134 Commits

Author SHA1 Message Date
github-actions[bot]
624f65d41b chore: bump version to 1.3.1 [skip ci] 2025-08-21 07:01:51 +00:00
Michele Dolfi
f02dbc0144 fix: configuration and performance fixes via upgrade of packages (#328)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-20 20:40:52 +02:00
Michele Dolfi
37fe02277b docs: fix parameter in api key docs (#323)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-15 11:00:05 +02:00
github-actions[bot]
783ada0580 chore: bump version to 1.3.0 [skip ci] 2025-08-14 14:26:57 +00:00
VIktor Kuropiantnyk
71edf41849 docs: example of docling-serve deployment in the RQ engine mode (#321)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 16:10:39 +02:00
Michele Dolfi
9a64410552 feat: Add configuration option for apikey security (#322)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 15:25:53 +02:00
Michele Dolfi
6e9aa8c759 docs: handling models in docling-serve (#319)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 09:12:04 +02:00
Michele Dolfi
885f319d3a feat: Add RQ engine (#315)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 08:48:31 +02:00
Tiago Santana
d584895e11 docs: add Gradio cache usage (#312)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-08-13 16:49:54 +02:00
github-actions[bot]
d26e6637d8 chore: bump version to 1.2.2 [skip ci] 2025-08-13 14:48:17 +00:00
VIktor Kuropiantnyk
7692eb2600 fix: update of transformers module to 4.55.1 (#316)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
2025-08-13 16:07:52 +02:00
github-actions[bot]
3bd7828570 chore: bump version to 1.2.1 [skip ci] 2025-08-13 07:37:55 +00:00
Michele Dolfi
8b470cba8e fix: handling of vlm model options and update deps (#314)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-13 09:32:21 +02:00
Tiago Santana
8048f4589a fix: add missing response type in sync endpoints (#309)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-08-08 12:32:19 +02:00
Thomas Vitale
b3058e91e0 docs: Update readme to use v1 (#306)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 09:02:29 +02:00
Thomas Vitale
63da9eedeb docs: Update deployment examples to use v1 API (#308)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 08:47:59 +02:00
Thomas Vitale
b15dc2529f docs: Fix typo in v1 migration instructions (#307)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 08:44:09 +02:00
github-actions[bot]
4c7207be00 chore: bump version to 1.2.0 [skip ci] 2025-08-07 09:20:10 +00:00
Michele Dolfi
db3fdb5bc1 feat: workers without shared models and convert params (#304)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-07 11:16:06 +02:00
Rui Dias Gomes
fd1b987e8d feat: add rocm image build support and fix cuda (#292)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
Signed-off-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
Co-authored-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
2025-07-31 14:22:42 +02:00
github-actions[bot]
ce15e0302b chore: bump version to 1.1.0 [skip ci] 2025-07-30 15:53:01 +00:00
Michele Dolfi
ecb1874a50 feat: Add docling-mcp in the distribution (#290)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-30 15:39:11 +02:00
Michele Dolfi
1333f71c9c fix: referenced paths relative to zip root (#289)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-30 14:49:26 +02:00
Tiago Santana
ec594d84fe feat: add 3.0 openapi endpoint (#287)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-07-30 14:08:59 +02:00
Tiago Santana
3771c1b554 feat: add new source and target (#270)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-07-29 14:44:49 +02:00
github-actions[bot]
24db461b14 chore: bump version to 1.0.1 [skip ci] 2025-07-21 07:34:14 +00:00
Michele Dolfi
8706706e87 fix: docling update v2.42.0 (#277)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-21 08:47:40 +02:00
Michele Dolfi
766adb2481 docs: typo in README (#276)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-18 14:37:54 +02:00
Michele Dolfi
8222cf8955 ci: add spellchecker with custom vocabulary and fix typos (#268)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-15 14:17:35 +02:00
github-actions[bot]
b922824e5b chore: bump version to 1.0.0 [skip ci] 2025-07-14 11:25:06 +00:00
Michele Dolfi
56e328baf7 feat!: v1 api with list of sources and target (#249)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-14 13:19:49 +02:00
Michele Dolfi
daa924a77e feat!: use orchestrators from jobkit (#248)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-10 15:47:22 +02:00
Eugene
e63197e89e chore: bump uv to 0.7.19 in container (#266)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-07-10 15:10:21 +02:00
github-actions[bot]
767ce0982b chore: bump version to 0.16.1 [skip ci] 2025-07-07 16:17:50 +00:00
Michele Dolfi
bfde1a0991 fix: upgrade deps including, docling v2.40.0 with locks in models init (#264)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-07-07 17:13:45 +02:00
VIktor Kuropiantnyk
eb3892ee14 fix: missing tesseract osd (#263)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
2025-07-07 16:36:43 +02:00
tassadarliu
93b84712b2 docs: fix typo (#259)
Signed-off-by: tassadarliu <rhapsodyn@gmail.com>
2025-07-07 08:47:34 +02:00
Yishen Miao
c45b937064 docs: change the doc example (#258)
Signed-off-by: Yishen Miao <mys721tx@gmail.com>
2025-07-07 08:47:21 +02:00
Francisco Arceo
50e431f30f docs: Update typo (#247)
Signed-off-by: Francisco Arceo <arceofrancisco@gmail.com>
2025-06-27 16:58:37 +02:00
Michele Dolfi
149a8cb1c0 fix: properly load models at boot (#244)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-27 12:20:38 +02:00
github-actions[bot]
5f9c20a985 chore: bump version to 0.16.0 [skip ci] 2025-06-25 09:52:08 +00:00
Michele Dolfi
80755a7d59 docs: Update example resources and improve README (#231)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-25 07:56:14 +02:00
Michele Dolfi
30aca92298 feat: package updates and more cuda images (#229)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-24 16:59:05 +02:00
github-actions[bot]
717fb3a8d8 chore: bump version to 0.15.0 [skip ci] 2025-06-17 15:00:38 +00:00
Michele Dolfi
873d05aefe feat: use redocs and scalar as api docs (#228)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-17 16:54:00 +02:00
Ryan Fernandes
196c5ce42a fix: "tesserocr" instead of "tesseract_cli" in usage docs (#223)
Signed-off-by: Ryan Fernandes <ryan@fernandes.us>
2025-06-17 16:53:51 +02:00
github-actions[bot]
b5c5f47892 chore: bump version to 0.14.0 [skip ci] 2025-06-17 13:10:27 +00:00
23Ro
d5455b7f66 fix: Typo in Headline (#220)
Signed-off-by: 23Ro <m.n@23ro.de>
2025-06-17 14:55:27 +02:00
Michele Dolfi
7a682494d6 chore: dco advisor (#224)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-17 09:38:56 +02:00
Eugene
524f6a8997 feat: Read supported file extensions from docling (#214)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-06-05 09:38:28 +02:00
github-actions[bot]
9ccf8e3b5e chore: bump version to 0.13.0 [skip ci] 2025-06-04 12:24:40 +00:00
Michele Dolfi
ffea34732b feat: upgrade docling to 2.36 (#212)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-04 14:20:34 +02:00
github-actions[bot]
b299af002b chore: bump version to 0.12.0 [skip ci] 2025-06-03 16:30:28 +00:00
Michele Dolfi
c4c41f16df feat: Export annotations in markdown and html (Docling upgrade) (#202)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-03 18:24:27 +02:00
Michele Dolfi
7066f3520a fix: processing complex params in multipart-form (#210)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-03 18:24:05 +02:00
Rui Dias Gomes
6a8190c315 docs: add openshift replicasets examples (#209)
Signed-off-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
Co-authored-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
2025-06-03 17:43:41 +02:00
github-actions[bot]
060ecd8b0e chore: bump version to 0.11.0 [skip ci] 2025-05-23 13:45:54 +00:00
Michele Dolfi
32b8a809f3 feat: page break placeholder in markdown exports options (#194)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-23 15:26:27 +02:00
Michele Dolfi
de002dfcdc feat: clear results registry (#192)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-23 14:30:57 +02:00
Michele Dolfi
abe5aa03f5 feat: Upgrade to Docling 2.33.0 (#198)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-22 17:00:29 +02:00
VIktor Kuropiantnyk
3f090b7d15 docs: Example and instructions on how to load model weights to persistent volume (#197)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
2025-05-21 13:04:46 +02:00
Michele Dolfi
21c1791e42 docs: async api usage and fixes (#195)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-19 13:57:35 +02:00
Michele Dolfi
00be428490 feat: api to trigger offloading the models (#188)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-14 15:02:18 +02:00
Kasper Dinkla
3ff1b2f983 feat: Figure annotations @ docling components 0.0.7 (#181)
Signed-off-by: DKL <dkl@zurich.ibm.com>
2025-05-08 16:31:10 +02:00
Michele Dolfi
8406fb9b59 fix: usage of hashlib for FIPS (#171)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-05-02 15:00:10 +02:00
github-actions[bot]
a2dcb0a20f chore: bump version to 0.10.1 [skip ci] 2025-04-30 16:04:30 +00:00
Michele Dolfi
36787bc061 fix: avoid missing specialized keys in the options hash (#166)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-30 13:14:34 +02:00
Michele Dolfi
509f4889f8 fix: allow users to set the area threshold for picture descriptions (#165)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
2025-04-30 12:37:24 +02:00
Michele Dolfi
919cf5c041 fix: expose max wait time in sync endpoints (#164)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-30 12:30:11 +02:00
Michele Dolfi
35c2630c61 fix: add flash-attn for cuda images (#161)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-29 16:58:33 +02:00
github-actions[bot]
382d675631 chore: bump version to 0.10.0 [skip ci] 2025-04-28 10:06:42 +00:00
Michele Dolfi
c65f3c654c feat: add support for file upload and return as file in async endpoints (#152)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-28 11:18:19 +02:00
nkh0472
829effec1a docs: fix new default pdf_backend (#158)
Signed-off-by: nkh0472 <67589323+nkh0472@users.noreply.github.com>
2025-04-28 09:46:13 +02:00
nkh0472
494d66f992 chore: typo fix (#156)
Signed-off-by: nkh0472 <67589323+nkh0472@users.noreply.github.com>
2025-04-28 08:41:26 +02:00
Quang Nam Ta
14bafb2628 docs: fixing small typo in docs (#155)
Signed-off-by: Quang Nam Ta <work.quangnamta@gmail.com>
2025-04-28 08:35:40 +02:00
github-actions[bot]
37e2e1ad09 chore: bump version to 0.9.0 [skip ci] 2025-04-25 07:56:40 +00:00
Michele Dolfi
71c5fae505 fix: produce image artifacts in referenced mode (#151)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-24 17:33:36 +02:00
Michele Dolfi
91956cbf4e docs: vlm and picture description options (#149)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-24 14:42:06 +02:00
Michele Dolfi
4c9571a052 feat: expose picture description options (#148)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
2025-04-24 13:49:44 +02:00
Tiago Santana
41624af09f test: add tests with fastapi client (#147)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-04-24 10:25:29 +02:00
Michele Dolfi
26bef5bec0 feat: Add parameters for Kubeflow pipeline engine (WIP) (#107)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-23 14:59:53 +02:00
github-actions[bot]
40bb21d347 chore: bump version to 0.8.0 [skip ci] 2025-04-22 13:04:33 +00:00
Michele Dolfi
ee89ee4dae feat: Add option for vlm pipeline (#143)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-22 14:46:33 +02:00
Michele Dolfi
6b3d281f02 feat: Expose more conversion options (#142)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-22 10:41:47 +02:00
Tiago Santana
b598872e5c feat(UI): change UI to use async endpoints (#131)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-19 19:59:07 +02:00
Michele Dolfi
087417e5c2 docs: fix required permissions for oauth2-proxy requests (#141)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-19 18:46:28 +02:00
Michele Dolfi
57f9073bc0 fix(UI): use https when calling the api (#139)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-19 17:35:54 +02:00
Rui Dias Gomes
525a43ff6f docs: update deployment examples (#135)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
Signed-off-by: Rui Dias Gomes <66125272+rmdg88@users.noreply.github.com>
2025-04-17 14:29:34 +02:00
Michele Dolfi
c1ce4719c9 fix: fix permissions in docker image (#136)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-04-17 14:27:43 +02:00
Kasper Dinkla
5dfb75d3b9 fix: picture caption visuals (#129)
Signed-off-by: DKL <dkl@zurich.ibm.com>
2025-04-15 13:17:00 +02:00
Michele Dolfi
420162e674 docs: fix image tag (#124)
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
2025-04-11 16:19:39 +02:00
github-actions[bot]
ff75bab21b chore: bump version to 0.7.0 [skip ci] 2025-03-31 13:44:01 +00:00
Michele Dolfi
7a0fabae07 feat: Expose TLS settings and example deploy with oauth-proxy (#112)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-31 14:51:30 +02:00
Maxim Lysak
9ffe49a359 chore: Readme picture (#108)
Signed-off-by: Maksym Lysak <mly@zurich.ibm.com>
Co-authored-by: Maksym Lysak <mly@zurich.ibm.com>
2025-03-31 08:29:09 -04:00
Michele Dolfi
68772bb6f0 feat: Offline static files (#109)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-26 18:54:54 -04:00
Michele Dolfi
20ec87a63a feat: Update to Docling 2.28 (#106)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-24 20:00:25 -04:00
Eugene
e30f458923 fix: Move ARGs to prevent cache invalidation (#104)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-03-22 12:31:42 +01:00
github-actions[bot]
03e405638f chore: bump version to 0.6.0 [skip ci] 2025-03-17 12:43:23 +00:00
Michele Dolfi
fd8e40a008 docs: simplify README and move details to docs (#102)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-17 13:40:12 +01:00
Michele Dolfi
422c402bab fix: allow changes in CORS settings (#100)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-17 09:49:17 +01:00
Michele Dolfi
ea090288d3 fix: avoid exploding options cache using lru and expose size parameter (#101)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-17 08:52:29 +01:00
Michele Dolfi
07c48edd5d fix: increase timeout_keep_alive and allow parameter changes (#98)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-16 09:03:40 +01:00
Michele Dolfi
a212547d28 fix: add warning when using incompatible parameters (#99)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-16 09:03:22 +01:00
Michele Dolfi
c76daac70c fix(ui): use --port parameter and avoid failing when image is not found (#97)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-16 09:02:53 +01:00
Michele Dolfi
7994b19b9f chore: move to docling-project gh org (#95)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-14 14:04:31 +01:00
Tiago Santana
ec57b528ed feat: expose options for new features (#92)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-03-13 17:09:59 +01:00
github-actions[bot]
b92c5d8899 chore: bump version to 0.5.1 [skip ci] 2025-03-10 17:31:51 +00:00
Eugene
3c9825df30 ci: Speed up python linting (#64)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-03-10 18:05:33 +01:00
Michele Dolfi
8dd0e216fd chore: extend timeout for downloading the model artifacts (#90)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-10 16:58:10 +01:00
Michele Dolfi
d406802f9d chore: update uv.lock with new release version (#89)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-10 16:57:48 +01:00
Michele Dolfi
a92ad48b28 fix: submodules in wheels (#85)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-10 16:19:34 +01:00
Eugene
da2b26099d chore: Remove unused OS deps (#80)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-03-10 08:53:25 +01:00
github-actions[bot]
98b46eda50 chore: bump version to 0.5.0 [skip ci] 2025-03-07 17:24:16 +00:00
Michele Dolfi
7e75919ae8 chore: Remove deprecated type aliases and run as pre-commit (#79)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-07 15:46:52 +01:00
Eugene
c95db36438 fix: Remove uv from image, merge ARG and ENV declarations (#57)
Signed-off-by: Eugene <fogaprod@gmail.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-07 15:33:21 +01:00
Michele Dolfi
82f8900197 feat: Async api (#60)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-07 11:26:50 +01:00
Eugene
ed851c95fe feat: display version in fastapi docs (#78)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-03-07 09:28:05 +01:00
Steffen Röcker
05df0735d3 fix(docs): Remove comma in convert/source curl example (#73)
Signed-off-by: Steffen Röcker <sroecker@redhat.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-03-06 08:12:09 +01:00
github-actions[bot]
cad1053e36 chore: bump version to 0.4.0 [skip ci] 2025-02-26 13:05:03 +00:00
Michele Dolfi
7e6d9cdef3 feat: New container images (#68)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-26 12:49:20 +01:00
Brent Salisbury
343b985287 Readme additions for running
Readme additions for a quickstart running of docling-serve

Signed-off-by: Brent Salisbury <bsalisbu@redhat.com>
2025-02-25 14:49:50 -08:00
Kasper Dinkla
c430d9b1a1 feat: Render DoclingDocument with npm docling-components in the example UI (#65)
Signed-off-by: DKL <dkl@zurich.ibm.com>
2025-02-25 11:27:42 +01:00
Anil Vishnoi
63141f1cc7 ci: Use release event to trigger the image publishing job for releases (#63)
Signed-off-by: Anil Vishnoi <vishnoianil@gmail.com>
2025-02-24 08:21:17 +01:00
Eugene
d5557fad9f refactor: Use bytes as options key (#58)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-02-21 18:03:27 +01:00
İlker SIĞIRCI
36967f7f61 chore(config): replace black,isort,flake and autoflake with ruff (#55)
Signed-off-by: ilker.sigirci <ilker.sigirci@data-boss.com.tr>
Signed-off-by: ilkersigirci <sigirci.ilker@mgail.com>
Co-authored-by: ilker.sigirci <ilker.sigirci@data-boss.com.tr>
2025-02-20 13:29:41 +01:00
github-actions[bot]
3b54d9b6ef chore: bump version to 0.3.0 [skip ci] 2025-02-19 21:22:27 +00:00
Michele Dolfi
4877248368 fix: set DOCLING_SERVE_ARTIFACTS_PATH in images (#53)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-19 22:03:56 +01:00
Michele Dolfi
ec33a61faa feat: Add new docling-serve cli (#50)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-19 20:54:13 +01:00
Eugene
663e03303a chore: use uv in start_server.sh and update docs (#49)
Signed-off-by: Eugene <fogaprod@gmail.com>
2025-02-19 19:25:00 +01:00
Guillaume Moutier
c64a450bf9 fix: Set root UI path when behind proxy (#38)
Signed-off-by: Guillaume Moutier <3944034+guimou@users.noreply.github.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Guillaume Moutier <3944034+guimou@users.noreply.github.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-19 10:32:43 +01:00
Michele Dolfi
ae3b4906f1 fix: support python 3.13 and docling updates and switch to uv (#48)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-19 09:53:07 +01:00
Michele Dolfi
7a351fcdea fix missing secrets inherit
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-13 17:02:01 +00:00
Michele Dolfi
1615f977a2 ci: add semantic release and build/publish python wheel (#41)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-02-13 16:49:43 +01:00
Guillaume Moutier
1bf487b18e Fix main when workers > 1 (#35)
Always load the app by using an import string

Signed-off-by: Guillaume Moutier <3944034+guimou@users.noreply.github.com>
Co-authored-by: Guillaume Moutier <3944034+guimou@users.noreply.github.com>
2025-02-12 09:54:49 +01:00
82 changed files with 13165 additions and 6569 deletions

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@@ -1,3 +1,3 @@
TESSDATA_PREFIX=/usr/share/tesseract/tessdata/
UVICORN_WORKERS=2
RELOAD=True
UVICORN_RELOAD=True

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@@ -1,7 +0,0 @@
[flake8]
max-line-length = 88
exclude = test/*
max-complexity = 18
docstring-convention = google
ignore = W503,E203
classmethod-decorators = classmethod,validator

12
.github/PULL_REQUEST_TEMPLATE.md vendored Normal file
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@@ -0,0 +1,12 @@
<!-- Thank you for contributing to Docling! -->
<!-- STEPS TO FOLLOW:
1. Add a description of the changes (frequently the same as the commit description)
2. Enter the issue number next to "Resolves #" below (if there is no tracking issue resolved, **remove that section**)
3. Make sure the PR title follows the **Commit Message Formatting**: https://www.conventionalcommits.org/en/v1.0.0/#summary.
-->
<!-- Uncomment this section with the issue number if an issue is being resolved
**Issue resolved by this Pull Request:**
Resolves #
--->

23
.github/SECURITY.md vendored Normal file
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@@ -0,0 +1,23 @@
# Security and Disclosure Information Policy for the Docling Project
The Docling team and community take security bugs seriously. We appreciate your efforts to responsibly disclose your findings, and will make every effort to acknowledge your contributions.
## Reporting a Vulnerability
If you think you've identified a security issue in an Docling project repository, please DO NOT report the issue publicly via the GitHub issue tracker, etc.
Instead, send an email with as many details as possible to [deepsearch-core@zurich.ibm.com](mailto:deepsearch-core@zurich.ibm.com). This is a private mailing list for the maintainers team.
Please do not create a public issue.
## Security Vulnerability Response
Each report is acknowledged and analyzed by the core maintainers within 3 working days.
Any vulnerability information shared with core maintainers stays within the Docling project and will not be disseminated to other projects unless it is necessary to get the issue fixed.
After the initial reply to your report, the security team will keep you informed of the progress towards a fix and full announcement, and may ask for additional information or guidance.
## Security Alerts
We will send announcements of security vulnerabilities and steps to remediate on the [Docling announcements](https://github.com/docling-project/docling/discussions/categories/announcements).

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@@ -1,19 +0,0 @@
name: 'Set up Poetry and install'
description: 'Set up a specific version of Poetry and install dependencies using caching.'
inputs:
python-version:
description: "Version range or exact version of Python or PyPy to use, using SemVer's version range syntax."
default: '3.11'
runs:
using: 'composite'
steps:
- name: Install poetry
run: pipx install poetry==1.8.3
shell: bash
- uses: actions/setup-python@v4
with:
python-version: ${{ inputs.python-version }}
cache: 'poetry'
- name: Install dependencies
run: poetry install --all-extras
shell: bash

2
.github/dco.yml vendored Normal file
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@@ -0,0 +1,2 @@
allowRemediationCommits:
individual: true

9
.github/mergify.yml vendored Normal file
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@@ -0,0 +1,9 @@
merge_protections:
- name: Enforce conventional commit
description: Make sure that we follow https://www.conventionalcommits.org/en/v1.0.0/
if:
- base = main
success_conditions:
- "title ~=
^(fix|feat|docs|style|refactor|perf|test|build|ci|chore|revert)(?:\\(.+\
\\))?(!)?:"

40
.github/scripts/release.sh vendored Executable file
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@@ -0,0 +1,40 @@
#!/bin/bash
set -e # trigger failure on error - do not remove!
set -x # display command on output
if [ -z "${TARGET_VERSION}" ]; then
>&2 echo "No TARGET_VERSION specified"
exit 1
fi
CHGLOG_FILE="${CHGLOG_FILE:-CHANGELOG.md}"
# update package version
uvx --from=toml-cli toml set --toml-path=pyproject.toml project.version "${TARGET_VERSION}"
uv lock --upgrade-package docling-serve
# collect release notes
REL_NOTES=$(mktemp)
uv run --no-sync semantic-release changelog --unreleased >> "${REL_NOTES}"
# update changelog
TMP_CHGLOG=$(mktemp)
TARGET_TAG_NAME="v${TARGET_VERSION}"
RELEASE_URL="$(gh repo view --json url -q ".url")/releases/tag/${TARGET_TAG_NAME}"
printf "## [${TARGET_TAG_NAME}](${RELEASE_URL}) - $(date -Idate)\n\n" >> "${TMP_CHGLOG}"
cat "${REL_NOTES}" >> "${TMP_CHGLOG}"
if [ -f "${CHGLOG_FILE}" ]; then
printf "\n" | cat - "${CHGLOG_FILE}" >> "${TMP_CHGLOG}"
fi
mv "${TMP_CHGLOG}" "${CHGLOG_FILE}"
# push changes
git config --global user.name 'github-actions[bot]'
git config --global user.email 'github-actions[bot]@users.noreply.github.com'
git add pyproject.toml uv.lock "${CHGLOG_FILE}"
COMMIT_MSG="chore: bump version to ${TARGET_VERSION} [skip ci]"
git commit -m "${COMMIT_MSG}"
git push origin main
# create GitHub release (incl. Git tag)
gh release create "${TARGET_TAG_NAME}" -F "${REL_NOTES}"

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@@ -0,0 +1,39 @@
[Dd]ocling
precommit
asgi
async
(?i)urls
uvicorn
[Ww]ebserver
RQ
(?i)url
keyfile
[Ww]ebsocket(s?)
[Kk]ubernetes
UI
(?i)vllm
APIs
[Ss]ubprocesses
(?i)api
Kubeflow
(?i)Jobkit
(?i)cpu
(?i)PyTorch
(?i)CUDA
(?i)NVIDIA
(?i)ROCm
(?i)env
Gradio
Podman
bool
Ollama
inbody
LGTMs
Dolfi
Lysak
Nikos
Nassar
Panos
Vagenas
Staar
Livathinos

11
.github/vale.ini vendored Normal file
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@@ -0,0 +1,11 @@
StylesPath = styles
MinAlertLevel = suggestion
; Packages = write-good, proselint
Vocab = Docling
[*.md]
BasedOnStyles = Vale
[CHANGELOG.md]
BasedOnStyles =

59
.github/workflows/cd.yml vendored Normal file
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@@ -0,0 +1,59 @@
name: "Run CD"
on:
workflow_dispatch:
jobs:
code-checks:
uses: ./.github/workflows/job-checks.yml
pre-release-check:
runs-on: ubuntu-latest
outputs:
TARGET_TAG_V: ${{ steps.version_check.outputs.TRGT_VERSION }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0 # for fetching tags, required for semantic-release
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
- name: Install dependencies
run: uv sync --only-dev
- name: Check version of potential release
id: version_check
run: |
TRGT_VERSION=$(uv run --no-sync semantic-release print-version)
echo "TRGT_VERSION=${TRGT_VERSION}" >> "$GITHUB_OUTPUT"
echo "${TRGT_VERSION}"
- name: Check notes of potential release
run: uv run --no-sync semantic-release changelog --unreleased
release:
needs: [code-checks, pre-release-check]
if: needs.pre-release-check.outputs.TARGET_TAG_V != ''
environment: auto-release
runs-on: ubuntu-latest
concurrency: release
steps:
- uses: actions/create-github-app-token@v1
id: app-token
with:
app-id: ${{ vars.CI_APP_ID }}
private-key: ${{ secrets.CI_PRIVATE_KEY }}
- uses: actions/checkout@v4
with:
token: ${{ steps.app-token.outputs.token }}
fetch-depth: 0 # for fetching tags, required for semantic-release
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
- name: Install dependencies
run: uv sync --only-dev
- name: Run release script
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
TARGET_VERSION: ${{ needs.pre-release-check.outputs.TARGET_TAG_V }}
CHGLOG_FILE: CHANGELOG.md
run: ./.github/scripts/release.sh
shell: bash

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@@ -1,34 +0,0 @@
name: Run linter checks
on:
push:
branches: ["main"]
pull_request:
branches: ["main"]
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
py-lint:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.11']
steps:
- uses: actions/checkout@v4
- uses: ./.github/actions/setup-poetry
with:
python-version: ${{ matrix.python-version }}
- name: Run styling check
run: poetry run pre-commit run --all-files
markdown-lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: markdownlint-cli2-action
uses: DavidAnson/markdownlint-cli2-action@v16
with:
globs: "**/*.md"

53
.github/workflows/ci-images-dryrun.yml vendored Normal file
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@@ -0,0 +1,53 @@
name: Dry run docling-serve image building
on:
workflow_call:
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
build_image:
name: Build ${{ matrix.spec.name }} container image
strategy:
matrix:
spec:
- name: docling-project/docling-serve
build_args: |
UV_SYNC_EXTRA_ARGS=--no-extra flash-attn
platforms: linux/amd64, linux/arm64
- name: docling-project/docling-serve-cpu
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cpu --no-extra flash-attn
platforms: linux/amd64, linux/arm64
# - name: docling-project/docling-serve-cu124
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
# platforms: linux/amd64
- name: docling-project/docling-serve-cu126
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu126
platforms: linux/amd64
- name: docling-project/docling-serve-cu128
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu128
platforms: linux/amd64
# - name: docling-project/docling-serve-rocm
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn
# platforms: linux/amd64
permissions:
packages: write
contents: read
attestations: write
id-token: write
uses: ./.github/workflows/job-image.yml
with:
publish: false
build_args: ${{ matrix.spec.build_args }}
ghcr_image_name: ${{ matrix.spec.name }}
quay_image_name: ""
platforms: ${{ matrix.spec.platforms }}

25
.github/workflows/ci.yml vendored Normal file
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@@ -0,0 +1,25 @@
name: "Run CI"
on:
push:
branches: ["main"]
pull_request:
branches: ["main"]
jobs:
code-checks:
# if: ${{ github.event_name == 'push' || (github.event.pull_request.head.repo.full_name != 'docling-project/docling-serve' && github.event.pull_request.head.repo.full_name != 'docling-project/docling-serve') }}
uses: ./.github/workflows/job-checks.yml
permissions:
packages: write
contents: read
attestations: write
id-token: write
build-images:
uses: ./.github/workflows/ci-images-dryrun.yml
permissions:
packages: write
contents: read
attestations: write
id-token: write

192
.github/workflows/dco-advisor.yml vendored Normal file
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@@ -0,0 +1,192 @@
name: DCO Advisor Bot
on:
pull_request_target:
types: [opened, reopened, synchronize]
permissions:
pull-requests: write
issues: write
jobs:
dco_advisor:
runs-on: ubuntu-latest
steps:
- name: Handle DCO check result
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const pr = context.payload.pull_request || context.payload.check_run?.pull_requests?.[0];
if (!pr) return;
const prNumber = pr.number;
const baseRef = pr.base.ref;
const headSha =
context.payload.check_run?.head_sha ||
pr.head?.sha;
const username = pr.user.login;
console.log("HEAD SHA:", headSha);
const sleep = ms => new Promise(resolve => setTimeout(resolve, ms));
// Poll until DCO check has a conclusion (max 6 attempts, 30s)
let dcoCheck = null;
for (let attempt = 0; attempt < 6; attempt++) {
const { data: checks } = await github.rest.checks.listForRef({
owner: context.repo.owner,
repo: context.repo.repo,
ref: headSha
});
console.log("All check runs:");
checks.check_runs.forEach(run => {
console.log(`- ${run.name} (${run.status}/${run.conclusion}) @ ${run.head_sha}`);
});
dcoCheck = checks.check_runs.find(run =>
run.name.toLowerCase().includes("dco") &&
!run.name.toLowerCase().includes("dco_advisor") &&
run.head_sha === headSha
);
if (dcoCheck?.conclusion) break;
console.log(`Waiting for DCO check... (${attempt + 1})`);
await sleep(5000); // wait 5 seconds
}
if (!dcoCheck || !dcoCheck.conclusion) {
console.log("DCO check did not complete in time.");
return;
}
const isFailure = ["failure", "action_required"].includes(dcoCheck.conclusion);
console.log(`DCO check conclusion for ${headSha}: ${dcoCheck.conclusion} (treated as ${isFailure ? "failure" : "success"})`);
// Parse DCO output for commit SHAs and author
let badCommits = [];
let authorName = "";
let authorEmail = "";
let moreInfo = `More info: [DCO check report](${dcoCheck?.html_url})`;
if (isFailure) {
const { data: commits } = await github.rest.pulls.listCommits({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: prNumber,
});
for (const commit of commits) {
const commitMessage = commit.commit.message;
const signoffMatch = commitMessage.match(/^Signed-off-by:\s+.+<.+>$/m);
if (!signoffMatch) {
console.log(`Bad commit found ${commit.sha}`)
badCommits.push({
sha: commit.sha,
authorName: commit.commit.author.name,
authorEmail: commit.commit.author.email,
});
}
}
}
// If multiple authors are present, you could adapt the message accordingly
// For now, we'll just use the first one
if (badCommits.length > 0) {
authorName = badCommits[0].authorName;
authorEmail = badCommits[0].authorEmail;
}
// Generate remediation commit message if needed
let remediationSnippet = "";
if (badCommits.length && authorEmail) {
remediationSnippet = `git commit --allow-empty -s -m "DCO Remediation Commit for ${authorName} <${authorEmail}>\n\n` +
badCommits.map(c => `I, ${c.authorName} <${c.authorEmail}>, hereby add my Signed-off-by to this commit: ${c.sha}`).join('\n') +
`"`;
} else {
remediationSnippet = "# Unable to auto-generate remediation message. Please check the DCO check details.";
}
// Build comment
const commentHeader = '<!-- dco-advice-bot -->';
let body = "";
if (isFailure) {
body = [
commentHeader,
'❌ **DCO Check Failed**',
'',
`Hi @${username}, your pull request has failed the Developer Certificate of Origin (DCO) check.`,
'',
'This repository supports **remediation commits**, so you can fix this without rewriting history — but you must follow the required message format.',
'',
'---',
'',
'### 🛠 Quick Fix: Add a remediation commit',
'Run this command:',
'',
'```bash',
remediationSnippet,
'git push',
'```',
'',
'---',
'',
'<details>',
'<summary>🔧 Advanced: Sign off each commit directly</summary>',
'',
'**For the latest commit:**',
'```bash',
'git commit --amend --signoff',
'git push --force-with-lease',
'```',
'',
'**For multiple commits:**',
'```bash',
`git rebase --signoff origin/${baseRef}`,
'git push --force-with-lease',
'```',
'',
'</details>',
'',
moreInfo
].join('\n');
} else {
body = [
commentHeader,
'✅ **DCO Check Passed**',
'',
`Thanks @${username}, all your commits are properly signed off. 🎉`
].join('\n');
}
// Get existing comments on the PR
const { data: comments } = await github.rest.issues.listComments({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: prNumber
});
// Look for a previous bot comment
const existingComment = comments.find(c =>
c.body.includes("<!-- dco-advice-bot -->")
);
if (existingComment) {
await github.rest.issues.updateComment({
owner: context.repo.owner,
repo: context.repo.repo,
comment_id: existingComment.id,
body: body
});
} else {
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: prNumber,
body: body
});
}

