Compare commits

...

317 Commits

Author SHA1 Message Date
d44d4bd6fd feat: support query date tool (#662) 2023-07-27 22:27:05 +08:00
2adaceab82 feat: bump version to 0.3.11 (#654) 2023-07-27 22:25:32 +08:00
d979955c8a feat: optimize current time (#661) 2023-07-27 22:15:07 +08:00
eae670ea4a feat: enchance chat user experience (#660) 2023-07-27 18:04:41 +08:00
b5825142d1 feat: add current time tool in universal chat agent (#659) 2023-07-27 17:39:36 +08:00
741e9303d4 fix: use sharp logo replace old logo (#658) 2023-07-27 16:34:30 +08:00
538e3fc256 fix: return message error in blocking mode (#657) 2023-07-27 16:14:45 +08:00
ba3dc8cae0 feat: fix dataset retrieve agent llm not support error (#656) 2023-07-27 15:45:52 +08:00
ae7c0380dc Feat/application api add speech to text (#655) 2023-07-27 14:53:19 +08:00
23e3413655 feat: chat in explore support agent (#647)
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
2023-07-27 13:27:34 +08:00
4fdb37771a feat: universal chat in explore (#649)
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
2023-07-27 13:08:57 +08:00
94b54b7ca9 feat: replace the end user column in the web page Log & Ann. with the… (#653)
Co-authored-by: Hao Fu <hao.fu@helloklarity.com>
2023-07-27 12:48:43 +08:00
f9412f5fdb fix: site enable check (#645) 2023-07-26 11:11:09 +08:00
1d6829f400 Feat/application config user input field collapse (#643) 2023-07-26 10:27:52 +08:00
f8bae897e5 fix: switch workspace (#642) 2023-07-26 10:25:35 +08:00
dd1172b57e Perf: Support for password display and hiding (#636)
Co-authored-by: Selenium39 <selenium39@qq.com>
2023-07-24 14:48:00 +08:00
67d326a558 fix(web): fix svg unrecognized props (#631) 2023-07-24 10:31:56 +08:00
fe747040bc downgrade next version (#626) 2023-07-21 12:27:23 +08:00
7d6c925cbc fix(web): using Tooltip unique selector key (#622) 2023-07-21 11:15:00 +08:00
f488d06b20 fix: Top P description error (#624) 2023-07-21 09:15:52 +08:00
c00a19ced3 fix(web): fix Embedded copy status when toggle options (#621) 2023-07-21 09:06:51 +08:00
e9810a6df2 fix: azure openai embedding model name error (#612) 2023-07-20 13:52:54 +08:00
cae15013e0 fix: azure openai deployment list was deprecated suddenly (#611) 2023-07-20 13:46:39 +08:00
52c84da051 add clean unused dataset command (#609) 2023-07-20 11:08:28 +08:00
026f0bfce9 Feat/clean vector dataset (#605) 2023-07-19 21:30:25 +08:00
d19181fb29 chore: minify embed js (#604) 2023-07-19 19:48:44 +08:00
2f9de2229f feat: embed into other site support set custom host (#580)
Co-authored-by: Joel <iamjoel007@gmail.com>
2023-07-19 19:43:07 +08:00
34f55739e0 fix(web): fix #596 copy-to-clipboard issue (#602) 2023-07-19 19:29:37 +08:00
668b059c07 fix: quick switch and click create conversation button may caused fetch conversation list error (#603) 2023-07-19 17:17:29 +08:00
753e5f1500 Fix/application configuration preview style (#597) 2023-07-19 12:41:35 +08:00
a6af8e5d8f Fix/new conversation in mobile phone (#593) 2023-07-18 16:57:28 +08:00
3e1d5ac51b Feat/header ssr (#594) 2023-07-18 16:57:14 +08:00
b0091452ca feat: add bash before entrypoint.sh in Dockerfile (#592) 2023-07-18 16:22:34 +08:00
eff115267f fix: anthropic completion error in blocking mode (#591) 2023-07-18 15:12:52 +08:00
07cde4f8fe feat: bump 0.3.10 (#589) 2023-07-18 15:04:49 +08:00
9f28a48a92 index add to db when dataset updated (#588) 2023-07-18 15:02:33 +08:00
0d3cd3b16a fix: azure provider select error when use custom azure provider (#587) 2023-07-18 14:34:09 +08:00
3dc82fb044 feat: remove davinci required model from azure provider (#586) 2023-07-18 14:14:56 +08:00
cb6e73347e Feat/add ruby sdk (#583) 2023-07-18 10:18:58 +08:00
ecd6cbaee6 Fix/use embedded chatbot with no track mode (#582) 2023-07-18 09:45:17 +08:00
d54e942264 Feat: hide password setting and invitation link in cloud version (#581) 2023-07-18 08:54:14 +08:00
28ba721455 Update README_CN.md (#575) 2023-07-17 11:08:26 +08:00
784dd7848e Update README.md (#576) 2023-07-17 11:08:03 +08:00
e2a5f8ba1a feat: bump version to 0.3.9 (#574) 2023-07-17 09:47:23 +08:00
8e11200306 feat: frontend support claude (#573)
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
2023-07-17 00:14:32 +08:00
7599f79a17 feat: claude api support (#572) 2023-07-17 00:14:19 +08:00
510389909c fix: change chatbot avart to dify icon (#571) 2023-07-16 16:30:55 +08:00
2c6e00174b add document limit check (#570) 2023-07-16 13:21:56 +08:00
24f3456990 fix: account check in runtime (#569) 2023-07-15 23:58:15 +08:00
20514ff288 fix: table too wide fix text generation ui (#566) 2023-07-14 18:15:56 +08:00
381d255290 fix setting-modal provider encrypted tip style (#565) 2023-07-14 17:10:02 +08:00
7f320f9146 feat: bump version to 0.3.8 (#559) 2023-07-14 11:53:15 +08:00
cd51d3323b feat: member invitation and activation (#535)
Co-authored-by: John Wang <takatost@gmail.com>
2023-07-14 11:19:26 +08:00
004b3caa43 Feature/add delete to service (#555) 2023-07-14 10:37:33 +08:00
dbe10799e3 fix: user cancel conversation show error (#558) 2023-07-13 10:32:45 +08:00
054ba88434 fix: regeneration not clear like status and sub more items (#557) 2023-07-13 10:31:07 +08:00
da82a11b26 feat: batch run support export as csv file (#556) 2023-07-13 09:30:16 +08:00
fec607db81 Feat/embedding (#553)
Co-authored-by: Gillian97 <jinling.sunshine@gmail.com>
Co-authored-by: Joel <iamjoel007@gmail.com>
2023-07-12 17:27:50 +08:00
397a92f2ee convert audio wav to mp3 (#552) 2023-07-12 17:18:56 +08:00
b91e226063 fix: api doc update conversation list api to real response (#548) 2023-07-12 13:53:06 +08:00
da5782df92 fix: mobile not auto show generation res (#544) 2023-07-11 17:16:28 +08:00
9af0da4450 fix jwt in web (#545) 2023-07-11 17:07:52 +08:00
d49ac1e4ac Feature/use jwt in web (#533)
Co-authored-by: crazywoola <li.zheng@dentsplysirona.com>
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
2023-07-11 15:21:20 +08:00
57de19a5ca feat: bump version to 0.3.7 (#540) 2023-07-10 15:23:38 +08:00
7c00a0b6a3 fix voice input in safari (#537) 2023-07-10 10:16:38 +08:00
a93506df18 Fix/dataset clean task (#534) 2023-07-08 17:29:56 +08:00
a03a92e9db Feat/chat support voice input (#532) 2023-07-07 17:50:42 +08:00
feebb5dd1f feat: dataset list add order by created at (#531) 2023-07-07 11:51:48 +08:00
6eee7cb42c feat: fix azure embedding Too many inputs problem (#530) 2023-07-07 11:17:36 +08:00
11baff6740 feat: text generation application support run batch (#529) 2023-07-07 10:35:05 +08:00
cde1797cc0 feat: max token add tip (#525) 2023-07-06 15:57:04 +08:00
d143284d99 Fix: stop embedding status display (#523) 2023-07-06 10:51:30 +08:00
2b94545190 fix check version api (#520) 2023-07-05 11:11:38 +08:00
ed6648a41e feat: dataset list add order by created at (#487) 2023-07-05 11:00:21 +08:00
5e2c3eeac3 fix: chat app added new var old conversation not work (#511) 2023-07-04 14:33:41 +08:00
b23d8a912b fix: add missing like i18n (#512) 2023-07-04 14:21:51 +08:00
4f13f8fd0a fix: change langenius text to dify (#498) 2023-07-02 14:01:11 +08:00
561c9cabd5 fix: input text repeat (#492) 2023-06-29 17:27:48 +08:00
39ea967b30 refact common layout (#490) 2023-06-29 15:30:12 +08:00
da04ff040b fix: remove document from dataset error when vector index npe (#489) 2023-06-29 13:09:22 +08:00
b9b0866a46 fix: generate summary error when tokens=4097 (#488) 2023-06-29 12:54:50 +08:00
c6ab7eebd9 fix: delete operation style error (#485) 2023-06-29 09:24:31 +08:00
db4e6d81c5 fix: choose dataset not selected after one page (#481) 2023-06-29 09:22:42 +08:00
df68a7c82b feat: Optimize the quality of the title generate (#484) 2023-06-28 19:59:20 +08:00
838825d747 feat: optimize conversation operation (#479) 2023-06-28 17:53:23 +08:00
a87f6f2837 fix: modal disappear (#478) 2023-06-28 16:44:17 +08:00
9d98669e7d fix: dataset destination error (#477) 2023-06-28 15:51:07 +08:00
408fbb0c70 fix: title, summary, suggested questions generate (#476) 2023-06-28 15:43:33 +08:00
998f819b04 use sub to operate all (#475) 2023-06-28 14:58:40 +08:00
6194b82752 feat: bump to 0.3.6 (#474) 2023-06-28 14:23:20 +08:00
334f46d0b6 Fix/json format (#466) 2023-06-28 13:58:50 +08:00
2eea114ac0 fix special code (#473) 2023-06-28 13:58:36 +08:00
97e9ebd29a Feature/add is deleted to conversations (#470) 2023-06-28 13:31:51 +08:00
ec261aea54 feat: conversation app support pin and delete conversation (#467) 2023-06-28 11:16:54 +08:00
accc5faae3 fix: delete dataset not trigger show start new conversation message (#471) 2023-06-28 10:39:40 +08:00
0462f09ecc fix: app nav call detail match explore app detail page (#469) 2023-06-27 18:40:24 +08:00
1226d73159 Feat/refact header (#468) 2023-06-27 18:02:01 +08:00
c67ecff3fe Fix/json format (#465) 2023-06-27 17:15:03 +08:00
d5b42c09ee fix: template parse error when history include {{any}} (#463) 2023-06-27 16:35:50 +08:00
835bf9fd8d fix: template parse error when pre prompt include {{}} (#462) 2023-06-27 15:51:55 +08:00
c720f831af feat: optimize template parse (#460) 2023-06-27 15:30:38 +08:00
df5763be37 feat: optimize openai error raise (#459) 2023-06-27 12:34:47 +08:00
80eebc2414 feat: upgrade nextjs version (#457) 2023-06-27 12:12:41 +08:00
17d196126c Feat/add icons (#450) 2023-06-26 15:36:52 +08:00
addf150a9e fix: hove x scroll shake (#449) 2023-06-26 13:35:12 +08:00
cad1532f7c feat: optimize index_struct copy (#442) 2023-06-25 17:52:22 +08:00
951afcaaed feat: optimize weaviate error msg (#441) 2023-06-25 17:05:56 +08:00
3241e4015b feat: upgrade langchain (#430)
Co-authored-by: jyong <718720800@qq.com>
2023-06-25 16:49:14 +08:00
Bin
1dee5de9b4 bugfix: conversation parameters (#438) 2023-06-25 16:14:42 +08:00
742bad93b5 feat: bump version to 0.3.5 (#433) 2023-06-21 16:18:41 +08:00
bb3cc6bba6 fix: file size limit to 15M (#431) 2023-06-21 16:08:57 +08:00
23ef2262bd fix: filter empty value in xlsx to improve vector similarity hit (#422) 2023-06-21 11:25:52 +08:00
d637a147ee feat: support batch upload files (#419) 2023-06-21 09:44:01 +08:00
8a4d19d9ba fix: actions 2023-06-21 09:10:07 +08:00
bea382f0dc fix: dataset can only choose first page data (#425)
Support infinite scroll loader data.
2023-06-20 18:08:28 +08:00
8b39e48957 fix REDIS_USERNAME format (#414) 2023-06-19 22:14:47 +08:00
5b4538f021 feat: add more labels 2023-06-19 22:09:02 +08:00
36dc05c4da fix chinese encoding (#411) 2023-06-19 18:41:17 +08:00
54f3bbbf47 feat: bump version to 0.3.4 (#406) 2023-06-19 16:44:48 +08:00
f797fab206 Fix/dataset add pages tip (#410) 2023-06-19 16:32:25 +08:00
ce2996e7d4 Fix/dataset init (#409) 2023-06-19 16:32:03 +08:00
82d07ed2a8 doc: add annaconda info (#402) 2023-06-19 11:09:40 +08:00
c39d8f954e fix: word break in en and other languages (#385) 2023-06-19 09:36:05 +08:00
226f28edcb Feature/self host notion import (#397) 2023-06-17 19:50:21 +08:00
402b0b81d2 feat: add community helm support readme (#395) 2023-06-17 18:25:40 +08:00
b08c19d926 fix encoding is none (#394) 2023-06-17 15:21:48 +08:00
9253f72dea Feat/dataset notion import (#392)
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
Co-authored-by: JzoNg <jzongcode@gmail.com>
2023-06-16 21:47:51 +08:00
f350948bde Fix the issue of decoding a non-UTF-8 encoded file using UTF-8 (#389) 2023-06-16 14:23:03 +08:00
eeb2c28526 Fix the issue of decoding a non-UTF-8 encoded file using UTF-8 encodi… (#378) 2023-06-16 14:12:07 +08:00
673288d58e fix(i18n): Make text gender neutral (#379) 2023-06-16 07:25:50 +08:00
772d67fd65 feat: suport var select options sortable (#376) 2023-06-15 17:07:17 +08:00
7552a6be36 feat: add last active at for accounts (#375) 2023-06-15 13:59:36 +08:00
33200090e8 feat: update actions 2023-06-15 12:51:51 +08:00
01a6c725fa fix: max token tooltip description (#370) 2023-06-15 10:06:43 +08:00
f6e04389e4 Community i18n doc (#365) 2023-06-15 09:39:56 +08:00
e22814b291 fix application model selector style (#360) 2023-06-14 14:23:41 +08:00
a66ef7210b feat: bump version to 0.3.3 (#359) 2023-06-14 12:17:56 +08:00
184afa69ff feat: add gpt-3.5-turbo-16k support and update openai gpt-3.5-turbo & Embedding Ada v2 unit price (#358) 2023-06-14 12:17:43 +08:00
ab115b5f87 fix: completion stop invalid (#355) 2023-06-13 17:47:42 +08:00
3bbc4ad3db fix: change default help link to english (#354) 2023-06-13 17:12:51 +08:00
87af414a52 feat: stop response enchancement (#352) 2023-06-13 16:34:53 +08:00
72555d5df8 feat: add frontend sentry docker compose config (#353) 2023-06-13 16:30:31 +08:00
fff39a307a feat: use react sentry to support pass config via runtime (#350) 2023-06-13 16:04:54 +08:00
a11f36ca60 fix: stop completion response not save to db (#351) 2023-06-13 15:47:58 +08:00
433f8cb57e Feature/add emoji to webapp (#345) 2023-06-13 14:54:12 +08:00
cd136fb293 feat: add WEAVIATE_BATCH_SIZE (#349) 2023-06-13 14:49:40 +08:00
6a3ab36101 feat: optimize weaviate batch size (#348) 2023-06-13 11:28:15 +08:00
1af968e73a feat: optimize api language support (#344) 2023-06-13 10:06:49 +08:00
94646f29c3 Update README_CN.md (#342) 2023-06-12 21:14:34 +08:00
e028a0595c Update README.md (#341) 2023-06-12 21:14:21 +08:00
b16a7b0b3b feat: stop response call api (#340) 2023-06-12 16:37:03 +08:00
e083a7067b Create README_ES.md (#335) 2023-06-10 18:25:13 +08:00
205459d54d fix: button abnormal style (#333) 2023-06-10 13:19:08 +08:00
3d14431b96 Fix/excel data format (#334) 2023-06-09 20:21:11 +08:00
2ba0ee989a feat: bump version to 0.3.2 (#330) 2023-06-09 16:25:26 +08:00
b055470147 Fix: xls not supported (#329) 2023-06-09 16:11:27 +08:00
5943385d42 Fix: the bug that allows regular users to add unregistered users to the workspace. (#328) 2023-06-09 16:07:53 +08:00
0abd67288b feat: support xlsx file parsing (#304)
Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
2023-06-09 15:57:19 +08:00
bbe58327c8 feat: remove ph (#327) 2023-06-09 14:39:37 +08:00
299c51ebc4 feat: npm sdk to 2.0 to fix steaming problem (#326) 2023-06-09 14:36:48 +08:00
3a7f58d2a6 Feature/fix streaming mode (#324) 2023-06-09 14:24:59 +08:00
6123bba96d feat: add reset-encrypt-key-pair cmd for self hosted mode (#325) 2023-06-09 11:36:38 +08:00
d5ab3b5072 fix: output code too long break ui (#320) 2023-06-08 16:27:37 +08:00
df26f82536 Feature/support xlsx (#311) 2023-06-08 15:23:38 +08:00
dbe0c43515 Chore: support gradient border and text (#317) 2023-06-08 09:38:11 +08:00
f4052fdbc7 fix: analysis all time param (#316) 2023-06-07 22:18:21 +08:00
b5ade19c75 feat: fix frontend docker image build fail (#314) 2023-06-07 16:47:49 +08:00
040eacb8bd fix: safari 14 not show modal (#310) 2023-06-07 09:59:33 +08:00
20899c44ff fix: segment search by keyword (#303) 2023-06-07 00:45:25 +08:00
35a2beb195 delete segment not commit (#309) 2023-06-06 23:16:51 +08:00
2056093855 update docker compose cmd (#308) 2023-06-06 20:26:45 +08:00
2bf48514bc fix markdown parser (#230) 2023-06-06 19:51:40 +08:00
c109b1a920 fix: stale.yml 2023-06-06 15:27:04 +08:00
45499328b8 fix: actions 2023-06-06 15:22:20 +08:00
4c61aa399d Create stale.yml 2023-06-06 15:19:27 +08:00
3e380c082a fix: reset some config not work: like var required status, dataset, feature status (#305) 2023-06-06 14:58:56 +08:00
53db5bab36 Feat/add GitHub star icon (#302) 2023-06-06 11:22:00 +08:00
6483beb096 Feat/auto rule generate (#300) 2023-06-06 10:52:02 +08:00
e61c84ca72 fix: header nav load more app (#296) 2023-06-06 10:42:32 +08:00
d70086b841 feat: sentry to dify account (#299) 2023-06-06 10:29:38 +08:00
a3ee037d6d feat: optimize output parse failed error (#298) 2023-06-05 11:23:51 +08:00
2de18a6490 fix: ignore VSCode setting.json path (#297) 2023-06-05 10:54:09 +08:00
4134e915ce fix: tooltip covered by high z index element (#295) 2023-06-05 10:49:06 +08:00
a838ba7b46 Chore/ignore vscode setting (#293) 2023-06-05 10:15:16 +08:00
5f38214a41 chore: mute handle message cut off (#291) 2023-06-05 09:55:03 +08:00
19b5cb1e10 feat: fix json end with `` (#285) 2023-06-02 17:34:24 +08:00
2478c88e07 feat: increase dataset description length to 400 (#283) 2023-06-02 14:03:18 +08:00
59e59c19b2 fix: missing imports (#281) 2023-06-01 23:40:34 +08:00
c67f626b66 Feat: Support re-segmentation (#114)
Co-authored-by: John Wang <takatost@gmail.com>
Co-authored-by: Jyong <718720800@qq.com>
Co-authored-by: 金伟强 <iamjoel007@gmail.com>
2023-06-01 23:19:36 +08:00
f65a3ad1cc Feature/replace default icon in overview (#279) 2023-06-01 13:06:56 +08:00
490858a4d5 feat: auto rule generator (#273) 2023-05-31 22:03:15 +08:00
44a1aa5e44 fix: dataset_tool npe (#274) 2023-05-31 17:16:27 +08:00
a616bf3129 Fix/long more suggestion not see all (#272) 2023-05-31 17:09:55 +08:00
f2f19484b8 fix: text generation too long hide the operation btn (#271) 2023-05-31 16:24:30 +08:00
f572b55237 chore: link prefetch deprecated. Remove warning message. (#270) 2023-05-31 14:56:14 +08:00
554570dc22 feat: feature support UI preview (#269) 2023-05-31 14:10:59 +08:00
5239b2c7ab Feat/dashboard more chart (#266) 2023-05-31 11:21:30 +08:00
ae94b067b3 feat: new stats (#265) 2023-05-31 11:20:24 +08:00
5e772bd10b fix: stop response btn hide messages (#261) 2023-05-30 16:15:08 +08:00
91bcbd0b26 fix: svg attr in ts file (#260) 2023-05-30 15:26:26 +08:00
54bb309d87 fix: remove sentry for community edtion and dev (#259) 2023-05-30 15:09:25 +08:00
75f7a96025 feat: ignore validate failed error log (#256) 2023-05-30 12:25:42 +08:00
ccd80653ff fix: query empty not allow (#255) 2023-05-30 12:24:51 +08:00
5ca88a4fd9 fix: raw json parse in llm router chain (#254) 2023-05-30 12:16:45 +08:00
a1c6cecf10 feat: bump to 0.3.1 (#253) 2023-05-30 11:31:22 +08:00
c5ccf382df chore: input area highlight and moblie hide tooltip (#251) 2023-05-30 11:16:31 +08:00
8358d0abfa fix: config file lint error (#250) 2023-05-30 10:32:26 +08:00
bad3b14438 fix: member invite text (#249) 2023-05-30 09:59:05 +08:00
f42ef494f8 Fix: correct links in app list (#248) 2023-05-30 08:08:33 +08:00
bb7f454ecd fix: dataset desc npe (#246) 2023-05-29 19:56:36 +08:00
7f48fadd41 fix: prompt template parantheses select error (#244) 2023-05-29 19:10:31 +08:00
af2138e8b8 fix: json parse in router chain output (#243) 2023-05-29 18:25:01 +08:00
091beffae7 feat: add code style (#242) 2023-05-29 17:49:01 +08:00
408fb502a1 fix: no var text still show split line (#239) 2023-05-29 14:35:21 +08:00
7660539689 fix: markdown code always show scrollbar (#237) 2023-05-29 14:05:59 +08:00
5a6061ff61 chore: handle sentry warning (#236) 2023-05-29 13:58:32 +08:00
970950e3a8 feat: support select multi datasets (#235) 2023-05-29 13:52:56 +08:00
431b2fd4a8 Feat: add sentry (#234) 2023-05-29 11:38:24 +08:00
88545184be feat: support multi datasets router chain mode (#231) 2023-05-28 22:44:54 +08:00
2c23caacd4 fix: introduction key error (#221) 2023-05-26 20:49:38 +08:00
9edea9bc49 fix: one chinese character cost token nums (#219) 2023-05-26 16:24:59 +08:00
d43279a1cc fix: robot emoji (#217) 2023-05-26 15:26:56 +08:00
10848d74a0 fix: changelog link (#216) 2023-05-26 10:22:35 +08:00
f9df23a091 fix: default icon (#213) 2023-05-26 09:55:37 +08:00
17a1c05728 fix: var highlight problme (#214) 2023-05-25 23:38:06 +08:00
66782ef19c chore: title support i18n (#212) 2023-05-25 22:13:43 +08:00
fb7f509e5c chore: show explore entrance (#211) 2023-05-25 21:49:12 +08:00
1a5acf43aa Fix/shared lock (#210) 2023-05-25 21:31:11 +08:00
4ef6392de5 feat: bump version to 0.3.0 (#207) 2023-05-25 20:48:47 +08:00
effdc824d9 feat: remove image sha- prefix in image tag (#206) 2023-05-25 20:33:04 +08:00
24fa452307 fix: image sha tag not push (#205) 2023-05-25 20:24:50 +08:00
9e00e3894e Feat/add release action build (#204) 2023-05-25 20:17:17 +08:00
023783372e feat: explore support multi language (#202) 2023-05-25 18:53:28 +08:00
1d06eba61a fix: prompt and preview not show html like tag (#201) 2023-05-25 18:42:42 +08:00
93e99fb343 feat: generation support gpt4 (#200) 2023-05-25 18:15:57 +08:00
b9ebce7ab7 fix: emoji picker in safari (#199) 2023-05-25 17:43:41 +08:00
33b3eaf324 Feat/explore (#198) 2023-05-25 16:59:47 +08:00
b6cca59517 fix: update recommend app params error (#197) 2023-05-25 16:01:41 +08:00
93ae18ea12 Feat: explore apps (#196) 2023-05-25 15:54:45 +08:00
99f7e4f277 fix: provider token validate (#195) 2023-05-25 13:27:27 +08:00
659c3e7a81 fix: nav ui bug (#191)
Co-authored-by: yuhao1118 <yuhao1118@bytedance.net>
2023-05-25 13:01:09 +08:00
7a16c88092 fix: php sdk error code (#179) 2023-05-24 21:05:05 +08:00
0bb253efe0 fix: providererror message when token validated fail (#190) 2023-05-24 19:50:14 +08:00
d93365d429 fix: azure embedding not support batch (#188) 2023-05-24 18:55:07 +08:00
8b44dba988 fix: api key copy fail (#186) 2023-05-24 16:11:25 +08:00
d96bcfa4ee fix: dataset setting (#183) 2023-05-24 14:20:21 +08:00
380b4b3ddc fix: refresh list on delete (#178) 2023-05-23 23:06:16 +08:00
e2bf18053c Fix/dateset update rule (#177) 2023-05-23 22:54:59 +08:00
4350bb9a00 Fix/human in answer (#174) 2023-05-23 19:54:04 +08:00
fe688b505a feat: support disable version check (#173) 2023-05-23 17:34:48 +08:00
056898bf21 fix: quota update error on azure openai (#172) 2023-05-23 16:16:22 +08:00
0e8afa3aa2 Feat/add ph (#171) 2023-05-23 16:05:05 +08:00
933bd06460 feat: add ph (#169) 2023-05-23 15:34:55 +08:00
b939039201 feat: add product hunt (#167) 2023-05-23 15:23:07 +08:00
6da5e54180 Feat/open azure validate (#163) 2023-05-23 14:16:26 +08:00
1c5f63de7e fix: azure-openai key validate (#164) 2023-05-23 14:15:33 +08:00
f3219ff107 fix: template string in template error (#162) 2023-05-23 13:16:33 +08:00
219011b62a fix: disable template string in query (#160) 2023-05-23 12:57:26 +08:00
90150a6ca9 Feat/optimize chat prompt (#158) 2023-05-23 12:26:28 +08:00
7722a7c5cd fix: bootstrap env (#127)
Co-authored-by: yuhao1118 <yuhao1118@bytedance.net>
2023-05-23 10:48:03 +08:00
4ba38465ac fix: dark-theme-btn-selected (#156) 2023-05-23 10:43:38 +08:00
9a5ae9f51f Feat: optimize error desc (#152) 2023-05-22 17:39:28 +08:00
a7c40a07d8 fix: seg no blank break ui (#150) 2023-05-22 17:22:28 +08:00
2d0d3365ed fix: buffer not return event show errors (#149) 2023-05-22 16:05:08 +08:00
54a6571462 fix: extra input for opening statement was not suitable for prompt (#143) 2023-05-22 14:32:22 +08:00
c43c3098a0 Update issue templates (#142) 2023-05-22 13:13:04 +08:00
eddd038959 Update issue templates (#140) 2023-05-22 13:01:46 +08:00
7a2291f450 fix: more than 6th options would be hide (#136) 2023-05-22 11:25:40 +08:00
17a8118154 fix: email reg (#135) 2023-05-22 10:39:51 +08:00
4db01403ae feat: add missing i18n (#130) 2023-05-22 10:12:17 +08:00
d8425f3f4c Fix the email validation problem for a.b@c.club. (#94)
Co-authored-by: yyzhang <yuanyuan.zhang@haochezhu.club>
2023-05-22 10:08:26 +08:00
38754734a2 Fix:style of new line (#134) 2023-05-22 09:09:53 +08:00
b42cd38cc9 fix: internal error when user is none in service api call (#129) 2023-05-21 17:29:47 +08:00
c6f715861a Fix: event listener of file dropping (#113) 2023-05-21 17:22:35 +08:00
b46511dd7b fix: emoji-picker-z-index (#125)
Co-authored-by: yuhao1118 <yuhao1118@bytedance.net>
2023-05-21 17:21:01 +08:00
e8e8f9e97d Fix: move pre prompt to user massasge in chat mode (#126) 2023-05-21 17:06:04 +08:00
18d1f6a6c6 fix: chat res table or code is very long caused ui problem (#124) 2023-05-21 16:27:24 +08:00
1b6e3ef964 Feat: optimize inner prompt (#121) 2023-05-21 11:29:10 +08:00
4779fcf6f1 feature: infinite scroll (#119)
Add infinite scroll support to app list and dataset list.
2023-05-20 21:55:47 +08:00
e8239ae631 feat: add celery document (#118) 2023-05-20 21:26:07 +08:00
94eb2a623e fix: fix chat res no blank too long caused ui problem (#116) 2023-05-20 17:19:39 +08:00
96809108ca fix: locale match error (#115) 2023-05-20 17:12:12 +08:00
8fc2663693 fix: weaviate batch insert timeout (#108) 2023-05-19 21:57:32 +08:00
37c3b8979c Feature/add emoji (#103) 2023-05-19 17:36:44 +08:00
f68b05d5ec Feat: support azure openai for temporary (#101) 2023-05-19 13:24:45 +08:00
3b3c604eb5 Add Japanese Documents (#96) 2023-05-18 23:45:38 +08:00
a43ef7a926 Feature/remove mock server (#88) 2023-05-18 10:50:34 +08:00
c6ba67a770 add a config to disable provider config validation (#85) 2023-05-18 08:25:37 +08:00
ac2a1bc954 fix: chat log overflow style upgrade (#87)
Co-authored-by: llx_changed <xi.liu@goodwe.com>
2023-05-18 00:11:17 +08:00
a4481a3f29 fix: prompt no blank too long break ui (#81) 2023-05-17 21:50:42 +08:00
15f932573a fix: settings modal (#74) 2023-05-17 19:05:51 +08:00
f8eefa31fe feat: add redis ssl support (#65) 2023-05-17 15:40:21 +08:00
0587ff0fba fix: remove empty segment in splitter (#68) 2023-05-17 15:02:58 +08:00
ce492d13f1 feat: gpt4 max token set to 8k (#67) 2023-05-17 14:53:15 +08:00
74d954610f Feat/support copy apikey and chat message (#62) 2023-05-17 11:22:25 +08:00
0abee44453 fix up typo (#57) 2023-05-16 22:58:46 +08:00
157cb2e048 feat: remove unnecessary workflow in pr (#58) 2023-05-16 22:58:13 +08:00
a4713c01d5 fix: remove v1 in app_base_url (#55) 2023-05-16 22:41:45 +08:00
8847bb1e45 Feat/optimize install wildcard support (#53) 2023-05-16 22:01:29 +08:00
5fcd5c2499 fix: spend time and token (#47) 2023-05-16 16:52:03 +08:00
d680fca996 fix: provider_response_latency type error (#45) 2023-05-16 16:51:39 +08:00
92fb4ab4c1 fix: help document link (#42) 2023-05-16 14:44:24 +08:00
815f794eef feat: optimize split rule when use custom split segment identifier (#35) 2023-05-16 12:57:25 +08:00
3117619ef3 Feature/add test to nodejs sdk (#31) 2023-05-16 09:22:47 +08:00
f5b2271c8c fix: import wrong user (#32) 2023-05-15 23:30:58 +08:00
a8155cba7e feat: exclude full storage folder instead of only priv folder in storage (#28) 2023-05-15 19:26:50 +08:00
0eca93ebd1 feat: CORS and cookie policies have been relaxed. (#23) 2023-05-15 17:33:35 +08:00
d8a716d857 fix: api and worker service volumes mount error (#21) 2023-05-15 16:57:50 +08:00
c2e7fe107a fix: nodejs endpoint (#20) 2023-05-15 16:57:05 +08:00
805da40b15 Update README_CN.md (#18) 2023-05-15 16:52:51 +08:00
4cfee55ec6 Update README.md (#17) 2023-05-15 16:52:27 +08:00
bcbdbed352 feat: Instructions for the initialization installation process after … (#11) 2023-05-15 13:49:34 +08:00
2e1cd3db28 fix: uuid-ossp extension create failed in pgsql (#10) 2023-05-15 12:03:08 +08:00
19eaf27126 fix: lodash package rename (#9)
Co-authored-by: Joel
2023-05-15 11:48:46 +08:00
4926a0fcb1 feat: remove unuseful flake8 (#7) 2023-05-15 11:28:29 +08:00
58db0fac36 fix: Corrected domain from http://dify.ai to https://dify.ai (#6) 2023-05-15 11:20:32 +08:00
367ef145d6 fix: Fix symbol errors in the nodejs-client's README.md file of the SDK (#3) 2023-05-15 11:20:12 +08:00
812 changed files with 34968 additions and 10079 deletions

View File

@ -0,0 +1,32 @@
---
name: "\U0001F41B Bug report"
about: Create a report to help us improve
title: ''
labels: bug
assignees: ''
---
<!--
Please provide a clear and concise description of what the bug is. Include
screenshots if needed. Please test using the latest version of the relevant
Dify packages to make sure your issue has not already been fixed.
-->
Dify version: Cloud | Self Host
## Steps To Reproduce
<!--
Your bug will get fixed much faster if we can run your code and it doesn't
have dependencies other than Dify. Issues without reproduction steps or
code examples may be immediately closed as not actionable.
-->
1.
2.
## The current behavior
## The expected behavior

View File

@ -0,0 +1,20 @@
---
name: "\U0001F680 Feature request"
about: Suggest an idea for this project
title: ''
labels: enhancement
assignees: ''
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context or screenshots about the feature request here.

