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165 Commits

Author SHA1 Message Date
dependabot[bot]
37c672b891 chore(deps): bump actions/setup-python from 5 to 6
Bumps [actions/setup-python](https://github.com/actions/setup-python) from 5 to 6.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-09-04 20:22:48 +00:00
Alex
f7db22edff Merge pull request #1937 from ManishMadan2882/main
Connectors: Google Drive Ingestion
2025-09-04 12:05:15 +01:00
ManishMadan2882
5a9bc6d2bf (feat:connector) infinite scroll file pick 2025-09-04 08:35:41 +05:30
ManishMadan2882
f7f6042579 (feat:connector) paginate files 2025-09-04 07:58:12 +05:30
ManishMadan2882
c4a598f3d3 (lint-fix) ruff 2025-09-03 19:29:34 +05:30
ManishMadan2882
7e2cbdd88c (feat:connector) redirect url as backend overhead 2025-09-03 09:57:13 +05:30
ManishMadan2882
3b3a04a249 (feat:connector) sync fixes UI, minor refactor 2025-09-02 20:28:23 +05:30
ManishMadan2882
f9b2c95695 (feat:connector) sync, simply re-ingest 2025-09-02 18:06:04 +05:30
ManishMadan2882
c2c18e8319 (feat:connector,fe) sync api, notification 2025-09-02 13:36:41 +05:30
ManishMadan2882
384ad3e0ac (feat:connector) raw sync flow 2025-09-02 13:34:31 +05:30
ManishMadan2882
8c986aaa7f Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-09-01 12:05:17 +05:30
ManishMadan2882
bb4ea76d30 (fix:connectorTree) path navigation fn 2025-09-01 12:04:58 +05:30
ManishMadan2882
2868e47cf8 (feat:connector) provider metadata, separate fe nested display 2025-08-29 18:05:58 +05:30
GH Action - Upstream Sync
e0adc3e5d5 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-29 01:36:09 +00:00
ManishMadan2882
e55d1a5865 (feat:connector,auth) consider user_id 2025-08-29 02:13:51 +05:30
ManishMadan2882
018273c6b2 (feat:connector) refactor, updated routes FE 2025-08-29 01:06:40 +05:30
Alex
44b8a11c04 Merge pull request #1936 from Ankit-Matth/feature/load-containers-from-dockerhub
Speed up scripts by loading containers from docker hub
2025-08-28 14:48:08 +01:00
Siddhant Rai
56e5aba559 fix: correct frontend image name in docker-compose configuration 2025-08-28 18:21:54 +05:30
Alex
46904ccd54 feat: add theme color meta tags for light and dark modes 2025-08-28 11:36:42 +01:00
Siddhant Rai
5b7c7a4471 fix: update Docker images in docker-compose to use 'develop' tag 2025-08-28 12:11:06 +05:30
Siddhant Rai
9da4215d1f feat: implement Docker Hub integration for building and pushing images in CI/CD workflow 2025-08-28 12:01:04 +05:30
ManishMadan2882
f39ac9945f (feat:auth) follow connector-session 2025-08-28 00:53:19 +05:30
ManishMadan2882
a0cc2e4d46 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-28 00:51:29 +05:30
ManishMadan2882
4065041a9f (feat:connectors) separate routes, namespace 2025-08-28 00:51:09 +05:30
GH Action - Upstream Sync
f08067a161 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-27 01:36:38 +00:00
Alex
545caacfa3 feat: prevent NUL character ingestion failures 2025-08-26 23:30:57 +01:00
Alex
a06f646637 feat: enhance tool call error handling 2025-08-26 22:37:21 +01:00
ManishMadan2882
578c68205a (feat:connectors) abstracting auth, base class 2025-08-26 02:46:36 +05:30
ManishMadan2882
f09f1433a9 (feat:connectors) separate layer 2025-08-26 01:38:36 +05:30
ManishMadan2882
15a9e97a1e (feat:ingest_connectors) spread config params 2025-08-26 00:56:39 +05:30
Ankit Matth
b3af4ee50b speed up scripts by using docker hub 2025-08-24 08:59:19 +05:30
GH Action - Upstream Sync
e25b988dc8 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-23 01:35:35 +00:00
ManishMadan2882
2410bd8654 (fix:driveLoader) folder ingesting 2025-08-22 19:07:52 +05:30
Alex
44d21ab703 fix: passing sources and chunk if agent is shared 2025-08-22 13:36:31 +01:00
Alex
e283957c8f Fix source field retrieval in SharedAgent to handle DBRef correctly 2025-08-22 11:41:35 +01:00
ManishMadan2882
b1210c4902 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-22 13:36:52 +05:30
ManishMadan2882
e7430f0fbc (feat:googleDrive,fe) file tree 2025-08-22 13:36:32 +05:30
ManishMadan2882
92d6ae54c3 (fix:google-oauth) no explicit datetime compare 2025-08-22 13:35:03 +05:30
ManishMadan2882
f82be23ca9 (feat:ingestion) external drive connect 2025-08-22 13:33:21 +05:30
ManishMadan2882
8c3f75e3e2 (feat:ingestion) google drive loader 2025-08-22 13:32:40 +05:30
GH Action - Upstream Sync
193d59f193 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-22 01:38:59 +00:00
ManishMadan2882
c2bebbaefa (feat:oauth/drive) raw fe integrate 2025-08-22 03:29:57 +05:30
Alex
7ae5a9c5a5 Refactor diagramId initialization to use a combination of Date.now() and random string for uniqueness 2025-08-21 14:50:37 +01:00
ManishMadan2882
3b69bea23d (chore:settings)addefault oath creds 2025-08-21 17:02:23 +05:30
ManishMadan2882
ab05726b99 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-21 02:46:56 +05:30
ManishMadan2882
b2b04268e9 (feat:drive) oauth flow 2025-08-21 02:46:32 +05:30
Alex
927d10d66e Update README.md 2025-08-17 12:44:47 +03:00
Alex
b67329623c Update README.md 2025-08-16 13:51:40 +03:00
Alex
6a02bcf15b Merge pull request #1873 from ManishMadan2882/main
Sources are the new Docs
2025-08-13 18:24:35 +01:00
Alex
cd0fbf79a3 Merge pull request #1924 from siiddhantt/feat/agent-schema-response
feat: add support for structured output and JSON schema validation
2025-08-13 17:33:29 +01:00
Alex
15d2d0115b Merge branch 'main' into feat/agent-schema-response 2025-08-13 17:12:26 +01:00
ManishMadan2882
d1a0fe6e91 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-13 17:39:59 +05:30
ManishMadan2882
1db80d140f (fix) search dropdowns 2025-08-13 17:39:39 +05:30
Siddhant Rai
896dcf1f9e feat: add support for structured output and JSON schema validation 2025-08-13 13:29:51 +05:30
GH Action - Upstream Sync
819a12fb49 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-13 01:45:41 +00:00
Alex
c68273706c Merge pull request #1920 from hanzalahwaheed/fix/response-bubble-btns
fix: always show the response bubble buttons.
2025-08-13 00:14:01 +01:00
Hanzalah Waheed
6bb0cd535a fix: rm redundant states. track feedback state w prop var 2025-08-13 02:36:58 +04:00
Hanzalah Waheed
cb9ec69cf6 chore: refactor code to use ternary operator for error type check 2025-08-13 02:31:25 +04:00
Hanzalah Waheed
143854fa81 fix: show both like and dislike buttons 2025-08-13 02:11:47 +04:00
ManishMadan2882
2f48a3d7d5 (feat:chunks) consistent path header 2025-08-13 02:53:32 +05:30
ManishMadan2882
ec95dafe1e (feat:sources) matching the figma 2025-08-13 01:35:23 +05:30
ManishMadan2882
3d1fe724e5 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-12 18:05:11 +05:30
ManishMadan2882
5c615d6f2d (feat:sources) card ui 2025-08-12 18:04:40 +05:30
GH Action - Upstream Sync
d72558eb36 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-12 01:43:57 +00:00
ManishMadan2882
65c33ad915 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-12 03:09:13 +05:30
ManishMadan2882
9be128a963 (feat:sources) closer to figma,ux 2025-08-12 03:08:47 +05:30
Hanzalah Waheed
eb05132008 fix: always show the response bubble buttons. 2025-08-12 00:16:21 +04:00
Alex
f94a093e8c fix: truncate long text fields to prevent overflow in logs and sources 2025-08-11 14:56:31 +01:00
GH Action - Upstream Sync
0d0c2daf64 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-09 01:44:41 +00:00
ManishMadan2882
823d948b25 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-08-08 21:59:01 +05:30
Alex
56831fbcf2 Merge pull request #1917 from ManishMadan2882/fix/agent_prompts
Fixes missing attributes on shared agents
2025-08-08 16:30:09 +01:00
ManishMadan2882
bf49b9cb88 (fix/shared_agent)missing main attr 2025-08-08 20:44:09 +05:30
GH Action - Upstream Sync
e01adffbad Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-08 01:54:52 +00:00
Alex
08a5d52d82 Update README.md 2025-08-07 17:20:45 +03:00
ManishMadan2882
fdae235742 (feat:sources) i18n 2025-08-07 12:53:12 +05:30
GH Action - Upstream Sync
9903fad1e9 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-07 01:55:18 +00:00
Alex
14bbd5338d Merge pull request #1909 from siiddhantt/main
fix: remove unnecessary parameter from fetchPreviewAnswer
2025-08-06 19:21:59 +01:00
Siddhant Rai
4a236c2f6f fix: remove unnecessary parameter from fetchPreviewAnswer 2025-08-06 22:34:06 +05:30
Alex
0a8cdbd7f1 fix: update token selector in FileTreeComponent 2025-08-06 12:44:21 +01:00
Alex
94c49843be Merge pull request #1906 from arc53/feat/pg-vector
feat: implement PGVectorStore for PostgreSQL vector storage
2025-08-06 10:42:34 +01:00
Alex
9281fac898 fix: improve error logging for index creation and add PARSE_IMAGE_REMOTE setting 2025-08-06 10:40:20 +01:00
GH Action - Upstream Sync
0b2736f454 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-06 01:55:04 +00:00
ManishMadan2882
ae116b0d0d (fix:agentPreview) build err 2025-08-06 02:55:39 +05:30
ManishMadan2882
ba260e3382 (fix:faiss) not save tmp dir 2025-08-06 02:53:39 +05:30
Alex
1282e7687f fix: add error handling for index creation in user and agents collections 2025-08-05 17:19:06 +01:00
Alex
b1d8266eef feat: implement PGVectorStore for PostgreSQL vector storage 2025-08-05 13:54:39 +01:00
Alex
7acae6935b Merge pull request #1905 from arc53/fix-qdrant
fix: qdrant issues
2025-08-05 12:26:24 +01:00
Alex
092c01cae7 fix: ruff lint 2025-08-05 12:22:33 +01:00
Alex
56a1066c30 fix: qdrant issues 2025-08-05 12:19:18 +01:00
ManishMadan2882
1356d71839 (lint) ruff fix 2025-08-05 15:37:39 +05:30
ManishMadan2882
1eb011e8c3 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-08-05 15:28:51 +05:30
ManishMadan2882
e349eb28b0 (fix:update_chunk) data integrity, uplod back faiss 2025-08-05 06:31:00 +05:30
ManishMadan2882
b000b235a2 (feat:sources) renamed docs,fe 2025-08-05 05:23:29 +05:30
ManishMadan2882
16fe92282e (fix:chunks) responsive, editing controls 2025-08-05 03:04:37 +05:30
ManishMadan2882
e218e88cf4 (fix:chunks) alignment and ui 2025-08-04 19:28:15 +05:30
ManishMadan2882
888ea81a32 (feat:fil_management) serialising updates, queue 2025-08-04 17:27:12 +05:30
ManishMadan2882
735fab7640 (feat:storage) sync base 2025-08-04 16:36:38 +05:30
ManishMadan2882
45745c2a47 (feat:docs) skeleton loader 2025-08-04 16:35:24 +05:30
Alex
4caff0fcf6 fix: enhance error logging for malformed request in stream route 2025-08-04 11:41:41 +01:00
Alex
762ea6ce7f Merge pull request #1866 from arc53/dependabot/npm_and_yarn/frontend/tailwindcss-4.1.11
build(deps-dev): bump tailwindcss from 4.1.10 to 4.1.11 in /frontend
2025-08-02 23:49:54 +01:00
ManishMadan2882
8b4f6553f3 (fix:menu) left and right 2025-08-02 02:08:35 +05:30
ManishMadan2882
a61e44d175 (feat:dir_tree) improvement 2025-08-02 01:48:43 +05:30
ManishMadan2882
e1b1558fc9 (feat:storage) rm dir 2025-08-02 00:54:09 +05:30
ManishMadan2882
53225bda4e (feat:reingestion) spit directories 2025-08-02 00:49:15 +05:30
ManishMadan2882
5212769848 (feat:reingest) UI, polling 2025-08-01 01:25:37 +05:30
ManishMadan2882
d5ded3c9f4 (feat:reingest) eat and spit specific chunks 2025-08-01 01:14:48 +05:30
ManishMadan2882
c92d778894 (feat:chunker) do not combine text 2025-07-31 02:13:55 +05:30
ManishMadan2882
829abd1ad6 (fix:textarea) consistent line indxs 2025-07-30 21:00:00 +05:30
ManishMadan2882
266d256a07 (feat:sources) management, simple re-ingest 2025-07-30 01:57:40 +05:30
Alex
8380cac3e7 Merge pull request #1900 from naaa760/docs/auth-type-configuration