View File

@@ -1,105 +0,0 @@
name: Dry run docling-serve image building
on:
pull_request:
branches: ["main"]
env:
GHCR_REGISTRY: ghcr.io
GHCR_DOCLING_SERVE_CPU_IMAGE_NAME: ds4sd/docling-serve-cpu
GHCR_DOCLING_SERVE_GPU_IMAGE_NAME: ds4sd/docling-serve
jobs:
build_cpu_image:
name: Build docling-serve "CPU only" container image
runs-on: ubuntu-latest
permissions:
packages: write
contents: read
attestations: write
id-token: write
steps:
- name: Check out the repo
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-${{ github.sha }}
restore-keys: |
${{ runner.os }}-buildx-
- name: Extract metadata (tags, labels) for docling-serve (CPU only) ghcr image
id: ghcr_serve_cpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_CPU_IMAGE_NAME }}
- name: Build docling-serve-cpu image
id: build-serve-cpu-ghcr
uses: docker/build-push-action@v5
with:
context: .
push: false
tags: ${{ steps.ghcr_serve_cpu_meta.outputs.tags }}
labels: ${{ steps.ghcr_serve_cpu_meta.outputs.labels }}
platforms: linux/amd64, linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=true
- name: Remove Local Docker Images
run: |
docker image prune -af
build_gpu_image:
name: Build docling-serve (with GPU support) container image
runs-on: ubuntu-latest
permissions:
packages: write
contents: read
attestations: write
id-token: write
steps:
- name: Check out the repo
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-${{ github.sha }}
restore-keys: |
${{ runner.os }}-buildx-
- name: Extract metadata (tags, labels) for docling-serve (GPU) ghcr image
id: ghcr_serve_gpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_GPU_IMAGE_NAME }}
- name: Build docling-serve (GPU) image
id: build-serve-gpu-ghcr
uses: docker/build-push-action@v5
with:
context: .
push: false
tags: ${{ steps.ghcr_serve_gpu_meta.outputs.tags }}
labels: ${{ steps.ghcr_serve_gpu_meta.outputs.labels }}
platforms: linux/amd64,linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=false

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@@ -4,193 +4,55 @@ on:
push:
branches:
- main
tags:
- 'v*'
release:
types: [published]
env:
GHCR_REGISTRY: ghcr.io
GHCR_DOCLING_SERVE_CPU_IMAGE_NAME: ds4sd/docling-serve-cpu
GHCR_DOCLING_SERVE_GPU_IMAGE_NAME: ds4sd/docling-serve
QUAY_REGISTRY: quay.io
QUAY_DOCLING_SERVE_CPU_IMAGE_NAME: ds4sd/docling-serve-cpu
QUAY_DOCLING_SERVE_GPU_IMAGE_NAME: ds4sd/docling-serve
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
build_and_publish_cpu_images:
name: Push docling-serve "CPU only" container image to GHCR and QUAY
runs-on: ubuntu-latest
environment: registry-creds
build_and_publish_images:
name: Build and push ${{ matrix.spec.name }} container image to GHCR and QUAY
strategy:
matrix:
spec:
- name: docling-project/docling-serve
build_args: |
UV_SYNC_EXTRA_ARGS=--no-extra flash-attn
platforms: linux/amd64, linux/arm64
- name: docling-project/docling-serve-cpu
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cpu --no-extra flash-attn
platforms: linux/amd64, linux/arm64
# - name: docling-project/docling-serve-cu124
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
# platforms: linux/amd64
- name: docling-project/docling-serve-cu126
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu126
platforms: linux/amd64
- name: docling-project/docling-serve-cu128
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu128
platforms: linux/amd64
# - name: docling-project/docling-serve-rocm
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn
# platforms: linux/amd64
permissions:
packages: write
contents: read
attestations: write
id-token: write
secrets: inherit
steps:
- name: Check out the repo
uses: actions/checkout@v4
- name: Log in to the GHCR container image registry
uses: docker/login-action@v3
with:
registry: ${{ env.GHCR_REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Log in to the Quay container image registry
uses: docker/login-action@v3
with:
registry: ${{ env.QUAY_REGISTRY }}
username: ${{ secrets.QUAY_USERNAME }}
password: ${{ secrets.QUAY_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-${{ github.sha }}
restore-keys: |
${{ runner.os }}-buildx-
- name: Extract metadata (tags, labels) for docling-serve (CPU only) ghcr image
id: ghcr_serve_cpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_CPU_IMAGE_NAME }}
- name: Build and push docling-serve-cpu image to ghcr.io
id: push-serve-cpu-ghcr
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.ghcr_serve_cpu_meta.outputs.tags }}
labels: ${{ steps.ghcr_serve_cpu_meta.outputs.labels }}
platforms: linux/amd64, linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=true
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v1
with:
subject-name: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_CPU_IMAGE_NAME}}
subject-digest: ${{ steps.push-serve-cpu-ghcr.outputs.digest }}
push-to-registry: true
- name: Extract metadata (tags, labels) for docling-serve (CPU only) quay image
id: quay_serve_cpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.QUAY_REGISTRY }}/${{ env.QUAY_DOCLING_SERVE_CPU_IMAGE_NAME }}
- name: Build and push docling-serve-cpu image to quay.io
id: push-serve-cpu-quay
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.quay_serve_cpu_meta.outputs.tags }}
labels: ${{ steps.quay_serve_cpu_meta.outputs.labels }}
platforms: linux/amd64, linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=true
- name: Remove Local Docker Images
run: |
docker image prune -af
build_and_publish_gpu_images:
name: Push docling-serve (with GPU support) container image to GHCR and QUAY
runs-on: ubuntu-latest
environment: registry-creds
permissions:
packages: write
contents: read
attestations: write
id-token: write
steps:
- name: Check out the repo
uses: actions/checkout@v4
- name: Log in to the GHCR container image registry
uses: docker/login-action@v3
with:
registry: ${{ env.GHCR_REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Log in to the Quay container image registry
uses: docker/login-action@v3
with:
registry: ${{ env.QUAY_REGISTRY }}
username: ${{ secrets.QUAY_USERNAME }}
password: ${{ secrets.QUAY_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-${{ github.sha }}
restore-keys: |
${{ runner.os }}-buildx-
- name: Extract metadata (tags, labels) for docling-serve (GPU) ghcr image
id: ghcr_serve_gpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_GPU_IMAGE_NAME }}
- name: Build and push docling-serve (GPU) image to ghcr.io
id: push-serve-gpu-ghcr
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.ghcr_serve_gpu_meta.outputs.tags }}
labels: ${{ steps.ghcr_serve_gpu_meta.outputs.labels }}
platforms: linux/amd64,linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=false
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v1
with:
subject-name: ${{ env.GHCR_REGISTRY }}/${{ env.GHCR_DOCLING_SERVE_GPU_IMAGE_NAME}}
subject-digest: ${{ steps.push-serve-gpu-ghcr.outputs.digest }}
push-to-registry: true
- name: Extract metadata (tags, labels) for docling-serve (GPU) quay image
id: quay_serve_gpu_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.QUAY_REGISTRY }}/${{ env.QUAY_DOCLING_SERVE_GPU_IMAGE_NAME }}
- name: Build and push docling-serve (GPU) image to quay.io
id: push-serve-gpu-quay
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.quay_serve_gpu_meta.outputs.tags }}
labels: ${{ steps.quay_serve_gpu_meta.outputs.labels }}
platforms: linux/amd64,linux/arm64
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: |
--build-arg CPU_ONLY=false
uses: ./.github/workflows/job-image.yml
with:
publish: true
environment: registry-creds
build_args: ${{ matrix.spec.build_args }}
ghcr_image_name: ${{ matrix.spec.name }}
quay_image_name: ${{ matrix.spec.name }}
platforms: ${{ matrix.spec.platforms }}

29
.github/workflows/job-build.yml vendored Normal file
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@@ -0,0 +1,29 @@
name: Run checks
on:
workflow_call:
jobs:
build-package:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.12']
steps:
- uses: actions/checkout@v4
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
- name: Install dependencies
run: uv sync --all-extras --no-extra flash-attn
- name: Build package
run: uv build
- name: Check content of wheel
run: unzip -l dist/*.whl
- name: Store the distribution packages
uses: actions/upload-artifact@v4
with:
name: python-package-distributions
path: dist/

68
.github/workflows/job-checks.yml vendored Normal file
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@@ -0,0 +1,68 @@
name: Run checks
on:
workflow_call:
jobs:
py-lint:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.12']
steps:
- uses: actions/checkout@v4
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
- name: pre-commit cache key
run: echo "PY=$(python -VV | sha256sum | cut -d' ' -f1)" >> "$GITHUB_ENV"
- uses: actions/cache@v4
with:
path: ~/.cache/pre-commit
key: pre-commit|${{ env.PY }}|${{ hashFiles('.pre-commit-config.yaml') }}
- name: Install dependencies
run: uv sync --frozen --all-extras --no-extra flash-attn
- name: Run styling check
run: uv run pre-commit run --all-files
build-package:
uses: ./.github/workflows/job-build.yml
test-package:
needs:
- build-package
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.12']
steps:
- name: Download all the dists
uses: actions/download-artifact@v4
with:
name: python-package-distributions
path: dist/
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
- name: Create virtual environment
run: uv venv
- name: Install package
run: uv pip install dist/*.whl
- name: Create the server
run: .venv/bin/python -c 'from docling_serve.app import create_app; create_app()'
markdown-lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: markdownlint-cli2-action
uses: DavidAnson/markdownlint-cli2-action@v16
with:
globs: "**/*.md"

141
.github/workflows/job-image.yml vendored Normal file
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@@ -0,0 +1,141 @@
name: Build docling-serve container image
on:
workflow_call:
inputs:
build_args:
type: string
description: "Extra build arguments for the build."
default: ""
ghcr_image_name:
type: string
description: "Name of the image for GHCR."
quay_image_name:
type: string
description: "Name of the image Quay."
platforms:
type: string
description: "Platform argument for building images."
default: linux/amd64, linux/arm64
publish:
type: boolean
description: "If true, the images will be published."
default: false
environment:
type: string
description: "GH Action environment"
default: ""
env:
GHCR_REGISTRY: ghcr.io
QUAY_REGISTRY: quay.io
jobs:
image:
runs-on: ubuntu-latest
permissions:
packages: write
contents: read
attestations: write
id-token: write
environment: ${{ inputs.environment }}
steps:
- name: Free up space in github runner
# Free space as indicated here : https://github.com/actions/runner-images/issues/2840#issuecomment-790492173
run: |
df -h
sudo rm -rf "/usr/local/share/boost"
sudo rm -rf "$AGENT_TOOLSDIRECTORY"
sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /usr/local/share/powershell /usr/share/swift /usr/local/.ghcup
# shellcheck disable=SC2046
sudo docker rmi "$(docker image ls -aq)" >/dev/null 2>&1 || true
df -h
- name: Check out the repo
uses: actions/checkout@v4
- name: Log in to the GHCR container image registry
if: ${{ inputs.publish }}
uses: docker/login-action@v3
with:
registry: ${{ env.GHCR_REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Log in to the Quay container image registry
if: ${{ inputs.publish }}
uses: docker/login-action@v3
with:
registry: ${{ env.QUAY_REGISTRY }}
username: ${{ secrets.QUAY_USERNAME }}
password: ${{ secrets.QUAY_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Cache Docker layers
uses: actions/cache@v4
with:
path: /tmp/.buildx-cache
key: ${{ runner.os }}-buildx-${{ github.sha }}
restore-keys: |
${{ runner.os }}-buildx-
- name: Extract metadata (tags, labels) for docling-serve ghcr image
id: ghcr_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.GHCR_REGISTRY }}/${{ inputs.ghcr_image_name }}
- name: Build and push image to ghcr.io
id: ghcr_push
uses: docker/build-push-action@v5
with:
context: .
push: ${{ inputs.publish }}
tags: ${{ steps.ghcr_meta.outputs.tags }}
labels: ${{ steps.ghcr_meta.outputs.labels }}
platforms: ${{ inputs.platforms}}
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
- name: Generate artifact attestation
if: ${{ inputs.publish }}
uses: actions/attest-build-provenance@v1
with:
subject-name: ${{ env.GHCR_REGISTRY }}/${{ inputs.ghcr_image_name }}
subject-digest: ${{ steps.ghcr_push.outputs.digest }}
push-to-registry: true
- name: Extract metadata (tags, labels) for docling-serve quay image
if: ${{ inputs.publish }}
id: quay_meta
uses: docker/metadata-action@v5
with:
images: ${{ env.QUAY_REGISTRY }}/${{ inputs.quay_image_name }}
- name: Build and push image to quay.io
if: ${{ inputs.publish }}
# id: push-serve-cpu-quay
uses: docker/build-push-action@v5
with:
context: .
push: ${{ inputs.publish }}
tags: ${{ steps.quay_meta.outputs.tags }}
labels: ${{ steps.quay_meta.outputs.labels }}
platforms: ${{ inputs.platforms}}
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
# - name: Inspect the image details
# run: |
# echo "${{ steps.ghcr_push.outputs.metadata }}"
- name: Remove Local Docker Images
run: |
docker image prune -af

34
.github/workflows/pypi.yml vendored Normal file
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@@ -0,0 +1,34 @@
name: "Build and publish package"
on:
release:
types: [published]
permissions:
contents: read
jobs:
build-package:
uses: ./.github/workflows/job-build.yml
build-and-publish:
needs:
- build-package
runs-on: ubuntu-latest
environment:
name: pypi
url: https://pypi.org/p/docling-serve # Replace <package-name> with your PyPI project name
permissions:
id-token: write # IMPORTANT: mandatory for trusted publishing
steps:
- name: Download all the dists
uses: actions/download-artifact@v4
with:
name: python-package-distributions
path: dist/
- name: Publish distribution 📦 to PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
# currently not working with reusable workflows
attestations: false

4
.gitignore vendored
View File

@@ -1,5 +1,7 @@
model_artifacts/
scratch/
.md-lint
actionlint
# Created by https://www.toptal.com/developers/gitignore/api/python,macos,virtualenv,pycharm,visualstudiocode,emacs,vim,jupyternotebooks
# Edit at https://www.toptal.com/developers/gitignore?templates=python,macos,virtualenv,pycharm,visualstudiocode,emacs,vim,jupyternotebooks
@@ -442,3 +444,5 @@ pip-selfcheck.json
# Makefile
.action-lint
.markdown-lint
cookies.txt

View File

@@ -3,6 +3,8 @@ config:
no-emphasis-as-header: false
first-line-heading: false
MD033:
allowed_elements: ["details", "summary"]
allowed_elements: ["details", "summary", "br", "a", "b", "p", "img"]
MD024:
siblings_only: true
globs:
- "**/*.md"

View File

@@ -1,49 +1,39 @@
fail_fast: true
repos:
- repo: local
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.9.6
hooks:
- id: system
name: Black
entry: poetry run black docling_serve tests
pass_filenames: false
language: system
files: '\.py$'
- repo: local
hooks:
- id: system
name: isort
entry: poetry run isort docling_serve tests
pass_filenames: false
language: system
files: '\.py$'
- repo: local
hooks:
- id: autoflake
name: autoflake
entry: poetry run autoflake docling_serve tests
pass_filenames: false
language: system
files: '\.py$'
- repo: local
hooks:
- id: system
name: flake8
entry: poetry run flake8 docling_serve
pass_filenames: false
language: system
files: '\.py$'
# Run the Ruff formatter.
- id: ruff-format
name: "Ruff formatter"
args: [--config=pyproject.toml]
files: '^(docling_serve|tests).*\.(py|ipynb)$'
# Run the Ruff linter.
- id: ruff
name: "Ruff linter"
args: [--exit-non-zero-on-fix, --fix, --config=pyproject.toml]
files: '^(docling_serve|tests).*\.(py|ipynb)$'
- repo: local
hooks:
- id: system
name: MyPy
entry: poetry run mypy docling_serve
entry: uv run --no-sync mypy docling_serve
pass_filenames: false
language: system
files: '\.py$'
- repo: local
- repo: https://github.com/errata-ai/vale
rev: v3.12.0 # Use latest stable version
hooks:
- id: system
name: Poetry check
entry: poetry check --lock
- id: vale
name: vale sync
pass_filenames: false
language: system
args: [sync, "--config=.github/vale.ini"]
- id: vale
name: Spell and Style Check with Vale
args: ["--config=.github/vale.ini"]
files: \.md$
- repo: https://github.com/astral-sh/uv-pre-commit
# uv version, https://github.com/astral-sh/uv-pre-commit/releases
rev: 0.8.3
hooks:
- id: uv-lock

1
.python-version Normal file
View File

@@ -0,0 +1 @@
3.12

287
CHANGELOG.md Normal file
View File

@@ -0,0 +1,287 @@
## [v1.3.1](https://github.com/docling-project/docling-serve/releases/tag/v1.3.1) - 2025-08-21
### Fix
* Configuration and performance fixes via upgrade of packages ([#328](https://github.com/docling-project/docling-serve/issues/328)) ([`f02dbc0`](https://github.com/docling-project/docling-serve/commit/f02dbc01449fe1caf3fb4a73c0a5f4adf8265faf))
### Documentation
* Fix parameter in api key docs ([#323](https://github.com/docling-project/docling-serve/issues/323)) ([`37fe022`](https://github.com/docling-project/docling-serve/commit/37fe02277b3e2358eced28e15b4360e7c82d3b43))
## [v1.3.0](https://github.com/docling-project/docling-serve/releases/tag/v1.3.0) - 2025-08-14
### Feature
* Add configuration option for apikey security ([#322](https://github.com/docling-project/docling-serve/issues/322)) ([`9a64410`](https://github.com/docling-project/docling-serve/commit/9a644105523d312431993ded8dd88e064550a5db))
* Add RQ engine ([#315](https://github.com/docling-project/docling-serve/issues/315)) ([`885f319`](https://github.com/docling-project/docling-serve/commit/885f319d3a3488a4090869560447437a4104f14e))
### Documentation
* Example of docling-serve deployment in the RQ engine mode ([#321](https://github.com/docling-project/docling-serve/issues/321)) ([`71edf41`](https://github.com/docling-project/docling-serve/commit/71edf4184960d8664ef9da20617e2d0f91793d36))
* Handling models in docling-serve ([#319](https://github.com/docling-project/docling-serve/issues/319)) ([`6e9aa8c`](https://github.com/docling-project/docling-serve/commit/6e9aa8c759220458281c7fe4c87443ac41023eee))
* Add Gradio cache usage ([#312](https://github.com/docling-project/docling-serve/issues/312)) ([`d584895`](https://github.com/docling-project/docling-serve/commit/d584895e1108d71a0f45deadcd3c669eb0a58133))
## [v1.2.2](https://github.com/docling-project/docling-serve/releases/tag/v1.2.2) - 2025-08-13
### Fix
* Update of transformers module to 4.55.1 ([#316](https://github.com/docling-project/docling-serve/issues/316)) ([`7692eb2`](https://github.com/docling-project/docling-serve/commit/7692eb26006fd4deaa021180c99e23a1b65de506))
## [v1.2.1](https://github.com/docling-project/docling-serve/releases/tag/v1.2.1) - 2025-08-13
### Fix
* Handling of vlm model options and update deps ([#314](https://github.com/docling-project/docling-serve/issues/314)) ([`8b470cb`](https://github.com/docling-project/docling-serve/commit/8b470cba8ef500c271eb84c8368c8a1a1a5a6d6a))
* Add missing response type in sync endpoints ([#309](https://github.com/docling-project/docling-serve/issues/309)) ([`8048f45`](https://github.com/docling-project/docling-serve/commit/8048f4589a91de2b2b391ab33a326efd1b29f25b))
### Documentation
* Update readme to use v1 ([#306](https://github.com/docling-project/docling-serve/issues/306)) ([`b3058e9`](https://github.com/docling-project/docling-serve/commit/b3058e91e0c56e27110eb50f22cbdd89640bf398))
* Update deployment examples to use v1 API ([#308](https://github.com/docling-project/docling-serve/issues/308)) ([`63da9ee`](https://github.com/docling-project/docling-serve/commit/63da9eedebae3ad31d04e65635e573194e413793))
* Fix typo in v1 migration instructions ([#307](https://github.com/docling-project/docling-serve/issues/307)) ([`b15dc25`](https://github.com/docling-project/docling-serve/commit/b15dc2529f78d68a475e5221c37408c3f77d8588))
## [v1.2.0](https://github.com/docling-project/docling-serve/releases/tag/v1.2.0) - 2025-08-07
### Feature
* Workers without shared models and convert params ([#304](https://github.com/docling-project/docling-serve/issues/304)) ([`db3fdb5`](https://github.com/docling-project/docling-serve/commit/db3fdb5bc1a0ae250afd420d737abc4071a7546c))
* Add rocm image build support and fix cuda ([#292](https://github.com/docling-project/docling-serve/issues/292)) ([`fd1b987`](https://github.com/docling-project/docling-serve/commit/fd1b987e8dc174f1a6013c003dde33e9acbae39a))
## [v1.1.0](https://github.com/docling-project/docling-serve/releases/tag/v1.1.0) - 2025-07-30
### Feature
* Add docling-mcp in the distribution ([#290](https://github.com/docling-project/docling-serve/issues/290)) ([`ecb1874`](https://github.com/docling-project/docling-serve/commit/ecb1874a507bef83d102e0e031e49fed34298637))
* Add 3.0 openapi endpoint ([#287](https://github.com/docling-project/docling-serve/issues/287)) ([`ec594d8`](https://github.com/docling-project/docling-serve/commit/ec594d84fe36df23e7d010a2fcf769856c43600b))
* Add new source and target ([#270](https://github.com/docling-project/docling-serve/issues/270)) ([`3771c1b`](https://github.com/docling-project/docling-serve/commit/3771c1b55403bd51966d07d8f760d5c4fbcc1760))
### Fix
* Referenced paths relative to zip root ([#289](https://github.com/docling-project/docling-serve/issues/289)) ([`1333f71`](https://github.com/docling-project/docling-serve/commit/1333f71c9c6495342b2169d574e921f828446f15))
## [v1.0.1](https://github.com/docling-project/docling-serve/releases/tag/v1.0.1) - 2025-07-21
### Fix
* Docling update v2.42.0 ([#277](https://github.com/docling-project/docling-serve/issues/277)) ([`8706706`](https://github.com/docling-project/docling-serve/commit/8706706e8797b0a06ec4baa7cf87988311be68b6))
### Documentation
* Typo in README ([#276](https://github.com/docling-project/docling-serve/issues/276)) ([`766adb2`](https://github.com/docling-project/docling-serve/commit/766adb248113c7bd5144d14b3c82929a2ad29f8e))
## [v1.0.0](https://github.com/docling-project/docling-serve/releases/tag/v1.0.0) - 2025-07-14
### Feature
* V1 api with list of sources and target ([#249](https://github.com/docling-project/docling-serve/issues/249)) ([`56e328b`](https://github.com/docling-project/docling-serve/commit/56e328baf76b4bb0476fc6ca820b52034e4f97bf))
* Use orchestrators from jobkit ([#248](https://github.com/docling-project/docling-serve/issues/248)) ([`daa924a`](https://github.com/docling-project/docling-serve/commit/daa924a77e56d063ef17347dfd8a838872a70529))
### Breaking
* v1 api with list of sources and target ([#249](https://github.com/docling-project/docling-serve/issues/249)) ([`56e328b`](https://github.com/docling-project/docling-serve/commit/56e328baf76b4bb0476fc6ca820b52034e4f97bf))
* use orchestrators from jobkit ([#248](https://github.com/docling-project/docling-serve/issues/248)) ([`daa924a`](https://github.com/docling-project/docling-serve/commit/daa924a77e56d063ef17347dfd8a838872a70529))
## [v0.16.1](https://github.com/docling-project/docling-serve/releases/tag/v0.16.1) - 2025-07-07
### Fix
* Upgrade deps including, docling v2.40.0 with locks in models init ([#264](https://github.com/docling-project/docling-serve/issues/264)) ([`bfde1a0`](https://github.com/docling-project/docling-serve/commit/bfde1a0991c2da53b72c4f131ff74fa10f6340de))
* Missing tesseract osd ([#263](https://github.com/docling-project/docling-serve/issues/263)) ([`eb3892e`](https://github.com/docling-project/docling-serve/commit/eb3892ee141eb2c941d580b095d8a266f2d2610c))
* Properly load models at boot ([#244](https://github.com/docling-project/docling-serve/issues/244)) ([`149a8cb`](https://github.com/docling-project/docling-serve/commit/149a8cb1c0a16c1e0b7d17f40b88b4d6e8f0109d))
### Documentation
* Fix typo ([#259](https://github.com/docling-project/docling-serve/issues/259)) ([`93b8471`](https://github.com/docling-project/docling-serve/commit/93b84712b2c6d180908a197847b52b217a7ff05f))
* Change the doc example ([#258](https://github.com/docling-project/docling-serve/issues/258)) ([`c45b937`](https://github.com/docling-project/docling-serve/commit/c45b93706466a073ab4a5c75aa8a267110873e26))
* Update typo ([#247](https://github.com/docling-project/docling-serve/issues/247)) ([`50e431f`](https://github.com/docling-project/docling-serve/commit/50e431f30fbffa33f43727417fe746d20cbb9d6b))
## [v0.16.0](https://github.com/docling-project/docling-serve/releases/tag/v0.16.0) - 2025-06-25
### Feature
* Package updates and more cuda images ([#229](https://github.com/docling-project/docling-serve/issues/229)) ([`30aca92`](https://github.com/docling-project/docling-serve/commit/30aca92298ab0d86bb4debcfcacb2dd8b9040a27))
### Documentation
* Update example resources and improve README ([#231](https://github.com/docling-project/docling-serve/issues/231)) ([`80755a7`](https://github.com/docling-project/docling-serve/commit/80755a7d5955f7d0c53df8e558fdd852dd1f5b75))
## [v0.15.0](https://github.com/docling-project/docling-serve/releases/tag/v0.15.0) - 2025-06-17
### Feature
* Use redocs and scalar as api docs ([#228](https://github.com/docling-project/docling-serve/issues/228)) ([`873d05a`](https://github.com/docling-project/docling-serve/commit/873d05aefe141c63b9c1cf53b23b4fa8c96de05d))
### Fix
* "tesserocr" instead of "tesseract_cli" in usage docs ([#223](https://github.com/docling-project/docling-serve/issues/223)) ([`196c5ce`](https://github.com/docling-project/docling-serve/commit/196c5ce42a04d77234a4212c3d9b9772d2c2073e))
## [v0.14.0](https://github.com/docling-project/docling-serve/releases/tag/v0.14.0) - 2025-06-17
### Feature
* Read supported file extensions from docling ([#214](https://github.com/docling-project/docling-serve/issues/214)) ([`524f6a8`](https://github.com/docling-project/docling-serve/commit/524f6a8997b86d2f869ca491ec8fb40585b42ca4))
### Fix
* Typo in Headline ([#220](https://github.com/docling-project/docling-serve/issues/220)) ([`d5455b7`](https://github.com/docling-project/docling-serve/commit/d5455b7f66de39ea1f8b8927b5968d2baa23ca88))
## [v0.13.0](https://github.com/docling-project/docling-serve/releases/tag/v0.13.0) - 2025-06-04
### Feature
* Upgrade docling to 2.36 ([#212](https://github.com/docling-project/docling-serve/issues/212)) ([`ffea347`](https://github.com/docling-project/docling-serve/commit/ffea34732b24fdd438fabd6df02d3d9ce66b4534))
## [v0.12.0](https://github.com/docling-project/docling-serve/releases/tag/v0.12.0) - 2025-06-03
### Feature
* Export annotations in markdown and html (Docling upgrade) ([#202](https://github.com/docling-project/docling-serve/issues/202)) ([`c4c41f1`](https://github.com/docling-project/docling-serve/commit/c4c41f16dff83c5d2a0b8a4c625b5de19b36b7c5))
### Fix
* Processing complex params in multipart-form ([#210](https://github.com/docling-project/docling-serve/issues/210)) ([`7066f35`](https://github.com/docling-project/docling-serve/commit/7066f3520a88c07df1c80a0cc6c4339eaac4d6a7))
### Documentation
* Add openshift replicasets examples ([#209](https://github.com/docling-project/docling-serve/issues/209)) ([`6a8190c`](https://github.com/docling-project/docling-serve/commit/6a8190c315792bd1e0e2b0af310656baaa5551e5))
## [v0.11.0](https://github.com/docling-project/docling-serve/releases/tag/v0.11.0) - 2025-05-23
### Feature
* Page break placeholder in markdown exports options ([#194](https://github.com/docling-project/docling-serve/issues/194)) ([`32b8a80`](https://github.com/docling-project/docling-serve/commit/32b8a809f348bf9fbde657f93589a56935d3749d))
* Clear results registry ([#192](https://github.com/docling-project/docling-serve/issues/192)) ([`de002df`](https://github.com/docling-project/docling-serve/commit/de002dfcdc111c942a08b156c84b7fa22b3fbaf3))
* Upgrade to Docling 2.33.0 ([#198](https://github.com/docling-project/docling-serve/issues/198)) ([`abe5aa0`](https://github.com/docling-project/docling-serve/commit/abe5aa03f54d44ecf5c6d76e3258028997a53e68))
* Api to trigger offloading the models ([#188](https://github.com/docling-project/docling-serve/issues/188)) ([`00be428`](https://github.com/docling-project/docling-serve/commit/00be4284904d55b78c75c5475578ef11c2ade94c))
* Figure annotations @ docling components 0.0.7 ([#181](https://github.com/docling-project/docling-serve/issues/181)) ([`3ff1b2f`](https://github.com/docling-project/docling-serve/commit/3ff1b2f9834aca37472a895a0e3da47560457d77))
### Fix
* Usage of hashlib for FIPS ([#171](https://github.com/docling-project/docling-serve/issues/171)) ([`8406fb9`](https://github.com/docling-project/docling-serve/commit/8406fb9b59d83247b8379974cabed497703dfc4d))
### Documentation
* Example and instructions on how to load model weights to persistent volume ([#197](https://github.com/docling-project/docling-serve/issues/197)) ([`3f090b7`](https://github.com/docling-project/docling-serve/commit/3f090b7d15eaf696611d89bbbba5b98569610828))
* Async api usage and fixes ([#195](https://github.com/docling-project/docling-serve/issues/195)) ([`21c1791`](https://github.com/docling-project/docling-serve/commit/21c1791e427f5b1946ed46c68dfda03c957dca8f))
## [v0.10.1](https://github.com/docling-project/docling-serve/releases/tag/v0.10.1) - 2025-04-30
### Fix
* Avoid missing specialized keys in the options hash ([#166](https://github.com/docling-project/docling-serve/issues/166)) ([`36787bc`](https://github.com/docling-project/docling-serve/commit/36787bc0616356a6199da618d8646de51636b34e))
* Allow users to set the area threshold for picture descriptions ([#165](https://github.com/docling-project/docling-serve/issues/165)) ([`509f488`](https://github.com/docling-project/docling-serve/commit/509f4889f8ed4c0f0ce25bec4126ef1f1199797c))
* Expose max wait time in sync endpoints ([#164](https://github.com/docling-project/docling-serve/issues/164)) ([`919cf5c`](https://github.com/docling-project/docling-serve/commit/919cf5c0414f2f11eb8012f451fed7a8f582b7ad))
* Add flash-attn for cuda images ([#161](https://github.com/docling-project/docling-serve/issues/161)) ([`35c2630`](https://github.com/docling-project/docling-serve/commit/35c2630c613cf229393fc67b6938152b063ff498))
## [v0.10.0](https://github.com/docling-project/docling-serve/releases/tag/v0.10.0) - 2025-04-28
### Feature
* Add support for file upload and return as file in async endpoints ([#152](https://github.com/docling-project/docling-serve/issues/152)) ([`c65f3c6`](https://github.com/docling-project/docling-serve/commit/c65f3c654c76c6b64b6aada1f0a153d74789d629))
### Documentation
* Fix new default pdf_backend ([#158](https://github.com/docling-project/docling-serve/issues/158)) ([`829effe`](https://github.com/docling-project/docling-serve/commit/829effec1a1b80320ccaf2c501be8015169b6fa3))
* Fixing small typo in docs ([#155](https://github.com/docling-project/docling-serve/issues/155)) ([`14bafb2`](https://github.com/docling-project/docling-serve/commit/14bafb26286b94f80b56846c50d6e9a6d99a9763))
## [v0.9.0](https://github.com/docling-project/docling-serve/releases/tag/v0.9.0) - 2025-04-25
### Feature
* Expose picture description options ([#148](https://github.com/docling-project/docling-serve/issues/148)) ([`4c9571a`](https://github.com/docling-project/docling-serve/commit/4c9571a052d5ec0044e49225bc5615e13cdb0a56))
* Add parameters for Kubeflow pipeline engine (WIP) ([#107](https://github.com/docling-project/docling-serve/issues/107)) ([`26bef5b`](https://github.com/docling-project/docling-serve/commit/26bef5bec060f0afd8d358816b68c3f2c0dd4bc2))
### Fix
* Produce image artifacts in referenced mode ([#151](https://github.com/docling-project/docling-serve/issues/151)) ([`71c5fae`](https://github.com/docling-project/docling-serve/commit/71c5fae505366459fd481d2ecdabc5ebed94d49c))
### Documentation
* Vlm and picture description options ([#149](https://github.com/docling-project/docling-serve/issues/149)) ([`91956cb`](https://github.com/docling-project/docling-serve/commit/91956cbf4e91cf82bb4d54ace397cdbbfaf594ba))
## [v0.8.0](https://github.com/docling-project/docling-serve/releases/tag/v0.8.0) - 2025-04-22
### Feature
* Add option for vlm pipeline ([#143](https://github.com/docling-project/docling-serve/issues/143)) ([`ee89ee4`](https://github.com/docling-project/docling-serve/commit/ee89ee4daee5e916bd6a3bdb452f78934cd03f60))
* Expose more conversion options ([#142](https://github.com/docling-project/docling-serve/issues/142)) ([`6b3d281`](https://github.com/docling-project/docling-serve/commit/6b3d281f02905c195ab75f25bb39f5c4d4e7b680))
* **UI:** Change UI to use async endpoints ([#131](https://github.com/docling-project/docling-serve/issues/131)) ([`b598872`](https://github.com/docling-project/docling-serve/commit/b598872e5c48928ac44417a11bb7acc0e5c3f0c6))
### Fix
* **UI:** Use https when calling the api ([#139](https://github.com/docling-project/docling-serve/issues/139)) ([`57f9073`](https://github.com/docling-project/docling-serve/commit/57f9073bc0daf72428b068ea28e2bec7cd76c37b))
* Fix permissions in docker image ([#136](https://github.com/docling-project/docling-serve/issues/136)) ([`c1ce471`](https://github.com/docling-project/docling-serve/commit/c1ce4719c933179ba3c59d73d0584853bbd6fa6a))
* Picture caption visuals ([#129](https://github.com/docling-project/docling-serve/issues/129)) ([`5dfb75d`](https://github.com/docling-project/docling-serve/commit/5dfb75d3b9a7022d1daad12edbb8ec7bbf9aa264))
### Documentation
* Fix required permissions for oauth2-proxy requests ([#141](https://github.com/docling-project/docling-serve/issues/141)) ([`087417e`](https://github.com/docling-project/docling-serve/commit/087417e5c2387d4ed95500222058f34d8a8702aa))
* Update deployment examples ([#135](https://github.com/docling-project/docling-serve/issues/135)) ([`525a43f`](https://github.com/docling-project/docling-serve/commit/525a43ff6f04b7cc80f9dd6a0e653a8d8c4ab317))
* Fix image tag ([#124](https://github.com/docling-project/docling-serve/issues/124)) ([`420162e`](https://github.com/docling-project/docling-serve/commit/420162e674cc38b4c3c13673ffbee4c20a1b15f1))
## [v0.7.0](https://github.com/docling-project/docling-serve/releases/tag/v0.7.0) - 2025-03-31
### Feature
* Expose TLS settings and example deploy with oauth-proxy ([#112](https://github.com/docling-project/docling-serve/issues/112)) ([`7a0faba`](https://github.com/docling-project/docling-serve/commit/7a0fabae07020c2659dbb22c3b0359909051a74c))
* Offline static files ([#109](https://github.com/docling-project/docling-serve/issues/109)) ([`68772bb`](https://github.com/docling-project/docling-serve/commit/68772bb6f0a87b71094a08ff851f5754c6ca6163))
* Update to Docling 2.28 ([#106](https://github.com/docling-project/docling-serve/issues/106)) ([`20ec87a`](https://github.com/docling-project/docling-serve/commit/20ec87a63a99145bc0ad7931549af8a0c30db641))
### Fix
* Move ARGs to prevent cache invalidation ([#104](https://github.com/docling-project/docling-serve/issues/104)) ([`e30f458`](https://github.com/docling-project/docling-serve/commit/e30f458923d34c169db7d5a5c296848716e8cac4))
## [v0.6.0](https://github.com/docling-project/docling-serve/releases/tag/v0.6.0) - 2025-03-17
### Feature
* Expose options for new features ([#92](https://github.com/docling-project/docling-serve/issues/92)) ([`ec57b52`](https://github.com/docling-project/docling-serve/commit/ec57b528ed3f8e7b9604ff4cdf06da3d52c714dd))
### Fix
* Allow changes in CORS settings ([#100](https://github.com/docling-project/docling-serve/issues/100)) ([`422c402`](https://github.com/docling-project/docling-serve/commit/422c402bab7f05e46274ede11f234a19a62e093e))
* Avoid exploding options cache using lru and expose size parameter ([#101](https://github.com/docling-project/docling-serve/issues/101)) ([`ea09028`](https://github.com/docling-project/docling-serve/commit/ea090288d3eec4ea8fbdcd32a6a497a99c89189d))
* Increase timeout_keep_alive and allow parameter changes ([#98](https://github.com/docling-project/docling-serve/issues/98)) ([`07c48ed`](https://github.com/docling-project/docling-serve/commit/07c48edd5d9437219d9623e3d05bc5166c5bb85a))
* Add warning when using incompatible parameters ([#99](https://github.com/docling-project/docling-serve/issues/99)) ([`a212547`](https://github.com/docling-project/docling-serve/commit/a212547d28d6588c65e52000dc7bc04f3f77e69e))
* **ui:** Use --port parameter and avoid failing when image is not found ([#97](https://github.com/docling-project/docling-serve/issues/97)) ([`c76daac`](https://github.com/docling-project/docling-serve/commit/c76daac70c87da412f791666881e48b74688b060))
### Documentation
* Simplify README and move details to docs ([#102](https://github.com/docling-project/docling-serve/issues/102)) ([`fd8e40a`](https://github.com/docling-project/docling-serve/commit/fd8e40a00849771263d9b75b9a56f6caeccb8517))
## [v0.5.1](https://github.com/docling-project/docling-serve/releases/tag/v0.5.1) - 2025-03-10
### Fix
* Submodules in wheels ([#85](https://github.com/docling-project/docling-serve/issues/85)) ([`a92ad48`](https://github.com/docling-project/docling-serve/commit/a92ad48b287bfcb134011dc0fc3f91ee04e067ee))
## [v0.5.0](https://github.com/docling-project/docling-serve/releases/tag/v0.5.0) - 2025-03-07
### Feature
* Async api ([#60](https://github.com/docling-project/docling-serve/issues/60)) ([`82f8900`](https://github.com/docling-project/docling-serve/commit/82f890019745859699c1b01f9ccfb64cb7e37906))
* Display version in fastapi docs ([#78](https://github.com/docling-project/docling-serve/issues/78)) ([`ed851c9`](https://github.com/docling-project/docling-serve/commit/ed851c95fee5f59305ddc3dcd5c09efce618470b))
### Fix
* Remove uv from image, merge ARG and ENV declarations ([#57](https://github.com/docling-project/docling-serve/issues/57)) ([`c95db36`](https://github.com/docling-project/docling-serve/commit/c95db3643807a4dfb96d93c8e10d6eb486c49a30))
* **docs:** Remove comma in convert/source curl example ([#73](https://github.com/docling-project/docling-serve/issues/73)) ([`05df073`](https://github.com/docling-project/docling-serve/commit/05df0735d35a589bdc2a11fcdd764a10f700cb6f))
## [v0.4.0](https://github.com/docling-project/docling-serve/releases/tag/v0.4.0) - 2025-02-26
### Feature
* New container images ([#68](https://github.com/docling-project/docling-serve/issues/68)) ([`7e6d9cd`](https://github.com/docling-project/docling-serve/commit/7e6d9cdef398df70a5b4d626aeb523c428c10d56))
* Render DoclingDocument with npm docling-components in the example UI ([#65](https://github.com/docling-project/docling-serve/issues/65)) ([`c430d9b`](https://github.com/docling-project/docling-serve/commit/c430d9b1a162ab29104d86ebaa1ac5a5488b1f09))
## [v0.3.0](https://github.com/docling-project/docling-serve/releases/tag/v0.3.0) - 2025-02-19
### Feature
* Add new docling-serve cli ([#50](https://github.com/docling-project/docling-serve/issues/50)) ([`ec33a61`](https://github.com/docling-project/docling-serve/commit/ec33a61faa7846b9b7998fbf557ebe39a3b800f6))
### Fix
* Set DOCLING_SERVE_ARTIFACTS_PATH in images ([#53](https://github.com/docling-project/docling-serve/issues/53)) ([`4877248`](https://github.com/docling-project/docling-serve/commit/487724836896576ca4f98e84abf15fd1c383bec8))
* Set root UI path when behind proxy ([#38](https://github.com/docling-project/docling-serve/issues/38)) ([`c64a450`](https://github.com/docling-project/docling-serve/commit/c64a450bf9ba9947ab180e92bef2763ff710b210))
* Support python 3.13 and docling updates and switch to uv ([#48](https://github.com/docling-project/docling-serve/issues/48)) ([`ae3b490`](https://github.com/docling-project/docling-serve/commit/ae3b4906f1c0829b1331ea491f3518741cabff71))

