diff --git a/CHANGELOG.md b/CHANGELOG.md
index 933aba35..8c802863 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,3 +1,14 @@
+## [v2.7.1](https://github.com/DS4SD/docling/releases/tag/v2.7.1) - 2024-11-26
+
+### Fix
+
+* Fixes for wordx ([#432](https://github.com/DS4SD/docling/issues/432)) ([`d0a1180`](https://github.com/DS4SD/docling/commit/d0a118047804765b1b8532e72e08272e678c0c93))
+* Force pydantic < 2.10.0 ([#407](https://github.com/DS4SD/docling/issues/407)) ([`d7072b4`](https://github.com/DS4SD/docling/commit/d7072b4b56227756eb2c7abd3a6e7387eeefe7c1))
+
+### Documentation
+
+* Add DocETL, Kotaemon, spaCy integrations; minor docs improvements ([#408](https://github.com/DS4SD/docling/issues/408)) ([`7a45b92`](https://github.com/DS4SD/docling/commit/7a45b92078b3a9fdd8f0650002eddc03e9d780af))
+
 ## [v2.7.0](https://github.com/DS4SD/docling/releases/tag/v2.7.0) - 2024-11-20
 
 ### Feature
diff --git a/docling/backend/msword_backend.py b/docling/backend/msword_backend.py
index 089e94c2..496bdb7b 100644
--- a/docling/backend/msword_backend.py
+++ b/docling/backend/msword_backend.py
@@ -14,7 +14,8 @@ from docling_core.types.doc import (
     TableData,
 )
 from lxml import etree
-from PIL import Image
+from lxml.etree import XPath
+from PIL import Image, UnidentifiedImageError
 
 from docling.backend.abstract_backend import DeclarativeDocumentBackend
 from docling.datamodel.base_models import InputFormat
@@ -132,8 +133,14 @@ class MsWordDocumentBackend(DeclarativeDocumentBackend):
     def walk_linear(self, body, docx_obj, doc) -> DoclingDocument:
         for element in body:
             tag_name = etree.QName(element).localname
+
             # Check for Inline Images (blip elements)
-            drawing_blip = element.xpath(".//a:blip")
+            namespaces = {
+                "a": "http://schemas.openxmlformats.org/drawingml/2006/main",
+                "r": "http://schemas.openxmlformats.org/officeDocument/2006/relationships",
+            }
+            xpath_expr = XPath(".//a:blip", namespaces=namespaces)
+            drawing_blip = xpath_expr(element)
 
             # Check for Tables
             if element.tag.endswith("tbl"):
@@ -210,7 +217,6 @@ class MsWordDocumentBackend(DeclarativeDocumentBackend):
         paragraph = docx.text.paragraph.Paragraph(element, docx_obj)
 
         if paragraph.text is None:
-            # _log.warn(f"paragraph has text==None")
             return
         text = paragraph.text.strip()
         # if len(text)==0 # keep empty paragraphs, they seperate adjacent lists!
@@ -502,10 +508,17 @@ class MsWordDocumentBackend(DeclarativeDocumentBackend):
         image_data = get_docx_image(element, drawing_blip)
         image_bytes = BytesIO(image_data)
         # Open the BytesIO object with PIL to create an Image
-        pil_image = Image.open(image_bytes)
-        doc.add_picture(
-            parent=self.parents[self.level],
-            image=ImageRef.from_pil(image=pil_image, dpi=72),
-            caption=None,
-        )
+        try:
+            pil_image = Image.open(image_bytes)
+            doc.add_picture(
+                parent=self.parents[self.level],
+                image=ImageRef.from_pil(image=pil_image, dpi=72),
+                caption=None,
+            )
+        except (UnidentifiedImageError, OSError) as e:
+            _log.warning("Warning: image cannot be loaded by Pillow")
+            doc.add_picture(
+                parent=self.parents[self.level],
+                caption=None,
+            )
         return
diff --git a/poetry.lock b/poetry.lock
index 461d0f5a..680af6dd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -896,13 +896,13 @@ files = [
 
 [[package]]
 name = "docling-core"
-version = "2.4.1"
+version = "2.5.0"
 description = "A python library to define and validate data types in Docling."
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "docling_core-2.4.1-py3-none-any.whl", hash = "sha256:d76f623f55e48ac4b2d5cda8388d039043d150baf5b1b24577189bfac6bf7475"},
-    {file = "docling_core-2.4.1.tar.gz", hash = "sha256:5656950aef376a3c77666778c0e3905496eb1aae5da4de1d6e750fbfc4be414c"},
+    {file = "docling_core-2.5.0-py3-none-any.whl", hash = "sha256:7694f89e10b46a4e85af74b8ead1b67b79a775993ac2207860d349eb70270b03"},
+    {file = "docling_core-2.5.0.tar.gz", hash = "sha256:41e9e24afc749bc4dd8751d845b1ad2dd699432c1af0513f3ed888c5d59114af"},
 ]
 
 [package.dependencies]
@@ -911,6 +911,7 @@ jsonschema = ">=4.16.0,<5.0.0"
 pandas = ">=2.1.4,<3.0.0"
 pillow = ">=10.3.0,<11.0.0"
 pydantic = ">=2.6.0,<2.10"
+pyyaml = ">=5.1,<7.0.0"
 tabulate = ">=0.9.0,<0.10.0"
 
 [[package]]
@@ -1034,27 +1035,6 @@ Shapely = "*"
 torch = "*"
 torchvision = ">=0.5"
 
-[[package]]
-name = "environs"
-version = "9.5.0"
-description = "simplified environment variable parsing"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "environs-9.5.0-py2.py3-none-any.whl", hash = "sha256:1e549569a3de49c05f856f40bce86979e7d5ffbbc4398e7f338574c220189124"},
-    {file = "environs-9.5.0.tar.gz", hash = "sha256:a76307b36fbe856bdca7ee9161e6c466fd7fcffc297109a118c59b54e27e30c9"},
-]
-
-[package.dependencies]
-marshmallow = ">=3.0.0"
-python-dotenv = "*"
-
-[package.extras]
-dev = ["dj-database-url", "dj-email-url", "django-cache-url", "flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "mypy (==0.910)", "pre-commit (>=2.4,<3.0)", "pytest", "tox"]
-django = ["dj-database-url", "dj-email-url", "django-cache-url"]
-lint = ["flake8 (==4.0.1)", "flake8-bugbear (==21.9.2)", "mypy (==0.910)", "pre-commit (>=2.4,<3.0)"]
-tests = ["dj-database-url", "dj-email-url", "django-cache-url", "pytest"]
-
 [[package]]
 name = "et-xmlfile"
 version = "2.0.0"
@@ -1387,70 +1367,70 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit",
 