View File

@ -0,0 +1,10 @@
---
name: "\U0001F914 Questions and Help"
about: Ask a usage or consultation question
title: ''
labels: ''
assignees: ''
---

View File

@ -1,61 +0,0 @@
#!/usr/bin/env bash
set -eo pipefail
SHA=$(git rev-parse HEAD)
REPO_NAME=langgenius/dify
API_REPO_NAME="${REPO_NAME}-api"
if [[ "${GITHUB_EVENT_NAME}" == "pull_request" ]]; then
REFSPEC=$(echo "${GITHUB_HEAD_REF}" | sed 's/[^a-zA-Z0-9]/-/g' | head -c 40)
PR_NUM=$(echo "${GITHUB_REF}" | sed 's:refs/pull/::' | sed 's:/merge::')
LATEST_TAG="pr-${PR_NUM}"
CACHE_FROM_TAG="latest"
elif [[ "${GITHUB_EVENT_NAME}" == "release" ]]; then
REFSPEC=$(echo "${GITHUB_REF}" | sed 's:refs/tags/::' | head -c 40)
LATEST_TAG="${REFSPEC}"
CACHE_FROM_TAG="latest"
else
REFSPEC=$(echo "${GITHUB_REF}" | sed 's:refs/heads/::' | sed 's/[^a-zA-Z0-9]/-/g' | head -c 40)
LATEST_TAG="${REFSPEC}"
CACHE_FROM_TAG="${REFSPEC}"
fi
if [[ "${REFSPEC}" == "main" ]]; then
LATEST_TAG="latest"
CACHE_FROM_TAG="latest"
fi
echo "Pulling cache image ${API_REPO_NAME}:${CACHE_FROM_TAG}"
if docker pull "${API_REPO_NAME}:${CACHE_FROM_TAG}"; then
API_CACHE_FROM_SCRIPT="--cache-from ${API_REPO_NAME}:${CACHE_FROM_TAG}"
else
echo "WARNING: Failed to pull ${API_REPO_NAME}:${CACHE_FROM_TAG}, disable build image cache."
API_CACHE_FROM_SCRIPT=""
fi
cat<<EOF
Rolling with tags:
- ${API_REPO_NAME}:${SHA}
- ${API_REPO_NAME}:${REFSPEC}
- ${API_REPO_NAME}:${LATEST_TAG}
EOF
#
# Build image
#
cd api
docker build \
${API_CACHE_FROM_SCRIPT} \
--build-arg COMMIT_SHA=${SHA} \
-t "${API_REPO_NAME}:${SHA}" \
-t "${API_REPO_NAME}:${REFSPEC}" \
-t "${API_REPO_NAME}:${LATEST_TAG}" \
--label "sha=${SHA}" \
--label "built_at=$(date)" \
--label "build_actor=${GITHUB_ACTOR}" \
.
# push
docker push --all-tags "${API_REPO_NAME}"

View File

@ -5,18 +5,19 @@ on:
branches:
- 'main'
- 'deploy/dev'
pull_request:
types: [synchronize, opened, reopened, ready_for_review]
release:
types: [published]
jobs:
build-and-push:
runs-on: ubuntu-latest
if: github.event.pull_request.draft == false
steps:
- name: "Checkout ${{ github.ref }} ( ${{ github.sha }} )"
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Login to Docker Hub
uses: docker/login-action@v2
@ -24,13 +25,29 @@ jobs:
username: ${{ secrets.DOCKERHUB_USER }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build and push Docker image
shell: bash
env:
DOCKERHUB_USER: ${{ secrets.DOCKERHUB_USER }}
DOCKERHUB_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}
run: |
/bin/bash .github/workflows/build-api-image.sh
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@v4
with:
images: langgenius/dify-api
tags: |
type=raw,value=latest,enable={{is_default_branch}}
type=ref,event=branch
type=sha,enable=true,priority=100,prefix=,suffix=,format=long
type=semver,pattern={{major}}.{{minor}}.{{patch}}
type=semver,pattern={{major}}.{{minor}}
type=semver,pattern={{major}}
- name: Build and push
uses: docker/build-push-action@v4
with:
context: "{{defaultContext}}:api"
platforms: linux/amd64,linux/arm64
build-args: |
COMMIT_SHA=${{ fromJSON(steps.meta.outputs.json).labels['org.opencontainers.image.revision'] }}
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Deploy to server
if: github.ref == 'refs/heads/deploy/dev'

View File

@ -1,60 +0,0 @@
#!/usr/bin/env bash
set -eo pipefail
SHA=$(git rev-parse HEAD)
REPO_NAME=langgenius/dify
WEB_REPO_NAME="${REPO_NAME}-web"
if [[ "${GITHUB_EVENT_NAME}" == "pull_request" ]]; then
REFSPEC=$(echo "${GITHUB_HEAD_REF}" | sed 's/[^a-zA-Z0-9]/-/g' | head -c 40)
PR_NUM=$(echo "${GITHUB_REF}" | sed 's:refs/pull/::' | sed 's:/merge::')
LATEST_TAG="pr-${PR_NUM}"
CACHE_FROM_TAG="latest"
elif [[ "${GITHUB_EVENT_NAME}" == "release" ]]; then
REFSPEC=$(echo "${GITHUB_REF}" | sed 's:refs/tags/::' | head -c 40)
LATEST_TAG="${REFSPEC}"
CACHE_FROM_TAG="latest"
else
REFSPEC=$(echo "${GITHUB_REF}" | sed 's:refs/heads/::' | sed 's/[^a-zA-Z0-9]/-/g' | head -c 40)
LATEST_TAG="${REFSPEC}"
CACHE_FROM_TAG="${REFSPEC}"
fi
if [[ "${REFSPEC}" == "main" ]]; then
LATEST_TAG="latest"
CACHE_FROM_TAG="latest"
fi
echo "Pulling cache image ${WEB_REPO_NAME}:${CACHE_FROM_TAG}"
if docker pull "${WEB_REPO_NAME}:${CACHE_FROM_TAG}"; then
WEB_CACHE_FROM_SCRIPT="--cache-from ${WEB_REPO_NAME}:${CACHE_FROM_TAG}"
else
echo "WARNING: Failed to pull ${WEB_REPO_NAME}:${CACHE_FROM_TAG}, disable build image cache."
WEB_CACHE_FROM_SCRIPT=""
fi
cat<<EOF
Rolling with tags:
- ${WEB_REPO_NAME}:${SHA}
- ${WEB_REPO_NAME}:${REFSPEC}
- ${WEB_REPO_NAME}:${LATEST_TAG}
EOF
#
# Build image
#
cd web
docker build \
${WEB_CACHE_FROM_SCRIPT} \
--build-arg COMMIT_SHA=${SHA} \
-t "${WEB_REPO_NAME}:${SHA}" \
-t "${WEB_REPO_NAME}:${REFSPEC}" \
-t "${WEB_REPO_NAME}:${LATEST_TAG}" \
--label "sha=${SHA}" \
--label "built_at=$(date)" \
--label "build_actor=${GITHUB_ACTOR}" \
.
docker push --all-tags "${WEB_REPO_NAME}"

View File

@ -5,18 +5,19 @@ on:
branches:
- 'main'
- 'deploy/dev'
pull_request:
types: [synchronize, opened, reopened, ready_for_review]
release:
types: [published]
jobs:
build-and-push:
runs-on: ubuntu-latest
if: github.event.pull_request.draft == false
steps:
- name: "Checkout ${{ github.ref }} ( ${{ github.sha }} )"
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Login to Docker Hub
uses: docker/login-action@v2
@ -24,13 +25,29 @@ jobs:
username: ${{ secrets.DOCKERHUB_USER }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build and push Docker image
shell: bash
env:
DOCKERHUB_USER: ${{ secrets.DOCKERHUB_USER }}
DOCKERHUB_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}
run: |
/bin/bash .github/workflows/build-web-image.sh
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@v4
with:
images: langgenius/dify-web
tags: |
type=raw,value=latest,enable={{is_default_branch}}
type=ref,event=branch
type=sha,enable=true,priority=100,prefix=,suffix=,format=long
type=semver,pattern={{major}}.{{minor}}.{{patch}}
type=semver,pattern={{major}}.{{minor}}
type=semver,pattern={{major}}
- name: Build and push
uses: docker/build-push-action@v4
with:
context: "{{defaultContext}}:web"
platforms: linux/amd64,linux/arm64
build-args: |
COMMIT_SHA=${{ fromJSON(steps.meta.outputs.json).labels['org.opencontainers.image.revision'] }}
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Deploy to server
if: github.ref == 'refs/heads/deploy/dev'

View File

@ -19,7 +19,7 @@ def check_file_for_chinese_comments(file_path):
def main():
has_chinese = False
excluded_files = ["model_template.py", 'stopwords.py', 'commands.py', 'indexing_runner.py']
excluded_files = ["model_template.py", 'stopwords.py', 'commands.py', 'indexing_runner.py', 'web_reader_tool.py']
for root, _, files in os.walk("."):
for file in files:

View File

@ -1,19 +0,0 @@
name: PEP8 Check
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
pep8:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python 3.10
uses: actions/setup-python@v4
with:
python-version: '3.10'
- name: Install flake8
run: pip install flake8
- name: Run flake8
run: flake8 --ignore=E501 .

30
.github/workflows/stale.yml vendored Normal file
View File

@ -0,0 +1,30 @@
# This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
#
# You can adjust the behavior by modifying this file.
# For more information, see:
# https://github.com/actions/stale
name: Mark stale issues and pull requests
on:
schedule:
- cron: '0 3 * * *'
jobs:
stale:
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/stale@v5
with:
days-before-issue-stale: 30
days-before-issue-close: 3
repo-token: ${{ secrets.GITHUB_TOKEN }}
stale-issue-message: "Close due to it's no longer active, if you have any questions, you can reopen it."
stale-pr-message: "Close due to it's no longer active, if you have any questions, you can reopen it."
stale-issue-label: 'no-issue-activity'
stale-pr-label: 'no-pr-activity'
any-of-labels: 'duplicate,question,invalid,wontfix,no-issue-activity,no-pr-activity,enhancement'

7
.gitignore vendored
View File

@ -109,6 +109,7 @@ venv/
ENV/
env.bak/
venv.bak/
.conda/
# Spyder project settings
.spyderproject
@ -130,7 +131,7 @@ dmypy.json
.idea/'
.DS_Store
.vscode
web/.vscode/settings.json
# Intellij IDEA Files
.idea/
@ -139,7 +140,7 @@ dmypy.json
api/.env
api/storage/*
docker/volumes/app/storage/privkeys/*
docker/volumes/app/storage/*
docker/volumes/db/data/*
docker/volumes/redis/data/*
docker/volumes/weaviate/*
@ -147,3 +148,5 @@ docker/volumes/weaviate/*
sdks/python-client/build
sdks/python-client/dist
sdks/python-client/dify_client.egg-info
.vscode/

View File

@ -22,14 +22,14 @@ To set up a working development environment, just fork the project git repositor
### Fork the repository
you need to fork the [repository](https://github.com/langgenius/langgenius-gateway).
you need to fork the [repository](https://github.com/langgenius/dify).
### Clone the repo
Clone your GitHub forked repository:
```
git clone git@github.com:<github_username>/langgenius-gateway.git
git clone git@github.com:<github_username>/dify.git
```
### Install backend
@ -54,3 +54,8 @@ Did you have an issue, like a merge conflict, or don't know how to open a pull r
## Community channels
Stuck somewhere? Have any questions? Join the [Discord Community Server](https://discord.gg/AhzKf7dNgk). We are here to help!
### i18n (Internationalization) Support
We are looking for contributors to help with translations in other languages. If you are interested in helping, please join the [Discord Community Server](https://discord.gg/AhzKf7dNgk) and let us know.
Also check out the [Frontend i18n README]((web/i18n/README_EN.md)) for more information.

View File

@ -51,3 +51,7 @@ git clone git@github.com:<github_username>/dify.git
## 社区渠道
遇到困难了吗?有任何问题吗? 加入 [Discord Community Server](https://discord.gg/AhzKf7dNgk),我们将为您提供帮助。
### 多语言支持
需要参与贡献翻译内容,请参阅[前端多语言翻译 README](web/i18n/README_CN.md)。

55
CONTRIBUTING_JA.md Normal file
View File

@ -0,0 +1,55 @@
# コントリビュート
[Dify](https://dify.ai) に興味を持ち、貢献したいと思うようになったことに感謝します!始める前に、
[行動規範](https://github.com/langgenius/.github/blob/main/CODE_OF_CONDUCT.md)を読み、
[既存の問題](https://github.com/langgenius/langgenius-gateway/issues)をチェックしてください。
本ドキュメントは、[Dify](https://dify.ai) をビルドしてテストするための開発環境の構築方法を説明するものです。
### 依存関係のインストール
[Dify](https://dify.ai)をビルドするには、お使いのマシンに以下の依存関係をインストールし、設定する必要があります:
- [Git](http://git-scm.com/)
- [Docker](https://www.docker.com/)
- [Docker Compose](https://docs.docker.com/compose/install/)
- [Node.js v18.x (LTS)](http://nodejs.org)
- [npm](https://www.npmjs.com/) バージョン 8.x.x もしくは [Yarn](https://yarnpkg.com/)
- [Python](https://www.python.org/) バージョン 3.10.x
## ローカル開発
開発環境を構築するには、プロジェクトの git リポジトリをフォークし、適切なパッケージマネージャを使用してバックエンドとフロントエンドの依存関係をインストールし、docker-compose スタックを実行するように作成します。
### リポジトリのフォーク
[リポジトリ](https://github.com/langgenius/dify) をフォークする必要があります。
### リポジトリのクローン
GitHub でフォークしたリポジトリのクローンを作成する:
```
git clone git@github.com:<github_username>/dify.git
```
### バックエンドのインストール
バックエンドアプリケーションのインストール方法については、[Backend README](api/README.md) を参照してください。
### フロントエンドのインストール
フロントエンドアプリケーションのインストール方法については、[Frontend README](web/README.md) を参照してください。
### ブラウザで dify にアクセス
[Dify](https://dify.ai) をローカル環境で見ることができるようになりました [http://localhost:3000](http://localhost:3000)。
## プルリクエストの作成
変更後、プルリクエスト (PR) をオープンしてください。プルリクエストを提出すると、Dify チーム/コミュニティの他の人があなたと一緒にそれをレビューします。
マージコンフリクトなどの問題が発生したり、プルリクエストの開き方がわからなくなったりしませんでしたか? [GitHub's pull request tutorial](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests) で、マージコンフリクトやその他の問題を解決する方法をチェックしてみてください。あなたの PR がマージされると、[コントリビュータチャート](https://github.com/langgenius/langgenius-gateway/graphs/contributors)にコントリビュータとして誇らしげに掲載されます。
## コミュニティチャンネル
お困りですか?何か質問がありますか? [Discord Community サーバ](https://discord.gg/AhzKf7dNgk)に参加してください。私たちがお手伝いします!

View File

@ -1,10 +1,12 @@
![](./images/describe-en.png)
<p align="center">
<a href="./README.md">English</a> |
<a href="./README_CN.md">简体中文</a>
<a href="./README_CN.md">简体中文</a> |
<a href="./README_JA.md">日本語</a> |
<a href="./README_ES.md">Español</a>
</p>
[Website](http://dify.ai) • [Docs](https://docs.dify.ai) • [Twitter](https://twitter.com/dify_ai)
[Website](https://dify.ai) • [Docs](https://docs.dify.ai) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
**Dify** is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement.
@ -15,13 +17,19 @@ A single API encompassing plugin capabilities, context enhancement, and more, sa
Visual data analysis, log review, and annotation for applications
Dify is compatible with Langchain, meaning we'll gradually support multiple LLMs, currently supported:
- GPT 3 (text-davinci-003)
- GPT 3.5 Turbo(ChatGPT)
- GPT-4
* **OpenAI** GPT4、GPT3.5-turbo、GPT3.5-turbo-16k、text-davinci-003
* **Azure OpenAI**
* **Antropic**Claude2、Claude-instant
> We've got 1000 free trial credits available for all cloud service users to try out the Claude model.Visit [Dify.ai](https://dify.ai) and
try it now.
* **hugging face Hub**Coming soon.
## Use Cloud Services
Visit [Dify.ai](http://dify.ai)
Visit [Dify.ai](https://dify.ai)
## Install the Community Edition
@ -38,10 +46,15 @@ The easiest way to start the Dify server is to run our [docker-compose.yml](dock
```bash
cd docker
docker-compose up -d
docker compose up -d
```
After running, you can access the Dify console in your browser at [http://localhost](http://localhost) and start the initialization operation.
After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization installation process.
### Helm Chart
A big thanks to @BorisPolonsky for providing us with a [Helm Chart](https://helm.sh/) version, which allows Dify to be deployed on Kubernetes.
You can go to https://github.com/BorisPolonsky/dify-helm for deployment information.
### Configuration
@ -81,22 +94,42 @@ A: English and Chinese are currently supported, and you can contribute language
[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
## Contributing
We welcome you to contribute to Dify to help make Dify better. We welcome contributions in various ways, submitting code, issues, new ideas, or sharing the interesting and useful AI applications you have created based on Dify. At the same time, we also welcome you to share Dify at different events, conferences, and social media.
### Submit a Pull Request
To ensure proper review, all code contributions, including from contributors with direct commit access, must be submitted as PR requests and approved by core developers before merging branches.
We welcome PRs from everyone! If you're willing to help out, you can learn more about how to contribute code to the project in the [Contribution Guide](CONTRIBUTING.md).
### Submit issues or ideas
You can submit your issues or ideas by adding issues to the Dify repository. If you encounter issues, please describe the steps you took to encounter the issue as much as possible so we can better discover it. If you have any new ideas for our product, we also welcome your feedback. Please share your insights as much as possible so we can get more feedback and further discussion in the community.
### Share your applications
We encourage all community members to share their AI applications built on Dify, which can be applied to different scenarios or different users. This will provide powerful inspiration for people who want to create AI capabilities! You can share your experience by [submitting an issue in the Dify-user-case repository](https://github.com/langgenius/dify-user-case/issues).
### Share Dify with others
We encourage community contributors to actively demonstrate different aspects of using Dify. You can talk or share any feature of using Dify at meetups and conferences, blogs or social media. We believe your unique sharing will be of great help to others! Mention @Dify.AI on Twitter and/or communicate on [Discord](https://discord.gg/FngNHpbcY7) so we can give pointers and tips and help you spread the word by promoting your content on the different Dify communication channels.
### Help others
You can also help people in need of help on Discord, GitHub issues or other social platforms, guide others to solve problems encountered during use and share usage experiences. This is also a great contribution! If you want to become a maintainer of the Dify community, please contact the official team via [Discord](https://discord.gg/FngNHpbcY7) or email us at support@dify.ai.
## Contact Us
If you have any questions, suggestions, or partnership inquiries, feel free to contact us through the following channels:
- Submit an Issue or PR on our GitHub Repo
- Join the discussion in our [Discord](https://discord.gg/AhzKf7dNgk) Community
- Join the discussion in our [Discord](https://discord.gg/FngNHpbcY7) Community
- Send an email to hello@dify.ai
We're eager to assist you and together create more fun and useful AI applications!
## Contributing
To ensure proper review, all code contributions - including those from contributors with direct commit access - must be submitted via pull requests and approved by the core development team prior to being merged.
We welcome all pull requests! If you'd like to help, check out the [Contribution Guide](CONTRIBUTING.md) for more information on how to get started.
## Security
To protect your privacy, please avoid posting security issues on GitHub. Instead, send your questions to security@dify.ai and we will provide you with a more detailed answer.

View File

@ -1,11 +1,13 @@
![](./images/describe-cn.jpg)
<p align="center">
<a href="./README.md">English</a> |
<a href="./README_CN.md">简体中文</a>
<a href="./README_CN.md">简体中文</a> |
<a href="./README_JA.md">日本語</a> |
<a href="./README_ES.md">Español</a>
</p>
[官方网站](http://dify.ai) • [文档](https://docs.dify.ai/v/zh-hans) • [Twitter](https://twitter.com/dify_ai)
[官方网站](https://dify.ai) • [文档](https://docs.dify.ai/v/zh-hans) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
**Dify** 是一个易用的 LLMOps 平台,旨在让更多人可以创建可持续运营的原生 AI 应用。Dify 提供多种类型应用的可视化编排,应用可开箱即用,也能以“后端即服务”的 API 提供服务。
@ -15,15 +17,20 @@
- 一套 API 即可包含插件、上下文增强等能力,替你省下了后端代码的编写工作
- 可视化的对应用进行数据分析,查阅日志或进行标注
Dify 兼容 Langchain这意味着我们将逐步支持多种 LLMs ,目前支持:
Dify 兼容 Langchain这意味着我们将逐步支持多种 LLMs ,目前支持的模型供应商
- GPT 3 (text-davinci-003)
- GPT 3.5 Turbo(ChatGPT)
- GPT-4
* **OpenAI**GPT4、GPT3.5-turbo、GPT3.5-turbo-16k、text-davinci-003
* **Azure OpenAI Service**
* **Anthropic**Claude2、Claude-instant
> 我们为所有注册云端版的用户免费提供了 1000 次 Claude 模型的消息调用额度,登录 [dify.ai](https://cloud.dify.ai) 即可使用。
* **Hugging Face Hub**(即将推出)
## 使用云服务
访问 [Dify.ai](http://cloud.dify.ai)
访问 [Dify.ai](https://cloud.dify.ai)
## 安装社区版
@ -40,10 +47,15 @@ Dify 兼容 Langchain这意味着我们将逐步支持多种 LLMs ,目前
```bash
cd docker
docker-compose up -d
docker compose up -d
```
运行后,可以在浏览器上访问 [http://localhost](http://localhost) 进入 Dify 控制台并开始初始化操作。
运行后,可以在浏览器上访问 [http://localhost/install](http://localhost/install) 进入 Dify 控制台并开始初始化安装操作。
### Helm Chart
非常感谢 @BorisPolonsky 为我们提供了一个 [Helm Chart](https://helm.sh/) 版本,可以在 Kubernetes 上部署 Dify。
您可以前往 https://github.com/BorisPolonsky/dify-helm 来获取部署信息。
### 配置
@ -82,20 +94,37 @@ A: 现已支持英文与中文,你可以为我们贡献语言包。
[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
## 贡献
我们欢迎你为 Dify 作出贡献帮助 Dify 变得更好。我们欢迎各种方式的贡献,提交代码、问题、新想法、或者分享你基于 Dify 创建出的各种有趣有用的 AI 应用。同时,我们也欢迎你在不同的活动、研讨会、社交媒体上分享 Dify。
### 贡献代码
为了确保正确审查,所有代码贡献 - 包括来自具有直接提交更改权限的贡献者 - 都必须提交 PR 请求并在合并分支之前得到核心开发人员的批准。
我们欢迎所有人提交 PR如果您愿意提供帮助可以在 [贡献指南](CONTRIBUTING_CN.md) 中了解有关如何为项目做出代码贡献的更多信息。
### 提交问题或想法
你可以通过 Dify 代码仓库新增 issues 来提交你的问题或想法。如遇到问题,请尽可能描述你遇到问题的操作步骤,以便我们更好地发现它。如果你对我们的产品有任何新想法,也欢迎向我们反馈,请尽可能多地分享你的见解,以便我们在社区中获得更多反馈和进一步讨论。
### 分享你的应用
我们鼓励所有社区成员分享他们基于 Dify 创造出的 AI 应用,它们可以是应用于不同情景或不同用户,这将有助于为希望基于 AI 能力创造的人们提供强大灵感!你可以通过 [Dify-user-case 仓库项目提交 issue](https://github.com/langgenius/dify-user-case) 来分享你的应用案例。
### 向别人分享 Dify
我们鼓励社区贡献者们积极展示你使用 Dify 的不同角度。你可以通过线下研讨会、博客或社交媒体上谈论或分享你使用 Dify 的任意功能,相信你独特的使用分享会给别人带来非常大的帮助!如果你需要任何指导帮助,欢迎联系我们 support@dify.ai ,你也可以在 twitter @Dify.AI 或在 [Discord 社区](https://discord.gg/FngNHpbcY7)交流来帮助你传播信息。
### 帮助别人
你还可以在 Discord、GitHub issues或其他社交平台上帮助需要帮助的人指导别人解决使用过程中遇到的问题和分享使用经验。这也是个非常了不起的贡献如果你希望成为 Dify 社区的维护者,请通过[Discord 社区](https://discord.gg/FngNHpbcY7) 联系官方团队或邮件联系我们 support@dify.ai.
## 联系我们
如果您有任何问题、建议或合作意向,欢迎通过以下方式联系我们:
- 在我们的 [GitHub Repo](https://github.com/langgenius/dify) 上提交 Issue 或 PR
- 在我们的 [Discord 社区](https://discord.gg/AhzKf7dNgk) 上加入讨论
- 在我们的 [Discord 社区](https://discord.gg/FngNHpbcY7) 上加入讨论
- 发送邮件至 hello@dify.ai
## 贡献代码
为了确保正确审查,所有代码贡献 - 包括来自具有直接提交更改权限的贡献者 - 都必须提交 PR 请求并在合并分支之前得到核心开发人员的批准。
我们欢迎所有人提交 PR如果您愿意提供帮助可以在 [贡献指南](CONTRIBUTING_CN.md) 中了解有关如何为项目做出贡献的更多信息。
## 安全
为了保护您的隐私,请避免在 GitHub 上发布安全问题。发送问题至 security@dify.ai我们将为您做更细致的解答。

124
README_ES.md Normal file
View File

@ -0,0 +1,124 @@
![](./images/describe-en.png)
<p align="center">
<a href="./README.md">English</a> |
<a href="./README_CN.md">简体中文</a> |
<a href="./README_JA.md">日本語</a> |
<a href="./README_ES.md">Español</a>
</p>
[Sitio web](https://dify.ai) • [Documentación](https://docs.dify.ai) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
**Dify** es una plataforma LLMOps fácil de usar diseñada para capacitar a más personas para que creen aplicaciones sostenibles basadas en IA. Con orquestación visual para varios tipos de aplicaciones, Dify ofrece aplicaciones listas para usar que también pueden funcionar como APIs de Backend-as-a-Service. Unifica tu proceso de desarrollo con una API para la integración de complementos y conjuntos de datos, y agiliza tus operaciones utilizando una interfaz única para la ingeniería de indicaciones, análisis visual y mejora continua.
Las aplicaciones creadas con Dify incluyen:
- Sitios web listos para usar que admiten el modo de formulario y el modo de conversación por chat.
- Una API única que abarca capacidades de complementos, mejora de contexto y más, lo que te ahorra esfuerzo de programación en el backend.
- Análisis visual de datos, revisión de registros y anotación para aplicaciones.
Dify es compatible con Langchain, lo que significa que gradualmente admitiremos múltiples LLMs, actualmente compatibles con:
- GPT 3 (text-davinci-003)
- GPT 3.5 Turbo (ChatGPT)
- GPT-4
## Usar servicios en la nube
Visita [Dify.ai](https://dify.ai)
## Instalar la Edición Comunitaria
### Requisitos del sistema
Antes de instalar Dify, asegúrate de que tu máquina cumple con los siguientes requisitos mínimos del sistema:
- CPU >= 1 Core
- RAM >= 4GB
### Inicio rápido
La forma más sencilla de iniciar el servidor de Dify es ejecutar nuestro archivo [docker-compose.yml](docker/docker-compose.yaml). Antes de ejecutar el comando de instalación, asegúrate de que [Docker](https://docs.docker.com/get-docker/) y [Docker Compose](https://docs.docker.com/compose/install/) estén instalados en tu máquina:
```bash
cd docker
docker compose up -d
```
Después de ejecutarlo, puedes acceder al panel de control de Dify en tu navegador desde [http://localhost/install](http://localhost/install) y comenzar el proceso de instalación de inicialización.
### Helm Chart
Un gran agradecimiento a @BorisPolonsky por proporcionarnos una versión de [Helm Chart](https://helm.sh/), que permite desplegar Dify en Kubernetes.
Puede ir a https://github.com/BorisPolonsky/dify-helm para obtener información de despliegue.
### Configuración
Si necesitas personalizar la configuración, consulta los comentarios en nuestro archivo [docker-compose.yml](docker/docker-compose.yaml) y configura manualmente la configuración del entorno. Después de realizar los cambios, ejecuta nuevamente 'docker-compose up -d'.
## Hoja de ruta
Funciones en desarrollo:
- **Conjuntos de datos**, admitiendo más conjuntos de datos, por ejemplo, sincronización de contenido desde Notion o páginas web.
Admitiremos más conjuntos de datos, incluidos texto, páginas web e incluso contenido de Notion. Los usuarios pueden construir aplicaciones de IA basadas en sus propias fuentes de datos
- **Complementos**, introduciendo complementos estándar de ChatGPT para aplicaciones, o utilizando complementos producidos por Dify.
Lanzaremos complementos que cumplan con el estándar de ChatGPT, o nuestros propios complementos de Dify para habilitar más capacidades en las aplicaciones.
- **Modelos de código abierto**, por ejemplo, adoptar Llama como proveedor de modelos o para un ajuste adicional.
Trabajaremos con excelentes modelos de código abierto como Llama, proporcionándolos como opciones de modelos en nuestra plataforma o utilizándolos para un ajuste adicional.
## Preguntas y respuestas
**P: ¿Qué puedo hacer con Dify?**
R: Dify es una herramienta de desarrollo y operaciones de LLM, simple pero poderosa. Puedes usarla para construir aplicaciones de calidad comercial y asistentes personales. Si deseas desarrollar tus propias aplicaciones, LangDifyGenius puede ahorrarte trabajo en el backend al integrar con OpenAI y ofrecer capacidades de operaciones visuales, lo que te permite mejorar y entrenar continuamente tu modelo GPT.
**P: ¿Cómo uso Dify para "entrenar" mi propio modelo?**
R: Una aplicación valiosa consta de Ingeniería de indicaciones, mejora de contexto y ajuste fino. Hemos creado un enfoque de programación híbrida que combina las indicaciones con lenguajes de programación (similar a un motor de plantillas), lo que facilita la incorporación de texto largo o la captura de subtítulos de un video de YouTube ingresado por el usuario, todo lo cual se enviará como contexto para que los LLM lo procesen. Damos gran importancia a la operabilidad de la aplicación, con los datos generados por los usuarios durante el uso de la aplicación disponibles para análisis, anotación y entrenamiento continuo. Sin las herramientas adecuadas, estos pasos pueden llevar mucho tiempo.
**P: ¿Qué necesito preparar si quiero crear mi propia aplicación?**
R: Suponemos que ya tienes una clave de API de OpenAI; si no la tienes, por favor regístrate. ¡Si ya tienes contenido que pueda servir como contexto de entrenamiento, eso es genial!
**P: ¿Qué idiomas de interfaz están disponibles?**
R: Actualmente se admiten inglés y chino, y puedes contribuir con paquetes de idiomas.
## Historial de estrellas
[![Gráfico de historial de estrellas](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
## Contáctanos
Si tienes alguna pregunta, sugerencia o consulta sobre asociación, no dudes en contactarnos a través de los siguientes canales:
- Presentar un problema o una solicitud de extracción en nuestro repositorio de GitHub.
- Únete a la discusión en nuestra comunidad de [Discord](https://discord.gg/FngNHpbcY7).
- Envía un correo electrónico a hello@dify.ai.
¡Estamos ansiosos por ayudarte y crear juntos aplicaciones de IA más divertidas y útiles!
## Contribuciones
Para garantizar una revisión adecuada, todas las contribuciones de código, incluidas las de los colaboradores con acceso directo a los compromisos, deben enviarse mediante solicitudes de extracción y ser aprobadas por el equipo principal de
desarrollo antes de fusionarse.
¡Agradecemos todas las solicitudes de extracción! Si deseas ayudar, consulta la [Guía de Contribución](CONTRIBUTING.md) para obtener más información sobre cómo comenzar.
## Seguridad
Para proteger tu privacidad, evita publicar problemas de seguridad en GitHub. En su lugar, envía tus preguntas a security@dify.ai y te proporcionaremos una respuesta más detallada.
## Citación
Este software utiliza el siguiente software de código abierto:
- Chase, H. (2022). LangChain [Software de computadora]. https://github.com/hwchase17/langchain
- Liu, J. (2022). LlamaIndex [Software de computadora]. doi: 10.5281/zenodo.1234.
Para obtener más información, consulta el sitio web oficial o el texto de la licencia del software correspondiente.
## Licencia
Este repositorio está disponible bajo la [Licencia de código abierto de Dify](LICENSE).