Docs: Expand and Clarify AUTH_TYPE Configuration and Authentication Methods (#1882)
2025-07-28 23:07:40 +01:00
ManishMadan2882
a24652f901 (feat:chunks) update iff changed 2025-07-28 19:35:41 +05:30
ManishMadan2882
2d203d3c70 (fix:chunks)responsive 2025-07-28 18:01:51 +05:30
Alex
48d21600da Merge pull request #1896 from siiddhantt/feat/rework-answer-routes
feat: answer routes re-structure for better maintainability and reuse
2025-07-26 14:18:10 +01:00
ManishMadan2882
2508d0fbb3 (fix:chunks) preserve paths 2025-07-26 00:27:39 +05:30
ManishMadan2882
e90e80c289 (fix:chunks) also count tokens 2025-07-26 00:16:45 +05:30
ManishMadan2882
5e4748f9d9 (fix:faiss) rely on storage abstrct 2025-07-26 00:14:17 +05:30
Siddhant Rai
212952f3e9 fix: allow api call in stream route + get_prompt error 2025-07-25 16:17:18 +05:30
naaa760
f99b6496c5 update 2025-07-25 14:48:49 +05:30
ManishMadan2882
67423d51b9 (feat:chunks) ask to edit, ui 2025-07-25 04:05:06 +05:30
ManishMadan2882
58465ece65 (feat:chunks) server-side filter on search 2025-07-25 01:43:50 +05:30
ManishMadan2882
8ede3a0173 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-07-23 20:48:00 +05:30
ManishMadan2882
ad2f0f8950 (chore:chunks) i18n 2025-07-23 20:47:36 +05:30
Siddhant Rai
76973a4b4c feat: answer routes re-structure for better maintainability and reuse 2025-07-23 20:07:42 +05:30
GH Action - Upstream Sync
b198e2e029 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-07-23 01:52:41 +00:00
ManishMadan2882
4d6ea401b5 (feat:chunks) line numbered editor 2025-07-23 03:36:18 +05:30
ManishMadan2882
b00c4cc3b6 (feat:chunk) editing mode 2025-07-23 02:22:56 +05:30
Alex
4185e64c65 Merge pull request #1893 from arc53/fix-attachment-bugs
fix: replace secure_filename with safe_filename for attachment handling
2025-07-22 16:24:55 +01:00
ManishMadan2882
6eb2c884a2 (refactor) separation in chunks/files view 2025-07-22 19:36:52 +05:30
Alex
6c0362a4cf fix: replace secure_filename with safe_filename for attachment handling 2025-07-22 12:56:17 +01:00
ManishMadan2882
50b1755a63 Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-07-21 16:31:57 +05:30
ManishMadan2882
ff3c7eb5fb (fix:delete_old) comply with storage abtrctn 2025-07-21 16:31:42 +05:30
ManishMadan2882
3755316d49 (fix:chunks) responsive design 2025-07-21 16:30:30 +05:30
GH Action - Upstream Sync
f952046847 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-07-19 01:47:09 +00:00
Alex
969cdb4a63 Merge pull request #1890 from siiddhantt/feat/enhance-agents
feat: enhance prompt selection in new agents
2025-07-18 13:07:45 +01:00
ManishMadan2882
f336d44595 (feat:chunks) search in dir 2025-07-18 15:03:23 +05:30
Siddhant Rai
a53f93c195 feat: enhance dropdown component and prompts integration 2025-07-18 14:02:29 +05:30
GH Action - Upstream Sync
fcb334ce33 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-07-17 01:50:59 +00:00
ManishMadan2882
8ddf04a904 (feat:chunks) use common header, navigate 2025-07-17 03:08:01 +05:30
ManishMadan2882
29698ca169 (feat:chunks) redesigned 2025-07-17 02:16:40 +05:30
ManishMadan2882
a9baf7436a Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-07-17 01:05:59 +05:30
ManishMadan2882
99a8962183 (fix/docs) menu event capture 2025-07-17 01:05:24 +05:30
Alex
afc5b15a6b Merge pull request #1887 from Krrish0902/fix-issue-1854
fix: Removed incorrect www from URL in DocsGPT Docs frontend (#1854)
2025-07-16 13:20:05 +01:00
GH Action - Upstream Sync
b6ab508e27 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-07-16 01:50:25 +00:00
ananthakrishnan
789e65557a fix: Removed incorrect www from URL in DocsGPT Docs frontend (#1854) 2025-07-15 22:02:02 +05:30
ManishMadan2882
8a7806ab2d (feat:nested source view) file tree, chunks display 2025-07-15 19:15:40 +05:30
Alex
493303e103 Merge pull request #1886 from arc53/copilot/fix-1878
🐛 Fix conversation summary prompt to use user query language
2025-07-15 12:57:14 +01:00
ManishMadan2882
1d9af05e9e (feat:storage) is dir fnc 2025-07-15 15:34:16 +05:30
ManishMadan2882
5b07c5f2e8 (feat:ingestion) unzip, extract and store 2025-07-15 15:31:26 +05:30
ManishMadan2882
a38d71bbfb (feat:get_chunks) filtered by relative path 2025-07-15 13:38:19 +05:30
ManishMadan2882
a24a3f868c (feat:dir-structure) adding route 2025-07-15 13:38:19 +05:30
ManishMadan2882
f60c516185 (feat:dir_tree) table with folder contents 2025-07-15 13:38:19 +05:30
Manish Madan
26f4646304 Merge branch 'arc53:main' into main 2025-07-14 23:02:36 +05:30
ananthakrishnan
3a351f67e6 fix: correct agent tools name when creating new agent (#1877) 2025-07-14 20:20:55 +05:30
dependabot[bot]
e7c09cb91e build(deps-dev): bump tailwindcss from 4.1.10 to 4.1.11 in /frontend
Bumps [tailwindcss](https://github.com/tailwindlabs/tailwindcss/tree/HEAD/packages/tailwindcss) from 4.1.10 to 4.1.11.
- [Release notes](https://github.com/tailwindlabs/tailwindcss/releases)
- [Changelog](https://github.com/tailwindlabs/tailwindcss/blob/main/CHANGELOG.md)
- [Commits](https://github.com/tailwindlabs/tailwindcss/commits/v4.1.11/packages/tailwindcss)

---
updated-dependencies:
- dependency-name: tailwindcss
  dependency-version: 4.1.11
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-07-14 09:02:48 +00:00
GH Action - Upstream Sync
c62040e232 Merge branch 'main' of https://github.com/arc53/DocsGPT 2025-07-11 01:49:09 +00:00
ManishMadan2882
d3b592bffc Merge branch 'main' of https://github.com/manishmadan2882/docsgpt 2025-07-09 01:29:59 +05:30
ManishMadan2882
4fcbdae5bf (feat:docs) cards UI 2025-07-08 02:46:34 +05:30
ManishMadan2882
ca95d7275a (feat:dateTimeUtils) localise weekday format 2025-07-08 02:32:18 +05:30
Manish Madan
61baf3701c Merge branch 'arc53:main' into main 2025-07-04 02:26:24 +05:30
ManishMadan2882
bbce872ac5 (fix:chunker) combine metadata as well 2025-07-04 02:19:58 +05:30
ManishMadan2882
0f7ebcd8e4 (feat:dir-reader) store mime types, file size in db 2025-07-03 18:09:19 +05:30
ManishMadan2882
82fc19e7b7 (fix:dir-reader) conflict of same filename in dir 2025-07-03 17:28:12 +05:30
ManishMadan2882
2ef23fe1b3 (feat:dir-reader) maintain dir structure in db 2025-07-03 01:24:22 +05:30
ManishMadan2882
fd905b1a06 (feat:dir-reader) save tokens with filenames 2025-07-02 16:30:29 +05:30
ManishMadan2882
ade704d065 (refactor:ingestion) pass file path once 2025-07-01 04:00:57 +05:30
104 changed files with 9667 additions and 2864 deletions

View File

@@ -21,7 +21,7 @@ jobs:
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.12'
- name: Install dependencies

View File

@@ -10,7 +10,7 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies

View File

@@ -3,11 +3,11 @@
</h1>
<p align="center">
<strong>Open-Source RAG Assistant</strong>
<strong>Private AI for agents, assistants and enterprise search</strong>
</p>
<p align="left">
<strong><a href="https://www.docsgpt.cloud/">DocsGPT</a></strong> is an open-source genAI tool that helps users get reliable answers from any knowledge source, while avoiding hallucinations. It enables quick and reliable information retrieval, with tooling and agentic system capability built in.
<strong><a href="https://www.docsgpt.cloud/">DocsGPT</a></strong> is an open-source AI platform for building intelligent agents and assistants. Features Agent Builder, deep research tools, document analysis (PDF, Office, web content), Multi-model support (choose your provider or run locally), and rich API connectivity for agents with actionable tools and integrations. Deploy anywhere with complete privacy control.
</p>
<div align="center">
@@ -19,10 +19,10 @@
<a href="https://discord.gg/n5BX8dh8rU">![link to discord](https://img.shields.io/discord/1070046503302877216)</a>
<a href="https://twitter.com/docsgptai">![X (formerly Twitter) URL](https://img.shields.io/twitter/follow/docsgptai)</a>
<a href="https://docs.docsgpt.cloud/quickstart">⚡️ Quickstart</a><a href="https://app.docsgpt.cloud/">☁️ Cloud Version</a><a href="https://discord.gg/n5BX8dh8rU">💬 Discord</a>
<br>
<a href="https://docs.docsgpt.cloud/">📖 Documentation</a><a href="https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md">👫 Contribute</a><a href="https://blog.docsgpt.cloud/">🗞 Blog</a>
<br>
<a href="https://docs.docsgpt.cloud/quickstart">⚡️ Quickstart</a><a href="https://app.docsgpt.cloud/">☁️ Cloud Version</a><a href="https://discord.gg/n5BX8dh8rU">💬 Discord</a>
<br>
<a href="https://docs.docsgpt.cloud/">📖 Documentation</a><a href="https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md">👫 Contribute</a><a href="https://blog.docsgpt.cloud/">🗞 Blog</a>
<br>
</div>
<div align="center">
@@ -53,9 +53,10 @@
- [x] New input box in the conversation menu (April 2025)
- [x] Add triggerable actions / tools (webhook) (April 2025)
- [x] Agent optimisations (May 2025)
- [ ] Filesystem sources update (July 2025)
- [ ] Anthropic Tool compatibility (July 2025)
- [ ] MCP support (July 2025)
- [x] Filesystem sources update (July 2025)
- [x] Json Responses (August 2025)
- [ ] Sharepoint integration (August 2025)
- [ ] MCP support (August 2025)
- [ ] Add OAuth 2.0 authentication for tools and sources (August 2025)
- [ ] Agent scheduling
@@ -71,11 +72,10 @@ We're eager to provide personalized assistance when deploying your DocsGPT to a
## Join the Lighthouse Program 🌟
Calling all developers and GenAI innovators! The **DocsGPT Lighthouse Program** connects technical leaders actively deploying or extending DocsGPT in real-world scenarios. Collaborate directly with our team to shape the roadmap, access priority support, and build enterprise-ready solutions with exclusive community insights.
Calling all developers and GenAI innovators! The **DocsGPT Lighthouse Program** connects technical leaders actively deploying or extending DocsGPT in real-world scenarios. Collaborate directly with our team to shape the roadmap, access priority support, and build enterprise-ready solutions with exclusive community insights.
[Learn More & Apply →](https://docs.google.com/forms/d/1KAADiJinUJ8EMQyfTXUIGyFbqINNClNR3jBNWq7DgTE)
## QuickStart
> [!Note]
@@ -106,7 +106,7 @@ A more detailed [Quickstart](https://docs.docsgpt.cloud/quickstart) is available
PowerShell -ExecutionPolicy Bypass -File .\setup.ps1
```
Either script will guide you through setting up DocsGPT. Four options available: using the public API, running locally, connecting to a local inference engine, or using a cloud API provider. Scripts will automatically configure your `.env` file and handle necessary downloads and installations based on your chosen option.
Either script will guide you through setting up DocsGPT. Four options available: using the public API, running locally, connecting to a local inference engine, or using a cloud API provider. Scripts will automatically configure your `.env` file and handle necessary downloads and installations based on your chosen option.
**Navigate to http://localhost:5173/**
@@ -115,6 +115,7 @@ To stop DocsGPT, open a terminal in the `DocsGPT` directory and run:
```bash
docker compose -f deployment/docker-compose.yaml down
```
(or use the specific `docker compose down` command shown after running the setup script).
> [!Note]
@@ -142,7 +143,6 @@ Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information abou
We as members, contributors, and leaders, pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. Please refer to the [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) file for more information about contributing.