 [[package]]
 name = "grpcio"
-version = "1.68.0"
+version = "1.67.1"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "grpcio-1.68.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:619b5d0f29f4f5351440e9343224c3e19912c21aeda44e0c49d0d147a8d01544"},
-    {file = "grpcio-1.68.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:a59f5822f9459bed098ffbceb2713abbf7c6fd13f2b9243461da5c338d0cd6c3"},
-    {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:c03d89df516128febc5a7e760d675b478ba25802447624edf7aa13b1e7b11e2a"},
-    {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:44bcbebb24363d587472089b89e2ea0ab2e2b4df0e4856ba4c0b087c82412121"},
-    {file = "grpcio-1.68.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:79f81b7fbfb136247b70465bd836fa1733043fdee539cd6031cb499e9608a110"},
-    {file = "grpcio-1.68.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:88fb2925789cfe6daa20900260ef0a1d0a61283dfb2d2fffe6194396a354c618"},
-    {file = "grpcio-1.68.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:99f06232b5c9138593ae6f2e355054318717d32a9c09cdc5a2885540835067a1"},
-    {file = "grpcio-1.68.0-cp310-cp310-win32.whl", hash = "sha256:a6213d2f7a22c3c30a479fb5e249b6b7e648e17f364598ff64d08a5136fe488b"},
-    {file = "grpcio-1.68.0-cp310-cp310-win_amd64.whl", hash = "sha256:15327ab81131ef9b94cb9f45b5bd98803a179c7c61205c8c0ac9aff9d6c4e82a"},
-    {file = "grpcio-1.68.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:3b2b559beb2d433129441783e5f42e3be40a9e1a89ec906efabf26591c5cd415"},
-    {file = "grpcio-1.68.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e46541de8425a4d6829ac6c5d9b16c03c292105fe9ebf78cb1c31e8d242f9155"},
-    {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:c1245651f3c9ea92a2db4f95d37b7597db6b246d5892bca6ee8c0e90d76fb73c"},
-    {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4f1931c7aa85be0fa6cea6af388e576f3bf6baee9e5d481c586980c774debcb4"},
-    {file = "grpcio-1.68.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b0ff09c81e3aded7a183bc6473639b46b6caa9c1901d6f5e2cba24b95e59e30"},
-    {file = "grpcio-1.68.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:8c73f9fbbaee1a132487e31585aa83987ddf626426d703ebcb9a528cf231c9b1"},
-    {file = "grpcio-1.68.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:6b2f98165ea2790ea159393a2246b56f580d24d7da0d0342c18a085299c40a75"},
-    {file = "grpcio-1.68.0-cp311-cp311-win32.whl", hash = "sha256:e1e7ed311afb351ff0d0e583a66fcb39675be112d61e7cfd6c8269884a98afbc"},
-    {file = "grpcio-1.68.0-cp311-cp311-win_amd64.whl", hash = "sha256:e0d2f68eaa0a755edd9a47d40e50dba6df2bceda66960dee1218da81a2834d27"},
-    {file = "grpcio-1.68.0-cp312-cp312-linux_armv7l.whl", hash = "sha256:8af6137cc4ae8e421690d276e7627cfc726d4293f6607acf9ea7260bd8fc3d7d"},
-    {file = "grpcio-1.68.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:4028b8e9a3bff6f377698587d642e24bd221810c06579a18420a17688e421af7"},
-    {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:f60fa2adf281fd73ae3a50677572521edca34ba373a45b457b5ebe87c2d01e1d"},
-    {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e18589e747c1e70b60fab6767ff99b2d0c359ea1db8a2cb524477f93cdbedf5b"},
-    {file = "grpcio-1.68.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0d30f3fee9372796f54d3100b31ee70972eaadcc87314be369360248a3dcffe"},
-    {file = "grpcio-1.68.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:7e0a3e72c0e9a1acab77bef14a73a416630b7fd2cbd893c0a873edc47c42c8cd"},
-    {file = "grpcio-1.68.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a831dcc343440969aaa812004685ed322cdb526cd197112d0db303b0da1e8659"},
-    {file = "grpcio-1.68.0-cp312-cp312-win32.whl", hash = "sha256:5a180328e92b9a0050958ced34dddcb86fec5a8b332f5a229e353dafc16cd332"},
-    {file = "grpcio-1.68.0-cp312-cp312-win_amd64.whl", hash = "sha256:2bddd04a790b69f7a7385f6a112f46ea0b34c4746f361ebafe9ca0be567c78e9"},
-    {file = "grpcio-1.68.0-cp313-cp313-linux_armv7l.whl", hash = "sha256:fc05759ffbd7875e0ff2bd877be1438dfe97c9312bbc558c8284a9afa1d0f40e"},
-    {file = "grpcio-1.68.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:15fa1fe25d365a13bc6d52fcac0e3ee1f9baebdde2c9b3b2425f8a4979fccea1"},
-    {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:32a9cb4686eb2e89d97022ecb9e1606d132f85c444354c17a7dbde4a455e4a3b"},
-    {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dba037ff8d284c8e7ea9a510c8ae0f5b016004f13c3648f72411c464b67ff2fb"},
-    {file = "grpcio-1.68.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0efbbd849867e0e569af09e165363ade75cf84f5229b2698d53cf22c7a4f9e21"},
-    {file = "grpcio-1.68.0-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:4e300e6978df0b65cc2d100c54e097c10dfc7018b9bd890bbbf08022d47f766d"},
-    {file = "grpcio-1.68.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:6f9c7ad1a23e1047f827385f4713b5b8c6c7d325705be1dd3e31fb00dcb2f665"},
-    {file = "grpcio-1.68.0-cp313-cp313-win32.whl", hash = "sha256:3ac7f10850fd0487fcce169c3c55509101c3bde2a3b454869639df2176b60a03"},
-    {file = "grpcio-1.68.0-cp313-cp313-win_amd64.whl", hash = "sha256:afbf45a62ba85a720491bfe9b2642f8761ff348006f5ef67e4622621f116b04a"},
-    {file = "grpcio-1.68.0-cp38-cp38-linux_armv7l.whl", hash = "sha256:f8f695d9576ce836eab27ba7401c60acaf9ef6cf2f70dfe5462055ba3df02cc3"},
-    {file = "grpcio-1.68.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:9fe1b141cda52f2ca73e17d2d3c6a9f3f3a0c255c216b50ce616e9dca7e3441d"},
-    {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:4df81d78fd1646bf94ced4fb4cd0a7fe2e91608089c522ef17bc7db26e64effd"},
-    {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:46a2d74d4dd8993151c6cd585594c082abe74112c8e4175ddda4106f2ceb022f"},
-    {file = "grpcio-1.68.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a17278d977746472698460c63abf333e1d806bd41f2224f90dbe9460101c9796"},
-    {file = "grpcio-1.68.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:15377bce516b1c861c35e18eaa1c280692bf563264836cece693c0f169b48829"},
-    {file = "grpcio-1.68.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cc5f0a4f5904b8c25729a0498886b797feb817d1fd3812554ffa39551112c161"},
-    {file = "grpcio-1.68.0-cp38-cp38-win32.whl", hash = "sha256:def1a60a111d24376e4b753db39705adbe9483ef4ca4761f825639d884d5da78"},
-    {file = "grpcio-1.68.0-cp38-cp38-win_amd64.whl", hash = "sha256:55d3b52fd41ec5772a953612db4e70ae741a6d6ed640c4c89a64f017a1ac02b5"},
-    {file = "grpcio-1.68.0-cp39-cp39-linux_armv7l.whl", hash = "sha256:0d230852ba97654453d290e98d6aa61cb48fa5fafb474fb4c4298d8721809354"},
-    {file = "grpcio-1.68.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:50992f214264e207e07222703c17d9cfdcc2c46ed5a1ea86843d440148ebbe10"},
-    {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:14331e5c27ed3545360464a139ed279aa09db088f6e9502e95ad4bfa852bb116"},
-    {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f84890b205692ea813653ece4ac9afa2139eae136e419231b0eec7c39fdbe4c2"},
-    {file = "grpcio-1.68.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b0cf343c6f4f6aa44863e13ec9ddfe299e0be68f87d68e777328bff785897b05"},
-    {file = "grpcio-1.68.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:fd2c2d47969daa0e27eadaf15c13b5e92605c5e5953d23c06d0b5239a2f176d3"},
-    {file = "grpcio-1.68.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:18668e36e7f4045820f069997834e94e8275910b1f03e078a6020bd464cb2363"},
-    {file = "grpcio-1.68.0-cp39-cp39-win32.whl", hash = "sha256:2af76ab7c427aaa26aa9187c3e3c42f38d3771f91a20f99657d992afada2294a"},
-    {file = "grpcio-1.68.0-cp39-cp39-win_amd64.whl", hash = "sha256:e694b5928b7b33ca2d3b4d5f9bf8b5888906f181daff6b406f4938f3a997a490"},
-    {file = "grpcio-1.68.0.tar.gz", hash = "sha256:7e7483d39b4a4fddb9906671e9ea21aaad4f031cdfc349fec76bdfa1e404543a"},
+    {file = "grpcio-1.67.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:8b0341d66a57f8a3119b77ab32207072be60c9bf79760fa609c5609f2deb1f3f"},
+    {file = "grpcio-1.67.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:f5a27dddefe0e2357d3e617b9079b4bfdc91341a91565111a21ed6ebbc51b22d"},
+    {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:43112046864317498a33bdc4797ae6a268c36345a910de9b9c17159d8346602f"},
+    {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c9b929f13677b10f63124c1a410994a401cdd85214ad83ab67cc077fc7e480f0"},
+    {file = "grpcio-1.67.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7d1797a8a3845437d327145959a2c0c47c05947c9eef5ff1a4c80e499dcc6fa"},
+    {file = "grpcio-1.67.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:0489063974d1452436139501bf6b180f63d4977223ee87488fe36858c5725292"},
+    {file = "grpcio-1.67.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:9fd042de4a82e3e7aca44008ee2fb5da01b3e5adb316348c21980f7f58adc311"},
+    {file = "grpcio-1.67.1-cp310-cp310-win32.whl", hash = "sha256:638354e698fd0c6c76b04540a850bf1db27b4d2515a19fcd5cf645c48d3eb1ed"},
+    {file = "grpcio-1.67.1-cp310-cp310-win_amd64.whl", hash = "sha256:608d87d1bdabf9e2868b12338cd38a79969eaf920c89d698ead08f48de9c0f9e"},
+    {file = "grpcio-1.67.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:7818c0454027ae3384235a65210bbf5464bd715450e30a3d40385453a85a70cb"},
+    {file = "grpcio-1.67.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ea33986b70f83844cd00814cee4451055cd8cab36f00ac64a31f5bb09b31919e"},
+    {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:c7a01337407dd89005527623a4a72c5c8e2894d22bead0895306b23c6695698f"},
+    {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:80b866f73224b0634f4312a4674c1be21b2b4afa73cb20953cbbb73a6b36c3cc"},
+    {file = "grpcio-1.67.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9fff78ba10d4250bfc07a01bd6254a6d87dc67f9627adece85c0b2ed754fa96"},
+    {file = "grpcio-1.67.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:8a23cbcc5bb11ea7dc6163078be36c065db68d915c24f5faa4f872c573bb400f"},
+    {file = "grpcio-1.67.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1a65b503d008f066e994f34f456e0647e5ceb34cfcec5ad180b1b44020ad4970"},
+    {file = "grpcio-1.67.1-cp311-cp311-win32.whl", hash = "sha256:e29ca27bec8e163dca0c98084040edec3bc49afd10f18b412f483cc68c712744"},
+    {file = "grpcio-1.67.1-cp311-cp311-win_amd64.whl", hash = "sha256:786a5b18544622bfb1e25cc08402bd44ea83edfb04b93798d85dca4d1a0b5be5"},
+    {file = "grpcio-1.67.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:267d1745894200e4c604958da5f856da6293f063327cb049a51fe67348e4f953"},
+    {file = "grpcio-1.67.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:85f69fdc1d28ce7cff8de3f9c67db2b0ca9ba4449644488c1e0303c146135ddb"},
+    {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:f26b0b547eb8d00e195274cdfc63ce64c8fc2d3e2d00b12bf468ece41a0423a0"},
+    {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4422581cdc628f77302270ff839a44f4c24fdc57887dc2a45b7e53d8fc2376af"},
+    {file = "grpcio-1.67.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1d7616d2ded471231c701489190379e0c311ee0a6c756f3c03e6a62b95a7146e"},
+    {file = "grpcio-1.67.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:8a00efecde9d6fcc3ab00c13f816313c040a28450e5e25739c24f432fc6d3c75"},
+    {file = "grpcio-1.67.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:699e964923b70f3101393710793289e42845791ea07565654ada0969522d0a38"},
+    {file = "grpcio-1.67.1-cp312-cp312-win32.whl", hash = "sha256:4e7b904484a634a0fff132958dabdb10d63e0927398273917da3ee103e8d1f78"},
+    {file = "grpcio-1.67.1-cp312-cp312-win_amd64.whl", hash = "sha256:5721e66a594a6c4204458004852719b38f3d5522082be9061d6510b455c90afc"},
+    {file = "grpcio-1.67.1-cp313-cp313-linux_armv7l.whl", hash = "sha256:aa0162e56fd10a5547fac8774c4899fc3e18c1aa4a4759d0ce2cd00d3696ea6b"},
+    {file = "grpcio-1.67.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:beee96c8c0b1a75d556fe57b92b58b4347c77a65781ee2ac749d550f2a365dc1"},
+    {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_aarch64.whl", hash = "sha256:a93deda571a1bf94ec1f6fcda2872dad3ae538700d94dc283c672a3b508ba3af"},
+    {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0e6f255980afef598a9e64a24efce87b625e3e3c80a45162d111a461a9f92955"},
+    {file = "grpcio-1.67.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e838cad2176ebd5d4a8bb03955138d6589ce9e2ce5d51c3ada34396dbd2dba8"},
+    {file = "grpcio-1.67.1-cp313-cp313-musllinux_1_1_i686.whl", hash = "sha256:a6703916c43b1d468d0756c8077b12017a9fcb6a1ef13faf49e67d20d7ebda62"},
+    {file = "grpcio-1.67.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:917e8d8994eed1d86b907ba2a61b9f0aef27a2155bca6cbb322430fc7135b7bb"},
+    {file = "grpcio-1.67.1-cp313-cp313-win32.whl", hash = "sha256:e279330bef1744040db8fc432becc8a727b84f456ab62b744d3fdb83f327e121"},
+    {file = "grpcio-1.67.1-cp313-cp313-win_amd64.whl", hash = "sha256:fa0c739ad8b1996bd24823950e3cb5152ae91fca1c09cc791190bf1627ffefba"},
+    {file = "grpcio-1.67.1-cp38-cp38-linux_armv7l.whl", hash = "sha256:178f5db771c4f9a9facb2ab37a434c46cb9be1a75e820f187ee3d1e7805c4f65"},
+    {file = "grpcio-1.67.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:0f3e49c738396e93b7ba9016e153eb09e0778e776df6090c1b8c91877cc1c426"},
+    {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:24e8a26dbfc5274d7474c27759b54486b8de23c709d76695237515bc8b5baeab"},
+    {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3b6c16489326d79ead41689c4b84bc40d522c9a7617219f4ad94bc7f448c5085"},
+    {file = "grpcio-1.67.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:60e6a4dcf5af7bbc36fd9f81c9f372e8ae580870a9e4b6eafe948cd334b81cf3"},
+    {file = "grpcio-1.67.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:95b5f2b857856ed78d72da93cd7d09b6db8ef30102e5e7fe0961fe4d9f7d48e8"},
+    {file = "grpcio-1.67.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b49359977c6ec9f5d0573ea4e0071ad278ef905aa74e420acc73fd28ce39e9ce"},
+    {file = "grpcio-1.67.1-cp38-cp38-win32.whl", hash = "sha256:f5b76ff64aaac53fede0cc93abf57894ab2a7362986ba22243d06218b93efe46"},
+    {file = "grpcio-1.67.1-cp38-cp38-win_amd64.whl", hash = "sha256:804c6457c3cd3ec04fe6006c739579b8d35c86ae3298ffca8de57b493524b771"},
+    {file = "grpcio-1.67.1-cp39-cp39-linux_armv7l.whl", hash = "sha256:a25bdea92b13ff4d7790962190bf6bf5c4639876e01c0f3dda70fc2769616335"},
+    {file = "grpcio-1.67.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:cdc491ae35a13535fd9196acb5afe1af37c8237df2e54427be3eecda3653127e"},
+    {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:85f862069b86a305497e74d0dc43c02de3d1d184fc2c180993aa8aa86fbd19b8"},
+    {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ec74ef02010186185de82cc594058a3ccd8d86821842bbac9873fd4a2cf8be8d"},
+    {file = "grpcio-1.67.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:01f616a964e540638af5130469451cf580ba8c7329f45ca998ab66e0c7dcdb04"},
+    {file = "grpcio-1.67.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:299b3d8c4f790c6bcca485f9963b4846dd92cf6f1b65d3697145d005c80f9fe8"},
+    {file = "grpcio-1.67.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:60336bff760fbb47d7e86165408126f1dded184448e9a4c892189eb7c9d3f90f"},
+    {file = "grpcio-1.67.1-cp39-cp39-win32.whl", hash = "sha256:5ed601c4c6008429e3d247ddb367fe8c7259c355757448d7c1ef7bd4a6739e8e"},
+    {file = "grpcio-1.67.1-cp39-cp39-win_amd64.whl", hash = "sha256:5db70d32d6703b89912af16d6d45d78406374a8b8ef0d28140351dd0ec610e98"},
+    {file = "grpcio-1.67.1.tar.gz", hash = "sha256:3dc2ed4cabea4dc14d5e708c2b426205956077cc5de419b4d4079315017e9732"},
 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.68.0)"]
+protobuf = ["grpcio-tools (>=1.67.1)"]
 
 [[package]]
 name = "h11"
@@ -1559,13 +1539,13 @@ pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_ve
 
 [[package]]
 name = "identify"
-version = "2.6.2"
+version = "2.6.3"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "identify-2.6.2-py2.py3-none-any.whl", hash = "sha256:c097384259f49e372f4ea00a19719d95ae27dd5ff0fd77ad630aa891306b82f3"},
-    {file = "identify-2.6.2.tar.gz", hash = "sha256:fab5c716c24d7a789775228823797296a2994b075fb6080ac83a102772a98cbd"},
+    {file = "identify-2.6.3-py2.py3-none-any.whl", hash = "sha256:9edba65473324c2ea9684b1f944fe3191db3345e50b6d04571d10ed164f8d7bd"},
+    {file = "identify-2.6.3.tar.gz", hash = "sha256:62f5dae9b5fef52c84cc188514e9ea4f3f636b1d8799ab5ebc475471f9e47a02"},
 ]
 
 [package.extras]
@@ -2168,13 +2148,13 @@ langchain-core = ">=0.2.38,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.145"
+version = "0.1.146"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.145-py3-none-any.whl", hash = "sha256:bd3001fc6738ad9061a2709d60f62a6bdf4892a17e63c7751f73a6f32a100729"},
-    {file = "langsmith-0.1.145.tar.gz", hash = "sha256:b6e53f7b1624846f03769a1fce673baf2a0a262b4f4129b1f6bd127a1f44f8fd"},
+    {file = "langsmith-0.1.146-py3-none-any.whl", hash = "sha256:9d062222f1a32c9b047dab0149b24958f988989cd8d4a5f9139ff959a51e59d8"},
+    {file = "langsmith-0.1.146.tar.gz", hash = "sha256:ead8b0b9d5b6cd3ac42937ec48bdf09d4afe7ca1bba22dc05eb65591a18106f8"},
 ]
 
 [package.dependencies]
@@ -2534,25 +2514,6 @@ files = [
     {file = "markupsafe-3.0.2.tar.gz", hash = "sha256:ee55d3edf80167e48ea11a923c7386f4669df67d7994554387f84e7d8b0a2bf0"},
 ]
 