View File

@@ -3,13 +3,13 @@
Our project welcomes external contributions. If you have an itch, please feel
free to scratch it.
To contribute code or documentation, please submit a [pull request](https://github.com/DS4SD/docling-serve/pulls).
To contribute code or documentation, please submit a [pull request](https://github.com/docling-project/docling-serve/pulls).
A good way to familiarize yourself with the codebase and contribution process is
to look for and tackle low-hanging fruit in the [issue tracker](https://github.com/DS4SD/docling-serve/issues).
to look for and tackle low-hanging fruit in the [issue tracker](https://github.com/docling-project/docling-serve/issues).
Before embarking on a more ambitious contribution, please quickly [get in touch](#communication) with us.
For general questions or support requests, please refer to the [discussion section](https://github.com/DS4SD/docling-serve/discussions).
For general questions or support requests, please refer to the [discussion section](https://github.com/docling-project/docling-serve/discussions).
**Note: We appreciate your effort, and want to avoid a situation where a contribution
requires extensive rework (by you or by us), sits in backlog for a long time, or
@@ -17,14 +17,14 @@ cannot be accepted at all!**
### Proposing new features
If you would like to implement a new feature, please [raise an issue](https://github.com/DS4SD/docling-serve/issues)
If you would like to implement a new feature, please [raise an issue](https://github.com/docling-project/docling-serve/issues)
before sending a pull request so the feature can be discussed. This is to avoid
you wasting your valuable time working on a feature that the project developers
are not interested in accepting into the code base.
### Fixing bugs
If you would like to fix a bug, please [raise an issue](https://github.com/DS4SD/docling-serve/issues) before sending a
If you would like to fix a bug, please [raise an issue](https://github.com/docling-project/docling-serve/issues) before sending a
pull request so it can be tracked.
### Merge approval
@@ -73,7 +73,7 @@ git commit -s
## Communication
Please feel free to connect with us using the [discussion section](https://github.com/DS4SD/docling-serve/discussions).
Please feel free to connect with us using the [discussion section](https://github.com/docling-project/docling-serve/discussions).
## Developing
@@ -142,8 +142,7 @@ poetry add NAME
We use the following tools to enforce code style:
- iSort, to sort imports
- Black, to format code
- ruff, to sort imports and format code
We run a series of checks on the code base on every commit, using `pre-commit`. To install the hooks, run:
@@ -157,4 +156,4 @@ To run the checks on-demand, run:
pre-commit run --all-files
```
Note: Checks like `Black` and `isort` will "fail" if they modify files. This is because `pre-commit` doesn't like to see files modified by their Hooks. In these cases, `git add` the modified files and `git commit` again.
Note: Formatting checks like `ruff` will "fail" if they modify files. This is because `pre-commit` doesn't like to see files modified by their Hooks. In these cases, `git add` the modified files and `git commit` again.

View File

@@ -1,15 +1,17 @@
ARG BASE_IMAGE=quay.io/sclorg/python-312-c9s:c9s
FROM ${BASE_IMAGE}
ARG UV_VERSION=0.8.3
ARG CPU_ONLY=false
ARG UV_SYNC_EXTRA_ARGS=""
USER 0
FROM ${BASE_IMAGE} AS docling-base
###################################################################################################
# OS Layer #
###################################################################################################
USER 0
RUN --mount=type=bind,source=os-packages.txt,target=/tmp/os-packages.txt \
dnf -y install --best --nodocs --setopt=install_weak_deps=False dnf-plugins-core && \
dnf config-manager --best --nodocs --setopt=install_weak_deps=False --save && \
@@ -19,43 +21,60 @@ RUN --mount=type=bind,source=os-packages.txt,target=/tmp/os-packages.txt \
dnf -y clean all && \
rm -rf /var/cache/dnf
RUN /usr/bin/fix-permissions /opt/app-root/src/.cache
ENV TESSDATA_PREFIX=/usr/share/tesseract/tessdata/
FROM ghcr.io/astral-sh/uv:${UV_VERSION} AS uv_stage
###################################################################################################
# Docling layer #
###################################################################################################
FROM docling-base
USER 1001
WORKDIR /opt/app-root/src
# On container environments, always set a thread budget to avoid undesired thread congestion.
ENV OMP_NUM_THREADS=4
ENV \
OMP_NUM_THREADS=4 \
LANG=en_US.UTF-8 \
LC_ALL=en_US.UTF-8 \
PYTHONIOENCODING=utf-8 \
UV_COMPILE_BYTECODE=1 \
UV_LINK_MODE=copy \
UV_PROJECT_ENVIRONMENT=/opt/app-root \
DOCLING_SERVE_ARTIFACTS_PATH=/opt/app-root/src/.cache/docling/models
ENV LANG=en_US.UTF-8
ENV LC_ALL=en_US.UTF-8
ENV PYTHONIOENCODING=utf-8
ARG UV_SYNC_EXTRA_ARGS
ENV WITH_UI=True
RUN --mount=from=uv_stage,source=/uv,target=/bin/uv \
--mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
--mount=type=bind,source=uv.lock,target=uv.lock \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
umask 002 && \
UV_SYNC_ARGS="--frozen --no-install-project --no-dev --all-extras" && \
uv sync ${UV_SYNC_ARGS} ${UV_SYNC_EXTRA_ARGS} --no-extra flash-attn && \
FLASH_ATTENTION_SKIP_CUDA_BUILD=TRUE uv sync ${UV_SYNC_ARGS} ${UV_SYNC_EXTRA_ARGS} --no-build-isolation-package=flash-attn
COPY --chown=1001:0 pyproject.toml poetry.lock models_download.py README.md ./
ARG MODELS_LIST="layout tableformer picture_classifier easyocr"
RUN pip install --no-cache-dir poetry && \
# We already are in a virtual environment, so we don't need to create a new one, only activate it.
poetry config virtualenvs.create false && \
source /opt/app-root/bin/activate && \
if [ "$CPU_ONLY" = "true" ]; then \
poetry install --no-root --no-cache --no-interaction --all-extras --with cpu --without dev; \
else \
poetry install --no-root --no-cache --no-interaction --all-extras --without dev; \
fi && \
echo "Downloading models..." && \
python models_download.py && \
chown -R 1001:0 /opt/app-root/src && \
chmod -R g=u /opt/app-root/src
RUN echo "Downloading models..." && \
HF_HUB_DOWNLOAD_TIMEOUT="90" \
HF_HUB_ETAG_TIMEOUT="90" \
docling-tools models download -o "${DOCLING_SERVE_ARTIFACTS_PATH}" ${MODELS_LIST} && \
chown -R 1001:0 ${DOCLING_SERVE_ARTIFACTS_PATH} && \
chmod -R g=u ${DOCLING_SERVE_ARTIFACTS_PATH}
COPY --chown=1001:0 --chmod=664 ./docling_serve ./docling_serve
COPY --chown=1001:0 ./docling_serve ./docling_serve
RUN --mount=from=uv_stage,source=/uv,target=/bin/uv \
--mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
--mount=type=bind,source=uv.lock,target=uv.lock \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
umask 002 && uv sync --frozen --no-dev --all-extras ${UV_SYNC_EXTRA_ARGS}
EXPOSE 5001
CMD ["python", "-m", "docling_serve"]
CMD ["docling-serve", "run"]

View File

@@ -1,11 +1,11 @@
# MAINTAINERS
- Christoph Auer - [@cau-git](https://github.com/cau-git)
- Michele Dolfi - [@dolfim-ibm](https://github.com/dolfim-ibm)
- Maxim Lysak - [@maxmnemonic](https://github.com/maxmnemonic)
- Nikos Livathinos - [@nikos-livathinos](https://github.com/nikos-livathinos)
- Ahmed Nassar - [@nassarofficial](https://github.com/nassarofficial)
- Panos Vagenas - [@vagenas](https://github.com/vagenas)
- Peter Staar - [@PeterStaar-IBM](https://github.com/PeterStaar-IBM)
- Christoph Auer - [`@cau-git`](https://github.com/cau-git)
- Michele Dolfi - [`@dolfim-ibm`](https://github.com/dolfim-ibm)
- Maxim Lysak - [`@maxmnemonic`](https://github.com/maxmnemonic)
- Nikos Livathinos - [`@nikos-livathinos`](https://github.com/nikos-livathinos)
- Ahmed Nassar - [`@nassarofficial`](https://github.com/nassarofficial)
- Panos Vagenas - [`@vagenas`](https://github.com/vagenas)
- Peter Staar - [`@PeterStaar-IBM`](https://github.com/PeterStaar-IBM)
Maintainers can be contacted at [deepsearch-core@zurich.ibm.com](mailto:deepsearch-core@zurich.ibm.com).

View File

@@ -17,6 +17,7 @@ else
endif
TAG=$(shell git rev-parse HEAD)
BRANCH_TAG=$(shell git rev-parse --abbrev-ref HEAD)
action-lint-file:
$(CMD_PREFIX) touch .action-lint
@@ -24,19 +25,47 @@ action-lint-file:
md-lint-file:
$(CMD_PREFIX) touch .markdown-lint
.PHONY: docling-serve-image
docling-serve-image: Containerfile ## Build docling-serve container image
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve]"
$(CMD_PREFIX) docker build --load -f Containerfile -t ghcr.io/docling-project/docling-serve:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve:$(TAG) ghcr.io/docling-project/docling-serve:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve:$(TAG) quay.io/docling-project/docling-serve:$(BRANCH_TAG)
.PHONY: docling-serve-cpu-image
docling-serve-cpu-image: Containerfile ## Build docling-serve "cpu only" container image
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve CPU ONLY]"
$(CMD_PREFIX) docker build --build-arg CPU_ONLY=true -f Containerfile --platform linux/amd64 -t ghcr.io/ds4sd/docling-serve-cpu:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve-cpu:$(TAG) ghcr.io/ds4sd/docling-serve-cpu:main
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve-cpu:$(TAG) quay.io/ds4sd/docling-serve-cpu:main
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve CPU]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group cpu --no-extra flash-attn" -f Containerfile -t ghcr.io/docling-project/docling-serve-cpu:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cpu:$(TAG) ghcr.io/docling-project/docling-serve-cpu:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cpu:$(TAG) quay.io/docling-project/docling-serve-cpu:$(BRANCH_TAG)
.PHONY: docling-serve-gpu-image
docling-serve-gpu-image: Containerfile ## Build docling-serve container image with GPU support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with GPU]"
$(CMD_PREFIX) docker build --build-arg CPU_ONLY=false -f Containerfile --platform linux/amd64 -t ghcr.io/ds4sd/docling-serve:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve:$(TAG) ghcr.io/ds4sd/docling-serve:main
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve:$(TAG) quay.io/ds4sd/docling-serve:main
.PHONY: docling-serve-cu124-image
docling-serve-cu124-image: Containerfile ## Build docling-serve container image with CUDA 12.4 support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with Cuda 12.4]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124" -f Containerfile --platform linux/amd64 -t ghcr.io/docling-project/docling-serve-cu124:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu124:$(TAG) ghcr.io/docling-project/docling-serve-cu124:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu124:$(TAG) quay.io/docling-project/docling-serve-cu124:$(BRANCH_TAG)
.PHONY: docling-serve-cu126-image
docling-serve-cu126-image: Containerfile ## Build docling-serve container image with CUDA 12.6 support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with Cuda 12.6]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu126" -f Containerfile --platform linux/amd64 -t ghcr.io/docling-project/docling-serve-cu126:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu126:$(TAG) ghcr.io/docling-project/docling-serve-cu126:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu126:$(TAG) quay.io/docling-project/docling-serve-cu126:$(BRANCH_TAG)
.PHONY: docling-serve-cu128-image
docling-serve-cu128-image: Containerfile ## Build docling-serve container image with CUDA 12.8 support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with Cuda 12.8]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu128" -f Containerfile --platform linux/amd64 -t ghcr.io/docling-project/docling-serve-cu128:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu128:$(TAG) ghcr.io/docling-project/docling-serve-cu128:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu128:$(TAG) quay.io/docling-project/docling-serve-cu128:$(BRANCH_TAG)
.PHONY: docling-serve-rocm-image
docling-serve-rocm-image: Containerfile ## Build docling-serve container image with ROCm support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with ROCm 6.3]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn" -f Containerfile --platform linux/amd64 -t ghcr.io/docling-project/docling-serve-rocm:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-rocm:$(TAG) ghcr.io/docling-project/docling-serve-rocm:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-rocm:$(TAG) quay.io/docling-project/docling-serve-rocm:$(BRANCH_TAG)
.PHONY: action-lint
action-lint: .action-lint ## Lint GitHub Action workflows
@@ -59,30 +88,50 @@ action-lint: .action-lint ## Lint GitHub Action workflows
md-lint: .md-lint ## Lint markdown files
.md-lint: $(wildcard */**/*.md) | md-lint-file
$(ECHO_PREFIX) printf " %-12s ./...\n" "[MD LINT]"
$(CMD_PREFIX) docker run --rm -v $$(pwd):/workdir davidanson/markdownlint-cli2:v0.14.0 "**/*.md"
$(CMD_PREFIX) docker run --rm -v $$(pwd):/workdir davidanson/markdownlint-cli2:v0.16.0 "**/*.md" "#.venv"
$(CMD_PREFIX) touch $@
.PHONY: py-Lint
py-lint: ## Lint Python files
$(ECHO_PREFIX) printf " %-12s ./...\n" "[PY LINT]"
$(CMD_PREFIX) if ! which poetry $(PIPE_DEV_NULL) ; then \
echo "Please install poetry." ; \
echo "pip install poetry" ; \
$(CMD_PREFIX) if ! which uv $(PIPE_DEV_NULL) ; then \
echo "Please install uv." ; \
exit 1 ; \
fi
$(CMD_PREFIX) poetry install --all-extras
$(CMD_PREFIX) poetry run pre-commit run --all-files
$(CMD_PREFIX) uv sync --extra ui
$(CMD_PREFIX) uv run pre-commit run --all-files
.PHONY: run-docling-cpu
run-docling-cpu: ## Run the docling-serve container with CPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-cpu 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with CPU support on port 5001...\n" "[RUN CPU]"
$(CMD_PREFIX) docker run -it --name docling-serve-cpu -p 5001:5001 ghcr.io/ds4sd/docling-serve-cpu:main
$(CMD_PREFIX) docker run -it --name docling-serve-cpu -p 5001:5001 ghcr.io/docling-project/docling-serve-cpu:main
.PHONY: run-docling-gpu
run-docling-gpu: ## Run the docling-serve container with GPU support and assign a container name
.PHONY: run-docling-cu124
run-docling-cu124: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-gpu 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN GPU]"
$(CMD_PREFIX) docker run -it --name docling-serve-gpu -p 5001:5001 ghcr.io/ds4sd/docling-serve:main
$(CMD_PREFIX) docker rm -f docling-serve-cu124 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.4]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu124 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu124:main
.PHONY: run-docling-cu126
run-docling-cu126: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-cu126 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.6]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu126 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu126:main
.PHONY: run-docling-cu128
run-docling-cu128: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-cu128 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.8]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu128 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu128:main
.PHONY: run-docling-rocm
run-docling-rocm: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-rocm 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN ROCm 6.3]"
$(CMD_PREFIX) docker run -it --name docling-serve-rocm -p 5001:5001 ghcr.io/docling-project/docling-serve-rocm:main

374
README.md
View File

@@ -1,342 +1,100 @@
<p align="center">
<a href="https://github.com/docling-project/docling-serve">
<img loading="lazy" alt="Docling" src="https://github.com/docling-project/docling-serve/raw/main/docs/assets/docling-serve-pic.png" width="30%"/>
</a>
</p>
# Docling Serve
Running [Docling](https://github.com/DS4SD/docling) as an API service.
Running [Docling](https://github.com/docling-project/docling) as an API service.
## Usage
📚 [Docling Serve documentation](./docs/README.md)
The API provides two endpoints: one for urls, one for files. This is necessary to send files directly in binary format instead of base64-encoded strings.
- Learning how to [configure the webserver](./docs/configuration.md)
- Get to know all [runtime options](./docs/usage.md) of the API
- Explore useful [deployment examples](./docs/deployment.md)
- And more
### Common parameters
> [!NOTE]
> **Migration to the `v1` API.** Docling Serve now has a stable v1 API. Read more on the [migration to v1](./docs/v1_migration.md).
On top of the source of file (see below), both endpoints support the same parameters, which are almost the same as the Docling CLI.
## Getting started
- `from_format` (List[str]): Input format(s) to convert from. Allowed values: `docx`, `pptx`, `html`, `image`, `pdf`, `asciidoc`, `md`. Defaults to all formats.
- `to_formats` (List[str]): Output format(s) to convert to. Allowed values: `md`, `json`, `html`, `text`, `doctags`. Defaults to `md`.
- `do_ocr` (bool): If enabled, the bitmap content will be processed using OCR. Defaults to `True`.
- `image_export_mode`: Image export mode for the document (only in case of JSON, Markdown or HTML). Allowed values: embedded, placeholder, referenced. Optional, defaults to `embedded`.
- `force_ocr` (bool): If enabled, replace any existing text with OCR-generated text over the full content. Defaults to `False`.
- `ocr_engine` (str): OCR engine to use. Allowed values: `easyocr`, `tesseract_cli`, `tesseract`, `rapidocr`, `ocrmac`. Defaults to `easyocr`.
- `ocr_lang` (List[str]): List of languages used by the OCR engine. Note that each OCR engine has different values for the language names. Defaults to empty.
- `pdf_backend` (str): PDF backend to use. Allowed values: `pypdfium2`, `dlparse_v1`, `dlparse_v2`. Defaults to `dlparse_v2`.
- `table_mode` (str): Table mode to use. Allowed values: `fast`, `accurate`. Defaults to `fast`.
- `abort_on_error` (bool): If enabled, abort on error. Defaults to false.
- `return_as_file` (boo): If enabled, return the output as a file. Defaults to false.
- `do_table_structure` (bool): If enabled, the table structure will be extracted. Defaults to true.
- `include_images` (bool): If enabled, images will be extracted from the document. Defaults to true.
- `images_scale` (float): Scale factor for images. Defaults to 2.0.
Install the `docling-serve` package and run the server.
### URL endpoint
```bash
# Using the python package
pip install "docling-serve[ui]"
docling-serve run --enable-ui
The endpoint is `/v1alpha/convert/source`, listening for POST requests of JSON payloads.
On top of the above parameters, you must send the URL(s) of the document you want process with either the `http_sources` or `file_sources` fields.
The first is fetching URL(s) (optionally using with extra headers), the second allows to provide documents as base64-encoded strings.
No `options` is required, they can be partially or completely omitted.
Simple payload example:
```json
{
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
# Using container images, e.g. with Podman
podman run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=1 quay.io/docling-project/docling-serve
```
<details>
The server is available at
<summary>Complete payload example:</summary>
- API <http://127.0.0.1:5001>
- API documentation <http://127.0.0.1:5001/docs>
- UI playground <http://127.0.0.1:5001/ui>
```json
{
"options": {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": true,
"force_ocr": false,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": false,
"return_as_file": false,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
```
![API documentation](img/fastapi-ui.png)
</details>
Try it out with a simple conversion:
<details>
<summary>CURL example:</summary>
```sh
```bash
curl -X 'POST' \
'http://localhost:5001/v1alpha/convert/source' \
'http://localhost:5001/v1/convert/source' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"options": {
"from_formats": [
"docx",
"pptx",
"html",
"image",
"pdf",
"asciidoc",
"md",
"xlsx"
],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": true,
"force_ocr": false,
"ocr_engine": "easyocr",
"ocr_lang": [
"fr",
"de",
"es",
"en"
],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": false,
"return_as_file": false,
"do_table_structure": true,
"include_images": true,
"images_scale": 2,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}'
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
</details>
### Container Images
<details>
<summary>Python example:</summary>
The following container images are available for running **Docling Serve** with different hardware and PyTorch configurations:
```python
import httpx
#### 📦 Distributed Images
async_client = httpx.AsyncClient(timeout=60.0)
url = "http://localhost:5001/v1alpha/convert/source"
payload = {
"options": {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": "en",
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
| Image | Description | Architectures | Size |
|-------|-------------|----------------|------|
| [`ghcr.io/docling-project/docling-serve`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve) <br> [`quay.io/docling-project/docling-serve`](https://quay.io/repository/docling-project/docling-serve) | Base image with all packages installed from the official PyPI index. | `linux/amd64`, `linux/arm64` | 4.4 GB (arm64) <br> 8.7 GB (amd64) |
| [`ghcr.io/docling-project/docling-serve-cpu`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cpu) <br> [`quay.io/docling-project/docling-serve-cpu`](https://quay.io/repository/docling-project/docling-serve-cpu) | CPU-only variant, using `torch` from the PyTorch CPU index. | `linux/amd64`, `linux/arm64` | 4.4 GB |
| [`ghcr.io/docling-project/docling-serve-cu126`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu126) <br> [`quay.io/docling-project/docling-serve-cu126`](https://quay.io/repository/docling-project/docling-serve-cu126) | CUDA 12.6 build with `torch` from the cu126 index. | `linux/amd64` | 10.0 GB |
| [`ghcr.io/docling-project/docling-serve-cu128`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu128) <br> [`quay.io/docling-project/docling-serve-cu128`](https://quay.io/repository/docling-project/docling-serve-cu128) | CUDA 12.8 build with `torch` from the cu128 index. | `linux/amd64` | 11.4 GB |
response = await async_client_client.post(url, json=payload)
#### 🚫 Not Distributed
data = response.json()
An image for AMD ROCm 6.3 (`docling-serve-rocm`) is supported but **not published** due to its large size.
To build it locally:
```bash
git clone --branch main git@github.com:docling-project/docling-serve.git
cd docling-serve/
make docling-serve-rocm-image
```
</details>
For deployment using Docker Compose, see [docs/deployment.md](docs/deployment.md).
#### File as base64
Coming soon: `docling-serve-slim` images will reduce the size by skipping the model weights download.
The `file_sources` argument in the endpoint allows to send files as base64-encoded strings.
When your PDF or other file type is too large, encoding it and passing it inline to curl
can lead to an “Argument list too long” error on some systems. To avoid this, we write
the JSON request body to a file and have curl read from that file.
### Demonstration UI
<details>
<summary>CURL steps:</summary>
An easy to use UI is available at the `/ui` endpoint.
```sh
# 1. Base64-encode the file
B64_DATA=$(base64 -w 0 /path/to/file/pdf-to-convert.pdf)
![Input controllers in the UI](img/ui-input.png)
# 2. Build the JSON with your options
cat <<EOF > /tmp/request_body.json
{
"options": {
},
"file_sources": [{
"base64_string": "${B64_DATA}",
"filename": "pdf-to-convert.pdf"
}]
}
EOF
# 3. POST the request to the docling service
curl -X POST "localhost:5001/v1alpha/convert/source" \
-H "Content-Type: application/json" \
-d @/tmp/request_body.json
```
</details>
### File endpoint
The endpoint is: `/v1alpha/convert/file`, listening for POST requests of Form payloads (necessary as the files are sent as multipart/form data). You can send one or multiple files.
<details>
<summary>CURL example:</summary>
```sh
curl -X 'POST' \
'http://127.0.0.1:5001/v1alpha/convert/file' \
-H 'accept: application/json' \
-H 'Content-Type: multipart/form-data' \
-F 'ocr_engine=easyocr' \
-F 'pdf_backend=dlparse_v2' \
-F 'from_formats=pdf' \
-F 'from_formats=docx' \
-F 'force_ocr=false' \
-F 'image_export_mode=embedded' \
-F 'ocr_lang=en' \
-F 'ocr_lang=pl' \
-F 'table_mode=fast' \
-F 'files=@2206.01062v1.pdf;type=application/pdf' \
-F 'abort_on_error=false' \
-F 'to_formats=md' \
-F 'to_formats=text' \
-F 'return_as_file=false' \
-F 'do_ocr=true'
```
</details>
<details>
<summary>Python example:</summary>
```python
import httpx
async_client = httpx.AsyncClient(timeout=60.0)
url = "http://localhost:5001/v1alpha/convert/file"
parameters = {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False
}
current_dir = os.path.dirname(__file__)
file_path = os.path.join(current_dir, '2206.01062v1.pdf')
files = {
'files': ('2206.01062v1.pdf', open(file_path, 'rb'), 'application/pdf'),
}
response = await async_client.post(url, files=files, data={"parameters": json.dumps(parameters)})
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
```
</details>
### Response format
The response can be a JSON Document or a File.
- If you process only one file, the response will be a JSON document with the following format:
```jsonc
{
"document": {
"md_content": "",
"json_content": {},
"html_content": "",
"text_content": "",
"doctags_content": ""
},
"status": "<success|partial_success|skipped|failure>",
"processing_time": 0.0,
"timings": {},
"errors": []
}
```
Depending on the value you set in `output_formats`, the different items will be populated with their respective results or empty.
`processing_time` is the Docling processing time in seconds, and `timings` (when enabled in the backend) provides the detailed
timing of all the internal Docling components.
- If you set the parameter `return_as_file` to True, the response will be a zip file.
- If multiple files are generated (multiple inputs, or one input but multiple outputs with `return_as_file` True), the response will be a zip file.
## Helpers
- A full Swagger UI is available at the `/docs` endpoint.
![swagger.png](img/swagger.png)
- An easy to use UI is available at the `/ui` endpoint.
![ui-input.png](img/ui-input.png)
![ui-output.png](img/ui-output.png)
## Development
### CPU only
```sh
# Install poetry if not already available
curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
poetry install --with cpu
```
### Cuda GPU
For GPU support use the following command:
```sh
# Install dependencies
poetry install
```
### Run the server
The [start_server.sh](./start_server.sh) executable is a convenient script for launching the local webserver.
```sh
# Run the server
bash start_server.sh
# Run the server with live reload
RELOAD=true bash start_server.sh
```
### Environment variables
The following variables are available:
`TESSDATA_PREFIX`: Tesseract data location, example `/usr/share/tesseract/tessdata/`.
`UVICORN_WORKERS`: Number of workers to use.
`RELOAD`: If `True`, this will enable auto-reload when you modify files, useful for development.
`WITH_UI`: If `True`, The Gradio UI will be available at `/ui`.
![Output visualization in the UI](img/ui-output.png)
## Get help and support
Please feel free to connect with us using the [discussion section](https://github.com/DS4SD/docling/discussions).
Please feel free to connect with us using the [discussion section](https://github.com/docling-project/docling/discussions).
## Contributing
Please read [Contributing to Docling Serve](https://github.com/DS4SD/docling-serve/blob/main/CONTRIBUTING.md) for details.
Please read [Contributing to Docling Serve](https://github.com/docling-project/docling-serve/blob/main/CONTRIBUTING.md) for details.
## References
@@ -344,14 +102,14 @@ If you use Docling in your projects, please consider citing the following:
```bib
@techreport{Docling,
author = {Deep Search Team},
month = {8},
title = {Docling Technical Report},
url = {https://arxiv.org/abs/2408.09869},
eprint = {2408.09869},
doi = {10.48550/arXiv.2408.09869},
version = {1.0.0},
year = {2024}
author = {Docling Contributors},
month = {1},
title = {Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion},
url = {https://arxiv.org/abs/2501.17887},
eprint = {2501.17887},
doi = {10.48550/arXiv.2501.17887},
version = {2.0.0},
year = {2025}
}
```

View File

@@ -1,20 +1,402 @@
import os
import importlib.metadata
import logging
import platform
import sys
import warnings
from pathlib import Path
from typing import Annotated, Any, Optional, Union
from docling_serve.app import app
from docling_serve.helper_functions import _str_to_bool
import typer
import uvicorn
from rich.console import Console
# Launch the FastAPI server
if __name__ == "__main__":
from uvicorn import run
from docling_serve.settings import docling_serve_settings, uvicorn_settings
from docling_serve.storage import get_scratch
port = int(os.getenv("PORT", "5001"))
workers = int(os.getenv("UVICORN_WORKERS", "1"))
reload = _str_to_bool(os.getenv("RELOAD", "False"))
run(
app,
host="0.0.0.0",
port=port,
workers=workers,
timeout_keep_alive=600,
reload=reload,
warnings.filterwarnings(action="ignore", category=UserWarning, module="pydantic|torch")
warnings.filterwarnings(action="ignore", category=FutureWarning, module="easyocr")
err_console = Console(stderr=True)
console = Console()
app = typer.Typer(
no_args_is_help=True,
rich_markup_mode="rich",
)
logger = logging.getLogger(__name__)
def version_callback(value: bool) -> None:
if value:
docling_serve_version = importlib.metadata.version("docling_serve")
docling_jobkit_version = importlib.metadata.version("docling-jobkit")
docling_version = importlib.metadata.version("docling")
docling_core_version = importlib.metadata.version("docling-core")
docling_ibm_models_version = importlib.metadata.version("docling-ibm-models")
docling_parse_version = importlib.metadata.version("docling-parse")
platform_str = platform.platform()
py_impl_version = sys.implementation.cache_tag
py_lang_version = platform.python_version()
console.print(f"Docling Serve version: {docling_serve_version}")
console.print(f"Docling Jobkit version: {docling_jobkit_version}")
console.print(f"Docling version: {docling_version}")
console.print(f"Docling Core version: {docling_core_version}")
console.print(f"Docling IBM Models version: {docling_ibm_models_version}")
console.print(f"Docling Parse version: {docling_parse_version}")
console.print(f"Python: {py_impl_version} ({py_lang_version})")
console.print(f"Platform: {platform_str}")
raise typer.Exit()
@app.callback()
def callback(
version: Annotated[
Union[bool, None],
typer.Option(help="Show the version and exit.", callback=version_callback),
] = None,
verbose: Annotated[
int,
typer.Option(
"--verbose",
"-v",
count=True,
help="Set the verbosity level. -v for info logging, -vv for debug logging.",
),
] = 0,
) -> None:
if verbose == 0:
logging.basicConfig(level=logging.WARNING)
elif verbose == 1:
logging.basicConfig(level=logging.INFO)
elif verbose == 2:
logging.basicConfig(level=logging.DEBUG)
def _run(
*,
command: str,
# Docling serve parameters
artifacts_path: Path | None,
enable_ui: bool,
) -> None:
server_type = "development" if command == "dev" else "production"
console.print(f"Starting {server_type} server 🚀")
run_subprocess = (
uvicorn_settings.workers is not None and uvicorn_settings.workers > 1
) or uvicorn_settings.reload
run_ssl = (
uvicorn_settings.ssl_certfile is not None
and uvicorn_settings.ssl_keyfile is not None
)
if run_subprocess and docling_serve_settings.artifacts_path != artifacts_path:
err_console.print(
"\n[yellow]:warning: The server will run with reload or multiple workers. \n"
"The argument [bold]--artifacts-path[/bold] will be ignored, please set the value \n"
"using the environment variable [bold]DOCLING_SERVE_ARTIFACTS_PATH[/bold].[/yellow]"
)
if run_subprocess and docling_serve_settings.enable_ui != enable_ui:
err_console.print(
"\n[yellow]:warning: The server will run with reload or multiple workers. \n"
"The argument [bold]--enable-ui[/bold] will be ignored, please set the value \n"
"using the environment variable [bold]DOCLING_SERVE_ENABLE_UI[/bold].[/yellow]"
)
# Propagate the settings to the app settings
docling_serve_settings.artifacts_path = artifacts_path
docling_serve_settings.enable_ui = enable_ui
# Print documentation
protocol = "https" if run_ssl else "http"
url = f"{protocol}://{uvicorn_settings.host}:{uvicorn_settings.port}"
url_docs = f"{url}/docs"
url_scalar = f"{url}/scalar"
url_ui = f"{url}/ui"
console.print("")
console.print(f"Server started at [link={url}]{url}[/]")
console.print(f"Documentation at [link={url_docs}]{url_docs}[/]")
console.print(f"Scalar docs at [link={url_docs}]{url_scalar}[/]")
if docling_serve_settings.enable_ui:
console.print(f"UI at [link={url_ui}]{url_ui}[/]")
if command == "dev":
console.print("")
console.print(
"Running in development mode, for production use: "
"[bold]docling-serve run[/]",
)
console.print("")
console.print("Logs:")
# Launch the server
uvicorn.run(
app="docling_serve.app:create_app",
factory=True,
host=uvicorn_settings.host,
port=uvicorn_settings.port,
reload=uvicorn_settings.reload,
workers=uvicorn_settings.workers,
root_path=uvicorn_settings.root_path,
proxy_headers=uvicorn_settings.proxy_headers,
timeout_keep_alive=uvicorn_settings.timeout_keep_alive,
ssl_certfile=uvicorn_settings.ssl_certfile,
ssl_keyfile=uvicorn_settings.ssl_keyfile,
ssl_keyfile_password=uvicorn_settings.ssl_keyfile_password,
)
@app.command()
def dev(
*,
# uvicorn options
host: Annotated[
str,
typer.Option(
help=(
"The host to serve on. For local development in localhost "
"use [blue]127.0.0.1[/blue]. To enable public access, "
"e.g. in a container, use all the IP addresses "
"available with [blue]0.0.0.0[/blue]."
)
),
] = "127.0.0.1",
port: Annotated[
int,
typer.Option(help="The port to serve on."),
] = uvicorn_settings.port,
reload: Annotated[
bool,
typer.Option(
help=(
"Enable auto-reload of the server when (code) files change. "
"This is [bold]resource intensive[/bold], "
"use it only during development."
)
),
] = True,
root_path: Annotated[
str,
typer.Option(
help=(
"The root path is used to tell your app that it is being served "
"to the outside world with some [bold]path prefix[/bold] "
"set up in some termination proxy or similar."
)
),
] = uvicorn_settings.root_path,
proxy_headers: Annotated[
bool,
typer.Option(
help=(
"Enable/Disable X-Forwarded-Proto, X-Forwarded-For, "
"X-Forwarded-Port to populate remote address info."
)
),
] = uvicorn_settings.proxy_headers,
timeout_keep_alive: Annotated[
int, typer.Option(help="Timeout for the server response.")
] = uvicorn_settings.timeout_keep_alive,
ssl_certfile: Annotated[
Optional[Path], typer.Option(help="SSL certificate file")
] = uvicorn_settings.ssl_certfile,
