15f032b5c319f307c89c6ae9e6b028b508bed8b2cf"},
 ]
 
 [package.dependencies]
@@ -7196,15 +7273,15 @@ files = [
 
 [[package]]
 name = "spark-nlp"
-version = "6.4.0"
+version = "6.4.2"
 description = "John Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment."
 optional = true
 python-versions = "*"
 groups = ["main"]
 markers = "extra == \"johnsnowlabs\""
 files = [
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 ]
 
 [[package]]
@@ -7662,7 +7739,7 @@ description = "threadpoolctl"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
-markers = "python_version == \"3.12\" and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"evaluate\") or platform_machine != \"wasm32\" or extra == \"evaluate\" or extra == \"mlflow\""
+markers = "(python_version == \"3.12\" or extra == \"evaluate\" or extra == \"mlflow\" or platform_machine != \"wasm32\") and (extra == \"databricks\" or extra == \"mlflow\" or extra == \"evaluate\" or platform_machine != \"wasm32\")"
 files = [
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@@ -7845,38 +7922,44 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.12.1+cpu"
+version = "2.13.0+cpu"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = true
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "extra == \"transformers\""
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+    {file = "torch-2.13.0+cpu-cp315-cp315t-manylinux_2_28_x86_64.whl", hash = "sha256:222a6681467cc7f6f05cd3068dfbc603def3a1e46d1d4620c1c8cdf6178bd563"},
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@@ -7884,7 +7967,7 @@ filelock = "*"
 fsspec = ">=0.8.5"
 jinja2 = "*"
 networkx = ">=2.5.1"
-setuptools = "<82"
+setuptools = ">=77.0.3"
 sympy = ">=1.13.3"
 typing-extensions = ">=4.10.0"
 
@@ -7920,14 +8003,14 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.68.3"
+version = "4.69.0"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
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 [package.dependencies]
@@ -7958,91 +8041,70 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.17.0,<1.19)", "pre-commit", "pytest
 
 [[package]]
 name = "transformers"
-version = "4.57.6"
-description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
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 optional = false
-python-versions = ">=3.9.0"
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 groups = ["main"]
 markers = "extra == \"transformers\""
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+vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
 
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-version = "0.26.8"
+version = "0.27.0"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
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+optional = false
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-markers = "extra == \"spacy\""
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 version = "2.7.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
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+optional = true
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+    {file = "yarl-1.24.5-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:82f75e05912e84b7a0fe57075d9c59de3cb352b928330f2eb69b2e1f54c3e1f0"},
+    {file = "yarl-1.24.5-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:16a2f5010280020e90f5330257e6944bc33e73593b136cc5a241e6c1dc292498"},
+    {file = "yarl-1.24.5-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:ffcd54362564dc1a30fb74d8b8a6e5a6b11ebd5e27266adc3b7427a21a6c9104"},
+    {file = "yarl-1.24.5-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:0465ec8cedc2349b97a6b595ace64084a50c6e839eca40aa0626f38b8350e331"},
+    {file = "yarl-1.24.5-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:4db9aecb141cb7a5447171b57aa1ed3a8fee06af40b992ffc31206c0b0121550"},
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+    {file = "yarl-1.24.5-cp314-cp314t-win_amd64.whl", hash = "sha256:5c88e5815a49d289e599f3513aa7fde0bc2092ff188f99c940f007f90f53d104"},
+    {file = "yarl-1.24.5-cp314-cp314t-win_arm64.whl", hash = "sha256:cf139c02f5f23ef6532040a30ff662c00a318c952334f211046b8e60b7f17688"},
+    {file = "yarl-1.24.5-py3-none-any.whl", hash = "sha256:a33700d13d9b7d84fd10947b09ff69fb9a792e519c8cb9764a3ca70baa6c23a7"},
+    {file = "yarl-1.24.5.tar.gz", hash = "sha256:e81b83143bee16329c23db3c1b2d82b29892fcbcb849186d2f6e98a5abe9a57f"},
 ]
 