123
README_JA.md Normal file
View File

@ -0,0 +1,123 @@
![](./images/describe-en.png)
<p align="center">
<a href="./README.md">English</a> |
<a href="./README_CN.md">简体中文</a> |
<a href="./README_JA.md">日本語</a> |
<a href="./README_ES.md">Español</a>
</p>
[Web サイト](https://dify.ai) • [ドキュメント](https://docs.dify.ai) • [Twitter](https://twitter.com/dify_ai) • [Discord](https://discord.gg/FngNHpbcY7)
**Dify** は、より多くの人々が持続可能な AI ネイティブアプリケーションを作成できるように設計された、使いやすい LLMOps プラットフォームです。様々なアプリケーションタイプに対応したビジュアルオーケストレーションにより Dify は Backend-as-a-Service API としても機能する、すぐに使えるアプリケーションを提供します。プラグインやデータセットを統合するための1つの API で開発プロセスを統一し、プロンプトエンジニアリング、ビジュアル分析、継続的な改善のための1つのインターフェイスを使って業務を合理化します。
Difyで作成したアプリケーションは以下の通りです:
フォームモードとチャット会話モードをサポートする、すぐに使える Web サイト
プラグイン機能、コンテキストの強化などを網羅する単一の API により、バックエンドのコーディングの手間を省きます。
アプリケーションの視覚的なデータ分析、ログレビュー、アノテーションが可能です。
Dify は LangChain と互換性があり、複数の LLM を徐々にサポートします:
- GPT 3 (text-davinci-003)
- GPT 3.5 Turbo(ChatGPT)
- GPT-4
## クラウドサービスの利用
[Dify.ai](https://dify.ai) をご覧ください
## Community Edition のインストール
### システム要件
Dify をインストールする前に、お使いのマシンが以下の最低システム要件を満たしていることを確認してください:
- CPU >= 1 Core
- RAM >= 4GB
### クイックスタート
Dify サーバーを起動する最も簡単な方法は、[docker-compose.yml](docker/docker-compose.yaml) ファイルを実行することです。インストールコマンドを実行する前に、[Docker](https://docs.docker.com/get-docker/) と [Docker Compose](https://docs.docker.com/compose/install/) がお使いのマシンにインストールされていることを確認してください:
```bash
cd docker
docker compose up -d
```
実行後、ブラウザで [http://localhost/install](http://localhost/install) にアクセスし、初期化インストール作業を開始することができます。
### Helm Chart
@BorisPolonsky に大感謝します。彼は Dify を Kubernetes 上にデプロイするための [Helm Chart](https://helm.sh/) バージョンを提供してくれました。
デプロイ情報については、https://github.com/BorisPolonsky/dify-helm をご覧ください。
### 構成
カスタマイズが必要な場合は、[docker-compose.yml](docker/docker-compose.yaml) ファイルのコメントを参照し、手動で環境設定をお願いします。変更後、再度 'docker-compose up -d' を実行してください。
## ロードマップ
開発中の機能:
- **データセット**, Notionやウェブページからのコンテンツ同期など、より多くのデータセットをサポートします
テキスト、ウェブページ、さらには Notion コンテンツなど、より多くのデータセットをサポートする予定です。ユーザーは、自分のデータソースをもとに AI アプリケーションを構築することができます。
- **プラグイン**, アプリケーションに ChatGPT プラグイン標準のプラグインを導入する、または Dify 制作のプラグインを利用する
今後、ChatGPT 規格に準拠したプラグインや、ディファイ独自のプラグインを公開し、より多くの機能をアプリケーションで実現できるようにします。
- **オープンソースモデル**, 例えばモデルプロバイダーとして Llama を採用したり、さらにファインチューニングを行う
Llama のような優れたオープンソースモデルを、私たちのプラットフォームのモデルオプションとして提供したり、さらなる微調整のために使用したりすることで、協力していきます。
## Q&A
**Q: Dify で何ができるのか?**
A: Dify はシンプルでパワフルな LLM 開発・運用ツールです。商用グレードのアプリケーション、パーソナルアシスタントを構築するために使用することができます。独自のアプリケーションを開発したい場合、LangDifyGenius は OpenAI と統合する際のバックエンド作業を省き、視覚的な操作機能を提供し、GPT モデルを継続的に改善・訓練することが可能です。
**Q: Dify を使って、自分のモデルを「トレーニング」するにはどうすればいいのでしょうか?**
A: プロンプトエンジニアリング、コンテキスト拡張、ファインチューニングからなる価値あるアプリケーションです。プロンプトとプログラミング言語を組み合わせたハイブリッドプログラミングアプローチ(テンプレートエンジンのようなもの)で、長文の埋め込みやユーザー入力の YouTube 動画からの字幕取り込みなどを簡単に実現し、これらはすべて LLM が処理するコンテキストとして提出される予定です。また、アプリケーションの操作性を重視し、ユーザーがアプリケーションを使用する際に生成したデータを分析、アノテーション、継続的なトレーニングに利用できるようにしました。適切なツールがなければ、これらのステップに時間がかかることがあります。
**Q: 自分でアプリケーションを作りたい場合、何を準備すればよいですか?**
A: すでに OpenAI API Key をお持ちだと思いますが、お持ちでない場合はご登録ください。もし、すでにトレーニングのコンテキストとなるコンテンツをお持ちでしたら、それは素晴らしいことです!
**Q: インターフェイスにどの言語が使えますか?**
A: 現在、英語と中国語に対応しており、言語パックを寄贈することも可能です。
## Star ヒストリー
[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
## お問合せ
ご質問、ご提案、パートナーシップに関するお問い合わせは、以下のチャンネルからお気軽にご連絡ください:
- GitHub Repo で Issue や PR を提出する
- [Discord](https://discord.gg/FngNHpbcY7) コミュニティで議論に参加する。
- hello@dify.ai にメールを送信します
私たちは、皆様のお手伝いをさせていただき、より楽しく、より便利な AI アプリケーションを一緒に作っていきたいと思っています!
## コントリビュート
適切なレビューを行うため、コミットへの直接アクセスが可能なコントリビュータを含むすべてのコードコントリビュータは、プルリクエストで提出し、マージされる前にコア開発チームによって承認される必要があります。
私たちはすべてのプルリクエストを歓迎します!協力したい方は、[コントリビューションガイド](CONTRIBUTING.md) をチェックしてみてください。
## セキュリティ
プライバシー保護のため、GitHub へのセキュリティ問題の投稿は避けてください。代わりに、あなたの質問を security@dify.ai に送ってください。より詳細な回答を提供します。
## 引用
本ソフトウェアは、以下のオープンソースソフトウェアを使用しています:
- Chase, H. (2022). LangChain [Computer software]. https://github.com/hwchase17/langchain
- Liu, J. (2022). LlamaIndex [Computer software]. doi: 10.5281/zenodo.1234.
詳しくは、各ソフトウェアの公式サイトまたはライセンス文をご参照ください。
## ライセンス
このリポジトリは、[Dify Open Source License](LICENSE) のもとで利用できます。

View File

@ -8,13 +8,19 @@ EDITION=SELF_HOSTED
SECRET_KEY=
# Console API base URL
CONSOLE_URL=http://127.0.0.1:5001
CONSOLE_API_URL=http://127.0.0.1:5001
# Console frontend web base URL
CONSOLE_WEB_URL=http://127.0.0.1:3000
# Service API base URL
API_URL=http://127.0.0.1:5001
SERVICE_API_URL=http://127.0.0.1:5001
# Web APP base URL
APP_URL=http://127.0.0.1:5001
# Web APP API base URL
APP_API_URL=http://127.0.0.1:5001
# Web APP frontend web base URL
APP_WEB_URL=http://127.0.0.1:3000
# celery configuration
CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1
@ -22,6 +28,7 @@ CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1
# redis configuration
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_USERNAME=
REDIS_PASSWORD=difyai123456
REDIS_DB=0
@ -72,14 +79,26 @@ VECTOR_STORE=weaviate
WEAVIATE_ENDPOINT=http://localhost:8080
WEAVIATE_API_KEY=WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih
WEAVIATE_GRPC_ENABLED=false
WEAVIATE_BATCH_SIZE=100
# Qdrant configuration, use `path:` prefix for local mode or `https://your-qdrant-cluster-url.qdrant.io` for remote mode
QDRANT_URL=path:storage/qdrant
QDRANT_API_KEY=your-qdrant-api-key
# Mail configuration, support: resend
MAIL_TYPE=
MAIL_DEFAULT_SEND_FROM=no-reply <no-reply@dify.ai>
RESEND_API_KEY=
# Sentry configuration
SENTRY_DSN=
# DEBUG
DEBUG=false
SQLALCHEMY_ECHO=false
# Notion import configuration, support public and internal
NOTION_INTEGRATION_TYPE=public
NOTION_CLIENT_SECRET=you-client-secret
NOTION_CLIENT_ID=you-client-id
NOTION_INTERNAL_SECRET=you-internal-secret

View File

@ -5,9 +5,11 @@ LABEL maintainer="takatost@gmail.com"
ENV FLASK_APP app.py
ENV EDITION SELF_HOSTED
ENV DEPLOY_ENV PRODUCTION
ENV CONSOLE_URL http://127.0.0.1:5001
ENV API_URL http://127.0.0.1:5001
ENV APP_URL http://127.0.0.1:5001
ENV CONSOLE_API_URL http://127.0.0.1:5001
ENV CONSOLE_WEB_URL http://127.0.0.1:3000
ENV SERVICE_API_URL http://127.0.0.1:5001
ENV APP_API_URL http://127.0.0.1:5001
ENV APP_WEB_URL http://127.0.0.1:3000
EXPOSE 5001
@ -25,4 +27,4 @@ RUN chmod +x /entrypoint.sh
ARG COMMIT_SHA
ENV COMMIT_SHA ${COMMIT_SHA}
ENTRYPOINT ["/entrypoint.sh"]
ENTRYPOINT ["/bin/bash", "/entrypoint.sh"]

View File

@ -17,6 +17,11 @@
```bash
openssl rand -base64 42
```
3.5 If you use annaconda, create a new environment and activate it
```bash
conda create --name dify python=3.10
conda activate dify
```
4. Install dependencies
```bash
pip install -r requirements.txt
@ -33,3 +38,4 @@
flask run --host 0.0.0.0 --port=5001 --debug
```
7. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
8. If you need to debug local async processing, you can run `celery -A app.celery worker`, celery can do dataset importing and other async tasks.

View File

@ -1,5 +1,9 @@
# -*- coding:utf-8 -*-
import os
from datetime import datetime
from werkzeug.exceptions import Forbidden
if not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != 'true':
from gevent import monkey
monkey.patch_all()
@ -12,20 +16,20 @@ from flask import Flask, request, Response, session
import flask_login
from flask_cors import CORS
from extensions import ext_session, ext_celery, ext_sentry, ext_redis, ext_login, ext_vector_store, ext_migrate, \
ext_database, ext_storage
from extensions import ext_session, ext_celery, ext_sentry, ext_redis, ext_login, ext_migrate, \
ext_database, ext_storage, ext_mail
from extensions.ext_database import db
from extensions.ext_login import login_manager
# DO NOT REMOVE BELOW
from models import model, account, dataset, web, task
from models import model, account, dataset, web, task, source, tool
from events import event_handlers
# DO NOT REMOVE ABOVE
import core
from config import Config, CloudEditionConfig
from commands import register_commands
from models.account import TenantAccountJoin
from models.account import TenantAccountJoin, AccountStatus
from models.model import Account, EndUser, App
import warnings
@ -77,11 +81,11 @@ def initialize_extensions(app):
ext_database.init_app(app)
ext_migrate.init(app, db)
ext_redis.init_app(app)
ext_vector_store.init_app(app)
ext_storage.init_app(app)
ext_celery.init_app(app)
ext_session.init_app(app)
ext_login.init_app(app)
ext_mail.init_app(app)
ext_sentry.init_app(app)
@ -99,6 +103,9 @@ def load_user(user_id):
account = db.session.query(Account).filter(Account.id == account_id).first()
if account:
if account.status == AccountStatus.BANNED.value or account.status == AccountStatus.CLOSED.value:
raise Forbidden('Account is banned or closed.')
workspace_id = session.get('workspace_id')
if workspace_id:
tenant_account_join = db.session.query(TenantAccountJoin).filter(
@ -122,6 +129,9 @@ def load_user(user_id):
account.current_tenant_id = tenant_account_join.tenant_id
session['workspace_id'] = account.current_tenant_id
account.last_active_at = datetime.utcnow()
db.session.commit()
# Log in the user with the updated user_id
flask_login.login_user(account, remember=True)
@ -145,13 +155,17 @@ def register_blueprints(app):
from controllers.web import bp as web_bp
from controllers.console import bp as console_app_bp
CORS(service_api_bp,
allow_headers=['Content-Type', 'Authorization', 'X-App-Code'],
methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH']
)
app.register_blueprint(service_api_bp)
CORS(web_bp,
resources={
r"/*": {"origins": app.config['WEB_API_CORS_ALLOW_ORIGINS']}},
supports_credentials=True,
allow_headers=['Content-Type', 'Authorization'],
allow_headers=['Content-Type', 'Authorization', 'X-App-Code'],
methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH'],
expose_headers=['X-Version', 'X-Env']
)

View File

@ -1,18 +1,27 @@
import datetime
import json
import logging
import random
import string
import time
import click
from flask import current_app
from werkzeug.exceptions import NotFound
from core.index.index import IndexBuilder
from libs.password import password_pattern, valid_password, hash_password
from libs.helper import email as email_validate
from extensions.ext_database import db
from models.account import InvitationCode
from models.model import Account, AppModelConfig, ApiToken, Site, App, RecommendedApp
from libs.rsa import generate_key_pair
from models.account import InvitationCode, Tenant
from models.dataset import Dataset, DatasetQuery, Document, DocumentSegment
from models.model import Account
import secrets
import base64
from models.provider import Provider, ProviderName
from services.provider_service import ProviderService
@click.command('reset-password', help='Reset the account password.')
@click.option('--email', prompt=True, help='The email address of the account whose password you need to reset')
@ -74,6 +83,31 @@ def reset_email(email, new_email, email_confirm):
click.echo(click.style('Congratulations!, email has been reset.', fg='green'))
@click.command('reset-encrypt-key-pair', help='Reset the asymmetric key pair of workspace for encrypt LLM credentials. '
'After the reset, all LLM credentials will become invalid, '
'requiring re-entry.'
'Only support SELF_HOSTED mode.')
@click.confirmation_option(prompt=click.style('Are you sure you want to reset encrypt key pair?'
' this operation cannot be rolled back!', fg='red'))
def reset_encrypt_key_pair():
if current_app.config['EDITION'] != 'SELF_HOSTED':
click.echo(click.style('Sorry, only support SELF_HOSTED mode.', fg='red'))
return
tenant = db.session.query(Tenant).first()
if not tenant:
click.echo(click.style('Sorry, no workspace found. Please enter /install to initialize.', fg='red'))
return
tenant.encrypt_public_key = generate_key_pair(tenant.id)
db.session.query(Provider).filter(Provider.provider_type == 'custom').delete()
db.session.commit()
click.echo(click.style('Congratulations! '
'the asymmetric key pair of workspace {} has been reset.'.format(tenant.id), fg='green'))
@click.command('generate-invitation-codes', help='Generate invitation codes.')
@click.option('--batch', help='The batch of invitation codes.')
@click.option('--count', prompt=True, help='Invitation codes count.')
@ -131,30 +165,127 @@ def generate_upper_string():
return result
@click.command('gen-recommended-apps', help='Number of records to generate')
def generate_recommended_apps():
print('Generating recommended app data...')
apps = App.query.all()
for app in apps:
recommended_app = RecommendedApp(
app_id=app.id,
description={
'en': 'Description for ' + app.name,
'zh': '描述 ' + app.name
},
copyright='Copyright ' + str(random.randint(1990, 2020)),
privacy_policy='https://privacypolicy.example.com',
category=random.choice(['Games', 'News', 'Music', 'Sports']),
position=random.randint(1, 100),
install_count=random.randint(100, 100000)
)
db.session.add(recommended_app)
db.session.commit()
print('Done!')
@click.command('recreate-all-dataset-indexes', help='Recreate all dataset indexes.')
def recreate_all_dataset_indexes():
click.echo(click.style('Start recreate all dataset indexes.', fg='green'))
recreate_count = 0
page = 1
while True:
try:
datasets = db.session.query(Dataset).filter(Dataset.indexing_technique == 'high_quality') \
.order_by(Dataset.created_at.desc()).paginate(page=page, per_page=50)
except NotFound:
break
page += 1
for dataset in datasets:
try:
click.echo('Recreating dataset index: {}'.format(dataset.id))
index = IndexBuilder.get_index(dataset, 'high_quality')
if index and index._is_origin():
index.recreate_dataset(dataset)
recreate_count += 1
else:
click.echo('passed.')
except Exception as e:
click.echo(
click.style('Recreate dataset index error: {} {}'.format(e.__class__.__name__, str(e)), fg='red'))
continue
click.echo(click.style('Congratulations! Recreate {} dataset indexes.'.format(recreate_count), fg='green'))
@click.command('clean-unused-dataset-indexes', help='Clean unused dataset indexes.')
def clean_unused_dataset_indexes():
click.echo(click.style('Start clean unused dataset indexes.', fg='green'))
clean_days = int(current_app.config.get('CLEAN_DAY_SETTING'))
start_at = time.perf_counter()
thirty_days_ago = datetime.datetime.now() - datetime.timedelta(days=clean_days)
page = 1
while True:
try:
datasets = db.session.query(Dataset).filter(Dataset.created_at < thirty_days_ago) \
.order_by(Dataset.created_at.desc()).paginate(page=page, per_page=50)
except NotFound:
break
page += 1
for dataset in datasets:
dataset_query = db.session.query(DatasetQuery).filter(
DatasetQuery.created_at > thirty_days_ago,
DatasetQuery.dataset_id == dataset.id
).all()
if not dataset_query or len(dataset_query) == 0:
documents = db.session.query(Document).filter(
Document.dataset_id == dataset.id,
Document.indexing_status == 'completed',
Document.enabled == True,
Document.archived == False,
Document.updated_at > thirty_days_ago
).all()
if not documents or len(documents) == 0:
try:
# remove index
vector_index = IndexBuilder.get_index(dataset, 'high_quality')
kw_index = IndexBuilder.get_index(dataset, 'economy')
# delete from vector index
if vector_index:
vector_index.delete()
kw_index.delete()
# update document
update_params = {
Document.enabled: False
}
Document.query.filter_by(dataset_id=dataset.id).update(update_params)
db.session.commit()
click.echo(click.style('Cleaned unused dataset {} from db success!'.format(dataset.id),
fg='green'))
except Exception as e:
click.echo(
click.style('clean dataset index error: {} {}'.format(e.__class__.__name__, str(e)),
fg='red'))
end_at = time.perf_counter()
click.echo(click.style('Cleaned unused dataset from db success latency: {}'.format(end_at - start_at), fg='green'))
@click.command('sync-anthropic-hosted-providers', help='Sync anthropic hosted providers.')
def sync_anthropic_hosted_providers():
click.echo(click.style('Start sync anthropic hosted providers.', fg='green'))
count = 0
page = 1
while True:
try:
tenants = db.session.query(Tenant).order_by(Tenant.created_at.desc()).paginate(page=page, per_page=50)
except NotFound:
break
page += 1
for tenant in tenants:
try:
click.echo('Syncing tenant anthropic hosted provider: {}'.format(tenant.id))
ProviderService.create_system_provider(
tenant,
ProviderName.ANTHROPIC.value,
current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT'],
True
)
count += 1
except Exception as e:
click.echo(click.style(
'Sync tenant anthropic hosted provider error: {} {}'.format(e.__class__.__name__, str(e)),
fg='red'))
continue
click.echo(click.style('Congratulations! Synced {} anthropic hosted providers.'.format(count), fg='green'))
def register_commands(app):
app.cli.add_command(reset_password)
app.cli.add_command(reset_email)
app.cli.add_command(generate_invitation_codes)
app.cli.add_command(generate_recommended_apps)
app.cli.add_command(reset_encrypt_key_pair)
app.cli.add_command(recreate_all_dataset_indexes)
app.cli.add_command(sync_anthropic_hosted_providers)
app.cli.add_command(clean_unused_dataset_indexes)

View File

@ -21,14 +21,18 @@ DEFAULTS = {
'REDIS_HOST': 'localhost',
'REDIS_PORT': '6379',
'REDIS_DB': '0',
'REDIS_USE_SSL': 'False',
'SESSION_REDIS_HOST': 'localhost',
'SESSION_REDIS_PORT': '6379',
'SESSION_REDIS_DB': '2',
'SESSION_REDIS_USE_SSL': 'False',
'OAUTH_REDIRECT_PATH': '/console/api/oauth/authorize',
'OAUTH_REDIRECT_INDEX_PATH': '/',
'CONSOLE_URL': 'https://cloud.dify.ai',
'API_URL': 'https://api.dify.ai',
'APP_URL': 'https://udify.app',
'CONSOLE_WEB_URL': 'https://cloud.dify.ai',
'CONSOLE_API_URL': 'https://cloud.dify.ai',
'SERVICE_API_URL': 'https://api.dify.ai',
'APP_WEB_URL': 'https://udify.app',
'APP_API_URL': 'https://udify.app',
'STORAGE_TYPE': 'local',
'STORAGE_LOCAL_PATH': 'storage',
'CHECK_UPDATE_URL': 'https://updates.dify.ai',
@ -41,9 +45,16 @@ DEFAULTS = {
'SENTRY_TRACES_SAMPLE_RATE': 1.0,
'SENTRY_PROFILES_SAMPLE_RATE': 1.0,
'WEAVIATE_GRPC_ENABLED': 'True',
'WEAVIATE_BATCH_SIZE': 100,
'CELERY_BACKEND': 'database',
'PDF_PREVIEW': 'True',
'LOG_LEVEL': 'INFO',
'DISABLE_PROVIDER_CONFIG_VALIDATION': 'False',
'DEFAULT_LLM_PROVIDER': 'openai',
'OPENAI_HOSTED_QUOTA_LIMIT': 200,
'ANTHROPIC_HOSTED_QUOTA_LIMIT': 1000,
'TENANT_DOCUMENT_COUNT': 100,
'CLEAN_DAY_SETTING': 30
}
@ -71,10 +82,15 @@ class Config:
def __init__(self):
# app settings
self.CONSOLE_API_URL = get_env('CONSOLE_URL') if get_env('CONSOLE_URL') else get_env('CONSOLE_API_URL')
self.CONSOLE_WEB_URL = get_env('CONSOLE_URL') if get_env('CONSOLE_URL') else get_env('CONSOLE_WEB_URL')
self.SERVICE_API_URL = get_env('API_URL') if get_env('API_URL') else get_env('SERVICE_API_URL')
self.APP_WEB_URL = get_env('APP_URL') if get_env('APP_URL') else get_env('APP_WEB_URL')
self.APP_API_URL = get_env('APP_URL') if get_env('APP_URL') else get_env('APP_API_URL')
self.CONSOLE_URL = get_env('CONSOLE_URL')
self.API_URL = get_env('API_URL')
self.APP_URL = get_env('APP_URL')
self.CURRENT_VERSION = "0.2.0"
self.CURRENT_VERSION = "0.3.11"
self.COMMIT_SHA = get_env('COMMIT_SHA')
self.EDITION = "SELF_HOSTED"
self.DEPLOY_ENV = get_env('DEPLOY_ENV')
@ -105,14 +121,18 @@ class Config:
# redis settings
self.REDIS_HOST = get_env('REDIS_HOST')
self.REDIS_PORT = get_env('REDIS_PORT')
self.REDIS_USERNAME = get_env('REDIS_USERNAME')
self.REDIS_PASSWORD = get_env('REDIS_PASSWORD')
self.REDIS_DB = get_env('REDIS_DB')
self.REDIS_USE_SSL = get_bool_env('REDIS_USE_SSL')
# session redis settings
self.SESSION_REDIS_HOST = get_env('SESSION_REDIS_HOST')
self.SESSION_REDIS_PORT = get_env('SESSION_REDIS_PORT')
self.SESSION_REDIS_USERNAME = get_env('SESSION_REDIS_USERNAME')
self.SESSION_REDIS_PASSWORD = get_env('SESSION_REDIS_PASSWORD')
self.SESSION_REDIS_DB = get_env('SESSION_REDIS_DB')
self.SESSION_REDIS_USE_SSL = get_bool_env('SESSION_REDIS_USE_SSL')
# storage settings
self.STORAGE_TYPE = get_env('STORAGE_TYPE')
@ -130,6 +150,7 @@ class Config:
self.WEAVIATE_ENDPOINT = get_env('WEAVIATE_ENDPOINT')
self.WEAVIATE_API_KEY = get_env('WEAVIATE_API_KEY')
self.WEAVIATE_GRPC_ENABLED = get_bool_env('WEAVIATE_GRPC_ENABLED')
self.WEAVIATE_BATCH_SIZE = int(get_env('WEAVIATE_BATCH_SIZE'))
# qdrant settings
self.QDRANT_URL = get_env('QDRANT_URL')
@ -137,10 +158,15 @@ class Config:
# cors settings
self.CONSOLE_CORS_ALLOW_ORIGINS = get_cors_allow_origins(
'CONSOLE_CORS_ALLOW_ORIGINS', self.CONSOLE_URL)
'CONSOLE_CORS_ALLOW_ORIGINS', self.CONSOLE_WEB_URL)
self.WEB_API_CORS_ALLOW_ORIGINS = get_cors_allow_origins(
'WEB_API_CORS_ALLOW_ORIGINS', '*')
# mail settings
self.MAIL_TYPE = get_env('MAIL_TYPE')
self.MAIL_DEFAULT_SEND_FROM = get_env('MAIL_DEFAULT_SEND_FROM')
self.RESEND_API_KEY = get_env('RESEND_API_KEY')
# sentry settings
self.SENTRY_DSN = get_env('SENTRY_DSN')
self.SENTRY_TRACES_SAMPLE_RATE = float(get_env('SENTRY_TRACES_SAMPLE_RATE'))
@ -165,9 +191,32 @@ class Config:
self.CELERY_BACKEND = get_env('CELERY_BACKEND')
self.CELERY_RESULT_BACKEND = 'db+{}'.format(self.SQLALCHEMY_DATABASE_URI) \
if self.CELERY_BACKEND == 'database' else self.CELERY_BROKER_URL
self.BROKER_USE_SSL = self.CELERY_BROKER_URL.startswith('rediss://')
# hosted provider credentials
self.OPENAI_API_KEY = get_env('OPENAI_API_KEY')
self.ANTHROPIC_API_KEY = get_env('ANTHROPIC_API_KEY')
self.OPENAI_HOSTED_QUOTA_LIMIT = get_env('OPENAI_HOSTED_QUOTA_LIMIT')
self.ANTHROPIC_HOSTED_QUOTA_LIMIT = get_env('ANTHROPIC_HOSTED_QUOTA_LIMIT')
# By default it is False
# You could disable it for compatibility with certain OpenAPI providers
self.DISABLE_PROVIDER_CONFIG_VALIDATION = get_bool_env('DISABLE_PROVIDER_CONFIG_VALIDATION')
# For temp use only
# set default LLM provider, default is 'openai', support `azure_openai`
self.DEFAULT_LLM_PROVIDER = get_env('DEFAULT_LLM_PROVIDER')
# notion import setting
self.NOTION_CLIENT_ID = get_env('NOTION_CLIENT_ID')
self.NOTION_CLIENT_SECRET = get_env('NOTION_CLIENT_SECRET')
self.NOTION_INTEGRATION_TYPE = get_env('NOTION_INTEGRATION_TYPE')
self.NOTION_INTERNAL_SECRET = get_env('NOTION_INTERNAL_SECRET')
self.NOTION_INTEGRATION_TOKEN = get_env('NOTION_INTEGRATION_TOKEN')
self.TENANT_DOCUMENT_COUNT = get_env('TENANT_DOCUMENT_COUNT')
self.CLEAN_DAY_SETTING = get_env('CLEAN_DAY_SETTING')
class CloudEditionConfig(Config):

View File

@ -5,16 +5,23 @@ from libs.external_api import ExternalApi
bp = Blueprint('console', __name__, url_prefix='/console/api')
api = ExternalApi(bp)
# Import other controllers
from . import setup, version, apikey, admin
# Import app controllers
from .app import app, site, explore, completion, model_config, statistic, conversation, message
from .app import app, site, completion, model_config, statistic, conversation, message, generator, audio
# Import auth controllers
from .auth import login, oauth
from .auth import login, oauth, data_source_oauth, activate
# Import datasets controllers
from .datasets import datasets, datasets_document, datasets_segments, file, hit_testing
from .datasets import datasets, datasets_document, datasets_segments, file, hit_testing, data_source
# Import other controllers
from . import setup, version, apikey
# Import workspace controllers
from .workspace import workspace, members, model_providers, account, tool_providers
from .workspace import workspace, members, providers, account
# Import explore controllers
from .explore import installed_app, recommended_app, completion, conversation, message, parameter, saved_message, audio
# Import universal chat controllers
from .universal_chat import chat, conversation, message, parameter, audio

View File

@ -0,0 +1,132 @@
import os
from functools import wraps
from flask import request
from flask_restful import Resource, reqparse
from werkzeug.exceptions import NotFound, Unauthorized
from controllers.console import api
from controllers.console.wraps import only_edition_cloud
from extensions.ext_database import db
from libs.helper import supported_language
from models.model import RecommendedApp, App, InstalledApp
def admin_required(view):
@wraps(view)
def decorated(*args, **kwargs):
if not os.getenv('ADMIN_API_KEY'):
raise Unauthorized('API key is invalid.')
auth_header = request.headers.get('Authorization')
if auth_header is None:
raise Unauthorized('Authorization header is missing.')
if ' ' not in auth_header:
raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
auth_scheme, auth_token = auth_header.split(None, 1)
auth_scheme = auth_scheme.lower()
if auth_scheme != 'bearer':
raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
if os.getenv('ADMIN_API_KEY') != auth_token:
raise Unauthorized('API key is invalid.')
return view(*args, **kwargs)
return decorated
class InsertExploreAppListApi(Resource):
@only_edition_cloud
@admin_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('app_id', type=str, required=True, nullable=False, location='json')
parser.add_argument('desc', type=str, location='json')
parser.add_argument('copyright', type=str, location='json')
parser.add_argument('privacy_policy', type=str, location='json')
parser.add_argument('language', type=supported_language, required=True, nullable=False, location='json')
parser.add_argument('category', type=str, required=True, nullable=False, location='json')
parser.add_argument('position', type=int, required=True, nullable=False, location='json')
args = parser.parse_args()
app = App.query.filter(App.id == args['app_id']).first()
if not app:
raise NotFound('App not found')
site = app.site
if not site:
desc = args['desc'] if args['desc'] else ''
copy_right = args['copyright'] if args['copyright'] else ''
privacy_policy = args['privacy_policy'] if args['privacy_policy'] else ''
else:
desc = site.description if (site.description if not args['desc'] else args['desc']) else ''
copy_right = site.copyright if (site.copyright if not args['copyright'] else args['copyright']) else ''
privacy_policy = site.privacy_policy \
if (site.privacy_policy if not args['privacy_policy'] else args['privacy_policy']) else ''
recommended_app = RecommendedApp.query.filter(RecommendedApp.app_id == args['app_id']).first()
if not recommended_app:
recommended_app = RecommendedApp(
app_id=app.id,
description=desc,
copyright=copy_right,
privacy_policy=privacy_policy,
language=args['language'],
category=args['category'],
position=args['position']
)
db.session.add(recommended_app)
app.is_public = True
db.session.commit()
return {'result': 'success'}, 201
else:
recommended_app.description = desc
recommended_app.copyright = copy_right
recommended_app.privacy_policy = privacy_policy
recommended_app.language = args['language']
recommended_app.category = args['category']
recommended_app.position = args['position']
app.is_public = True
db.session.commit()
return {'result': 'success'}, 200
class InsertExploreAppApi(Resource):
@only_edition_cloud
@admin_required
def delete(self, app_id):
recommended_app = RecommendedApp.query.filter(RecommendedApp.app_id == str(app_id)).first()
if not recommended_app:
return {'result': 'success'}, 204
app = App.query.filter(App.id == recommended_app.app_id).first()
if app:
app.is_public = False
installed_apps = InstalledApp.query.filter(
InstalledApp.app_id == recommended_app.app_id,
InstalledApp.tenant_id != InstalledApp.app_owner_tenant_id
).all()
for installed_app in installed_apps:
db.session.delete(installed_app)
db.session.delete(recommended_app)
db.session.commit()
return {'result': 'success'}, 204
api.add_resource(InsertExploreAppListApi, '/admin/insert-explore-apps')
api.add_resource(InsertExploreAppApi, '/admin/insert-explore-apps/<uuid:app_id>')

View File

@ -17,6 +17,6 @@ def _get_app(app_id, mode=None):
raise NotFound("App not found")
if mode and app.mode != mode:
raise AppUnavailableError()
raise NotFound("The {} app not found".format(mode))
return app

View File

@ -9,25 +9,22 @@ from werkzeug.exceptions import Unauthorized, Forbidden
from constants.model_template import model_templates, demo_model_templates
from controllers.console import api
from controllers.console.app.error import AppNotFoundError, ProviderNotInitializeError, ProviderQuotaExceededError, \
CompletionRequestError, ProviderModelCurrentlyNotSupportError
from controllers.console.app.error import AppNotFoundError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.generator.llm_generator import LLMGenerator
from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, LLMBadRequestError, LLMAPIConnectionError, \
LLMAPIUnavailableError, LLMRateLimitError, LLMAuthorizationError, ModelCurrentlyNotSupportError
from events.app_event import app_was_created, app_was_deleted
from libs.helper import TimestampField
from extensions.ext_database import db
from models.model import App, AppModelConfig, Site, InstalledApp
from services.account_service import TenantService
from models.model import App, AppModelConfig, Site
from services.app_model_config_service import AppModelConfigService
model_config_fields = {
'opening_statement': fields.String,
'suggested_questions': fields.Raw(attribute='suggested_questions_list'),
'suggested_questions_after_answer': fields.Raw(attribute='suggested_questions_after_answer_dict'),
'speech_to_text': fields.Raw(attribute='speech_to_text_dict'),
'more_like_this': fields.Raw(attribute='more_like_this_dict'),
'sensitive_word_avoidance': fields.Raw(attribute='sensitive_word_avoidance_dict'),
'model': fields.Raw(attribute='model_dict'),
'user_input_form': fields.Raw(attribute='user_input_form_list'),
'pre_prompt': fields.String,
@ -100,7 +97,8 @@ class AppListApi(Resource):
args = parser.parse_args()
app_models = db.paginate(
db.select(App).where(App.tenant_id == current_user.current_tenant_id).order_by(App.created_at.desc()),
db.select(App).where(App.tenant_id == current_user.current_tenant_id,
App.is_universal == False).order_by(App.created_at.desc()),
page=args['page'],
per_page=args['limit'],
error_out=False)
@ -149,7 +147,9 @@ class AppListApi(Resource):
opening_statement=model_configuration['opening_statement'],
suggested_questions=json.dumps(model_configuration['suggested_questions']),
suggested_questions_after_answer=json.dumps(model_configuration['suggested_questions_after_answer']),
speech_to_text=json.dumps(model_configuration['speech_to_text']),
more_like_this=json.dumps(model_configuration['more_like_this']),
sensitive_word_avoidance=json.dumps(model_configuration['sensitive_word_avoidance']),
model=json.dumps(model_configuration['model']),
user_input_form=json.dumps(model_configuration['user_input_form']),
pre_prompt=model_configuration['pre_prompt'],
@ -220,7 +220,11 @@ class AppTemplateApi(Resource):
account = current_user
interface_language = account.interface_language
return {'data': demo_model_templates.get(interface_language)}
templates = demo_model_templates.get(interface_language)
if not templates:
templates = demo_model_templates.get('en-US')
return {'data': templates}
class AppApi(Resource):
@ -435,7 +439,9 @@ class AppCopy(Resource):
opening_statement=app_config.opening_statement,
suggested_questions=app_config.suggested_questions,
suggested_questions_after_answer=app_config.suggested_questions_after_answer,
speech_to_text=app_config.speech_to_text,
more_like_this=app_config.more_like_this,
sensitive_word_avoidance=app_config.sensitive_word_avoidance,
model=app_config.model,
user_input_form=app_config.user_input_form,
pre_prompt=app_config.pre_prompt,
@ -478,35 +484,6 @@ class AppExport(Resource):
pass
class IntroductionGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('prompt_template', type=str, required=True, location='json')
args = parser.parse_args()
account = current_user
try:
answer = LLMGenerator.generate_introduction(
account.current_tenant_id,
args['prompt_template']
)
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
return {'introduction': answer}
api.add_resource(AppListApi, '/apps')
api.add_resource(AppTemplateApi, '/app-templates')
api.add_resource(AppApi, '/apps/<uuid:app_id>')
@ -515,4 +492,3 @@ api.add_resource(AppNameApi, '/apps/<uuid:app_id>/name')
api.add_resource(AppSiteStatus, '/apps/<uuid:app_id>/site-enable')
api.add_resource(AppApiStatus, '/apps/<uuid:app_id>/api-enable')
api.add_resource(AppRateLimit, '/apps/<uuid:app_id>/rate-limit')
api.add_resource(IntroductionGenerateApi, '/introduction-generate')