ssl_keyfile: Annotated[
Optional[Path], typer.Option(help="SSL key file")
] = uvicorn_settings.ssl_keyfile,
ssl_keyfile_password: Annotated[
Optional[str], typer.Option(help="SSL keyfile password")
] = uvicorn_settings.ssl_keyfile_password,
# docling options
artifacts_path: Annotated[
Optional[Path],
typer.Option(
help=(
"If set to a valid directory, "
"the model weights will be loaded from this path."
)
),
] = docling_serve_settings.artifacts_path,
enable_ui: Annotated[bool, typer.Option(help="Enable the development UI.")] = True,
) -> Any:
"""
Run a [bold]Docling Serve[/bold] app in [yellow]development[/yellow] mode. 🧪
This is equivalent to [bold]docling-serve run[/bold] but with [bold]reload[/bold]
enabled and listening on the [blue]127.0.0.1[/blue] address.
Options can be set also with the corresponding ENV variable, with the exception
of --enable-ui, --host and --reload.
"""
uvicorn_settings.host = host
uvicorn_settings.port = port
uvicorn_settings.reload = reload
uvicorn_settings.root_path = root_path
uvicorn_settings.proxy_headers = proxy_headers
uvicorn_settings.timeout_keep_alive = timeout_keep_alive
uvicorn_settings.ssl_certfile = ssl_certfile
uvicorn_settings.ssl_keyfile = ssl_keyfile
uvicorn_settings.ssl_keyfile_password = ssl_keyfile_password
_run(
command="dev",
artifacts_path=artifacts_path,
enable_ui=enable_ui,
)
@app.command()
def run(
*,
host: Annotated[
str,
typer.Option(
help=(
"The host to serve on. For local development in localhost "
"use [blue]127.0.0.1[/blue]. To enable public access, "
"e.g. in a container, use all the IP addresses "
"available with [blue]0.0.0.0[/blue]."
)
),
] = uvicorn_settings.host,
port: Annotated[
int,
typer.Option(help="The port to serve on."),
] = uvicorn_settings.port,
reload: Annotated[
bool,
typer.Option(
help=(
"Enable auto-reload of the server when (code) files change. "
"This is [bold]resource intensive[/bold], "
"use it only during development."
)
),
] = uvicorn_settings.reload,
workers: Annotated[
Union[int, None],
typer.Option(
help=(
"Use multiple worker processes. "
"Mutually exclusive with the --reload flag."
)
),
] = uvicorn_settings.workers,
root_path: Annotated[
str,
typer.Option(
help=(
"The root path is used to tell your app that it is being served "
"to the outside world with some [bold]path prefix[/bold] "
"set up in some termination proxy or similar."
)
),
] = uvicorn_settings.root_path,
proxy_headers: Annotated[
bool,
typer.Option(
help=(
"Enable/Disable X-Forwarded-Proto, X-Forwarded-For, "
"X-Forwarded-Port to populate remote address info."
)
),
] = uvicorn_settings.proxy_headers,
timeout_keep_alive: Annotated[
int, typer.Option(help="Timeout for the server response.")
] = uvicorn_settings.timeout_keep_alive,
ssl_certfile: Annotated[
Optional[Path], typer.Option(help="SSL certificate file")
] = uvicorn_settings.ssl_certfile,
ssl_keyfile: Annotated[
Optional[Path], typer.Option(help="SSL key file")
] = uvicorn_settings.ssl_keyfile,
ssl_keyfile_password: Annotated[
Optional[str], typer.Option(help="SSL keyfile password")
] = uvicorn_settings.ssl_keyfile_password,
# docling options
artifacts_path: Annotated[
Optional[Path],
typer.Option(
help=(
"If set to a valid directory, "
"the model weights will be loaded from this path."
)
),
] = docling_serve_settings.artifacts_path,
enable_ui: Annotated[
bool, typer.Option(help="Enable the development UI.")
] = docling_serve_settings.enable_ui,
) -> Any:
"""
Run a [bold]Docling Serve[/bold] app in [green]production[/green] mode. 🚀
This is equivalent to [bold]docling-serve dev[/bold] but with [bold]reload[/bold]
disabled and listening on the [blue]0.0.0.0[/blue] address.
Options can be set also with the corresponding ENV variable, e.g. UVICORN_PORT
or DOCLING_SERVE_ENABLE_UI.
"""
uvicorn_settings.host = host
uvicorn_settings.port = port
uvicorn_settings.reload = reload
uvicorn_settings.workers = workers
uvicorn_settings.root_path = root_path
uvicorn_settings.proxy_headers = proxy_headers
uvicorn_settings.timeout_keep_alive = timeout_keep_alive
uvicorn_settings.ssl_certfile = ssl_certfile
uvicorn_settings.ssl_keyfile = ssl_keyfile
uvicorn_settings.ssl_keyfile_password = ssl_keyfile_password
_run(
command="run",
artifacts_path=artifacts_path,
enable_ui=enable_ui,
)
@app.command()
def rq_worker() -> Any:
"""
Run the [bold]Docling JobKit[/bold] RQ worker.
"""
from docling_jobkit.convert.manager import DoclingConverterManagerConfig
from docling_jobkit.orchestrators.rq.orchestrator import RQOrchestratorConfig
from docling_jobkit.orchestrators.rq.worker import run_worker
rq_config = RQOrchestratorConfig(
redis_url=docling_serve_settings.eng_rq_redis_url,
results_prefix=docling_serve_settings.eng_rq_results_prefix,
sub_channel=docling_serve_settings.eng_rq_sub_channel,
scratch_dir=get_scratch(),
)
cm_config = DoclingConverterManagerConfig(
artifacts_path=docling_serve_settings.artifacts_path,
options_cache_size=docling_serve_settings.options_cache_size,
enable_remote_services=docling_serve_settings.enable_remote_services,
allow_external_plugins=docling_serve_settings.allow_external_plugins,
max_num_pages=docling_serve_settings.max_num_pages,
max_file_size=docling_serve_settings.max_file_size,
)
run_worker(
rq_config=rq_config,
cm_config=cm_config,
)
def main() -> None:
app()
# Launch the CLI when calling python -m docling_serve
if __name__ == "__main__":
main()

View File

@@ -1,38 +1,78 @@
import asyncio
import copy
import importlib.metadata
import logging
import os
import tempfile
import shutil
import time
from contextlib import asynccontextmanager
from io import BytesIO
from pathlib import Path
from typing import Annotated, Any, Dict, List, Optional, Union
from typing import Annotated
from docling.datamodel.base_models import DocumentStream, InputFormat
from docling.document_converter import DocumentConverter
from dotenv import load_dotenv
from fastapi import BackgroundTasks, FastAPI, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import RedirectResponse
from pydantic import BaseModel
from docling_serve.docling_conversion import (
ConvertDocumentFileSourcesRequest,
ConvertDocumentsOptions,
ConvertDocumentsRequest,
convert_documents,
converters,
get_pdf_pipeline_opts,
from fastapi import (
BackgroundTasks,
Depends,
FastAPI,
Form,
HTTPException,
Query,
UploadFile,
WebSocket,
WebSocketDisconnect,
status,
)
from docling_serve.helper_functions import FormDepends, _str_to_bool
from docling_serve.response_preparation import ConvertDocumentResponse, process_results
from fastapi.middleware.cors import CORSMiddleware
from fastapi.openapi.docs import (
get_redoc_html,
get_swagger_ui_html,
get_swagger_ui_oauth2_redirect_html,
)
from fastapi.responses import JSONResponse, RedirectResponse
from fastapi.staticfiles import StaticFiles
from scalar_fastapi import get_scalar_api_reference
# Load local env vars if present
load_dotenv()
from docling.datamodel.base_models import DocumentStream
from docling_jobkit.datamodel.callback import (
ProgressCallbackRequest,
ProgressCallbackResponse,
)
from docling_jobkit.datamodel.http_inputs import FileSource, HttpSource
from docling_jobkit.datamodel.s3_coords import S3Coordinates
from docling_jobkit.datamodel.task import Task, TaskSource
from docling_jobkit.datamodel.task_targets import (
InBodyTarget,
TaskTarget,
ZipTarget,
)
from docling_jobkit.orchestrators.base_orchestrator import (
BaseOrchestrator,
ProgressInvalid,
TaskNotFoundError,
)
WITH_UI = _str_to_bool(os.getenv("WITH_UI", "False"))
if WITH_UI:
import gradio as gr
from docling_serve.gradio_ui import ui as gradio_ui
from docling_serve.auth import APIKeyAuth, AuthenticationResult
from docling_serve.datamodel.convert import ConvertDocumentsRequestOptions
from docling_serve.datamodel.requests import (
ConvertDocumentsRequest,
FileSourceRequest,
HttpSourceRequest,
S3SourceRequest,
TargetName,
)
from docling_serve.datamodel.responses import (
ClearResponse,
ConvertDocumentResponse,
HealthCheckResponse,
MessageKind,
PresignedUrlConvertDocumentResponse,
TaskStatusResponse,
WebsocketMessage,
)
from docling_serve.helper_functions import FormDepends
from docling_serve.orchestrator_factory import get_async_orchestrator
from docling_serve.response_preparation import prepare_response
from docling_serve.settings import docling_serve_settings
from docling_serve.storage import get_scratch
from docling_serve.websocket_notifier import WebsocketNotifier
# Set up custom logging as we'll be intermixes with FastAPI/Uvicorn's logging
@@ -70,155 +110,608 @@ _log = logging.getLogger(__name__)
# Context manager to initialize and clean up the lifespan of the FastAPI app
@asynccontextmanager
async def lifespan(app: FastAPI):
# settings = Settings()
scratch_dir = get_scratch()
# Converter with default options
pdf_format_option, options_hash = get_pdf_pipeline_opts(ConvertDocumentsOptions())
converters[options_hash] = DocumentConverter(
format_options={
InputFormat.PDF: pdf_format_option,
InputFormat.IMAGE: pdf_format_option,
}
)
orchestrator = get_async_orchestrator()
notifier = WebsocketNotifier(orchestrator)
orchestrator.bind_notifier(notifier)
converters[options_hash].initialize_pipeline(InputFormat.PDF)
# Warm up processing cache
if docling_serve_settings.load_models_at_boot:
await orchestrator.warm_up_caches()
# Start the background queue processor
queue_task = asyncio.create_task(orchestrator.process_queue())
yield
converters.clear()
if WITH_UI:
gradio_ui.close()
# Cancel the background queue processor on shutdown
queue_task.cancel()
try:
await queue_task
except asyncio.CancelledError:
_log.info("Queue processor cancelled.")
# Remove scratch directory in case it was a tempfile
if docling_serve_settings.scratch_path is not None:
shutil.rmtree(scratch_dir, ignore_errors=True)
##################################
# App creation and configuration #
##################################
app = FastAPI(
title="Docling Serve",
lifespan=lifespan,
)
origins = ["*"]
methods = ["*"]
headers = ["*"]
def create_app(): # noqa: C901
try:
version = importlib.metadata.version("docling_serve")
except importlib.metadata.PackageNotFoundError:
_log.warning("Unable to get docling_serve version, falling back to 0.0.0")
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=methods,
allow_headers=headers,
)
version = "0.0.0"
# Mount the Gradio app
if WITH_UI:
tmp_output_dir = Path(tempfile.mkdtemp())
gradio_ui.gradio_output_dir = tmp_output_dir
app = gr.mount_gradio_app(
app, gradio_ui, path="/ui", allowed_paths=["./logo.png", tmp_output_dir]
offline_docs_assets = False
if (
docling_serve_settings.static_path is not None
and (docling_serve_settings.static_path).is_dir()
):
offline_docs_assets = True
_log.info("Found static assets.")
require_auth = APIKeyAuth(docling_serve_settings.api_key)
app = FastAPI(
title="Docling Serve",
docs_url=None if offline_docs_assets else "/swagger",
redoc_url=None if offline_docs_assets else "/docs",
lifespan=lifespan,
version=version,
)
origins = docling_serve_settings.cors_origins
methods = docling_serve_settings.cors_methods
headers = docling_serve_settings.cors_headers
#############################
# API Endpoints definitions #
#############################
# Favicon
@app.get("/favicon.ico", include_in_schema=False)
async def favicon():
response = RedirectResponse(url="https://ds4sd.github.io/docling/assets/logo.png")
return response
# Status
class HealthCheckResponse(BaseModel):
status: str = "ok"
@app.get("/health")
def health() -> HealthCheckResponse:
return HealthCheckResponse()
# API readiness compatibility for OpenShift AI Workbench
@app.get("/api", include_in_schema=False)
def api_check() -> HealthCheckResponse:
return HealthCheckResponse()
# Convert a document from URL(s)
@app.post(
"/v1alpha/convert/source",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
# "description": "Return the JSON item or an image.",
}
},
)
def process_url(
background_tasks: BackgroundTasks, conversion_request: ConvertDocumentsRequest
):
sources: List[Union[str, DocumentStream]] = []
headers: Optional[Dict[str, Any]] = None
if isinstance(conversion_request, ConvertDocumentFileSourcesRequest):
for file_source in conversion_request.file_sources:
sources.append(file_source.to_document_stream())
else:
for http_source in conversion_request.http_sources:
sources.append(http_source.url)
if headers is None and http_source.headers:
headers = http_source.headers
# Note: results are only an iterator->lazy evaluation
results = convert_documents(
sources=sources, options=conversion_request.options, headers=headers
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=methods,
allow_headers=headers,
)
# The real processing will happen here
response = process_results(
background_tasks=background_tasks,
conversion_options=conversion_request.options,
conv_results=results,
# Mount the Gradio app
if docling_serve_settings.enable_ui:
try:
import gradio as gr
from docling_serve.gradio_ui import ui as gradio_ui
tmp_output_dir = get_scratch() / "gradio"
tmp_output_dir.mkdir(exist_ok=True, parents=True)
gradio_ui.gradio_output_dir = tmp_output_dir
app = gr.mount_gradio_app(
app,
gradio_ui,
path="/ui",
allowed_paths=["./logo.png", tmp_output_dir],
root_path="/ui",
)
except ImportError:
_log.warning(
"Docling Serve enable_ui is activated, but gradio is not installed. "
"Install it with `pip install docling-serve[ui]` "
"or `pip install gradio`"
)
#############################
# Offline assets definition #
#############################
if offline_docs_assets:
app.mount(
"/static",
StaticFiles(directory=docling_serve_settings.static_path),
name="static",
)
@app.get("/swagger", include_in_schema=False)
async def custom_swagger_ui_html():
return get_swagger_ui_html(
openapi_url=app.openapi_url,
title=app.title + " - Swagger UI",
oauth2_redirect_url=app.swagger_ui_oauth2_redirect_url,
swagger_js_url="/static/swagger-ui-bundle.js",
swagger_css_url="/static/swagger-ui.css",
)
@app.get(app.swagger_ui_oauth2_redirect_url, include_in_schema=False)
async def swagger_ui_redirect():
return get_swagger_ui_oauth2_redirect_html()
@app.get("/docs", include_in_schema=False)
async def redoc_html():
return get_redoc_html(
openapi_url=app.openapi_url,
title=app.title + " - ReDoc",
redoc_js_url="/static/redoc.standalone.js",
)
@app.get("/scalar", include_in_schema=False)
async def scalar_html():
return get_scalar_api_reference(
openapi_url=app.openapi_url,
title=app.title,
scalar_favicon_url="https://raw.githubusercontent.com/docling-project/docling/refs/heads/main/docs/assets/logo.svg",
# hide_client_button=True, # not yet released but in main
)
########################
# Async / Sync helpers #
########################
async def _enque_source(
orchestrator: BaseOrchestrator, conversion_request: ConvertDocumentsRequest
) -> Task:
sources: list[TaskSource] = []
for s in conversion_request.sources:
if isinstance(s, FileSourceRequest):
sources.append(FileSource.model_validate(s))
elif isinstance(s, HttpSourceRequest):
sources.append(HttpSource.model_validate(s))
elif isinstance(s, S3SourceRequest):
sources.append(S3Coordinates.model_validate(s))
task = await orchestrator.enqueue(
sources=sources,
options=conversion_request.options,
target=conversion_request.target,
)
return task
async def _enque_file(
orchestrator: BaseOrchestrator,
files: list[UploadFile],
options: ConvertDocumentsRequestOptions,
target: TaskTarget,
) -> Task:
_log.info(f"Received {len(files)} files for processing.")
# Load the uploaded files to Docling DocumentStream
file_sources: list[TaskSource] = []
for i, file in enumerate(files):
buf = BytesIO(file.file.read())
suffix = "" if len(file_sources) == 1 else f"_{i}"
name = file.filename if file.filename else f"file{suffix}.pdf"
file_sources.append(DocumentStream(name=name, stream=buf))
task = await orchestrator.enqueue(
sources=file_sources, options=options, target=target
)
return task
async def _wait_task_complete(orchestrator: BaseOrchestrator, task_id: str) -> bool:
start_time = time.monotonic()
while True:
task = await orchestrator.task_status(task_id=task_id)
if task.is_completed():
return True
await asyncio.sleep(5)
elapsed_time = time.monotonic() - start_time
if elapsed_time > docling_serve_settings.max_sync_wait:
return False
##########################################
# Downgrade openapi 3.1 to 3.0.x helpers #
##########################################
def ensure_array_items(schema):
"""Ensure that array items are defined."""
if "type" in schema and schema["type"] == "array":
if "items" not in schema or schema["items"] is None:
schema["items"] = {"type": "string"}
elif isinstance(schema["items"], dict):
if "type" not in schema["items"]:
schema["items"]["type"] = "string"
def handle_discriminators(schema):
"""Ensure that discriminator properties are included in required."""
if "discriminator" in schema and "propertyName" in schema["discriminator"]:
prop = schema["discriminator"]["propertyName"]
if "properties" in schema and prop in schema["properties"]:
if "required" not in schema:
schema["required"] = []
if prop not in schema["required"]:
schema["required"].append(prop)
def handle_properties(schema):
"""Ensure that property 'kind' is included in required."""
if "properties" in schema and "kind" in schema["properties"]:
if "required" not in schema:
schema["required"] = []
if "kind" not in schema["required"]:
schema["required"].append("kind")
# Downgrade openapi 3.1 to 3.0.x
def downgrade_openapi31_to_30(spec):
def strip_unsupported(obj):
if isinstance(obj, dict):
obj = {
k: strip_unsupported(v)
for k, v in obj.items()
if k not in ("const", "examples", "prefixItems")
}
handle_discriminators(obj)
ensure_array_items(obj)
# Check for oneOf and anyOf to handle nested schemas
for key in ["oneOf", "anyOf"]:
if key in obj:
for sub in obj[key]:
handle_discriminators(sub)
ensure_array_items(sub)
return obj
elif isinstance(obj, list):
return [strip_unsupported(i) for i in obj]
return obj
if "components" in spec and "schemas" in spec["components"]:
for schema_name, schema in spec["components"]["schemas"].items():
handle_properties(schema)
return strip_unsupported(copy.deepcopy(spec))
#############################
# API Endpoints definitions #
#############################
@app.get("/openapi-3.0.json")
def openapi_30():
spec = app.openapi()
downgraded = downgrade_openapi31_to_30(spec)
downgraded["openapi"] = "3.0.3"
return JSONResponse(downgraded)
# Favicon
@app.get("/favicon.ico", include_in_schema=False)
async def favicon():
logo_url = "https://raw.githubusercontent.com/docling-project/docling/refs/heads/main/docs/assets/logo.svg"
if offline_docs_assets:
logo_url = "/static/logo.svg"
response = RedirectResponse(url=logo_url)
return response
@app.get("/health")
def health() -> HealthCheckResponse:
return HealthCheckResponse()
# API readiness compatibility for OpenShift AI Workbench
@app.get("/api", include_in_schema=False)
def api_check() -> HealthCheckResponse:
return HealthCheckResponse()
# Convert a document from URL(s)
@app.post(
"/v1/convert/source",
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
# "description": "Return the JSON item or an image.",
}
},
)
async def process_url(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
conversion_request: ConvertDocumentsRequest,
):
task = await _enque_source(
orchestrator=orchestrator, conversion_request=conversion_request
)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
)
return response
if not completed:
# TODO: abort task!
return HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
# Convert a document from file(s)
@app.post(
"/v1alpha/convert/file",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def process_file(
background_tasks: BackgroundTasks,
files: List[UploadFile],
options: Annotated[ConvertDocumentsOptions, FormDepends(ConvertDocumentsOptions)],
):
_log.info(f"Received {len(files)} files for processing.")
# Load the uploaded files to Docling DocumentStream
file_sources = []
for file in files:
buf = BytesIO(file.file.read())
name = file.filename if file.filename else "file.pdf"
file_sources.append(DocumentStream(name=name, stream=buf))
results = convert_documents(sources=file_sources, options=options)
response = process_results(
background_tasks=background_tasks,
conversion_options=options,
conv_results=results,
# Convert a document from file(s)
@app.post(
"/v1/convert/file",
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def process_file(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
files: list[UploadFile],
options: Annotated[
ConvertDocumentsRequestOptions, FormDepends(ConvertDocumentsRequestOptions)
],
target_type: Annotated[TargetName, Form()] = TargetName.INBODY,
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
orchestrator=orchestrator, files=files, options=options, target=target
)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
)
return response
if not completed:
# TODO: abort task!
return HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
# Convert a document from URL(s) using the async api
@app.post(
"/v1/convert/source/async",
response_model=TaskStatusResponse,
)
async def process_url_async(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
conversion_request: ConvertDocumentsRequest,
):
task = await _enque_source(
orchestrator=orchestrator, conversion_request=conversion_request
)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
# Convert a document from file(s) using the async api
@app.post(
"/v1/convert/file/async",
response_model=TaskStatusResponse,
)
async def process_file_async(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
background_tasks: BackgroundTasks,
files: list[UploadFile],
options: Annotated[
ConvertDocumentsRequestOptions, FormDepends(ConvertDocumentsRequestOptions)
],
target_type: Annotated[TargetName, Form()] = TargetName.INBODY,
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
orchestrator=orchestrator, files=files, options=options, target=target
)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
# Task status poll
@app.get(
"/v1/status/poll/{task_id}",
response_model=TaskStatusResponse,
)
async def task_status_poll(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
task_id: str,
wait: Annotated[
float,
Query(description="Number of seconds to wait for a completed status."),
] = 0.0,
):
try:
task = await orchestrator.task_status(task_id=task_id, wait=wait)
task_queue_position = await orchestrator.get_queue_position(task_id=task_id)
except TaskNotFoundError:
raise HTTPException(status_code=404, detail="Task not found.")
return TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
# Task status websocket
@app.websocket(
"/v1/status/ws/{task_id}",
)
async def task_status_ws(
websocket: WebSocket,
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
task_id: str,
api_key: Annotated[str, Query()] = "",
):
if docling_serve_settings.api_key:
if api_key != docling_serve_settings.api_key:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Api key is required as ?api_key=SECRET.",
)
assert isinstance(orchestrator.notifier, WebsocketNotifier)
await websocket.accept()
if task_id not in orchestrator.tasks:
await websocket.send_text(
WebsocketMessage(
message=MessageKind.ERROR, error="Task not found."
).model_dump_json()
)
await websocket.close()
return
task = orchestrator.tasks[task_id]
# Track active WebSocket connections for this job
orchestrator.notifier.task_subscribers[task_id].add(websocket)
try:
task_queue_position = await orchestrator.get_queue_position(task_id=task_id)
task_response = TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
await websocket.send_text(
WebsocketMessage(
message=MessageKind.CONNECTION, task=task_response
).model_dump_json()
)
while True:
task_queue_position = await orchestrator.get_queue_position(
task_id=task_id
)
task_response = TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
await websocket.send_text(
WebsocketMessage(
message=MessageKind.UPDATE, task=task_response
).model_dump_json()
)
# each client message will be interpreted as a request for update
msg = await websocket.receive_text()
_log.debug(f"Received message: {msg}")
except WebSocketDisconnect:
_log.info(f"WebSocket disconnected for job {task_id}")
finally:
orchestrator.notifier.task_subscribers[task_id].remove(websocket)
# Task result
@app.get(
"/v1/result/{task_id}",
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def task_result(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
background_tasks: BackgroundTasks,
task_id: str,
):
try:
task_result = await orchestrator.task_result(task_id=task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task_id=task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
except TaskNotFoundError:
raise HTTPException(status_code=404, detail="Task not found.")
# Update task progress
@app.post(
"/v1/callback/task/progress",
response_model=ProgressCallbackResponse,
)
async def callback_task_progress(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
request: ProgressCallbackRequest,
):
try:
await orchestrator.receive_task_progress(request=request)
return ProgressCallbackResponse(status="ack")
except TaskNotFoundError:
raise HTTPException(status_code=404, detail="Task not found.")
except ProgressInvalid as err:
raise HTTPException(
status_code=400, detail=f"Invalid progress payload: {err}"
)
#### Clear requests
# Offload models
@app.get(
"/v1/clear/converters",
response_model=ClearResponse,
)
async def clear_converters(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
):
await orchestrator.clear_converters()
return ClearResponse()
# Clean results
@app.get(
"/v1/clear/results",
response_model=ClearResponse,
)
async def clear_results(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
older_then: float = 3600,
):
await orchestrator.clear_results(older_than=older_then)
return ClearResponse()
return app

56
docling_serve/auth.py Normal file
View File

@@ -0,0 +1,56 @@
from typing import Any
from fastapi import HTTPException, Request, status
from fastapi.security import APIKeyHeader
from pydantic import BaseModel
class AuthenticationResult(BaseModel):
valid: bool
errors: list[str] = []
detail: Any | None = None
class APIKeyAuth(APIKeyHeader):
"""
FastAPI dependency which evaluates a status API Key.
"""
def __init__(
self,
api_key: str,
header_name: str = "X-Api-Key",
fail_on_unauthorized: bool = True,
) -> None:
self.api_key = api_key
self.header_name = header_name
super().__init__(name=self.header_name, auto_error=False)
async def _validate_api_key(self, header_api_key: str | None):
if header_api_key is None:
return AuthenticationResult(
valid=False, errors=[f"Missing header {self.header_name}."]
)
header_api_key = header_api_key.strip()
# Otherwise check the apikey
if header_api_key == self.api_key or self.api_key == "":
return AuthenticationResult(
valid=True,
detail=header_api_key,
)
else:
return AuthenticationResult(
valid=False,
errors=["The provided API Key is invalid."],
)
async def __call__(self, request: Request) -> AuthenticationResult: # type: ignore
header_api_key = await super().__call__(request=request)
result = await self._validate_api_key(header_api_key)
if self.api_key and not result.valid:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail=result.detail
)
return result

View File

View File

@@ -0,0 +1,40 @@
# Define the input options for the API
from typing import Annotated
from pydantic import Field
from docling.datamodel.pipeline_options import (
EasyOcrOptions,
)
from docling.models.factories import get_ocr_factory
from docling_jobkit.datamodel.convert import ConvertDocumentsOptions
from docling_serve.settings import docling_serve_settings
ocr_factory = get_ocr_factory(
allow_external_plugins=docling_serve_settings.allow_external_plugins
)
ocr_engines_enum = ocr_factory.get_enum()
class ConvertDocumentsRequestOptions(ConvertDocumentsOptions):
ocr_engine: Annotated[ # type: ignore
ocr_engines_enum,
Field(
description=(
"The OCR engine to use. String. "
f"Allowed values: {', '.join([v.value for v in ocr_engines_enum])}. "
"Optional, defaults to easyocr."
),
examples=[EasyOcrOptions.kind],
),
] = ocr_engines_enum(EasyOcrOptions.kind) # type: ignore
document_timeout: Annotated[
float,
Field(
description="The timeout for processing each document, in seconds.",
gt=0,
le=docling_serve_settings.max_document_timeout,
),
] = docling_serve_settings.max_document_timeout

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@@ -0,0 +1,72 @@
import enum
from typing import Annotated, Literal
from pydantic import BaseModel, Field, model_validator
from pydantic_core import PydanticCustomError
from typing_extensions import Self
from docling_jobkit.datamodel.http_inputs import FileSource, HttpSource
from docling_jobkit.datamodel.s3_coords import S3Coordinates
from docling_jobkit.datamodel.task_targets import (
InBodyTarget,
S3Target,
TaskTarget,
ZipTarget,
)
from docling_serve.datamodel.convert import ConvertDocumentsRequestOptions
from docling_serve.settings import AsyncEngine, docling_serve_settings
## Sources
class FileSourceRequest(FileSource):
kind: Literal["file"] = "file"
class HttpSourceRequest(HttpSource):
kind: Literal["http"] = "http"
class S3SourceRequest(S3Coordinates):
kind: Literal["s3"] = "s3"
## Multipart targets
class TargetName(str, enum.Enum):
INBODY = InBodyTarget().kind
ZIP = ZipTarget().kind
## Aliases
SourceRequestItem = Annotated[
FileSourceRequest | HttpSourceRequest | S3SourceRequest, Field(discriminator="kind")
]
## Complete Source request
class ConvertDocumentsRequest(BaseModel):
options: ConvertDocumentsRequestOptions = ConvertDocumentsRequestOptions()
sources: list[SourceRequestItem]
target: TaskTarget = InBodyTarget()
@model_validator(mode="after")
def validate_s3_source_and_target(self) -> Self:
for source in self.sources:
if isinstance(source, S3SourceRequest):
if docling_serve_settings.eng_kind != AsyncEngine.KFP:
raise PydanticCustomError(
"error source", 'source kind "s3" requires engine kind "KFP"'
)
if self.target.kind != "s3":
raise PydanticCustomError(
"error source", 'source kind "s3" requires target kind "s3"'
)
if isinstance(self.target, S3Target):
for source in self.sources:
if isinstance(source, S3SourceRequest):
return self
raise PydanticCustomError(
"error target", 'target kind "s3" requires source kind "s3"'
)
return self

View File

@@ -0,0 +1,56 @@
import enum
from typing import Optional
from pydantic import BaseModel
from docling.datamodel.document import ConversionStatus, ErrorItem
from docling.utils.profiling import ProfilingItem
from docling_jobkit.datamodel.result import ExportDocumentResponse
from docling_jobkit.datamodel.task_meta import TaskProcessingMeta
# Status
class HealthCheckResponse(BaseModel):
status: str = "ok"
class ClearResponse(BaseModel):
status: str = "ok"
class ConvertDocumentResponse(BaseModel):
document: ExportDocumentResponse
status: ConversionStatus
errors: list[ErrorItem] = []
processing_time: float
timings: dict[str, ProfilingItem] = {}
class PresignedUrlConvertDocumentResponse(BaseModel):
processing_time: float
num_converted: int
num_succeeded: int
num_failed: int
class ConvertDocumentErrorResponse(BaseModel):
status: ConversionStatus
class TaskStatusResponse(BaseModel):
task_id: str
task_status: str
task_position: Optional[int] = None
task_meta: Optional[TaskProcessingMeta] = None
class MessageKind(str, enum.Enum):
CONNECTION = "connection"
UPDATE = "update"
ERROR = "error"
class WebsocketMessage(BaseModel):
message: MessageKind
task: Optional[TaskStatusResponse] = None
error: Optional[str] = None

View File

@@ -1,400 +0,0 @@
import base64
import hashlib
import json
import logging
from io import BytesIO
from pathlib import Path
from typing import (
Annotated,
Any,
Dict,
Iterable,
Iterator,
List,
Optional,
Tuple,
Type,
Union,
)
from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.backend.docling_parse_v2_backend import DoclingParseV2DocumentBackend
from docling.backend.pdf_backend import PdfDocumentBackend
from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
from docling.datamodel.base_models import DocumentStream, InputFormat, OutputFormat
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import (
EasyOcrOptions,
OcrEngine,
OcrOptions,
PdfBackend,
PdfPipelineOptions,
RapidOcrOptions,
TableFormerMode,
TesseractOcrOptions,
)
from docling.document_converter import DocumentConverter, FormatOption, PdfFormatOption
from docling_core.types.doc import ImageRefMode
from fastapi import HTTPException
from pydantic import BaseModel, Field
from docling_serve.helper_functions import _to_list_of_strings
_log = logging.getLogger(__name__)
# Define the input options for the API
class ConvertDocumentsOptions(BaseModel):
from_formats: Annotated[
List[InputFormat],
Field(
description=(
"Input format(s) to convert from. String or list of strings. "
f"Allowed values: {', '.join([v.value for v in InputFormat])}. "
"Optional, defaults to all formats."
),
examples=[[v.value for v in InputFormat]],
),
] = [v for v in InputFormat]
to_formats: Annotated[
List[OutputFormat],
Field(
description=(
"Output format(s) to convert to. String or list of strings. "
f"Allowed values: {', '.join([v.value for v in OutputFormat])}. "
"Optional, defaults to Markdown."
),
examples=[[OutputFormat.MARKDOWN]],
),
] = [OutputFormat.MARKDOWN]
image_export_mode: Annotated[
ImageRefMode,
Field(
description=(
"Image export mode for the document (in case of JSON,"
" Markdown or HTML). "
f"Allowed values: {', '.join([v.value for v in ImageRefMode])}. "
"Optional, defaults to Embedded."
),
examples=[ImageRefMode.EMBEDDED.value],
# pattern="embedded|placeholder|referenced",
),
] = ImageRefMode.EMBEDDED
do_ocr: Annotated[
bool,
Field(
description=(
"If enabled, the bitmap content will be processed using OCR. "
"Boolean. Optional, defaults to true"
),
# examples=[True],
),
] = True
force_ocr: Annotated[
bool,
Field(
description=(
"If enabled, replace existing text with OCR-generated "
"text over content. Boolean. Optional, defaults to false."
),
# examples=[False],
),
] = False
# TODO: use a restricted list based on what is installed on the system
ocr_engine: Annotated[
OcrEngine,
Field(
description=(
"The OCR engine to use. String. "
"Allowed values: easyocr, tesseract, rapidocr. "
"Optional, defaults to easyocr."
),
examples=[OcrEngine.EASYOCR],
),
] = OcrEngine.EASYOCR
ocr_lang: Annotated[
Optional[List[str]],
Field(
description=(
"List of languages used by the OCR engine. "
"Note that each OCR engine has "
"different values for the language names. String or list of strings. "
"Optional, defaults to empty."
),
examples=[["fr", "de", "es", "en"]],
),
] = None
pdf_backend: Annotated[
PdfBackend,
Field(
description=(
"The PDF backend to use. String. "
f"Allowed values: {', '.join([v.value for v in PdfBackend])}. "
f"Optional, defaults to {PdfBackend.DLPARSE_V2.value}."
),
examples=[PdfBackend.DLPARSE_V2],
),
] = PdfBackend.DLPARSE_V2
table_mode: Annotated[
TableFormerMode,
Field(
TableFormerMode.FAST,
description=(