## Many Thanks To Our Contributors⚡
<a href="https://github.com/arc53/DocsGPT/graphs/contributors" alt="View Contributors">

View File

@@ -1,3 +1,4 @@
import logging
import uuid
from abc import ABC, abstractmethod
from typing import Dict, Generator, List, Optional
@@ -6,15 +7,15 @@ from bson.objectid import ObjectId
from application.agents.tools.tool_action_parser import ToolActionParser
from application.agents.tools.tool_manager import ToolManager
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.llm.handlers.handler_creator import LLMHandlerCreator
from application.llm.llm_creator import LLMCreator
from application.logging import build_stack_data, log_activity, LogContext
from application.retriever.base import BaseRetriever
logger = logging.getLogger(__name__)
class BaseAgent(ABC):
def __init__(
@@ -28,6 +29,7 @@ class BaseAgent(ABC):
chat_history: Optional[List[Dict]] = None,
decoded_token: Optional[Dict] = None,
attachments: Optional[List[Dict]] = None,
json_schema: Optional[Dict] = None,
):
self.endpoint = endpoint
self.llm_name = llm_name
@@ -51,6 +53,7 @@ class BaseAgent(ABC):
llm_name if llm_name else "default"
)
self.attachments = attachments or []
self.json_schema = json_schema
@log_activity()
def gen(
@@ -137,6 +140,40 @@ class BaseAgent(ABC):
tool_id, action_name, call_args = parser.parse_args(call)
call_id = getattr(call, "id", None) or str(uuid.uuid4())
# Check if parsing failed
if tool_id is None or action_name is None:
error_message = f"Error: Failed to parse LLM tool call. Tool name: {getattr(call, 'name', 'unknown')}"
logger.error(error_message)
tool_call_data = {
"tool_name": "unknown",
"call_id": call_id,
"action_name": getattr(call, 'name', 'unknown'),
"arguments": call_args or {},
"result": f"Failed to parse tool call. Invalid tool name format: {getattr(call, 'name', 'unknown')}",
}
yield {"type": "tool_call", "data": {**tool_call_data, "status": "error"}}
self.tool_calls.append(tool_call_data)
return "Failed to parse tool call.", call_id
# Check if tool_id exists in available tools
if tool_id not in tools_dict:
error_message = f"Error: Tool ID '{tool_id}' extracted from LLM call not found in available tools_dict. Available IDs: {list(tools_dict.keys())}"
logger.error(error_message)
# Return error result
tool_call_data = {
"tool_name": "unknown",
"call_id": call_id,
"action_name": f"{action_name}_{tool_id}",
"arguments": call_args,
"result": f"Tool with ID {tool_id} not found. Available tools: {list(tools_dict.keys())}",
}
yield {"type": "tool_call", "data": {**tool_call_data, "status": "error"}}
self.tool_calls.append(tool_call_data)
return f"Tool with ID {tool_id} not found.", call_id
tool_call_data = {
"tool_name": tools_dict[tool_id]["name"],
"call_id": call_id,
@@ -283,6 +320,21 @@ class BaseAgent(ABC):
and self.tools
):
gen_kwargs["tools"] = self.tools
if (
self.json_schema
and hasattr(self.llm, "_supports_structured_output")
and self.llm._supports_structured_output()
):
structured_format = self.llm.prepare_structured_output_format(
self.json_schema
)
if structured_format:
if self.llm_name == "openai":
gen_kwargs["response_format"] = structured_format
elif self.llm_name == "google":
gen_kwargs["response_schema"] = structured_format
resp = self.llm.gen_stream(**gen_kwargs)
if log_context:
@@ -307,11 +359,25 @@ class BaseAgent(ABC):
return resp
def _handle_response(self, response, tools_dict, messages, log_context):
is_structured_output = (
self.json_schema is not None
and hasattr(self.llm, "_supports_structured_output")
and self.llm._supports_structured_output()
)
if isinstance(response, str):
yield {"answer": response}
answer_data = {"answer": response}
if is_structured_output:
answer_data["structured"] = True
answer_data["schema"] = self.json_schema
yield answer_data
return
if hasattr(response, "message") and getattr(response.message, "content", None):
yield {"answer": response.message.content}
answer_data = {"answer": response.message.content}
if is_structured_output:
answer_data["structured"] = True
answer_data["schema"] = self.json_schema
yield answer_data
return
processed_response_gen = self._llm_handler(
response, tools_dict, messages, log_context, self.attachments
@@ -319,8 +385,16 @@ class BaseAgent(ABC):
for event in processed_response_gen:
if isinstance(event, str):
yield {"answer": event}
answer_data = {"answer": event}
if is_structured_output:
answer_data["structured"] = True
answer_data["schema"] = self.json_schema
yield answer_data
elif hasattr(event, "message") and getattr(event.message, "content", None):
yield {"answer": event.message.content}
answer_data = {"answer": event.message.content}
if is_structured_output:
answer_data["structured"] = True
answer_data["schema"] = self.json_schema
yield answer_data
elif isinstance(event, dict) and "type" in event:
yield event

View File

@@ -19,8 +19,20 @@ class ToolActionParser:
def _parse_openai_llm(self, call):
try:
call_args = json.loads(call.arguments)
tool_id = call.name.split("_")[-1]
action_name = call.name.rsplit("_", 1)[0]
tool_parts = call.name.split("_")
# If the tool name doesn't contain an underscore, it's likely a hallucinated tool
if len(tool_parts) < 2:
logger.warning(f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id")
return None, None, None
tool_id = tool_parts[-1]
action_name = "_".join(tool_parts[:-1])
# Validate that tool_id looks like a numerical ID
if not tool_id.isdigit():
logger.warning(f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call.")
except (AttributeError, TypeError) as e:
logger.error(f"Error parsing OpenAI LLM call: {e}")
return None, None, None
@@ -29,8 +41,20 @@ class ToolActionParser:
def _parse_google_llm(self, call):
try:
call_args = call.arguments
tool_id = call.name.split("_")[-1]
action_name = call.name.rsplit("_", 1)[0]
tool_parts = call.name.split("_")
# If the tool name doesn't contain an underscore, it's likely a hallucinated tool
if len(tool_parts) < 2:
logger.warning(f"Invalid tool name format: {call.name}. Expected format: action_name_tool_id")
return None, None, None
tool_id = tool_parts[-1]
action_name = "_".join(tool_parts[:-1])
# Validate that tool_id looks like a numerical ID
if not tool_id.isdigit():
logger.warning(f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call.")
except (AttributeError, TypeError) as e:
logger.error(f"Error parsing Google LLM call: {e}")
return None, None, None

View File

@@ -0,0 +1,7 @@
from flask_restx import Api
api = Api(
version="1.0",
title="DocsGPT API",
description="API for DocsGPT",
)

View File

@@ -0,0 +1,19 @@
from flask import Blueprint
from application.api import api
from application.api.answer.routes.answer import AnswerResource
from application.api.answer.routes.base import answer_ns
from application.api.answer.routes.stream import StreamResource
answer = Blueprint("answer", __name__)
api.add_namespace(answer_ns)
def init_answer_routes():
api.add_resource(StreamResource, "/stream")
api.add_resource(AnswerResource, "/api/answer")
init_answer_routes()

View File

@@ -1,914 +0,0 @@
import asyncio
import datetime
import json
import logging
import os
import traceback
from bson.dbref import DBRef
from bson.objectid import ObjectId
from flask import Blueprint, make_response, request, Response
from flask_restx import fields, Namespace, Resource
from application.agents.agent_creator import AgentCreator
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.error import bad_request
from application.extensions import api
from application.llm.llm_creator import LLMCreator
from application.retriever.retriever_creator import RetrieverCreator
from application.utils import check_required_fields, limit_chat_history
logger = logging.getLogger(__name__)
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
conversations_collection = db["conversations"]
sources_collection = db["sources"]
prompts_collection = db["prompts"]
agents_collection = db["agents"]
user_logs_collection = db["user_logs"]
attachments_collection = db["attachments"]
answer = Blueprint("answer", __name__)
answer_ns = Namespace("answer", description="Answer related operations", path="/")
api.add_namespace(answer_ns)
gpt_model = ""
# to have some kind of default behaviour
if settings.LLM_PROVIDER == "openai":
gpt_model = "gpt-4o-mini"
elif settings.LLM_PROVIDER == "anthropic":
gpt_model = "claude-2"
elif settings.LLM_PROVIDER == "groq":
gpt_model = "llama3-8b-8192"
elif settings.LLM_PROVIDER == "novita":
gpt_model = "deepseek/deepseek-r1"
if settings.LLM_NAME: # in case there is particular model name configured
gpt_model = settings.LLM_NAME
# load the prompts
current_dir = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
)
with open(os.path.join(current_dir, "prompts", "chat_combine_default.txt"), "r") as f:
chat_combine_template = f.read()
with open(os.path.join(current_dir, "prompts", "chat_reduce_prompt.txt"), "r") as f:
chat_reduce_template = f.read()
with open(os.path.join(current_dir, "prompts", "chat_combine_creative.txt"), "r") as f:
chat_combine_creative = f.read()
with open(os.path.join(current_dir, "prompts", "chat_combine_strict.txt"), "r") as f:
chat_combine_strict = f.read()
api_key_set = settings.API_KEY is not None
embeddings_key_set = settings.EMBEDDINGS_KEY is not None
async def async_generate(chain, question, chat_history):
result = await chain.arun({"question": question, "chat_history": chat_history})
return result
def run_async_chain(chain, question, chat_history):
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
result = {}
try:
answer = loop.run_until_complete(async_generate(chain, question, chat_history))
finally:
loop.close()
result["answer"] = answer
return result
def get_agent_key(agent_id, user_id):
if not agent_id:
return None, False, None
try:
agent = agents_collection.find_one({"_id": ObjectId(agent_id)})
if agent is None:
raise Exception("Agent not found", 404)
is_owner = agent.get("user") == user_id
if is_owner:
agents_collection.update_one(
{"_id": ObjectId(agent_id)},
{"$set": {"lastUsedAt": datetime.datetime.now(datetime.timezone.utc)}},
)
return str(agent["key"]), False, None
is_shared_with_user = agent.get(
"shared_publicly", False
) or user_id in agent.get("shared_with", [])
if is_shared_with_user:
return str(agent["key"]), True, agent.get("shared_token")
raise Exception("Unauthorized access to the agent", 403)
except Exception as e:
logger.error(f"Error in get_agent_key: {str(e)}", exc_info=True)
raise
def get_data_from_api_key(api_key):
data = agents_collection.find_one({"key": api_key})
if not data:
raise Exception("Invalid API Key, please generate a new key", 401)
source = data.get("source")
if isinstance(source, DBRef):
source_doc = db.dereference(source)
data["source"] = str(source_doc["_id"])
data["retriever"] = source_doc.get("retriever", data.get("retriever"))
else:
data["source"] = {}
return data
def get_retriever(source_id: str):
doc = sources_collection.find_one({"_id": ObjectId(source_id)})
if doc is None:
raise Exception("Source document does not exist", 404)
retriever_name = None if "retriever" not in doc else doc["retriever"]
return retriever_name
def is_azure_configured():
return (
settings.OPENAI_API_BASE
and settings.OPENAI_API_VERSION
and settings.AZURE_DEPLOYMENT_NAME
)
def save_conversation(
conversation_id,
question,
response,
thought,
source_log_docs,
tool_calls,
llm,
decoded_token,
index=None,
api_key=None,
agent_id=None,
is_shared_usage=False,
shared_token=None,
attachment_ids=None,
):
current_time = datetime.datetime.now(datetime.timezone.utc)
if conversation_id is not None and index is not None:
conversations_collection.update_one(
{"_id": ObjectId(conversation_id), f"queries.{index}": {"$exists": True}},
{
"$set": {
f"queries.{index}.prompt": question,
f"queries.{index}.response": response,
f"queries.{index}.thought": thought,
f"queries.{index}.sources": source_log_docs,
f"queries.{index}.tool_calls": tool_calls,
f"queries.{index}.timestamp": current_time,
f"queries.{index}.attachments": attachment_ids,
}
},
)
##remove following queries from the array
conversations_collection.update_one(
{"_id": ObjectId(conversation_id), f"queries.{index}": {"$exists": True}},
{"$push": {"queries": {"$each": [], "$slice": index + 1}}},
)
elif conversation_id is not None and conversation_id != "None":
conversations_collection.update_one(
{"_id": ObjectId(conversation_id)},
{
"$push": {
"queries": {
"prompt": question,
"response": response,
"thought": thought,
"sources": source_log_docs,
"tool_calls": tool_calls,
"timestamp": current_time,
"attachments": attachment_ids,
}
}
},
)
else:
# create new conversation
# generate summary
messages_summary = [
{
"role": "assistant",
"content": "Summarise following conversation in no more than 3 "
"words, respond ONLY with the summary, use the same "
"language as the user query",
},
{
"role": "user",
"content": "Summarise following conversation in no more than 3 words, "
"respond ONLY with the summary, use the same language as the "
"user query \n\nUser: " + question + "\n\n" + "AI: " + response,
},
]
completion = llm.gen(model=gpt_model, messages=messages_summary, max_tokens=30)
conversation_data = {
"user": decoded_token.get("sub"),
"date": datetime.datetime.utcnow(),
"name": completion,
"queries": [
{
"prompt": question,
"response": response,
"thought": thought,
"sources": source_log_docs,
"tool_calls": tool_calls,
"timestamp": current_time,
"attachments": attachment_ids,
}
],
}
if api_key:
if agent_id:
conversation_data["agent_id"] = agent_id
if is_shared_usage:
conversation_data["is_shared_usage"] = is_shared_usage
conversation_data["shared_token"] = shared_token
api_key_doc = agents_collection.find_one({"key": api_key})
if api_key_doc:
conversation_data["api_key"] = api_key_doc["key"]
conversation_id = conversations_collection.insert_one(
conversation_data
).inserted_id
return conversation_id
def get_prompt(prompt_id):
if prompt_id == "default":
prompt = chat_combine_template
elif prompt_id == "creative":
prompt = chat_combine_creative
elif prompt_id == "strict":
prompt = chat_combine_strict
else:
prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
return prompt
def complete_stream(
question,
agent,
retriever,
conversation_id,
user_api_key,
decoded_token,
isNoneDoc=False,
index=None,
should_save_conversation=True,
attachment_ids=None,
agent_id=None,
is_shared_usage=False,
shared_token=None,
):
try:
response_full, thought, source_log_docs, tool_calls = "", "", [], []
answer = agent.gen(query=question, retriever=retriever)
for line in answer:
if "answer" in line:
response_full += str(line["answer"])
data = json.dumps({"type": "answer", "answer": line["answer"]})
yield f"data: {data}\n\n"
elif "sources" in line:
truncated_sources = []
source_log_docs = line["sources"]
for source in line["sources"]:
truncated_source = source.copy()
if "text" in truncated_source:
truncated_source["text"] = (
truncated_source["text"][:100].strip() + "..."