-[[package]]
-name = "marshmallow"
-version = "3.23.1"
-description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "marshmallow-3.23.1-py3-none-any.whl", hash = "sha256:fece2eb2c941180ea1b7fcbd4a83c51bfdd50093fdd3ad2585ee5e1df2508491"},
-    {file = "marshmallow-3.23.1.tar.gz", hash = "sha256:3a8dfda6edd8dcdbf216c0ede1d1e78d230a6dc9c5a088f58c4083b974a0d468"},
-]
-
-[package.dependencies]
-packaging = ">=17.0"
-
-[package.extras]
-dev = ["marshmallow[tests]", "pre-commit (>=3.5,<5.0)", "tox"]
-docs = ["alabaster (==1.0.0)", "autodocsumm (==0.2.14)", "sphinx (==8.1.3)", "sphinx-issues (==5.0.0)", "sphinx-version-warning (==1.1.2)"]
-tests = ["pytest", "simplejson"]
-
 [[package]]
 name = "matplotlib-inline"
 version = "0.1.7"
@@ -2730,13 +2691,13 @@ pygments = ">2.12.0"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.45"
+version = "9.5.46"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.45-py3-none-any.whl", hash = "sha256:a9be237cfd0be14be75f40f1726d83aa3a81ce44808dc3594d47a7a592f44547"},
-    {file = "mkdocs_material-9.5.45.tar.gz", hash = "sha256:286489cf0beca4a129d91d59d6417419c63bceed1ce5cd0ec1fc7e1ebffb8189"},
+    {file = "mkdocs_material-9.5.46-py3-none-any.whl", hash = "sha256:98f0a2039c62e551a68aad0791a8d41324ff90c03a6e6cea381a384b84908b83"},
+    {file = "mkdocs_material-9.5.46.tar.gz", hash = "sha256:ae2043f4238e572f9a40e0b577f50400d6fc31e2fef8ea141800aebf3bd273d7"},
 ]
 
 [package.dependencies]
@@ -3303,6 +3264,18 @@ files = [
     {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-win_amd64.whl", hash = "sha256:2b964d60e8cf11b5e1073d179d85fa340c120e99b3067558f3cf98dd69d02906"},
 ]
 
+[[package]]
+name = "nvidia-cublas-cu12"
+version = "12.4.5.8"
+description = "CUBLAS native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0f8aa1706812e00b9f19dfe0cdb3999b092ccb8ca168c0db5b8ea712456fd9b3"},
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl", hash = "sha256:2fc8da60df463fdefa81e323eef2e36489e1c94335b5358bcb38360adf75ac9b"},
+    {file = "nvidia_cublas_cu12-12.4.5.8-py3-none-win_amd64.whl", hash = "sha256:5a796786da89203a0657eda402bcdcec6180254a8ac22d72213abc42069522dc"},
+]
+
 [[package]]
 name = "nvidia-cuda-cupti-cu12"
 version = "12.1.105"
@@ -3314,6 +3287,18 @@ files = [
     {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:bea8236d13a0ac7190bd2919c3e8e6ce1e402104276e6f9694479e48bb0eb2a4"},
 ]
 
+[[package]]
+name = "nvidia-cuda-cupti-cu12"
+version = "12.4.127"
+description = "CUDA profiling tools runtime libs."
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:79279b35cf6f91da114182a5ce1864997fd52294a87a16179ce275773799458a"},
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:9dec60f5ac126f7bb551c055072b69d85392b13311fcc1bcda2202d172df30fb"},
+    {file = "nvidia_cuda_cupti_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:5688d203301ab051449a2b1cb6690fbe90d2b372f411521c86018b950f3d7922"},
+]
+
 [[package]]
 name = "nvidia-cuda-nvrtc-cu12"
 version = "12.1.105"
@@ -3325,6 +3310,18 @@ files = [
     {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed"},
 ]
 
+[[package]]
+name = "nvidia-cuda-nvrtc-cu12"
+version = "12.4.127"
+description = "NVRTC native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0eedf14185e04b76aa05b1fea04133e59f465b6f960c0cbf4e37c3cb6b0ea198"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a178759ebb095827bd30ef56598ec182b85547f1508941a3d560eb7ea1fbf338"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:a961b2f1d5f17b14867c619ceb99ef6fcec12e46612711bcec78eb05068a60ec"},
+]
+
 [[package]]
 name = "nvidia-cuda-runtime-cu12"
 version = "12.1.105"
@@ -3336,6 +3333,18 @@ files = [
     {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:dfb46ef84d73fababab44cf03e3b83f80700d27ca300e537f85f636fac474344"},
 ]
 
+[[package]]
+name = "nvidia-cuda-runtime-cu12"
+version = "12.4.127"
+description = "CUDA Runtime native Libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:961fe0e2e716a2a1d967aab7caee97512f71767f852f67432d572e36cb3a11f3"},
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:64403288fa2136ee8e467cdc9c9427e0434110899d07c779f25b5c068934faa5"},
+    {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:09c2e35f48359752dfa822c09918211844a3d93c100a715d79b59591130c5e1e"},
+]
+
 [[package]]
 name = "nvidia-cudnn-cu12"
 version = "8.9.2.26"
@@ -3374,6 +3383,21 @@ files = [
     {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-win_amd64.whl", hash = "sha256:d9ac353f78ff89951da4af698f80870b1534ed69993f10a4cf1d96f21357e253"},
 ]
 
+[[package]]
+name = "nvidia-cufft-cu12"
+version = "11.2.1.3"
+description = "CUFFT native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5dad8008fc7f92f5ddfa2101430917ce2ffacd86824914c82e28990ad7f00399"},
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f083fc24912aa410be21fa16d157fed2055dab1cc4b6934a0e03cba69eb242b9"},
+    {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-win_amd64.whl", hash = "sha256:d802f4954291101186078ccbe22fc285a902136f974d369540fd4a5333d1440b"},
+]
+
+[package.dependencies]
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-curand-cu12"
 version = "10.3.2.106"
@@ -3385,6 +3409,18 @@ files = [
     {file = "nvidia_curand_cu12-10.3.2.106-py3-none-win_amd64.whl", hash = "sha256:75b6b0c574c0037839121317e17fd01f8a69fd2ef8e25853d826fec30bdba74a"},
 ]
 
+[[package]]
+name = "nvidia-curand-cu12"
+version = "10.3.5.147"
+description = "CURAND native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1f173f09e3e3c76ab084aba0de819c49e56614feae5c12f69883f4ae9bb5fad9"},
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a88f583d4e0bb643c49743469964103aa59f7f708d862c3ddb0fc07f851e3b8b"},
+    {file = "nvidia_curand_cu12-10.3.5.147-py3-none-win_amd64.whl", hash = "sha256:f307cc191f96efe9e8f05a87096abc20d08845a841889ef78cb06924437f6771"},
+]
+
 [[package]]
 name = "nvidia-cusolver-cu12"
 version = "11.4.5.107"
@@ -3401,6 +3437,23 @@ nvidia-cublas-cu12 = "*"
 nvidia-cusparse-cu12 = "*"
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cusolver-cu12"
+version = "11.6.1.9"
+description = "CUDA solver native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_aarch64.whl", hash = "sha256:d338f155f174f90724bbde3758b7ac375a70ce8e706d70b018dd3375545fc84e"},
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl", hash = "sha256:19e33fa442bcfd085b3086c4ebf7e8debc07cfe01e11513cc6d332fd918ac260"},
+    {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-win_amd64.whl", hash = "sha256:e77314c9d7b694fcebc84f58989f3aa4fb4cb442f12ca1a9bde50f5e8f6d1b9c"},
+]
+
+[package.dependencies]
+nvidia-cublas-cu12 = "*"
+nvidia-cusparse-cu12 = "*"
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-cusparse-cu12"
 version = "12.1.0.106"
@@ -3415,6 +3468,21 @@ files = [
 [package.dependencies]
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cusparse-cu12"
+version = "12.3.1.170"
+description = "CUSPARSE native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_aarch64.whl", hash = "sha256:9d32f62896231ebe0480efd8a7f702e143c98cfaa0e8a76df3386c1ba2b54df3"},
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ea4f11a2904e2a8dc4b1833cc1b5181cde564edd0d5cd33e3c168eff2d1863f1"},
+    {file = "nvidia_cusparse_cu12-12.3.1.170-py3-none-win_amd64.whl", hash = "sha256:9bc90fb087bc7b4c15641521f31c0371e9a612fc2ba12c338d3ae032e6b6797f"},
+]
+
+[package.dependencies]
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-nccl-cu12"
 version = "2.19.3"
@@ -3427,13 +3495,24 @@ files = [
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.20.5"
+version = "2.21.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01"},
-    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
+    {file = "nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:8579076d30a8c24988834445f8d633c697d42397e92ffc3f63fa26766d25e0a0"},
+]
+
+[[package]]
+name = "nvidia-nvjitlink-cu12"
+version = "12.4.127"
+description = "Nvidia JIT LTO Library"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:4abe7fef64914ccfa909bc2ba39739670ecc9e820c83ccc7a6ed414122599b83"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:06b3b9b25bf3f8af351d664978ca26a16d2c5127dbd53c0497e28d1fb9611d57"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:fd9020c501d27d135f983c6d3e244b197a7ccad769e34df53a42e276b0e25fa1"},
 ]
 
 [[package]]
@@ -3459,6 +3538,18 @@ files = [
     {file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
 ]
 
+[[package]]
+name = "nvidia-nvtx-cu12"
+version = "12.4.127"
+description = "NVIDIA Tools Extension"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7959ad635db13edf4fc65c06a6e9f9e55fc2f92596db928d169c0bb031e88ef3"},
+    {file = "nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:781e950d9b9f60d8241ccea575b32f5105a5baf4c2351cab5256a24869f12a1a"},
+    {file = "nvidia_nvtx_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:641dccaaa1139f3ffb0d3164b4b84f9d253397e38246a4f2f36728b48566d485"},
+]
+
 [[package]]
 name = "ocrmac"
 version = "1.0.0"
@@ -3576,9 +3667,9 @@ numpy = [
     {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
-    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
 ]
 
 [[package]]
@@ -3602,9 +3693,9 @@ numpy = [
     {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
-    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
 ]
 
 [[package]]
@@ -4586,21 +4677,21 @@ extra = ["pygments (>=2.12)"]
 
 [[package]]
 name = "pymilvus"
-version = "2.4.9"
+version = "2.5.0"
 description = "Python Sdk for Milvus"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pymilvus-2.4.9-py3-none-any.whl", hash = "sha256:45313607d2c164064bdc44e0f933cb6d6afa92e9efcc7f357c5240c57db58fbe"},
-    {file = "pymilvus-2.4.9.tar.gz", hash = "sha256:0937663700007c23a84cfc0656160b301f6ff9247aaec4c96d599a6b43572136"},
+    {file = "pymilvus-2.5.0-py3-none-any.whl", hash = "sha256:a0e8653d8fe78019abfda79b3404ef7423f312501e8cbd7dc728051ce8732652"},
+    {file = "pymilvus-2.5.0.tar.gz", hash = "sha256:4da14a3bd957a4921166f9355fd1f1ac5c5e4e80b46f12f64d9c9a6dcb8cb395"},
 ]
 
 [package.dependencies]
-environs = "<=9.5.0"
-grpcio = ">=1.49.1"
-milvus-lite = {version = ">=2.4.0,<2.5.0", markers = "sys_platform != \"win32\""}
+grpcio = ">=1.49.1,<=1.67.1"
+milvus-lite = {version = ">=2.4.0", markers = "sys_platform != \"win32\""}
 pandas = ">=1.2.4"
 protobuf = ">=3.20.0"
+python-dotenv = ">=1.0.1,<2.0.0"
 setuptools = ">69"
 ujson = ">=2.0.0"
 
@@ -6103,6 +6194,23 @@ pure-eval = "*"
 [package.extras]
 tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
+[[package]]
+name = "sympy"
+version = "1.13.1"
+description = "Computer algebra system (CAS) in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "sympy-1.13.1-py3-none-any.whl", hash = "sha256:db36cdc64bf61b9b24578b6f7bab1ecdd2452cf008f34faa33776680c26d66f8"},
+    {file = "sympy-1.13.1.tar.gz", hash = "sha256:9cebf7e04ff162015ce31c9c6c9144daa34a93bd082f54fd8f12deca4f47515f"},
+]
+
+[package.dependencies]
+mpmath = ">=1.1.0,<1.4"
+
+[package.extras]
+dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
+
 [[package]]
 name = "sympy"
 version = "1.13.3"
@@ -6248,123 +6356,26 @@ files = [
 