View File

@ -0,0 +1,69 @@
# -*- coding:utf-8 -*-
import logging
from flask import request
from flask_login import login_required
from werkzeug.exceptions import InternalServerError, NotFound
import services
from controllers.console import api
from controllers.console.app import _get_app
from controllers.console.app.error import AppUnavailableError, \
ProviderNotInitializeError, CompletionRequestError, ProviderQuotaExceededError, \
ProviderModelCurrentlyNotSupportError, NoAudioUploadedError, AudioTooLargeError, \
UnsupportedAudioTypeError, ProviderNotSupportSpeechToTextError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from flask_restful import Resource
from services.audio_service import AudioService
from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
class ChatMessageAudioApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self, app_id):
app_id = str(app_id)
app_model = _get_app(app_id, 'chat')
file = request.files['file']
try:
response = AudioService.transcript(
tenant_id=app_model.tenant_id,
file=file,
)
return response
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except NoAudioUploadedServiceError:
raise NoAudioUploadedError()
except AudioTooLargeServiceError as e:
raise AudioTooLargeError(str(e))
except UnsupportedAudioTypeServiceError:
raise UnsupportedAudioTypeError()
except ProviderNotSupportSpeechToTextServiceError:
raise ProviderNotSupportSpeechToTextError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
api.add_resource(ChatMessageAudioApi, '/apps/<uuid:app_id>/audio-to-text')

View File

@ -63,8 +63,8 @@ class CompletionMessageApi(Resource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -133,8 +133,8 @@ class ChatMessageApi(Resource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -164,8 +164,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:

View File

@ -45,7 +45,7 @@ message_detail_fields = {
'message_tokens': fields.Integer,
'answer': fields.String,
'answer_tokens': fields.Integer,
'provider_response_latency': fields.Integer,
'provider_response_latency': fields.Float,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_account_id': fields.String,
@ -95,6 +95,7 @@ class CompletionConversationApi(Resource):
'status': fields.String,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_end_user_session_id': fields.String(attribute='end_user.session_id'),
'from_account_id': fields.String,
'read_at': TimestampField,
'created_at': TimestampField,
@ -135,6 +136,8 @@ class CompletionConversationApi(Resource):
query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'completion')
query = query.options(joinedload(Conversation.end_user))
if args['keyword']:
query = query.join(
Message, Message.conversation_id == Conversation.id
@ -160,7 +163,7 @@ class CompletionConversationApi(Resource):
if args['end']:
end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
end_datetime = end_datetime.replace(second=0)
end_datetime = end_datetime.replace(second=59)
end_datetime_timezone = timezone.localize(end_datetime)
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
@ -209,6 +212,26 @@ class CompletionConversationDetailApi(Resource):
conversation_id = str(conversation_id)
return _get_conversation(app_id, conversation_id, 'completion')
@setup_required
@login_required
@account_initialization_required
def delete(self, app_id, conversation_id):
app_id = str(app_id)
conversation_id = str(conversation_id)
app = _get_app(app_id, 'chat')
conversation = db.session.query(Conversation) \
.filter(Conversation.id == conversation_id, Conversation.app_id == app.id).first()
if not conversation:
raise NotFound("Conversation Not Exists.")
conversation.is_deleted = True
db.session.commit()
return {'result': 'success'}, 204
class ChatConversationApi(Resource):
@ -226,6 +249,7 @@ class ChatConversationApi(Resource):
'status': fields.String,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_end_user_session_id': fields.String(attribute='end_user.session_id'),
'from_account_id': fields.String,
'summary': fields.String(attribute='summary_or_query'),
'read_at': TimestampField,
@ -268,6 +292,8 @@ class ChatConversationApi(Resource):
query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'chat')
query = query.options(joinedload(Conversation.end_user))
if args['keyword']:
query = query.join(
Message, Message.conversation_id == Conversation.id
@ -296,7 +322,7 @@ class ChatConversationApi(Resource):
if args['end']:
end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
end_datetime = end_datetime.replace(second=0)
end_datetime = end_datetime.replace(second=59)
end_datetime_timezone = timezone.localize(end_datetime)
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
@ -356,6 +382,27 @@ class ChatConversationDetailApi(Resource):
conversation_id = str(conversation_id)
return _get_conversation(app_id, conversation_id, 'chat')
@setup_required
@login_required
@account_initialization_required
def delete(self, app_id, conversation_id):
app_id = str(app_id)
conversation_id = str(conversation_id)
# get app info
app = _get_app(app_id, 'chat')
conversation = db.session.query(Conversation) \
.filter(Conversation.id == conversation_id, Conversation.app_id == app.id).first()
if not conversation:
raise NotFound("Conversation Not Exists.")
conversation.is_deleted = True
db.session.commit()
return {'result': 'success'}, 204

View File

@ -9,31 +9,33 @@ class AppNotFoundError(BaseHTTPException):
class ProviderNotInitializeError(BaseHTTPException):
error_code = 'provider_not_initialize'
description = "Provider Token not initialize."
description = "No valid model provider credentials found. " \
"Please go to Settings -> Model Provider to complete your provider credentials."
code = 400
class ProviderQuotaExceededError(BaseHTTPException):
error_code = 'provider_quota_exceeded'
description = "Provider quota exceeded."
description = "Your quota for Dify Hosted Model Provider has been exhausted. " \
"Please go to Settings -> Model Provider to complete your own provider credentials."
code = 400
class ProviderModelCurrentlyNotSupportError(BaseHTTPException):
error_code = 'model_currently_not_support'
description = "GPT-4 currently not support."
description = "Dify Hosted OpenAI trial currently not support the GPT-4 model."
code = 400
class ConversationCompletedError(BaseHTTPException):
error_code = 'conversation_completed'
description = "Conversation was completed."
description = "The conversation has ended. Please start a new conversation."
code = 400
class AppUnavailableError(BaseHTTPException):
error_code = 'app_unavailable'
description = "App unavailable."
description = "App unavailable, please check your app configurations."
code = 400
@ -45,5 +47,29 @@ class CompletionRequestError(BaseHTTPException):
class AppMoreLikeThisDisabledError(BaseHTTPException):
error_code = 'app_more_like_this_disabled'
description = "More like this disabled."
description = "The 'More like this' feature is disabled. Please refresh your page."
code = 403
class NoAudioUploadedError(BaseHTTPException):
error_code = 'no_audio_uploaded'
description = "Please upload your audio."
code = 400
class AudioTooLargeError(BaseHTTPException):
error_code = 'audio_too_large'
description = "Audio size exceeded. {message}"
code = 413
class UnsupportedAudioTypeError(BaseHTTPException):
error_code = 'unsupported_audio_type'
description = "Audio type not allowed."
code = 415
class ProviderNotSupportSpeechToTextError(BaseHTTPException):
error_code = 'provider_not_support_speech_to_text'
description = "Provider not support speech to text."
code = 400

View File

@ -1,209 +0,0 @@
# -*- coding:utf-8 -*-
from datetime import datetime
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, fields, marshal_with, abort, inputs
from sqlalchemy import and_
from controllers.console import api
from extensions.ext_database import db
from models.model import Tenant, App, InstalledApp, RecommendedApp
from services.account_service import TenantService
app_fields = {
'id': fields.String,
'name': fields.String,
'mode': fields.String,
'icon': fields.String,
'icon_background': fields.String
}
installed_app_fields = {
'id': fields.String,
'app': fields.Nested(app_fields, attribute='app'),
'app_owner_tenant_id': fields.String,
'is_pinned': fields.Boolean,
'last_used_at': fields.DateTime,
'editable': fields.Boolean
}
installed_app_list_fields = {
'installed_apps': fields.List(fields.Nested(installed_app_fields))
}
recommended_app_fields = {
'app': fields.Nested(app_fields, attribute='app'),
'app_id': fields.String,
'description': fields.String(attribute='description'),
'copyright': fields.String,
'privacy_policy': fields.String,
'category': fields.String,
'position': fields.Integer,
'is_listed': fields.Boolean,
'install_count': fields.Integer,
'installed': fields.Boolean,
'editable': fields.Boolean
}
recommended_app_list_fields = {
'recommended_apps': fields.List(fields.Nested(recommended_app_fields)),
'categories': fields.List(fields.String)
}
class InstalledAppsListResource(Resource):
@login_required
@marshal_with(installed_app_list_fields)
def get(self):
current_tenant_id = Tenant.query.first().id
installed_apps = db.session.query(InstalledApp).filter(
InstalledApp.tenant_id == current_tenant_id
).all()
current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
installed_apps = [
{
**installed_app,
"editable": current_user.role in ["owner", "admin"],
}
for installed_app in installed_apps
]
installed_apps.sort(key=lambda app: (-app.is_pinned, app.last_used_at))
return {'installed_apps': installed_apps}
@login_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('app_id', type=str, required=True, help='Invalid app_id')
args = parser.parse_args()
current_tenant_id = Tenant.query.first().id
app = App.query.get(args['app_id'])
if app is None:
abort(404, message='App not found')
recommended_app = RecommendedApp.query.filter(RecommendedApp.app_id == args['app_id']).first()
if recommended_app is None:
abort(404, message='App not found')
if not app.is_public:
abort(403, message="You can't install a non-public app")
installed_app = InstalledApp.query.filter(and_(
InstalledApp.app_id == args['app_id'],
InstalledApp.tenant_id == current_tenant_id
)).first()
if installed_app is None:
# todo: position
recommended_app.install_count += 1
new_installed_app = InstalledApp(
app_id=args['app_id'],
tenant_id=current_tenant_id,
is_pinned=False,
last_used_at=datetime.utcnow()
)
db.session.add(new_installed_app)
db.session.commit()
return {'message': 'App installed successfully'}
class InstalledAppResource(Resource):
@login_required
def delete(self, installed_app_id):
installed_app = InstalledApp.query.filter(and_(
InstalledApp.id == str(installed_app_id),
InstalledApp.tenant_id == current_user.current_tenant_id
)).first()
if installed_app is None:
abort(404, message='App not found')
if installed_app.app_owner_tenant_id == current_user.current_tenant_id:
abort(400, message="You can't uninstall an app owned by the current tenant")
db.session.delete(installed_app)
db.session.commit()
return {'result': 'success', 'message': 'App uninstalled successfully'}
@login_required
def patch(self, installed_app_id):
parser = reqparse.RequestParser()
parser.add_argument('is_pinned', type=inputs.boolean)
args = parser.parse_args()
current_tenant_id = Tenant.query.first().id
installed_app = InstalledApp.query.filter(and_(
InstalledApp.id == str(installed_app_id),
InstalledApp.tenant_id == current_tenant_id
)).first()
if installed_app is None:
abort(404, message='Installed app not found')
commit_args = False
if 'is_pinned' in args:
installed_app.is_pinned = args['is_pinned']
commit_args = True
if commit_args:
db.session.commit()
return {'result': 'success', 'message': 'App info updated successfully'}
class RecommendedAppsResource(Resource):
@login_required
@marshal_with(recommended_app_list_fields)
def get(self):
recommended_apps = db.session.query(RecommendedApp).filter(
RecommendedApp.is_listed == True
).all()
categories = set()
current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
recommended_apps_result = []
for recommended_app in recommended_apps:
installed = db.session.query(InstalledApp).filter(
and_(
InstalledApp.app_id == recommended_app.app_id,
InstalledApp.tenant_id == current_user.current_tenant_id
)
).first() is not None
language_prefix = current_user.interface_language.split('-')[0]
desc = None
if recommended_app.description:
if language_prefix in recommended_app.description:
desc = recommended_app.description[language_prefix]
elif 'en' in recommended_app.description:
desc = recommended_app.description['en']
recommended_app_result = {
'id': recommended_app.id,
'app': recommended_app.app,
'app_id': recommended_app.app_id,
'description': desc,
'copyright': recommended_app.copyright,
'privacy_policy': recommended_app.privacy_policy,
'category': recommended_app.category,
'position': recommended_app.position,
'is_listed': recommended_app.is_listed,
'install_count': recommended_app.install_count,
'installed': installed,
'editable': current_user.role in ['owner', 'admin'],
}
recommended_apps_result.append(recommended_app_result)
categories.add(recommended_app.category) # add category to categories
return {'recommended_apps': recommended_apps_result, 'categories': list(categories)}
api.add_resource(InstalledAppsListResource, '/installed-apps')
api.add_resource(InstalledAppResource, '/installed-apps/<uuid:installed_app_id>')
api.add_resource(RecommendedAppsResource, '/explore/apps')

View File

@ -0,0 +1,75 @@
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse
from controllers.console import api
from controllers.console.app.error import ProviderNotInitializeError, ProviderQuotaExceededError, \
CompletionRequestError, ProviderModelCurrentlyNotSupportError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.generator.llm_generator import LLMGenerator
from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, LLMBadRequestError, LLMAPIConnectionError, \
LLMAPIUnavailableError, LLMRateLimitError, LLMAuthorizationError, ModelCurrentlyNotSupportError
class IntroductionGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('prompt_template', type=str, required=True, location='json')
args = parser.parse_args()
account = current_user
try:
answer = LLMGenerator.generate_introduction(
account.current_tenant_id,
args['prompt_template']
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
return {'introduction': answer}
class RuleGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('audiences', type=str, required=True, nullable=False, location='json')
parser.add_argument('hoping_to_solve', type=str, required=True, nullable=False, location='json')
args = parser.parse_args()
account = current_user
try:
rules = LLMGenerator.generate_rule_config(
account.current_tenant_id,
args['audiences'],
args['hoping_to_solve']
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
return rules
api.add_resource(IntroductionGenerateApi, '/introduction-generate')
api.add_resource(RuleGenerateApi, '/rule-generate')

View File

@ -26,46 +26,46 @@ from services.errors.conversation import ConversationNotExistsError
from services.errors.message import MessageNotExistsError
from services.message_service import MessageService
account_fields = {
'id': fields.String,
'name': fields.String,
'email': fields.String
}
class ChatMessageApi(Resource):
account_fields = {
'id': fields.String,
'name': fields.String,
'email': fields.String
}
feedback_fields = {
'rating': fields.String,
'content': fields.String,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_account': fields.Nested(account_fields, allow_null=True),
}
feedback_fields = {
'rating': fields.String,
'content': fields.String,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_account': fields.Nested(account_fields, allow_null=True),
}
annotation_fields = {
'content': fields.String,
'account': fields.Nested(account_fields, allow_null=True),
'created_at': TimestampField
}
annotation_fields = {
'content': fields.String,
'account': fields.Nested(account_fields, allow_null=True),
'created_at': TimestampField
}
message_detail_fields = {
'id': fields.String,
'conversation_id': fields.String,
'inputs': fields.Raw,
'query': fields.String,
'message': fields.Raw,
'message_tokens': fields.Integer,
'answer': fields.String,
'answer_tokens': fields.Integer,
'provider_response_latency': fields.Float,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_account_id': fields.String,
'feedbacks': fields.List(fields.Nested(feedback_fields)),
'annotation': fields.Nested(annotation_fields, allow_null=True),
'created_at': TimestampField
}
message_detail_fields = {
'id': fields.String,
'conversation_id': fields.String,
'inputs': fields.Raw,
'query': fields.String,
'message': fields.Raw,
'message_tokens': fields.Integer,
'answer': fields.String,
'answer_tokens': fields.Integer,
'provider_response_latency': fields.Integer,
'from_source': fields.String,
'from_end_user_id': fields.String,
'from_account_id': fields.String,
'feedbacks': fields.List(fields.Nested(feedback_fields)),
'annotation': fields.Nested(annotation_fields, allow_null=True),
'created_at': TimestampField
}
class ChatMessageListApi(Resource):
message_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
@ -253,7 +253,8 @@ class MessageMoreLikeThisApi(Resource):
message_id = str(message_id)
parser = reqparse.RequestParser()
parser.add_argument('response_mode', type=str, required=True, choices=['blocking', 'streaming'], location='args')
parser.add_argument('response_mode', type=str, required=True, choices=['blocking', 'streaming'],
location='args')
args = parser.parse_args()
streaming = args['response_mode'] == 'streaming'
@ -268,8 +269,8 @@ class MessageMoreLikeThisApi(Resource):
raise NotFound("Message Not Exists.")
except MoreLikeThisDisabledError:
raise AppMoreLikeThisDisabledError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -296,12 +297,13 @@ def compact_response(response: Union[dict | Generator]) -> Response:
yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
except MoreLikeThisDisabledError:
yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:
yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
yield "data: " + json.dumps(
api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
@ -337,8 +339,8 @@ class MessageSuggestedQuestionApi(Resource):
raise NotFound("Message not found")
except ConversationNotExistsError:
raise NotFound("Conversation not found")
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -353,9 +355,33 @@ class MessageSuggestedQuestionApi(Resource):
return {'data': questions}
class MessageApi(Resource):
@setup_required
@login_required
@account_initialization_required
@marshal_with(message_detail_fields)
def get(self, app_id, message_id):
app_id = str(app_id)
message_id = str(message_id)
# get app info
app_model = _get_app(app_id, 'chat')
message = db.session.query(Message).filter(
Message.id == message_id,
Message.app_id == app_model.id
).first()
if not message:
raise NotFound("Message Not Exists.")
return message
api.add_resource(MessageMoreLikeThisApi, '/apps/<uuid:app_id>/completion-messages/<uuid:message_id>/more-like-this')
api.add_resource(MessageSuggestedQuestionApi, '/apps/<uuid:app_id>/chat-messages/<uuid:message_id>/suggested-questions')
api.add_resource(ChatMessageApi, '/apps/<uuid:app_id>/chat-messages', endpoint='chat_messages')
api.add_resource(ChatMessageListApi, '/apps/<uuid:app_id>/chat-messages', endpoint='console_chat_messages')
api.add_resource(MessageFeedbackApi, '/apps/<uuid:app_id>/feedbacks')
api.add_resource(MessageAnnotationApi, '/apps/<uuid:app_id>/annotations')
api.add_resource(MessageAnnotationCountApi, '/apps/<uuid:app_id>/annotations/count')
api.add_resource(MessageApi, '/apps/<uuid:app_id>/messages/<uuid:message_id>', endpoint='console_message')

View File

@ -41,7 +41,9 @@ class ModelConfigResource(Resource):
opening_statement=model_configuration['opening_statement'],
suggested_questions=json.dumps(model_configuration['suggested_questions']),
suggested_questions_after_answer=json.dumps(model_configuration['suggested_questions_after_answer']),
speech_to_text=json.dumps(model_configuration['speech_to_text']),
more_like_this=json.dumps(model_configuration['more_like_this']),
sensitive_word_avoidance=json.dumps(model_configuration['sensitive_word_avoidance']),
model=json.dumps(model_configuration['model']),
user_input_form=json.dumps(model_configuration['user_input_form']),
pre_prompt=model_configuration['pre_prompt'],

View File

@ -1,4 +1,5 @@
# -*- coding:utf-8 -*-
from decimal import Decimal
from datetime import datetime
import pytz
@ -59,18 +60,20 @@ class DailyConversationStatistic(Resource):
arg_dict['end'] = end_datetime_utc
sql_query += ' GROUP BY date order by date'
rs = db.session.execute(sql_query, arg_dict)
response_date = []
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_date.append({
response_data.append({
'date': str(i.date),
'conversation_count': i.conversation_count
})
return jsonify({
'data': response_date
'data': response_data
})
@ -119,18 +122,20 @@ class DailyTerminalsStatistic(Resource):
arg_dict['end'] = end_datetime_utc
sql_query += ' GROUP BY date order by date'
rs = db.session.execute(sql_query, arg_dict)
response_date = []
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_date.append({
response_data.append({
'date': str(i.date),
'terminal_count': i.terminal_count
})
return jsonify({
'data': response_date
'data': response_data
})
@ -180,12 +185,14 @@ class DailyTokenCostStatistic(Resource):
arg_dict['end'] = end_datetime_utc
sql_query += ' GROUP BY date order by date'
rs = db.session.execute(sql_query, arg_dict)
response_date = []
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_date.append({
response_data.append({
'date': str(i.date),
'token_count': i.token_count,
'total_price': i.total_price,
@ -193,10 +200,207 @@ class DailyTokenCostStatistic(Resource):
})
return jsonify({
'data': response_date
'data': response_data
})
class AverageSessionInteractionStatistic(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, app_id):
account = current_user
app_id = str(app_id)
app_model = _get_app(app_id, 'chat')
parser = reqparse.RequestParser()
parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
args = parser.parse_args()
sql_query = """SELECT date(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
AVG(subquery.message_count) AS interactions
FROM (SELECT m.conversation_id, COUNT(m.id) AS message_count
FROM conversations c
JOIN messages m ON c.id = m.conversation_id
WHERE c.override_model_configs IS NULL AND c.app_id = :app_id"""
arg_dict = {'tz': account.timezone, 'app_id': app_model.id}
timezone = pytz.timezone(account.timezone)
utc_timezone = pytz.utc
if args['start']:
start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
start_datetime = start_datetime.replace(second=0)
start_datetime_timezone = timezone.localize(start_datetime)
start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and c.created_at >= :start'
arg_dict['start'] = start_datetime_utc
if args['end']:
end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
end_datetime = end_datetime.replace(second=0)
end_datetime_timezone = timezone.localize(end_datetime)
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and c.created_at < :end'
arg_dict['end'] = end_datetime_utc
sql_query += """
GROUP BY m.conversation_id) subquery
LEFT JOIN conversations c on c.id=subquery.conversation_id
GROUP BY date
ORDER BY date"""
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_data.append({
'date': str(i.date),
'interactions': float(i.interactions.quantize(Decimal('0.01')))
})
return jsonify({
'data': response_data
})
class UserSatisfactionRateStatistic(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, app_id):
account = current_user
app_id = str(app_id)
app_model = _get_app(app_id)
parser = reqparse.RequestParser()
parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
args = parser.parse_args()
sql_query = '''
SELECT date(DATE_TRUNC('day', m.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
COUNT(m.id) as message_count, COUNT(mf.id) as feedback_count
FROM messages m
LEFT JOIN message_feedbacks mf on mf.message_id=m.id
WHERE m.app_id = :app_id
'''
arg_dict = {'tz': account.timezone, 'app_id': app_model.id}
timezone = pytz.timezone(account.timezone)
utc_timezone = pytz.utc
if args['start']:
start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
start_datetime = start_datetime.replace(second=0)
start_datetime_timezone = timezone.localize(start_datetime)
start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and m.created_at >= :start'
arg_dict['start'] = start_datetime_utc
if args['end']:
end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
end_datetime = end_datetime.replace(second=0)
end_datetime_timezone = timezone.localize(end_datetime)
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and m.created_at < :end'
arg_dict['end'] = end_datetime_utc
sql_query += ' GROUP BY date order by date'
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_data.append({
'date': str(i.date),
'rate': round((i.feedback_count * 1000 / i.message_count) if i.message_count > 0 else 0, 2),
})
return jsonify({
'data': response_data
})
class AverageResponseTimeStatistic(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, app_id):
account = current_user
app_id = str(app_id)
app_model = _get_app(app_id, 'completion')
parser = reqparse.RequestParser()
parser.add_argument('start', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
parser.add_argument('end', type=datetime_string('%Y-%m-%d %H:%M'), location='args')
args = parser.parse_args()
sql_query = '''
SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
AVG(provider_response_latency) as latency
FROM messages
WHERE app_id = :app_id
'''
arg_dict = {'tz': account.timezone, 'app_id': app_model.id}
timezone = pytz.timezone(account.timezone)
utc_timezone = pytz.utc
if args['start']:
start_datetime = datetime.strptime(args['start'], '%Y-%m-%d %H:%M')
start_datetime = start_datetime.replace(second=0)
start_datetime_timezone = timezone.localize(start_datetime)
start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and created_at >= :start'
arg_dict['start'] = start_datetime_utc
if args['end']:
end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
end_datetime = end_datetime.replace(second=0)
end_datetime_timezone = timezone.localize(end_datetime)
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
sql_query += ' and created_at < :end'
arg_dict['end'] = end_datetime_utc
sql_query += ' GROUP BY date order by date'
with db.engine.begin() as conn:
rs = conn.execute(db.text(sql_query), arg_dict)
response_data = []
for i in rs:
response_data.append({
'date': str(i.date),
'latency': round(i.latency * 1000, 4)
})
return jsonify({
'data': response_data
})
api.add_resource(DailyConversationStatistic, '/apps/<uuid:app_id>/statistics/daily-conversations')
api.add_resource(DailyTerminalsStatistic, '/apps/<uuid:app_id>/statistics/daily-end-users')
api.add_resource(DailyTokenCostStatistic, '/apps/<uuid:app_id>/statistics/token-costs')
api.add_resource(AverageSessionInteractionStatistic, '/apps/<uuid:app_id>/statistics/average-session-interactions')
api.add_resource(UserSatisfactionRateStatistic, '/apps/<uuid:app_id>/statistics/user-satisfaction-rate')
api.add_resource(AverageResponseTimeStatistic, '/apps/<uuid:app_id>/statistics/average-response-time')

View File

@ -0,0 +1,75 @@
import base64
import secrets
from datetime import datetime
from flask_restful import Resource, reqparse
from controllers.console import api
from controllers.console.error import AlreadyActivateError
from extensions.ext_database import db
from libs.helper import email, str_len, supported_language, timezone
from libs.password import valid_password, hash_password
from models.account import AccountStatus, Tenant
from services.account_service import RegisterService
class ActivateCheckApi(Resource):
def get(self):
parser = reqparse.RequestParser()
parser.add_argument('workspace_id', type=str, required=True, nullable=False, location='args')
parser.add_argument('email', type=email, required=True, nullable=False, location='args')
parser.add_argument('token', type=str, required=True, nullable=False, location='args')
args = parser.parse_args()
account = RegisterService.get_account_if_token_valid(args['workspace_id'], args['email'], args['token'])
tenant = db.session.query(Tenant).filter(
Tenant.id == args['workspace_id'],
Tenant.status == 'normal'
).first()
return {'is_valid': account is not None, 'workspace_name': tenant.name}
class ActivateApi(Resource):
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('workspace_id', type=str, required=True, nullable=False, location='json')
parser.add_argument('email', type=email, required=True, nullable=False, location='json')
parser.add_argument('token', type=str, required=True, nullable=False, location='json')
parser.add_argument('name', type=str_len(30), required=True, nullable=False, location='json')
parser.add_argument('password', type=valid_password, required=True, nullable=False, location='json')
parser.add_argument('interface_language', type=supported_language, required=True, nullable=False,
location='json')
parser.add_argument('timezone', type=timezone, required=True, nullable=False, location='json')
args = parser.parse_args()
account = RegisterService.get_account_if_token_valid(args['workspace_id'], args['email'], args['token'])
if account is None:
raise AlreadyActivateError()
RegisterService.revoke_token(args['workspace_id'], args['email'], args['token'])
account.name = args['name']
# generate password salt
salt = secrets.token_bytes(16)
base64_salt = base64.b64encode(salt).decode()
# encrypt password with salt
password_hashed = hash_password(args['password'], salt)
base64_password_hashed = base64.b64encode(password_hashed).decode()
account.password = base64_password_hashed
account.password_salt = base64_salt
account.interface_language = args['interface_language']
account.timezone = args['timezone']
account.interface_theme = 'light'
account.status = AccountStatus.ACTIVE.value
account.initialized_at = datetime.utcnow()
db.session.commit()
return {'result': 'success'}
api.add_resource(ActivateCheckApi, '/activate/check')
api.add_resource(ActivateApi, '/activate')

View File

@ -0,0 +1,101 @@
import logging
from datetime import datetime
from typing import Optional
import flask_login
import requests
from flask import request, redirect, current_app, session
from flask_login import current_user, login_required
from flask_restful import Resource
from werkzeug.exceptions import Forbidden
from libs.oauth_data_source import NotionOAuth
from controllers.console import api
from ..setup import setup_required
from ..wraps import account_initialization_required
def get_oauth_providers():
with current_app.app_context():
notion_oauth = NotionOAuth(client_id=current_app.config.get('NOTION_CLIENT_ID'),
client_secret=current_app.config.get(
'NOTION_CLIENT_SECRET'),
redirect_uri=current_app.config.get(
'CONSOLE_API_URL') + '/console/api/oauth/data-source/callback/notion')
OAUTH_PROVIDERS = {
'notion': notion_oauth
}
return OAUTH_PROVIDERS
class OAuthDataSource(Resource):
def get(self, provider: str):
# The role of the current user in the table must be admin or owner
if current_user.current_tenant.current_role not in ['admin', 'owner']:
raise Forbidden()
OAUTH_DATASOURCE_PROVIDERS = get_oauth_providers()
with current_app.app_context():
oauth_provider = OAUTH_DATASOURCE_PROVIDERS.get(provider)
print(vars(oauth_provider))
if not oauth_provider:
return {'error': 'Invalid provider'}, 400
if current_app.config.get('NOTION_INTEGRATION_TYPE') == 'internal':
internal_secret = current_app.config.get('NOTION_INTERNAL_SECRET')
oauth_provider.save_internal_access_token(internal_secret)
return redirect(f'{current_app.config.get("CONSOLE_WEB_URL")}?oauth_data_source=success')
else:
auth_url = oauth_provider.get_authorization_url()
return redirect(auth_url)
class OAuthDataSourceCallback(Resource):
def get(self, provider: str):
OAUTH_DATASOURCE_PROVIDERS = get_oauth_providers()
with current_app.app_context():
oauth_provider = OAUTH_DATASOURCE_PROVIDERS.get(provider)
if not oauth_provider:
return {'error': 'Invalid provider'}, 400
if 'code' in request.args:
code = request.args.get('code')
try:
oauth_provider.get_access_token(code)
except requests.exceptions.HTTPError as e:
logging.exception(
f"An error occurred during the OAuthCallback process with {provider}: {e.response.text}")
return {'error': 'OAuth data source process failed'}, 400
return redirect(f'{current_app.config.get("CONSOLE_WEB_URL")}?oauth_data_source=success')
elif 'error' in request.args:
error = request.args.get('error')
return redirect(f'{current_app.config.get("CONSOLE_WEB_URL")}?oauth_data_source={error}')
else:
return redirect(f'{current_app.config.get("CONSOLE_WEB_URL")}?oauth_data_source=access_denied')
class OAuthDataSourceSync(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, provider, binding_id):
provider = str(provider)
binding_id = str(binding_id)
OAUTH_DATASOURCE_PROVIDERS = get_oauth_providers()
with current_app.app_context():
oauth_provider = OAUTH_DATASOURCE_PROVIDERS.get(provider)
if not oauth_provider:
return {'error': 'Invalid provider'}, 400
try:
oauth_provider.sync_data_source(binding_id)
except requests.exceptions.HTTPError as e:
logging.exception(
f"An error occurred during the OAuthCallback process with {provider}: {e.response.text}")
return {'error': 'OAuth data source process failed'}, 400
return {'result': 'success'}, 200
api.add_resource(OAuthDataSource, '/oauth/data-source/<string:provider>')
api.add_resource(OAuthDataSourceCallback, '/oauth/data-source/callback/<string:provider>')
api.add_resource(OAuthDataSourceSync, '/oauth/data-source/<string:provider>/<uuid:binding_id>/sync')

View File

@ -20,13 +20,13 @@ def get_oauth_providers():
client_secret=current_app.config.get(
'GITHUB_CLIENT_SECRET'),
redirect_uri=current_app.config.get(
'CONSOLE_URL') + '/console/api/oauth/authorize/github')
'CONSOLE_API_URL') + '/console/api/oauth/authorize/github')
google_oauth = GoogleOAuth(client_id=current_app.config.get('GOOGLE_CLIENT_ID'),
client_secret=current_app.config.get(
'GOOGLE_CLIENT_SECRET'),
redirect_uri=current_app.config.get(
'CONSOLE_URL') + '/console/api/oauth/authorize/google')
'CONSOLE_API_URL') + '/console/api/oauth/authorize/google')
OAUTH_PROVIDERS = {
'github': github_oauth,
@ -80,7 +80,7 @@ class OAuthCallback(Resource):
flask_login.login_user(account, remember=True)
AccountService.update_last_login(account, request)
return redirect(f'{current_app.config.get("CONSOLE_URL")}?oauth_login=success')
return redirect(f'{current_app.config.get("CONSOLE_WEB_URL")}?oauth_login=success')
def _get_account_by_openid_or_email(provider: str, user_info: OAuthUserInfo) -> Optional[Account]:

View File

@ -0,0 +1,304 @@
import datetime
import json
from cachetools import TTLCache
from flask import request, current_app
from flask_login import login_required, current_user
from flask_restful import Resource, marshal_with, fields, reqparse, marshal
from werkzeug.exceptions import NotFound
from controllers.console import api
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.data_loader.loader.notion import NotionLoader
from core.indexing_runner import IndexingRunner
from extensions.ext_database import db
from libs.helper import TimestampField
from models.dataset import Document
from models.source import DataSourceBinding
from services.dataset_service import DatasetService, DocumentService
from tasks.document_indexing_sync_task import document_indexing_sync_task
cache = TTLCache(maxsize=None, ttl=30)
FILE_SIZE_LIMIT = 15 * 1024 * 1024 # 15MB
ALLOWED_EXTENSIONS = ['txt', 'markdown', 'md', 'pdf', 'html', 'htm']
PREVIEW_WORDS_LIMIT = 3000
class DataSourceApi(Resource):
integrate_icon_fields = {
'type': fields.String,
'url': fields.String,
'emoji': fields.String
}
integrate_page_fields = {
'page_name': fields.String,
'page_id': fields.String,
'page_icon': fields.Nested(integrate_icon_fields, allow_null=True),
'parent_id': fields.String,
'type': fields.String
}
integrate_workspace_fields = {
'workspace_name': fields.String,
'workspace_id': fields.String,
'workspace_icon': fields.String,
'pages': fields.List(fields.Nested(integrate_page_fields)),
'total': fields.Integer
}
integrate_fields = {
'id': fields.String,
'provider': fields.String,
'created_at': TimestampField,
'is_bound': fields.Boolean,
'disabled': fields.Boolean,
'link': fields.String,
'source_info': fields.Nested(integrate_workspace_fields)
}
integrate_list_fields = {
'data': fields.List(fields.Nested(integrate_fields)),
}
@setup_required
@login_required
@account_initialization_required
@marshal_with(integrate_list_fields)
def get(self):
# get workspace data source integrates
data_source_integrates = db.session.query(DataSourceBinding).filter(
DataSourceBinding.tenant_id == current_user.current_tenant_id,
DataSourceBinding.disabled == False
).all()
base_url = request.url_root.rstrip('/')
data_source_oauth_base_path = "/console/api/oauth/data-source"
providers = ["notion"]
integrate_data = []
for provider in providers:
# existing_integrate = next((ai for ai in data_source_integrates if ai.provider == provider), None)
existing_integrates = filter(lambda item: item.provider == provider, data_source_integrates)
if existing_integrates:
for existing_integrate in list(existing_integrates):
integrate_data.append({
'id': existing_integrate.id,
'provider': provider,
'created_at': existing_integrate.created_at,
'is_bound': True,
'disabled': existing_integrate.disabled,
'source_info': existing_integrate.source_info,
'link': f'{base_url}{data_source_oauth_base_path}/{provider}'
})
else:
integrate_data.append({
'id': None,
'provider': provider,
'created_at': None,
'source_info': None,
'is_bound': False,
'disabled': None,
'link': f'{base_url}{data_source_oauth_base_path}/{provider}'
})
return {'data': integrate_data}, 200
@setup_required
@login_required
@account_initialization_required
def patch(self, binding_id, action):
binding_id = str(binding_id)
action = str(action)
data_source_binding = DataSourceBinding.query.filter_by(
id=binding_id
).first()
if data_source_binding is None:
raise NotFound('Data source binding not found.')
# enable binding
if action == 'enable':
if data_source_binding.disabled:
data_source_binding.disabled = False
data_source_binding.updated_at = datetime.datetime.utcnow()
db.session.add(data_source_binding)
db.session.commit()
else:
raise ValueError('Data source is not disabled.')
# disable binding
if action == 'disable':
if not data_source_binding.disabled:
data_source_binding.disabled = True
data_source_binding.updated_at = datetime.datetime.utcnow()
db.session.add(data_source_binding)
db.session.commit()
else:
raise ValueError('Data source is disabled.')
return {'result': 'success'}, 200
class DataSourceNotionListApi(Resource):
integrate_icon_fields = {
'type': fields.String,
'url': fields.String,
'emoji': fields.String
}
integrate_page_fields = {
'page_name': fields.String,
'page_id': fields.String,
'page_icon': fields.Nested(integrate_icon_fields, allow_null=True),
'is_bound': fields.Boolean,
'parent_id': fields.String,
'type': fields.String
}
integrate_workspace_fields = {
'workspace_name': fields.String,
'workspace_id': fields.String,
'workspace_icon': fields.String,
'pages': fields.List(fields.Nested(integrate_page_fields))
}
integrate_notion_info_list_fields = {
'notion_info': fields.List(fields.Nested(integrate_workspace_fields)),
}
@setup_required
@login_required
@account_initialization_required
@marshal_with(integrate_notion_info_list_fields)
def get(self):
dataset_id = request.args.get('dataset_id', default=None, type=str)
exist_page_ids = []
# import notion in the exist dataset
if dataset_id:
dataset = DatasetService.get_dataset(dataset_id)
if not dataset:
raise NotFound('Dataset not found.')
if dataset.data_source_type != 'notion_import':
raise ValueError('Dataset is not notion type.')
documents = Document.query.filter_by(
dataset_id=dataset_id,
tenant_id=current_user.current_tenant_id,
data_source_type='notion_import',
enabled=True
).all()
if documents:
for document in documents:
data_source_info = json.loads(document.data_source_info)
exist_page_ids.append(data_source_info['notion_page_id'])
# get all authorized pages
data_source_bindings = DataSourceBinding.query.filter_by(
tenant_id=current_user.current_tenant_id,
provider='notion',
disabled=False
).all()
if not data_source_bindings:
return {
'notion_info': []
}, 200
pre_import_info_list = []
for data_source_binding in data_source_bindings:
source_info = data_source_binding.source_info
pages = source_info['pages']
# Filter out already bound pages
for page in pages:
if page['page_id'] in exist_page_ids:
page['is_bound'] = True
else:
page['is_bound'] = False
pre_import_info = {
'workspace_name': source_info['workspace_name'],
'workspace_icon': source_info['workspace_icon'],
'workspace_id': source_info['workspace_id'],
'pages': pages,
}
pre_import_info_list.append(pre_import_info)
return {
'notion_info': pre_import_info_list
}, 200
class DataSourceNotionApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, workspace_id, page_id, page_type):
workspace_id = str(workspace_id)
page_id = str(page_id)
data_source_binding = DataSourceBinding.query.filter(
db.and_(
DataSourceBinding.tenant_id == current_user.current_tenant_id,
DataSourceBinding.provider == 'notion',
DataSourceBinding.disabled == False,
DataSourceBinding.source_info['workspace_id'] == f'"{workspace_id}"'
)
).first()
if not data_source_binding:
raise NotFound('Data source binding not found.')
loader = NotionLoader(
notion_access_token=data_source_binding.access_token,
notion_workspace_id=workspace_id,
notion_obj_id=page_id,
notion_page_type=page_type
)
text_docs = loader.load()
return {
'content': "\n".join([doc.page_content for doc in text_docs])
}, 200
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('notion_info_list', type=list, required=True, nullable=True, location='json')
parser.add_argument('process_rule', type=dict, required=True, nullable=True, location='json')
args = parser.parse_args()
# validate args
DocumentService.estimate_args_validate(args)
indexing_runner = IndexingRunner()
response = indexing_runner.notion_indexing_estimate(args['notion_info_list'], args['process_rule'])
return response, 200
class DataSourceNotionDatasetSyncApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id):
dataset_id_str = str(dataset_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
documents = DocumentService.get_document_by_dataset_id(dataset_id_str)
for document in documents:
document_indexing_sync_task.delay(dataset_id_str, document.id)
return 200
class DataSourceNotionDocumentSyncApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id, document_id):
dataset_id_str = str(dataset_id)
document_id_str = str(document_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
document = DocumentService.get_document(dataset_id_str, document_id_str)
if document is None:
raise NotFound("Document not found.")
document_indexing_sync_task.delay(dataset_id_str, document_id_str)
return 200
api.add_resource(DataSourceApi, '/data-source/integrates', '/data-source/integrates/<uuid:binding_id>/<string:action>')
api.add_resource(DataSourceNotionListApi, '/notion/pre-import/pages')
api.add_resource(DataSourceNotionApi,
'/notion/workspaces/<uuid:workspace_id>/pages/<uuid:page_id>/<string:page_type>/preview',
'/datasets/notion-indexing-estimate')
api.add_resource(DataSourceNotionDatasetSyncApi, '/datasets/<uuid:dataset_id>/notion/sync')
api.add_resource(DataSourceNotionDocumentSyncApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/notion/sync')

View File

@ -3,7 +3,6 @@ from flask import request
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, fields, marshal, marshal_with
from werkzeug.exceptions import NotFound, Forbidden
import services
from controllers.console import api
from controllers.console.datasets.error import DatasetNameDuplicateError
@ -12,8 +11,9 @@ from controllers.console.wraps import account_initialization_required
from core.indexing_runner import IndexingRunner
from libs.helper import TimestampField
from extensions.ext_database import db
from models.dataset import DocumentSegment, Document
from models.model import UploadFile
from services.dataset_service import DatasetService
from services.dataset_service import DatasetService, DocumentService
dataset_detail_fields = {
'id': fields.String,
@ -50,8 +50,8 @@ def _validate_name(name):
def _validate_description_length(description):
if len(description) > 200:
raise ValueError('Description cannot exceed 200 characters.')
if len(description) > 400:
raise ValueError('Description cannot exceed 400 characters.')
return description
@ -217,17 +217,31 @@ class DatasetIndexingEstimateApi(Resource):
@login_required
@account_initialization_required
def post(self):
segment_rule = request.get_json()
file_detail = db.session.query(UploadFile).filter(
UploadFile.tenant_id == current_user.current_tenant_id,
UploadFile.id == segment_rule["file_id"]
).first()
parser = reqparse.RequestParser()
parser.add_argument('info_list', type=dict, required=True, nullable=True, location='json')
parser.add_argument('process_rule', type=dict, required=True, nullable=True, location='json')
args = parser.parse_args()
# validate args
DocumentService.estimate_args_validate(args)
if args['info_list']['data_source_type'] == 'upload_file':
file_ids = args['info_list']['file_info_list']['file_ids']
file_details = db.session.query(UploadFile).filter(
UploadFile.tenant_id == current_user.current_tenant_id,
UploadFile.id.in_(file_ids)
).all()
if file_detail is None:
raise NotFound("File not found.")
if file_details is None:
raise NotFound("File not found.")
indexing_runner = IndexingRunner()
response = indexing_runner.indexing_estimate(file_detail, segment_rule['process_rule'])
indexing_runner = IndexingRunner()
response = indexing_runner.file_indexing_estimate(file_details, args['process_rule'])
elif args['info_list']['data_source_type'] == 'notion_import':
indexing_runner = IndexingRunner()
response = indexing_runner.notion_indexing_estimate(args['info_list']['notion_info_list'],
args['process_rule'])
else:
raise ValueError('Data source type not support')
return response, 200
@ -274,8 +288,54 @@ class DatasetRelatedAppListApi(Resource):
}, 200
class DatasetIndexingStatusApi(Resource):
document_status_fields = {
'id': fields.String,
'indexing_status': fields.String,
'processing_started_at': TimestampField,
'parsing_completed_at': TimestampField,
'cleaning_completed_at': TimestampField,
'splitting_completed_at': TimestampField,
'completed_at': TimestampField,
'paused_at': TimestampField,
'error': fields.String,
'stopped_at': TimestampField,
'completed_segments': fields.Integer,
'total_segments': fields.Integer,
}
document_status_fields_list = {
'data': fields.List(fields.Nested(document_status_fields))
}
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id):
dataset_id = str(dataset_id)
documents = db.session.query(Document).filter(
Document.dataset_id == dataset_id,
Document.tenant_id == current_user.current_tenant_id
).all()
documents_status = []
for document in documents:
completed_segments = DocumentSegment.query.filter(DocumentSegment.completed_at.isnot(None),
DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
total_segments = DocumentSegment.query.filter(DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
document.completed_segments = completed_segments
document.total_segments = total_segments
documents_status.append(marshal(document, self.document_status_fields))
data = {
'data': documents_status
}
return data
api.add_resource(DatasetListApi, '/datasets')
api.add_resource(DatasetApi, '/datasets/<uuid:dataset_id>')
api.add_resource(DatasetQueryApi, '/datasets/<uuid:dataset_id>/queries')
api.add_resource(DatasetIndexingEstimateApi, '/datasets/file-indexing-estimate')
api.add_resource(DatasetIndexingEstimateApi, '/datasets/indexing-estimate')
api.add_resource(DatasetRelatedAppListApi, '/datasets/<uuid:dataset_id>/related-apps')
api.add_resource(DatasetIndexingStatusApi, '/datasets/<uuid:dataset_id>/indexing-status')

View File

@ -1,6 +1,7 @@
# -*- coding:utf-8 -*-
import random
from datetime import datetime
from typing import List
from flask import request
from flask_login import login_required, current_user
@ -10,13 +11,14 @@ from werkzeug.exceptions import NotFound, Forbidden
import services
from controllers.console import api
from controllers.console.app.error import ProviderNotInitializeError
from controllers.console.app.error import ProviderNotInitializeError, ProviderQuotaExceededError, \
ProviderModelCurrentlyNotSupportError
from controllers.console.datasets.error import DocumentAlreadyFinishedError, InvalidActionError, DocumentIndexingError, \
InvalidMetadataError, ArchivedDocumentImmutableError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.indexing_runner import IndexingRunner
from core.llm.error import ProviderTokenNotInitError
from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from extensions.ext_redis import redis_client
from libs.helper import TimestampField
from extensions.ext_database import db
@ -60,6 +62,29 @@ document_fields = {
'hit_count': fields.Integer,
}
document_with_segments_fields = {
'id': fields.String,
'position': fields.Integer,
'data_source_type': fields.String,
'data_source_info': fields.Raw(attribute='data_source_info_dict'),
'dataset_process_rule_id': fields.String,
'name': fields.String,
'created_from': fields.String,
'created_by': fields.String,
'created_at': TimestampField,
'tokens': fields.Integer,
'indexing_status': fields.String,
'error': fields.String,
'enabled': fields.Boolean,
'disabled_at': TimestampField,
'disabled_by': fields.String,
'archived': fields.Boolean,
'display_status': fields.String,
'word_count': fields.Integer,
'hit_count': fields.Integer,
'completed_segments': fields.Integer,
'total_segments': fields.Integer
}
class DocumentResource(Resource):
def get_document(self, dataset_id: str, document_id: str) -> Document:
@ -82,6 +107,23 @@ class DocumentResource(Resource):
return document
def get_batch_documents(self, dataset_id: str, batch: str) -> List[Document]:
dataset = DatasetService.get_dataset(dataset_id)
if not dataset:
raise NotFound('Dataset not found.')
try:
DatasetService.check_dataset_permission(dataset, current_user)
except services.errors.account.NoPermissionError as e:
raise Forbidden(str(e))
documents = DocumentService.get_batch_documents(dataset_id, batch)
if not documents:
raise NotFound('Documents not found.')
return documents
class GetProcessRuleApi(Resource):
@setup_required
@ -131,9 +173,9 @@ class DatasetDocumentListApi(Resource):
dataset_id = str(dataset_id)
page = request.args.get('page', default=1, type=int)
limit = request.args.get('limit', default=20, type=int)
search = request.args.get('search', default=None, type=str)
search = request.args.get('keyword', default=None, type=str)
sort = request.args.get('sort', default='-created_at', type=str)
fetch = request.args.get('fetch', default=False, type=bool)
dataset = DatasetService.get_dataset(dataset_id)
if not dataset:
raise NotFound('Dataset not found.')
@ -172,9 +214,20 @@ class DatasetDocumentListApi(Resource):
paginated_documents = query.paginate(
page=page, per_page=limit, max_per_page=100, error_out=False)
documents = paginated_documents.items
if fetch:
for document in documents:
completed_segments = DocumentSegment.query.filter(DocumentSegment.completed_at.isnot(None),
DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
total_segments = DocumentSegment.query.filter(DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
document.completed_segments = completed_segments
document.total_segments = total_segments
data = marshal(documents, document_with_segments_fields)
else:
data = marshal(documents, document_fields)
response = {
'data': marshal(documents, document_fields),
'data': data,
'has_more': len(documents) == limit,
'limit': limit,
'total': paginated_documents.total,
@ -183,10 +236,15 @@ class DatasetDocumentListApi(Resource):
return response
documents_and_batch_fields = {
'documents': fields.List(fields.Nested(document_fields)),
'batch': fields.String
}
@setup_required
@login_required
@account_initialization_required
@marshal_with(document_fields)
@marshal_with(documents_and_batch_fields)
def post(self, dataset_id):
dataset_id = str(dataset_id)
@ -207,9 +265,10 @@ class DatasetDocumentListApi(Resource):
parser = reqparse.RequestParser()
parser.add_argument('indexing_technique', type=str, choices=Dataset.INDEXING_TECHNIQUE_LIST, nullable=False,
location='json')
parser.add_argument('data_source', type=dict, required=True, nullable=True, location='json')
parser.add_argument('process_rule', type=dict, required=True, nullable=True, location='json')
parser.add_argument('data_source', type=dict, required=False, location='json')
parser.add_argument('process_rule', type=dict, required=False, location='json')
parser.add_argument('duplicate', type=bool, nullable=False, location='json')
parser.add_argument('original_document_id', type=str, required=False, location='json')
args = parser.parse_args()
if not dataset.indexing_technique and not args['indexing_technique']:
@ -219,17 +278,25 @@ class DatasetDocumentListApi(Resource):
DocumentService.document_create_args_validate(args)
try:
document = DocumentService.save_document_with_dataset_id(dataset, args, current_user)
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
documents, batch = DocumentService.save_document_with_dataset_id(dataset, args, current_user)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
return document
return {
'documents': documents,
'batch': batch
}
class DatasetInitApi(Resource):
dataset_and_document_fields = {
'dataset': fields.Nested(dataset_fields),
'document': fields.Nested(document_fields)
'documents': fields.List(fields.Nested(document_fields)),
'batch': fields.String
}
@setup_required
@ -252,17 +319,22 @@ class DatasetInitApi(Resource):
DocumentService.document_create_args_validate(args)
try:
dataset, document = DocumentService.save_document_without_dataset_id(
dataset, documents, batch = DocumentService.save_document_without_dataset_id(
tenant_id=current_user.current_tenant_id,
document_data=args,
account=current_user
)
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
response = {
'dataset': dataset,
'document': document
'documents': documents,
'batch': batch
}
return response
@ -307,11 +379,122 @@ class DocumentIndexingEstimateApi(DocumentResource):
raise NotFound('File not found.')
indexing_runner = IndexingRunner()
response = indexing_runner.indexing_estimate(file, data_process_rule_dict)
response = indexing_runner.file_indexing_estimate([file], data_process_rule_dict)
return response
class DocumentBatchIndexingEstimateApi(DocumentResource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id, batch):
dataset_id = str(dataset_id)
batch = str(batch)
dataset = DatasetService.get_dataset(dataset_id)
if dataset is None:
raise NotFound("Dataset not found.")
documents = self.get_batch_documents(dataset_id, batch)
response = {
"tokens": 0,
"total_price": 0,
"currency": "USD",
"total_segments": 0,
"preview": []
}
if not documents:
return response
data_process_rule = documents[0].dataset_process_rule
data_process_rule_dict = data_process_rule.to_dict()
info_list = []
for document in documents:
if document.indexing_status in ['completed', 'error']:
raise DocumentAlreadyFinishedError()
data_source_info = document.data_source_info_dict
# format document files info
if data_source_info and 'upload_file_id' in data_source_info:
file_id = data_source_info['upload_file_id']
info_list.append(file_id)
# format document notion info
elif data_source_info and 'notion_workspace_id' in data_source_info and 'notion_page_id' in data_source_info:
pages = []
page = {
'page_id': data_source_info['notion_page_id'],
'type': data_source_info['type']
}
pages.append(page)
notion_info = {
'workspace_id': data_source_info['notion_workspace_id'],
'pages': pages
}
info_list.append(notion_info)
if dataset.data_source_type == 'upload_file':
file_details = db.session.query(UploadFile).filter(
UploadFile.tenant_id == current_user.current_tenant_id,
UploadFile.id in info_list
).all()
if file_details is None:
raise NotFound("File not found.")
indexing_runner = IndexingRunner()
response = indexing_runner.file_indexing_estimate(file_details, data_process_rule_dict)
elif dataset.data_source_type:
indexing_runner = IndexingRunner()
response = indexing_runner.notion_indexing_estimate(info_list,
data_process_rule_dict)
else:
raise ValueError('Data source type not support')
return response
class DocumentBatchIndexingStatusApi(DocumentResource):
document_status_fields = {
'id': fields.String,
'indexing_status': fields.String,
'processing_started_at': TimestampField,
'parsing_completed_at': TimestampField,
'cleaning_completed_at': TimestampField,
'splitting_completed_at': TimestampField,
'completed_at': TimestampField,
'paused_at': TimestampField,
'error': fields.String,
'stopped_at': TimestampField,
'completed_segments': fields.Integer,
'total_segments': fields.Integer,
}
document_status_fields_list = {
'data': fields.List(fields.Nested(document_status_fields))
}
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id, batch):
dataset_id = str(dataset_id)
batch = str(batch)
documents = self.get_batch_documents(dataset_id, batch)
documents_status = []
for document in documents:
completed_segments = DocumentSegment.query.filter(DocumentSegment.completed_at.isnot(None),
DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
total_segments = DocumentSegment.query.filter(DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
document.completed_segments = completed_segments
document.total_segments = total_segments
documents_status.append(marshal(document, self.document_status_fields))
data = {
'data': documents_status
}
return data
class DocumentIndexingStatusApi(DocumentResource):
document_status_fields = {
'id': fields.String,
@ -338,10 +521,12 @@ class DocumentIndexingStatusApi(DocumentResource):
completed_segments = DocumentSegment.query \
.filter(DocumentSegment.completed_at.isnot(None),
DocumentSegment.document_id == str(document_id)) \
DocumentSegment.document_id == str(document_id),
DocumentSegment.status != 're_segment') \
.count()
total_segments = DocumentSegment.query \
.filter_by(document_id=str(document_id)) \
.filter(DocumentSegment.document_id == str(document_id),
DocumentSegment.status != 're_segment') \
.count()
document.completed_segments = completed_segments
@ -396,7 +581,7 @@ class DocumentDetailApi(DocumentResource):
'disabled_by': document.disabled_by,
'archived': document.archived,
'segment_count': document.segment_count,
'average_segment_length': document.average_segment_length,
'average_segment_length': document.average_segment_length,
'hit_count': document.hit_count,
'display_status': document.display_status
}
@ -416,7 +601,7 @@ class DocumentDetailApi(DocumentResource):
'created_at': document.created_at.timestamp(),
'tokens': document.tokens,
'indexing_status': document.indexing_status,
'completed_at': int(document.completed_at.timestamp())if document.completed_at else None,
'completed_at': int(document.completed_at.timestamp()) if document.completed_at else None,
'updated_at': int(document.updated_at.timestamp()) if document.updated_at else None,
'indexing_latency': document.indexing_latency,
'error': document.error,
@ -567,6 +752,8 @@ class DocumentStatusApi(DocumentResource):
return {'result': 'success'}, 200
elif action == "disable":
if not document.completed_at or document.indexing_status != 'completed':
raise InvalidActionError('Document is not completed.')
if not document.enabled:
raise InvalidActionError('Document already disabled.')
@ -666,6 +853,10 @@ api.add_resource(DatasetInitApi,
'/datasets/init')
api.add_resource(DocumentIndexingEstimateApi,
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/indexing-estimate')
api.add_resource(DocumentBatchIndexingEstimateApi,
'/datasets/<uuid:dataset_id>/batch/<string:batch>/indexing-estimate')
api.add_resource(DocumentBatchIndexingStatusApi,
'/datasets/<uuid:dataset_id>/batch/<string:batch>/indexing-status')
api.add_resource(DocumentIndexingStatusApi,
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/indexing-status')
api.add_resource(DocumentDetailApi,

View File

@ -78,12 +78,14 @@ class DatasetDocumentSegmentListApi(Resource):
parser.add_argument('hit_count_gte', type=int,
default=None, location='args')
parser.add_argument('enabled', type=str, default='all', location='args')
parser.add_argument('keyword', type=str, default=None, location='args')
args = parser.parse_args()
last_id = args['last_id']
limit = min(args['limit'], 100)
status_list = args['status']
hit_count_gte = args['hit_count_gte']
keyword = args['keyword']
query = DocumentSegment.query.filter(
DocumentSegment.document_id == str(document_id),
@ -104,6 +106,9 @@ class DatasetDocumentSegmentListApi(Resource):
if hit_count_gte is not None:
query = query.filter(DocumentSegment.hit_count >= hit_count_gte)
if keyword:
query = query.where(DocumentSegment.content.ilike(f'%{keyword}%'))
if args['enabled'].lower() != 'all':
if args['enabled'].lower() == 'true':
query = query.filter(DocumentSegment.enabled == True)

View File

@ -3,7 +3,7 @@ from libs.exception import BaseHTTPException
class NoFileUploadedError(BaseHTTPException):
error_code = 'no_file_uploaded'
description = "No file uploaded."
description = "Please upload your file."
code = 400
@ -27,25 +27,25 @@ class UnsupportedFileTypeError(BaseHTTPException):
class HighQualityDatasetOnlyError(BaseHTTPException):
error_code = 'high_quality_dataset_only'
description = "High quality dataset only."
description = "Current operation only supports 'high-quality' datasets."
code = 400
class DatasetNotInitializedError(BaseHTTPException):
error_code = 'dataset_not_initialized'
description = "Dataset not initialized."
description = "The dataset is still being initialized or indexing. Please wait a moment."
code = 400
class ArchivedDocumentImmutableError(BaseHTTPException):
error_code = 'archived_document_immutable'
description = "Cannot process an archived document."
description = "The archived document is not editable."
code = 403
class DatasetNameDuplicateError(BaseHTTPException):
error_code = 'dataset_name_duplicate'
description = "Dataset name already exists."
description = "The dataset name already exists. Please modify your dataset name."
code = 409
@ -57,17 +57,17 @@ class InvalidActionError(BaseHTTPException):
class DocumentAlreadyFinishedError(BaseHTTPException):
error_code = 'document_already_finished'
description = "Document already finished."
description = "The document has been processed. Please refresh the page or go to the document details."
code = 400
class DocumentIndexingError(BaseHTTPException):
error_code = 'document_indexing'
description = "Document indexing."
description = "The document is being processed and cannot be edited."
code = 400
class InvalidMetadataError(BaseHTTPException):
error_code = 'invalid_metadata'
description = "Invalid metadata."
description = "The metadata content is incorrect. Please check and verify."
code = 400

View File

@ -1,6 +1,7 @@
import datetime
import hashlib
import tempfile
import chardet
import time
import uuid
from pathlib import Path
@ -16,8 +17,7 @@ from controllers.console.datasets.error import NoFileUploadedError, TooManyFiles
UnsupportedFileTypeError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.index.readers.html_parser import HTMLParser
from core.index.readers.pdf_parser import PDFParser
from core.data_loader.file_extractor import FileExtractor
from extensions.ext_storage import storage
from libs.helper import TimestampField
from extensions.ext_database import db
@ -26,7 +26,7 @@ from models.model import UploadFile
cache = TTLCache(maxsize=None, ttl=30)
FILE_SIZE_LIMIT = 15 * 1024 * 1024 # 15MB
ALLOWED_EXTENSIONS = ['txt', 'markdown', 'md', 'pdf', 'html', 'htm']
ALLOWED_EXTENSIONS = ['txt', 'markdown', 'md', 'pdf', 'html', 'htm', 'xlsx']
PREVIEW_WORDS_LIMIT = 3000
@ -121,24 +121,7 @@ class FilePreviewApi(Resource):
if extension not in ALLOWED_EXTENSIONS:
raise UnsupportedFileTypeError()
with tempfile.TemporaryDirectory() as temp_dir:
suffix = Path(upload_file.key).suffix
filepath = f"{temp_dir}/{next(tempfile._get_candidate_names())}{suffix}"
storage.download(upload_file.key, filepath)
if extension == 'pdf':
parser = PDFParser({'upload_file': upload_file})
text = parser.parse_file(Path(filepath))
elif extension in ['html', 'htm']:
# Use BeautifulSoup to extract text
parser = HTMLParser()
text = parser.parse_file(Path(filepath))
else:
# ['txt', 'markdown', 'md']
with open(filepath, "rb") as fp:
data = fp.read()
text = data.decode(encoding='utf-8').strip() if data else ''
text = FileExtractor.load(upload_file, return_text=True)
text = text[0:PREVIEW_WORDS_LIMIT] if text else ''
return {'content': text}

View File

@ -6,9 +6,12 @@ from werkzeug.exceptions import InternalServerError, NotFound, Forbidden
import services
from controllers.console import api
from controllers.console.app.error import ProviderNotInitializeError, ProviderQuotaExceededError, \
ProviderModelCurrentlyNotSupportError
from controllers.console.datasets.error import HighQualityDatasetOnlyError, DatasetNotInitializedError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from libs.helper import TimestampField
from services.dataset_service import DatasetService
from services.hit_testing_service import HitTestingService
@ -92,6 +95,12 @@ class HitTestingApi(Resource):
return {"query": response['query'], 'records': marshal(response['records'], hit_testing_record_fields)}
except services.errors.index.IndexNotInitializedError:
raise DatasetNotInitializedError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except Exception as e:
logging.exception("Hit testing failed.")
raise InternalServerError(str(e))

View File

@ -3,13 +3,14 @@ from libs.exception import BaseHTTPException
class AlreadySetupError(BaseHTTPException):
error_code = 'already_setup'
description = "Application already setup."
description = "Dify has been successfully installed. Please refresh the page or return to the dashboard homepage."
code = 403
class NotSetupError(BaseHTTPException):
error_code = 'not_setup'
description = "Application not setup."
description = "Dify has not been initialized and installed yet. " \
"Please proceed with the initialization and installation process first."
code = 401
@ -17,3 +18,9 @@ class AccountNotLinkTenantError(BaseHTTPException):
error_code = 'account_not_link_tenant'
description = "Account not link tenant."
code = 403
class AlreadyActivateError(BaseHTTPException):
error_code = 'already_activate'
description = "Auth Token is invalid or account already activated, please check again."
code = 403

View File

@ -0,0 +1,66 @@
# -*- coding:utf-8 -*-
import logging
from flask import request
from werkzeug.exceptions import InternalServerError
import services
from controllers.console import api
from controllers.console.app.error import AppUnavailableError, ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError, \
NoAudioUploadedError, AudioTooLargeError, \
UnsupportedAudioTypeError, ProviderNotSupportSpeechToTextError
from controllers.console.explore.wraps import InstalledAppResource
from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from services.audio_service import AudioService
from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
from models.model import AppModelConfig
class ChatAudioApi(InstalledAppResource):
def post(self, installed_app):
app_model = installed_app.app
app_model_config: AppModelConfig = app_model.app_model_config
if not app_model_config.speech_to_text_dict['enabled']:
raise AppUnavailableError()
file = request.files['file']
try:
response = AudioService.transcript(
tenant_id=app_model.tenant_id,
file=file,
)
return response
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except NoAudioUploadedServiceError:
raise NoAudioUploadedError()
except AudioTooLargeServiceError as e:
raise AudioTooLargeError(str(e))
except UnsupportedAudioTypeServiceError:
raise UnsupportedAudioTypeError()
except ProviderNotSupportSpeechToTextServiceError:
raise ProviderNotSupportSpeechToTextError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
api.add_resource(ChatAudioApi, '/installed-apps/<uuid:installed_app_id>/audio-to-text', endpoint='installed_app_audio')

View File

@ -0,0 +1,180 @@
# -*- coding:utf-8 -*-
import json
import logging
from typing import Generator, Union
from flask import Response, stream_with_context
from flask_login import current_user
from flask_restful import reqparse
from werkzeug.exceptions import InternalServerError, NotFound
import services
from controllers.console import api
from controllers.console.app.error import ConversationCompletedError, AppUnavailableError, ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
from controllers.console.explore.error import NotCompletionAppError, NotChatAppError
from controllers.console.explore.wraps import InstalledAppResource
from core.conversation_message_task import PubHandler
from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from libs.helper import uuid_value
from services.completion_service import CompletionService
# define completion api for user
class CompletionApi(InstalledAppResource):
def post(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'completion':
raise NotCompletionAppError()
parser = reqparse.RequestParser()
parser.add_argument('inputs', type=dict, required=True, location='json')
parser.add_argument('query', type=str, location='json')
parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
args = parser.parse_args()
streaming = args['response_mode'] == 'streaming'
try:
response = CompletionService.completion(
app_model=app_model,
user=current_user,
args=args,
from_source='console',
streaming=streaming
)
return compact_response(response)
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.conversation.ConversationCompletedError:
raise ConversationCompletedError()
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
class CompletionStopApi(InstalledAppResource):
def post(self, installed_app, task_id):
app_model = installed_app.app
if app_model.mode != 'completion':
raise NotCompletionAppError()
PubHandler.stop(current_user, task_id)
return {'result': 'success'}, 200
class ChatApi(InstalledAppResource):
def post(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
parser = reqparse.RequestParser()
parser.add_argument('inputs', type=dict, required=True, location='json')
parser.add_argument('query', type=str, required=True, location='json')
parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
parser.add_argument('conversation_id', type=uuid_value, location='json')
args = parser.parse_args()
streaming = args['response_mode'] == 'streaming'
try:
response = CompletionService.completion(
app_model=app_model,
user=current_user,
args=args,
from_source='console',
streaming=streaming
)
return compact_response(response)
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.conversation.ConversationCompletedError:
raise ConversationCompletedError()
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
class ChatStopApi(InstalledAppResource):
def post(self, installed_app, task_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
PubHandler.stop(current_user, task_id)
return {'result': 'success'}, 200
def compact_response(response: Union[dict | Generator]) -> Response:
if isinstance(response, dict):
return Response(response=json.dumps(response), status=200, mimetype='application/json')
else:
def generate() -> Generator:
try:
for chunk in response:
yield chunk
except services.errors.conversation.ConversationNotExistsError:
yield "data: " + json.dumps(api.handle_error(NotFound("Conversation Not Exists.")).get_json()) + "\n\n"
except services.errors.conversation.ConversationCompletedError:
yield "data: " + json.dumps(api.handle_error(ConversationCompletedError()).get_json()) + "\n\n"
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:
yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
except ValueError as e:
yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
except Exception:
logging.exception("internal server error.")
yield "data: " + json.dumps(api.handle_error(InternalServerError()).get_json()) + "\n\n"
return Response(stream_with_context(generate()), status=200,
mimetype='text/event-stream')
api.add_resource(CompletionApi, '/installed-apps/<uuid:installed_app_id>/completion-messages', endpoint='installed_app_completion')
api.add_resource(CompletionStopApi, '/installed-apps/<uuid:installed_app_id>/completion-messages/<string:task_id>/stop', endpoint='installed_app_stop_completion')
api.add_resource(ChatApi, '/installed-apps/<uuid:installed_app_id>/chat-messages', endpoint='installed_app_chat_completion')
api.add_resource(ChatStopApi, '/installed-apps/<uuid:installed_app_id>/chat-messages/<string:task_id>/stop', endpoint='installed_app_stop_chat_completion')