)
truncated_sources.append(truncated_source)
if len(truncated_sources) > 0:
data = json.dumps({"type": "source", "source": truncated_sources})
yield f"data: {data}\n\n"
elif "tool_calls" in line:
tool_calls = line["tool_calls"]
elif "thought" in line:
thought += line["thought"]
data = json.dumps({"type": "thought", "thought": line["thought"]})
yield f"data: {data}\n\n"
elif "type" in line:
data = json.dumps(line)
yield f"data: {data}\n\n"
if isNoneDoc:
for doc in source_log_docs:
doc["source"] = "None"
llm = LLMCreator.create_llm(
settings.LLM_PROVIDER,
api_key=settings.API_KEY,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
if should_save_conversation:
conversation_id = save_conversation(
conversation_id,
question,
response_full,
thought,
source_log_docs,
tool_calls,
llm,
decoded_token,
index,
api_key=user_api_key,
attachment_ids=attachment_ids,
agent_id=agent_id,
is_shared_usage=is_shared_usage,
shared_token=shared_token,
)
else:
conversation_id = None
# send data.type = "end" to indicate that the stream has ended as json
data = json.dumps({"type": "id", "id": str(conversation_id)})
yield f"data: {data}\n\n"
retriever_params = retriever.get_params()
user_logs_collection.insert_one(
{
"action": "stream_answer",
"level": "info",
"user": decoded_token.get("sub"),
"api_key": user_api_key,
"question": question,
"response": response_full,
"sources": source_log_docs,
"retriever_params": retriever_params,
"attachments": attachment_ids,
"timestamp": datetime.datetime.now(datetime.timezone.utc),
}
)
data = json.dumps({"type": "end"})
yield f"data: {data}\n\n"
except Exception as e:
logger.error(f"Error in stream: {str(e)}", exc_info=True)
data = json.dumps(
{
"type": "error",
"error": "Please try again later. We apologize for any inconvenience.",
}
)
yield f"data: {data}\n\n"
return
@answer_ns.route("/stream")
class Stream(Resource):
stream_model = api.model(
"StreamModel",
{
"question": fields.String(
required=True, description="Question to be asked"
),
"history": fields.List(
fields.String, required=False, description="Chat history"
),
"conversation_id": fields.String(
required=False, description="Conversation ID"
),
"prompt_id": fields.String(
required=False, default="default", description="Prompt ID"
),
"chunks": fields.Integer(
required=False, default=2, description="Number of chunks"
),
"token_limit": fields.Integer(required=False, description="Token limit"),
"retriever": fields.String(required=False, description="Retriever type"),
"api_key": fields.String(required=False, description="API key"),
"active_docs": fields.String(
required=False, description="Active documents"
),
"isNoneDoc": fields.Boolean(
required=False, description="Flag indicating if no document is used"
),
"index": fields.Integer(
required=False, description="Index of the query to update"
),
"save_conversation": fields.Boolean(
required=False,
default=True,
description="Whether to save the conversation",
),
"attachments": fields.List(
fields.String, required=False, description="List of attachment IDs"
),
},
)
@api.expect(stream_model)
@api.doc(description="Stream a response based on the question and retriever")
def post(self):
data = request.get_json()
required_fields = ["question"]
if "index" in data:
required_fields = ["question", "conversation_id"]
missing_fields = check_required_fields(data, required_fields)
if missing_fields:
return missing_fields
save_conv = data.get("save_conversation", True)
try:
question = data["question"]
history = limit_chat_history(
json.loads(data.get("history", "[]")), gpt_model=gpt_model
)
conversation_id = data.get("conversation_id")
prompt_id = data.get("prompt_id", "default")
attachment_ids = data.get("attachments", [])
index = data.get("index", None)
chunks = int(data.get("chunks", 2))
token_limit = data.get("token_limit", settings.DEFAULT_MAX_HISTORY)
retriever_name = data.get("retriever", "classic")
agent_id = data.get("agent_id", None)
agent_type = settings.AGENT_NAME
decoded_token = getattr(request, "decoded_token", None)
user_sub = decoded_token.get("sub") if decoded_token else None
agent_key, is_shared_usage, shared_token = get_agent_key(agent_id, user_sub)
if agent_key:
data.update({"api_key": agent_key})
else:
agent_id = None
if "api_key" in data:
data_key = get_data_from_api_key(data["api_key"])
chunks = int(data_key.get("chunks", 2))
prompt_id = data_key.get("prompt_id", "default")
source = {"active_docs": data_key.get("source")}
retriever_name = data_key.get("retriever", retriever_name)
user_api_key = data["api_key"]
agent_type = data_key.get("agent_type", agent_type)
if is_shared_usage:
decoded_token = request.decoded_token
else:
decoded_token = {"sub": data_key.get("user")}
is_shared_usage = False
elif "active_docs" in data:
source = {"active_docs": data["active_docs"]}
retriever_name = get_retriever(data["active_docs"]) or retriever_name
user_api_key = None
decoded_token = request.decoded_token
else:
source = {}
user_api_key = None
decoded_token = request.decoded_token
if not decoded_token:
return make_response({"error": "Unauthorized"}, 401)
attachments = get_attachments_content(
attachment_ids, decoded_token.get("sub")
)
logger.info(
f"/stream - request_data: {data}, source: {source}, attachments: {len(attachments)}",
extra={"data": json.dumps({"request_data": data, "source": source})},
)
prompt = get_prompt(prompt_id)
if "isNoneDoc" in data and data["isNoneDoc"] is True:
chunks = 0
agent = AgentCreator.create_agent(
agent_type,
endpoint="stream",
llm_name=settings.LLM_PROVIDER,
gpt_model=gpt_model,
api_key=settings.API_KEY,
user_api_key=user_api_key,
prompt=prompt,
chat_history=history,
decoded_token=decoded_token,
attachments=attachments,
)
retriever = RetrieverCreator.create_retriever(
retriever_name,
source=source,
chat_history=history,
prompt=prompt,
chunks=chunks,
token_limit=token_limit,
gpt_model=gpt_model,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
return Response(
complete_stream(
question=question,
agent=agent,
retriever=retriever,
conversation_id=conversation_id,
user_api_key=user_api_key,
decoded_token=decoded_token,
isNoneDoc=data.get("isNoneDoc"),
index=index,
should_save_conversation=save_conv,
attachment_ids=attachment_ids,
agent_id=agent_id,
is_shared_usage=is_shared_usage,
shared_token=shared_token,
),
mimetype="text/event-stream",
)
except ValueError:
message = "Malformed request body"
logger.error(f"/stream - error: {message}")
return Response(
error_stream_generate(message),
status=400,
mimetype="text/event-stream",
)
except Exception as e:
logger.error(
f"/stream - error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
status_code = 400
return Response(
error_stream_generate("Unknown error occurred"),
status=status_code,
mimetype="text/event-stream",
)
def error_stream_generate(err_response):
data = json.dumps({"type": "error", "error": err_response})
yield f"data: {data}\n\n"
@answer_ns.route("/api/answer")
class Answer(Resource):
answer_model = api.model(
"AnswerModel",
{
"question": fields.String(
required=True, description="The question to answer"
),
"history": fields.List(
fields.String, required=False, description="Conversation history"
),
"conversation_id": fields.String(
required=False, description="Conversation ID"
),
"prompt_id": fields.String(
required=False, default="default", description="Prompt ID"
),
"chunks": fields.Integer(
required=False, default=2, description="Number of chunks"
),
"token_limit": fields.Integer(required=False, description="Token limit"),
"retriever": fields.String(required=False, description="Retriever type"),
"api_key": fields.String(required=False, description="API key"),
"active_docs": fields.String(
required=False, description="Active documents"
),
"isNoneDoc": fields.Boolean(
required=False, description="Flag indicating if no document is used"
),
},
)
@api.expect(answer_model)
@api.doc(description="Provide an answer based on the question and retriever")
def post(self):
data = request.get_json()
required_fields = ["question"]
missing_fields = check_required_fields(data, required_fields)
if missing_fields:
return missing_fields
try:
question = data["question"]
history = limit_chat_history(
json.loads(data.get("history", "[]")), gpt_model=gpt_model
)
conversation_id = data.get("conversation_id")
prompt_id = data.get("prompt_id", "default")
chunks = int(data.get("chunks", 2))
token_limit = data.get("token_limit", settings.DEFAULT_MAX_HISTORY)
retriever_name = data.get("retriever", "classic")
agent_type = settings.AGENT_NAME
if "api_key" in data:
data_key = get_data_from_api_key(data["api_key"])
chunks = int(data_key.get("chunks", 2))
prompt_id = data_key.get("prompt_id", "default")
source = {"active_docs": data_key.get("source")}
retriever_name = data_key.get("retriever", retriever_name)
user_api_key = data["api_key"]
agent_type = data_key.get("agent_type", agent_type)
decoded_token = {"sub": data_key.get("user")}
elif "active_docs" in data:
source = {"active_docs": data["active_docs"]}
retriever_name = get_retriever(data["active_docs"]) or retriever_name
user_api_key = None
decoded_token = request.decoded_token
else:
source = {}
user_api_key = None
decoded_token = request.decoded_token
if not decoded_token:
return make_response({"error": "Unauthorized"}, 401)
prompt = get_prompt(prompt_id)
logger.info(
f"/api/answer - request_data: {data}, source: {source}",
extra={"data": json.dumps({"request_data": data, "source": source})},
)
agent = AgentCreator.create_agent(
agent_type,
endpoint="api/answer",
llm_name=settings.LLM_PROVIDER,
gpt_model=gpt_model,
api_key=settings.API_KEY,
user_api_key=user_api_key,
prompt=prompt,
chat_history=history,
decoded_token=decoded_token,
)
retriever = RetrieverCreator.create_retriever(
retriever_name,
source=source,
chat_history=history,
prompt=prompt,
chunks=chunks,
token_limit=token_limit,
gpt_model=gpt_model,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
response_full = ""
source_log_docs = []
tool_calls = []
stream_ended = False
thought = ""
for line in complete_stream(
question=question,
agent=agent,
retriever=retriever,
conversation_id=conversation_id,
user_api_key=user_api_key,
decoded_token=decoded_token,
isNoneDoc=data.get("isNoneDoc"),
index=None,
should_save_conversation=False,
):
try:
event_data = line.replace("data: ", "").strip()
event = json.loads(event_data)
if event["type"] == "answer":
response_full += event["answer"]
elif event["type"] == "source":
source_log_docs = event["source"]
elif event["type"] == "tool_calls":
tool_calls = event["tool_calls"]
elif event["type"] == "thought":
thought = event["thought"]
elif event["type"] == "error":
logger.error(f"Error from stream: {event['error']}")
return bad_request(500, event["error"])
elif event["type"] == "end":
stream_ended = True
except (json.JSONDecodeError, KeyError) as e:
logger.warning(f"Error parsing stream event: {e}, line: {line}")
continue
if not stream_ended:
logger.error("Stream ended unexpectedly without an 'end' event.")
return bad_request(500, "Stream ended unexpectedly.")