 [[package]]
 name = "tokenizers"
-version = "0.20.3"
+version = "0.20.4"
 description = ""
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tokenizers-0.20.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:31ccab28dbb1a9fe539787210b0026e22debeab1662970f61c2d921f7557f7e4"},
-    {file = "tokenizers-0.20.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c6361191f762bda98c773da418cf511cbaa0cb8d0a1196f16f8c0119bde68ff8"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f128d5da1202b78fa0a10d8d938610472487da01b57098d48f7e944384362514"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:79c4121a2e9433ad7ef0769b9ca1f7dd7fa4c0cd501763d0a030afcbc6384481"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b7850fde24197fe5cd6556e2fdba53a6d3bae67c531ea33a3d7c420b90904141"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b357970c095dc134978a68c67d845a1e3803ab7c4fbb39195bde914e7e13cf8b"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a333d878c4970b72d6c07848b90c05f6b045cf9273fc2bc04a27211721ad6118"},
-    {file = "tokenizers-0.20.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1fd9fee817f655a8f50049f685e224828abfadd436b8ff67979fc1d054b435f1"},
-    {file = "tokenizers-0.20.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9e7816808b402129393a435ea2a509679b41246175d6e5e9f25b8692bfaa272b"},
-    {file = "tokenizers-0.20.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ba96367db9d8a730d3a1d5996b4b7babb846c3994b8ef14008cd8660f55db59d"},
-    {file = "tokenizers-0.20.3-cp310-none-win32.whl", hash = "sha256:ee31ba9d7df6a98619426283e80c6359f167e2e9882d9ce1b0254937dbd32f3f"},
-    {file = "tokenizers-0.20.3-cp310-none-win_amd64.whl", hash = "sha256:a845c08fdad554fe0871d1255df85772f91236e5fd6b9287ef8b64f5807dbd0c"},
-    {file = "tokenizers-0.20.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:585b51e06ca1f4839ce7759941e66766d7b060dccfdc57c4ca1e5b9a33013a90"},
-    {file = "tokenizers-0.20.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:61cbf11954f3b481d08723ebd048ba4b11e582986f9be74d2c3bdd9293a4538d"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ef820880d5e4e8484e2fa54ff8d297bb32519eaa7815694dc835ace9130a3eea"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:67ef4dcb8841a4988cd00dd288fb95dfc8e22ed021f01f37348fd51c2b055ba9"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff1ef8bd47a02b0dc191688ccb4da53600df5d4c9a05a4b68e1e3de4823e78eb"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:444d188186eab3148baf0615b522461b41b1f0cd58cd57b862ec94b6ac9780f1"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:37c04c032c1442740b2c2d925f1857885c07619224a533123ac7ea71ca5713da"},
-    {file = "tokenizers-0.20.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:453c7769d22231960ee0e883d1005c93c68015025a5e4ae56275406d94a3c907"},
-    {file = "tokenizers-0.20.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4bb31f7b2847e439766aaa9cc7bccf7ac7088052deccdb2275c952d96f691c6a"},
-    {file = "tokenizers-0.20.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:843729bf0f991b29655a069a2ff58a4c24375a553c70955e15e37a90dd4e045c"},
-    {file = "tokenizers-0.20.3-cp311-none-win32.whl", hash = "sha256:efcce3a927b1e20ca694ba13f7a68c59b0bd859ef71e441db68ee42cf20c2442"},
-    {file = "tokenizers-0.20.3-cp311-none-win_amd64.whl", hash = "sha256:88301aa0801f225725b6df5dea3d77c80365ff2362ca7e252583f2b4809c4cc0"},
-    {file = "tokenizers-0.20.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:49d12a32e190fad0e79e5bdb788d05da2f20d8e006b13a70859ac47fecf6ab2f"},
-    {file = "tokenizers-0.20.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:282848cacfb9c06d5e51489f38ec5aa0b3cd1e247a023061945f71f41d949d73"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abe4e08c7d0cd6154c795deb5bf81d2122f36daf075e0c12a8b050d824ef0a64"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ca94fc1b73b3883c98f0c88c77700b13d55b49f1071dfd57df2b06f3ff7afd64"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ef279c7e239f95c8bdd6ff319d9870f30f0d24915b04895f55b1adcf96d6c60d"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:16384073973f6ccbde9852157a4fdfe632bb65208139c9d0c0bd0176a71fd67f"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:312d522caeb8a1a42ebdec87118d99b22667782b67898a76c963c058a7e41d4f"},
-    {file = "tokenizers-0.20.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2b7cb962564785a83dafbba0144ecb7f579f1d57d8c406cdaa7f32fe32f18ad"},
-    {file = "tokenizers-0.20.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:124c5882ebb88dadae1fc788a582299fcd3a8bd84fc3e260b9918cf28b8751f5"},
-    {file = "tokenizers-0.20.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:2b6e54e71f84c4202111a489879005cb14b92616a87417f6c102c833af961ea2"},
-    {file = "tokenizers-0.20.3-cp312-none-win32.whl", hash = "sha256:83d9bfbe9af86f2d9df4833c22e94d94750f1d0cd9bfb22a7bb90a86f61cdb1c"},
-    {file = "tokenizers-0.20.3-cp312-none-win_amd64.whl", hash = "sha256:44def74cee574d609a36e17c8914311d1b5dbcfe37c55fd29369d42591b91cf2"},
-    {file = "tokenizers-0.20.3-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:e0b630e0b536ef0e3c8b42c685c1bc93bd19e98c0f1543db52911f8ede42cf84"},
-    {file = "tokenizers-0.20.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a02d160d2b19bcbfdf28bd9a4bf11be4cb97d0499c000d95d4c4b1a4312740b6"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e3d80d89b068bc30034034b5319218c7c0a91b00af19679833f55f3becb6945"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:174a54910bed1b089226512b4458ea60d6d6fd93060254734d3bc3540953c51c"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:098b8a632b8656aa5802c46689462c5c48f02510f24029d71c208ec2c822e771"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:78c8c143e3ae41e718588281eb3e212c2b31623c9d6d40410ec464d7d6221fb5"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b26b0aadb18cd8701077362ba359a06683662d5cafe3e8e8aba10eb05c037f1"},
-    {file = "tokenizers-0.20.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:07d7851a72717321022f3774e84aa9d595a041d643fafa2e87fbc9b18711dac0"},
-    {file = "tokenizers-0.20.3-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:bd44e48a430ada902c6266a8245f5036c4fe744fcb51f699999fbe82aa438797"},
-    {file = "tokenizers-0.20.3-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:a4c186bb006ccbe1f5cc4e0380d1ce7806f5955c244074fd96abc55e27b77f01"},
-    {file = "tokenizers-0.20.3-cp313-none-win32.whl", hash = "sha256:6e19e0f1d854d6ab7ea0c743d06e764d1d9a546932be0a67f33087645f00fe13"},
-    {file = "tokenizers-0.20.3-cp313-none-win_amd64.whl", hash = "sha256:d50ede425c7e60966a9680d41b58b3a0950afa1bb570488e2972fa61662c4273"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-macosx_10_12_x86_64.whl", hash = "sha256:9adda1ff5fb9dcdf899ceca672a4e2ce9e797adb512a6467305ca3d8bfcfbdd0"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-macosx_11_0_arm64.whl", hash = "sha256:6dde2cae6004ba7a3badff4a11911cae03ebf23e97eebfc0e71fef2530e5074f"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c4a7fd678b35614fca708579eb95b7587a5e8a6d328171bd2488fd9f27d82be4"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:1b80e3c7283a01a356bd2210f53d1a4a5d32b269c2024389ed0173137708d50e"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a8cc0e8176b762973758a77f0d9c4467d310e33165fb74173418ca3734944da4"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d5634b2e2f5f3d2b4439d2d74066e22eb4b1f04f3fea05cb2a3c12d89b5a3bcd"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b4ba635165bc1ea46f2da8e5d80b5f70f6ec42161e38d96dbef33bb39df73964"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18e4c7c64172e7789bd8b07aa3087ea87c4c4de7e90937a2aa036b5d92332536"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:1f74909ef7675c26d4095a817ec3393d67f3158ca4836c233212e5613ef640c4"},
-    {file = "tokenizers-0.20.3-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:0e9b81321a1e05b16487d312b4264984513f8b4a7556229cafac6e88c2036b09"},
-    {file = "tokenizers-0.20.3-cp37-none-win32.whl", hash = "sha256:ab48184cd58b4a03022a2ec75b54c9f600ffea9a733612c02325ed636f353729"},
-    {file = "tokenizers-0.20.3-cp37-none-win_amd64.whl", hash = "sha256:60ac483cebee1c12c71878523e768df02fa17e4c54412966cb3ac862c91b36c1"},
-    {file = "tokenizers-0.20.3-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:3229ef103c89583d10b9378afa5d601b91e6337530a0988e17ca8d635329a996"},
-    {file = "tokenizers-0.20.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:6ac52cc24bad3de865c7e65b1c4e7b70d00938a8ae09a92a453b8f676e714ad5"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:04627b7b502fa6a2a005e1bd446fa4247d89abcb1afaa1b81eb90e21aba9a60f"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c27ceb887f0e81a3c377eb4605dca7a95a81262761c0fba308d627b2abb98f2b"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:65ab780194da4e1fcf5670523a2f377c4838ebf5249efe41fa1eddd2a84fb49d"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:98d343134f47159e81f7f242264b0eb222e6b802f37173c8d7d7b64d5c9d1388"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f2475bb004ab2009d29aff13b5047bfdb3d4b474f0aa9d4faa13a7f34dbbbb43"},
-    {file = "tokenizers-0.20.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7b6583a65c01db1197c1eb36857ceba8ec329d53afadd268b42a6b04f4965724"},
-    {file = "tokenizers-0.20.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:62d00ba208358c037eeab7bfc00a905adc67b2d31b68ab40ed09d75881e114ea"},
-    {file = "tokenizers-0.20.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:0fc7a39e5bedc817bda395a798dfe2d9c5f7c71153c90d381b5135a0328d9520"},
-    {file = "tokenizers-0.20.3-cp38-none-win32.whl", hash = "sha256:84d40ee0f8550d64d3ea92dd7d24a8557a9172165bdb986c9fb2503b4fe4e3b6"},
-    {file = "tokenizers-0.20.3-cp38-none-win_amd64.whl", hash = "sha256:205a45246ed7f1718cf3785cff88450ba603352412aaf220ace026384aa3f1c0"},
-    {file = "tokenizers-0.20.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:93e37f0269a11dc3b1a953f1fca9707f0929ebf8b4063c591c71a0664219988e"},
-    {file = "tokenizers-0.20.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f4cb0c614b0135e781de96c2af87e73da0389ac1458e2a97562ed26e29490d8d"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7eb2fb1c432f5746b22f8a7f09fc18c4156cb0031c77f53cb19379d82d43297a"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bfa8d029bb156181b006643309d6b673615a24e4ed24cf03aa191d599b996f51"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f90549622de3bf476ad9f1dd6f3f952ec3ed6ab8615ae88ef060d0c5bfad55d"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a1d469c74eebf5c43fd61cd9b030e271d17198edd7bd45392e03a3c091d7d6d4"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bee8f53b2594749f4460d53253bae55d718f04e9b633efa0f5df8938bd98e4f0"},
-    {file = "tokenizers-0.20.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:938441babf3e5720e4459e306ef2809fb267680df9d1ff2873458b22aef60248"},
-    {file = "tokenizers-0.20.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:7310ab23d7b0caebecc0e8be11a1146f320f5f07284000f6ea54793e83de1b75"},
-    {file = "tokenizers-0.20.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:16121eb030a2b13094cfec936b0c12e8b4063c5f839591ea7d0212336d8f9921"},
-    {file = "tokenizers-0.20.3-cp39-none-win32.whl", hash = "sha256:401cc21ef642ee235985d747f65e18f639464d377c70836c9003df208d582064"},
-    {file = "tokenizers-0.20.3-cp39-none-win_amd64.whl", hash = "sha256:7498f3ea7746133335a6adb67a77cf77227a8b82c8483f644a2e5f86fea42b8d"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:e919f2e3e68bb51dc31de4fcbbeff3bdf9c1cad489044c75e2b982a91059bd3c"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:b8e9608f2773996cc272156e305bd79066163a66b0390fe21750aff62df1ac07"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:39270a7050deaf50f7caff4c532c01b3c48f6608d42b3eacdebdc6795478c8df"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e005466632b1c5d2d2120f6de8aa768cc9d36cd1ab7d51d0c27a114c91a1e6ee"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a07962340b36189b6c8feda552ea1bfeee6cf067ff922a1d7760662c2ee229e5"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:55046ad3dd5f2b3c67501fcc8c9cbe3e901d8355f08a3b745e9b57894855f85b"},
-    {file = "tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:efcf0eb939988b627558aaf2b9dc3e56d759cad2e0cfa04fcab378e4b48fc4fd"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f3558a7ae6a6d38a77dfce12172a1e2e1bf3e8871e744a1861cd7591ea9ebe24"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d53029fe44bc70c3ff14ef512460a0cf583495a0f8e2f4b70e26eb9438e38a9"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:57a2a56397b2bec5a629b516b23f0f8a3e4f978c7488d4a299980f8375954b85"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1e5bfaae740ef9ece000f8a07e78ac0e2b085c5ce9648f8593ddf0243c9f76d"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:fbaf3ea28fedfb2283da60e710aff25492e795a7397cad8a50f1e079b65a5a70"},
-    {file = "tokenizers-0.20.3-pp37-pypy37_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c47c037116310dc976eb96b008e41b9cfaba002ed8005848d4d632ee0b7ba9ae"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:c31751f0721f58f5e19bb27c1acc259aeff860d8629c4e1a900b26a1979ada8e"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:c697cbd3be7a79ea250ea5f380d6f12e534c543cfb137d5c734966b3ee4f34cc"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b48971b88ef9130bf35b41b35fd857c3c4dae4a9cd7990ebc7fc03e59cc92438"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4e615de179bbe060ab33773f0d98a8a8572b5883dd7dac66c1de8c056c7e748c"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da1ec842035ed9999c62e45fbe0ff14b7e8a7e02bb97688cc6313cf65e5cd755"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:6ee4954c1dd23aadc27958dad759006e71659d497dcb0ef0c7c87ea992c16ebd"},
-    {file = "tokenizers-0.20.3-pp38-pypy38_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:3eda46ca402751ec82553a321bf35a617b76bbed7586e768c02ccacbdda94d6d"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:de082392a85eb0055cc055c535bff2f0cc15d7a000bdc36fbf601a0f3cf8507a"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:c3db46cc0647bfd88263afdb739b92017a02a87ee30945cb3e86c7e25c7c9917"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a292392f24ab9abac5cfa8197e5a6208f2e43723420217e1ceba0b4ec77816ac"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8dcd91f4e60f62b20d83a87a84fe062035a1e3ff49a8c2bbdeb2d441c8e311f4"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:900991a2b8ee35961b1095db7e265342e0e42a84c1a594823d5ee9f8fb791958"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:5a8d8261ca2133d4f98aa9627c748189502b3787537ba3d7e2beb4f7cfc5d627"},
-    {file = "tokenizers-0.20.3-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:c4fd4d71e6deb6ddf99d8d0eab87d1d16f635898906e631914a9bae8ae9f2cfb"},
-    {file = "tokenizers-0.20.3.tar.gz", hash = "sha256:2278b34c5d0dd78e087e1ca7f9b1dcbf129d80211afa645f214bd6e051037539"},
+    {file = "tokenizers-0.20.4-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:25f59ebc5b79e7bbafe86bfec62696468016627157d8a9ceba5092486796a156"},
+    {file = "tokenizers-0.20.4-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:f41df992797ad0ff9472e8a2c7a3ef7178667935d984639b73da7d19b33ea4e2"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7786004e180fab72e6e873e982ccd18b3cfa31521d397b6c024cc19175abf91b"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:075635cd7e6936cc4b3a13901c1a05690d5b533ce3d0f035dee21117dd4f04ae"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aa392bae7f0a36e4c97ad43100390ad84f2a1bfff6742604774210f7d7a4fa13"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eee647ccba9cbd36b5ec4e8e73d25dbd586ec06de7a43ff83a3dad9fec466a29"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:735ffc9bba65d20f8ab5f82dfbab262bb066afc7dee3684c5e5435e7a5da445d"},
+    {file = "tokenizers-0.20.4-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:05c2bab579c1f31292b48bb79b6334b5346c1ec87dac81089e6098b8a20b2fd4"},
+    {file = "tokenizers-0.20.4-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:3e960ad5c467a95e5665e518151ed9024e7aa111d2c54ff1938162cc7c2b8959"},
+    {file = "tokenizers-0.20.4-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:e59a405459ed31b73426b364752c2e7c73f4a94210a63fd7acd161a774af7bd2"},
+    {file = "tokenizers-0.20.4-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:84bf8b4a7bbf1c6bb78775ae309a5c69d08dadf7b88125d6d19ccb4738a87350"},
+    {file = "tokenizers-0.20.4-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a6d392a20ca70692aaba8a636677b57f6c67655879773ba2b6be8cb4a19ce6b8"},
+    {file = "tokenizers-0.20.4-cp39-abi3-win32.whl", hash = "sha256:60ea37c885a9bb8efa53b7542ea83561cd00eb3ffb47a77f5ae622d9f7f66ffe"},
+    {file = "tokenizers-0.20.4-cp39-abi3-win_amd64.whl", hash = "sha256:6cba92b87969ddf5a7e2f2293577c30129d8c22c6f68e8c626d3e76b8d52412c"},
+    {file = "tokenizers-0.20.4.tar.gz", hash = "sha256:db50ac15e92981227f499268541306824f49e97dbeec05d118ebdc7c2d22322c"},
 ]
 