"Mode to use for table structure, String. "
f"Allowed values: {', '.join([v.value for v in TableFormerMode])}. "
"Optional, defaults to fast."
),
examples=[TableFormerMode.FAST],
# pattern="fast|accurate",
),
] = TableFormerMode.FAST
abort_on_error: Annotated[
bool,
Field(
description=(
"Abort on error if enabled. " "Boolean. Optional, defaults to false."
),
# examples=[False],
),
] = False
return_as_file: Annotated[
bool,
Field(
description=(
"Return the output as a zip file "
"(will happen anyway if multiple files are generated). "
"Boolean. Optional, defaults to false."
),
examples=[False],
),
] = False
do_table_structure: Annotated[
bool,
Field(
description=(
"If enabled, the table structure will be extracted. "
"Boolean. Optional, defaults to true."
),
examples=[True],
),
] = True
include_images: Annotated[
bool,
Field(
description=(
"If enabled, images will be extracted from the document. "
"Boolean. Optional, defaults to true."
),
examples=[True],
),
] = True
images_scale: Annotated[
float,
Field(
description="Scale factor for images. Float. Optional, defaults to 2.0.",
examples=[2.0],
),
] = 2.0
class DocumentsConvertBase(BaseModel):
options: ConvertDocumentsOptions = ConvertDocumentsOptions()
class HttpSource(BaseModel):
url: Annotated[
str,
Field(
description="HTTP url to process",
examples=["https://arxiv.org/pdf/2206.01062"],
),
]
headers: Annotated[
Dict[str, Any],
Field(
description="Additional headers used to fetch the urls, "
"e.g. authorization, agent, etc"
),
] = {}
class FileSource(BaseModel):
base64_string: Annotated[
str,
Field(
description="Content of the file serialized in base64. "
"For example it can be obtained via "
"`base64 -w 0 /path/to/file/pdf-to-convert.pdf`."
),
]
filename: Annotated[
str,
Field(description="Filename of the uploaded document", examples=["file.pdf"]),
]
def to_document_stream(self) -> DocumentStream:
buf = BytesIO(base64.b64decode(self.base64_string))
return DocumentStream(stream=buf, name=self.filename)
class ConvertDocumentHttpSourcesRequest(DocumentsConvertBase):
http_sources: List[HttpSource]
class ConvertDocumentFileSourcesRequest(DocumentsConvertBase):
file_sources: List[FileSource]
ConvertDocumentsRequest = Union[
ConvertDocumentFileSourcesRequest, ConvertDocumentHttpSourcesRequest
]
# Document converters will be preloaded and stored in a dictionary
converters: Dict[str, DocumentConverter] = {}
# Custom serializer for PdfFormatOption
# (model_dump_json does not work with some classes)
def _serialize_pdf_format_option(pdf_format_option: PdfFormatOption) -> str:
data = pdf_format_option.model_dump()
# pipeline_options are not fully serialized by model_dump, dedicated pass
if pdf_format_option.pipeline_options:
data["pipeline_options"] = pdf_format_option.pipeline_options.model_dump()
# Replace `pipeline_cls` with a string representation
data["pipeline_cls"] = repr(data["pipeline_cls"])
# Replace `backend` with a string representation
data["backend"] = repr(data["backend"])
# Handle `device` in `accelerator_options`
if "accelerator_options" in data and "device" in data["accelerator_options"]:
data["accelerator_options"]["device"] = repr(
data["accelerator_options"]["device"]
)
# Serialize the dictionary to JSON with sorted keys to have consistent hashes
return json.dumps(data, sort_keys=True)
# Computes the PDF pipeline options and returns the PdfFormatOption and its hash
def get_pdf_pipeline_opts(
request: ConvertDocumentsOptions,
) -> Tuple[PdfFormatOption, str]:
if request.ocr_engine == OcrEngine.EASYOCR:
try:
import easyocr # noqa: F401
except ImportError:
raise HTTPException(
status_code=400,
detail="The requested OCR engine"
f" (ocr_engine={request.ocr_engine.value})"
" is not available on this system. Please choose another OCR engine "
"or contact your system administrator.",
)
ocr_options: OcrOptions = EasyOcrOptions(force_full_page_ocr=request.force_ocr)
elif request.ocr_engine == OcrEngine.TESSERACT:
try:
import tesserocr # noqa: F401
except ImportError:
raise HTTPException(
status_code=400,
detail="The requested OCR engine"
f" (ocr_engine={request.ocr_engine.value})"
" is not available on this system. Please choose another OCR engine "
"or contact your system administrator.",
)
ocr_options = TesseractOcrOptions(force_full_page_ocr=request.force_ocr)
elif request.ocr_engine == OcrEngine.RAPIDOCR:
try:
from rapidocr_onnxruntime import RapidOCR # noqa: F401
except ImportError:
raise HTTPException(
status_code=400,
detail="The requested OCR engine"
f" (ocr_engine={request.ocr_engine.value})"
" is not available on this system. Please choose another OCR engine "
"or contact your system administrator.",
)
ocr_options = RapidOcrOptions(force_full_page_ocr=request.force_ocr)
else:
raise RuntimeError(f"Unexpected OCR engine type {request.ocr_engine}")
if request.ocr_lang is not None:
if isinstance(request.ocr_lang, str):
ocr_options.lang = _to_list_of_strings(request.ocr_lang)
else:
ocr_options.lang = request.ocr_lang
pipeline_options = PdfPipelineOptions(
do_ocr=request.do_ocr,
ocr_options=ocr_options,
do_table_structure=request.do_table_structure,
)
pipeline_options.table_structure_options.do_cell_matching = True # do_cell_matching
pipeline_options.table_structure_options.mode = TableFormerMode(request.table_mode)
if request.image_export_mode != ImageRefMode.PLACEHOLDER:
pipeline_options.generate_page_images = True
if request.images_scale:
pipeline_options.images_scale = request.images_scale
if request.pdf_backend == PdfBackend.DLPARSE_V1:
backend: Type[PdfDocumentBackend] = DoclingParseDocumentBackend
elif request.pdf_backend == PdfBackend.DLPARSE_V2:
backend = DoclingParseV2DocumentBackend
elif request.pdf_backend == PdfBackend.PYPDFIUM2:
backend = PyPdfiumDocumentBackend
else:
raise RuntimeError(f"Unexpected PDF backend type {request.pdf_backend}")
pdf_format_option = PdfFormatOption(
pipeline_options=pipeline_options,
backend=backend,
)
serialized_data = _serialize_pdf_format_option(pdf_format_option)
options_hash = hashlib.sha1(serialized_data.encode()).hexdigest()
return pdf_format_option, options_hash
def convert_documents(
sources: Iterable[Union[Path, str, DocumentStream]],
options: ConvertDocumentsOptions,
headers: Optional[Dict[str, Any]] = None,
):
pdf_format_option, options_hash = get_pdf_pipeline_opts(options)
if options_hash not in converters:
format_options: Dict[InputFormat, FormatOption] = {
InputFormat.PDF: pdf_format_option,
InputFormat.IMAGE: pdf_format_option,
}
converters[options_hash] = DocumentConverter(format_options=format_options)
_log.info(f"We now have {len(converters)} converters in memory.")
results: Iterator[ConversionResult] = converters[options_hash].convert_all(
sources,
headers=headers,
)
return results

View File

@@ -1,17 +1,52 @@
import base64
import importlib
import itertools
import json
import logging
import os
import ssl
import tempfile
import time
from pathlib import Path
from typing import Optional
import certifi
import gradio as gr
import requests
import httpx
from docling.datamodel.base_models import FormatToExtensions
from docling.datamodel.pipeline_options import (
PdfBackend,
ProcessingPipeline,
TableFormerMode,
TableStructureOptions,
)
from docling_serve.helper_functions import _to_list_of_strings
from docling_serve.settings import docling_serve_settings, uvicorn_settings
logger = logging.getLogger(__name__)
############################
# Path of static artifacts #
############################
logo_path = "https://raw.githubusercontent.com/docling-project/docling/refs/heads/main/docs/assets/logo.svg"
js_components_url = "https://unpkg.com/@docling/docling-components@0.0.7"
if (
docling_serve_settings.static_path is not None
and docling_serve_settings.static_path.is_dir()
):
logo_path = str(docling_serve_settings.static_path / "logo.svg")
js_components_url = "/static/docling-components.js"
##############################
# Head JS for web components #
##############################
head = f"""
<script src="{js_components_url}" type="module"></script>
"""
#################
# CSS and theme #
#################
@@ -49,6 +84,14 @@ css = """
#file_input_zone {
height: 140px;
}
docling-img {
gap: 1rem;
}
docling-img::part(page) {
box-shadow: 0 0.5rem 1rem 0 rgba(0, 0, 0, 0.2);
}
"""
theme = gr.themes.Default(
@@ -80,8 +123,29 @@ file_output_path = None # Will be set when a new file is generated
#############
def get_api_endpoint() -> str:
protocol = "http"
if uvicorn_settings.ssl_keyfile is not None:
protocol = "https"
return f"{protocol}://{docling_serve_settings.api_host}:{uvicorn_settings.port}"
def get_ssl_context() -> ssl.SSLContext:
ctx = ssl.create_default_context(cafile=certifi.where())
kube_sa_ca_cert_path = Path(
"/run/secrets/kubernetes.io/serviceaccount/service-ca.crt"
)
if (
uvicorn_settings.ssl_keyfile is not None
and ".svc." in docling_serve_settings.api_host
and kube_sa_ca_cert_path.exists()
):
ctx.load_verify_locations(cafile=kube_sa_ca_cert_path)
return ctx
def health_check():
response = requests.get(f"http://localhost:{int(os.getenv('PORT', '5001'))}/health")
response = httpx.get(f"{get_api_endpoint()}/health")
if response.status_code == 200:
return "Healthy"
return "Unhealthy"
@@ -97,6 +161,11 @@ def set_outputs_visibility_direct(x, y):
return content, file
def set_task_id_visibility(x):
task_id_row = gr.Row(visible=x)
return task_id_row
def set_outputs_visibility_process(x):
content = gr.Row(visible=not x)
file = gr.Row(visible=x)
@@ -108,16 +177,20 @@ def set_download_button_label(label_text: gr.State):
def clear_outputs():
task_id_rendered = ""
markdown_content = ""
json_content = ""
json_rendered_content = ""
html_content = ""
text_content = ""
doctags_content = ""
return (
task_id_rendered,
markdown_content,
markdown_content,
json_content,
json_rendered_content,
html_content,
html_content,
text_content,
@@ -133,12 +206,16 @@ def clear_file_input():
return None
def auto_set_return_as_file(url_input, file_input, image_export_mode):
def auto_set_return_as_file(
url_input_value: str,
file_input_value: Optional[list[str]],
image_export_mode_value: str,
):
# If more than one input source is provided, return as file
if (
(len(url_input.split(",")) > 1)
or (file_input and len(file_input) > 1)
or (image_export_mode == "referenced")
(len(url_input_value.split(",")) > 1)
or (file_input_value and len(file_input_value) > 1)
or (image_export_mode_value == "referenced")
):
return True
else:
@@ -156,10 +233,64 @@ def change_ocr_lang(ocr_engine):
return "english,chinese"
def wait_task_finish(auth: str, task_id: str, return_as_file: bool):
conversion_sucess = False
task_finished = False
task_status = ""
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
ssl_ctx = get_ssl_context()
while not task_finished:
try:
response = httpx.get(
f"{get_api_endpoint()}/v1/status/poll/{task_id}?wait=5",
headers=headers,
verify=ssl_ctx,
timeout=15,
)
task_status = response.json()["task_status"]
if task_status == "success":
conversion_sucess = True
task_finished = True
if task_status in ("failure", "revoked"):
conversion_sucess = False
task_finished = True
raise RuntimeError(f"Task failed with status {task_status!r}")
time.sleep(5)
except Exception as e:
logger.error(f"Error processing file(s): {e}")
conversion_sucess = False
task_finished = True
raise gr.Error(f"Error processing file(s): {e}", print_exception=False)
if conversion_sucess:
try:
response = httpx.get(
f"{get_api_endpoint()}/v1/result/{task_id}",
headers=headers,
timeout=15,
verify=ssl_ctx,
)
output = response_to_output(response, return_as_file)
return output
except Exception as e:
logger.error(f"Error getting task result: {e}")
raise gr.Error(
f"Error getting task result, conversion finished with status: {task_status}"
)
def process_url(
auth,
input_sources,
to_formats,
image_export_mode,
pipeline,
ocr,
force_ocr,
ocr_engine,
@@ -168,12 +299,20 @@ def process_url(
table_mode,
abort_on_error,
return_as_file,
do_code_enrichment,
do_formula_enrichment,
do_picture_classification,
do_picture_description,
):
target = {"kind": "zip" if return_as_file else "inbody"}
parameters = {
"http_sources": [{"url": source} for source in input_sources.split(",")],
"sources": [
{"kind": "http", "url": source} for source in input_sources.split(",")
],
"options": {
"to_formats": to_formats,
"image_export_mode": image_export_mode,
"pipeline": pipeline,
"ocr": ocr,
"force_ocr": force_ocr,
"ocr_engine": ocr_engine,
@@ -181,20 +320,34 @@ def process_url(
"pdf_backend": pdf_backend,
"table_mode": table_mode,
"abort_on_error": abort_on_error,
"return_as_file": return_as_file,
"do_code_enrichment": do_code_enrichment,
"do_formula_enrichment": do_formula_enrichment,
"do_picture_classification": do_picture_classification,
"do_picture_description": do_picture_description,
},
"target": target,
}
if (
not parameters["http_sources"]
or len(parameters["http_sources"]) == 0
or parameters["http_sources"][0]["url"] == ""
not parameters["sources"]
or len(parameters["sources"]) == 0
or parameters["sources"][0]["url"] == ""
):
logger.error("No input sources provided.")
raise gr.Error("No input sources provided.", print_exception=False)
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
print(f"{headers=}")
try:
response = requests.post(
f"http://localhost:{int(os.getenv('PORT', '5001'))}/v1alpha/convert/source",
ssl_ctx = get_ssl_context()
response = httpx.post(
f"{get_api_endpoint()}/v1/convert/source/async",
json=parameters,
headers=headers,
verify=ssl_ctx,
timeout=60,
)
except Exception as e:
logger.error(f"Error processing URL: {e}")
@@ -204,14 +357,23 @@ def process_url(
error_message = data.get("detail", "An unknown error occurred.")
logger.error(f"Error processing file: {error_message}")
raise gr.Error(f"Error processing file: {error_message}", print_exception=False)
output = response_to_output(response, return_as_file)
return output
task_id_rendered = response.json()["task_id"]
return task_id_rendered
def file_to_base64(file):
with open(file.name, "rb") as f:
encoded_string = base64.b64encode(f.read()).decode("utf-8")
return encoded_string
def process_file(
auth,
files,
to_formats,
image_export_mode,
pipeline,
ocr,
force_ocr,
ocr_engine,
@@ -220,30 +382,54 @@ def process_file(
table_mode,
abort_on_error,
return_as_file,
do_code_enrichment,
do_formula_enrichment,
do_picture_classification,
do_picture_description,
):
if not files or len(files) == 0 or files[0] == "":
if not files or len(files) == 0:
logger.error("No files provided.")
raise gr.Error("No files provided.", print_exception=False)
files_data = [("files", (file.name, open(file.name, "rb"))) for file in files]
files_data = [
{"kind": "file", "base64_string": file_to_base64(file), "filename": file.name}
for file in files
]
target = {"kind": "zip" if return_as_file else "inbody"}
parameters = {
"to_formats": to_formats,
"image_export_mode": image_export_mode,
"ocr": str(ocr).lower(),
"force_ocr": str(force_ocr).lower(),
"ocr_engine": ocr_engine,
"ocr_lang": _to_list_of_strings(ocr_lang),
"pdf_backend": pdf_backend,
"table_mode": table_mode,
"abort_on_error": str(abort_on_error).lower(),
"return_as_file": str(return_as_file).lower(),
"sources": files_data,
"options": {
"to_formats": to_formats,
"image_export_mode": image_export_mode,
"pipeline": pipeline,
"ocr": ocr,
"force_ocr": force_ocr,
"ocr_engine": ocr_engine,
"ocr_lang": _to_list_of_strings(ocr_lang),
"pdf_backend": pdf_backend,
"table_mode": table_mode,
"abort_on_error": abort_on_error,
"return_as_file": return_as_file,
"do_code_enrichment": do_code_enrichment,
"do_formula_enrichment": do_formula_enrichment,
"do_picture_classification": do_picture_classification,
"do_picture_description": do_picture_description,
},
"target": target,
}
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
try:
response = requests.post(
f"http://localhost:{int(os.getenv('PORT', '5001'))}/v1alpha/convert/file",
files=files_data,
data=parameters,
ssl_ctx = get_ssl_context()
response = httpx.post(
f"{get_api_endpoint()}/v1/convert/source/async",
json=parameters,
headers=headers,
verify=ssl_ctx,
timeout=60,
)
except Exception as e:
logger.error(f"Error processing file(s): {e}")
@@ -253,13 +439,15 @@ def process_file(
error_message = data.get("detail", "An unknown error occurred.")
logger.error(f"Error processing file: {error_message}")
raise gr.Error(f"Error processing file: {error_message}", print_exception=False)
output = response_to_output(response, return_as_file)
return output
task_id_rendered = response.json()["task_id"]
return task_id_rendered
def response_to_output(response, return_as_file):
markdown_content = ""
json_content = ""
json_rendered_content = ""
html_content = ""
text_content = ""
doctags_content = ""
@@ -282,6 +470,12 @@ def response_to_output(response, return_as_file):
json_content = json.dumps(
full_content.get("document").get("json_content"), indent=2
)
# Embed document JSON and trigger load at client via an image.
json_rendered_content = f"""
<docling-img id="dclimg" pagenumbers><docling-tooltip></docling-tooltip></docling-img>
<script id="dcljson" type="application/json" onload="document.getElementById('dclimg').src = JSON.parse(document.getElementById('dcljson').textContent);">{json_content}</script>
<img src onerror="document.getElementById('dclimg').src = JSON.parse(document.getElementById('dcljson').textContent);" />
"""
html_content = full_content.get("document").get("html_content")
text_content = full_content.get("document").get("text_content")
doctags_content = full_content.get("document").get("doctags_content")
@@ -289,6 +483,7 @@ def response_to_output(response, return_as_file):
markdown_content,
markdown_content,
json_content,
json_rendered_content,
html_content,
html_content,
text_content,
@@ -302,12 +497,12 @@ def response_to_output(response, return_as_file):
############
with gr.Blocks(
head=head,
css=css,
theme=theme,
title="Docling Serve",
delete_cache=(3600, 3600), # Delete all files older than 1 hour every hour
delete_cache=(3600, 36000), # Delete all files older than 10 hour every hour
) as ui:
# Constants stored in states to be able to pass them as inputs to functions
processing_text = gr.State("Processing your document(s), please wait...")
true_bool = gr.State(True)
@@ -317,17 +512,21 @@ with gr.Blocks(
with gr.Row(elem_id="check_health"):
# Logo
with gr.Column(scale=1, min_width=90):
gr.Image(
"https://ds4sd.github.io/docling/assets/logo.png",
height=80,
width=80,
show_download_button=False,
show_label=False,
show_fullscreen_button=False,
container=False,
elem_id="logo",
scale=0,
)
try:
gr.Image(
logo_path,
height=80,
width=80,
show_download_button=False,
show_label=False,
show_fullscreen_button=False,
container=False,
elem_id="logo",
scale=0,
)
except Exception:
logger.warning("Logo not found.")
# Title
with gr.Column(scale=1, min_width=200):
gr.Markdown(
@@ -356,59 +555,60 @@ with gr.Blocks(
)
# URL Processing Tab
with gr.Tab("Convert URL(s)"):
with gr.Tab("Convert URL"):
with gr.Row():
with gr.Column(scale=4):
url_input = gr.Textbox(
label="Input Sources (comma-separated URLs)",
placeholder="https://arxiv.org/pdf/2206.01062",
label="URL Input Source",
placeholder="https://arxiv.org/pdf/2501.17887",
)
with gr.Column(scale=1):
url_process_btn = gr.Button("Process URL(s)", scale=1)
url_process_btn = gr.Button("Process URL", scale=1)
url_reset_btn = gr.Button("Reset", scale=1)
# File Processing Tab
with gr.Tab("Convert File(s)"):
with gr.Tab("Convert File"):
with gr.Row():
with gr.Column(scale=4):
file_input = gr.File(
elem_id="file_input_zone",
label="Upload Files",
label="Upload File",
file_types=[
".pdf",
".docx",
".pptx",
".html",
".xlsx",
".asciidoc",
".txt",
".md",
".jpg",
".jpeg",
".png",
".gif",
f".{v}"
for v in itertools.chain.from_iterable(
FormatToExtensions.values()
)
],
file_count="multiple",
scale=4,
)
with gr.Column(scale=1):
file_process_btn = gr.Button("Process File(s)", scale=1)
file_process_btn = gr.Button("Process File", scale=1)
file_reset_btn = gr.Button("Reset", scale=1)
# Auth
with gr.Row(visible=bool(docling_serve_settings.api_key)):
with gr.Column():
auth = gr.Textbox(
label="Authentication",
placeholder="API Key",
type="password",
)
# Options
with gr.Accordion("Options") as options:
with gr.Row():
with gr.Column(scale=1):
to_formats = gr.CheckboxGroup(
[
("Markdown", "md"),
("Docling (JSON)", "json"),
("Markdown", "md"),
("HTML", "html"),
("Plain Text", "text"),
("Doc Tags", "doctags"),
],
label="To Formats",
value=["md"],
value=["json", "md"],
)
with gr.Column(scale=1):
image_export_mode = gr.Radio(
@@ -420,6 +620,14 @@ with gr.Blocks(
label="Image Export Mode",
value="embedded",
)
with gr.Row():
with gr.Column(scale=1, min_width=200):
pipeline = gr.Radio(
[(v.value.capitalize(), v.value) for v in ProcessingPipeline],
label="Pipeline type",
value=ProcessingPipeline.STANDARD.value,
)
with gr.Row():
with gr.Column(scale=1, min_width=200):
ocr = gr.Checkbox(label="Enable OCR", value=True)
@@ -440,30 +648,53 @@ with gr.Blocks(
)
ocr_engine.change(change_ocr_lang, inputs=[ocr_engine], outputs=[ocr_lang])
with gr.Row():
with gr.Column(scale=2):
with gr.Column(scale=4):
pdf_backend = gr.Radio(
["pypdfium2", "dlparse_v1", "dlparse_v2"],
[v.value for v in PdfBackend],
label="PDF Backend",
value="dlparse_v2",
value=PdfBackend.DLPARSE_V4.value,
)
with gr.Column(scale=2):
table_mode = gr.Radio(
["fast", "accurate"], label="Table Mode", value="fast"
[(v.value.capitalize(), v.value) for v in TableFormerMode],
label="Table Mode",
value=TableStructureOptions().mode.value,
)
with gr.Column(scale=1):
abort_on_error = gr.Checkbox(label="Abort on Error", value=False)
return_as_file = gr.Checkbox(label="Return as File", value=False)
with gr.Row():
with gr.Column():
do_code_enrichment = gr.Checkbox(
label="Enable code enrichment", value=False
)
do_formula_enrichment = gr.Checkbox(
label="Enable formula enrichment", value=False
)
with gr.Column():
do_picture_classification = gr.Checkbox(
label="Enable picture classification", value=False
)
do_picture_description = gr.Checkbox(
label="Enable picture description", value=False
)
# Task id output
with gr.Row(visible=False) as task_id_output:
task_id_rendered = gr.Textbox(label="Task id", interactive=False)
# Document output
with gr.Row(visible=False) as content_output:
with gr.Tab("Docling (JSON)"):
output_json = gr.Code(language="json", wrap_lines=True, show_label=False)
with gr.Tab("Docling-Rendered"):
output_json_rendered = gr.HTML(label="Response")
with gr.Tab("Markdown"):
output_markdown = gr.Code(
language="markdown", wrap_lines=True, show_label=False
)
with gr.Tab("Markdown-Rendered"):
output_markdown_rendered = gr.Markdown(label="Response")
with gr.Tab("Docling (JSON)"):
output_json = gr.Code(language="json", wrap_lines=True, show_label=False)
with gr.Tab("HTML"):
output_html = gr.Code(language="html", wrap_lines=True, show_label=False)
with gr.Tab("HTML-Rendered"):
@@ -503,28 +734,32 @@ with gr.Blocks(
set_options_visibility, inputs=[false_bool], outputs=[options]
).then(
set_download_button_label, inputs=[processing_text], outputs=[download_file_btn]
).then(
set_outputs_visibility_process,
inputs=[return_as_file],
outputs=[content_output, file_output],
).then(
clear_outputs,
inputs=None,
outputs=[
task_id_rendered,
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
output_doctags,
],
).then(
set_task_id_visibility,
inputs=[true_bool],
outputs=[task_id_output],
).then(
process_url,
inputs=[
auth,
url_input,
to_formats,
image_export_mode,
pipeline,
ocr,
force_ocr,
ocr_engine,
@@ -533,11 +768,26 @@ with gr.Blocks(
table_mode,
abort_on_error,
return_as_file,
do_code_enrichment,
do_formula_enrichment,
do_picture_classification,
do_picture_description,
],
outputs=[
task_id_rendered,
],
).then(
set_outputs_visibility_process,
inputs=[return_as_file],
outputs=[content_output, file_output],
).then(
wait_task_finish,
inputs=[auth, task_id_rendered, return_as_file],
outputs=[
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
@@ -553,6 +803,7 @@ with gr.Blocks(
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
@@ -562,7 +813,7 @@ with gr.Blocks(
set_outputs_visibility_direct,
inputs=[false_bool, false_bool],
outputs=[content_output, file_output],
).then(
).then(set_task_id_visibility, inputs=[false_bool], outputs=[task_id_output]).then(
clear_url_input, inputs=None, outputs=[url_input]
)
@@ -571,28 +822,32 @@ with gr.Blocks(
set_options_visibility, inputs=[false_bool], outputs=[options]
).then(
set_download_button_label, inputs=[processing_text], outputs=[download_file_btn]
).then(
set_outputs_visibility_process,
inputs=[return_as_file],
outputs=[content_output, file_output],
).then(
clear_outputs,
inputs=None,
outputs=[
task_id_rendered,
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
output_doctags,
],
).then(
set_task_id_visibility,
inputs=[true_bool],
outputs=[task_id_output],
).then(
process_file,
inputs=[
auth,
file_input,
to_formats,
image_export_mode,
pipeline,
ocr,
force_ocr,
ocr_engine,
@@ -601,11 +856,26 @@ with gr.Blocks(
table_mode,
abort_on_error,
return_as_file,
do_code_enrichment,
do_formula_enrichment,
do_picture_classification,
do_picture_description,
],
outputs=[
task_id_rendered,
],
).then(
set_outputs_visibility_process,
inputs=[return_as_file],
outputs=[content_output, file_output],
).then(
wait_task_finish,
inputs=[auth, task_id_rendered, return_as_file],
outputs=[
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
@@ -621,6 +891,7 @@ with gr.Blocks(
output_markdown,
output_markdown_rendered,
output_json,
output_json_rendered,
output_html,
output_html_rendered,
output_text,
@@ -630,6 +901,6 @@ with gr.Blocks(
set_outputs_visibility_direct,
inputs=[false_bool, false_bool],
outputs=[content_output, file_output],
).then(
).then(set_task_id_visibility, inputs=[false_bool], outputs=[task_id_output]).then(
clear_file_input, inputs=None, outputs=[file_input]
)

View File

@@ -1,41 +1,99 @@
import inspect
import json
import re
from typing import List, Type, Union
from typing import Union, get_args, get_origin
from fastapi import Depends, Form
from pydantic import BaseModel
from pydantic import BaseModel, TypeAdapter
def is_pydantic_model(type_):
try:
if inspect.isclass(type_) and issubclass(type_, BaseModel):
return True
origin = get_origin(type_)
if origin is Union:
args = get_args(type_)
return any(
inspect.isclass(arg) and issubclass(arg, BaseModel)
for arg in args
if arg is not type(None)
)
except Exception:
pass
return False
# Adapted from
# https://github.com/fastapi/fastapi/discussions/8971#discussioncomment-7892972
def FormDepends(cls: Type[BaseModel]):
def FormDepends(cls: type[BaseModel]):
new_parameters = []
for field_name, model_field in cls.model_fields.items():
annotation = model_field.annotation
description = model_field.description
default = (
Form(..., description=description, examples=model_field.examples)
if model_field.is_required()
else Form(
model_field.default,
examples=model_field.examples,
description=description,
)
)
# Flatten nested Pydantic models by accepting them as JSON strings
if is_pydantic_model(annotation):
annotation = str
default = Form(
None
if model_field.default is None
else json.dumps(model_field.default.model_dump(mode="json")),
description=description,
examples=None
if not model_field.examples
else [
json.dumps(ex.model_dump(mode="json"))
for ex in model_field.examples
],
)
new_parameters.append(
inspect.Parameter(
name=field_name,
kind=inspect.Parameter.POSITIONAL_ONLY,
default=(
Form(...)
if model_field.is_required()
else Form(model_field.default)
),
annotation=model_field.annotation,
default=default,
annotation=annotation,
)
)
async def as_form_func(**data):
for field_name, model_field in cls.model_fields.items():
value = data.get(field_name)
annotation = model_field.annotation
# Parse nested models from JSON string
if value is not None and is_pydantic_model(annotation):
try:
validator = TypeAdapter(annotation)
data[field_name] = validator.validate_json(value)
except Exception as e:
raise ValueError(f"Invalid JSON for field '{field_name}': {e}")
return cls(**data)
sig = inspect.signature(as_form_func)
sig = sig.replace(parameters=new_parameters)
as_form_func.__signature__ = sig # type: ignore
return Depends(as_form_func)
def _to_list_of_strings(input_value: Union[str, List[str]]) -> List[str]:
def split_and_strip(value: str) -> List[str]:
def _to_list_of_strings(input_value: Union[str, list[str]]) -> list[str]:
def split_and_strip(value: str) -> list[str]:
if re.search(r"[;,]", value):
return [item.strip() for item in re.split(r"[;,]", value)]
else:

View File

@@ -0,0 +1,69 @@
from functools import lru_cache
from docling_jobkit.orchestrators.base_orchestrator import BaseOrchestrator
from docling_serve.settings import AsyncEngine, docling_serve_settings
from docling_serve.storage import get_scratch
@lru_cache
def get_async_orchestrator() -> BaseOrchestrator:
if docling_serve_settings.eng_kind == AsyncEngine.LOCAL:
from docling_jobkit.convert.manager import (
DoclingConverterManager,
DoclingConverterManagerConfig,
)
from docling_jobkit.orchestrators.local.orchestrator import (
LocalOrchestrator,
LocalOrchestratorConfig,
)
local_config = LocalOrchestratorConfig(
num_workers=docling_serve_settings.eng_loc_num_workers,
shared_models=docling_serve_settings.eng_loc_share_models,
scratch_dir=get_scratch(),
)
cm_config = DoclingConverterManagerConfig(
artifacts_path=docling_serve_settings.artifacts_path,
options_cache_size=docling_serve_settings.options_cache_size,
enable_remote_services=docling_serve_settings.enable_remote_services,
allow_external_plugins=docling_serve_settings.allow_external_plugins,
max_num_pages=docling_serve_settings.max_num_pages,
max_file_size=docling_serve_settings.max_file_size,
)
cm = DoclingConverterManager(config=cm_config)
return LocalOrchestrator(config=local_config, converter_manager=cm)
elif docling_serve_settings.eng_kind == AsyncEngine.RQ:
from docling_jobkit.orchestrators.rq.orchestrator import (
RQOrchestrator,
RQOrchestratorConfig,
)
rq_config = RQOrchestratorConfig(
redis_url=docling_serve_settings.eng_rq_redis_url,
results_prefix=docling_serve_settings.eng_rq_results_prefix,
sub_channel=docling_serve_settings.eng_rq_sub_channel,
scratch_dir=get_scratch(),
)
return RQOrchestrator(config=rq_config)
elif docling_serve_settings.eng_kind == AsyncEngine.KFP:
from docling_jobkit.orchestrators.kfp.orchestrator import (
KfpOrchestrator,
KfpOrchestratorConfig,
)
kfp_config = KfpOrchestratorConfig(
endpoint=docling_serve_settings.eng_kfp_endpoint,
token=docling_serve_settings.eng_kfp_token,
ca_cert_path=docling_serve_settings.eng_kfp_ca_cert_path,
self_callback_endpoint=docling_serve_settings.eng_kfp_self_callback_endpoint,
self_callback_token_path=docling_serve_settings.eng_kfp_self_callback_token_path,
self_callback_ca_cert_path=docling_serve_settings.eng_kfp_self_callback_ca_cert_path,
)
return KfpOrchestrator(config=kfp_config)
raise RuntimeError(f"Engine {docling_serve_settings.eng_kind} not recognized.")

View File

@@ -1,248 +1,69 @@
import asyncio
import logging
import os
import shutil
import tempfile
import time
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Union
from docling.datamodel.base_models import OutputFormat
from docling.datamodel.document import ConversionResult, ConversionStatus, ErrorItem
from docling.utils.profiling import ProfilingItem
from docling_core.types.doc import DoclingDocument, ImageRefMode
from fastapi import BackgroundTasks, HTTPException
from fastapi.responses import FileResponse
from pydantic import BaseModel
from fastapi import BackgroundTasks, Response
from docling_serve.docling_conversion import ConvertDocumentsOptions
from docling_jobkit.datamodel.result import (
ConvertDocumentResult,
ExportResult,
RemoteTargetResult,
ZipArchiveResult,
)
from docling_jobkit.orchestrators.base_orchestrator import (
BaseOrchestrator,
)
from docling_serve.datamodel.responses import (
ConvertDocumentResponse,
PresignedUrlConvertDocumentResponse,
)
from docling_serve.settings import docling_serve_settings
_log = logging.getLogger(__name__)
class DocumentResponse(BaseModel):
filename: str
md_content: Optional[str] = None
json_content: Optional[DoclingDocument] = None
html_content: Optional[str] = None
text_content: Optional[str] = None
doctags_content: Optional[str] = None
class ConvertDocumentResponse(BaseModel):
document: DocumentResponse
status: ConversionStatus
errors: List[ErrorItem] = []
processing_time: float
timings: Dict[str, ProfilingItem] = {}
class ConvertDocumentErrorResponse(BaseModel):
status: ConversionStatus
def _export_document_as_content(
conv_res: ConversionResult,
export_json: bool,
export_html: bool,
export_md: bool,
export_txt: bool,
export_doctags: bool,
image_mode: ImageRefMode,
):
document = DocumentResponse(filename=conv_res.input.file.name)
if conv_res.status == ConversionStatus.SUCCESS:
new_doc = conv_res.document._make_copy_with_refmode(Path(), image_mode)
# Create the different formats
if export_json:
document.json_content = new_doc
if export_html:
document.html_content = new_doc.export_to_html(image_mode=image_mode)
if export_txt:
document.text_content = new_doc.export_to_markdown(
strict_text=True, image_mode=image_mode
)
if export_md:
document.md_content = new_doc.export_to_markdown(image_mode=image_mode)
if export_doctags:
document.doctags_content = new_doc.export_to_document_tokens()
elif conv_res.status == ConversionStatus.SKIPPED:
raise HTTPException(status_code=400, detail=conv_res.errors)
else:
raise HTTPException(status_code=500, detail=conv_res.errors)
return document
def _export_documents_as_files(
conv_results: Iterable[ConversionResult],
output_dir: Path,
export_json: bool,
export_html: bool,
export_md: bool,
export_txt: bool,
export_doctags: bool,
image_export_mode: ImageRefMode,
):
success_count = 0
failure_count = 0
for conv_res in conv_results:
if conv_res.status == ConversionStatus.SUCCESS:
success_count += 1
doc_filename = conv_res.input.file.stem
# Export JSON format:
if export_json:
fname = output_dir / f"{doc_filename}.json"
_log.info(f"writing JSON output to {fname}")
conv_res.document.save_as_json(
filename=fname, image_mode=image_export_mode
)
# Export HTML format:
if export_html:
fname = output_dir / f"{doc_filename}.html"
_log.info(f"writing HTML output to {fname}")
conv_res.document.save_as_html(
filename=fname, image_mode=image_export_mode
)
# Export Text format:
if export_txt:
fname = output_dir / f"{doc_filename}.txt"
_log.info(f"writing TXT output to {fname}")
conv_res.document.save_as_markdown(
filename=fname,
strict_text=True,
image_mode=ImageRefMode.PLACEHOLDER,
)
# Export Markdown format:
if export_md:
fname = output_dir / f"{doc_filename}.md"
_log.info(f"writing Markdown output to {fname}")
conv_res.document.save_as_markdown(
filename=fname, image_mode=image_export_mode
)
# Export Document Tags format:
if export_doctags:
fname = output_dir / f"{doc_filename}.doctags"
_log.info(f"writing Doc Tags output to {fname}")