if data.get("isNoneDoc"):
for doc in source_log_docs:
doc["source"] = "None"
llm = LLMCreator.create_llm(
settings.LLM_PROVIDER,
api_key=settings.API_KEY,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
result = {"answer": response_full, "sources": source_log_docs}
result["conversation_id"] = str(
save_conversation(
conversation_id,
question,
response_full,
thought,
source_log_docs,
tool_calls,
llm,
decoded_token,
api_key=user_api_key,
)
)
retriever_params = retriever.get_params()
user_logs_collection.insert_one(
{
"action": "api_answer",
"level": "info",
"user": decoded_token.get("sub"),
"api_key": user_api_key,
"question": question,
"response": response_full,
"sources": source_log_docs,
"retriever_params": retriever_params,
"timestamp": datetime.datetime.now(datetime.timezone.utc),
}
)
except Exception as e:
logger.error(
f"/api/answer - error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
return bad_request(500, str(e))
return make_response(result, 200)
@answer_ns.route("/api/search")
class Search(Resource):
search_model = api.model(
"SearchModel",
{
"question": fields.String(
required=True, description="The question to search"
),
"chunks": fields.Integer(
required=False, default=2, description="Number of chunks"
),
"api_key": fields.String(
required=False, description="API key for authentication"
),
"active_docs": fields.String(
required=False, description="Active documents for retrieval"
),
"retriever": fields.String(required=False, description="Retriever type"),
"token_limit": fields.Integer(
required=False, description="Limit for tokens"
),
"isNoneDoc": fields.Boolean(
required=False, description="Flag indicating if no document is used"
),
},
)
@api.expect(search_model)
@api.doc(
description="Search for relevant documents based on the question and retriever"
)
def post(self):
data = request.get_json()
required_fields = ["question"]
missing_fields = check_required_fields(data, required_fields)
if missing_fields:
return missing_fields
try:
question = data["question"]
chunks = int(data.get("chunks", 2))
token_limit = data.get("token_limit", settings.DEFAULT_MAX_HISTORY)
retriever_name = data.get("retriever", "classic")
if "api_key" in data:
data_key = get_data_from_api_key(data["api_key"])
chunks = int(data_key.get("chunks", 2))
source = {"active_docs": data_key.get("source")}
user_api_key = data["api_key"]
decoded_token = {"sub": data_key.get("user")}
elif "active_docs" in data:
source = {"active_docs": data["active_docs"]}
user_api_key = None
decoded_token = request.decoded_token
else:
source = {}
user_api_key = None
decoded_token = request.decoded_token
if not decoded_token:
return make_response({"error": "Unauthorized"}, 401)
logger.info(
f"/api/answer - request_data: {data}, source: {source}",
extra={"data": json.dumps({"request_data": data, "source": source})},
)
retriever = RetrieverCreator.create_retriever(
retriever_name,
source=source,
chat_history=[],
prompt="default",
chunks=chunks,
token_limit=token_limit,
gpt_model=gpt_model,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
docs = retriever.search(question)
retriever_params = retriever.get_params()
user_logs_collection.insert_one(
{
"action": "api_search",
"level": "info",
"user": decoded_token.get("sub"),
"api_key": user_api_key,
"question": question,
"sources": docs,
"retriever_params": retriever_params,
"timestamp": datetime.datetime.now(datetime.timezone.utc),
}
)
if data.get("isNoneDoc"):
for doc in docs:
doc["source"] = "None"
except Exception as e:
logger.error(
f"/api/search - error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
return bad_request(500, str(e))
return make_response(docs, 200)
def get_attachments_content(attachment_ids, user):
"""
Retrieve content from attachment documents based on their IDs.
Args:
attachment_ids (list): List of attachment document IDs
user (str): User identifier to verify ownership
Returns:
list: List of dictionaries containing attachment content and metadata
"""
if not attachment_ids:
return []
attachments = []
for attachment_id in attachment_ids:
try:
attachment_doc = attachments_collection.find_one(
{"_id": ObjectId(attachment_id), "user": user}
)
if attachment_doc:
attachments.append(attachment_doc)
except Exception as e:
logger.error(
f"Error retrieving attachment {attachment_id}: {e}", exc_info=True
)
return attachments

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@@ -0,0 +1,122 @@
import logging
import traceback
from flask import make_response, request
from flask_restx import fields, Resource
from application.api import api
from application.api.answer.routes.base import answer_ns, BaseAnswerResource
from application.api.answer.services.stream_processor import StreamProcessor
logger = logging.getLogger(__name__)
@answer_ns.route("/api/answer")
class AnswerResource(Resource, BaseAnswerResource):
def __init__(self, *args, **kwargs):
Resource.__init__(self, *args, **kwargs)
BaseAnswerResource.__init__(self)
answer_model = answer_ns.model(
"AnswerModel",
{
"question": fields.String(
required=True, description="Question to be asked"
),
"history": fields.List(
fields.String,
required=False,
description="Conversation history (only for new conversations)",
),
"conversation_id": fields.String(
required=False,
description="Existing conversation ID (loads history)",
),
"prompt_id": fields.String(
required=False, default="default", description="Prompt ID"
),
"chunks": fields.Integer(
required=False, default=2, description="Number of chunks"
),
"token_limit": fields.Integer(required=False, description="Token limit"),
"retriever": fields.String(required=False, description="Retriever type"),
"api_key": fields.String(required=False, description="API key"),
"active_docs": fields.String(
required=False, description="Active documents"
),
"isNoneDoc": fields.Boolean(
required=False, description="Flag indicating if no document is used"
),
"save_conversation": fields.Boolean(
required=False,
default=True,
description="Whether to save the conversation",
),
},
)
@api.expect(answer_model)
@api.doc(description="Provide a response based on the question and retriever")
def post(self):
data = request.get_json()
if error := self.validate_request(data):
return error
decoded_token = getattr(request, "decoded_token", None)
processor = StreamProcessor(data, decoded_token)
try:
processor.initialize()
if not processor.decoded_token:
return make_response({"error": "Unauthorized"}, 401)
agent = processor.create_agent()
retriever = processor.create_retriever()
stream = self.complete_stream(
question=data["question"],
agent=agent,
retriever=retriever,
conversation_id=processor.conversation_id,
user_api_key=processor.agent_config.get("user_api_key"),
decoded_token=processor.decoded_token,
isNoneDoc=data.get("isNoneDoc"),
index=None,
should_save_conversation=data.get("save_conversation", True),
)
stream_result = self.process_response_stream(stream)
if len(stream_result) == 7:
(
conversation_id,
response,
sources,
tool_calls,
thought,
error,
structured_info,
) = stream_result
else:
conversation_id, response, sources, tool_calls, thought, error = (
stream_result
)
structured_info = None
if error:
return make_response({"error": error}, 400)
result = {
"conversation_id": conversation_id,
"answer": response,
"sources": sources,
"tool_calls": tool_calls,
"thought": thought,
}
if structured_info:
result.update(structured_info)
except Exception as e:
logger.error(
f"/api/answer - error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
return make_response({"error": str(e)}, 500)
return make_response(result, 200)

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@@ -0,0 +1,263 @@
import datetime
import json
import logging
from typing import Any, Dict, Generator, List, Optional
from flask import Response
from flask_restx import Namespace
from application.api.answer.services.conversation_service import ConversationService
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.llm.llm_creator import LLMCreator
from application.utils import check_required_fields, get_gpt_model
logger = logging.getLogger(__name__)
answer_ns = Namespace("answer", description="Answer related operations", path="/")
class BaseAnswerResource:
"""Shared base class for answer endpoints"""
def __init__(self):
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
self.user_logs_collection = db["user_logs"]
self.gpt_model = get_gpt_model()
self.conversation_service = ConversationService()
def validate_request(
self, data: Dict[str, Any], require_conversation_id: bool = False
) -> Optional[Response]:
"""Common request validation"""
required_fields = ["question"]
if require_conversation_id:
required_fields.append("conversation_id")
if missing_fields := check_required_fields(data, required_fields):
return missing_fields
return None
def complete_stream(
self,
question: str,
agent: Any,
retriever: Any,
conversation_id: Optional[str],
user_api_key: Optional[str],
decoded_token: Dict[str, Any],
isNoneDoc: bool = False,
index: Optional[int] = None,
should_save_conversation: bool = True,
attachment_ids: Optional[List[str]] = None,
agent_id: Optional[str] = None,
is_shared_usage: bool = False,
shared_token: Optional[str] = None,
) -> Generator[str, None, None]:
"""
Generator function that streams the complete conversation response.
Args:
question: The user's question
agent: The agent instance
retriever: The retriever instance
conversation_id: Existing conversation ID
user_api_key: User's API key if any
decoded_token: Decoded JWT token
isNoneDoc: Flag for document-less responses
index: Index of message to update
should_save_conversation: Whether to persist the conversation
attachment_ids: List of attachment IDs
agent_id: ID of agent used
is_shared_usage: Flag for shared agent usage
shared_token: Token for shared agent
Yields:
Server-sent event strings
"""
try:
response_full, thought, source_log_docs, tool_calls = "", "", [], []
is_structured = False
schema_info = None
structured_chunks = []
for line in agent.gen(query=question, retriever=retriever):
if "answer" in line:
response_full += str(line["answer"])
if line.get("structured"):
is_structured = True
schema_info = line.get("schema")
structured_chunks.append(line["answer"])
else:
data = json.dumps({"type": "answer", "answer": line["answer"]})
yield f"data: {data}\n\n"
elif "sources" in line:
truncated_sources = []
source_log_docs = line["sources"]
for source in line["sources"]:
truncated_source = source.copy()
if "text" in truncated_source:
truncated_source["text"] = (
truncated_source["text"][:100].strip() + "..."
)
truncated_sources.append(truncated_source)
if truncated_sources:
data = json.dumps(
{"type": "source", "source": truncated_sources}
)
yield f"data: {data}\n\n"
elif "tool_calls" in line:
tool_calls = line["tool_calls"]
elif "thought" in line:
thought += line["thought"]
data = json.dumps({"type": "thought", "thought": line["thought"]})
yield f"data: {data}\n\n"
elif "type" in line:
data = json.dumps(line)
yield f"data: {data}\n\n"
if is_structured and structured_chunks:
structured_data = {
"type": "structured_answer",
"answer": response_full,
"structured": True,
"schema": schema_info,
}
data = json.dumps(structured_data)
yield f"data: {data}\n\n"
if isNoneDoc:
for doc in source_log_docs:
doc["source"] = "None"
llm = LLMCreator.create_llm(
settings.LLM_PROVIDER,
api_key=settings.API_KEY,
user_api_key=user_api_key,
decoded_token=decoded_token,
)
if should_save_conversation:
conversation_id = self.conversation_service.save_conversation(
conversation_id,
question,
response_full,
thought,
source_log_docs,
tool_calls,
llm,
self.gpt_model,
decoded_token,
index=index,
api_key=user_api_key,
agent_id=agent_id,
is_shared_usage=is_shared_usage,
shared_token=shared_token,
attachment_ids=attachment_ids,
)
else:
conversation_id = None
id_data = {"type": "id", "id": str(conversation_id)}
data = json.dumps(id_data)
yield f"data: {data}\n\n"
retriever_params = retriever.get_params()
log_data = {
"action": "stream_answer",
"level": "info",
"user": decoded_token.get("sub"),
"api_key": user_api_key,
"question": question,
"response": response_full,
"sources": source_log_docs,
"retriever_params": retriever_params,
"attachments": attachment_ids,
"timestamp": datetime.datetime.now(datetime.timezone.utc),
}
if is_structured:
log_data["structured_output"] = True
if schema_info:
log_data["schema"] = schema_info
# clean up text fields to be no longer than 10000 characters
for key, value in log_data.items():
if isinstance(value, str) and len(value) > 10000:
log_data[key] = value[:10000]
self.user_logs_collection.insert_one(log_data)
# End of stream
data = json.dumps({"type": "end"})
yield f"data: {data}\n\n"
except Exception as e:
logger.error(f"Error in stream: {str(e)}", exc_info=True)
data = json.dumps(
{
"type": "error",
"error": "Please try again later. We apologize for any inconvenience.",
}
)
yield f"data: {data}\n\n"
return
def process_response_stream(self, stream):
"""Process the stream response for non-streaming endpoint"""
conversation_id = ""
response_full = ""
source_log_docs = []
tool_calls = []
thought = ""
stream_ended = False
is_structured = False
schema_info = None
for line in stream:
try:
event_data = line.replace("data: ", "").strip()
event = json.loads(event_data)
if event["type"] == "id":
conversation_id = event["id"]
elif event["type"] == "answer":
response_full += event["answer"]
elif event["type"] == "structured_answer":
response_full = event["answer"]
is_structured = True
schema_info = event.get("schema")
elif event["type"] == "source":
source_log_docs = event["source"]
elif event["type"] == "tool_calls":
tool_calls = event["tool_calls"]
elif event["type"] == "thought":
thought = event["thought"]
elif event["type"] == "error":
logger.error(f"Error from stream: {event['error']}")
return None, None, None, None, event["error"]
elif event["type"] == "end":
stream_ended = True
except (json.JSONDecodeError, KeyError) as e:
logger.warning(f"Error parsing stream event: {e}, line: {line}")
continue
if not stream_ended:
logger.error("Stream ended unexpectedly without an 'end' event.")