View File

@ -0,0 +1,130 @@
# -*- coding:utf-8 -*-
from flask_login import current_user
from flask_restful import fields, reqparse, marshal_with
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound
from controllers.console import api
from controllers.console.explore.error import NotChatAppError
from controllers.console.explore.wraps import InstalledAppResource
from libs.helper import TimestampField, uuid_value
from services.conversation_service import ConversationService
from services.errors.conversation import LastConversationNotExistsError, ConversationNotExistsError
from services.web_conversation_service import WebConversationService
conversation_fields = {
'id': fields.String,
'name': fields.String,
'inputs': fields.Raw,
'status': fields.String,
'introduction': fields.String,
'created_at': TimestampField
}
conversation_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
'data': fields.List(fields.Nested(conversation_fields))
}
class ConversationListApi(InstalledAppResource):
@marshal_with(conversation_infinite_scroll_pagination_fields)
def get(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
parser = reqparse.RequestParser()
parser.add_argument('last_id', type=uuid_value, location='args')
parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
parser.add_argument('pinned', type=str, choices=['true', 'false', None], location='args')
args = parser.parse_args()
pinned = None
if 'pinned' in args and args['pinned'] is not None:
pinned = True if args['pinned'] == 'true' else False
try:
return WebConversationService.pagination_by_last_id(
app_model=app_model,
user=current_user,
last_id=args['last_id'],
limit=args['limit'],
pinned=pinned
)
except LastConversationNotExistsError:
raise NotFound("Last Conversation Not Exists.")
class ConversationApi(InstalledAppResource):
def delete(self, installed_app, c_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
conversation_id = str(c_id)
try:
ConversationService.delete(app_model, conversation_id, current_user)
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
WebConversationService.unpin(app_model, conversation_id, current_user)
return {"result": "success"}, 204
class ConversationRenameApi(InstalledAppResource):
@marshal_with(conversation_fields)
def post(self, installed_app, c_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
conversation_id = str(c_id)
parser = reqparse.RequestParser()
parser.add_argument('name', type=str, required=True, location='json')
args = parser.parse_args()
try:
return ConversationService.rename(app_model, conversation_id, current_user, args['name'])
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
class ConversationPinApi(InstalledAppResource):
def patch(self, installed_app, c_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
conversation_id = str(c_id)
try:
WebConversationService.pin(app_model, conversation_id, current_user)
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
return {"result": "success"}
class ConversationUnPinApi(InstalledAppResource):
def patch(self, installed_app, c_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
conversation_id = str(c_id)
WebConversationService.unpin(app_model, conversation_id, current_user)
return {"result": "success"}
api.add_resource(ConversationRenameApi, '/installed-apps/<uuid:installed_app_id>/conversations/<uuid:c_id>/name', endpoint='installed_app_conversation_rename')
api.add_resource(ConversationListApi, '/installed-apps/<uuid:installed_app_id>/conversations', endpoint='installed_app_conversations')
api.add_resource(ConversationApi, '/installed-apps/<uuid:installed_app_id>/conversations/<uuid:c_id>', endpoint='installed_app_conversation')
api.add_resource(ConversationPinApi, '/installed-apps/<uuid:installed_app_id>/conversations/<uuid:c_id>/pin', endpoint='installed_app_conversation_pin')
api.add_resource(ConversationUnPinApi, '/installed-apps/<uuid:installed_app_id>/conversations/<uuid:c_id>/unpin', endpoint='installed_app_conversation_unpin')

View File

@ -0,0 +1,20 @@
# -*- coding:utf-8 -*-
from libs.exception import BaseHTTPException
class NotCompletionAppError(BaseHTTPException):
error_code = 'not_completion_app'
description = "Not Completion App"
code = 400
class NotChatAppError(BaseHTTPException):
error_code = 'not_chat_app'
description = "Not Chat App"
code = 400
class AppSuggestedQuestionsAfterAnswerDisabledError(BaseHTTPException):
error_code = 'app_suggested_questions_after_answer_disabled'
description = "Function Suggested questions after answer disabled."
code = 403

View File

@ -0,0 +1,143 @@
# -*- coding:utf-8 -*-
from datetime import datetime
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, fields, marshal_with, inputs
from sqlalchemy import and_
from werkzeug.exceptions import NotFound, Forbidden, BadRequest
from controllers.console import api
from controllers.console.explore.wraps import InstalledAppResource
from controllers.console.wraps import account_initialization_required
from extensions.ext_database import db
from libs.helper import TimestampField
from models.model import App, InstalledApp, RecommendedApp
from services.account_service import TenantService
app_fields = {
'id': fields.String,
'name': fields.String,
'mode': fields.String,
'icon': fields.String,
'icon_background': fields.String
}
installed_app_fields = {
'id': fields.String,
'app': fields.Nested(app_fields),
'app_owner_tenant_id': fields.String,
'is_pinned': fields.Boolean,
'last_used_at': TimestampField,
'editable': fields.Boolean,
'uninstallable': fields.Boolean,
}
installed_app_list_fields = {
'installed_apps': fields.List(fields.Nested(installed_app_fields))
}
class InstalledAppsListApi(Resource):
@login_required
@account_initialization_required
@marshal_with(installed_app_list_fields)
def get(self):
current_tenant_id = current_user.current_tenant_id
installed_apps = db.session.query(InstalledApp).filter(
InstalledApp.tenant_id == current_tenant_id
).all()
current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
installed_apps = [
{
'id': installed_app.id,
'app': installed_app.app,
'app_owner_tenant_id': installed_app.app_owner_tenant_id,
'is_pinned': installed_app.is_pinned,
'last_used_at': installed_app.last_used_at,
"editable": current_user.role in ["owner", "admin"],
"uninstallable": current_tenant_id == installed_app.app_owner_tenant_id
}
for installed_app in installed_apps
]
installed_apps.sort(key=lambda app: (-app['is_pinned'], app['last_used_at']
if app['last_used_at'] is not None else datetime.min))
return {'installed_apps': installed_apps}
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('app_id', type=str, required=True, help='Invalid app_id')
args = parser.parse_args()
recommended_app = RecommendedApp.query.filter(RecommendedApp.app_id == args['app_id']).first()
if recommended_app is None:
raise NotFound('App not found')
current_tenant_id = current_user.current_tenant_id
app = db.session.query(App).filter(
App.id == args['app_id']
).first()
if app is None:
raise NotFound('App not found')
if not app.is_public:
raise Forbidden('You can\'t install a non-public app')
installed_app = InstalledApp.query.filter(and_(
InstalledApp.app_id == args['app_id'],
InstalledApp.tenant_id == current_tenant_id
)).first()
if installed_app is None:
# todo: position
recommended_app.install_count += 1
new_installed_app = InstalledApp(
app_id=args['app_id'],
tenant_id=current_tenant_id,
app_owner_tenant_id=app.tenant_id,
is_pinned=False,
last_used_at=datetime.utcnow()
)
db.session.add(new_installed_app)
db.session.commit()
return {'message': 'App installed successfully'}
class InstalledAppApi(InstalledAppResource):
"""
update and delete an installed app
use InstalledAppResource to apply default decorators and get installed_app
"""
def delete(self, installed_app):
if installed_app.app_owner_tenant_id == current_user.current_tenant_id:
raise BadRequest('You can\'t uninstall an app owned by the current tenant')
db.session.delete(installed_app)
db.session.commit()
return {'result': 'success', 'message': 'App uninstalled successfully'}
def patch(self, installed_app):
parser = reqparse.RequestParser()
parser.add_argument('is_pinned', type=inputs.boolean)
args = parser.parse_args()
commit_args = False
if 'is_pinned' in args:
installed_app.is_pinned = args['is_pinned']
commit_args = True
if commit_args:
db.session.commit()
return {'result': 'success', 'message': 'App info updated successfully'}
api.add_resource(InstalledAppsListApi, '/installed-apps')
api.add_resource(InstalledAppApi, '/installed-apps/<uuid:installed_app_id>')

View File

@ -0,0 +1,196 @@
# -*- coding:utf-8 -*-
import json
import logging
from typing import Generator, Union
from flask import stream_with_context, Response
from flask_login import current_user
from flask_restful import reqparse, fields, marshal_with
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound, InternalServerError
import services
from controllers.console import api
from controllers.console.app.error import AppMoreLikeThisDisabledError, ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
from controllers.console.explore.error import NotCompletionAppError, AppSuggestedQuestionsAfterAnswerDisabledError
from controllers.console.explore.wraps import InstalledAppResource
from core.llm.error import LLMRateLimitError, LLMBadRequestError, LLMAuthorizationError, LLMAPIConnectionError, \
ProviderTokenNotInitError, LLMAPIUnavailableError, QuotaExceededError, ModelCurrentlyNotSupportError
from libs.helper import uuid_value, TimestampField
from services.completion_service import CompletionService
from services.errors.app import MoreLikeThisDisabledError
from services.errors.conversation import ConversationNotExistsError
from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
from services.message_service import MessageService
class MessageListApi(InstalledAppResource):
feedback_fields = {
'rating': fields.String
}
message_fields = {
'id': fields.String,
'conversation_id': fields.String,
'inputs': fields.Raw,
'query': fields.String,
'answer': fields.String,
'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
'created_at': TimestampField
}
message_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
'data': fields.List(fields.Nested(message_fields))
}
@marshal_with(message_infinite_scroll_pagination_fields)
def get(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotChatAppError()
parser = reqparse.RequestParser()
parser.add_argument('conversation_id', required=True, type=uuid_value, location='args')
parser.add_argument('first_id', type=uuid_value, location='args')
parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
args = parser.parse_args()
try:
return MessageService.pagination_by_first_id(app_model, current_user,
args['conversation_id'], args['first_id'], args['limit'])
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.message.FirstMessageNotExistsError:
raise NotFound("First Message Not Exists.")
class MessageFeedbackApi(InstalledAppResource):
def post(self, installed_app, message_id):
app_model = installed_app.app
message_id = str(message_id)
parser = reqparse.RequestParser()
parser.add_argument('rating', type=str, choices=['like', 'dislike', None], location='json')
args = parser.parse_args()
try:
MessageService.create_feedback(app_model, message_id, current_user, args['rating'])
except services.errors.message.MessageNotExistsError:
raise NotFound("Message Not Exists.")
return {'result': 'success'}
class MessageMoreLikeThisApi(InstalledAppResource):
def get(self, installed_app, message_id):
app_model = installed_app.app
if app_model.mode != 'completion':
raise NotCompletionAppError()
message_id = str(message_id)
parser = reqparse.RequestParser()
parser.add_argument('response_mode', type=str, required=True, choices=['blocking', 'streaming'], location='args')
args = parser.parse_args()
streaming = args['response_mode'] == 'streaming'
try:
response = CompletionService.generate_more_like_this(app_model, current_user, message_id, streaming)
return compact_response(response)
except MessageNotExistsError:
raise NotFound("Message Not Exists.")
except MoreLikeThisDisabledError:
raise AppMoreLikeThisDisabledError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception:
logging.exception("internal server error.")
raise InternalServerError()
def compact_response(response: Union[dict | Generator]) -> Response:
if isinstance(response, dict):
return Response(response=json.dumps(response), status=200, mimetype='application/json')
else:
def generate() -> Generator:
try:
for chunk in response:
yield chunk
except MessageNotExistsError:
yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
except MoreLikeThisDisabledError:
yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:
yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
except ValueError as e:
yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
except Exception:
logging.exception("internal server error.")
yield "data: " + json.dumps(api.handle_error(InternalServerError()).get_json()) + "\n\n"
return Response(stream_with_context(generate()), status=200,
mimetype='text/event-stream')
class MessageSuggestedQuestionApi(InstalledAppResource):
def get(self, installed_app, message_id):
app_model = installed_app.app
if app_model.mode != 'chat':
raise NotCompletionAppError()
message_id = str(message_id)
try:
questions = MessageService.get_suggested_questions_after_answer(
app_model=app_model,
user=current_user,
message_id=message_id
)
except MessageNotExistsError:
raise NotFound("Message not found")
except ConversationNotExistsError:
raise NotFound("Conversation not found")
except SuggestedQuestionsAfterAnswerDisabledError:
raise AppSuggestedQuestionsAfterAnswerDisabledError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except Exception:
logging.exception("internal server error.")
raise InternalServerError()
return {'data': questions}
api.add_resource(MessageListApi, '/installed-apps/<uuid:installed_app_id>/messages', endpoint='installed_app_messages')
api.add_resource(MessageFeedbackApi, '/installed-apps/<uuid:installed_app_id>/messages/<uuid:message_id>/feedbacks', endpoint='installed_app_message_feedback')
api.add_resource(MessageMoreLikeThisApi, '/installed-apps/<uuid:installed_app_id>/messages/<uuid:message_id>/more-like-this', endpoint='installed_app_more_like_this')
api.add_resource(MessageSuggestedQuestionApi, '/installed-apps/<uuid:installed_app_id>/messages/<uuid:message_id>/suggested-questions', endpoint='installed_app_suggested_question')

View File

@ -0,0 +1,50 @@
# -*- coding:utf-8 -*-
from flask_restful import marshal_with, fields
from controllers.console import api
from controllers.console.explore.wraps import InstalledAppResource
from core.llm.llm_builder import LLMBuilder
from models.provider import ProviderName
from models.model import InstalledApp
class AppParameterApi(InstalledAppResource):
"""Resource for app variables."""
variable_fields = {
'key': fields.String,
'name': fields.String,
'description': fields.String,
'type': fields.String,
'default': fields.String,
'max_length': fields.Integer,
'options': fields.List(fields.String)
}
parameters_fields = {
'opening_statement': fields.String,
'suggested_questions': fields.Raw,
'suggested_questions_after_answer': fields.Raw,
'speech_to_text': fields.Raw,
'more_like_this': fields.Raw,
'user_input_form': fields.Raw,
}
@marshal_with(parameters_fields)
def get(self, installed_app: InstalledApp):
"""Retrieve app parameters."""
app_model = installed_app.app
app_model_config = app_model.app_model_config
provider_name = LLMBuilder.get_default_provider(installed_app.tenant_id, 'whisper-1')
return {
'opening_statement': app_model_config.opening_statement,
'suggested_questions': app_model_config.suggested_questions_list,
'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
'more_like_this': app_model_config.more_like_this_dict,
'user_input_form': app_model_config.user_input_form_list
}
api.add_resource(AppParameterApi, '/installed-apps/<uuid:installed_app_id>/parameters', endpoint='installed_app_parameters')

View File

@ -0,0 +1,138 @@
# -*- coding:utf-8 -*-
from flask_login import login_required, current_user
from flask_restful import Resource, fields, marshal_with
from sqlalchemy import and_
from controllers.console import api
from controllers.console.app.error import AppNotFoundError
from controllers.console.wraps import account_initialization_required
from extensions.ext_database import db
from models.model import App, InstalledApp, RecommendedApp
from services.account_service import TenantService
app_fields = {
'id': fields.String,
'name': fields.String,
'mode': fields.String,
'icon': fields.String,
'icon_background': fields.String
}
recommended_app_fields = {
'app': fields.Nested(app_fields, attribute='app'),
'app_id': fields.String,
'description': fields.String(attribute='description'),
'copyright': fields.String,
'privacy_policy': fields.String,
'category': fields.String,
'position': fields.Integer,
'is_listed': fields.Boolean,
'install_count': fields.Integer,
'installed': fields.Boolean,
'editable': fields.Boolean
}
recommended_app_list_fields = {
'recommended_apps': fields.List(fields.Nested(recommended_app_fields)),
'categories': fields.List(fields.String)
}
class RecommendedAppListApi(Resource):
@login_required
@account_initialization_required
@marshal_with(recommended_app_list_fields)
def get(self):
language_prefix = current_user.interface_language if current_user.interface_language else 'en-US'
recommended_apps = db.session.query(RecommendedApp).filter(
RecommendedApp.is_listed == True,
RecommendedApp.language == language_prefix
).all()
categories = set()
current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
recommended_apps_result = []
for recommended_app in recommended_apps:
installed = db.session.query(InstalledApp).filter(
and_(
InstalledApp.app_id == recommended_app.app_id,
InstalledApp.tenant_id == current_user.current_tenant_id
)
).first() is not None
app = recommended_app.app
if not app or not app.is_public:
continue
site = app.site
if not site:
continue
recommended_app_result = {
'id': recommended_app.id,
'app': app,
'app_id': recommended_app.app_id,
'description': site.description,
'copyright': site.copyright,
'privacy_policy': site.privacy_policy,
'category': recommended_app.category,
'position': recommended_app.position,
'is_listed': recommended_app.is_listed,
'install_count': recommended_app.install_count,
'installed': installed,
'editable': current_user.role in ['owner', 'admin'],
}
recommended_apps_result.append(recommended_app_result)
categories.add(recommended_app.category) # add category to categories
return {'recommended_apps': recommended_apps_result, 'categories': list(categories)}
class RecommendedAppApi(Resource):
model_config_fields = {
'opening_statement': fields.String,
'suggested_questions': fields.Raw(attribute='suggested_questions_list'),
'suggested_questions_after_answer': fields.Raw(attribute='suggested_questions_after_answer_dict'),
'more_like_this': fields.Raw(attribute='more_like_this_dict'),
'model': fields.Raw(attribute='model_dict'),
'user_input_form': fields.Raw(attribute='user_input_form_list'),
'pre_prompt': fields.String,
'agent_mode': fields.Raw(attribute='agent_mode_dict'),
}
app_simple_detail_fields = {
'id': fields.String,
'name': fields.String,
'icon': fields.String,
'icon_background': fields.String,
'mode': fields.String,
'app_model_config': fields.Nested(model_config_fields),
}
@login_required
@account_initialization_required
@marshal_with(app_simple_detail_fields)
def get(self, app_id):
app_id = str(app_id)
# is in public recommended list
recommended_app = db.session.query(RecommendedApp).filter(
RecommendedApp.is_listed == True,
RecommendedApp.app_id == app_id
).first()
if not recommended_app:
raise AppNotFoundError
# get app detail
app = db.session.query(App).filter(App.id == app_id).first()
if not app or not app.is_public:
raise AppNotFoundError
return app
api.add_resource(RecommendedAppListApi, '/explore/apps')
api.add_resource(RecommendedAppApi, '/explore/apps/<uuid:app_id>')

View File

@ -0,0 +1,79 @@
from flask_login import current_user
from flask_restful import reqparse, marshal_with, fields
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound
from controllers.console import api
from controllers.console.explore.error import NotCompletionAppError
from controllers.console.explore.wraps import InstalledAppResource
from libs.helper import uuid_value, TimestampField
from services.errors.message import MessageNotExistsError
from services.saved_message_service import SavedMessageService
feedback_fields = {
'rating': fields.String
}
message_fields = {
'id': fields.String,
'inputs': fields.Raw,
'query': fields.String,
'answer': fields.String,
'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
'created_at': TimestampField
}
class SavedMessageListApi(InstalledAppResource):
saved_message_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
'data': fields.List(fields.Nested(message_fields))
}
@marshal_with(saved_message_infinite_scroll_pagination_fields)
def get(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'completion':
raise NotCompletionAppError()
parser = reqparse.RequestParser()
parser.add_argument('last_id', type=uuid_value, location='args')
parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
args = parser.parse_args()
return SavedMessageService.pagination_by_last_id(app_model, current_user, args['last_id'], args['limit'])
def post(self, installed_app):
app_model = installed_app.app
if app_model.mode != 'completion':
raise NotCompletionAppError()
parser = reqparse.RequestParser()
parser.add_argument('message_id', type=uuid_value, required=True, location='json')
args = parser.parse_args()
try:
SavedMessageService.save(app_model, current_user, args['message_id'])
except MessageNotExistsError:
raise NotFound("Message Not Exists.")
return {'result': 'success'}
class SavedMessageApi(InstalledAppResource):
def delete(self, installed_app, message_id):
app_model = installed_app.app
message_id = str(message_id)
if app_model.mode != 'completion':
raise NotCompletionAppError()
SavedMessageService.delete(app_model, current_user, message_id)
return {'result': 'success'}
api.add_resource(SavedMessageListApi, '/installed-apps/<uuid:installed_app_id>/saved-messages', endpoint='installed_app_saved_messages')
api.add_resource(SavedMessageApi, '/installed-apps/<uuid:installed_app_id>/saved-messages/<uuid:message_id>', endpoint='installed_app_saved_message')

View File

@ -0,0 +1,48 @@
from flask_login import login_required, current_user
from flask_restful import Resource
from functools import wraps
from werkzeug.exceptions import NotFound
from controllers.console.wraps import account_initialization_required
from extensions.ext_database import db
from models.model import InstalledApp
def installed_app_required(view=None):
def decorator(view):
@wraps(view)
def decorated(*args, **kwargs):
if not kwargs.get('installed_app_id'):
raise ValueError('missing installed_app_id in path parameters')
installed_app_id = kwargs.get('installed_app_id')
installed_app_id = str(installed_app_id)
del kwargs['installed_app_id']
installed_app = db.session.query(InstalledApp).filter(
InstalledApp.id == str(installed_app_id),
InstalledApp.tenant_id == current_user.current_tenant_id
).first()
if installed_app is None:
raise NotFound('Installed app not found')
if not installed_app.app:
db.session.delete(installed_app)
db.session.commit()
raise NotFound('Installed app not found')
return view(installed_app, *args, **kwargs)
return decorated
if view:
return decorator(view)
return decorator
class InstalledAppResource(Resource):
# must be reversed if there are multiple decorators
method_decorators = [installed_app_required, account_initialization_required, login_required]

View File

@ -0,0 +1,66 @@
# -*- coding:utf-8 -*-
import logging
from flask import request
from werkzeug.exceptions import InternalServerError
import services
from controllers.console import api
from controllers.console.app.error import AppUnavailableError, ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError, \
NoAudioUploadedError, AudioTooLargeError, \
UnsupportedAudioTypeError, ProviderNotSupportSpeechToTextError
from controllers.console.universal_chat.wraps import UniversalChatResource
from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from services.audio_service import AudioService
from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
from models.model import AppModelConfig
class UniversalChatAudioApi(UniversalChatResource):
def post(self, universal_app):
app_model = universal_app
app_model_config: AppModelConfig = app_model.app_model_config
if not app_model_config.speech_to_text_dict['enabled']:
raise AppUnavailableError()
file = request.files['file']
try:
response = AudioService.transcript(
tenant_id=app_model.tenant_id,
file=file,
)
return response
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except NoAudioUploadedServiceError:
raise NoAudioUploadedError()
except AudioTooLargeServiceError as e:
raise AudioTooLargeError(str(e))
except UnsupportedAudioTypeServiceError:
raise UnsupportedAudioTypeError()
except ProviderNotSupportSpeechToTextServiceError:
raise ProviderNotSupportSpeechToTextError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
api.add_resource(UniversalChatAudioApi, '/universal-chat/audio-to-text')

View File

@ -0,0 +1,142 @@
import json
import logging
from typing import Generator, Union
from flask import Response, stream_with_context
from flask_login import current_user
from flask_restful import reqparse
from werkzeug.exceptions import InternalServerError, NotFound
import services
from controllers.console import api
from controllers.console.app.error import ConversationCompletedError, AppUnavailableError, ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
from controllers.console.universal_chat.wraps import UniversalChatResource
from core.constant import llm_constant
from core.conversation_message_task import PubHandler
from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError, \
LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError, LLMRateLimitError, LLMAuthorizationError
from libs.helper import uuid_value
from services.completion_service import CompletionService
class UniversalChatApi(UniversalChatResource):
def post(self, universal_app):
app_model = universal_app
parser = reqparse.RequestParser()
parser.add_argument('query', type=str, required=True, location='json')
parser.add_argument('conversation_id', type=uuid_value, location='json')
parser.add_argument('model', type=str, required=True, location='json')
parser.add_argument('tools', type=list, required=True, location='json')
args = parser.parse_args()
app_model_config = app_model.app_model_config
# update app model config
args['model_config'] = app_model_config.to_dict()
args['model_config']['model']['name'] = args['model']
if not llm_constant.models[args['model']]:
raise ValueError("Model not exists.")
args['model_config']['model']['provider'] = llm_constant.models[args['model']]
args['model_config']['agent_mode']['tools'] = args['tools']
if not args['model_config']['agent_mode']['tools']:
args['model_config']['agent_mode']['tools'] = [
{
"current_datetime": {
"enabled": True
}
}
]
else:
args['model_config']['agent_mode']['tools'].append({
"current_datetime": {
"enabled": True
}
})
args['inputs'] = {}
del args['model']
del args['tools']
try:
response = CompletionService.completion(
app_model=app_model,
user=current_user,
args=args,
from_source='console',
streaming=True,
is_model_config_override=True,
)
return compact_response(response)
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.conversation.ConversationCompletedError:
raise ConversationCompletedError()
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
class UniversalChatStopApi(UniversalChatResource):
def post(self, universal_app, task_id):
PubHandler.stop(current_user, task_id)
return {'result': 'success'}, 200
def compact_response(response: Union[dict | Generator]) -> Response:
if isinstance(response, dict):
return Response(response=json.dumps(response), status=200, mimetype='application/json')
else:
def generate() -> Generator:
try:
for chunk in response:
yield chunk
except services.errors.conversation.ConversationNotExistsError:
yield "data: " + json.dumps(api.handle_error(NotFound("Conversation Not Exists.")).get_json()) + "\n\n"
except services.errors.conversation.ConversationCompletedError:
yield "data: " + json.dumps(api.handle_error(ConversationCompletedError()).get_json()) + "\n\n"
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:
yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
except ValueError as e:
yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
except Exception:
logging.exception("internal server error.")
yield "data: " + json.dumps(api.handle_error(InternalServerError()).get_json()) + "\n\n"
return Response(stream_with_context(generate()), status=200,
mimetype='text/event-stream')
api.add_resource(UniversalChatApi, '/universal-chat/messages')
api.add_resource(UniversalChatStopApi, '/universal-chat/messages/<string:task_id>/stop')

View File

@ -0,0 +1,118 @@
# -*- coding:utf-8 -*-
from flask_login import current_user
from flask_restful import fields, reqparse, marshal_with
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound
from controllers.console import api
from controllers.console.universal_chat.wraps import UniversalChatResource
from libs.helper import TimestampField, uuid_value
from services.conversation_service import ConversationService
from services.errors.conversation import LastConversationNotExistsError, ConversationNotExistsError
from services.web_conversation_service import WebConversationService
conversation_fields = {
'id': fields.String,
'name': fields.String,
'inputs': fields.Raw,
'status': fields.String,
'introduction': fields.String,
'created_at': TimestampField,
'model_config': fields.Raw,
}
conversation_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
'data': fields.List(fields.Nested(conversation_fields))
}
class UniversalChatConversationListApi(UniversalChatResource):
@marshal_with(conversation_infinite_scroll_pagination_fields)
def get(self, universal_app):
app_model = universal_app
parser = reqparse.RequestParser()
parser.add_argument('last_id', type=uuid_value, location='args')
parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
parser.add_argument('pinned', type=str, choices=['true', 'false', None], location='args')
args = parser.parse_args()
pinned = None
if 'pinned' in args and args['pinned'] is not None:
pinned = True if args['pinned'] == 'true' else False
try:
return WebConversationService.pagination_by_last_id(
app_model=app_model,
user=current_user,
last_id=args['last_id'],
limit=args['limit'],
pinned=pinned
)
except LastConversationNotExistsError:
raise NotFound("Last Conversation Not Exists.")
class UniversalChatConversationApi(UniversalChatResource):
def delete(self, universal_app, c_id):
app_model = universal_app
conversation_id = str(c_id)
try:
ConversationService.delete(app_model, conversation_id, current_user)
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
WebConversationService.unpin(app_model, conversation_id, current_user)
return {"result": "success"}, 204
class UniversalChatConversationRenameApi(UniversalChatResource):
@marshal_with(conversation_fields)
def post(self, universal_app, c_id):
app_model = universal_app
conversation_id = str(c_id)
parser = reqparse.RequestParser()
parser.add_argument('name', type=str, required=True, location='json')
args = parser.parse_args()
try:
return ConversationService.rename(app_model, conversation_id, current_user, args['name'])
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
class UniversalChatConversationPinApi(UniversalChatResource):
def patch(self, universal_app, c_id):
app_model = universal_app
conversation_id = str(c_id)
try:
WebConversationService.pin(app_model, conversation_id, current_user)
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
return {"result": "success"}
class UniversalChatConversationUnPinApi(UniversalChatResource):
def patch(self, universal_app, c_id):
app_model = universal_app
conversation_id = str(c_id)
WebConversationService.unpin(app_model, conversation_id, current_user)
return {"result": "success"}
api.add_resource(UniversalChatConversationRenameApi, '/universal-chat/conversations/<uuid:c_id>/name')
api.add_resource(UniversalChatConversationListApi, '/universal-chat/conversations')
api.add_resource(UniversalChatConversationApi, '/universal-chat/conversations/<uuid:c_id>')
api.add_resource(UniversalChatConversationPinApi, '/universal-chat/conversations/<uuid:c_id>/pin')
api.add_resource(UniversalChatConversationUnPinApi, '/universal-chat/conversations/<uuid:c_id>/unpin')

View File

@ -0,0 +1,127 @@
# -*- coding:utf-8 -*-
import logging
from flask_login import current_user
from flask_restful import reqparse, fields, marshal_with
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound, InternalServerError
import services
from controllers.console import api
from controllers.console.app.error import ProviderNotInitializeError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
from controllers.console.explore.error import AppSuggestedQuestionsAfterAnswerDisabledError
from controllers.console.universal_chat.wraps import UniversalChatResource
from core.llm.error import LLMRateLimitError, LLMBadRequestError, LLMAuthorizationError, LLMAPIConnectionError, \
ProviderTokenNotInitError, LLMAPIUnavailableError, QuotaExceededError, ModelCurrentlyNotSupportError
from libs.helper import uuid_value, TimestampField
from services.errors.conversation import ConversationNotExistsError
from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
from services.message_service import MessageService
class UniversalChatMessageListApi(UniversalChatResource):
feedback_fields = {
'rating': fields.String
}
agent_thought_fields = {
'id': fields.String,
'chain_id': fields.String,
'message_id': fields.String,
'position': fields.Integer,
'thought': fields.String,
'tool': fields.String,
'tool_input': fields.String,
'created_at': TimestampField
}
message_fields = {
'id': fields.String,
'conversation_id': fields.String,
'inputs': fields.Raw,
'query': fields.String,
'answer': fields.String,
'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
'created_at': TimestampField,
'agent_thoughts': fields.List(fields.Nested(agent_thought_fields))
}
message_infinite_scroll_pagination_fields = {
'limit': fields.Integer,
'has_more': fields.Boolean,
'data': fields.List(fields.Nested(message_fields))
}
@marshal_with(message_infinite_scroll_pagination_fields)
def get(self, universal_app):
app_model = universal_app
parser = reqparse.RequestParser()
parser.add_argument('conversation_id', required=True, type=uuid_value, location='args')
parser.add_argument('first_id', type=uuid_value, location='args')
parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
args = parser.parse_args()
try:
return MessageService.pagination_by_first_id(app_model, current_user,
args['conversation_id'], args['first_id'], args['limit'])
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.message.FirstMessageNotExistsError:
raise NotFound("First Message Not Exists.")
class UniversalChatMessageFeedbackApi(UniversalChatResource):
def post(self, universal_app, message_id):
app_model = universal_app
message_id = str(message_id)
parser = reqparse.RequestParser()
parser.add_argument('rating', type=str, choices=['like', 'dislike', None], location='json')
args = parser.parse_args()
try:
MessageService.create_feedback(app_model, message_id, current_user, args['rating'])
except services.errors.message.MessageNotExistsError:
raise NotFound("Message Not Exists.")
return {'result': 'success'}
class UniversalChatMessageSuggestedQuestionApi(UniversalChatResource):
def get(self, universal_app, message_id):
app_model = universal_app
message_id = str(message_id)
try:
questions = MessageService.get_suggested_questions_after_answer(
app_model=app_model,
user=current_user,
message_id=message_id
)
except MessageNotExistsError:
raise NotFound("Message not found")
except ConversationNotExistsError:
raise NotFound("Conversation not found")
except SuggestedQuestionsAfterAnswerDisabledError:
raise AppSuggestedQuestionsAfterAnswerDisabledError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except Exception:
logging.exception("internal server error.")
raise InternalServerError()
return {'data': questions}
api.add_resource(UniversalChatMessageListApi, '/universal-chat/messages')
api.add_resource(UniversalChatMessageFeedbackApi, '/universal-chat/messages/<uuid:message_id>/feedbacks')
api.add_resource(UniversalChatMessageSuggestedQuestionApi, '/universal-chat/messages/<uuid:message_id>/suggested-questions')