 [package.dependencies]
@@ -9069,4 +9132,4 @@ transformers = ["accelerate", "datasets", "torch", "transformers"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.12,<3.15"
-content-hash = "28c2167bf2c74f64c76b6670e79bdb386616ce8132bf9d19a38c03e876cf69b5"
+content-hash = "99ee40f566f1aecd0d61318463603676fa5666b30b81dc29ea717ff40e4e3bae"
diff --git a/pyproject.toml b/pyproject.toml
index 31779a6c4..939e6c378 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -60,7 +60,7 @@ pydantic = ">=2.10.0"
 johnsnowlabs = {version = "^6.0.4", optional = true}
 rouge-score = { version = "^0.1.2", optional = true }
 evaluate = { version = "^0.4.0", optional = true }
-transformers = "^4.52.4"
+transformers = ">=5.5.0"
 huggingface_hub = { version = ">0.16.0", optional = true}
 spacy = { version = ">=3.0.0", optional = true }
 nest-asyncio = "^1.5.0"
@@ -73,13 +73,13 @@ tqdm = "^4.67.1"
 cohere = { version = "^4.10.0", optional = true}
 ai21 = {version = "^1.1.0", optional = true}
 metaflow = {version = ">=2.9.0", optional = true}
-accelerate = {version = "^1.10.0", optional = true}
+accelerate = {version = ">=1.10.0", optional = true}
 seqeval = {version = "^1.2.0", optional = true}
 mlflow = {version = ">=3.10.1", optional = true}
 datasets = {version = ">=3.6.0", optional = true}
 matplotlib = {version = "^3.7.2", optional = true}
 tenacity = {version = "^8.2.2", optional = true}
-langchain = {version = ">=0.3.15", optional = true}
+langchain = {version = ">=1.3.13", optional = true}
 typing-extensions = "^4.10.0"
 langchain-openai = {version = ">=0.3.7", optional = true}
 boto3 = {version = "^1.34.93", optional = true}
@@ -116,7 +116,7 @@ ipdb = "^0.13.13"
 pytest = "^7.4.0"
 taskipy = "^1.11.0"
 en-core-web-sm = { url = "https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.8.0/en_core_web_sm-3.8.0.tar.gz" }
-black = "^24.10.0"
+black = ">=26.3.1"
 pyproject-flake8 = "^7.0.0"
 pre-commit = "^3.3.3"
 pydocstyle = "^6.3.0"
diff --git a/tests/test_augmentation.py b/tests/test_augmentation.py
index 10c49bc80..ac4cb92b6 100644
--- a/tests/test_augmentation.py
+++ b/tests/test_augmentation.py
@@ -42,13 +42,13 @@ def setUp(self) -> None:
             "spacy_textclassification_hf_dataset": {
                 "task": "text-classification",
                 "model": {"model": "textcat_imdb", "hub": "spacy"},
-                "data": {"data_source": "imdb", "source": "huggingface"},
+                "data": {"data_source": "stanfordnlp/imdb", "source": "huggingface"},
                 "config": "tests/fixtures/config_text_classification.yaml",
             },
             "huggingface_textclassification_hf_dataset": {
                 "task": "text-classification",
                 "model": {"model": "lvwerra/distilbert-imdb", "hub": "huggingface"},
-                "data": {"data_source": "imdb", "source": "huggingface"},
+                "data": {"data_source": "stanfordnlp/imdb", "source": "huggingface"},
                 "config": "tests/fixtures/config_text_classification.yaml",
             },
         }
@@ -203,7 +203,7 @@ def test_hf_dataset_textclassification_hf(self):
         self.assertIsInstance(report, pd.DataFrame)
         custom_proportions = {"uppercase": 0.8, "lowercase": 0.8}
         harness.augment(
-            training_data={"data_source": "imdb", "source": "huggingface"},
+            training_data={"data_source": "stanfordnlp/imdb", "source": "huggingface"},
             save_data_path="tests/fixtures/augmented_train_transformed.csv",
             custom_proportions=custom_proportions,
             export_mode="transformed",
@@ -223,7 +223,7 @@ def test_hf_dataset_textclassification_spacy(self):
         self.assertIsInstance(report, pd.DataFrame)
         custom_proportions = {"uppercase": 0.8, "lowercase": 0.8}
         harness.augment(
-            training_data={"data_source": "imdb", "source": "huggingface"},
+            training_data={"data_source": "stanfordnlp/imdb", "source": "huggingface"},
             save_data_path="tests/fixtures/augmented_train_transformed.csv",
             custom_proportions=custom_proportions,
             export_mode="transformed",
diff --git a/tests/test_datasource.py b/tests/test_datasource.py
index 745e40e3e..2580f1950 100644
--- a/tests/test_datasource.py
+++ b/tests/test_datasource.py
@@ -202,7 +202,7 @@ def test_export_data_conll(self):
         (
             HuggingFaceDataset(
                 source_info={
-                    "data_source": "dbrd",
+                    "data_source": "benjaminvdb/dbrd",
                     "feature_column": "text",
                     "target_column": "label",
                     "split": "test[:30]",
@@ -382,7 +382,7 @@ def test_load_data(self, dataset, feature_col, target_col):
     "dataset_config",
     [
         {"data_source": "synthetic-math-data"},
-        {"data_source": "synthetic-nlp-data", "subset": "sst2"},
+        {"data_source": "synthetic-nlp-data", "subset": "SetFit/sst2"},
     ],
 )
 class TestSynteticData:
diff --git a/tests/test_harness.py b/tests/test_harness.py
index 5305f951d..8124070c7 100644
--- a/tests/test_harness.py
+++ b/tests/test_harness.py
@@ -170,7 +170,11 @@ def test_load_HF_data_text_classification(self):
         tc_harness = Harness(
             task="text-classification",
             model={"model": "aychang/roberta-base-imdb", "hub": "huggingface"},
-            data={"data_source": "imdb", "source": "huggingface"},
+            data={
+                "data_source": "stanfordnlp/imdb",
+                "source": "huggingface",
+                "split": "test",
+            },
         )
         tc_harness.data = tc_harness.data[:10]
         tc_harness.generate()
diff --git a/tests/test_nlp_tasks.py b/tests/test_nlp_tasks.py
index ef80b14b9..5b6c6dbd4 100644
--- a/tests/test_nlp_tasks.py
+++ b/tests/test_nlp_tasks.py
@@ -3,7 +3,6 @@
 from langtest import Harness
 from langtest.utils.custom_types import Sample
 