return None, None, None, None, "Stream ended unexpectedly"
result = (
conversation_id,
response_full,
source_log_docs,
tool_calls,
thought,
None,
)
if is_structured:
result = result + ({"structured": True, "schema": schema_info},)
return result
def error_stream_generate(self, err_response):
data = json.dumps({"type": "error", "error": err_response})
yield f"data: {data}\n\n"

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import logging
import traceback
from flask import request, Response
from flask_restx import fields, Resource
from application.api import api
from application.api.answer.routes.base import answer_ns, BaseAnswerResource
from application.api.answer.services.stream_processor import StreamProcessor
logger = logging.getLogger(__name__)
@answer_ns.route("/stream")
class StreamResource(Resource, BaseAnswerResource):
def __init__(self, *args, **kwargs):
Resource.__init__(self, *args, **kwargs)
BaseAnswerResource.__init__(self)
stream_model = answer_ns.model(
"StreamModel",
{
"question": fields.String(
required=True, description="Question to be asked"
),
"history": fields.List(
fields.String,
required=False,
description="Conversation history (only for new conversations)",
),
"conversation_id": fields.String(
required=False,
description="Existing conversation ID (loads history)",
),
"prompt_id": fields.String(
required=False, default="default", description="Prompt ID"
),
"chunks": fields.Integer(
required=False, default=2, description="Number of chunks"
),
"token_limit": fields.Integer(required=False, description="Token limit"),
"retriever": fields.String(required=False, description="Retriever type"),
"api_key": fields.String(required=False, description="API key"),
"active_docs": fields.String(
required=False, description="Active documents"
),
"isNoneDoc": fields.Boolean(
required=False, description="Flag indicating if no document is used"
),
"index": fields.Integer(
required=False, description="Index of the query to update"
),
"save_conversation": fields.Boolean(
required=False,
default=True,
description="Whether to save the conversation",
),
"attachments": fields.List(
fields.String, required=False, description="List of attachment IDs"
),
},
)
@api.expect(stream_model)
@api.doc(description="Stream a response based on the question and retriever")
def post(self):
data = request.get_json()
if error := self.validate_request(data, "index" in data):
return error
decoded_token = getattr(request, "decoded_token", None)
processor = StreamProcessor(data, decoded_token)
try:
processor.initialize()
agent = processor.create_agent()
retriever = processor.create_retriever()
return Response(
self.complete_stream(
question=data["question"],
agent=agent,
retriever=retriever,
conversation_id=processor.conversation_id,
user_api_key=processor.agent_config.get("user_api_key"),
decoded_token=processor.decoded_token,
isNoneDoc=data.get("isNoneDoc"),
index=data.get("index"),
should_save_conversation=data.get("save_conversation", True),
attachment_ids=data.get("attachments", []),
agent_id=data.get("agent_id"),
is_shared_usage=processor.is_shared_usage,
shared_token=processor.shared_token,
),
mimetype="text/event-stream",
)
except ValueError as e:
message = "Malformed request body"
logger.error(
f"/stream - error: {message} - specific error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
return Response(
self.error_stream_generate(message),
status=400,
mimetype="text/event-stream",
)
except Exception as e:
logger.error(
f"/stream - error: {str(e)} - traceback: {traceback.format_exc()}",
extra={"error": str(e), "traceback": traceback.format_exc()},
)
return Response(
self.error_stream_generate("Unknown error occurred"),
status=400,
mimetype="text/event-stream",
)

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import logging
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from bson import ObjectId
logger = logging.getLogger(__name__)
class ConversationService:
def __init__(self):
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
self.conversations_collection = db["conversations"]
self.agents_collection = db["agents"]
def get_conversation(
self, conversation_id: str, user_id: str
) -> Optional[Dict[str, Any]]:
"""Retrieve a conversation with proper access control"""
if not conversation_id or not user_id:
return None
try:
conversation = self.conversations_collection.find_one(
{
"_id": ObjectId(conversation_id),
"$or": [{"user": user_id}, {"shared_with": user_id}],
}
)
if not conversation:
logger.warning(
f"Conversation not found or unauthorized - ID: {conversation_id}, User: {user_id}"
)
return None
conversation["_id"] = str(conversation["_id"])
return conversation
except Exception as e:
logger.error(f"Error fetching conversation: {str(e)}", exc_info=True)
return None
def save_conversation(
self,
conversation_id: Optional[str],
question: str,
response: str,
thought: str,
sources: List[Dict[str, Any]],
tool_calls: List[Dict[str, Any]],
llm: Any,
gpt_model: str,
decoded_token: Dict[str, Any],
index: Optional[int] = None,
api_key: Optional[str] = None,
agent_id: Optional[str] = None,
is_shared_usage: bool = False,
shared_token: Optional[str] = None,
attachment_ids: Optional[List[str]] = None,
) -> str:
"""Save or update a conversation in the database"""
user_id = decoded_token.get("sub")
if not user_id:
raise ValueError("User ID not found in token")
current_time = datetime.now(timezone.utc)
# clean up in sources array such that we save max 1k characters for text part
for source in sources:
if "text" in source and isinstance(source["text"], str):
source["text"] = source["text"][:1000]
if conversation_id is not None and index is not None:
# Update existing conversation with new query
result = self.conversations_collection.update_one(
{
"_id": ObjectId(conversation_id),
"user": user_id,
f"queries.{index}": {"$exists": True},
},
{
"$set": {
f"queries.{index}.prompt": question,
f"queries.{index}.response": response,
f"queries.{index}.thought": thought,
f"queries.{index}.sources": sources,
f"queries.{index}.tool_calls": tool_calls,
f"queries.{index}.timestamp": current_time,
f"queries.{index}.attachments": attachment_ids,
}
},
)
if result.matched_count == 0:
raise ValueError("Conversation not found or unauthorized")
self.conversations_collection.update_one(
{
"_id": ObjectId(conversation_id),
"user": user_id,
f"queries.{index}": {"$exists": True},
},
{"$push": {"queries": {"$each": [], "$slice": index + 1}}},
)
return conversation_id
elif conversation_id:
# Append new message to existing conversation
result = self.conversations_collection.update_one(
{"_id": ObjectId(conversation_id), "user": user_id},
{
"$push": {
"queries": {
"prompt": question,
"response": response,
"thought": thought,
"sources": sources,
"tool_calls": tool_calls,
"timestamp": current_time,
"attachments": attachment_ids,
}
}
},
)
if result.matched_count == 0:
raise ValueError("Conversation not found or unauthorized")
return conversation_id
else:
# Create new conversation
messages_summary = [
{
"role": "assistant",
"content": "Summarise following conversation in no more than 3 "
"words, respond ONLY with the summary, use the same "
"language as the user query",
},
{
"role": "user",
"content": "Summarise following conversation in no more than 3 words, "
"respond ONLY with the summary, use the same language as the "
"user query \n\nUser: " + question + "\n\n" + "AI: " + response,
},
]
completion = llm.gen(
model=gpt_model, messages=messages_summary, max_tokens=30
)
conversation_data = {
"user": user_id,
"date": current_time,
"name": completion,
"queries": [
{
"prompt": question,
"response": response,
"thought": thought,
"sources": sources,
"tool_calls": tool_calls,
"timestamp": current_time,
"attachments": attachment_ids,
}
],
}
if api_key:
if agent_id:
conversation_data["agent_id"] = agent_id
if is_shared_usage:
conversation_data["is_shared_usage"] = is_shared_usage
conversation_data["shared_token"] = shared_token
agent = self.agents_collection.find_one({"key": api_key})
if agent:
conversation_data["api_key"] = agent["key"]
result = self.conversations_collection.insert_one(conversation_data)
return str(result.inserted_id)

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import datetime
import json
import logging
import os
from pathlib import Path
from typing import Any, Dict, Optional
from bson.dbref import DBRef
from bson.objectid import ObjectId
from application.agents.agent_creator import AgentCreator
from application.api.answer.services.conversation_service import ConversationService
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.retriever.retriever_creator import RetrieverCreator
from application.utils import get_gpt_model, limit_chat_history
logger = logging.getLogger(__name__)
def get_prompt(prompt_id: str, prompts_collection=None) -> str:
"""
Get a prompt by preset name or MongoDB ID
"""
current_dir = Path(__file__).resolve().parents[3]
prompts_dir = current_dir / "prompts"
preset_mapping = {
"default": "chat_combine_default.txt",
"creative": "chat_combine_creative.txt",
"strict": "chat_combine_strict.txt",
"reduce": "chat_reduce_prompt.txt",
}
if prompt_id in preset_mapping:
file_path = os.path.join(prompts_dir, preset_mapping[prompt_id])
try:
with open(file_path, "r") as f:
return f.read()
except FileNotFoundError:
raise FileNotFoundError(f"Prompt file not found: {file_path}")
try:
if prompts_collection is None:
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
prompts_collection = db["prompts"]
prompt_doc = prompts_collection.find_one({"_id": ObjectId(prompt_id)})
if not prompt_doc:
raise ValueError(f"Prompt with ID {prompt_id} not found")
return prompt_doc["content"]
except Exception as e:
raise ValueError(f"Invalid prompt ID: {prompt_id}") from e
class StreamProcessor:
def __init__(
self, request_data: Dict[str, Any], decoded_token: Optional[Dict[str, Any]]
):
mongo = MongoDB.get_client()
self.db = mongo[settings.MONGO_DB_NAME]
self.agents_collection = self.db["agents"]
self.attachments_collection = self.db["attachments"]
self.prompts_collection = self.db["prompts"]
self.data = request_data
self.decoded_token = decoded_token
self.initial_user_id = (
self.decoded_token.get("sub") if self.decoded_token is not None else None
)
self.conversation_id = self.data.get("conversation_id")
self.source = (
{"active_docs": self.data["active_docs"]}
if "active_docs" in self.data
else {}
)
self.attachments = []
self.history = []
self.agent_config = {}
self.retriever_config = {}
self.is_shared_usage = False
self.shared_token = None
self.gpt_model = get_gpt_model()
self.conversation_service = ConversationService()
def initialize(self):
"""Initialize all required components for processing"""
self._configure_retriever()
self._configure_agent()
self._load_conversation_history()
self._process_attachments()
def _load_conversation_history(self):
"""Load conversation history either from DB or request"""
if self.conversation_id and self.initial_user_id:
conversation = self.conversation_service.get_conversation(
self.conversation_id, self.initial_user_id
)
if not conversation:
raise ValueError("Conversation not found or unauthorized")
self.history = [
{"prompt": query["prompt"], "response": query["response"]}
for query in conversation.get("queries", [])
]
else:
self.history = limit_chat_history(
json.loads(self.data.get("history", "[]")), gpt_model=self.gpt_model
)
def _process_attachments(self):
"""Process any attachments in the request"""
attachment_ids = self.data.get("attachments", [])
self.attachments = self._get_attachments_content(
attachment_ids, self.initial_user_id
)
def _get_attachments_content(self, attachment_ids, user_id):
"""
Retrieve content from attachment documents based on their IDs.
"""
if not attachment_ids:
return []
attachments = []
for attachment_id in attachment_ids:
try:
attachment_doc = self.attachments_collection.find_one(
{"_id": ObjectId(attachment_id), "user": user_id}
)
if attachment_doc:
attachments.append(attachment_doc)
except Exception as e:
logger.error(
f"Error retrieving attachment {attachment_id}: {e}", exc_info=True
)
return attachments
def _get_agent_key(self, agent_id: Optional[str], user_id: Optional[str]) -> tuple:
"""Get API key for agent with access control"""
if not agent_id:
return None, False, None
try:
agent = self.agents_collection.find_one({"_id": ObjectId(agent_id)})
if agent is None:
raise Exception("Agent not found")
is_owner = agent.get("user") == user_id
is_shared_with_user = agent.get(
"shared_publicly", False
) or user_id in agent.get("shared_with", [])
if not (is_owner or is_shared_with_user):
raise Exception("Unauthorized access to the agent")
if is_owner:
self.agents_collection.update_one(
{"_id": ObjectId(agent_id)},
{
"$set": {
"lastUsedAt": datetime.datetime.now(datetime.timezone.utc)
}
},
)
return str(agent["key"]), not is_owner, agent.get("shared_token")
except Exception as e:
logger.error(f"Error in get_agent_key: {str(e)}", exc_info=True)
raise
def _get_data_from_api_key(self, api_key: str) -> Dict[str, Any]:
data = self.agents_collection.find_one({"key": api_key})
if not data:
raise Exception("Invalid API Key, please generate a new key", 401)
source = data.get("source")
if isinstance(source, DBRef):
source_doc = self.db.dereference(source)
data["source"] = str(source_doc["_id"])
data["retriever"] = source_doc.get("retriever", data.get("retriever"))
data["chunks"] = source_doc.get("chunks", data.get("chunks"))
else:
data["source"] = None
return data
def _configure_agent(self):
"""Configure the agent based on request data"""
agent_id = self.data.get("agent_id")
self.agent_key, self.is_shared_usage, self.shared_token = self._get_agent_key(
agent_id, self.initial_user_id
)
api_key = self.data.get("api_key")
if api_key:
data_key = self._get_data_from_api_key(api_key)
self.agent_config.update(
{
"prompt_id": data_key.get("prompt_id", "default"),
"agent_type": data_key.get("agent_type", settings.AGENT_NAME),
"user_api_key": api_key,
"json_schema": data_key.get("json_schema"),
}
)
self.initial_user_id = data_key.get("user")
self.decoded_token = {"sub": data_key.get("user")}
if data_key.get("source"):
self.source = {"active_docs": data_key["source"]}
if data_key.get("retriever"):
self.retriever_config["retriever_name"] = data_key["retriever"]
if data_key.get("chunks") is not None:
self.retriever_config["chunks"] = data_key["chunks"]
elif self.agent_key:
data_key = self._get_data_from_api_key(self.agent_key)
self.agent_config.update(
{
"prompt_id": data_key.get("prompt_id", "default"),
"agent_type": data_key.get("agent_type", settings.AGENT_NAME),
"user_api_key": self.agent_key,
"json_schema": data_key.get("json_schema"),
}
)
self.decoded_token = (
self.decoded_token
if self.is_shared_usage
else {"sub": data_key.get("user")}
)
if data_key.get("source"):
self.source = {"active_docs": data_key["source"]}
if data_key.get("retriever"):
self.retriever_config["retriever_name"] = data_key["retriever"]
if data_key.get("chunks") is not None:
self.retriever_config["chunks"] = data_key["chunks"]
else:
self.agent_config.update(
{
"prompt_id": self.data.get("prompt_id", "default"),
"agent_type": settings.AGENT_NAME,
"user_api_key": None,
"json_schema": None,
}
)
def _configure_retriever(self):
"""Configure the retriever based on request data"""
self.retriever_config = {
"retriever_name": self.data.get("retriever", "classic"),
"chunks": int(self.data.get("chunks", 2)),
"token_limit": self.data.get("token_limit", settings.DEFAULT_MAX_HISTORY),
}
if "isNoneDoc" in self.data and self.data["isNoneDoc"]:
self.retriever_config["chunks"] = 0
def create_agent(self):
"""Create and return the configured agent"""
return AgentCreator.create_agent(
self.agent_config["agent_type"],
endpoint="stream",
llm_name=settings.LLM_PROVIDER,
gpt_model=self.gpt_model,
api_key=settings.API_KEY,
user_api_key=self.agent_config["user_api_key"],
prompt=get_prompt(self.agent_config["prompt_id"], self.prompts_collection),
chat_history=self.history,
decoded_token=self.decoded_token,
attachments=self.attachments,
json_schema=self.agent_config.get("json_schema"),
)
def create_retriever(self):
"""Create and return the configured retriever"""
return RetrieverCreator.create_retriever(
self.retriever_config["retriever_name"],
source=self.source,
chat_history=self.history,
prompt=get_prompt(self.agent_config["prompt_id"], self.prompts_collection),
chunks=self.retriever_config["chunks"],
token_limit=self.retriever_config["token_limit"],
gpt_model=self.gpt_model,
user_api_key=self.agent_config["user_api_key"],
decoded_token=self.decoded_token,
)

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import datetime
import json
import logging
from bson.objectid import ObjectId
from flask import (
Blueprint,
current_app,
jsonify,
make_response,
request
)
from flask_restx import fields, Namespace, Resource
from application.api.user.tasks import (
ingest_connector_task,
)
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.api import api
from application.utils import (
check_required_fields
)
from application.parser.connectors.connector_creator import ConnectorCreator
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
sources_collection = db["sources"]
sessions_collection = db["connector_sessions"]
connector = Blueprint("connector", __name__)
connectors_ns = Namespace("connectors", description="Connector operations", path="/")
api.add_namespace(connectors_ns)
@connectors_ns.route("/api/connectors/upload")
class UploadConnector(Resource):
@api.expect(
api.model(
"ConnectorUploadModel",
{
"user": fields.String(required=True, description="User ID"),
"source": fields.String(
required=True, description="Source type (google_drive, github, etc.)"