conv_res.document.save_as_document_tokens(filename=fname)
else:
_log.warning(f"Document {conv_res.input.file} failed to convert.")
failure_count += 1
_log.info(
f"Processed {success_count + failure_count} docs, "
f"of which {failure_count} failed"
)
def process_results(
async def prepare_response(
task_id: str,
task_result: ConvertDocumentResult,
orchestrator: BaseOrchestrator,
background_tasks: BackgroundTasks,
conversion_options: ConvertDocumentsOptions,
conv_results: Iterable[ConversionResult],
) -> Union[ConvertDocumentResponse, FileResponse]:
# Let's start by processing the documents
try:
start_time = time.monotonic()
# Convert the iterator to a list to count the number of results and get timings
# As it's an iterator (lazy evaluation), it will also start the conversion
conv_results = list(conv_results)
processing_time = time.monotonic() - start_time
_log.info(
f"Processed {len(conv_results)} docs in {processing_time:.2f} seconds."
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if len(conv_results) == 0:
raise HTTPException(
status_code=500, detail="No documents were generated by Docling."
)
# We have some results, let's prepare the response
response: Union[FileResponse, ConvertDocumentResponse]
# Booleans to know what to export
export_json = OutputFormat.JSON in conversion_options.to_formats
export_html = OutputFormat.HTML in conversion_options.to_formats
export_md = OutputFormat.MARKDOWN in conversion_options.to_formats
export_txt = OutputFormat.TEXT in conversion_options.to_formats
export_doctags = OutputFormat.DOCTAGS in conversion_options.to_formats
# Only 1 document was processed, and we are not returning it as a file
if len(conv_results) == 1 and not conversion_options.return_as_file:
conv_res = conv_results[0]
document = _export_document_as_content(
conv_res,
export_json=export_json,
export_html=export_html,
export_md=export_md,
export_txt=export_txt,
export_doctags=export_doctags,
image_mode=conversion_options.image_export_mode,
)
):
response: Response | ConvertDocumentResponse | PresignedUrlConvertDocumentResponse
if isinstance(task_result.result, ExportResult):
response = ConvertDocumentResponse(
document=document,
status=conv_res.status,
processing_time=processing_time,
timings=conv_res.timings,
document=task_result.result.content,
status=task_result.result.status,
processing_time=task_result.processing_time,
timings=task_result.result.timings,
errors=task_result.result.errors,
)
elif isinstance(task_result.result, ZipArchiveResult):
response = Response(
content=task_result.result.content,
media_type="application/zip",
headers={
"Content-Disposition": 'attachment; filename="converted_docs.zip"'
},
)
elif isinstance(task_result.result, RemoteTargetResult):
response = PresignedUrlConvertDocumentResponse(
processing_time=task_result.processing_time,
num_converted=task_result.num_converted,
num_succeeded=task_result.num_succeeded,
num_failed=task_result.num_failed,
)
# Multiple documents were processed, or we are forced returning as a file
else:
# Temporary directory to store the outputs
work_dir = Path(tempfile.mkdtemp(prefix="docling_"))
output_dir = work_dir / "output"
output_dir.mkdir(parents=True, exist_ok=True)
raise ValueError("Unknown result type")
# Worker pid to use in archive identification as we may have multiple workers
os.getpid()
if docling_serve_settings.single_use_results:
# Export the documents
_export_documents_as_files(
conv_results=conv_results,
output_dir=output_dir,
export_json=export_json,
export_html=export_html,
export_md=export_md,
export_txt=export_txt,
export_doctags=export_doctags,
image_export_mode=conversion_options.image_export_mode,
)
async def _remove_task_impl():
await asyncio.sleep(docling_serve_settings.result_removal_delay)
await orchestrator.delete_task(task_id=task_id)
files = os.listdir(output_dir)
async def _remove_task():
asyncio.create_task(_remove_task_impl()) # noqa: RUF006
if len(files) == 0:
raise HTTPException(status_code=500, detail="No documents were exported.")
file_path = work_dir / "converted_docs.zip"
shutil.make_archive(
base_name=str(file_path.with_suffix("")),
format="zip",
root_dir=output_dir,
)
# Other cleanups after the response is sent
# Output directory
background_tasks.add_task(shutil.rmtree, work_dir, ignore_errors=True)
response = FileResponse(
file_path, filename=file_path.name, media_type="application/zip"
)
background_tasks.add_task(_remove_task)
return response

View File

@@ -1,6 +1,105 @@
import enum
import sys
from pathlib import Path
from typing import Optional, Union
from pydantic import AnyUrl, model_validator
from pydantic_settings import BaseSettings, SettingsConfigDict
from typing_extensions import Self
class Settings(BaseSettings):
class UvicornSettings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="UVICORN_", env_file=".env", extra="allow"
)
model_config = SettingsConfigDict(env_prefix="DOCLING_")
host: str = "0.0.0.0"
port: int = 5001
reload: bool = False
root_path: str = ""
proxy_headers: bool = True
timeout_keep_alive: int = 60
ssl_certfile: Optional[Path] = None
ssl_keyfile: Optional[Path] = None
ssl_keyfile_password: Optional[str] = None
workers: Union[int, None] = None
class AsyncEngine(str, enum.Enum):
LOCAL = "local"
KFP = "kfp"
RQ = "rq"
class DoclingServeSettings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="DOCLING_SERVE_",
env_file=".env",
env_parse_none_str="",
extra="allow",
)
enable_ui: bool = False
api_host: str = "localhost"
artifacts_path: Optional[Path] = None
static_path: Optional[Path] = None
scratch_path: Optional[Path] = None
single_use_results: bool = True
result_removal_delay: float = 300 # 5 minutes
load_models_at_boot: bool = True
options_cache_size: int = 2
enable_remote_services: bool = False
allow_external_plugins: bool = False
api_key: str = ""
max_document_timeout: float = 3_600 * 24 * 7 # 7 days
max_num_pages: int = sys.maxsize
max_file_size: int = sys.maxsize
max_sync_wait: int = 120 # 2 minutes
cors_origins: list[str] = ["*"]
cors_methods: list[str] = ["*"]
cors_headers: list[str] = ["*"]
eng_kind: AsyncEngine = AsyncEngine.LOCAL
# Local engine
eng_loc_num_workers: int = 2
eng_loc_share_models: bool = False
# RQ engine
eng_rq_redis_url: str = ""
eng_rq_results_prefix: str = "docling:results"
eng_rq_sub_channel: str = "docling:updates"
# KFP engine
eng_kfp_endpoint: Optional[AnyUrl] = None
eng_kfp_token: Optional[str] = None
eng_kfp_ca_cert_path: Optional[str] = None
eng_kfp_self_callback_endpoint: Optional[str] = None
eng_kfp_self_callback_token_path: Optional[Path] = None
eng_kfp_self_callback_ca_cert_path: Optional[Path] = None
eng_kfp_experimental: bool = False
@model_validator(mode="after")
def engine_settings(self) -> Self:
# Validate KFP engine settings
if self.eng_kind == AsyncEngine.KFP:
if self.eng_kfp_endpoint is None:
raise ValueError("KFP endpoint is required when using the KFP engine.")
if self.eng_kind == AsyncEngine.KFP:
if not self.eng_kfp_experimental:
raise ValueError(
"KFP is not yet working. To enable the development version, you must set DOCLING_SERVE_ENG_KFP_EXPERIMENTAL=true."
)
if self.eng_kind == AsyncEngine.RQ:
if not self.eng_rq_redis_url:
raise ValueError("RQ Redis url is required when using the RQ engine.")
return self
uvicorn_settings = UvicornSettings()
docling_serve_settings = DoclingServeSettings()

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import tempfile
from functools import lru_cache
from pathlib import Path
from docling_serve.settings import docling_serve_settings
@lru_cache
def get_scratch() -> Path:
scratch_dir = (
docling_serve_settings.scratch_path
if docling_serve_settings.scratch_path is not None
else Path(tempfile.mkdtemp(prefix="docling_"))
)
scratch_dir.mkdir(exist_ok=True, parents=True)
return scratch_dir

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from fastapi import WebSocket
from docling_jobkit.datamodel.task_meta import TaskStatus
from docling_jobkit.orchestrators.base_notifier import BaseNotifier
from docling_jobkit.orchestrators.base_orchestrator import BaseOrchestrator
from docling_serve.datamodel.responses import (
MessageKind,
TaskStatusResponse,
WebsocketMessage,
)
class WebsocketNotifier(BaseNotifier):
def __init__(self, orchestrator: BaseOrchestrator):
super().__init__(orchestrator)
self.task_subscribers: dict[str, set[WebSocket]] = {}
async def add_task(self, task_id: str):
self.task_subscribers[task_id] = set()
async def remove_task(self, task_id: str):
if task_id in self.task_subscribers:
for websocket in self.task_subscribers[task_id]:
await websocket.close()
del self.task_subscribers[task_id]
async def notify_task_subscribers(self, task_id: str):
if task_id not in self.task_subscribers:
raise RuntimeError(f"Task {task_id} does not have a subscribers list.")
task = await self.orchestrator.get_raw_task(task_id=task_id)
task_queue_position = await self.orchestrator.get_queue_position(task_id)
msg = TaskStatusResponse(
task_id=task.task_id,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
for websocket in self.task_subscribers[task_id]:
await websocket.send_text(
WebsocketMessage(message=MessageKind.UPDATE, task=msg).model_dump_json()
)
if task.is_completed():
await websocket.close()
async def notify_queue_positions(self):
for task_id in self.task_subscribers.keys():
# notify only pending tasks
if self.orchestrator.tasks[task_id].task_status != TaskStatus.PENDING:
continue
await self.notify_task_subscribers(task_id)

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# Docling Serve documentation
This documentation pages explore the webserver configurations, runtime options, deployment examples as well as development best practices.
- [Configuration](./configuration.md)
- [Handling models](./models.md)
- [Usage](./usage.md)
- [Deployment](./deployment.md)
- [Development](./development.md)
- [`v1` migration](./v1_migration.md)

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# Configuration
The `docling-serve` executable allows to configure the server via command line
options as well as environment variables.
Configurations are divided between the settings used for the `uvicorn` asgi
server and the actual app-specific configurations.
> [!WARNING]
> When the server is running with `reload` or with multiple `workers`, uvicorn
> will spawn multiple subprocesses. This invalidates all the values configured
> via the CLI command line options. Please use environment variables in this
> type of deployments.
## Webserver configuration
The following table shows the options which are propagated directly to the
`uvicorn` webserver runtime.
| CLI option | ENV | Default | Description |
| -----------|-----|---------|-------------|
| `--host` | `UVICORN_HOST` | `0.0.0.0` for `run`, `localhost` for `dev` | THe host to serve on. |
| `--port` | `UVICORN_PORT` | `5001` | The port to serve on. |
| `--reload` | `UVICORN_RELOAD` | `false` for `run`, `true` for `dev` | Enable auto-reload of the server when (code) files change. |
| `--workers` | `UVICORN_WORKERS` | `1` | Use multiple worker processes. |
| `--root-path` | `UVICORN_ROOT_PATH` | `""` | The root path is used to tell your app that it is being served to the outside world with some |
| `--proxy-headers` | `UVICORN_PROXY_HEADERS` | `true` | Enable/Disable X-Forwarded-Proto, X-Forwarded-For, X-Forwarded-Port to populate remote address info. |
| `--timeout-keep-alive` | `UVICORN_TIMEOUT_KEEP_ALIVE` | `60` | Timeout for the server response. |
| `--ssl-certfile` | `UVICORN_SSL_CERTFILE` | | SSL certificate file. |
| `--ssl-keyfile` | `UVICORN_SSL_KEYFILE` | | SSL key file. |
| `--ssl-keyfile-password` | `UVICORN_SSL_KEYFILE_PASSWORD` | | SSL keyfile password. |
## Docling Serve configuration
THe following table describes the options to configure the Docling Serve app.
| CLI option | ENV | Default | Description |
| -----------|-----|---------|-------------|
| `--artifacts-path` | `DOCLING_SERVE_ARTIFACTS_PATH` | unset | If set to a valid directory, the model weights will be loaded from this path |
| | `DOCLING_SERVE_STATIC_PATH` | unset | If set to a valid directory, the static assets for the docs and UI will be loaded from this path |
| | `DOCLING_SERVE_SCRATCH_PATH` | | If set, this directory will be used as scratch workspace, e.g. storing the results before they get requested. If unset, a temporary created is created for this purpose. |
| `--enable-ui` | `DOCLING_SERVE_ENABLE_UI` | `false` | Enable the demonstrator UI. |
| | `DOCLING_SERVE_ENABLE_REMOTE_SERVICES` | `false` | Allow pipeline components making remote connections. For example, this is needed when using a vision-language model via APIs. |
| | `DOCLING_SERVE_ALLOW_EXTERNAL_PLUGINS` | `false` | Allow the selection of third-party plugins. |
| | `DOCLING_SERVE_SINGLE_USE_RESULTS` | `true` | If true, results can be accessed only once. If false, the results accumulate in the scratch directory. |
| | `DOCLING_SERVE_RESULT_REMOVAL_DELAY` | `300` | When `DOCLING_SERVE_SINGLE_USE_RESULTS` is active, this is the delay before results are removed from the task registry. |
| | `DOCLING_SERVE_MAX_DOCUMENT_TIMEOUT` | `604800` (7 days) | The maximum time for processing a document. |
| | `DOCLING_SERVE_MAX_NUM_PAGES` | | The maximum number of pages for a document to be processed. |
| | `DOCLING_SERVE_MAX_FILE_SIZE` | | The maximum file size for a document to be processed. |
| | `DOCLING_SERVE_MAX_SYNC_WAIT` | `120` | Max number of seconds a synchronous endpoint is waiting for the task completion. |
| | `DOCLING_SERVE_LOAD_MODELS_AT_BOOT` | `True` | If enabled, the models for the default options will be loaded at boot. |
| | `DOCLING_SERVE_OPTIONS_CACHE_SIZE` | `2` | How many DocumentConveter objects (including their loaded models) to keep in the cache. |
| | `DOCLING_SERVE_CORS_ORIGINS` | `["*"]` | A list of origins that should be permitted to make cross-origin requests. |
| | `DOCLING_SERVE_CORS_METHODS` | `["*"]` | A list of HTTP methods that should be allowed for cross-origin requests. |
| | `DOCLING_SERVE_CORS_HEADERS` | `["*"]` | A list of HTTP request headers that should be supported for cross-origin requests. |
| | `DOCLING_SERVE_API_KEY` | | If specified, all the API requests must contain the header `X-Api-Key` with this value. |
| | `DOCLING_SERVE_ENG_KIND` | `local` | The compute engine to use for the async tasks. Possible values are `local`, `rq` and `kfp`. See below for more configurations of the engines. |
### Compute engine
Docling Serve can be deployed with several possible of compute engine.
The selected compute engine will be running all the async jobs.
#### Local engine
The following table describes the options to configure the Docling Serve local engine.
| ENV | Default | Description |
|-----|---------|-------------|
| `DOCLING_SERVE_ENG_LOC_NUM_WORKERS` | 2 | Number of workers/threads processing the incoming tasks. |
| `DOCLING_SERVE_ENG_LOC_SHARE_MODELS` | False | If true, each process will share the same models among all thread workers. Otherwise, one instance of the models is allocated for each worker thread. |
#### RQ engine
The following table describes the options to configure the Docling Serve RQ engine.
| ENV | Default | Description |
|-----|---------|-------------|
| `DOCLING_SERVE_ENG_RQ_REDIS_URL` | (required) | The connection Redis url, e.g. `redis://localhost:6373/` |
| `DOCLING_SERVE_ENG_RQ_RESULTS_PREFIX` | `docling:results` | The prefix used for storing the results in Redis. |
| `DOCLING_SERVE_ENG_RQ_RESULTS_PREFIX` | `docling:updates` | The channel key name used for storing communicating updates between the workers and the orchestrator. |
#### KFP engine
The following table describes the options to configure the Docling Serve KFP engine.
| ENV | Default | Description |
|-----|---------|-------------|
| `DOCLING_SERVE_ENG_KFP_ENDPOINT` | | Must be set to the Kubeflow Pipeline endpoint. When using the in-cluster deployment, make sure to use the cluster endpoint, e.g. `https://NAME.NAMESPACE.svc.cluster.local:8888` |
| `DOCLING_SERVE_ENG_KFP_TOKEN` | | The authentication token for KFP. For in-cluster deployment, the app will load automatically the token of the ServiceAccount. |
| `DOCLING_SERVE_ENG_KFP_CA_CERT_PATH` | | Path to the CA certificates for the KFP endpoint. For in-cluster deployment, the app will load automatically the internal CA. |
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_ENDPOINT` | | If set, it enables internal callbacks providing status update of the KFP job. Usually something like `https://NAME.NAMESPACE.svc.cluster.local:5001/v1/callback/task/progress`. |
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_TOKEN_PATH` | | The token used for authenticating the progress callback. For cluster-internal workloads, use `/run/secrets/kubernetes.io/serviceaccount/token`. |
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_CA_CERT_PATH` | | The CA certificate for the progress callback. For cluster-inetrnal workloads, use `/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt`. |
#### Gradio UI
When using Gradio UI and using the option to output conversion as file, Gradio uses cache to prevent files to be overwritten ([more info here](https://www.gradio.app/guides/file-access#the-gradio-cache)), and we defined the cache clean frequency of one hour to clean files older than 10hours. For situations that files need to be available to download from UI older than 10 hours, there is two options:
- Increase the older age of files to clean [here](https://github.com/docling-project/docling-serve/blob/main/docling_serve/gradio_ui.py#L483) to suffice the age desired;
- Or set the clean up manually by defining the temporary dir of Gradio to use the same as `DOCLING_SERVE_SCRATCH_PATH` absolute path. This can be achieved by setting the environment variable `GRADIO_TEMP_DIR`, that can be done via command line `export GRADIO_TEMP_DIR="<same_path_as_scratch>"` or in `Dockerfile` using `ENV GRADIO_TEMP_DIR="<same_path_as_scratch>"`. After this, set the clean of cache to `None` [here](https://github.com/docling-project/docling-serve/blob/main/docling_serve/gradio_ui.py#L483). Now, the clean up of `DOCLING_SERVE_SCRATCH_PATH` will also clean the Gradio temporary dir. (If you use this option, please remember when reversing changes to remove the environment variable `GRADIO_TEMP_DIR`, otherwise may lead to files not be available to download).

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# AMD ROCm deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-rocm:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
ROCR_VISIBLE_DEVICES: "0" # https://rocm.docs.amd.com/en/latest/conceptual/gpu-isolation.html#rocr-visible-devices
## This section is for compatibility with older cards
# HSA_OVERRIDE_GFX_VERSION: "11.0.0"
# HSA_ENABLE_SDMA: "0"
devices:
- /dev/kfd:/dev/kfd
- /dev/dri:/dev/dri
group_add:
- 44 # video group GID from host
- 992 # render group GID from host
restart: always

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# NVIDIA CUDA deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-cu126:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
NVIDIA_VISIBLE_DEVICES: "all" # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html
# deploy: # This section is for compatibility with Swarm
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: all
# capabilities: [gpu]
runtime: nvidia
restart: always

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kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
containers:
- name: api
resources:
limits:
cpu: 2
memory: 4Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
- name: DOCLING_SERVE_ARTIFACTS_PATH
value: '/modelcache'
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc

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apiVersion: batch/v1
kind: Job
metadata:
name: docling-model-cache-load
spec:
selector: {}
template:
metadata:
name: docling-model-load
spec:
containers:
- name: loader
image: ghcr.io/docling-project/docling-serve-cpu:main
command:
- docling-tools
- models
- download
- '--output-dir=/modelcache'
- 'layout'
- 'tableformer'
- 'code_formula'
- 'picture_classifier'
- 'smolvlm'
- 'granite_vision'
- 'easyocr'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
restartPolicy: Never

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apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: docling-model-cache-pvc
spec:
accessModes:
- ReadWriteOnce
volumeMode: Filesystem
resources:
requests:
storage: 10Gi

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# This example deployment configures Docling Serve with a OAuth-Proxy sidecar and TLS termination
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: docling-serve
labels:
app: docling-serve
annotations:
serviceaccounts.openshift.io/oauth-redirectreference.primary: '{"kind":"OAuthRedirectReference","apiVersion":"v1","reference":{"kind":"Route","name":"docling-serve"}}'
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: docling-serve-oauth
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:auth-delegator
subjects:
- kind: ServiceAccount
name: docling-serve
namespace: docling
---
apiVersion: route.openshift.io/v1
kind: Route
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
to:
kind: Service
name: docling-serve
port:
targetPort: oauth
tls:
termination: Reencrypt
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
annotations:
service.alpha.openshift.io/serving-cert-secret-name: docling-serve-tls
spec:
ports:
- name: oauth
port: 8443
targetPort: oauth
- name: http
port: 5001
targetPort: http
selector:
app: docling-serve
component: docling-serve-api
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
serviceAccountName: docling-serve
containers:
- name: api
resources:
limits:
cpu: 2000m
memory: 4Gi
requests:
cpu: 800m
memory: 1Gi
readinessProbe:
httpGet:
path: /health
port: http
scheme: HTTPS
initialDelaySeconds: 10
timeoutSeconds: 2
periodSeconds: 5
successThreshold: 1
failureThreshold: 3
livenessProbe:
httpGet:
path: /health
port: http
scheme: HTTPS
initialDelaySeconds: 3
timeoutSeconds: 4
periodSeconds: 10
successThreshold: 1
failureThreshold: 5
env:
- name: NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
- name: DOCLING_SERVE_API_HOST
value: 'docling-serve.$(NAMESPACE).svc.cluster.local'
- name: UVICORN_SSL_CERTFILE
value: '/etc/tls/private/tls.crt'
- name: UVICORN_SSL_KEYFILE
value: '/etc/tls/private/tls.key'
ports:
- name: http
containerPort: 5001
protocol: TCP
volumeMounts:
- name: proxy-tls
mountPath: /etc/tls/private
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu:fix-ui-with-https'
- name: oauth-proxy
resources:
limits:
cpu: 100m
memory: 256Mi
requests:
cpu: 100m
memory: 256Mi
readinessProbe:
httpGet:
path: /oauth/healthz
port: oauth
scheme: HTTPS
initialDelaySeconds: 5
timeoutSeconds: 1
periodSeconds: 5
successThreshold: 1
failureThreshold: 3
livenessProbe:
httpGet:
path: /oauth/healthz
port: oauth
scheme: HTTPS
initialDelaySeconds: 30
timeoutSeconds: 1
periodSeconds: 5
successThreshold: 1
failureThreshold: 3
ports:
- name: oauth
containerPort: 8443
protocol: TCP
imagePullPolicy: IfNotPresent
volumeMounts:
- name: proxy-tls
mountPath: /etc/tls/private
env:
- name: NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
image: 'registry.redhat.io/openshift4/ose-oauth-proxy:v4.13'
args:
- '--https-address=:8443'
- '--provider=openshift'
- '--openshift-service-account=docling-serve'
- '--upstream=https://docling-serve.$(NAMESPACE).svc.cluster.local:5001'
- '--upstream-ca=/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt'
- '--tls-cert=/etc/tls/private/tls.crt'
- '--tls-key=/etc/tls/private/tls.key'
- '--cookie-secret=SECRET'
- '--openshift-delegate-urls={"/": {"group":"route.openshift.io","resource":"routes","verb":"get","name":"docling-serve","namespace":"$(NAMESPACE)"}}'
- '--openshift-sar={"namespace":"$(NAMESPACE)","resource":"routes","resourceName":"docling-serve","verb":"get","resourceAPIGroup":"route.openshift.io"}'
- '--skip-auth-regex=''(^/health|^/docs)'''
volumes:
- name: proxy-tls
secret:
secretName: docling-serve-tls
defaultMode: 420

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# This example deployment configures Docling Serve with a Route + Sticky sessions, a Service and cpu image
---
kind: Route
apiVersion: route.openshift.io/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
annotations:
haproxy.router.openshift.io/disable_cookies: "false" # this annotation enables the sticky sessions
spec:
path: /
to:
kind: Service
name: docling-serve
port:
targetPort: http
tls:
termination: edge
insecureEdgeTerminationPolicy: Redirect
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
ports:
- name: http
port: 5001
targetPort: http
selector:
app: docling-serve
component: docling-serve-api
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 3
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
containers:
- name: api
resources:
limits:
cpu: 1
memory: 4Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve'

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# This example deployment configures Docling Serve with a Service and RQ workers
# Create following secret
# kubectl create secret generic docling-serve-rq-secrets --from-literal=REDIS_PASSWORD=myredispassword --from-literal=RQ_REDIS_URL=redis://:myredispassword@docling-serve-redis-service:6373/
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
ports:
- name: http
port: 5001
targetPort: http
selector:
app: docling-serve
component: docling-serve-api
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
containers:
- name: api
resources:
limits:
cpu: 1
memory: 8Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
- name: DOCLING_SERVE_ENG_KIND
value: 'rq'
- name: DOCLING_SERVE_ENG_RQ_REDIS_URL
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: RQ_REDIS_URL
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu'
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve-rq-workers
labels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
spec:
replicas: 2
selector:
matchLabels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
template:
metadata:
labels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
spec:
restartPolicy: Always
containers:
- name: worker
resources:
limits:
cpu: 1
memory: 4Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENG_KIND
value: 'rq'
- name: DOCLING_SERVE_ENG_RQ_REDIS_URL
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: RQ_REDIS_URL
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu'
command: ["docling-serve"]
args: ["rq-worker"]
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: docling-serve-redis
labels:
app: docling-serve-redis
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve-redis
template:
metadata:
labels:
app: docling-serve-redis
spec:
restartPolicy: Always
terminationGracePeriodSeconds: 30
containers:
- name: redis
resources:
limits:
cpu: 1
memory: 1Gi
requests:
cpu: 250m
memory: 100Mi
image: redis:latest
command: ["redis-server"]
args:
- "--port"
- "6373"
- "--dir"
- "/mnt/redis/data"
- "--appendonly"
- "yes"
- "--requirepass"
- "$(REDIS_PASSWORD)"
ports:
- containerPort: 6373
env:
- name: REDIS_PASSWORD
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: REDIS_PASSWORD
volumeMounts:
- name: redis-data
mountPath: /mnt/redis/data
securityContext:
fsGroup: 1004
runAsNonRoot: true
allowPrivilegeEscalation: false
capabilities:
drop:
- ALL
seccompProfile:
type: RuntimeDefault
volumes:
- name: redis-data
emptyDir:
medium: Memory
sizeLimit: 2Gi
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve-redis-service
labels:
app: docling-serve-redis
spec:
type: NodePort
ports:
- name: redis-service
protocol: TCP
port: 6373
targetPort: 6373
selector:
app: docling-serve-redis

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# This example deployment configures Docling Serve with a Service and cuda image
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
ports:
- name: http
port: 5001
targetPort: http
selector:
app: docling-serve
component: docling-serve-api
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
containers:
- name: api
resources:
limits:
cpu: 1
memory: 4Gi
nvidia.com/gpu: 1 # Limit to one GPU
requests:
cpu: 250m
memory: 1Gi
nvidia.com/gpu: 1 # Limit to one GPU
env:
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cu124'

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# Deployment Examples
This document provides deployment examples for running the application in different environments.
Choose the deployment option that best fits your setup.
- **[Local GPU NVIDIA](#local-gpu-nvidia)**: For deploying the application locally on a machine with a supported NVIDIA GPU (using Docker Compose).
- **[Local GPU AMD](#local-gpu-amd)**: For deploying the application locally on a machine with a supported AMD GPU (using Docker Compose).
- **[OpenShift](#openshift)**: For deploying the application on an OpenShift cluster, designed for cloud-native environments.
---
## Local GPU NVIDIA
### Docker compose
Manifest example: [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml)
This deployment has the following features:
- NVIDIA cuda enabled
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
For using the API:
```sh
# Make a test query
curl -X 'POST' \
"localhost:5001/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
<details>
<summary><b>Requirements</b></summary>
- debian/ubuntu/rhel/fedora/opensuse
- docker
- nvidia drivers >=550.54.14
- nvidia-container-toolkit
Docs:
- [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/supported-platforms.html)
- [CUDA Toolkit Release Notes](https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#id6)
</details>
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml) file or use `count: all`)
```sh
nvidia-smi
```
2. Check if the NVIDIA Container Toolkit is installed/updated
```sh
# debian
dpkg -l | grep nvidia-container-toolkit
```
```sh
# rhel
rpm -q nvidia-container-toolkit
```
NVIDIA Container Toolkit install steps can be found here:
<https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html>
3. Check which runtime is being used by Docker
```sh
# docker
docker info | grep -i runtime
```
4. If the default Docker runtime changes back from 'nvidia' to 'default' after restarting the Docker service (optional):
Backup the daemon.json file:
```sh
sudo cp /etc/docker/daemon.json /etc/docker/daemon.json.bak
```
Update the daemon.json file:
```sh
echo '{
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime"
}
},
"default-runtime": "nvidia"
}' | sudo tee /etc/docker/daemon.json > /dev/null
```
Restart the Docker service:
```sh
sudo systemctl restart docker
```
Confirm 'nvidia' is the default runtime used by Docker by repeating step 3.
5. Run the container:
```sh
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
</details>
## Local GPU AMD
### Docker compose
Manifest example: [compose-amd.yaml](./deploy-examples/compose-amd.yaml)
This deployment has the following features:
- AMD rocm enabled
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-amd.yaml up -d
```
For using the API:
```sh
# Make a test query
curl -X 'POST' \
"localhost:5001/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
<details>
<summary><b>Requirements</b></summary>
- debian/ubuntu/rhel/fedora/opensuse
- docker
- AMDGPU driver >=6.3
- AMD ROCm >=6.3
Docs:
- [AMD ROCm installation](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
</details>
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
rocm-smi --showdriverversion
rocminfo | grep -i "ROCm version"
```
2. Find both video group GID and render group GID from host (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
getent group video
getent group render
```
3. Build the image locally (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
make docling-serve-rocm-image
```
</details>
## OpenShift
### Simple deployment
Manifest example: [docling-serve-simple.yaml](./deploy-examples/docling-serve-simple.yaml)
This deployment example has the following features:
- Deployment configuration
- Service configuration
- NVIDIA cuda enabled
Install the app with:
```sh
oc apply -f docs/deploy-examples/docling-serve-simple.yaml
```
For using the API:
```sh
# Port-forward the service
oc port-forward svc/docling-serve 5001:5001
# Make a test query
curl -X 'POST' \
"localhost:5001/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
### Multiple workers with RQ
Manifest example: [`docling-serve-rq-workers.yaml`](./deploy-examples/docling-serve-rq-workers.yaml)
This deployment example has the following features:
- Deployment configuration
- Service configuration
- Redis deployment
- Multiple (2 by default) worker Pods
Install the app with:
- create k8s secret:
```sh
kubectl create secret generic docling-serve-rq-secrets --from-literal=REDIS_PASSWORD=myredispassword --from-literal=RQ_REDIS_URL=redis://:myredispassword@docling-serve-redis-service:6373/
```
- apply deployment manifest:
```sh
oc apply -f docs/deploy-examples/docling-serve-rq-workers.yaml
```
### Secure deployment with `oauth-proxy`
Manifest example: [docling-serve-oauth.yaml](./deploy-examples/docling-serve-oauth.yaml)
This deployment has the following features:
- TLS encryption between all components (using the cluster-internal CA authority).
- Authentication via a secure `oauth-proxy` sidecar.
- Expose the service using a secure OpenShift `Route`
Install the app with:
```sh
oc apply -f docs/deploy-examples/docling-serve-oauth.yaml
```
For using the API:
```sh
# Retrieve the endpoint
DOCLING_NAME=docling-serve
DOCLING_ROUTE="https://$(oc get routes ${DOCLING_NAME} --template={{.spec.host}})"
# Retrieve the authentication token
OCP_AUTH_TOKEN=$(oc whoami --show-token)
# Make a test query
curl -X 'POST' \
"${DOCLING_ROUTE}/v1/convert/source/async" \
-H "Authorization: Bearer ${OCP_AUTH_TOKEN}" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
### ReplicaSets with `sticky sessions`
Manifest example: [docling-serve-replicas-w-sticky-sessions.yaml](./deploy-examples/docling-serve-replicas-w-sticky-sessions.yaml)
This deployment has the following features:
- Deployment configuration with 3 replicas
- Service configuration
- Expose the service using a OpenShift `Route` and enables sticky sessions
Install the app with:
```sh
oc apply -f docs/deploy-examples/docling-serve-replicas-w-sticky-sessions.yaml
```
For using the API:
```sh
# Retrieve the endpoint
DOCLING_NAME=docling-serve
DOCLING_ROUTE="https://$(oc get routes $DOCLING_NAME --template={{.spec.host}})"
# Make a test query, store the cookie and taskid
task_id=$(curl -s -X 'POST' \
"${DOCLING_ROUTE}/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}' \
-c cookies.txt | grep -oP '"task_id":"\K[^"]+')
```
```sh
# Grab the taskid and cookie to check the task status
curl -v -X 'GET' \
"${DOCLING_ROUTE}/v1/status/poll/$task_id?wait=0" \
-H "accept: application/json" \
-b "cookies.txt"
```