View File

@ -0,0 +1,36 @@
# -*- coding:utf-8 -*-
from flask_restful import marshal_with, fields
from controllers.console import api
from controllers.console.universal_chat.wraps import UniversalChatResource
from core.llm.llm_builder import LLMBuilder
from models.provider import ProviderName
from models.model import App
class UniversalChatParameterApi(UniversalChatResource):
"""Resource for app variables."""
parameters_fields = {
'opening_statement': fields.String,
'suggested_questions': fields.Raw,
'suggested_questions_after_answer': fields.Raw,
'speech_to_text': fields.Raw,
}
@marshal_with(parameters_fields)
def get(self, universal_app: App):
"""Retrieve app parameters."""
app_model = universal_app
app_model_config = app_model.app_model_config
provider_name = LLMBuilder.get_default_provider(universal_app.tenant_id, 'whisper-1')
return {
'opening_statement': app_model_config.opening_statement,
'suggested_questions': app_model_config.suggested_questions_list,
'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
}
api.add_resource(UniversalChatParameterApi, '/universal-chat/parameters')

View File

@ -0,0 +1,84 @@
import json
from functools import wraps
from flask_login import login_required, current_user
from flask_restful import Resource
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from extensions.ext_database import db
from models.model import App, AppModelConfig
def universal_chat_app_required(view=None):
def decorator(view):
@wraps(view)
def decorated(*args, **kwargs):
# get universal chat app
universal_app = db.session.query(App).filter(
App.tenant_id == current_user.current_tenant_id,
App.is_universal == True
).first()
if universal_app is None:
# create universal app if not exists
universal_app = App(
tenant_id=current_user.current_tenant_id,
name='Universal Chat',
mode='chat',
is_universal=True,
icon='',
icon_background='',
api_rpm=0,
api_rph=0,
enable_site=False,
enable_api=False,
status='normal'
)
db.session.add(universal_app)
db.session.flush()
app_model_config = AppModelConfig(
provider="",
model_id="",
configs={},
opening_statement='',
suggested_questions=json.dumps([]),
suggested_questions_after_answer=json.dumps({'enabled': True}),
speech_to_text=json.dumps({'enabled': True}),
more_like_this=None,
sensitive_word_avoidance=None,
model=json.dumps({
"provider": "openai",
"name": "gpt-3.5-turbo-16k",
"completion_params": {
"max_tokens": 800,
"temperature": 0.8,
"top_p": 1,
"presence_penalty": 0,
"frequency_penalty": 0
}
}),
user_input_form=json.dumps([]),
pre_prompt='',
agent_mode=json.dumps({"enabled": True, "strategy": "function_call", "tools": []}),
)
app_model_config.app_id = universal_app.id
db.session.add(app_model_config)
db.session.flush()
universal_app.app_model_config_id = app_model_config.id
db.session.commit()
return view(universal_app, *args, **kwargs)
return decorated
if view:
return decorator(view)
return decorator
class UniversalChatResource(Resource):
# must be reversed if there are multiple decorators
method_decorators = [universal_chat_app_required, account_initialization_required, login_required, setup_required]

View File

@ -19,13 +19,26 @@ class VersionApi(Resource):
args = parser.parse_args()
check_update_url = current_app.config['CHECK_UPDATE_URL']
if not check_update_url:
return {
'version': '0.0.0',
'release_date': '',
'release_notes': '',
'can_auto_update': False
}
try:
response = requests.get(check_update_url, {
'current_version': args.get('current_version')
})
except Exception as error:
logging.exception("Check update error.")
raise InternalServerError()
logging.warning("Check update version error: {}.".format(str(error)))
return {
'version': args.get('current_version'),
'release_date': '',
'release_notes': '',
'can_auto_update': False
}
content = json.loads(response.content)
return {

View File

@ -6,22 +6,23 @@ from flask import current_app, request
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, fields, marshal_with
from services.errors.account import CurrentPasswordIncorrectError as ServiceCurrentPasswordIncorrectError
from controllers.console import api
from controllers.console.setup import setup_required
from controllers.console.workspace.error import AccountAlreadyInitedError, InvalidInvitationCodeError, \
RepeatPasswordNotMatchError
RepeatPasswordNotMatchError, CurrentPasswordIncorrectError
from controllers.console.wraps import account_initialization_required
from libs.helper import TimestampField, supported_language, timezone
from extensions.ext_database import db
from models.account import InvitationCode, AccountIntegrate
from services.account_service import AccountService
account_fields = {
'id': fields.String,
'name': fields.String,
'avatar': fields.String,
'email': fields.String,
'is_password_set': fields.Boolean,
'interface_language': fields.String,
'interface_theme': fields.String,
'timezone': fields.String,
@ -194,8 +195,11 @@ class AccountPasswordApi(Resource):
if args['new_password'] != args['repeat_new_password']:
raise RepeatPasswordNotMatchError()
AccountService.update_account_password(
current_user, args['password'], args['new_password'])
try:
AccountService.update_account_password(
current_user, args['password'], args['new_password'])
except ServiceCurrentPasswordIncorrectError:
raise CurrentPasswordIncorrectError()
return {"result": "success"}

View File

@ -7,6 +7,12 @@ class RepeatPasswordNotMatchError(BaseHTTPException):
code = 400
class CurrentPasswordIncorrectError(BaseHTTPException):
error_code = 'current_password_incorrect'
description = "Current password is incorrect."
code = 400
class ProviderRequestFailedError(BaseHTTPException):
error_code = 'provider_request_failed'
description = None
@ -21,11 +27,11 @@ class InvalidInvitationCodeError(BaseHTTPException):
class AccountAlreadyInitedError(BaseHTTPException):
error_code = 'account_already_inited'
description = "Account already inited."
description = "The account has been initialized. Please refresh the page."
code = 400
class AccountNotInitializedError(BaseHTTPException):
error_code = 'account_not_initialized'
description = "Account not initialized."
description = "The account has not been initialized yet. Please proceed with the initialization process first."
code = 400

View File

@ -1,5 +1,5 @@
# -*- coding:utf-8 -*-
from flask import current_app
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, marshal_with, abort, fields, marshal
@ -60,7 +60,8 @@ class MemberInviteEmailApi(Resource):
inviter = current_user
try:
RegisterService.invite_new_member(inviter.current_tenant, invitee_email, role=invitee_role, inviter=inviter)
token = RegisterService.invite_new_member(inviter.current_tenant, invitee_email, role=invitee_role,
inviter=inviter)
account = db.session.query(Account, TenantAccountJoin.role).join(
TenantAccountJoin, Account.id == TenantAccountJoin.account_id
).filter(Account.email == args['email']).first()
@ -78,7 +79,16 @@ class MemberInviteEmailApi(Resource):
# todo:413
return {'result': 'success', 'account': account}, 201
return {
'result': 'success',
'account': account,
'invite_url': '{}/activate?workspace_id={}&email={}&token={}'.format(
current_app.config.get("CONSOLE_WEB_URL"),
str(current_user.current_tenant_id),
invitee_email,
token
)
}, 201
class MemberCancelInviteApi(Resource):
@ -88,7 +98,7 @@ class MemberCancelInviteApi(Resource):
@login_required
@account_initialization_required
def delete(self, member_id):
member = Account.query.get(str(member_id))
member = db.session.query(Account).filter(Account.id == str(member_id)).first()
if not member:
abort(404)

View File

@ -3,6 +3,7 @@ import base64
import json
import logging
from flask import current_app
from flask_login import login_required, current_user
from flask_restful import Resource, reqparse, abort
from werkzeug.exceptions import Forbidden
@ -34,7 +35,7 @@ class ProviderListApi(Resource):
plaintext, the rest is replaced by * and the last two bits are displayed in plaintext
"""
ProviderService.init_supported_provider(current_user.current_tenant, "cloud")
ProviderService.init_supported_provider(current_user.current_tenant)
providers = Provider.query.filter_by(tenant_id=tenant_id).all()
provider_list = [
@ -50,7 +51,8 @@ class ProviderListApi(Resource):
'quota_used': p.quota_used
} if p.provider_type == ProviderType.SYSTEM.value else {}),
'token': ProviderService.get_obfuscated_api_key(current_user.current_tenant,
ProviderName(p.provider_name))
ProviderName(p.provider_name), only_custom=True)
if p.provider_type == ProviderType.CUSTOM.value else None
}
for p in providers
]
@ -82,29 +84,33 @@ class ProviderTokenApi(Resource):
args = parser.parse_args()
if not args['token']:
raise ValueError('Token is empty')
if args['token']:
try:
ProviderService.validate_provider_configs(
tenant=current_user.current_tenant,
provider_name=ProviderName(provider),
configs=args['token']
)
token_is_valid = True
except ValidateFailedError as ex:
raise ValueError(str(ex))
try:
ProviderService.validate_provider_configs(
base64_encrypted_token = ProviderService.get_encrypted_token(
tenant=current_user.current_tenant,
provider_name=ProviderName(provider),
configs=args['token']
)
token_is_valid = True
except ValidateFailedError:
else:
base64_encrypted_token = None
token_is_valid = False
tenant = current_user.current_tenant
base64_encrypted_token = ProviderService.get_encrypted_token(
tenant=current_user.current_tenant,
provider_name=ProviderName(provider),
configs=args['token']
)
provider_model = Provider.query.filter_by(tenant_id=tenant.id, provider_name=provider,
provider_type=ProviderType.CUSTOM.value).first()
provider_model = db.session.query(Provider).filter(
Provider.tenant_id == tenant.id,
Provider.provider_name == provider,
Provider.provider_type == ProviderType.CUSTOM.value
).first()
# Only allow updating token for CUSTOM provider type
if provider_model:
@ -117,9 +123,20 @@ class ProviderTokenApi(Resource):
is_valid=token_is_valid)
db.session.add(provider_model)
if provider in [ProviderName.OPENAI.value, ProviderName.AZURE_OPENAI.value] and provider_model.is_valid:
other_providers = db.session.query(Provider).filter(
Provider.tenant_id == tenant.id,
Provider.provider_name.in_([ProviderName.OPENAI.value, ProviderName.AZURE_OPENAI.value]),
Provider.provider_name != provider,
Provider.provider_type == ProviderType.CUSTOM.value
).all()
for other_provider in other_providers:
other_provider.is_valid = False
db.session.commit()
if provider in [ProviderName.ANTHROPIC.value, ProviderName.AZURE_OPENAI.value, ProviderName.COHERE.value,
if provider in [ProviderName.AZURE_OPENAI.value, ProviderName.COHERE.value,
ProviderName.HUGGINGFACEHUB.value]:
return {'result': 'success', 'warning': 'MOCK: This provider is not supported yet.'}, 201
@ -143,7 +160,7 @@ class ProviderTokenValidateApi(Resource):
args = parser.parse_args()
# todo: remove this when the provider is supported
if provider in [ProviderName.ANTHROPIC.value, ProviderName.AZURE_OPENAI.value, ProviderName.COHERE.value,
if provider in [ProviderName.COHERE.value,
ProviderName.HUGGINGFACEHUB.value]:
return {'result': 'success', 'warning': 'MOCK: This provider is not supported yet.'}
@ -189,7 +206,19 @@ class ProviderSystemApi(Resource):
provider_model.is_valid = args['is_enabled']
db.session.commit()
elif not provider_model:
ProviderService.create_system_provider(tenant, provider, args['is_enabled'])
if provider == ProviderName.OPENAI.value:
quota_limit = current_app.config['OPENAI_HOSTED_QUOTA_LIMIT']
elif provider == ProviderName.ANTHROPIC.value:
quota_limit = current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT']
else:
quota_limit = 0
ProviderService.create_system_provider(
tenant,
provider,
quota_limit,
args['is_enabled']
)
else:
abort(403)

View File

@ -0,0 +1,136 @@
import json
from flask_login import login_required, current_user
from flask_restful import Resource, abort, reqparse
from werkzeug.exceptions import Forbidden
from controllers.console import api
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.tool.provider.errors import ToolValidateFailedError
from core.tool.provider.tool_provider_service import ToolProviderService
from extensions.ext_database import db
from models.tool import ToolProvider, ToolProviderName
class ToolProviderListApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self):
tenant_id = current_user.current_tenant_id
tool_credential_dict = {}
for tool_name in ToolProviderName:
tool_credential_dict[tool_name.value] = {
'tool_name': tool_name.value,
'is_enabled': False,
'credentials': None
}
tool_providers = db.session.query(ToolProvider).filter(ToolProvider.tenant_id == tenant_id).all()
for p in tool_providers:
if p.is_enabled:
tool_credential_dict[p.tool_name] = {
'tool_name': p.tool_name,
'is_enabled': p.is_enabled,
'credentials': ToolProviderService(tenant_id, p.tool_name).get_credentials(obfuscated=True)
}
return list(tool_credential_dict.values())
class ToolProviderCredentialsApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self, provider):
if provider not in [p.value for p in ToolProviderName]:
abort(404)
# The role of the current user in the ta table must be admin or owner
if current_user.current_tenant.current_role not in ['admin', 'owner']:
raise Forbidden(f'User {current_user.id} is not authorized to update provider token, '
f'current_role is {current_user.current_tenant.current_role}')
parser = reqparse.RequestParser()
parser.add_argument('credentials', type=dict, required=True, nullable=False, location='json')
args = parser.parse_args()
tenant_id = current_user.current_tenant_id
tool_provider_service = ToolProviderService(tenant_id, provider)
try:
tool_provider_service.credentials_validate(args['credentials'])
except ToolValidateFailedError as ex:
raise ValueError(str(ex))
encrypted_credentials = json.dumps(tool_provider_service.encrypt_credentials(args['credentials']))
tenant = current_user.current_tenant
tool_provider_model = db.session.query(ToolProvider).filter(
ToolProvider.tenant_id == tenant.id,
ToolProvider.tool_name == provider,
).first()
# Only allow updating token for CUSTOM provider type
if tool_provider_model:
tool_provider_model.encrypted_credentials = encrypted_credentials
tool_provider_model.is_enabled = True
else:
tool_provider_model = ToolProvider(
tenant_id=tenant.id,
tool_name=provider,
encrypted_credentials=encrypted_credentials,
is_enabled=True
)
db.session.add(tool_provider_model)
db.session.commit()
return {'result': 'success'}, 201
class ToolProviderCredentialsValidateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self, provider):
if provider not in [p.value for p in ToolProviderName]:
abort(404)
parser = reqparse.RequestParser()
parser.add_argument('credentials', type=dict, required=True, nullable=False, location='json')
args = parser.parse_args()
result = True
error = None
tenant_id = current_user.current_tenant_id
tool_provider_service = ToolProviderService(tenant_id, provider)
try:
tool_provider_service.credentials_validate(args['credentials'])
except ToolValidateFailedError as ex:
result = False
error = str(ex)
response = {'result': 'success' if result else 'error'}
if not result:
response['error'] = error
return response
api.add_resource(ToolProviderListApi, '/workspaces/current/tool-providers')
api.add_resource(ToolProviderCredentialsApi, '/workspaces/current/tool-providers/<provider>/credentials')
api.add_resource(ToolProviderCredentialsValidateApi,
'/workspaces/current/tool-providers/<provider>/credentials-validate')

View File

@ -7,6 +7,6 @@ bp = Blueprint('service_api', __name__, url_prefix='/v1')
api = ExternalApi(bp)
from .app import completion, app, conversation, message
from .app import completion, app, conversation, message, audio
from .dataset import document

View File

@ -4,6 +4,10 @@ from flask_restful import fields, marshal_with
from controllers.service_api import api
from controllers.service_api.wraps import AppApiResource
from core.llm.llm_builder import LLMBuilder
from models.provider import ProviderName
from models.model import App
class AppParameterApi(AppApiResource):
"""Resource for app variables."""
@ -22,19 +26,22 @@ class AppParameterApi(AppApiResource):
'opening_statement': fields.String,
'suggested_questions': fields.Raw,
'suggested_questions_after_answer': fields.Raw,
'speech_to_text': fields.Raw,
'more_like_this': fields.Raw,
'user_input_form': fields.Raw,
}
@marshal_with(parameters_fields)
def get(self, app_model, end_user):
def get(self, app_model: App, end_user):
"""Retrieve app parameters."""
app_model_config = app_model.app_model_config
provider_name = LLMBuilder.get_default_provider(app_model.tenant_id, 'whisper-1')
return {
'opening_statement': app_model_config.opening_statement,
'suggested_questions': app_model_config.suggested_questions_list,
'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
'more_like_this': app_model_config.more_like_this_dict,
'user_input_form': app_model_config.user_input_form_list
}

View File

@ -0,0 +1,61 @@
import logging
from flask import request
from werkzeug.exceptions import InternalServerError
import services
from controllers.service_api import api
from controllers.service_api.app.error import AppUnavailableError, ProviderNotInitializeError, CompletionRequestError, ProviderQuotaExceededError, \
ProviderModelCurrentlyNotSupportError, NoAudioUploadedError, AudioTooLargeError, UnsupportedAudioTypeError, \
ProviderNotSupportSpeechToTextError
from controllers.service_api.wraps import AppApiResource
from core.llm.error import LLMBadRequestError, LLMAuthorizationError, LLMAPIUnavailableError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from models.model import App, AppModelConfig
from services.audio_service import AudioService
from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
class AudioApi(AppApiResource):
def post(self, app_model: App, end_user):
app_model_config: AppModelConfig = app_model.app_model_config
if not app_model_config.speech_to_text_dict['enabled']:
raise AppUnavailableError()
file = request.files['file']
try:
response = AudioService.transcript(
tenant_id=app_model.tenant_id,
file=file,
)
return response
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except NoAudioUploadedServiceError:
raise NoAudioUploadedError()
except AudioTooLargeServiceError as e:
raise AudioTooLargeError(str(e))
except UnsupportedAudioTypeServiceError:
raise UnsupportedAudioTypeError()
except ProviderNotSupportSpeechToTextServiceError:
raise ProviderNotSupportSpeechToTextError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
api.add_resource(AudioApi, '/audio-to-text')

View File

@ -54,8 +54,8 @@ class CompletionApi(AppApiResource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -115,8 +115,8 @@ class ChatApi(AppApiResource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -156,8 +156,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:

View File

@ -1,4 +1,5 @@
# -*- coding:utf-8 -*-
from flask import request
from flask_restful import fields, marshal_with, reqparse
from flask_restful.inputs import int_range
from werkzeug.exceptions import NotFound
@ -48,6 +49,24 @@ class ConversationApi(AppApiResource):
except services.errors.conversation.LastConversationNotExistsError:
raise NotFound("Last Conversation Not Exists.")
class ConversationDetailApi(AppApiResource):
@marshal_with(conversation_fields)
def delete(self, app_model, end_user, c_id):
if app_model.mode != 'chat':
raise NotChatAppError()
conversation_id = str(c_id)
user = request.get_json().get('user')
if end_user is None and user is not None:
end_user = create_or_update_end_user_for_user_id(app_model, user)
try:
ConversationService.delete(app_model, conversation_id, end_user)
return {"result": "success"}
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
class ConversationRenameApi(AppApiResource):
@ -74,3 +93,5 @@ class ConversationRenameApi(AppApiResource):
api.add_resource(ConversationRenameApi, '/conversations/<uuid:c_id>/name', endpoint='conversation_name')
api.add_resource(ConversationApi, '/conversations')
api.add_resource(ConversationApi, '/conversations/<uuid:c_id>', endpoint='conversation')
api.add_resource(ConversationDetailApi, '/conversations/<uuid:c_id>', endpoint='conversation_detail')

View File

@ -4,43 +4,45 @@ from libs.exception import BaseHTTPException
class AppUnavailableError(BaseHTTPException):
error_code = 'app_unavailable'
description = "App unavailable."
description = "App unavailable, please check your app configurations."
code = 400
class NotCompletionAppError(BaseHTTPException):
error_code = 'not_completion_app'
description = "Not Completion App"
description = "Please check if your Completion app mode matches the right API route."
code = 400
class NotChatAppError(BaseHTTPException):
error_code = 'not_chat_app'
description = "Not Chat App"
description = "Please check if your Chat app mode matches the right API route."
code = 400
class ConversationCompletedError(BaseHTTPException):
error_code = 'conversation_completed'
description = "Conversation Completed."
description = "The conversation has ended. Please start a new conversation."
code = 400
class ProviderNotInitializeError(BaseHTTPException):
error_code = 'provider_not_initialize'
description = "Provider Token not initialize."
description = "No valid model provider credentials found. " \
"Please go to Settings -> Model Provider to complete your provider credentials."
code = 400
class ProviderQuotaExceededError(BaseHTTPException):
error_code = 'provider_quota_exceeded'
description = "Provider quota exceeded."
description = "Your quota for Dify Hosted OpenAI has been exhausted. " \
"Please go to Settings -> Model Provider to complete your own provider credentials."
code = 400
class ProviderModelCurrentlyNotSupportError(BaseHTTPException):
error_code = 'model_currently_not_support'
description = "GPT-4 currently not support."
description = "Dify Hosted OpenAI trial currently not support the GPT-4 model."
code = 400
@ -49,3 +51,27 @@ class CompletionRequestError(BaseHTTPException):
description = "Completion request failed."
code = 400
class NoAudioUploadedError(BaseHTTPException):
error_code = 'no_audio_uploaded'
description = "Please upload your audio."
code = 400
class AudioTooLargeError(BaseHTTPException):
error_code = 'audio_too_large'
description = "Audio size exceeded. {message}"
code = 413
class UnsupportedAudioTypeError(BaseHTTPException):
error_code = 'unsupported_audio_type'
description = "Audio type not allowed."
code = 415
class ProviderNotSupportSpeechToTextError(BaseHTTPException):
error_code = 'provider_not_support_speech_to_text'
description = "Provider not support speech to text."
code = 400

View File

@ -69,21 +69,25 @@ class DocumentListApi(DatasetApiResource):
document_data = {
'data_source': {
'type': 'upload_file',
'info': upload_file.id
'info': [
{
'upload_file_id': upload_file.id
}
]
}
}
try:
document = DocumentService.save_document_with_dataset_id(
documents, batch = DocumentService.save_document_with_dataset_id(
dataset=dataset,
document_data=document_data,
account=dataset.created_by_account,
dataset_process_rule=dataset.latest_process_rule,
created_from='api'
)
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
document = documents[0]
if doc_type and doc_metadata:
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[doc_type]

View File

@ -16,5 +16,5 @@ class DocumentIndexingError(BaseHTTPException):
class DatasetNotInitedError(BaseHTTPException):
error_code = 'dataset_not_inited'
description = "Dataset not inited."
description = "The dataset is still being initialized or indexing. Please wait a moment."
code = 403

View File

@ -7,4 +7,4 @@ bp = Blueprint('web', __name__, url_prefix='/api')
api = ExternalApi(bp)
from . import completion, app, conversation, message, site, saved_message
from . import completion, app, conversation, message, site, saved_message, audio, passport

View File

@ -4,6 +4,10 @@ from flask_restful import marshal_with, fields
from controllers.web import api
from controllers.web.wraps import WebApiResource
from core.llm.llm_builder import LLMBuilder
from models.provider import ProviderName
from models.model import App
class AppParameterApi(WebApiResource):
"""Resource for app variables."""
@ -21,19 +25,22 @@ class AppParameterApi(WebApiResource):
'opening_statement': fields.String,
'suggested_questions': fields.Raw,
'suggested_questions_after_answer': fields.Raw,
'speech_to_text': fields.Raw,
'more_like_this': fields.Raw,
'user_input_form': fields.Raw,
}
@marshal_with(parameters_fields)
def get(self, app_model, end_user):
def get(self, app_model: App, end_user):
"""Retrieve app parameters."""
app_model_config = app_model.app_model_config
provider_name = LLMBuilder.get_default_provider(app_model.tenant_id, 'whisper-1')
return {
'opening_statement': app_model_config.opening_statement,
'suggested_questions': app_model_config.suggested_questions_list,
'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
'more_like_this': app_model_config.more_like_this_dict,
'user_input_form': app_model_config.user_input_form_list
}

View File

@ -0,0 +1,63 @@
# -*- coding:utf-8 -*-
import logging
from flask import request
from werkzeug.exceptions import InternalServerError
import services
from controllers.web import api
from controllers.web.error import AppUnavailableError, ProviderNotInitializeError, CompletionRequestError, \
ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, NoAudioUploadedError, AudioTooLargeError, \
UnsupportedAudioTypeError, ProviderNotSupportSpeechToTextError
from controllers.web.wraps import WebApiResource
from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
from services.audio_service import AudioService
from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
from models.model import App, AppModelConfig
class AudioApi(WebApiResource):
def post(self, app_model: App, end_user):
app_model_config: AppModelConfig = app_model.app_model_config
if not app_model_config.speech_to_text_dict['enabled']:
raise AppUnavailableError()
file = request.files['file']
try:
response = AudioService.transcript(
tenant_id=app_model.tenant_id,
file=file,
)
return response
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except NoAudioUploadedServiceError:
raise NoAudioUploadedError()
except AudioTooLargeServiceError as e:
raise AudioTooLargeError(str(e))
except UnsupportedAudioTypeServiceError:
raise UnsupportedAudioTypeError()
except ProviderNotSupportSpeechToTextServiceError:
raise ProviderNotSupportSpeechToTextError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
LLMRateLimitError, LLMAuthorizationError) as e:
raise CompletionRequestError(str(e))
except ValueError as e:
raise e
except Exception as e:
logging.exception("internal server error.")
raise InternalServerError()
api.add_resource(AudioApi, '/audio-to-text')

View File

@ -52,8 +52,8 @@ class CompletionApi(WebApiResource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -109,8 +109,8 @@ class ChatApi(WebApiResource):
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -150,8 +150,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
except services.errors.app_model_config.AppModelConfigBrokenError:
logging.exception("App model config broken.")
yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:

View File

@ -47,7 +47,7 @@ class ConversationListApi(WebApiResource):
try:
return WebConversationService.pagination_by_last_id(
app_model=app_model,
end_user=end_user,
user=end_user,
last_id=args['last_id'],
limit=args['limit'],
pinned=pinned
@ -62,7 +62,10 @@ class ConversationApi(WebApiResource):
raise NotChatAppError()
conversation_id = str(c_id)
ConversationService.delete(app_model, conversation_id, end_user)
try:
ConversationService.delete(app_model, conversation_id, end_user)
except ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
WebConversationService.unpin(app_model, conversation_id, end_user)
return {"result": "success"}, 204

View File

@ -4,43 +4,45 @@ from libs.exception import BaseHTTPException
class AppUnavailableError(BaseHTTPException):
error_code = 'app_unavailable'
description = "App unavailable."
description = "App unavailable, please check your app configurations."
code = 400
class NotCompletionAppError(BaseHTTPException):
error_code = 'not_completion_app'
description = "Not Completion App"
description = "Please check if your Completion app mode matches the right API route."
code = 400
class NotChatAppError(BaseHTTPException):
error_code = 'not_chat_app'
description = "Not Chat App"
description = "Please check if your Chat app mode matches the right API route."
code = 400
class ConversationCompletedError(BaseHTTPException):
error_code = 'conversation_completed'
description = "Conversation Completed."
description = "The conversation has ended. Please start a new conversation."
code = 400
class ProviderNotInitializeError(BaseHTTPException):
error_code = 'provider_not_initialize'
description = "Provider Token not initialize."
description = "No valid model provider credentials found. " \
"Please go to Settings -> Model Provider to complete your provider credentials."
code = 400
class ProviderQuotaExceededError(BaseHTTPException):
error_code = 'provider_quota_exceeded'
description = "Provider quota exceeded."
description = "Your quota for Dify Hosted OpenAI has been exhausted. " \
"Please go to Settings -> Model Provider to complete your own provider credentials."
code = 400
class ProviderModelCurrentlyNotSupportError(BaseHTTPException):
error_code = 'model_currently_not_support'
description = "GPT-4 currently not support."
description = "Dify Hosted OpenAI trial currently not support the GPT-4 model."
code = 400
@ -52,11 +54,35 @@ class CompletionRequestError(BaseHTTPException):
class AppMoreLikeThisDisabledError(BaseHTTPException):
error_code = 'app_more_like_this_disabled'
description = "More like this disabled."
description = "The 'More like this' feature is disabled. Please refresh your page."
code = 403
class AppSuggestedQuestionsAfterAnswerDisabledError(BaseHTTPException):
error_code = 'app_suggested_questions_after_answer_disabled'
description = "Function Suggested questions after answer disabled."
description = "The 'Suggested Questions After Answer' feature is disabled. Please refresh your page."
code = 403
class NoAudioUploadedError(BaseHTTPException):
error_code = 'no_audio_uploaded'
description = "Please upload your audio."
code = 400
class AudioTooLargeError(BaseHTTPException):
error_code = 'audio_too_large'
description = "Audio size exceeded. {message}"
code = 413
class UnsupportedAudioTypeError(BaseHTTPException):
error_code = 'unsupported_audio_type'
description = "Audio type not allowed."
code = 415
class ProviderNotSupportSpeechToTextError(BaseHTTPException):
error_code = 'provider_not_support_speech_to_text'
description = "Provider not support speech to text."
code = 400

View File

@ -101,8 +101,8 @@ class MessageMoreLikeThisApi(WebApiResource):
raise NotFound("Message Not Exists.")
except MoreLikeThisDisabledError:
raise AppMoreLikeThisDisabledError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
@ -129,8 +129,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
except MoreLikeThisDisabledError:
yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
except ProviderTokenNotInitError:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
except ProviderTokenNotInitError as ex:
yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
except QuotaExceededError:
yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
except ModelCurrentlyNotSupportError:
@ -167,8 +167,8 @@ class MessageSuggestedQuestionApi(WebApiResource):
raise NotFound("Conversation not found")
except SuggestedQuestionsAfterAnswerDisabledError:
raise AppSuggestedQuestionsAfterAnswerDisabledError()
except ProviderTokenNotInitError:
raise ProviderNotInitializeError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:

View File

@ -0,0 +1,64 @@
# -*- coding:utf-8 -*-
import uuid
from controllers.web import api
from flask_restful import Resource
from flask import request
from werkzeug.exceptions import Unauthorized, NotFound
from models.model import Site, EndUser, App
from extensions.ext_database import db
from libs.passport import PassportService
class PassportResource(Resource):
"""Base resource for passport."""
def get(self):
app_id = request.headers.get('X-App-Code')
if app_id is None:
raise Unauthorized('X-App-Code header is missing.')
# get site from db and check if it is normal
site = db.session.query(Site).filter(
Site.code == app_id,
Site.status == 'normal'
).first()
if not site:
raise NotFound()
# get app from db and check if it is normal and enable_site
app_model = db.session.query(App).filter(App.id == site.app_id).first()
if not app_model or app_model.status != 'normal' or not app_model.enable_site:
raise NotFound()
end_user = EndUser(
tenant_id=app_model.tenant_id,
app_id=app_model.id,
type='browser',
is_anonymous=True,
session_id=generate_session_id(),
)
db.session.add(end_user)
db.session.commit()
payload = {
"iss": site.app_id,
'sub': 'Web API Passport',
'app_id': site.app_id,
'end_user_id': end_user.id,
}
tk = PassportService().issue(payload)
return {
'access_token': tk,
}
api.add_resource(PassportResource, '/passport')
def generate_session_id():
"""
Generate a unique session ID.
"""
while True:
session_id = str(uuid.uuid4())
existing_count = db.session.query(EndUser) \
.filter(EndUser.session_id == session_id).count()
if existing_count == 0:
return session_id

View File

@ -1,107 +1,50 @@
# -*- coding:utf-8 -*-
import uuid
from functools import wraps
from flask import request, session
from flask import request
from flask_restful import Resource
from werkzeug.exceptions import NotFound, Unauthorized
from extensions.ext_database import db
from models.model import App, Site, EndUser
from models.model import App, EndUser
from libs.passport import PassportService
def validate_token(view=None):
def validate_jwt_token(view=None):
def decorator(view):
@wraps(view)
def decorated(*args, **kwargs):
site = validate_and_get_site()
app_model = db.session.query(App).get(site.app_id)
if not app_model:
raise NotFound()
if app_model.status != 'normal':
raise NotFound()
if not app_model.enable_site:
raise NotFound()
end_user = create_or_update_end_user_for_session(app_model)
app_model, end_user = decode_jwt_token()
return view(app_model, end_user, *args, **kwargs)
return decorated
if view:
return decorator(view)
return decorator
def validate_and_get_site():
"""
Validate and get API token.
"""
def decode_jwt_token():
auth_header = request.headers.get('Authorization')
if auth_header is None:
raise Unauthorized()
raise Unauthorized('Authorization header is missing.')
auth_scheme, auth_token = auth_header.split(None, 1)
if ' ' not in auth_header:
raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
auth_scheme, tk = auth_header.split(None, 1)
auth_scheme = auth_scheme.lower()
if auth_scheme != 'bearer':
raise Unauthorized()
site = db.session.query(Site).filter(
Site.code == auth_token,
Site.status == 'normal'
).first()
if not site:
raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
decoded = PassportService().verify(tk)
app_model = db.session.query(App).filter(App.id == decoded['app_id']).first()
if not app_model:
raise NotFound()
if app_model.enable_site is False:
raise Unauthorized('Site is disabled.')
end_user = db.session.query(EndUser).filter(EndUser.id == decoded['end_user_id']).first()
if not end_user:
raise NotFound()
return site
def create_or_update_end_user_for_session(app_model):
"""
Create or update session terminal based on session ID.
"""
if 'session_id' not in session:
session['session_id'] = generate_session_id()
session_id = session.get('session_id')
end_user = db.session.query(EndUser) \
.filter(
EndUser.session_id == session_id,
EndUser.type == 'browser'
).first()
if end_user is None:
end_user = EndUser(
tenant_id=app_model.tenant_id,
app_id=app_model.id,
type='browser',
is_anonymous=True,
session_id=session_id
)
db.session.add(end_user)
db.session.commit()
return end_user
def generate_session_id():
"""
Generate a unique session ID.
"""
count = 1
session_id = ''
while count != 0:
session_id = str(uuid.uuid4())
count = db.session.query(EndUser) \
.filter(EndUser.session_id == session_id).count()
return session_id
return app_model, end_user
class WebApiResource(Resource):
method_decorators = [validate_token]
method_decorators = [validate_jwt_token]