),
"name": fields.String(required=True, description="Job name"),
"data": fields.String(required=True, description="Configuration data"),
"repo_url": fields.String(description="GitHub repository URL"),
},
)
)
@api.doc(
description="Uploads connector source for vectorization",
)
def post(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
data = request.form
required_fields = ["user", "source", "name", "data"]
missing_fields = check_required_fields(data, required_fields)
if missing_fields:
return missing_fields
try:
config = json.loads(data["data"])
source_data = None
sync_frequency = config.get("sync_frequency", "never")
if data["source"] == "github":
source_data = config.get("repo_url")
elif data["source"] in ["crawler", "url"]:
source_data = config.get("url")
elif data["source"] == "reddit":
source_data = config
elif data["source"] in ConnectorCreator.get_supported_connectors():
session_token = config.get("session_token")
if not session_token:
return make_response(jsonify({
"success": False,
"error": f"Missing session_token in {data['source']} configuration"
}), 400)
file_ids = config.get("file_ids", [])
if isinstance(file_ids, str):
file_ids = [id.strip() for id in file_ids.split(',') if id.strip()]
elif not isinstance(file_ids, list):
file_ids = []
folder_ids = config.get("folder_ids", [])
if isinstance(folder_ids, str):
folder_ids = [id.strip() for id in folder_ids.split(',') if id.strip()]
elif not isinstance(folder_ids, list):
folder_ids = []
config["file_ids"] = file_ids
config["folder_ids"] = folder_ids
task = ingest_connector_task.delay(
job_name=data["name"],
user=decoded_token.get("sub"),
source_type=data["source"],
session_token=session_token,
file_ids=file_ids,
folder_ids=folder_ids,
recursive=config.get("recursive", False),
retriever=config.get("retriever", "classic"),
sync_frequency=sync_frequency
)
return make_response(jsonify({"success": True, "task_id": task.id}), 200)
task = ingest_connector_task.delay(
source_data=source_data,
job_name=data["name"],
user=decoded_token.get("sub"),
loader=data["source"],
sync_frequency=sync_frequency
)
except Exception as err:
current_app.logger.error(
f"Error uploading connector source: {err}", exc_info=True
)
return make_response(jsonify({"success": False}), 400)
return make_response(jsonify({"success": True, "task_id": task.id}), 200)
@connectors_ns.route("/api/connectors/task_status")
class ConnectorTaskStatus(Resource):
task_status_model = api.model(
"ConnectorTaskStatusModel",
{"task_id": fields.String(required=True, description="Task ID")},
)
@api.expect(task_status_model)
@api.doc(description="Get connector task status")
def get(self):
task_id = request.args.get("task_id")
if not task_id:
return make_response(
jsonify({"success": False, "message": "Task ID is required"}), 400
)
try:
from application.celery_init import celery
task = celery.AsyncResult(task_id)
task_meta = task.info
print(f"Task status: {task.status}")
if not isinstance(
task_meta, (dict, list, str, int, float, bool, type(None))
):
task_meta = str(task_meta)
except Exception as err:
current_app.logger.error(f"Error getting task status: {err}", exc_info=True)
return make_response(jsonify({"success": False}), 400)
return make_response(jsonify({"status": task.status, "result": task_meta}), 200)
@connectors_ns.route("/api/connectors/sources")
class ConnectorSources(Resource):
@api.doc(description="Get connector sources")
def get(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
user = decoded_token.get("sub")
try:
sources = sources_collection.find({"user": user, "type": "connector"}).sort("date", -1)
connector_sources = []
for source in sources:
connector_sources.append({
"id": str(source["_id"]),
"name": source.get("name"),
"date": source.get("date"),
"type": source.get("type"),
"source": source.get("source"),
"tokens": source.get("tokens", ""),
"retriever": source.get("retriever", "classic"),
"syncFrequency": source.get("sync_frequency", ""),
})
except Exception as err:
current_app.logger.error(f"Error retrieving connector sources: {err}", exc_info=True)
return make_response(jsonify({"success": False}), 400)
return make_response(jsonify(connector_sources), 200)
@connectors_ns.route("/api/connectors/delete")
class DeleteConnectorSource(Resource):
@api.doc(
description="Delete a connector source",
params={"source_id": "The source ID to delete"},
)
def delete(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
source_id = request.args.get("source_id")
if not source_id:
return make_response(
jsonify({"success": False, "message": "source_id is required"}), 400
)
try:
result = sources_collection.delete_one(
{"_id": ObjectId(source_id), "user": decoded_token.get("sub")}
)
if result.deleted_count == 0:
return make_response(
jsonify({"success": False, "message": "Source not found"}), 404
)
except Exception as err:
current_app.logger.error(
f"Error deleting connector source: {err}", exc_info=True
)
return make_response(jsonify({"success": False}), 400)
return make_response(jsonify({"success": True}), 200)
@connectors_ns.route("/api/connectors/auth")
class ConnectorAuth(Resource):
@api.doc(description="Get connector OAuth authorization URL", params={"provider": "Connector provider (e.g., google_drive)"})
def get(self):
try:
provider = request.args.get('provider') or request.args.get('source')
if not provider:
return make_response(jsonify({"success": False, "error": "Missing provider"}), 400)
if not ConnectorCreator.is_supported(provider):
return make_response(jsonify({"success": False, "error": f"Unsupported provider: {provider}"}), 400)
import uuid
state = str(uuid.uuid4())
auth = ConnectorCreator.create_auth(provider)
authorization_url = auth.get_authorization_url(state=state)
return make_response(jsonify({
"success": True,
"authorization_url": authorization_url,
"state": state
}), 200)
except Exception as e:
current_app.logger.error(f"Error generating connector auth URL: {e}")
return make_response(jsonify({"success": False, "error": str(e)}), 500)
@connectors_ns.route("/api/connectors/callback")
class ConnectorsCallback(Resource):
@api.doc(description="Handle OAuth callback for external connectors")
def get(self):
"""Handle OAuth callback for external connectors"""
try:
from application.parser.connectors.connector_creator import ConnectorCreator
from flask import request, redirect
import uuid
provider = request.args.get('provider', 'google_drive')
authorization_code = request.args.get('code')
_ = request.args.get('state')
error = request.args.get('error')
if error:
return redirect(f"/api/connectors/callback-status?status=error&message=OAuth+error:+{error}.+Please+try+again+and+make+sure+to+grant+all+requested+permissions,+including+offline+access.&provider={provider}")
if not authorization_code:
return redirect(f"/api/connectors/callback-status?status=error&message=Authorization+code+not+provided.+Please+complete+the+authorization+process+and+make+sure+to+grant+offline+access.&provider={provider}")
try:
auth = ConnectorCreator.create_auth(provider)
token_info = auth.exchange_code_for_tokens(authorization_code)
session_token = str(uuid.uuid4())
try:
credentials = auth.create_credentials_from_token_info(token_info)
service = auth.build_drive_service(credentials)
user_info = service.about().get(fields="user").execute()
user_email = user_info.get('user', {}).get('emailAddress', 'Connected User')
except Exception as e:
current_app.logger.warning(f"Could not get user info: {e}")
user_email = 'Connected User'
sanitized_token_info = {
"access_token": token_info.get("access_token"),
"refresh_token": token_info.get("refresh_token"),
"token_uri": token_info.get("token_uri"),
"expiry": token_info.get("expiry"),
"scopes": token_info.get("scopes")
}
user_id = request.decoded_token.get("sub") if getattr(request, "decoded_token", None) else None
sessions_collection.insert_one({
"session_token": session_token,
"user": user_id,
"token_info": sanitized_token_info,
"created_at": datetime.datetime.now(datetime.timezone.utc),
"user_email": user_email,
"provider": provider
})
# Redirect to success page with session token and user email
return redirect(f"/api/connectors/callback-status?status=success&message=Authentication+successful&provider={provider}&session_token={session_token}&user_email={user_email}")
except Exception as e:
current_app.logger.error(f"Error exchanging code for tokens: {str(e)}", exc_info=True)
return redirect(f"/api/connectors/callback-status?status=error&message=Failed+to+exchange+authorization+code+for+tokens:+{str(e)}&provider={provider}")
except Exception as e:
current_app.logger.error(f"Error handling connector callback: {e}")
return redirect(f"/api/connectors/callback-status?status=error&message=Failed+to+complete+connector+authentication:+{str(e)}.+Please+try+again+and+make+sure+to+grant+all+requested+permissions,+including+offline+access.")