 [package.dependencies]
@@ -6457,31 +6468,28 @@ optree = ["optree (>=0.9.1)"]
 
 [[package]]
 name = "torch"
-version = "2.4.1"
+version = "2.5.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "torch-2.4.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:362f82e23a4cd46341daabb76fba08f04cd646df9bfaf5da50af97cb60ca4971"},
-    {file = "torch-2.4.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:e8ac1985c3ff0f60d85b991954cfc2cc25f79c84545aead422763148ed2759e3"},
-    {file = "torch-2.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:91e326e2ccfb1496e3bee58f70ef605aeb27bd26be07ba64f37dcaac3d070ada"},
-    {file = "torch-2.4.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:d36a8ef100f5bff3e9c3cea934b9e0d7ea277cb8210c7152d34a9a6c5830eadd"},
-    {file = "torch-2.4.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:0b5f88afdfa05a335d80351e3cea57d38e578c8689f751d35e0ff36bce872113"},
-    {file = "torch-2.4.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:ef503165f2341942bfdf2bd520152f19540d0c0e34961232f134dc59ad435be8"},
-    {file = "torch-2.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:092e7c2280c860eff762ac08c4bdcd53d701677851670695e0c22d6d345b269c"},
-    {file = "torch-2.4.1-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:ddddbd8b066e743934a4200b3d54267a46db02106876d21cf31f7da7a96f98ea"},
-    {file = "torch-2.4.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:fdc4fe11db3eb93c1115d3e973a27ac7c1a8318af8934ffa36b0370efe28e042"},
-    {file = "torch-2.4.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:18835374f599207a9e82c262153c20ddf42ea49bc76b6eadad8e5f49729f6e4d"},
-    {file = "torch-2.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:ebea70ff30544fc021d441ce6b219a88b67524f01170b1c538d7d3ebb5e7f56c"},
-    {file = "torch-2.4.1-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:72b484d5b6cec1a735bf3fa5a1c4883d01748698c5e9cfdbeb4ffab7c7987e0d"},
-    {file = "torch-2.4.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:c99e1db4bf0c5347107845d715b4aa1097e601bdc36343d758963055e9599d93"},
-    {file = "torch-2.4.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:b57f07e92858db78c5b72857b4f0b33a65b00dc5d68e7948a8494b0314efb880"},
-    {file = "torch-2.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:f18197f3f7c15cde2115892b64f17c80dbf01ed72b008020e7da339902742cf6"},
-    {file = "torch-2.4.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:5fc1d4d7ed265ef853579caf272686d1ed87cebdcd04f2a498f800ffc53dab71"},
-    {file = "torch-2.4.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:40f6d3fe3bae74efcf08cb7f8295eaddd8a838ce89e9d26929d4edd6d5e4329d"},
-    {file = "torch-2.4.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:c9299c16c9743001ecef515536ac45900247f4338ecdf70746f2461f9e4831db"},
-    {file = "torch-2.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:6bce130f2cd2d52ba4e2c6ada461808de7e5eccbac692525337cfb4c19421846"},
-    {file = "torch-2.4.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:a38de2803ee6050309aac032676536c3d3b6a9804248537e38e098d0e14817ec"},
+    {file = "torch-2.5.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:71328e1bbe39d213b8721678f9dcac30dfc452a46d586f1d514a6aa0a99d4744"},
+    {file = "torch-2.5.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:34bfa1a852e5714cbfa17f27c49d8ce35e1b7af5608c4bc6e81392c352dbc601"},
+    {file = "torch-2.5.1-cp310-cp310-win_amd64.whl", hash = "sha256:32a037bd98a241df6c93e4c789b683335da76a2ac142c0973675b715102dc5fa"},
+    {file = "torch-2.5.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:23d062bf70776a3d04dbe74db950db2a5245e1ba4f27208a87f0d743b0d06e86"},
+    {file = "torch-2.5.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:de5b7d6740c4b636ef4db92be922f0edc425b65ed78c5076c43c42d362a45457"},
+    {file = "torch-2.5.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:340ce0432cad0d37f5a31be666896e16788f1adf8ad7be481196b503dad675b9"},
+    {file = "torch-2.5.1-cp311-cp311-win_amd64.whl", hash = "sha256:603c52d2fe06433c18b747d25f5c333f9c1d58615620578c326d66f258686f9a"},
+    {file = "torch-2.5.1-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:31f8c39660962f9ae4eeec995e3049b5492eb7360dd4f07377658ef4d728fa4c"},
+    {file = "torch-2.5.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:ed231a4b3a5952177fafb661213d690a72caaad97d5824dd4fc17ab9e15cec03"},
+    {file = "torch-2.5.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:3f4b7f10a247e0dcd7ea97dc2d3bfbfc90302ed36d7f3952b0008d0df264e697"},
+    {file = "torch-2.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:73e58e78f7d220917c5dbfad1a40e09df9929d3b95d25e57d9f8558f84c9a11c"},
+    {file = "torch-2.5.1-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:8c712df61101964eb11910a846514011f0b6f5920c55dbf567bff8a34163d5b1"},
+    {file = "torch-2.5.1-cp313-cp313-manylinux1_x86_64.whl", hash = "sha256:9b61edf3b4f6e3b0e0adda8b3960266b9009d02b37555971f4d1c8f7a05afed7"},
+    {file = "torch-2.5.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:1f3b7fb3cf7ab97fae52161423f81be8c6b8afac8d9760823fd623994581e1a3"},
+    {file = "torch-2.5.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:7974e3dce28b5a21fb554b73e1bc9072c25dde873fa00d54280861e7a009d7dc"},
+    {file = "torch-2.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:46c817d3ea33696ad3b9df5e774dba2257e9a4cd3c4a3afbf92f6bb13ac5ce2d"},
+    {file = "torch-2.5.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:8046768b7f6d35b85d101b4b38cba8aa2f3cd51952bc4c06a49580f2ce682291"},
 ]
 
 [package.dependencies]
@@ -6489,25 +6497,26 @@ filelock = "*"
 fsspec = "*"
 jinja2 = "*"
 networkx = "*"
-nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cublas-cu12 = {version = "12.4.5.8", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-cupti-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-nvrtc-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-runtime-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-setuptools = "*"
-sympy = "*"
-triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
+nvidia-cufft-cu12 = {version = "11.2.1.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-curand-cu12 = {version = "10.3.5.147", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusolver-cu12 = {version = "11.6.1.9", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusparse-cu12 = {version = "12.3.1.170", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.21.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvjitlink-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvtx-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+setuptools = {version = "*", markers = "python_version >= \"3.12\""}
+sympy = {version = "1.13.1", markers = "python_version >= \"3.9\""}
+triton = {version = "3.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.11.0)"]
+optree = ["optree (>=0.12.0)"]
 
 [[package]]
 name = "torchvision"
@@ -6553,37 +6562,33 @@ scipy = ["scipy"]
 
 [[package]]
 name = "torchvision"
-version = "0.19.1"
+version = "0.20.1"
 description = "image and video datasets and models for torch deep learning"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "torchvision-0.19.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:54e8513099e6f586356c70f809d34f391af71ad182fe071cc328a28af2c40608"},
-    {file = "torchvision-0.19.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:20a1f5e02bfdad7714e55fa3fa698347c11d829fa65e11e5a84df07d93350eed"},
-    {file = "torchvision-0.19.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:7b063116164be52fc6deb4762de7f8c90bfa3a65f8d5caf17f8e2d5aadc75a04"},
-    {file = "torchvision-0.19.1-cp310-cp310-win_amd64.whl", hash = "sha256:f40b6acabfa886da1bc3768f47679c61feee6bde90deb979d9f300df8c8a0145"},
-    {file = "torchvision-0.19.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:40514282b4896d62765b8e26d7091c32e17c35817d00ec4be2362ea3ba3d1787"},
-    {file = "torchvision-0.19.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:5a91be061ae5d6d5b95e833b93e57ca4d3c56c5a57444dd15da2e3e7fba96050"},
-    {file = "torchvision-0.19.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:d71a6a6fe3a5281ca3487d4c56ad4aad20ff70f82f1d7c79bcb6e7b0c2af00c8"},
-    {file = "torchvision-0.19.1-cp311-cp311-win_amd64.whl", hash = "sha256:70dea324174f5e9981b68e4b7cd524512c106ba64aedef560a86a0bbf2fbf62c"},
-    {file = "torchvision-0.19.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:27ece277ff0f6cdc7fed0627279c632dcb2e58187da771eca24b0fbcf3f8590d"},
-    {file = "torchvision-0.19.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:c659ff92a61f188a1a7baef2850f3c0b6c85685447453c03d0e645ba8f1dcc1c"},
-    {file = "torchvision-0.19.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:c07bf43c2a145d792ecd9d0503d6c73577147ece508d45600d8aac77e4cdfcf9"},
-    {file = "torchvision-0.19.1-cp312-cp312-win_amd64.whl", hash = "sha256:b4283d283675556bb0eae31d29996f53861b17cbdcdf3509e6bc050414ac9289"},
-    {file = "torchvision-0.19.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4c4e4f5b24ea6b087b02ed492ab1e21bba3352c4577e2def14248cfc60732338"},
-    {file = "torchvision-0.19.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:9281d63ead929bb19143731154cd1d8bf0b5e9873dff8578a40e90a6bec3c6fa"},
-    {file = "torchvision-0.19.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:4d10bc9083c4d5fadd7edd7b729700a7be48dab4f62278df3bc73fa48e48a155"},
-    {file = "torchvision-0.19.1-cp38-cp38-win_amd64.whl", hash = "sha256:ccf085ef1824fb9e16f1901285bf89c298c62dfd93267a39e8ee42c71255242f"},
-    {file = "torchvision-0.19.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:731f434d91586769e255b5d70ed1a4457e0a1394a95f4aacf0e1e7e21f80c098"},
-    {file = "torchvision-0.19.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:febe4f14d4afcb47cc861d8be7760ab6a123cd0817f97faf5771488cb6aa90f4"},
-    {file = "torchvision-0.19.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:e328309b8670a2e889b2fe76a1c2744a099c11c984da9a822357bd9debd699a5"},
-    {file = "torchvision-0.19.1-cp39-cp39-win_amd64.whl", hash = "sha256:6616f12e00a22e7f3fedbd0fccb0804c05e8fe22871668f10eae65cf3f283614"},
+    {file = "torchvision-0.20.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4878fefb96ef293d06c27210918adc83c399d9faaf34cda5a63e129f772328f1"},
+    {file = "torchvision-0.20.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:8ffbdf8bf5b30eade22d459f5a313329eeadb20dc75efa142987b53c007098c3"},
+    {file = "torchvision-0.20.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:75f8a4d51a593c4bab6c9bf7d75bdd88691b00a53b07656678bc55a3a753dd73"},
+    {file = "torchvision-0.20.1-cp310-cp310-win_amd64.whl", hash = "sha256:22c2fa44e20eb404b85e42b22b453863a14b0927d25e550fd4f84eea97fa5b39"},
+    {file = "torchvision-0.20.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:344b339e15e6bbb59ee0700772616d0afefd209920c762b1604368d8c3458322"},
+    {file = "torchvision-0.20.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:86f6523dee420000fe14c3527f6c8e0175139fda7d995b187f54a0b0ebec7eb6"},
+    {file = "torchvision-0.20.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:a40d766345927639da322c693934e5f91b1ba2218846c7104b868dea2314ce8e"},
+    {file = "torchvision-0.20.1-cp311-cp311-win_amd64.whl", hash = "sha256:5b501d5c04b034d2ecda96a31ed050e383cf8201352e4c9276ca249cbecfded0"},
+    {file = "torchvision-0.20.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1a31256ff945d64f006bb306813a7c95a531fe16bfb2535c837dd4c104533d7a"},
+    {file = "torchvision-0.20.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:17cd78adddf81dac57d7dccc9277a4d686425b1c55715f308769770cb26cad5c"},
+    {file = "torchvision-0.20.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:9f853ba4497ac4691815ad41b523ee23cf5ba4f87b1ce869d704052e233ca8b7"},
+    {file = "torchvision-0.20.1-cp312-cp312-win_amd64.whl", hash = "sha256:4a330422c36dbfc946d3a6c1caec3489db07ecdf3675d83369adb2e5a0ca17c4"},
+    {file = "torchvision-0.20.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2cd58406978b813188cf4e9135b218775b57e0bb86d4a88f0339874b8a224819"},
+    {file = "torchvision-0.20.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:408766b2f0ada9e1bc880d12346cec9638535af5df6459ba9ac4ce5c46402f91"},
+    {file = "torchvision-0.20.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:abcb8005de8dc393dbd1310ecb669dc68ab664b9107af6d698a6341d1d3f2c3c"},
+    {file = "torchvision-0.20.1-cp39-cp39-win_amd64.whl", hash = "sha256:ea9678163bbf19568f4f959d927f3751eeb833cc8eac949de507edde38c1fc9f"},
 ]
 