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# Development
## Install dependencies
### CPU only
```sh
# Install uv if not already available
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install dependencies
uv sync --extra cpu
```
### Cuda GPU
For GPU support use the following command:
```sh
# Install dependencies
uv sync
```
### Gradio UI and different OCR backends
`/ui` endpoint using `gradio` and different OCR backends can be enabled via package extras:
```sh
# Enable ui and rapidocr
uv sync --extra ui --extra rapidocr
```
```sh
# Enable tesserocr
uv sync --extra tesserocr
```
See `[project.optional-dependencies]` section in `pyproject.toml` for full list of options and runtime options with `uv run docling-serve --help`.
### Run the server
The `docling-serve` executable is a convenient script for launching the webserver both in
development and production mode.
```sh
# Run the server in development mode
# - reload is enabled by default
# - listening on the 127.0.0.1 address
# - ui is enabled by default
docling-serve dev
# Run the server in production mode
# - reload is disabled by default
# - listening on the 0.0.0.0 address
# - ui is disabled by default
docling-serve run
```

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# Handling Models in Docling Serve
When enabling steps in Docling Serve that require extra models (such as picture classification, picture description, table detection, code recognition, formula extraction, or vision-language modules), you must ensure those models are available in the runtime environment. The standard container image includes only the default models. Any additional models must be downloaded and made available before use. If required models are missing, Docling Serve will raise runtime errors rather than downloading them automatically. This default choice wants to guarantee the system is not calling external services.
## Model Storage Location
Docling Serve loads models from the directory specified by the `DOCLING_SERVE_ARTIFACTS_PATH` environment variable. This path must be consistent across model download and runtime. When running with multiple workers or reload enabled, you must use the environment variable rather than the CLI argument for configuration [[source]](./configuration.md).
## Approaches for Making Extra Models Available
There are several ways to ensure required models are present:
### 1. Disable Local Models (Trigger Auto-Download)
You can configure the container to download all models at startup by clearing the artifacts path:
```sh
podman run -d -p 5001:5001 --name docling-serve \
-e DOCLING_SERVE_ARTIFACTS_PATH="" \
-e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve
```
This approach is simple for local development but not recommended for production, as it increases startup time and depends on network availability.
### 2. Build a Custom Image with Pre-Downloaded Models
You can create a new image that includes the required models:
```Dockerfile
FROM quay.io/docling-project/docling-serve
RUN docling-tools models download smolvlm
```
This method is suitable for production, as it ensures all models are present in the image and avoids runtime downloads.
### 3. Update the Entrypoint to Download Models Before Startup
You can override the entrypoint to download models before starting the service:
```sh
podman run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve \
-- sh -c 'exec docling-tools models download smolvlm && exec docling-serve run'
```
This is useful for environments where you want to keep the base image unchanged but still automate model preparation.
### 4. Mount a Volume with Pre-Downloaded Models
Download models locally and mount them into the container:
```sh
# Download the models locally
docling-tools models download --all -o models
# Start the container with the local models folder
podman run -p 5001:5001 \
-v $(pwd)/models:/opt/app-root/src/models \
-e DOCLING_SERVE_ARTIFACTS_PATH="/opt/app-root/src/models" \
-e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve
```
This approach is robust for both local and production deployments, especially when using persistent storage.
## Kubernetes/Cluster Deployments
For Kubernetes or OpenShift clusters, the recommended approach is to use a PersistentVolumeClaim (PVC) for model storage, a Kubernetes Job to download models, and mount the volume into the deployment. This ensures models persist across pod restarts and scale-out scenarios.
### Example: PersistentVolumeClaim
```yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: docling-model-cache-pvc
spec:
accessModes:
- ReadWriteOnce
volumeMode: Filesystem
resources:
requests:
storage: 10Gi
```
If you don't want to use default storage class, set your custom storage class with following:
```yaml
spec:
...
storageClassName: <Storage Class Name>
```
Manifest example: [docling-model-cache-pvc.yaml](./deploy-examples/docling-model-cache-pvc.yaml)
### Example: Model Download Job
```yaml
apiVersion: batch/v1
kind: Job
metadata:
name: docling-model-cache-load
spec:
template:
spec:
containers:
- name: loader
image: ghcr.io/docling-project/docling-serve-cpu:main
command:
- docling-tools
- models
- download
- '--output-dir=/modelcache'
- 'layout'
- 'tableformer'
- 'code_formula'
- 'picture_classifier'
- 'smolvlm'
- 'granite_vision'
- 'easyocr'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
restartPolicy: Never
```
The job will mount the previously created persistent volume and execute command similar to how we would load models locally:
`docling-tools models download --output-dir <MOUNT-PATH> [LIST_OF_MODELS]`
In manifest, we specify desired models individually, or we can use `--all` parameter to download all models.
Manifest example: [docling-model-cache-job.yaml](./deploy-examples/docling-model-cache-job.yaml)
### Example: Deployment with Mounted Volume
```yaml
spec:
template:
spec:
containers:
- name: api
env:
- name: DOCLING_SERVE_ARTIFACTS_PATH
value: '/modelcache'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
```
The value of `DOCLING_SERVE_ARTIFACTS_PATH` must match the mount path where models are stored.
Now, when docling-serve is executing tasks, the underlying docling installation will load model weights from mounted volume.
Manifest example: [docling-model-cache-deployment.yaml](./deploy-examples/docling-model-cache-deployment.yaml)
## Local Docker Execution
For local Docker or Podman execution, you can use any of the approaches above. Mounting a local directory with pre-downloaded models is the most reliable for repeated runs and avoids network dependencies.
## Troubleshooting and Best Practices
- If a required model is missing from the artifacts path, Docling Serve will raise a runtime error.
- Always ensure the value of `DOCLING_SERVE_ARTIFACTS_PATH` matches the directory where models are stored and mounted.
- For production and cluster environments, prefer persistent storage and pre-loading models via a dedicated job.
For more details and YAML manifest examples, see the [deployment documentation](./deployment.md).

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# Usage
The API provides two endpoints: one for urls, one for files. This is necessary to send files directly in binary format instead of base64-encoded strings.
## Common parameters
On top of the source of file (see below), both endpoints support the same parameters, which are almost the same as the Docling CLI.
- `from_formats` (List[str]): Input format(s) to convert from. Allowed values: `docx`, `pptx`, `html`, `image`, `pdf`, `asciidoc`, `md`. Defaults to all formats.
- `to_formats` (List[str]): Output format(s) to convert to. Allowed values: `md`, `json`, `html`, `text`, `doctags`. Defaults to `md`.
- `pipeline` (str). The choice of which pipeline to use. Allowed values are `standard` and `vlm`. Defaults to `standard`.
- `page_range` (tuple). If specified, only convert a range of pages. The page number starts at 1.
- `do_ocr` (bool): If enabled, the bitmap content will be processed using OCR. Defaults to `True`.
- `image_export_mode`: Image export mode for the document (only in case of JSON, Markdown or HTML). Allowed values: embedded, placeholder, referenced. Optional, defaults to `embedded`.
- `force_ocr` (bool): If enabled, replace any existing text with OCR-generated text over the full content. Defaults to `False`.
- `ocr_engine` (str): OCR engine to use. Allowed values: `easyocr`, `tesserocr`, `tesseract`, `rapidocr`, `ocrmac`. Defaults to `easyocr`. To use the `tesserocr` engine, `tesserocr` must be installed where docling-serve is running: `pip install tesserocr`
- `ocr_lang` (List[str]): List of languages used by the OCR engine. Note that each OCR engine has different values for the language names. Defaults to empty.
- `pdf_backend` (str): PDF backend to use. Allowed values: `pypdfium2`, `dlparse_v1`, `dlparse_v2`, `dlparse_v4`. Defaults to `dlparse_v4`.
- `table_mode` (str): Table mode to use. Allowed values: `fast`, `accurate`. Defaults to `fast`.
- `abort_on_error` (bool): If enabled, abort on error. Defaults to false.
- `md_page_break_placeholder` (str): Add this placeholder between pages in the markdown output.
- `do_table_structure` (bool): If enabled, the table structure will be extracted. Defaults to true.
- `do_code_enrichment` (bool): If enabled, perform OCR code enrichment. Defaults to false.
- `do_formula_enrichment` (bool): If enabled, perform formula OCR, return LaTeX code. Defaults to false.
- `do_picture_classification` (bool): If enabled, classify pictures in documents. Defaults to false.
- `do_picture_description` (bool): If enabled, describe pictures in documents. Defaults to false.
- `picture_description_area_threshold` (float): Minimum percentage of the area for a picture to be processed with the models. Defaults to 0.05.
- `picture_description_local` (dict): Options for running a local vision-language model in the picture description. The parameters refer to a model hosted on Hugging Face. This parameter is mutually exclusive with `picture_description_api`.
- `picture_description_api` (dict): API details for using a vision-language model in the picture description. This parameter is mutually exclusive with `picture_description_local`.
- `include_images` (bool): If enabled, images will be extracted from the document. Defaults to false.
- `images_scale` (float): Scale factor for images. Defaults to 2.0.
### Authentication
When authentication is activated (see the parameter `DOCLING_SERVE_API_KEY` in [configuration.md](./configuration.md)), all the API requests **must** provide the header `X-Api-Key` with the correct secret key.
## Convert endpoints
### Source endpoint
The endpoint is `/v1/convert/source`, listening for POST requests of JSON payloads.
On top of the above parameters, you must send the URL(s) of the document you want process with either the `http_sources` or `file_sources` fields.
The first is fetching URL(s) (optionally using with extra headers), the second allows to provide documents as base64-encoded strings.
No `options` is required, they can be partially or completely omitted.
Simple payload example:
```json
{
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
```
<details>
<summary>Complete payload example:</summary>
```json
{
"options": {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": true,
"force_ocr": false,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": false,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
```
</details>
<details>
<summary>CURL example:</summary>
```sh
curl -X 'POST' \
'http://localhost:5001/v1/convert/source' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"options": {
"from_formats": [
"docx",
"pptx",
"html",
"image",
"pdf",
"asciidoc",
"md",
"xlsx"
],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": true,
"force_ocr": false,
"ocr_engine": "easyocr",
"ocr_lang": [
"fr",
"de",
"es",
"en"
],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": false,
"do_table_structure": true,
"include_images": true,
"images_scale": 2
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}'
```
</details>
<details>
<summary>Python example:</summary>
```python
import httpx
async_client = httpx.AsyncClient(timeout=60.0)
url = "http://localhost:5001/v1/convert/source"
payload = {
"options": {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": "en",
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}]
}
response = await async_client_client.post(url, json=payload)
data = response.json()
```
</details>
#### File as base64
The `file_sources` argument in the endpoint allows to send files as base64-encoded strings.
When your PDF or other file type is too large, encoding it and passing it inline to curl
can lead to an “Argument list too long” error on some systems. To avoid this, we write
the JSON request body to a file and have curl read from that file.
<details>
<summary>CURL steps:</summary>
```sh
# 1. Base64-encode the file
B64_DATA=$(base64 -w 0 /path/to/file/pdf-to-convert.pdf)
# 2. Build the JSON with your options
cat <<EOF > /tmp/request_body.json
{
"options": {
},
"file_sources": [{
"base64_string": "${B64_DATA}",
"filename": "pdf-to-convert.pdf"
}]
}
EOF
# 3. POST the request to the docling service
curl -X POST "localhost:5001/v1/convert/source" \
-H "Content-Type: application/json" \
-d @/tmp/request_body.json
```
</details>
### File endpoint
The endpoint is: `/v1/convert/file`, listening for POST requests of Form payloads (necessary as the files are sent as multipart/form data). You can send one or multiple files.
<details>
<summary>CURL example:</summary>
```sh
curl -X 'POST' \
'http://127.0.0.1:5001/v1/convert/file' \
-H 'accept: application/json' \
-H 'Content-Type: multipart/form-data' \
-F 'ocr_engine=easyocr' \
-F 'pdf_backend=dlparse_v2' \
-F 'from_formats=pdf' \
-F 'from_formats=docx' \
-F 'force_ocr=false' \
-F 'image_export_mode=embedded' \
-F 'ocr_lang=en' \
-F 'ocr_lang=pl' \
-F 'table_mode=fast' \
-F 'files=@2206.01062v1.pdf;type=application/pdf' \
-F 'abort_on_error=false' \
-F 'to_formats=md' \
-F 'to_formats=text' \
-F 'do_ocr=true'
```
</details>
<details>
<summary>Python example:</summary>
```python
import httpx
async_client = httpx.AsyncClient(timeout=60.0)
url = "http://localhost:5001/v1/convert/file"
parameters = {
"from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"do_ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
}
current_dir = os.path.dirname(__file__)
file_path = os.path.join(current_dir, '2206.01062v1.pdf')
files = {
'files': ('2206.01062v1.pdf', open(file_path, 'rb'), 'application/pdf'),
}
response = await async_client.post(url, files=files, data=parameters)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
```
</details>
### Picture description options
When the picture description enrichment is activated, users may specify which model and which execution mode to use for this task. There are two choices for the execution mode: _local_ will run the vision-language model directly, _api_ will invoke an external API endpoint.
The local option is specified with:
```jsonc
{
"picture_description_local": {
"repo_id": "", // Repository id from the Hugging Face Hub.
"generation_config": {"max_new_tokens": 200, "do_sample": false}, // HF generation config.
"prompt": "Describe this image in a few sentences. ", // Prompt used when calling the vision-language model.
}
}
```
The possible values for `generation_config` are documented in the [Hugging Face text generation docs](https://huggingface.co/docs/transformers/en/main_classes/text_generation#transformers.GenerationConfig).
The api option is specified with:
```jsonc
{
"picture_description_api": {
"url": "", // Endpoint which accepts openai-api compatible requests.
"headers": {}, // Headers used for calling the API endpoint. For example, it could include authentication headers.
"params": {}, // Model parameters.
"timeout": 20, // Timeout for the API request.
"prompt": "Describe this image in a few sentences. ", // Prompt used when calling the vision-language model.
}
}
```
Example URLs are:
- `http://localhost:8000/v1/chat/completions` for the local vllm api, with example `picture_description_api`:
- the `HuggingFaceTB/SmolVLM-256M-Instruct` model
```json
{
"url": "http://localhost:8000/v1/chat/completions",
"params": {
"model": "HuggingFaceTB/SmolVLM-256M-Instruct",
"max_completion_tokens": 200,
}
}
```
- the `ibm-granite/granite-vision-3.2-2b` model
```json
{
"url": "http://localhost:8000/v1/chat/completions",
"params": {
"model": "ibm-granite/granite-vision-3.2-2b",
"max_completion_tokens": 200,
}
}
```
- `http://localhost:11434/v1/chat/completions` for the local Ollama api, with example `picture_description_api`:
- the `granite3.2-vision:2b` model
```json
{
"url": "http://localhost:11434/v1/chat/completions",
"params": {
"model": "granite3.2-vision:2b"
}
}
```
Note that when using `picture_description_api`, the server must be launched with `DOCLING_SERVE_ENABLE_REMOTE_SERVICES=true`.
## Response format
The response can be a JSON Document or a File.
- If you process only one file, the response will be a JSON document with the following format:
```jsonc
{
"document": {
"md_content": "",
"json_content": {},
"html_content": "",
"text_content": "",
"doctags_content": ""
},
"status": "<success|partial_success|skipped|failure>",
"processing_time": 0.0,
"timings": {},
"errors": []
}
```
Depending on the value you set in `output_formats`, the different items will be populated with their respective results or empty.
`processing_time` is the Docling processing time in seconds, and `timings` (when enabled in the backend) provides the detailed
timing of all the internal Docling components.
- If you set the parameter `target` to the zip mode, the response will be a zip file.
- If multiple files are generated (multiple inputs, or one input but multiple outputs with the zip target mode), the response will be a zip file.
## Asynchronous API
Both `/v1/convert/source` and `/v1/convert/file` endpoints are available as asynchronous variants.
The advantage of the asynchronous endpoints is the possible to interrupt the connection, check for the progress update and fetch the result.
This approach is more resilient against network instabilities and allows the client application logic to easily interleave conversion with other tasks.
Launch an asynchronous conversion with:
- `POST /v1/convert/source/async` when providing the input as sources.
- `POST /v1/convert/file/async` when providing the input as multipart-form files.
The response format is a task detail:
```jsonc
{
"task_id": "<task_id>", // the task_id which can be used for the next operations
"task_status": "pending|started|success|failure", // the task status
"task_position": 1, // the position in the queue
"task_meta": null, // metadata e.g. how many documents are in the total job and how many have been converted
}
```
### Polling status
For checking the progress of the conversion task and wait for its completion, use the endpoint:
- `GET /v1/status/poll/{task_id}`
<details>
<summary>Example waiting loop:</summary>
```python
import time
import httpx
# ...
# response from the async task submission
task = response.json()
while task["task_status"] not in ("success", "failure"):
response = httpx.get(f"{base_url}/status/poll/{task['task_id']}")
task = response.json()
time.sleep(5)
```
<details>
### Subscribe with websockets
Using websocket you can get the client application being notified about updates of the conversion task.
To start the websocket connection, use the endpoint:
- `/v1/status/ws/{task_id}`
Websocket messages are JSON object with the following structure:
```jsonc
{
"message": "connection|update|error", // type of message being sent
"task": {}, // the same content of the task description
"error": "", // description of the error
}
```
<details>
<summary>Example websocket usage:</summary>
```python
from websockets.sync.client import connect
uri = f"ws://{base_url}/v1/status/ws/{task['task_id']}"
with connect(uri) as websocket:
for message in websocket:
try:
payload = json.loads(message)
if payload["message"] == "error":
break
if payload["message"] == "error" and payload["task"]["task_status"] in ("success", "failure"):
break
except:
break
```
</details>
### Fetch results
When the task is completed, the result can be fetched with the endpoint:
- `GET /v1/result/{task_id}`

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# Migration to the `v1` API
Docling Serve from the initial prototype `v1alpha` API to the stable `v1` API.
This page provides simple instructions to upgrade your application to the new API.
## API changes
The breaking changes introduced in the `v1` release of Docling Serve are designed to provide a stable schema which
allows the project to provide new capabilities as new type of input sources, targets and also the definition of callback for event-driven applications.
### Endpoint names
All endpoints are renamed from `/v1alpha/` to `/v1/`.
### Sources
When using the `/v1/convert/source` endpoint, input documents have to be specified with the `sources: []` argument, which is replacing the usage of `file_sources` and `http_sources`.
Old version:
```jsonc
{
"options": {}, // conversion options
"file_sources": [ // input documents provided as base64-encoded strings
{"base64_string": "abc123...", "filename": "file.pdf"}
],
"http_sources": [ // input documents provided as http urls
{"url": "https://..."}
]
}
```
New version:
```jsonc
{
"options": {}, // conversion options
"sources": [
// input document provided as base64-encoded string
{"kind": "file", "base64_string": "abc123...", "filename": "file.pdf"},
// input document provided as http urls
{"kind": "http", "url": "https://..."},
]
}
```
### Targets
Switching between output formats, i.e. from the JSON inbody response to the zip archive response, users have to specify the `target` argument, which is replacing the usage of `options.return_as_file`.
Old version:
```jsonc
{
"options": {
"return_as_file": true // <-- to be removed
},
// ...
}
```
New version:
```jsonc
{
"options": {},
"target": {"kind": "zip"}, // <-- add this
// ...
}
```
## Continue with the old API
If you are not able to apply the changes above to your application, please consider pinning of the previous `v0.x` container images, e.g.
```sh
podman run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=1 quay.io/docling-project/docling-serve:v0.16.1
```
_Note that the old prototype API will not be supported in new `v1.x` versions._

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import os
import zipfile
import requests
from deepsearch_glm.utils.load_pretrained_models import load_pretrained_nlp_models
from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline
# Download Docling models
StandardPdfPipeline.download_models_hf(force=True)
load_pretrained_nlp_models(verbose=True)
# Download EasyOCR models
urls = [
"https://github.com/JaidedAI/EasyOCR/releases/download/v1.3/latin_g2.zip",
"https://github.com/JaidedAI/EasyOCR/releases/download/pre-v1.1.6/craft_mlt_25k.zip"
]
local_zip_paths = [
"/opt/app-root/src/latin_g2.zip",
"/opt/app-root/src/craft_mlt_25k.zip"
]
extract_path = "/opt/app-root/src/.EasyOCR/model/"
for url, local_zip_path in zip(urls, local_zip_paths):
# Download the file
response = requests.get(url)
with open(local_zip_path, "wb") as file:
file.write(response.content)
# Unzip the file
with zipfile.ZipFile(local_zip_path, "r") as zip_ref:
zip_ref.extractall(extract_path)
# Clean up the zip file
os.remove(local_zip_path)

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@@ -1,8 +1,7 @@
tesseract
tesseract-devel
tesseract-langpack-eng
tesseract-osd
leptonica-devel
libglvnd-glx
glib2
wget
git