View File

@ -3,50 +3,34 @@ from typing import Optional
import langchain
from flask import Flask
from jieba.analyse import default_tfidf
from langchain import set_handler
from langchain.prompts.base import DEFAULT_FORMATTER_MAPPING
from llama_index import IndexStructType, QueryMode
from llama_index.indices.registry import INDEX_STRUT_TYPE_TO_QUERY_MAP
from pydantic import BaseModel
from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
from core.index.keyword_table.jieba_keyword_table import GPTJIEBAKeywordTableIndex
from core.index.keyword_table.stopwords import STOPWORDS
from core.prompt.prompt_template import OneLineFormatter
from core.vector_store.vector_store import VectorStore
from core.vector_store.vector_store_index_query import EnhanceGPTVectorStoreIndexQuery
class HostedOpenAICredential(BaseModel):
api_key: str
class HostedAnthropicCredential(BaseModel):
api_key: str
class HostedLLMCredentials(BaseModel):
openai: Optional[HostedOpenAICredential] = None
anthropic: Optional[HostedAnthropicCredential] = None
hosted_llm_credentials = HostedLLMCredentials()
def init_app(app: Flask):
formatter = OneLineFormatter()
DEFAULT_FORMATTER_MAPPING['f-string'] = formatter.format
INDEX_STRUT_TYPE_TO_QUERY_MAP[IndexStructType.KEYWORD_TABLE] = GPTJIEBAKeywordTableIndex.get_query_map()
INDEX_STRUT_TYPE_TO_QUERY_MAP[IndexStructType.WEAVIATE] = {
QueryMode.DEFAULT: EnhanceGPTVectorStoreIndexQuery,
QueryMode.EMBEDDING: EnhanceGPTVectorStoreIndexQuery,
}
INDEX_STRUT_TYPE_TO_QUERY_MAP[IndexStructType.QDRANT] = {
QueryMode.DEFAULT: EnhanceGPTVectorStoreIndexQuery,
QueryMode.EMBEDDING: EnhanceGPTVectorStoreIndexQuery,
}
default_tfidf.stop_words = STOPWORDS
if os.environ.get("DEBUG") and os.environ.get("DEBUG").lower() == 'true':
langchain.verbose = True
set_handler(DifyStdOutCallbackHandler())
if app.config.get("OPENAI_API_KEY"):
hosted_llm_credentials.openai = HostedOpenAICredential(api_key=app.config.get("OPENAI_API_KEY"))
if app.config.get("ANTHROPIC_API_KEY"):
hosted_llm_credentials.anthropic = HostedAnthropicCredential(api_key=app.config.get("ANTHROPIC_API_KEY"))

View File

@ -0,0 +1,35 @@
from typing import cast, List
from langchain import OpenAI
from langchain.base_language import BaseLanguageModel
from langchain.chat_models.openai import ChatOpenAI
from langchain.schema import BaseMessage
from core.constant import llm_constant
class CalcTokenMixin:
def get_num_tokens_from_messages(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
llm = cast(ChatOpenAI, llm)
return llm.get_num_tokens_from_messages(messages)
def get_message_rest_tokens(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
"""
Got the rest tokens available for the model after excluding messages tokens and completion max tokens
:param llm:
:param messages:
:return:
"""
llm = cast(ChatOpenAI, llm)
llm_max_tokens = llm_constant.max_context_token_length[llm.model_name]
completion_max_tokens = llm.max_tokens
used_tokens = self.get_num_tokens_from_messages(llm, messages, **kwargs)
rest_tokens = llm_max_tokens - completion_max_tokens - used_tokens
return rest_tokens
class ExceededLLMTokensLimitError(Exception):
pass

View File

@ -0,0 +1,83 @@
from typing import Tuple, List, Any, Union, Sequence, Optional, cast
from langchain.agents import OpenAIFunctionsAgent, BaseSingleActionAgent
from langchain.callbacks.base import BaseCallbackManager
from langchain.callbacks.manager import Callbacks
from langchain.prompts.chat import BaseMessagePromptTemplate
from langchain.schema import AgentAction, AgentFinish, BaseLanguageModel, SystemMessage
from langchain.tools import BaseTool
from core.tool.dataset_retriever_tool import DatasetRetrieverTool
class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
"""
An Multi Dataset Retrieve Agent driven by Router.
"""
def should_use_agent(self, query: str):
"""
return should use agent
:param query:
:return:
"""
return True
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date, along with observations
**kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
if len(self.tools) == 0:
return AgentFinish(return_values={"output": ''}, log='')
elif len(self.tools) == 1:
tool = next(iter(self.tools))
tool = cast(DatasetRetrieverTool, tool)
rst = tool.run(tool_input={'dataset_id': tool.dataset_id, 'query': kwargs['input']})
return AgentFinish(return_values={"output": rst}, log=rst)
if intermediate_steps:
_, observation = intermediate_steps[-1]
return AgentFinish(return_values={"output": observation}, log=observation)
return super().plan(intermediate_steps, callbacks, **kwargs)
async def aplan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
raise NotImplementedError()
@classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
),
**kwargs: Any,
) -> BaseSingleActionAgent:
return super().from_llm_and_tools(
llm=llm,
tools=tools,
callback_manager=callback_manager,
extra_prompt_messages=extra_prompt_messages,
system_message=system_message,
**kwargs,
)

View File

@ -0,0 +1,112 @@
from typing import List, Tuple, Any, Union, Sequence, Optional
from langchain.agents import OpenAIFunctionsAgent, BaseSingleActionAgent
from langchain.agents.openai_functions_agent.base import _parse_ai_message, \
_format_intermediate_steps
from langchain.callbacks.base import BaseCallbackManager
from langchain.callbacks.manager import Callbacks
from langchain.prompts.chat import BaseMessagePromptTemplate
from langchain.schema import AgentAction, AgentFinish, SystemMessage, BaseLanguageModel
from langchain.tools import BaseTool
from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError
from core.agent.agent.openai_function_call_summarize_mixin import OpenAIFunctionCallSummarizeMixin
class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, OpenAIFunctionCallSummarizeMixin):
@classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
),
**kwargs: Any,
) -> BaseSingleActionAgent:
return super().from_llm_and_tools(
llm=llm,
tools=tools,
callback_manager=callback_manager,
extra_prompt_messages=extra_prompt_messages,
system_message=cls.get_system_message(),
**kwargs,
)
def should_use_agent(self, query: str):
"""
return should use agent
:param query:
:return:
"""
original_max_tokens = self.llm.max_tokens
self.llm.max_tokens = 15
prompt = self.prompt.format_prompt(input=query, agent_scratchpad=[])
messages = prompt.to_messages()
predicted_message = self.llm.predict_messages(
messages, functions=self.functions, callbacks=None
)
function_call = predicted_message.additional_kwargs.get("function_call", {})
self.llm.max_tokens = original_max_tokens
return True if function_call else False
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date, along with observations
**kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
agent_scratchpad = _format_intermediate_steps(intermediate_steps)
selected_inputs = {
k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
}
full_inputs = dict(**selected_inputs, agent_scratchpad=agent_scratchpad)
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
# summarize messages if rest_tokens < 0
try:
messages = self.summarize_messages_if_needed(self.llm, messages, functions=self.functions)
except ExceededLLMTokensLimitError as e:
return AgentFinish(return_values={"output": str(e)}, log=str(e))
predicted_message = self.llm.predict_messages(
messages, functions=self.functions, callbacks=callbacks
)
agent_decision = _parse_ai_message(predicted_message)
return agent_decision
@classmethod
def get_system_message(cls):
return SystemMessage(content="You are a helpful AI assistant.\n"
"The current date or current time you know is wrong.\n"
"Respond directly if appropriate.")
def return_stopped_response(
self,
early_stopping_method: str,
intermediate_steps: List[Tuple[AgentAction, str]],
**kwargs: Any,
) -> AgentFinish:
try:
return super().return_stopped_response(early_stopping_method, intermediate_steps, **kwargs)
except ValueError:
return AgentFinish({"output": "I'm sorry, I don't know how to respond to that."}, "")

View File

@ -0,0 +1,132 @@
from typing import cast, List
from langchain.chat_models import ChatOpenAI
from langchain.chat_models.openai import _convert_message_to_dict
from langchain.memory.summary import SummarizerMixin
from langchain.schema import SystemMessage, HumanMessage, BaseMessage, AIMessage, BaseLanguageModel
from pydantic import BaseModel
from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError, CalcTokenMixin
class OpenAIFunctionCallSummarizeMixin(BaseModel, CalcTokenMixin):
moving_summary_buffer: str = ""
moving_summary_index: int = 0
summary_llm: BaseLanguageModel
def summarize_messages_if_needed(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> List[BaseMessage]:
# calculate rest tokens and summarize previous function observation messages if rest_tokens < 0
rest_tokens = self.get_message_rest_tokens(llm, messages, **kwargs)
rest_tokens = rest_tokens - 20 # to deal with the inaccuracy of rest_tokens
if rest_tokens >= 0:
return messages
system_message = None
human_message = None
should_summary_messages = []
for message in messages:
if isinstance(message, SystemMessage):
system_message = message
elif isinstance(message, HumanMessage):
human_message = message
else:
should_summary_messages.append(message)
if len(should_summary_messages) > 2:
ai_message = should_summary_messages[-2]
function_message = should_summary_messages[-1]
should_summary_messages = should_summary_messages[self.moving_summary_index:-2]
self.moving_summary_index = len(should_summary_messages)
else:
error_msg = "Exceeded LLM tokens limit, stopped."
raise ExceededLLMTokensLimitError(error_msg)
new_messages = [system_message, human_message]
if self.moving_summary_index == 0:
should_summary_messages.insert(0, human_message)
summary_handler = SummarizerMixin(llm=self.summary_llm)
self.moving_summary_buffer = summary_handler.predict_new_summary(
messages=should_summary_messages,
existing_summary=self.moving_summary_buffer
)
new_messages.append(AIMessage(content=self.moving_summary_buffer))
new_messages.append(ai_message)
new_messages.append(function_message)
return new_messages
def get_num_tokens_from_messages(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
"""Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package.
Official documentation: https://github.com/openai/openai-cookbook/blob/
main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb"""
llm = cast(ChatOpenAI, llm)
model, encoding = llm._get_encoding_model()
if model.startswith("gpt-3.5-turbo"):
# every message follows <im_start>{role/name}\n{content}<im_end>\n
tokens_per_message = 4
# if there's a name, the role is omitted
tokens_per_name = -1
elif model.startswith("gpt-4"):
tokens_per_message = 3
tokens_per_name = 1
else:
raise NotImplementedError(
f"get_num_tokens_from_messages() is not presently implemented "
f"for model {model}."
"See https://github.com/openai/openai-python/blob/main/chatml.md for "
"information on how messages are converted to tokens."
)
num_tokens = 0
for m in messages:
message = _convert_message_to_dict(m)
num_tokens += tokens_per_message
for key, value in message.items():
if key == "function_call":
for f_key, f_value in value.items():
num_tokens += len(encoding.encode(f_key))
num_tokens += len(encoding.encode(f_value))
else:
num_tokens += len(encoding.encode(value))
if key == "name":
num_tokens += tokens_per_name
# every reply is primed with <im_start>assistant
num_tokens += 3
if kwargs.get('functions'):
for function in kwargs.get('functions'):
num_tokens += len(encoding.encode('name'))
num_tokens += len(encoding.encode(function.get("name")))
num_tokens += len(encoding.encode('description'))
num_tokens += len(encoding.encode(function.get("description")))
parameters = function.get("parameters")
num_tokens += len(encoding.encode('parameters'))
if 'title' in parameters:
num_tokens += len(encoding.encode('title'))
num_tokens += len(encoding.encode(parameters.get("title")))
num_tokens += len(encoding.encode('type'))
num_tokens += len(encoding.encode(parameters.get("type")))
if 'properties' in parameters:
num_tokens += len(encoding.encode('properties'))
for key, value in parameters.get('properties').items():
num_tokens += len(encoding.encode(key))
for field_key, field_value in value.items():
num_tokens += len(encoding.encode(field_key))
if field_key == 'enum':
for enum_field in field_value:
num_tokens += 3
num_tokens += len(encoding.encode(enum_field))
else:
num_tokens += len(encoding.encode(field_key))
num_tokens += len(encoding.encode(str(field_value)))
if 'required' in parameters:
num_tokens += len(encoding.encode('required'))
for required_field in parameters['required']:
num_tokens += 3
num_tokens += len(encoding.encode(required_field))
return num_tokens

View File

@ -0,0 +1,102 @@
from typing import List, Tuple, Any, Union, Sequence, Optional
from langchain.agents import BaseMultiActionAgent
from langchain.agents.openai_functions_multi_agent.base import OpenAIMultiFunctionsAgent, _format_intermediate_steps, \
_parse_ai_message
from langchain.callbacks.base import BaseCallbackManager
from langchain.callbacks.manager import Callbacks
from langchain.prompts.chat import BaseMessagePromptTemplate
from langchain.schema import AgentAction, AgentFinish, SystemMessage, BaseLanguageModel
from langchain.tools import BaseTool
from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError
from core.agent.agent.openai_function_call_summarize_mixin import OpenAIFunctionCallSummarizeMixin
class AutoSummarizingOpenMultiAIFunctionCallAgent(OpenAIMultiFunctionsAgent, OpenAIFunctionCallSummarizeMixin):
@classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
),
**kwargs: Any,
) -> BaseMultiActionAgent:
return super().from_llm_and_tools(
llm=llm,
tools=tools,
callback_manager=callback_manager,
extra_prompt_messages=extra_prompt_messages,
system_message=cls.get_system_message(),
**kwargs,
)
def should_use_agent(self, query: str):
"""
return should use agent
:param query:
:return:
"""
original_max_tokens = self.llm.max_tokens
self.llm.max_tokens = 15
prompt = self.prompt.format_prompt(input=query, agent_scratchpad=[])
messages = prompt.to_messages()
predicted_message = self.llm.predict_messages(
messages, functions=self.functions, callbacks=None
)
function_call = predicted_message.additional_kwargs.get("function_call", {})
self.llm.max_tokens = original_max_tokens
return True if function_call else False
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date, along with observations
**kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
agent_scratchpad = _format_intermediate_steps(intermediate_steps)
selected_inputs = {
k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
}
full_inputs = dict(**selected_inputs, agent_scratchpad=agent_scratchpad)
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
# summarize messages if rest_tokens < 0
try:
messages = self.summarize_messages_if_needed(self.llm, messages, functions=self.functions)
except ExceededLLMTokensLimitError as e:
return AgentFinish(return_values={"output": str(e)}, log=str(e))
predicted_message = self.llm.predict_messages(
messages, functions=self.functions, callbacks=callbacks
)
agent_decision = _parse_ai_message(predicted_message)
return agent_decision
@classmethod
def get_system_message(cls):
# get current time
return SystemMessage(content="You are a helpful AI assistant.\n"
"The current date or current time you know is wrong.\n"
"Respond directly if appropriate.")

View File

@ -0,0 +1,29 @@
import json
import re
from typing import Union
from langchain.agents.structured_chat.output_parser import StructuredChatOutputParser as LCStructuredChatOutputParser, \
logger
from langchain.schema import AgentAction, AgentFinish, OutputParserException
class StructuredChatOutputParser(LCStructuredChatOutputParser):
def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
try:
action_match = re.search(r"```(.*?)\n(.*?)```?", text, re.DOTALL)
if action_match is not None:
response = json.loads(action_match.group(2).strip(), strict=False)
if isinstance(response, list):
# gpt turbo frequently ignores the directive to emit a single action
logger.warning("Got multiple action responses: %s", response)
response = response[0]
if response["action"] == "Final Answer":
return AgentFinish({"output": response["action_input"]}, text)
else:
return AgentAction(
response["action"], response.get("action_input", {}), text
)
else:
return AgentFinish({"output": text}, text)
except Exception as e:
raise OutputParserException(f"Could not parse LLM output: {text}") from e

View File

@ -0,0 +1,182 @@
import re
from typing import List, Tuple, Any, Union, Sequence, Optional
from langchain import BasePromptTemplate
from langchain.agents import StructuredChatAgent, AgentOutputParser, Agent
from langchain.agents.structured_chat.base import HUMAN_MESSAGE_TEMPLATE
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.base import BaseCallbackManager
from langchain.callbacks.manager import Callbacks
from langchain.memory.summary import SummarizerMixin
from langchain.prompts import SystemMessagePromptTemplate, HumanMessagePromptTemplate, ChatPromptTemplate
from langchain.schema import AgentAction, AgentFinish, AIMessage, HumanMessage
from langchain.tools import BaseTool
from langchain.agents.structured_chat.prompt import PREFIX, SUFFIX
from core.agent.agent.calc_token_mixin import CalcTokenMixin, ExceededLLMTokensLimitError
FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
The nouns in the format of "Thought", "Action", "Action Input", "Final Answer" must be expressed in English.
Valid "action" values: "Final Answer" or {tool_names}
Provide only ONE action per $JSON_BLOB, as shown:
```
{{{{
"action": $TOOL_NAME,
"action_input": $INPUT
}}}}
```
Follow this format:
Question: input question to answer
Thought: consider previous and subsequent steps
Action:
```
$JSON_BLOB
```
Observation: action result
... (repeat Thought/Action/Observation N times)
Thought: I know what to respond
Action:
```
{{{{
"action": "Final Answer",
"action_input": "Final response to human"
}}}}
```"""
class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
moving_summary_buffer: str = ""
moving_summary_index: int = 0
summary_llm: BaseLanguageModel
def should_use_agent(self, query: str):
"""
return should use agent
Using the ReACT mode to determine whether an agent is needed is costly,
so it's better to just use an Agent for reasoning, which is cheaper.
:param query:
:return:
"""
return True
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date,
along with observations
callbacks: Callbacks to run.
**kwargs: User inputs.
Returns:
Action specifying what tool to use.
"""
full_inputs = self.get_full_inputs(intermediate_steps, **kwargs)
prompts, _ = self.llm_chain.prep_prompts(input_list=[self.llm_chain.prep_inputs(full_inputs)])
messages = []
if prompts:
messages = prompts[0].to_messages()
rest_tokens = self.get_message_rest_tokens(self.llm_chain.llm, messages)
if rest_tokens < 0:
full_inputs = self.summarize_messages(intermediate_steps, **kwargs)
full_output = self.llm_chain.predict(callbacks=callbacks, **full_inputs)
return self.output_parser.parse(full_output)
def summarize_messages(self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs):
if len(intermediate_steps) >= 2:
should_summary_intermediate_steps = intermediate_steps[self.moving_summary_index:-1]
should_summary_messages = [AIMessage(content=observation)
for _, observation in should_summary_intermediate_steps]
if self.moving_summary_index == 0:
should_summary_messages.insert(0, HumanMessage(content=kwargs.get("input")))
self.moving_summary_index = len(intermediate_steps)
else:
error_msg = "Exceeded LLM tokens limit, stopped."
raise ExceededLLMTokensLimitError(error_msg)
summary_handler = SummarizerMixin(llm=self.summary_llm)
if self.moving_summary_buffer and 'chat_history' in kwargs:
kwargs["chat_history"].pop()
self.moving_summary_buffer = summary_handler.predict_new_summary(
messages=should_summary_messages,
existing_summary=self.moving_summary_buffer
)
if 'chat_history' in kwargs:
kwargs["chat_history"].append(AIMessage(content=self.moving_summary_buffer))
return self.get_full_inputs([intermediate_steps[-1]], **kwargs)
@classmethod
def create_prompt(
cls,
tools: Sequence[BaseTool],
prefix: str = PREFIX,
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
) -> BasePromptTemplate:
tool_strings = []
for tool in tools:
args_schema = re.sub("}", "}}}}", re.sub("{", "{{{{", str(tool.args)))
tool_strings.append(f"{tool.name}: {tool.description}, args: {args_schema}")
formatted_tools = "\n".join(tool_strings)
tool_names = ", ".join([('"' + tool.name + '"') for tool in tools])
format_instructions = format_instructions.format(tool_names=tool_names)
template = "\n\n".join([prefix, formatted_tools, format_instructions, suffix])
if input_variables is None:
input_variables = ["input", "agent_scratchpad"]
_memory_prompts = memory_prompts or []
messages = [
SystemMessagePromptTemplate.from_template(template),
*_memory_prompts,
HumanMessagePromptTemplate.from_template(human_message_template),
]
return ChatPromptTemplate(input_variables=input_variables, messages=messages)
@classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
output_parser: Optional[AgentOutputParser] = None,
prefix: str = PREFIX,
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
**kwargs: Any,
) -> Agent:
return super().from_llm_and_tools(
llm=llm,
tools=tools,
callback_manager=callback_manager,
output_parser=output_parser,
prefix=prefix,
suffix=suffix,
human_message_template=human_message_template,
format_instructions=format_instructions,
input_variables=input_variables,
memory_prompts=memory_prompts,
**kwargs,
)

View File

@ -1,89 +0,0 @@
from typing import Optional
from langchain import LLMChain
from langchain.agents import ZeroShotAgent, AgentExecutor, ConversationalAgent
from langchain.callbacks import CallbackManager
from langchain.memory.chat_memory import BaseChatMemory
from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
from core.callback_handler.dataset_tool_callback_handler import DatasetToolCallbackHandler
from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
from core.llm.llm_builder import LLMBuilder
class AgentBuilder:
@classmethod
def to_agent_chain(cls, tenant_id: str, tools, memory: Optional[BaseChatMemory],
dataset_tool_callback_handler: DatasetToolCallbackHandler,
agent_loop_gather_callback_handler: AgentLoopGatherCallbackHandler):
llm_callback_manager = CallbackManager([agent_loop_gather_callback_handler, DifyStdOutCallbackHandler()])
llm = LLMBuilder.to_llm(
tenant_id=tenant_id,
model_name=agent_loop_gather_callback_handler.model_name,
temperature=0,
max_tokens=1024,
callback_manager=llm_callback_manager
)
tool_callback_manager = CallbackManager([
agent_loop_gather_callback_handler,
dataset_tool_callback_handler,
DifyStdOutCallbackHandler()
])
for tool in tools:
tool.callback_manager = tool_callback_manager
prompt = cls.build_agent_prompt_template(
tools=tools,
memory=memory,
)
agent_llm_chain = LLMChain(
llm=llm,
prompt=prompt,
)
agent = cls.build_agent(agent_llm_chain=agent_llm_chain, memory=memory)
agent_callback_manager = CallbackManager(
[agent_loop_gather_callback_handler, DifyStdOutCallbackHandler()]
)
agent_chain = AgentExecutor.from_agent_and_tools(
tools=tools,
agent=agent,
memory=memory,
callback_manager=agent_callback_manager,
max_iterations=6,
early_stopping_method="generate",
# `generate` will continue to complete the last inference after reaching the iteration limit or request time limit
)
return agent_chain
@classmethod
def build_agent_prompt_template(cls, tools, memory: Optional[BaseChatMemory]):
if memory:
prompt = ConversationalAgent.create_prompt(
tools=tools,
)
else:
prompt = ZeroShotAgent.create_prompt(
tools=tools,
)
return prompt
@classmethod
def build_agent(cls, agent_llm_chain: LLMChain, memory: Optional[BaseChatMemory]):
if memory:
agent = ConversationalAgent(
llm_chain=agent_llm_chain
)
else:
agent = ZeroShotAgent(
llm_chain=agent_llm_chain
)
return agent

View File

@ -0,0 +1,122 @@
import enum
import logging
from typing import Union, Optional
from langchain.agents import BaseSingleActionAgent, BaseMultiActionAgent
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.manager import Callbacks
from langchain.memory.chat_memory import BaseChatMemory
from langchain.tools import BaseTool
from pydantic import BaseModel, Extra
from core.agent.agent.multi_dataset_router_agent import MultiDatasetRouterAgent
from core.agent.agent.openai_function_call import AutoSummarizingOpenAIFunctionCallAgent
from core.agent.agent.openai_multi_function_call import AutoSummarizingOpenMultiAIFunctionCallAgent
from core.agent.agent.output_parser.structured_chat import StructuredChatOutputParser
from core.agent.agent.structured_chat import AutoSummarizingStructuredChatAgent
from langchain.agents import AgentExecutor as LCAgentExecutor
from core.tool.dataset_retriever_tool import DatasetRetrieverTool
class PlanningStrategy(str, enum.Enum):
ROUTER = 'router'
REACT = 'react'
FUNCTION_CALL = 'function_call'
MULTI_FUNCTION_CALL = 'multi_function_call'
class AgentConfiguration(BaseModel):
strategy: PlanningStrategy
llm: BaseLanguageModel
tools: list[BaseTool]
summary_llm: BaseLanguageModel
dataset_llm: BaseLanguageModel
memory: Optional[BaseChatMemory] = None
callbacks: Callbacks = None
max_iterations: int = 6
max_execution_time: Optional[float] = None
early_stopping_method: str = "generate"
# `generate` will continue to complete the last inference after reaching the iteration limit or request time limit
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
arbitrary_types_allowed = True
class AgentExecuteResult(BaseModel):
strategy: PlanningStrategy
output: Optional[str]
configuration: AgentConfiguration
class AgentExecutor:
def __init__(self, configuration: AgentConfiguration):
self.configuration = configuration
self.agent = self._init_agent()
def _init_agent(self) -> Union[BaseSingleActionAgent | BaseMultiActionAgent]:
if self.configuration.strategy == PlanningStrategy.REACT:
agent = AutoSummarizingStructuredChatAgent.from_llm_and_tools(
llm=self.configuration.llm,
tools=self.configuration.tools,
output_parser=StructuredChatOutputParser(),
summary_llm=self.configuration.summary_llm,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.FUNCTION_CALL:
agent = AutoSummarizingOpenAIFunctionCallAgent.from_llm_and_tools(
llm=self.configuration.llm,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None, # used for read chat histories memory
summary_llm=self.configuration.summary_llm,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.MULTI_FUNCTION_CALL:
agent = AutoSummarizingOpenMultiAIFunctionCallAgent.from_llm_and_tools(
llm=self.configuration.llm,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None, # used for read chat histories memory
summary_llm=self.configuration.summary_llm,
verbose=True
)
elif self.configuration.strategy == PlanningStrategy.ROUTER:
self.configuration.tools = [t for t in self.configuration.tools if isinstance(t, DatasetRetrieverTool)]
agent = MultiDatasetRouterAgent.from_llm_and_tools(
llm=self.configuration.dataset_llm,
tools=self.configuration.tools,
extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None,
verbose=True
)
else:
raise NotImplementedError(f"Unknown Agent Strategy: {self.configuration.strategy}")
return agent
def should_use_agent(self, query: str) -> bool:
return self.agent.should_use_agent(query)
def run(self, query: str) -> AgentExecuteResult:
agent_executor = LCAgentExecutor.from_agent_and_tools(
agent=self.agent,
tools=self.configuration.tools,
memory=self.configuration.memory,
max_iterations=self.configuration.max_iterations,
max_execution_time=self.configuration.max_execution_time,
early_stopping_method=self.configuration.early_stopping_method,
callbacks=self.configuration.callbacks
)
try:
output = agent_executor.run(query)
except Exception:
logging.exception("agent_executor run failed")
output = None
return AgentExecuteResult(
output=output,
strategy=self.configuration.strategy,
configuration=self.configuration
)

View File

@ -1,10 +1,12 @@
import json
import logging
import time
from typing import Any, Dict, List, Union, Optional
from langchain.agents import openai_functions_agent, openai_functions_multi_agent
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
from langchain.schema import AgentAction, AgentFinish, LLMResult, ChatGeneration
from core.callback_handler.entity.agent_loop import AgentLoop
from core.conversation_message_task import ConversationMessageTask
@ -12,6 +14,7 @@ from core.conversation_message_task import ConversationMessageTask
class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
"""Callback Handler that prints to std out."""
raise_error: bool = True
def __init__(self, model_name, conversation_message_task: ConversationMessageTask) -> None:
"""Initialize callback handler."""
@ -19,6 +22,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
self.conversation_message_task = conversation_message_task
self._agent_loops = []
self._current_loop = None
self._message_agent_thought = None
self.current_chain = None
@property
@ -28,6 +32,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
def clear_agent_loops(self) -> None:
self._agent_loops = []
self._current_loop = None
self._message_agent_thought = None
@property
def always_verbose(self) -> bool:
@ -60,13 +65,21 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
# kwargs={}
if self._current_loop and self._current_loop.status == 'llm_started':
self._current_loop.status = 'llm_end'
self._current_loop.prompt_tokens = response.llm_output['token_usage']['prompt_tokens']
self._current_loop.completion = response.generations[0][0].text
self._current_loop.completion_tokens = response.llm_output['token_usage']['completion_tokens']
if response.llm_output:
self._current_loop.prompt_tokens = response.llm_output['token_usage']['prompt_tokens']
completion_generation = response.generations[0][0]
if isinstance(completion_generation, ChatGeneration):
completion_message = completion_generation.message
if 'function_call' in completion_message.additional_kwargs:
self._current_loop.completion \
= json.dumps({'function_call': completion_message.additional_kwargs['function_call']})
else:
self._current_loop.completion = response.generations[0][0].text
else:
self._current_loop.completion = completion_generation.text
def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Do nothing."""
pass
if response.llm_output:
self._current_loop.completion_tokens = response.llm_output['token_usage']['completion_tokens']
def on_llm_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
@ -74,21 +87,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
logging.error(error)
self._agent_loops = []
self._current_loop = None
def on_chain_start(
self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
) -> None:
"""Print out that we are entering a chain."""
pass
def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
"""Print out that we finished a chain."""
pass
def on_chain_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> None:
logging.error(error)
self._message_agent_thought = None
def on_tool_start(
self,
@ -107,15 +106,29 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
) -> Any:
"""Run on agent action."""
tool = action.tool
tool_input = action.tool_input
action_name_position = action.log.index("\nAction:") + 1 if action.log else -1
thought = action.log[:action_name_position].strip() if action.log else ''
tool_input = json.dumps({"query": action.tool_input}
if isinstance(action.tool_input, str) else action.tool_input)
completion = None
if isinstance(action, openai_functions_agent.base._FunctionsAgentAction) \
or isinstance(action, openai_functions_multi_agent.base._FunctionsAgentAction):
thought = action.log.strip()
completion = json.dumps({'function_call': action.message_log[0].additional_kwargs['function_call']})
else:
action_name_position = action.log.index("Action:") if action.log else -1
thought = action.log[:action_name_position].strip() if action.log else ''
if self._current_loop and self._current_loop.status == 'llm_end':
self._current_loop.status = 'agent_action'
self._current_loop.thought = thought
self._current_loop.tool_name = tool
self._current_loop.tool_input = tool_input
if completion is not None:
self._current_loop.completion = completion
self._message_agent_thought = self.conversation_message_task.on_agent_start(
self.current_chain,
self._current_loop
)
def on_tool_end(
self,
@ -138,10 +151,13 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
self._current_loop.completed_at = time.perf_counter()
self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
self.conversation_message_task.on_agent_end(self.current_chain, self.model_name, self._current_loop)
self.conversation_message_task.on_agent_end(
self._message_agent_thought, self.model_name, self._current_loop
)
self._agent_loops.append(self._current_loop)
self._current_loop = None
self._message_agent_thought = None
def on_tool_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
@ -150,16 +166,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
logging.error(error)
self._agent_loops = []
self._current_loop = None
def on_text(
self,
text: str,
color: Optional[str] = None,
end: str = "",
**kwargs: Optional[str],
) -> None:
"""Run on additional input from chains and agents."""
pass
self._message_agent_thought = None
def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
"""Run on agent end."""
@ -169,10 +176,18 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
self._current_loop.completed = True
self._current_loop.completed_at = time.perf_counter()
self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
self._current_loop.thought = '[DONE]'
self._message_agent_thought = self.conversation_message_task.on_agent_start(
self.current_chain,
self._current_loop
)
self.conversation_message_task.on_agent_end(self.current_chain, self.model_name, self._current_loop)
self.conversation_message_task.on_agent_end(
self._message_agent_thought, self.model_name, self._current_loop
)
self._agent_loops.append(self._current_loop)
self._current_loop = None
self._message_agent_thought = None
elif not self._current_loop and self._agent_loops:
self._agent_loops[-1].status = 'agent_finish'

View File

@ -1,9 +1,9 @@
import json
import logging
from typing import Any, Dict, List, Union, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
from core.callback_handler.entity.dataset_query import DatasetQueryObj
from core.conversation_message_task import ConversationMessageTask
@ -11,6 +11,7 @@ from core.conversation_message_task import ConversationMessageTask
class DatasetToolCallbackHandler(BaseCallbackHandler):
"""Callback Handler that prints to std out."""
raise_error: bool = True
def __init__(self, conversation_message_task: ConversationMessageTask) -> None:
"""Initialize callback handler."""
@ -43,9 +44,11 @@ class DatasetToolCallbackHandler(BaseCallbackHandler):
input_str: str,
**kwargs: Any,
) -> None:
tool_name = serialized.get('name')
dataset_id = tool_name[len("dataset-"):]
self.conversation_message_task.on_dataset_query_end(DatasetQueryObj(dataset_id=dataset_id, query=input_str))
# tool_name = serialized.get('name')
input_dict = json.loads(input_str.replace("'", "\""))
dataset_id = input_dict.get('dataset_id')
query = input_dict.get('query')
self.conversation_message_task.on_dataset_query_end(DatasetQueryObj(dataset_id=dataset_id, query=query))
def on_tool_end(
self,
@ -66,52 +69,3 @@ class DatasetToolCallbackHandler(BaseCallbackHandler):
) -> None:
"""Do nothing."""
logging.error(error)
def on_chain_start(
self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
) -> None:
pass
def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
pass
def on_chain_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> None:
pass
def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
pass
def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
pass
def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Do nothing."""
pass
def on_llm_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> None:
logging.error(error)
def on_agent_action(
self, action: AgentAction, color: Optional[str] = None, **kwargs: Any
) -> Any:
pass
def on_text(
self,
text: str,
color: Optional[str] = None,
end: str = "",
**kwargs: Optional[str],
) -> None:
"""Run on additional input from chains and agents."""
pass
def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
"""Run on agent end."""
pass

View File

@ -10,9 +10,9 @@ class AgentLoop(BaseModel):
tool_output: str = None
prompt: str = None
prompt_tokens: int = None
prompt_tokens: int = 0
completion: str = None
completion_tokens: int = None
completion_tokens: int = 0
latency: float = None

Some files were not shown because too many files have changed in this diff Show More