 [package.dependencies]
 numpy = "*"
 pillow = ">=5.3.0,<8.3.dev0 || >=8.4.dev0"
-torch = "2.4.1"
+torch = "2.5.1"
 
 [package.extras]
 gdown = ["gdown (>=4.7.3)"]
@@ -6739,21 +6744,16 @@ tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
 
 [[package]]
 name = "triton"
-version = "3.0.0"
+version = "3.1.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 files = [
-    {file = "triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a"},
-    {file = "triton-3.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5ce8520437c602fb633f1324cc3871c47bee3b67acf9756c1a66309b60e3216c"},
-    {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
-    {file = "triton-3.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bcbf3b1c48af6a28011a5c40a5b3b9b5330530c3827716b5fbf6d7adcc1e53e9"},
-    {file = "triton-3.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6e5727202f7078c56f91ff13ad0c1abab14a0e7f2c87e91b12b6f64f3e8ae609"},
-    {file = "triton-3.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39b052da883351fdf6be3d93cedae6db3b8e3988d3b09ed221bccecfa9612230"},
-    {file = "triton-3.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cd34f19a8582af96e6291d4afce25dac08cb2a5d218c599163761e8e0827208e"},
-    {file = "triton-3.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0d5e10de8c011adeb7c878c6ce0dd6073b14367749e34467f1cff2bde1b78253"},
-    {file = "triton-3.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8903767951bf86ec960b4fe4e21bc970055afc65e9d57e916d79ae3c93665e3"},
-    {file = "triton-3.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41004fb1ae9a53fcb3e970745feb87f0e3c94c6ce1ba86e95fa3b8537894bef7"},
+    {file = "triton-3.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b0dd10a925263abbe9fa37dcde67a5e9b2383fc269fdf59f5657cac38c5d1d8"},
+    {file = "triton-3.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0f34f6e7885d1bf0eaaf7ba875a5f0ce6f3c13ba98f9503651c1e6dc6757ed5c"},
+    {file = "triton-3.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c8182f42fd8080a7d39d666814fa36c5e30cc00ea7eeeb1a2983dbb4c99a0fdc"},
+    {file = "triton-3.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6dadaca7fc24de34e180271b5cf864c16755702e9f63a16f62df714a8099126a"},
+    {file = "triton-3.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aafa9a20cd0d9fee523cd4504aa7131807a864cd77dcf6efe7e981f18b8c6c11"},
 ]
 
 [package.dependencies]
@@ -6806,13 +6806,13 @@ typing-extensions = ">=3.7.4.3"
 
 [[package]]
 name = "types-openpyxl"
-version = "3.1.5.20241114"
+version = "3.1.5.20241126"
 description = "Typing stubs for openpyxl"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-openpyxl-3.1.5.20241114.tar.gz", hash = "sha256:caeb9aafed8a5ffabdc74f880b148d90375364a1cfe7915d5065c5d79f3fe6a2"},
-    {file = "types_openpyxl-3.1.5.20241114-py3-none-any.whl", hash = "sha256:f2925f595b08f5aef1baa725c9ee40baaf51beb05d98ac150593d3bdd37b1029"},
+    {file = "types_openpyxl-3.1.5.20241126-py3-none-any.whl", hash = "sha256:e50ad5c2dec2c92cca521abed5c039975226e8e76389f17ab0ef813595593fbe"},
+    {file = "types_openpyxl-3.1.5.20241126.tar.gz", hash = "sha256:f599afab19f87aa11672ee675346401d82a0dac71988df9a5411cdb1e7477377"},
 ]
 
 [[package]]
@@ -6968,13 +6968,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.27.1"
+version = "20.28.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.27.1-py3-none-any.whl", hash = "sha256:f11f1b8a29525562925f745563bfd48b189450f61fb34c4f9cc79dd5aa32a1f4"},
-    {file = "virtualenv-20.27.1.tar.gz", hash = "sha256:142c6be10212543b32c6c45d3d3893dff89112cc588b7d0879ae5a1ec03a47ba"},
+    {file = "virtualenv-20.28.0-py3-none-any.whl", hash = "sha256:23eae1b4516ecd610481eda647f3a7c09aea295055337331bb4e6892ecce47b0"},
+    {file = "virtualenv-20.28.0.tar.gz", hash = "sha256:2c9c3262bb8e7b87ea801d715fae4495e6032450c71d2309be9550e7364049aa"},
 ]
 