-
 task_configurations = [
     {
         "task": "ner",
@@ -22,7 +21,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "evaluation": {
                 "metric": "embedding_distance",
@@ -45,7 +44,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "evaluation": {
                 "metric": "string_distance",
@@ -68,7 +67,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "tests": {
                 "defaults": {"min_pass_rate": 0.65},
@@ -84,7 +83,7 @@
         "model": {"model": "t5-base", "hub": "huggingface"},
         "data": {"data_source": "XSum", "split": "test-tiny"},
         "config": {
-            "model_parameters": {"max_tokens": 128, "task": "text2text-generation"},
+            "model_parameters": {"max_tokens": 128, "task": "text-generation"},
             "tests": {
                 "defaults": {"min_pass_rate": 0.65},
                 "robustness": {
@@ -140,7 +139,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "tests": {
                 "defaults": {
@@ -194,7 +193,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "tests": {
                 "defaults": {
@@ -211,7 +210,7 @@
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "tests": {
                 "defaults": {
@@ -260,7 +259,7 @@ def test_nlp_task(task_parameters):
         "config": {
             "model_parameters": {
                 "max_tokens": 20,
-                "task": "text2text-generation",
+                "task": "text-generation",
             },
             "tests": {
                 "defaults": {
diff --git a/tests/test_translation.py b/tests/test_translation.py
index 86e8aa7cd..55bacc33d 100644
--- a/tests/test_translation.py
+++ b/tests/test_translation.py
@@ -20,7 +20,7 @@ def setUp(self) -> None:
         # configure the harness
         self.harness.configure(
             {
-                "model_parameters": {"target_language": "de"},
+                "model_parameters": {"target_language": "German"},
                 "tests": {
                     "defaults": {"min_pass_rate": 1.0},
                     "robustness": {