4699
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@@ -1,123 +1,266 @@
[tool.poetry]
[project]
name = "docling-serve"
version = "0.2.0"
version = "1.3.1" # DO NOT EDIT, updated automatically
description = "Running Docling as a service"
license = "MIT"
license = {text = "MIT"}
authors = [
"Michele Dolfi <dol@zurich.ibm.com>",
"Christoph Auer <cau@zurich.ibm.com>",
"Panos Vagenas <pva@zurich.ibm.com>",
"Cesar Berrospi Ramis <ceb@zurich.ibm.com>",
"Peter Staar <taa@zurich.ibm.com>",
{name="Michele Dolfi", email="dol@zurich.ibm.com"},
{name="Guillaume Moutier", email="gmoutier@redhat.com"},
{name="Anil Vishnoi", email="avishnoi@redhat.com"},
{name="Panos Vagenas", email="pva@zurich.ibm.com"},
{name="Christoph Auer", email="cau@zurich.ibm.com"},
{name="Peter Staar", email="taa@zurich.ibm.com"},
]
maintainers = [
"Peter Staar <taa@zurich.ibm.com>",
"Christoph Auer <cau@zurich.ibm.com>",
"Michele Dolfi <dol@zurich.ibm.com>",
"Cesar Berrospi Ramis <ceb@zurich.ibm.com>",
"Panos Vagenas <pva@zurich.ibm.com>",
{name="Michele Dolfi", email="dol@zurich.ibm.com"},
{name="Anil Vishnoi", email="avishnoi@redhat.com"},
{name="Panos Vagenas", email="pva@zurich.ibm.com"},
{name="Christoph Auer", email="cau@zurich.ibm.com"},
{name="Peter Staar", email="taa@zurich.ibm.com"},
]
readme = "README.md"
repository = "https://github.com/DS4SD/docling-serve"
homepage = "https://github.com/DS4SD/docling-serve"
classifiers = [
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
# "Development Status :: 5 - Production/Stable",
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Typing :: Typed",
"Programming Language :: Python :: 3"
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
]
requires-python = ">=3.10"
dependencies = [
"docling~=2.38",
"docling-core>=2.44.1",
"docling-jobkit[kfp,rq,vlm]>=1.4.0,<2.0.0",
"fastapi[standard]~=0.115",
"httpx~=0.28",
"pydantic~=2.10",
"pydantic-settings~=2.4",
"python-multipart>=0.0.14,<0.1.0",
"typer~=0.12",
"uvicorn[standard]>=0.29.0,<1.0.0",
"websockets~=14.0",
"scalar-fastapi>=1.0.3",
"docling-mcp>=1.0.0",
]
[tool.poetry.dependencies]
python = ">=3.10,<3.13" # 3.10 needed for Gradio, and no torchvision build for 3.13 yet
docling = "^2.14.0"
fastapi = {version = "^0.115.6", extras = ["standard"]}
gradio = { version = "^5.9.1", optional = true }
uvicorn = "~0.29.0"
pydantic = "^2.10.3"
pydantic-settings = "^2.4.0"
python-multipart = "^0.0.19"
httpx = "^0.28.1"
tesserocr = { version = "^2.7.1", optional = true }
rapidocr-onnxruntime = { version = "^1.4.0", optional = true, markers = "python_version < '3.13'" }
onnxruntime = [
# 1.19.2 is the last version with python3.9 support,
# see https://github.com/microsoft/onnxruntime/releases/tag/v1.20.0
{ version = ">=1.7.0,<1.20.0", optional = true, markers = "python_version < '3.10'" },
{ version = "^1.7.0", optional = true, markers = "python_version >= '3.10'" }
[project.optional-dependencies]
ui = [
"gradio~=5.9",
"pydantic<2.11.0", # fix compatibility between gradio and new pydantic 2.11
]
tesserocr = [
"tesserocr~=2.7"
]
rapidocr = [
"rapidocr-onnxruntime~=1.4; python_version<'3.13'",
"onnxruntime~=1.7",
]
flash-attn = [
"flash-attn~=2.8.2; sys_platform == 'linux' and platform_machine == 'x86_64'"
]
[dependency-groups]
dev = [
"asgi-lifespan~=2.0",
"mypy~=1.11",
"pre-commit-uv~=4.1",
"pytest~=8.3",
"pytest-asyncio~=0.24",
"pytest-check~=2.4",
"python-semantic-release~=7.32",
"ruff>=0.9.6",
]
[tool.poetry.extras]
ui = ["gradio"]
tesserocr = ["tesserocr"]
rapidocr = ["rapidocr-onnxruntime", "onnxruntime"]
pypi = [
"torch>=2.7.1",
"torchvision>=0.22.1",
]
cpu = [
"torch>=2.7.1",
"torchvision>=0.22.1",
]
[tool.poetry.group.pypi-torch]
optional = false
cu124 = [
"torch>=2.6.0 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
"torchvision>=0.21.0 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
]
[tool.poetry.group.pypi-torch.dependencies]
cu126 = [
"torch>=2.7.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
"torchvision>=0.22.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
]
cu128 = [
"torch>=2.7.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
"torchvision>=0.22.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
]
rocm = [
"torch>=2.7.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
"torchvision>=0.22.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
"pytorch-triton-rocm>=3.3.1 ; sys_platform == 'linux' and platform_machine == 'x86_64' and python_version < '3.13'",
]
[tool.uv]
package = true
default-groups = ["dev", "pypi"]
conflicts = [
[
{ group = "pypi" },
{ group = "cpu" },
{ group = "cu124" },
{ group = "cu126" },
{ group = "cu128" },
{ group = "rocm" },
],
]
environments = ["sys_platform != 'darwin' or platform_machine != 'x86_64'"]
override-dependencies = [
"urllib3~=2.0"
]
[tool.uv.sources]
torch = [
{version = "!=2.4.1+cpu" },
{ index = "pytorch-pypi", group = "pypi" },
{ index = "pytorch-cpu", group = "cpu" },
{ index = "pytorch-cu124", group = "cu124", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu126", group = "cu126", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu128", group = "cu128", marker = "sys_platform == 'linux'" },
{ index = "pytorch-rocm", group = "rocm", marker = "sys_platform == 'linux'" },
]
torchvision = [
{version = "!=0.19.1+cpu" },
{ index = "pytorch-pypi", group = "pypi" },
{ index = "pytorch-cpu", group = "cpu" },
{ index = "pytorch-cu124", group = "cu124", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu126", group = "cu126", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu128", group = "cu128", marker = "sys_platform == 'linux'" },
{ index = "pytorch-rocm", group = "rocm", marker = "sys_platform == 'linux'" },
]
[tool.poetry.group.cpu]
optional = true
[tool.poetry.group.cpu.dependencies]
torch = [
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.10"', url="https://download.pytorch.org/whl/cpu/torch-2.4.1%2Bcpu-cp310-cp310-linux_x86_64.whl"},
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.11"', url="https://download.pytorch.org/whl/cpu/torch-2.4.1%2Bcpu-cp311-cp311-linux_x86_64.whl"},
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.12"', url="https://download.pytorch.org/whl/cpu/torch-2.4.1%2Bcpu-cp312-cp312-linux_x86_64.whl"},
]
torchvision = [
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.10"', url="https://download.pytorch.org/whl/cpu/torchvision-0.19.1%2Bcpu-cp310-cp310-linux_x86_64.whl"},
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.11"', url="https://download.pytorch.org/whl/cpu/torchvision-0.19.1%2Bcpu-cp311-cp311-linux_x86_64.whl"},
{markers = 'platform_machine=="x86_64" and sys_platform=="linux" and python_version == "3.12"', url="https://download.pytorch.org/whl/cpu/torchvision-0.19.1%2Bcpu-cp312-cp312-linux_x86_64.whl"},
pytorch-triton-rocm = [
{ index = "pytorch-rocm", marker = "sys_platform == 'linux'" },
]
[tool.poetry.group.constraints.dependencies]
numpy = [
{ version = "^2.1.0", markers = 'python_version >= "3.13"' },
{ version = "^1.24.4", markers = 'python_version < "3.13"' },
]
# docling-jobkit = { git = "https://github.com/docling-project/docling-jobkit/", rev = "main" }
# docling-jobkit = { path = "../docling-jobkit", editable = true }
[tool.poetry.group.dev.dependencies]
black = "^24.8.0"
isort = "^5.13.2"
pre-commit = "^3.8.0"
autoflake = "^2.3.1"
flake8 = "^7.1.1"
pytest = "^8.3.4"
pytest-asyncio = "^0.24.0"
pytest-check = "^2.4.1"
mypy = "^1.11.2"
[[tool.uv.index]]
name = "pytorch-pypi"
url = "https://pypi.org/simple"
explicit = true
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true
[tool.black]
[[tool.uv.index]]
name = "pytorch-cu124"
url = "https://download.pytorch.org/whl/cu124"
explicit = true
[[tool.uv.index]]
name = "pytorch-cu126"
url = "https://download.pytorch.org/whl/cu126"
explicit = true
[[tool.uv.index]]
name = "pytorch-cu128"
url = "https://download.pytorch.org/whl/cu128"
explicit = true
[[tool.uv.index]]
name = "pytorch-rocm"
url = "https://download.pytorch.org/whl/rocm6.3"
explicit = true
[tool.setuptools.packages.find]
include = ["docling_serve*"]
namespaces = true
[project.scripts]
docling-serve = "docling_serve.__main__:main"
[project.urls]
Homepage = "https://github.com/docling-project/docling-serve"
# Documentation = "https://ds4sd.github.io/docling"
Repository = "https://github.com/docling-project/docling-serve"
Issues = "https://github.com/docling-project/docling-serve/issues"
Changelog = "https://github.com/docling-project/docling-serve/blob/main/CHANGELOG.md"
[tool.ruff]
target-version = "py310"
line-length = 88
target-version = ["py310"]
include = '\.pyi?$'
respect-gitignore = true
[tool.isort]
profile = "black"
line_length = 88
py_version=311
# extend-exclude = [
# "tests",
# ]
[tool.autoflake]
in-place = true
remove-all-unused-imports = true
remove-unused-variables = true
expand-star-imports = true
recursive = true
[tool.ruff.format]
skip-magic-trailing-comma = false
[tool.ruff.lint]
select = [
# "B", # flake8-bugbear
"C", # flake8-comprehensions
"C9", # mccabe
# "D", # flake8-docstrings
"E", # pycodestyle errors (default)
"F", # pyflakes (default)
"I", # isort
"PD", # pandas-vet
"PIE", # pie
# "PTH", # pathlib
"Q", # flake8-quotes
# "RET", # return
"RUF", # Enable all ruff-specific checks
# "SIM", # simplify
"S307", # eval
# "T20", # (disallow print statements) keep debugging statements out of the codebase
"W", # pycodestyle warnings
"ASYNC", # async
"UP", # pyupgrade
]
ignore = [
"E501", # Line too long, handled by ruff formatter
"D107", # "Missing docstring in __init__",
"F811", # "redefinition of the same function"
"PL", # Pylint
"RUF012", # Mutable Class Attributes
"UP007", # Option and Union
]
#extend-select = []
[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["E402", "F401"]
"tests/*.py" = ["ASYNC"] # Disable ASYNC check for tests
[tool.ruff.lint.mccabe]
max-complexity = 15
[tool.ruff.lint.isort.sections]
"docling" = ["docling", "docling_core", "docling_jobkit"]
[tool.ruff.lint.isort]
combine-as-imports = true
section-order = [
"future",
"standard-library",
"third-party",
"docling",
"first-party",
"local-folder",
]
[tool.mypy]
pretty = true
@@ -131,11 +274,11 @@ module = [
"easyocr.*",
"tesserocr.*",
"rapidocr_onnxruntime.*",
"docling_conversion.*",
"gradio_ui.*",
"response_preparation.*",
"helper_functions.*",
"requests.*",
"kfp.*",
"kfp_server_api.*",
"mlx_vlm.*",
"scalar_fastapi.*",
]
ignore_missing_imports = true
@@ -150,3 +293,16 @@ addopts = "-rA --color=yes --tb=short --maxfail=5"
markers = [
"asyncio",
]
[tool.semantic_release]
# for default values check:
# https://github.com/python-semantic-release/python-semantic-release/blob/v7.32.2/semantic_release/defaults.cfg
version_source = "tag_only"
branch = "main"
# configure types which should trigger minor and patch version bumps respectively
# (note that they must be a subset of the configured allowed types):
parser_angular_allowed_types = "build,chore,ci,docs,feat,fix,perf,style,refactor,test"
parser_angular_minor_types = "feat"
parser_angular_patch_types = "fix,perf"

View File

@@ -1,30 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
# Network settings
export PORT="${PORT:-5001}"
export HOST="${HOST:-"0.0.0.0"}"
# Performance settings
UVICORN_WORKERS="${UVICORN_WORKERS:-1}"
# Development settings
export WITH_UI="${WITH_UI:-"true"}"
export RELOAD=${RELOAD:-"false"}
# --------------------------------------
# Process env settings
EXTRA_ARGS=""
if [ "$RELOAD" == "true" ]; then
EXTRA_ARGS="$EXTRA_ARGS --reload"
fi
# Launch
exec poetry run uvicorn \
docling_serve.app:app \
--host=${HOST} \
--port=${PORT} \
--timeout-keep-alive=600 \
${EXTRA_ARGS} \
--workers=${UVICORN_WORKERS}

View File

@@ -6,17 +6,22 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_file(async_client):
"""Test convert single file to all outputs"""
url = "http://localhost:5001/v1alpha/convert/file"
url = "http://localhost:5001/v1/convert/file"
options = {
"from_formats": [
"docx",
@@ -37,7 +42,6 @@ async def test_convert_file(async_client):
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False,
}
current_dir = os.path.dirname(__file__)
@@ -47,9 +51,7 @@ async def test_convert_file(async_client):
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await async_client.post(
url, files=files, data={"options": json.dumps(options)}
)
response = await async_client.post(url, files=files, data=options)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
@@ -89,19 +91,14 @@ async def test_convert_file(async_client):
check.is_in(
'{"schema_name": "DoclingDocument"',
json.dumps(data["document"]["json_content"]),
msg=f"JSON document should contain '{{\\n \"schema_name\": \"DoclingDocument'\". Received: {safe_slice(data['document']['json_content'])}",
msg=f'JSON document should contain \'{{\\n "schema_name": "DoclingDocument\'". Received: {safe_slice(data["document"]["json_content"])}',
)
# HTML check
check.is_in(
"html_content",
data.get("document", {}),
msg=f"Response should contain 'html_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("html_content") is not None:
check.is_in(
'<!DOCTYPE html>\n<html lang="en">\n<head>',
"<!DOCTYPE html>\n<html>\n<head>",
data["document"]["html_content"],
msg=f"HTML document should contain '<!DOCTYPE html>\\n<html lang=\"en'>. Received: {safe_slice(data['document']['html_content'])}",
msg=f"HTML document should contain '<!DOCTYPE html>\\n<html>'. Received: {safe_slice(data['document']['html_content'])}",
)
# Text check
check.is_in(
@@ -123,7 +120,7 @@ async def test_convert_file(async_client):
)
if data.get("document", {}).get("doctags_content") is not None:
check.is_in(
"<document>\n<section_header_level_1><location>",
"<doctag><page_header><loc",
data["document"]["doctags_content"],
msg=f"DocTags document should contain '<document>\\n<section_header_level_1><location>'. Received: {safe_slice(data['document']['doctags_content'])}",
msg=f"DocTags document should contain '<doctag><page_header><loc'. Received: {safe_slice(data['document']['doctags_content'])}",
)

View File

@@ -0,0 +1,75 @@
import json
import time
from pathlib import Path
import httpx
import pytest
import pytest_asyncio
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client):
"""Test convert URL to all outputs"""
base_url = "http://localhost:5001/v1"
payload = {
"to_formats": ["md", "json", "html"],
"image_export_mode": "placeholder",
"ocr": False,
"abort_on_error": False,
}
file_path = Path(__file__).parent / "2206.01062v1.pdf"
files = {
"files": (file_path.name, file_path.open("rb"), "application/pdf"),
}
for n in range(1):
response = await async_client.post(
f"{base_url}/convert/file/async", files=files, data=payload
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await async_client.get(f"{base_url}/status/poll/{task['task_id']}")
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
print(f"{task['task_position']=}")
time.sleep(2)
assert task["task_status"] == "success"
print(f"Task completed with status {task['task_status']=}")
result_resp = await async_client.get(f"{base_url}/result/{task['task_id']}")
assert result_resp.status_code == 200, "Response should be 200 OK"
result = result_resp.json()
print("Got result.")
assert "md_content" in result["document"]
assert result["document"]["md_content"] is not None
assert len(result["document"]["md_content"]) > 10
assert "html_content" in result["document"]
assert result["document"]["html_content"] is not None
assert len(result["document"]["html_content"]) > 10
assert "json_content" in result["document"]
assert result["document"]["json_content"] is not None
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"

View File

@@ -5,17 +5,22 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client):
"""Test convert URL to all outputs"""
url = "http://localhost:5001/v1alpha/convert/source"
url = "http://localhost:5001/v1/convert/source"
payload = {
"options": {
"from_formats": [
@@ -37,9 +42,8 @@ async def test_convert_url(async_client):
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False,
},
"http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}],
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2206.01062"}],
}
print(json.dumps(payload, indent=2))
@@ -83,7 +87,7 @@ async def test_convert_url(async_client):
check.is_in(
'{"schema_name": "DoclingDocument"',
json.dumps(data["document"]["json_content"]),
msg=f"JSON document should contain '{{\\n \"schema_name\": \"DoclingDocument'\". Received: {safe_slice(data['document']['json_content'])}",
msg=f'JSON document should contain \'{{\\n "schema_name": "DoclingDocument\'". Received: {safe_slice(data["document"]["json_content"])}',
)
# HTML check
check.is_in(
@@ -93,9 +97,9 @@ async def test_convert_url(async_client):
)
if data.get("document", {}).get("html_content") is not None:
check.is_in(
'<!DOCTYPE html>\n<html lang="en">\n<head>',
"<!DOCTYPE html>\n<html>\n<head>",
data["document"]["html_content"],
msg=f"HTML document should contain '<!DOCTYPE html>\\n<html lang=\"en'>. Received: {safe_slice(data['document']['html_content'])}",
msg=f"HTML document should contain '<!DOCTYPE html>\\n<html>'. Received: {safe_slice(data['document']['html_content'])}",
)
# Text check
check.is_in(
@@ -117,7 +121,7 @@ async def test_convert_url(async_client):
)
if data.get("document", {}).get("doctags_content") is not None:
check.is_in(
"<document>\n<section_header_level_1><location>",
"<doctag><page_header><loc",
data["document"]["doctags_content"],
msg=f"DocTags document should contain '<document>\\n<section_header_level_1><location>'. Received: {safe_slice(data['document']['doctags_content'])}",
msg=f"DocTags document should contain '<doctag><page_header><loc'. Received: {safe_slice(data['document']['doctags_content'])}",
)

View File

@@ -0,0 +1,71 @@
import base64
from pathlib import Path
import httpx
import pytest
import pytest_asyncio
from websockets.sync.client import connect
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client: httpx.AsyncClient):
"""Test convert URL to all outputs"""
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
doc_filename = Path("tests/2408.09869v5.pdf")
encoded_doc = base64.b64encode(doc_filename.read_bytes()).decode()
base_url = "http://localhost:5001/v1"
payload = {
"options": {
"to_formats": ["md", "json"],
"image_export_mode": "placeholder",
"ocr": True,
"abort_on_error": False,
# "do_picture_description": True,
# "picture_description_api": {
# "url": "http://localhost:11434/v1/chat/completions",
# "params": {
# "model": "granite3.2-vision:2b",
# }
# },
# "picture_description_local": {
# "repo_id": "HuggingFaceTB/SmolVLM-256M-Instruct",
# },
},
# "sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}],
"sources": [
{
"kind": "file",
"base64_string": encoded_doc,
"filename": doc_filename.name,
}
],
}
# print(json.dumps(payload, indent=2))
for n in range(5):
response = await async_client.post(
f"{base_url}/convert/source/async", json=payload
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
uri = f"ws://localhost:5001/v1/status/ws/{task['task_id']}?api_key={docling_serve_settings.api_key}"
with connect(uri) as websocket:
for message in websocket:
print(message)

64
tests/test_1-url-async.py Normal file
View File

@@ -0,0 +1,64 @@
import json
import random
import time
import httpx
import pytest
import pytest_asyncio
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client):
"""Test convert URL to all outputs"""
example_docs = [
"https://arxiv.org/pdf/2411.19710",
"https://arxiv.org/pdf/2501.17887",
"https://www.nature.com/articles/s41467-024-50779-y.pdf",
"https://arxiv.org/pdf/2306.12802",
"https://arxiv.org/pdf/2311.18481",
]
base_url = "http://localhost:5001/v1"
payload = {
"options": {
"to_formats": ["md", "json"],
"image_export_mode": "placeholder",
"ocr": True,
"abort_on_error": False,
},
"sources": [{"kind": "http", "url": random.choice(example_docs)}],
}
print(json.dumps(payload, indent=2))
for n in range(3):
response = await async_client.post(
f"{base_url}/convert/source/async", json=payload
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await async_client.get(f"{base_url}/status/poll/{task['task_id']}")
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
print(f"{task['task_position']=}")
time.sleep(2)
assert task["task_status"] == "success"

View File

@@ -1,4 +1,3 @@
import json
import os
import httpx
@@ -6,17 +5,22 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_file(async_client):
"""Test convert single file to all outputs"""
url = "http://localhost:5001/v1alpha/convert/file"
url = "http://localhost:5001/v1/convert/file"
options = {
"from_formats": [
"docx",
@@ -37,7 +41,6 @@ async def test_convert_file(async_client):
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False,
}
current_dir = os.path.dirname(__file__)
@@ -48,27 +51,25 @@ async def test_convert_file(async_client):
("files", ("2408.09869v5.pdf", open(file_path, "rb"), "application/pdf")),
]
response = await async_client.post(
url, files=files, data={"options": json.dumps(options)}
)
response = await async_client.post(url, files=files, data=options)
assert response.status_code == 200, "Response should be 200 OK"
# Check for zip file attachment
content_disposition = response.headers.get("content-disposition")
with check:
assert (
content_disposition is not None
), "Content-Disposition header should be present"
assert content_disposition is not None, (
"Content-Disposition header should be present"
)
with check:
assert "attachment" in content_disposition, "Response should be an attachment"
with check:
assert (
'filename="converted_docs.zip"' in content_disposition
), "Attachment filename should be 'converted_docs.zip'"
assert 'filename="converted_docs.zip"' in content_disposition, (
"Attachment filename should be 'converted_docs.zip'"
)
content_type = response.headers.get("content-type")
with check:
assert (
content_type == "application/zip"
), "Content-Type should be 'application/zip'"
assert content_type == "application/zip", (
"Content-Type should be 'application/zip'"
)

View File

@@ -3,17 +3,22 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client):
"""Test convert URL to all outputs"""
url = "http://localhost:5001/v1alpha/convert/source"
url = "http://localhost:5001/v1/convert/source"
payload = {
"options": {
"from_formats": [
@@ -35,12 +40,12 @@ async def test_convert_url(async_client):
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
"return_as_file": False,
},
"http_sources": [
{"url": "https://arxiv.org/pdf/2206.01062"},
{"url": "https://arxiv.org/pdf/2408.09869"},
"sources": [
{"kind": "http", "url": "https://arxiv.org/pdf/2206.01062"},
{"kind": "http", "url": "https://arxiv.org/pdf/2408.09869"},
],
"target": {"kind": "zip"},
}
response = await async_client.post(url, json=payload)
@@ -50,18 +55,18 @@ async def test_convert_url(async_client):
content_disposition = response.headers.get("content-disposition")
with check:
assert (
content_disposition is not None
), "Content-Disposition header should be present"
assert content_disposition is not None, (
"Content-Disposition header should be present"
)
with check:
assert "attachment" in content_disposition, "Response should be an attachment"
with check:
assert (
'filename="converted_docs.zip"' in content_disposition
), "Attachment filename should be 'converted_docs.zip'"
assert 'filename="converted_docs.zip"' in content_disposition, (
"Attachment filename should be 'converted_docs.zip'"
)
content_type = response.headers.get("content-type")
with check:
assert (
content_type == "application/zip"
), "Content-Type should be 'application/zip'"
assert content_type == "application/zip", (
"Content-Type should be 'application/zip'"
)

View File

@@ -0,0 +1,93 @@
import json
import time
import httpx
import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client):
"""Test convert URL to all outputs"""
base_url = "http://localhost:5001/v1"
payload = {
"options": {
"from_formats": [
"docx",
"pptx",
"html",
"image",
"pdf",
"asciidoc",
"md",
"xlsx",
],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
},
"sources": [
{"kind": "http", "url": "https://arxiv.org/pdf/2206.01062"},
{"kind": "http", "url": "https://arxiv.org/pdf/2408.09869"},
],
"target": {"kind": "zip"},
}
response = await async_client.post(f"{base_url}/convert/source/async", json=payload)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await async_client.get(f"{base_url}/status/poll/{task['task_id']}")
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
print(f"{task['task_position']=}")
time.sleep(2)
assert task["task_status"] == "success"
result_resp = await async_client.get(f"{base_url}/result/{task['task_id']}")
assert result_resp.status_code == 200, "Response should be 200 OK"
# Check for zip file attachment
content_disposition = result_resp.headers.get("content-disposition")
with check:
assert content_disposition is not None, (
"Content-Disposition header should be present"
)
with check:
assert "attachment" in content_disposition, "Response should be an attachment"
with check:
assert 'filename="converted_docs.zip"' in content_disposition, (
"Attachment filename should be 'converted_docs.zip'"
)
content_type = result_resp.headers.get("content-type")
with check:
assert content_type == "application/zip", (
"Content-Type should be 'application/zip'"
)

View File

@@ -0,0 +1,206 @@
import asyncio
import io
import json
import os
import zipfile
import pytest
import pytest_asyncio
from asgi_lifespan import LifespanManager
from httpx import ASGITransport, AsyncClient
from pytest_check import check
from docling_core.types.doc import DoclingDocument, PictureItem
from docling_serve.app import create_app
from docling_serve.settings import docling_serve_settings
@pytest.fixture(scope="session")
def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
async with LifespanManager(app) as manager:
print("Launching lifespan of app.")
yield manager.app
@pytest_asyncio.fixture(scope="session")
async def client(app):
async with AsyncClient(
transport=ASGITransport(app=app), base_url="http://app.io"
) as client:
print("Client is ready")
yield client
@pytest.mark.asyncio
async def test_health(client: AsyncClient):
response = await client.get("/health")
assert response.status_code == 200
assert response.json() == {"status": "ok"}
@pytest.mark.asyncio
async def test_convert_file(client: AsyncClient, auth_headers: dict):
"""Test convert single file to all outputs"""
endpoint = "/v1/convert/file"
options = {
"from_formats": [
"docx",
"pptx",
"html",
"image",
"pdf",
"asciidoc",
"md",
"xlsx",
],
"to_formats": ["md", "json", "html", "text", "doctags"],
"image_export_mode": "placeholder",
"ocr": True,
"force_ocr": False,
"ocr_engine": "easyocr",
"ocr_lang": ["en"],
"pdf_backend": "dlparse_v2",
"table_mode": "fast",
"abort_on_error": False,
}
current_dir = os.path.dirname(__file__)
file_path = os.path.join(current_dir, "2206.01062v1.pdf")
files = {
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
# Response content checks
# Helper function to safely slice strings
def safe_slice(value, length=100):
if isinstance(value, str):
return value[:length]
return str(value) # Convert non-string values to string for debug purposes
# Document check
check.is_in(
"document",
data,
msg=f"Response should contain 'document' key. Received keys: {list(data.keys())}",
)
# MD check
check.is_in(
"md_content",
data.get("document", {}),
msg=f"Response should contain 'md_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("md_content") is not None:
check.is_in(
"## DocLayNet: ",
data["document"]["md_content"],
msg=f"Markdown document should contain 'DocLayNet: '. Received: {safe_slice(data['document']['md_content'])}",
)
# JSON check
check.is_in(
"json_content",
data.get("document", {}),
msg=f"Response should contain 'json_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("json_content") is not None:
check.is_in(
'{"schema_name": "DoclingDocument"',
json.dumps(data["document"]["json_content"]),
msg=f'JSON document should contain \'{{\\n "schema_name": "DoclingDocument\'". Received: {safe_slice(data["document"]["json_content"])}',
)
# HTML check
check.is_in(
"html_content",
data.get("document", {}),
msg=f"Response should contain 'html_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("html_content") is not None:
check.is_in(
"<!DOCTYPE html>\n<html>\n<head>",
data["document"]["html_content"],
msg=f"HTML document should contain '<!DOCTYPE html>\n<html>\n<head>'. Received: {safe_slice(data['document']['html_content'])}",
)
# Text check
check.is_in(
"text_content",
data.get("document", {}),
msg=f"Response should contain 'text_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("text_content") is not None:
check.is_in(
"DocLayNet: A Large Human-Annotated Dataset",
data["document"]["text_content"],
msg=f"Text document should contain 'DocLayNet: A Large Human-Annotated Dataset'. Received: {safe_slice(data['document']['text_content'])}",
)
# DocTags check
check.is_in(
"doctags_content",
data.get("document", {}),
msg=f"Response should contain 'doctags_content' key. Received keys: {list(data.get('document', {}).keys())}",
)
if data.get("document", {}).get("doctags_content") is not None:
check.is_in(
"<doctag><page_header>",
data["document"]["doctags_content"],
msg=f"DocTags document should contain '<doctag><page_header>'. Received: {safe_slice(data['document']['doctags_content'])}",
)
@pytest.mark.asyncio
async def test_referenced_artifacts(client: AsyncClient, auth_headers: dict):
"""Test that paths in the zip file are relative to the zip file root."""
endpoint = "/v1/convert/file"
options = {
"to_formats": ["json"],
"image_export_mode": "referenced",
"target_type": "zip",
"ocr": False,
}
current_dir = os.path.dirname(__file__)
file_path = os.path.join(current_dir, "2206.01062v1.pdf")
files = {
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
with zipfile.ZipFile(io.BytesIO(response.content)) as zip_file:
namelist = zip_file.namelist()
for file in namelist:
if file.endswith(".json"):
doc = DoclingDocument.model_validate(json.loads(zip_file.read(file)))
for item, _level in doc.iterate_items():
if isinstance(item, PictureItem):
assert item.image is not None
print(f"{item.image.uri}=")
assert str(item.image.uri) in namelist

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import asyncio
import json
import os
import pytest
import pytest_asyncio
from asgi_lifespan import LifespanManager
from httpx import ASGITransport, AsyncClient
from docling_core.types import DoclingDocument
from docling_core.types.doc.document import PictureDescriptionData
from docling_serve.app import create_app
from docling_serve.settings import docling_serve_settings
@pytest.fixture(scope="session")
def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
async with LifespanManager(app) as manager:
print("Launching lifespan of app.")
yield manager.app
@pytest_asyncio.fixture(scope="session")
async def client(app):
async with AsyncClient(
transport=ASGITransport(app=app), base_url="http://app.io"
) as client:
print("Client is ready")
yield client
@pytest.mark.asyncio
async def test_convert_file(client: AsyncClient, auth_headers: dict):
"""Test convert single file to all outputs"""
endpoint = "/v1/convert/file"
options = {
"to_formats": ["md", "json"],
"image_export_mode": "placeholder",
"ocr": False,
"do_picture_description": True,
"picture_description_api": json.dumps(
{
"url": "http://localhost:11434/v1/chat/completions", # ollama
"params": {"model": "granite3.2-vision:2b"},
"timeout": 60,
"prompt": "Describe this image in a few sentences. ",
}
),
}
current_dir = os.path.dirname(__file__)
file_path = os.path.join(current_dir, "2206.01062v1.pdf")
files = {
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
doc = DoclingDocument.model_validate(data["document"]["json_content"])
for pic in doc.pictures:
for ann in pic.annotations:
if isinstance(ann, PictureDescriptionData):
print(f"{pic.self_ref}")
print(ann.text)

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import asyncio
import base64
import json
from pathlib import Path
import pytest
import pytest_asyncio
from asgi_lifespan import LifespanManager
from httpx import ASGITransport, AsyncClient
from docling_serve.app import create_app
from docling_serve.settings import docling_serve_settings
@pytest.fixture(scope="session")
def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
async with LifespanManager(app) as manager:
print("Launching lifespan of app.")
yield manager.app
@pytest_asyncio.fixture(scope="session")
async def client(app):
async with AsyncClient(
transport=ASGITransport(app=app), base_url="http://app.io"
) as client:
print("Client is ready")
yield client
async def convert_file(client: AsyncClient, auth_headers: dict):
doc_filename = Path("tests/2408.09869v5.pdf")
encoded_doc = base64.b64encode(doc_filename.read_bytes()).decode()
payload = {
"options": {
"to_formats": ["json"],
},
"sources": [
{
"kind": "file",
"base64_string": encoded_doc,
"filename": doc_filename.name,
}
],
}
response = await client.post(
"/v1/convert/source/async", json=payload, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await client.get(
f"/v1/status/poll/{task['task_id']}", headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
print(f"{task['task_position']=}")
await asyncio.sleep(2)
assert task["task_status"] == "success"
return task
@pytest.mark.asyncio
async def test_clear_results(client: AsyncClient, auth_headers: dict):
"""Test removal of task."""
# Set long delay deletion
docling_serve_settings.result_removal_delay = 100
# Convert and wait for completion
task = await convert_file(client, auth_headers=auth_headers)
# Get result once
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result 1 ok.")
result = result_response.json()
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
# Get result twice
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result 2 ok.")
result = result_response.json()
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
# Clear
clear_response = await client.get(
"/v1/clear/results?older_then=0", headers=auth_headers
)
assert clear_response.status_code == 200, "Response should be 200 OK"
print("Clear ok.")
# Get deleted result
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 404, "Response should be removed"
print("Result was no longer found.")
@pytest.mark.asyncio
async def test_delay_remove(client: AsyncClient, auth_headers: dict):
"""Test automatic removal of task with delay."""
# Set short delay deletion
docling_serve_settings.result_removal_delay = 5
# Convert and wait for completion
task = await convert_file(client, auth_headers=auth_headers)
# Get result once
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result ok.")
result = result_response.json()
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
print("Sleeping to wait the automatic task deletion.")
await asyncio.sleep(10)
# Get deleted result
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 404, "Response should be removed"

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