 [package.dependencies]
@@ -7415,4 +7415,4 @@ tesserocr = ["tesserocr"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "eddea0c7af1ce850730e7f0c1b8eb7581651ccc233805ce1fb719a7f3d572612"
+content-hash = "37aeaba10d70b728cffd5e0403ae02bdc9a34d0c3a9781cebad920233336988d"
diff --git a/pyproject.toml b/pyproject.toml
index 11d46571..814348e1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "docling"
-version = "2.7.0"  # DO NOT EDIT, updated automatically
+version = "2.7.1"  # DO NOT EDIT, updated automatically
 description = "SDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications."
 authors = ["Christoph Auer <cau@zurich.ibm.com>", "Michele Dolfi <dol@zurich.ibm.com>", "Maxim Lysak <mly@zurich.ibm.com>", "Nikos Livathinos <nli@zurich.ibm.com>", "Ahmed Nassar <ahn@zurich.ibm.com>", "Panos Vagenas <pva@zurich.ibm.com>", "Peter Staar <taa@zurich.ibm.com>"]
 license = "MIT"
@@ -48,6 +48,7 @@ beautifulsoup4 = "^4.12.3"
 pandas = "^2.1.4"
 marko = "^2.1.2"
 openpyxl = "^3.1.5"
+lxml = ">=4.0.0,<6.0.0"
 ocrmac = { version = "^1.0.0", markers = "sys_platform == 'darwin'", optional = true }
 rapidocr-onnxruntime = { version = "^1.4.0", optional = true, markers = "python_version < '3.13'" }
 onnxruntime = [
diff --git a/tests/data/docx/test_emf_docx.docx b/tests/data/docx/test_emf_docx.docx
new file mode 100644
index 00000000..12ade783
Binary files /dev/null and b/tests/data/docx/test_emf_docx.docx differ
diff --git a/tests/data/groundtruth/docling_v2/tablecell.docx.itxt b/tests/data/groundtruth/docling_v2/tablecell.docx.itxt
new file mode 100644
index 00000000..f972efcd
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/tablecell.docx.itxt
@@ -0,0 +1,10 @@
+item-0 at level 0: unspecified: group _root_
+  item-1 at level 1: list: group list
+    item-2 at level 2: list_item: Hello world1
+    item-3 at level 2: list_item: Hello2
+  item-4 at level 1: paragraph: 
+  item-5 at level 1: paragraph: Some text before
+  item-6 at level 1: table with [3x3]
+  item-7 at level 1: paragraph: 
+  item-8 at level 1: paragraph: 
+  item-9 at level 1: paragraph: Some text after
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/tablecell.docx.json b/tests/data/groundtruth/docling_v2/tablecell.docx.json
new file mode 100644
index 00000000..d811cc86
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/tablecell.docx.json
@@ -0,0 +1,392 @@
+{
+  "schema_name": "DoclingDocument",
+  "version": "1.0.0",
+  "name": "tablecell",
+  "origin": {
+    "mimetype": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+    "binary_hash": 1111850039819445035,
+    "filename": "tablecell.docx"
+  },
+  "furniture": {
+    "self_ref": "#/furniture",
+    "children": [],
+    "name": "_root_",
+    "label": "unspecified"
+  },
+  "body": {
+    "self_ref": "#/body",
+    "children": [
+      {
+        "$ref": "#/groups/0"
+      },
+      {
+        "$ref": "#/texts/2"
+      },
+      {
+        "$ref": "#/texts/3"
+      },
+      {
+        "$ref": "#/tables/0"
+      },
+      {
+        "$ref": "#/texts/4"
+      },
+      {
+        "$ref": "#/texts/5"
+      },
+      {
+        "$ref": "#/texts/6"
+      }
+    ],
+    "name": "_root_",
+    "label": "unspecified"
+  },
+  "groups": [
+    {
+      "self_ref": "#/groups/0",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [
+        {
+          "$ref": "#/texts/0"
+        },
+        {
+          "$ref": "#/texts/1"
+        }
+      ],
+      "name": "list",
+      "label": "list"
+    }
+  ],
+  "texts": [
+    {
+      "self_ref": "#/texts/0",
+      "parent": {
+        "$ref": "#/groups/0"
+      },
+      "children": [],
+      "label": "list_item",
+      "prov": [],
+      "orig": "Hello world1",
+      "text": "Hello world1",
+      "enumerated": false,
+      "marker": "-"
+    },
+    {
+      "self_ref": "#/texts/1",
+      "parent": {
+        "$ref": "#/groups/0"
+      },
+      "children": [],
+      "label": "list_item",
+      "prov": [],
+      "orig": "Hello2",
+      "text": "Hello2",
+      "enumerated": false,
+      "marker": "-"
+    },
+    {
+      "self_ref": "#/texts/2",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "",
+      "text": ""
+    },
+    {
+      "self_ref": "#/texts/3",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Some text before",
+      "text": "Some text before"
+    },
+    {
+      "self_ref": "#/texts/4",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "",
+      "text": ""
+    },
+    {
+      "self_ref": "#/texts/5",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "",
+      "text": ""
+    },
+    {
+      "self_ref": "#/texts/6",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Some text after",
+      "text": "Some text after"
+    }
+  ],
+  "pictures": [],
+  "tables": [
+    {
+      "self_ref": "#/tables/0",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "table",
+      "prov": [],
+      "captions": [],
+      "references": [],
+      "footnotes": [],
+      "data": {
+        "table_cells": [
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 0,
+            "end_row_offset_idx": 1,
+            "start_col_offset_idx": 0,
+            "end_col_offset_idx": 1,
+            "text": "Tab1",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 0,
+            "end_row_offset_idx": 1,
+            "start_col_offset_idx": 1,
+            "end_col_offset_idx": 2,
+            "text": "Tab2",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 0,
+            "end_row_offset_idx": 1,
+            "start_col_offset_idx": 2,
+            "end_col_offset_idx": 3,
+            "text": "Tab3",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 1,
+            "end_row_offset_idx": 2,
+            "start_col_offset_idx": 0,
+            "end_col_offset_idx": 1,
+            "text": "A",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 1,
+            "end_row_offset_idx": 2,
+            "start_col_offset_idx": 1,
+            "end_col_offset_idx": 2,
+            "text": "B",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 1,
+            "end_row_offset_idx": 2,
+            "start_col_offset_idx": 2,
+            "end_col_offset_idx": 3,
+            "text": "C",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 2,
+            "end_row_offset_idx": 3,
+            "start_col_offset_idx": 0,
+            "end_col_offset_idx": 1,
+            "text": "D",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 2,
+            "end_row_offset_idx": 3,
+            "start_col_offset_idx": 1,
+            "end_col_offset_idx": 2,
+            "text": "E",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          },
+          {
+            "row_span": 1,
+            "col_span": 1,
+            "start_row_offset_idx": 2,
+            "end_row_offset_idx": 3,
+            "start_col_offset_idx": 2,
+            "end_col_offset_idx": 3,
+            "text": "F",
+            "column_header": false,
+            "row_header": false,
+            "row_section": false
+          }
+        ],
+        "num_rows": 3,
+        "num_cols": 3,
+        "grid": [
+          [
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 0,
+              "end_row_offset_idx": 1,
+              "start_col_offset_idx": 0,
+              "end_col_offset_idx": 1,
+              "text": "Tab1",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 0,
+              "end_row_offset_idx": 1,
+              "start_col_offset_idx": 1,
+              "end_col_offset_idx": 2,
+              "text": "Tab2",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 0,
+              "end_row_offset_idx": 1,
+              "start_col_offset_idx": 2,
+              "end_col_offset_idx": 3,
+              "text": "Tab3",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            }
+          ],
+          [
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 1,
+              "end_row_offset_idx": 2,
+              "start_col_offset_idx": 0,
+              "end_col_offset_idx": 1,
+              "text": "A",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 1,
+              "end_row_offset_idx": 2,
+              "start_col_offset_idx": 1,
+              "end_col_offset_idx": 2,
+              "text": "B",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 1,
+              "end_row_offset_idx": 2,
+              "start_col_offset_idx": 2,
+              "end_col_offset_idx": 3,
+              "text": "C",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            }
+          ],
+          [
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 2,
+              "end_row_offset_idx": 3,
+              "start_col_offset_idx": 0,
+              "end_col_offset_idx": 1,
+              "text": "D",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 2,
+              "end_row_offset_idx": 3,
+              "start_col_offset_idx": 1,
+              "end_col_offset_idx": 2,
+              "text": "E",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            },
+            {
+              "row_span": 1,
+              "col_span": 1,
+              "start_row_offset_idx": 2,
+              "end_row_offset_idx": 3,
+              "start_col_offset_idx": 2,
+              "end_col_offset_idx": 3,
+              "text": "F",
+              "column_header": false,
+              "row_header": false,
+              "row_section": false
+            }
+          ]
+        ]
+      }
+    }
+  ],
+  "key_value_items": [],
+  "pages": {}
+}
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/tablecell.docx.md b/tests/data/groundtruth/docling_v2/tablecell.docx.md
new file mode 100644
index 00000000..f7a3de6c
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/tablecell.docx.md
@@ -0,0 +1,11 @@
+- Hello world1
+- Hello2
+
+Some text before
+
+| Tab1   | Tab2   | Tab3   |
+|--------|--------|--------|
+| A      | B      | C      |
+| D      | E      | F      |
+
+Some text after
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/test_emf_docx.docx.itxt b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.itxt
new file mode 100644
index 00000000..220b5533
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.itxt
@@ -0,0 +1,8 @@
+item-0 at level 0: unspecified: group _root_
+  item-1 at level 1: paragraph: Test with three images in unusual formats
+  item-2 at level 1: paragraph: Raster in emf:
+  item-3 at level 1: picture
+  item-4 at level 1: paragraph: Vector in emf:
+  item-5 at level 1: picture
+  item-6 at level 1: paragraph: Raster in webp:
+  item-7 at level 1: picture
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/test_emf_docx.docx.json b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.json
new file mode 100644
index 00000000..6418a215
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.json
@@ -0,0 +1,144 @@
+{
+  "schema_name": "DoclingDocument",
+  "version": "1.0.0",
+  "name": "test_emf_docx",
+  "origin": {
+    "mimetype": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+    "binary_hash": 17745489605737899558,
+    "filename": "test_emf_docx.docx"
+  },
+  "furniture": {
+    "self_ref": "#/furniture",
+    "children": [],
+    "name": "_root_",
+    "label": "unspecified"
+  },
+  "body": {
+    "self_ref": "#/body",
+    "children": [
+      {
+        "$ref": "#/texts/0"
+      },
+      {
+        "$ref": "#/texts/1"
+      },
+      {
+        "$ref": "#/pictures/0"
+      },
+      {
+        "$ref": "#/texts/2"
+      },
+      {
+        "$ref": "#/pictures/1"
+      },
+      {
+        "$ref": "#/texts/3"
+      },
+      {
+        "$ref": "#/pictures/2"
+      }
+    ],
+    "name": "_root_",
+    "label": "unspecified"
+  },
+  "groups": [],
+  "texts": [
+    {
+      "self_ref": "#/texts/0",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Test with three images in unusual formats",
+      "text": "Test with three images in unusual formats"
+    },
+    {
+      "self_ref": "#/texts/1",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Raster in emf:",
+      "text": "Raster in emf:"
+    },
+    {
+      "self_ref": "#/texts/2",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Vector in emf:",
+      "text": "Vector in emf:"
+    },
+    {
+      "self_ref": "#/texts/3",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "paragraph",
+      "prov": [],
+      "orig": "Raster in webp:",
+      "text": "Raster in webp:"
+    }
+  ],
+  "pictures": [
+    {
+      "self_ref": "#/pictures/0",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "picture",
+      "prov": [],
+      "captions": [],
+      "references": [],
+      "footnotes": [],
+      "annotations": []
+    },
+    {
+      "self_ref": "#/pictures/1",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "picture",
+      "prov": [],
+      "captions": [],
+      "references": [],
+      "footnotes": [],
+      "annotations": []
+    },
+    {
+      "self_ref": "#/pictures/2",
+      "parent": {
+        "$ref": "#/body"
+      },
+      "children": [],
+      "label": "picture",
+      "prov": [],
+      "captions": [],
+      "references": [],
+      "footnotes": [],
+      "image": {
+        "mimetype": "image/png",
+        "dpi": 72,
+        "size": {
+          "width": 400.0,
+          "height": 400.0
+        },
+        "uri": "data:image/png;base64,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"
+      },
+      "annotations": []
+    }
+  ],
+  "tables": [],
+  "key_value_items": [],
+  "pages": {}
+}
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/test_emf_docx.docx.md b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.md
new file mode 100644
index 00000000..4ebcbf21
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/test_emf_docx.docx.md
@@ -0,0 +1,13 @@
+Test with three images in unusual formats
+
+Raster in emf:
+
+<!-- image -->
+
+Vector in emf:
+
+<!-- image -->
+
+Raster in webp:
+
+<!-- image -->
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/word_sample.json b/tests/data/groundtruth/docling_v2/word_sample.json
new file mode 100644
index 00000000..42f154f6
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/word_sample.json
@@ -0,0 +1 @@
+{"schema_name": "DoclingDocument", "version": "1.0.0", "name": "word_sample", "origin": {"mimetype": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "binary_hash": 5964280909995938039, "filename": "word_sample.docx"}, "furniture": {"self_ref": "#/furniture", "children": [], "name": "_root_", "label": "unspecified"}, "body": {"self_ref": "#/body", "children": [{"$ref": "#/texts/0"}, {"$ref": "#/texts/1"}], "name": "_root_", "label": "unspecified"}, "groups": [{"self_ref": "#/groups/0", "parent": {"$ref": "#/texts/4"}, "children": [{"$ref": "#/texts/6"}, {"$ref": "#/texts/7"}, {"$ref": "#/texts/8"}], "name": "list", "label": "list"}, {"self_ref": "#/groups/1", "parent": {"$ref": "#/texts/4"}, "children": [{"$ref": "#/texts/10"}, {"$ref": "#/texts/11"}, {"$ref": "#/texts/12"}], "name": "list", "label": "list"}, {"self_ref": "#/groups/2", "parent": {"$ref": "#/texts/14"}, "children": [{"$ref": "#/texts/20"}, {"$ref": "#/texts/21"}, {"$ref": "#/texts/22"}], "name": "list", "label": "list"}], "texts": [{"self_ref": "#/texts/0", "parent": {"$ref": "#/body"}, "children": [], "label": "paragraph", "prov": [], "orig": "Summer activities", "text": "Summer activities"}, {"self_ref": "#/texts/1", "parent": {"$ref": "#/body"}, "children": [{"$ref": "#/texts/2"}, {"$ref": "#/pictures/0"}, {"$ref": "#/texts/3"}, {"$ref": "#/texts/4"}], "label": "title", "prov": [], "orig": "Swimming in the lake", "text": "Swimming in the lake"}, {"self_ref": "#/texts/2", "parent": {"$ref": "#/texts/1"}, "children": [], "label": "paragraph", "prov": [], "orig": "Duck", "text": "Duck"}, {"self_ref": "#/texts/3", "parent": {"$ref": "#/texts/1"}, "children": [], "label": "paragraph", "prov": [], "orig": "Figure 1: This is a cute duckling", "text": "Figure 1: This is a cute duckling"}, {"self_ref": "#/texts/4", "parent": {"$ref": "#/texts/1"}, "children": [{"$ref": "#/texts/5"}, {"$ref": "#/groups/0"}, {"$ref": "#/texts/9"}, {"$ref": "#/groups/1"}, {"$ref": "#/texts/13"}, {"$ref": "#/texts/14"}], "label": "section_header", "prov": [], "orig": "Let\u2019s swim!", "text": "Let\u2019s swim!", "level": 1}, {"self_ref": "#/texts/5", "parent": {"$ref": "#/texts/4"}, "children": [], "label": "paragraph", "prov": [], "orig": "To get started with swimming, first lay down in a water and try not to drown:", "text": "To get started with swimming, first lay down in a water and try not to drown:"}, {"self_ref": "#/texts/6", "parent": {"$ref": "#/groups/0"}, "children": [], "label": "list_item", "prov": [], "orig": "You can relax and look around", "text": "You can relax and look around", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/7", "parent": {"$ref": "#/groups/0"}, "children": [], "label": "list_item", "prov": [], "orig": "Paddle about", "text": "Paddle about", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/8", "parent": {"$ref": "#/groups/0"}, "children": [], "label": "list_item", "prov": [], "orig": "Enjoy summer warmth", "text": "Enjoy summer warmth", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/9", "parent": {"$ref": "#/texts/4"}, "children": [], "label": "paragraph", "prov": [], "orig": "Also, don\u2019t forget:", "text": "Also, don\u2019t forget:"}, {"self_ref": "#/texts/10", "parent": {"$ref": "#/groups/1"}, "children": [], "label": "list_item", "prov": [], "orig": "Wear sunglasses", "text": "Wear sunglasses", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/11", "parent": {"$ref": "#/groups/1"}, "children": [], "label": "list_item", "prov": [], "orig": "Don\u2019t forget to drink water", "text": "Don\u2019t forget to drink water", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/12", "parent": {"$ref": "#/groups/1"}, "children": [], "label": "list_item", "prov": [], "orig": "Use sun cream", "text": "Use sun cream", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/13", "parent": {"$ref": "#/texts/4"}, "children": [], "label": "paragraph", "prov": [], "orig": "Hmm, what else\u2026", "text": "Hmm, what else\u2026"}, {"self_ref": "#/texts/14", "parent": {"$ref": "#/texts/4"}, "children": [{"$ref": "#/texts/15"}, {"$ref": "#/texts/16"}, {"$ref": "#/texts/17"}, {"$ref": "#/tables/0"}, {"$ref": "#/texts/18"}, {"$ref": "#/texts/19"}, {"$ref": "#/groups/2"}], "label": "section_header", "prov": [], "orig": "Let\u2019s eat", "text": "Let\u2019s eat", "level": 2}, {"self_ref": "#/texts/15", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "paragraph", "prov": [], "orig": "After we had a good day of swimming in the lake, it\u2019s important to eat something nice", "text": "After we had a good day of swimming in the lake, it\u2019s important to eat something nice"}, {"self_ref": "#/texts/16", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "paragraph", "prov": [], "orig": "I like to eat leaves", "text": "I like to eat leaves"}, {"self_ref": "#/texts/17", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "paragraph", "prov": [], "orig": "Here are some interesting things a respectful duck could eat:", "text": "Here are some interesting things a respectful duck could eat:"}, {"self_ref": "#/texts/18", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "paragraph", "prov": [], "orig": "", "text": ""}, {"self_ref": "#/texts/19", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "paragraph", "prov": [], "orig": "And let\u2019s add another list in the end:", "text": "And let\u2019s add another list in the end:"}, {"self_ref": "#/texts/20", "parent": {"$ref": "#/groups/2"}, "children": [], "label": "list_item", "prov": [], "orig": "Leaves", "text": "Leaves", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/21", "parent": {"$ref": "#/groups/2"}, "children": [], "label": "list_item", "prov": [], "orig": "Berries", "text": "Berries", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/22", "parent": {"$ref": "#/groups/2"}, "children": [], "label": "list_item", "prov": [], "orig": "Grain", "text": "Grain", "enumerated": false, "marker": "-"}], "pictures": [{"self_ref": "#/pictures/0", "parent": {"$ref": "#/texts/1"}, "children": [], "label": "picture", "prov": [], "captions": [], "references": [], "footnotes": [], "image": {"mimetype": "image/png", "dpi": 72, "size": {"width": 397.0, "height": 397.0}, "uri": "data:image/png;base64,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"}, "annotations": []}], "tables": [{"self_ref": "#/tables/0", "parent": {"$ref": "#/texts/14"}, "children": [], "label": "table", "prov": [], "captions": [], "references": [], "footnotes": [], "data": {"table_cells": [{"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Food", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "Calories per portion", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Leaves", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Ash, Elm, Maple", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "50", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Berries", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Blueberry, Strawberry, Cranberry", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "150", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Grain", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Corn, Buckwheat, Barley", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "200", "column_header": false, "row_header": false, "row_section": false}], "num_rows": 4, "num_cols": 3, "grid": [[{"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Food", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 0, "end_row_offset_idx": 1, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "Calories per portion", "column_header": false, "row_header": false, "row_section": false}], [{"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Leaves", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Ash, Elm, Maple", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 1, "end_row_offset_idx": 2, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "50", "column_header": false, "row_header": false, "row_section": false}], [{"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Berries", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Blueberry, Strawberry, Cranberry", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 2, "end_row_offset_idx": 3, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "150", "column_header": false, "row_header": false, "row_section": false}], [{"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 0, "end_col_offset_idx": 1, "text": "Grain", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 1, "end_col_offset_idx": 2, "text": "Corn, Buckwheat, Barley", "column_header": false, "row_header": false, "row_section": false}, {"row_span": 1, "col_span": 1, "start_row_offset_idx": 3, "end_row_offset_idx": 4, "start_col_offset_idx": 2, "end_col_offset_idx": 3, "text": "200", "column_header": false, "row_header": false, "row_section": false}]]}}], "key_value_items": [], "pages": {}}
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/word_sample.md b/tests/data/groundtruth/docling_v2/word_sample.md
new file mode 100644
index 00000000..9c5a96e0
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/word_sample.md
@@ -0,0 +1,45 @@
+Summer activities
+
+# Swimming in the lake
+
+Duck
+
+<!-- image -->
+
+Figure 1: This is a cute duckling
+
+## Let’s swim!
+
+To get started with swimming, first lay down in a water and try not to drown:
+
+- You can relax and look around
+- Paddle about
+- Enjoy summer warmth
+
+Also, don’t forget:
+
+- Wear sunglasses
+- Don’t forget to drink water
+- Use sun cream
+
+Hmm, what else…
+
+### Let’s eat
+
+After we had a good day of swimming in the lake, it’s important to eat something nice
+
+I like to eat leaves
+
+Here are some interesting things a respectful duck could eat:
+
+|         | Food                             |   Calories per portion |
+|---------|----------------------------------|------------------------|
+| Leaves  | Ash, Elm, Maple                  |                     50 |
+| Berries | Blueberry, Strawberry, Cranberry |                    150 |
+| Grain   | Corn, Buckwheat, Barley          |                    200 |
+
+And let’s add another list in the end:
+
+- Leaves
+- Berries
+- Grain
\ No newline at end of file
diff --git a/tests/data/groundtruth/docling_v2/word_sample.yaml b/tests/data/groundtruth/docling_v2/word_sample.yaml
new file mode 100644
index 00000000..b11146e2
--- /dev/null
+++ b/tests/data/groundtruth/docling_v2/word_sample.yaml
@@ -0,0 +1,546 @@
+body:
+  children:
+  - $ref: '#/texts/0'
+  - $ref: '#/texts/1'
+  label: unspecified
+  name: _root_
+  self_ref: '#/body'
+furniture:
+  children: []
+  label: unspecified
+  name: _root_
+  self_ref: '#/furniture'
+groups:
+- children:
+  - $ref: '#/texts/6'
+  - $ref: '#/texts/7'
+  - $ref: '#/texts/8'
+  label: list
+  name: list
+  parent:
+    $ref: '#/texts/4'
+  self_ref: '#/groups/0'
+- children:
+  - $ref: '#/texts/10'
+  - $ref: '#/texts/11'
+  - $ref: '#/texts/12'
+  label: list
+  name: list
+  parent:
+    $ref: '#/texts/4'
+  self_ref: '#/groups/1'
+- children:
+  - $ref: '#/texts/20'
+  - $ref: '#/texts/21'
+  - $ref: '#/texts/22'
+  label: list
+  name: list
+  parent:
+    $ref: '#/texts/14'
+  self_ref: '#/groups/2'
+key_value_items: []
+name: word_sample
+origin:
+  binary_hash: 5964280909995938039
+  filename: word_sample.docx
+  mimetype: application/vnd.openxmlformats-officedocument.wordprocessingml.document
+pages: {}
+pictures:
+- annotations: []
+  captions: []
+  children: []
+  footnotes: []
+  image:
+    dpi: 72
+    mimetype: image/png
+    size:
+      height: 397.0
+      width: 397.0
+    uri: data:image/png;base64,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
+  label: picture
+  parent:
+    $ref: '#/texts/1'
+  prov: []
+  references: []
+  self_ref: '#/pictures/0'
+schema_name: DoclingDocument
+tables:
+- captions: []
+  children: []
+  data:
+    grid:
+    - - col_span: 1
+        column_header: false
+        end_col_offset_idx: 1
+        end_row_offset_idx: 1
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 0
+        start_row_offset_idx: 0
+        text: ''
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 2
+        end_row_offset_idx: 1
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 1
+        start_row_offset_idx: 0
+        text: Food
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 3
+        end_row_offset_idx: 1
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 2
+        start_row_offset_idx: 0
+        text: Calories per portion
+    - - col_span: 1
+        column_header: false
+        end_col_offset_idx: 1
+        end_row_offset_idx: 2
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 0
+        start_row_offset_idx: 1
+        text: Leaves
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 2
+        end_row_offset_idx: 2
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 1
+        start_row_offset_idx: 1
+        text: Ash, Elm, Maple
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 3
+        end_row_offset_idx: 2
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 2
+        start_row_offset_idx: 1
+        text: '50'
+    - - col_span: 1
+        column_header: false
+        end_col_offset_idx: 1
+        end_row_offset_idx: 3
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 0
+        start_row_offset_idx: 2
+        text: Berries
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 2
+        end_row_offset_idx: 3
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 1
+        start_row_offset_idx: 2
+        text: Blueberry, Strawberry, Cranberry
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 3
+        end_row_offset_idx: 3
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 2
+        start_row_offset_idx: 2
+        text: '150'
+    - - col_span: 1
+        column_header: false
+        end_col_offset_idx: 1
+        end_row_offset_idx: 4
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 0
+        start_row_offset_idx: 3
+        text: Grain
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 2
+        end_row_offset_idx: 4
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 1
+        start_row_offset_idx: 3
+        text: Corn, Buckwheat, Barley
+      - col_span: 1
+        column_header: false
+        end_col_offset_idx: 3
+        end_row_offset_idx: 4
+        row_header: false
+        row_section: false
+        row_span: 1
+        start_col_offset_idx: 2
+        start_row_offset_idx: 3
+        text: '200'
+    num_cols: 3
+    num_rows: 4
+    table_cells:
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 1
+      end_row_offset_idx: 1
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 0
+      start_row_offset_idx: 0
+      text: ''
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 2
+      end_row_offset_idx: 1
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 1
+      start_row_offset_idx: 0
+      text: Food
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 3
+      end_row_offset_idx: 1
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 2
+      start_row_offset_idx: 0
+      text: Calories per portion
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 1
+      end_row_offset_idx: 2
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 0
+      start_row_offset_idx: 1
+      text: Leaves
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 2
+      end_row_offset_idx: 2
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 1
+      start_row_offset_idx: 1
+      text: Ash, Elm, Maple
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 3
+      end_row_offset_idx: 2
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 2
+      start_row_offset_idx: 1
+      text: '50'
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 1
+      end_row_offset_idx: 3
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 0
+      start_row_offset_idx: 2
+      text: Berries
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 2
+      end_row_offset_idx: 3
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 1
+      start_row_offset_idx: 2
+      text: Blueberry, Strawberry, Cranberry
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 3
+      end_row_offset_idx: 3
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 2
+      start_row_offset_idx: 2
+      text: '150'
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 1
+      end_row_offset_idx: 4
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 0
+      start_row_offset_idx: 3
+      text: Grain
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 2
+      end_row_offset_idx: 4
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 1
+      start_row_offset_idx: 3
+      text: Corn, Buckwheat, Barley
+    - col_span: 1
+      column_header: false
+      end_col_offset_idx: 3
+      end_row_offset_idx: 4
+      row_header: false
+      row_section: false
+      row_span: 1
+      start_col_offset_idx: 2
+      start_row_offset_idx: 3
+      text: '200'
+  footnotes: []
+  label: table
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  references: []
+  self_ref: '#/tables/0'
+texts:
+- children: []
+  label: paragraph
+  orig: Summer activities
+  parent:
+    $ref: '#/body'
+  prov: []
+  self_ref: '#/texts/0'
+  text: Summer activities
+- children:
+  - $ref: '#/texts/2'
+  - $ref: '#/pictures/0'
+  - $ref: '#/texts/3'
+  - $ref: '#/texts/4'
+  label: title
+  orig: Swimming in the lake
+  parent:
+    $ref: '#/body'
+  prov: []
+  self_ref: '#/texts/1'
+  text: Swimming in the lake
+- children: []
+  label: paragraph
+  orig: Duck
+  parent:
+    $ref: '#/texts/1'
+  prov: []
+  self_ref: '#/texts/2'
+  text: Duck
+- children: []
+  label: paragraph
+  orig: 'Figure 1: This is a cute duckling'
+  parent:
+    $ref: '#/texts/1'
+  prov: []
+  self_ref: '#/texts/3'
+  text: 'Figure 1: This is a cute duckling'
+- children:
+  - $ref: '#/texts/5'
+  - $ref: '#/groups/0'
+  - $ref: '#/texts/9'
+  - $ref: '#/groups/1'
+  - $ref: '#/texts/13'
+  - $ref: '#/texts/14'
+  label: section_header
+  level: 1
+  orig: "Let\u2019s swim!"
+  parent:
+    $ref: '#/texts/1'
+  prov: []
+  self_ref: '#/texts/4'
+  text: "Let\u2019s swim!"
+- children: []
+  label: paragraph
+  orig: 'To get started with swimming, first lay down in a water and try not to drown:'
+  parent:
+    $ref: '#/texts/4'
+  prov: []
+  self_ref: '#/texts/5'
+  text: 'To get started with swimming, first lay down in a water and try not to drown:'
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: You can relax and look around
+  parent:
+    $ref: '#/groups/0'
+  prov: []
+  self_ref: '#/texts/6'
+  text: You can relax and look around
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Paddle about
+  parent:
+    $ref: '#/groups/0'
+  prov: []
+  self_ref: '#/texts/7'
+  text: Paddle about
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Enjoy summer warmth
+  parent:
+    $ref: '#/groups/0'
+  prov: []
+  self_ref: '#/texts/8'
+  text: Enjoy summer warmth
+- children: []
+  label: paragraph
+  orig: "Also, don\u2019t forget:"
+  parent:
+    $ref: '#/texts/4'
+  prov: []
+  self_ref: '#/texts/9'
+  text: "Also, don\u2019t forget:"
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Wear sunglasses
+  parent:
+    $ref: '#/groups/1'
+  prov: []
+  self_ref: '#/texts/10'
+  text: Wear sunglasses
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: "Don\u2019t forget to drink water"
+  parent:
+    $ref: '#/groups/1'
+  prov: []
+  self_ref: '#/texts/11'
+  text: "Don\u2019t forget to drink water"
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Use sun cream
+  parent:
+    $ref: '#/groups/1'
+  prov: []
+  self_ref: '#/texts/12'
+  text: Use sun cream
+- children: []
+  label: paragraph
+  orig: "Hmm, what else\u2026"
+  parent:
+    $ref: '#/texts/4'
+  prov: []
+  self_ref: '#/texts/13'
+  text: "Hmm, what else\u2026"
+- children:
+  - $ref: '#/texts/15'
+  - $ref: '#/texts/16'
+  - $ref: '#/texts/17'
+  - $ref: '#/tables/0'
+  - $ref: '#/texts/18'
+  - $ref: '#/texts/19'
+  - $ref: '#/groups/2'
+  label: section_header
+  level: 2
+  orig: "Let\u2019s eat"
+  parent:
+    $ref: '#/texts/4'
+  prov: []
+  self_ref: '#/texts/14'
+  text: "Let\u2019s eat"
+- children: []
+  label: paragraph
+  orig: "After we had a good day of swimming in the lake, it\u2019s important to eat\
+    \ something nice"
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  self_ref: '#/texts/15'
+  text: "After we had a good day of swimming in the lake, it\u2019s important to eat\
+    \ something nice"
+- children: []
+  label: paragraph
+  orig: I like to eat leaves
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  self_ref: '#/texts/16'
+  text: I like to eat leaves
+- children: []
+  label: paragraph
+  orig: 'Here are some interesting things a respectful duck could eat:'
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  self_ref: '#/texts/17'
+  text: 'Here are some interesting things a respectful duck could eat:'
+- children: []
+  label: paragraph
+  orig: ''
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  self_ref: '#/texts/18'
+  text: ''
+- children: []
+  label: paragraph
+  orig: "And let\u2019s add another list in the end:"
+  parent:
+    $ref: '#/texts/14'
+  prov: []
+  self_ref: '#/texts/19'
+  text: "And let\u2019s add another list in the end:"
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Leaves
+  parent:
+    $ref: '#/groups/2'
+  prov: []
+  self_ref: '#/texts/20'
+  text: Leaves
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Berries
+  parent:
+    $ref: '#/groups/2'
+  prov: []
+  self_ref: '#/texts/21'
+  text: Berries
+- children: []
+  enumerated: false
+  label: list_item
+  marker: '-'
+  orig: Grain
+  parent:
+    $ref: '#/groups/2'
+  prov: []
+  self_ref: '#/texts/22'
+  text: Grain
+version: 1.0.0