@connectors_ns.route("/api/connectors/refresh")
class ConnectorRefresh(Resource):
@api.expect(api.model("ConnectorRefreshModel", {"provider": fields.String(required=True), "refresh_token": fields.String(required=True)}))
@api.doc(description="Refresh connector access token")
def post(self):
try:
data = request.get_json()
provider = data.get('provider')
refresh_token = data.get('refresh_token')
if not provider or not refresh_token:
return make_response(jsonify({"success": False, "error": "provider and refresh_token are required"}), 400)
auth = ConnectorCreator.create_auth(provider)
token_info = auth.refresh_access_token(refresh_token)
return make_response(jsonify({"success": True, "token_info": token_info}), 200)
except Exception as e:
current_app.logger.error(f"Error refreshing token for connector: {e}")
return make_response(jsonify({"success": False, "error": str(e)}), 500)
@connectors_ns.route("/api/connectors/files")
class ConnectorFiles(Resource):
@api.expect(api.model("ConnectorFilesModel", {"provider": fields.String(required=True), "session_token": fields.String(required=True), "folder_id": fields.String(required=False), "limit": fields.Integer(required=False), "page_token": fields.String(required=False)}))
@api.doc(description="List files from a connector provider (supports pagination)")
def post(self):
try:
data = request.get_json()
provider = data.get('provider')
session_token = data.get('session_token')
folder_id = data.get('folder_id')
limit = data.get('limit', 10)
page_token = data.get('page_token')
if not provider or not session_token:
return make_response(jsonify({"success": False, "error": "provider and session_token are required"}), 400)
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False, "error": "Unauthorized"}), 401)
user = decoded_token.get('sub')
session = sessions_collection.find_one({"session_token": session_token, "user": user})
if not session:
return make_response(jsonify({"success": False, "error": "Invalid or unauthorized session"}), 401)
loader = ConnectorCreator.create_connector(provider, session_token)
documents = loader.load_data({
'limit': limit,
'list_only': True,
'session_token': session_token,
'folder_id': folder_id,
'page_token': page_token
})
files = []
for doc in documents[:limit]:
metadata = doc.extra_info
modified_time = metadata.get('modified_time')
if modified_time:
date_part = modified_time.split('T')[0]
time_part = modified_time.split('T')[1].split('.')[0].split('Z')[0]
formatted_time = f"{date_part} {time_part}"
else:
formatted_time = None
files.append({
'id': doc.doc_id,
'name': metadata.get('file_name', 'Unknown File'),
'type': metadata.get('mime_type', 'unknown'),
'size': metadata.get('size', None),
'modifiedTime': formatted_time
})
next_token = getattr(loader, 'next_page_token', None)
has_more = bool(next_token)
return make_response(jsonify({"success": True, "files": files, "total": len(files), "next_page_token": next_token, "has_more": has_more}), 200)
except Exception as e:
current_app.logger.error(f"Error loading connector files: {e}")
return make_response(jsonify({"success": False, "error": f"Failed to load files: {str(e)}"}), 500)
@connectors_ns.route("/api/connectors/validate-session")
class ConnectorValidateSession(Resource):
@api.expect(api.model("ConnectorValidateSessionModel", {"provider": fields.String(required=True), "session_token": fields.String(required=True)}))
@api.doc(description="Validate connector session token and return user info")
def post(self):
try:
data = request.get_json()
provider = data.get('provider')
session_token = data.get('session_token')
if not provider or not session_token:
return make_response(jsonify({"success": False, "error": "provider and session_token are required"}), 400)
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False, "error": "Unauthorized"}), 401)
user = decoded_token.get('sub')
session = sessions_collection.find_one({"session_token": session_token, "user": user})
if not session or "token_info" not in session:
return make_response(jsonify({"success": False, "error": "Invalid or expired session"}), 401)
token_info = session["token_info"]
auth = ConnectorCreator.create_auth(provider)
is_expired = auth.is_token_expired(token_info)
return make_response(jsonify({
"success": True,
"expired": is_expired,
"user_email": session.get('user_email', 'Connected User')
}), 200)
except Exception as e:
current_app.logger.error(f"Error validating connector session: {e}")
return make_response(jsonify({"success": False, "error": str(e)}), 500)
@connectors_ns.route("/api/connectors/disconnect")
class ConnectorDisconnect(Resource):
@api.expect(api.model("ConnectorDisconnectModel", {"provider": fields.String(required=True), "session_token": fields.String(required=False)}))
@api.doc(description="Disconnect a connector session")
def post(self):
try:
data = request.get_json()
provider = data.get('provider')
session_token = data.get('session_token')
if not provider:
return make_response(jsonify({"success": False, "error": "provider is required"}), 400)
if session_token:
sessions_collection.delete_one({"session_token": session_token})
return make_response(jsonify({"success": True}), 200)
except Exception as e:
current_app.logger.error(f"Error disconnecting connector session: {e}")
return make_response(jsonify({"success": False, "error": str(e)}), 500)
@connectors_ns.route("/api/connectors/sync")
class ConnectorSync(Resource):
@api.expect(
api.model(
"ConnectorSyncModel",
{
"source_id": fields.String(required=True, description="Source ID to sync"),
"session_token": fields.String(required=True, description="Authentication token")
},
)
)
@api.doc(description="Sync connector source to check for modifications")
def post(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
try:
data = request.get_json()
source_id = data.get('source_id')
session_token = data.get('session_token')
if not all([source_id, session_token]):
return make_response(
jsonify({
"success": False,
"error": "source_id and session_token are required"
}),
400
)
source = sources_collection.find_one({"_id": ObjectId(source_id)})
if not source:
return make_response(
jsonify({
"success": False,
"error": "Source not found"
}),
404
)
if source.get('user') != decoded_token.get('sub'):
return make_response(
jsonify({
"success": False,
"error": "Unauthorized access to source"
}),
403
)
remote_data = {}
try:
if source.get('remote_data'):
remote_data = json.loads(source.get('remote_data'))
except json.JSONDecodeError:
current_app.logger.error(f"Invalid remote_data format for source {source_id}")
remote_data = {}
source_type = remote_data.get('provider')
if not source_type:
return make_response(
jsonify({
"success": False,
"error": "Source provider not found in remote_data"
}),
400
)
# Extract configuration from remote_data
file_ids = remote_data.get('file_ids', [])
folder_ids = remote_data.get('folder_ids', [])
recursive = remote_data.get('recursive', True)
# Start the sync task
task = ingest_connector_task.delay(
job_name=source.get('name'),
user=decoded_token.get('sub'),
source_type=source_type,
session_token=session_token,
file_ids=file_ids,
folder_ids=folder_ids,
recursive=recursive,
retriever=source.get('retriever', 'classic'),
operation_mode="sync",
doc_id=source_id,
sync_frequency=source.get('sync_frequency', 'never')
)
return make_response(
jsonify({
"success": True,
"task_id": task.id
}),
200
)
except Exception as err:
current_app.logger.error(
f"Error syncing connector source: {err}",
exc_info=True
)
return make_response(
jsonify({
"success": False,
"error": str(err)
}),
400
)
@connectors_ns.route("/api/connectors/callback-status")
class ConnectorCallbackStatus(Resource):
@api.doc(description="Return HTML page with connector authentication status")
def get(self):
"""Return HTML page with connector authentication status"""
try:
status = request.args.get('status', 'error')
message = request.args.get('message', '')
provider = request.args.get('provider', 'connector')
session_token = request.args.get('session_token', '')
user_email = request.args.get('user_email', '')
html_content = f"""
<!DOCTYPE html>
<html>
<head>
<title>{provider.replace('_', ' ').title()} Authentication</title>
<style>
body {{ font-family: Arial, sans-serif; text-align: center; padding: 40px; }}
.container {{ max-width: 600px; margin: 0 auto; }}
.success {{ color: #4CAF50; }}
.error {{ color: #F44336; }}
</style>
<script>
window.onload = function() {{
const status = "{status}";
const sessionToken = "{session_token}";
const userEmail = "{user_email}";
if (status === "success" && window.opener) {{
window.opener.postMessage({{
type: '{provider}_auth_success',
session_token: sessionToken,
user_email: userEmail
}}, '*');
setTimeout(() => window.close(), 3000);
}}
}};
</script>
</head>
<body>
<div class="container">
<h2>{provider.replace('_', ' ').title()} Authentication</h2>
<div class="{status}">
<p>{message}</p>
{f'<p>Connected as: {user_email}</p>' if status == 'success' else ''}
</div>
<p><small>You can close this window. {f"Your {provider.replace('_', ' ').title()} is now connected and ready to use." if status == 'success' else ''}</small></p>
</div>
</body>
</html>
"""
return make_response(html_content, 200, {'Content-Type': 'text/html'})
except Exception as e:
current_app.logger.error(f"Error rendering callback status page: {e}")
return make_response("Authentication error occurred", 500, {'Content-Type': 'text/html'})

View File

@@ -1,5 +1,6 @@
import os
import datetime
import json
from flask import Blueprint, request, send_from_directory
from werkzeug.utils import secure_filename
from bson.objectid import ObjectId
@@ -48,7 +49,17 @@ def upload_index_files():
remote_data = request.form["remote_data"] if "remote_data" in request.form else None
sync_frequency = request.form["sync_frequency"] if "sync_frequency" in request.form else None
original_file_path = request.form.get("original_file_path")
file_path = request.form.get("file_path")
directory_structure = request.form.get("directory_structure")
if directory_structure:
try:
directory_structure = json.loads(directory_structure)
except Exception:
logger.error("Error parsing directory_structure")
directory_structure = {}
else:
directory_structure = {}
storage = StorageCreator.get_storage()
index_base_path = f"indexes/{id}"
@@ -66,10 +77,13 @@ def upload_index_files():
file_pkl = request.files["file_pkl"]
if file_pkl.filename == "":
return {"status": "no file name"}
# Save index files to storage
storage.save_file(file_faiss, f"{index_base_path}/index.faiss")
storage.save_file(file_pkl, f"{index_base_path}/index.pkl")
faiss_storage_path = f"{index_base_path}/index.faiss"
pkl_storage_path = f"{index_base_path}/index.pkl"
storage.save_file(file_faiss, faiss_storage_path)
storage.save_file(file_pkl, pkl_storage_path)
existing_entry = sources_collection.find_one({"_id": ObjectId(id)})
if existing_entry:
@@ -87,7 +101,8 @@ def upload_index_files():
"retriever": retriever,
"remote_data": remote_data,
"sync_frequency": sync_frequency,
"file_path": original_file_path,
"file_path": file_path,
"directory_structure": directory_structure,
}
},
)
@@ -105,7 +120,8 @@ def upload_index_files():
"retriever": retriever,
"remote_data": remote_data,
"sync_frequency": sync_frequency,
"file_path": original_file_path,
"file_path": file_path,
"directory_structure": directory_structure,
}
)
return {"status": "ok"}

View File

@@ -3,11 +3,11 @@ import json
import math
import os
import secrets
import shutil
import uuid
from functools import wraps
from typing import Optional, Tuple
import tempfile
import zipfile
from bson.binary import Binary, UuidRepresentation
from bson.dbref import DBRef
from bson.objectid import ObjectId
@@ -28,13 +28,14 @@ from application.agents.tools.tool_manager import ToolManager
from application.api.user.tasks import (
ingest,
ingest_connector_task,
ingest_remote,
process_agent_webhook,
store_attachment,
)
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.extensions import api
from application.api import api
from application.storage.storage_creator import StorageCreator
from application.tts.google_tts import GoogleTTS
from application.utils import (
@@ -44,7 +45,9 @@ from application.utils import (
validate_function_name,
validate_required_fields,
)
from application.utils import num_tokens_from_string
from application.vectorstore.vector_creator import VectorCreator
from application.parser.connectors.connector_creator import ConnectorCreator
storage = StorageCreator.get_storage()
@@ -62,12 +65,15 @@ user_logs_collection = db["user_logs"]
user_tools_collection = db["user_tools"]
attachments_collection = db["attachments"]
agents_collection.create_index(
[("shared", 1)],
name="shared_index",
background=True,
)
users_collection.create_index("user_id", unique=True)
try:
agents_collection.create_index(
[("shared", 1)],
name="shared_index",
background=True,
)
users_collection.create_index("user_id", unique=True)
except Exception as e:
print("Error creating indexes:", e)
user = Blueprint("user", __name__)
user_ns = Namespace("user", description="User related operations", path="/")
@@ -471,7 +477,7 @@ class DeleteByIds(Resource):
@user_ns.route("/api/delete_old")
class DeleteOldIndexes(Resource):
@api.doc(
description="Deletes old indexes",
description="Deletes old indexes and associated files",
params={"source_id": "The source ID to delete"},
)
def get(self):
@@ -488,21 +494,40 @@ class DeleteOldIndexes(Resource):
)
if not doc:
return make_response(jsonify({"status": "not found"}), 404)
storage = StorageCreator.get_storage()
try:
# Delete vector index
if settings.VECTOR_STORE == "faiss":
shutil.rmtree(os.path.join(current_dir, "indexes", str(doc["_id"])))
index_path = f"indexes/{str(doc['_id'])}"
if storage.file_exists(f"{index_path}/index.faiss"):
storage.delete_file(f"{index_path}/index.faiss")
if storage.file_exists(f"{index_path}/index.pkl"):
storage.delete_file(f"{index_path}/index.pkl")
else:
vectorstore = VectorCreator.create_vectorstore(
settings.VECTOR_STORE, source_id=str(doc["_id"])
)
vectorstore.delete_index()
if "file_path" in doc and doc["file_path"]:
file_path = doc["file_path"]
if storage.is_directory(file_path):
files = storage.list_files(file_path)
for f in files:
storage.delete_file(f)
else:
storage.delete_file(file_path)
except FileNotFoundError:
pass
except Exception as err:
current_app.logger.error(
f"Error deleting old indexes: {err}", exc_info=True
f"Error deleting files and indexes: {err}", exc_info=True
)
return make_response(jsonify({"success": False}), 400)
sources_collection.delete_one({"_id": ObjectId(source_id)})
return make_response(jsonify({"success": True}), 200)
@@ -546,146 +571,276 @@ class UploadFile(Resource):
# Create safe versions for filesystem operations
safe_user = safe_filename(user)
dir_name = safe_filename(job_name)
base_path = f"{settings.UPLOAD_FOLDER}/{safe_user}/{dir_name}"
try:
storage = StorageCreator.get_storage()
base_path = f"{settings.UPLOAD_FOLDER}/{safe_user}/{dir_name}"
if len(files) > 1:
temp_files = []
for file in files:
filename = safe_filename(file.filename)
temp_path = f"{base_path}/temp/{filename}"
storage.save_file(file, temp_path)
temp_files.append(temp_path)
print(f"Saved file: {filename}")
zip_filename = f"{dir_name}.zip"
zip_path = f"{base_path}/{zip_filename}"
zip_temp_path = None
def create_zip_archive(temp_paths, dir_name, storage):
import tempfile
for file in files:
original_filename = file.filename
safe_file = safe_filename(original_filename)
with tempfile.NamedTemporaryFile(
delete=False, suffix=".zip"
) as temp_zip_file:
zip_output_path = temp_zip_file.name
with tempfile.TemporaryDirectory() as stage_dir:
for path in temp_paths:
try:
file_data = storage.get_file(path)
with open(
os.path.join(stage_dir, os.path.basename(path)),
"wb",
) as f:
f.write(file_data.read())
except Exception as e:
current_app.logger.error(
f"Error processing file {path} for zipping: {e}",
exc_info=True,
)
if os.path.exists(zip_output_path):
os.remove(zip_output_path)
raise
with tempfile.TemporaryDirectory() as temp_dir:
temp_file_path = os.path.join(temp_dir, safe_file)
file.save(temp_file_path)
if zipfile.is_zipfile(temp_file_path):
try:
shutil.make_archive(
base_name=zip_output_path.replace(".zip", ""),
format="zip",
root_dir=stage_dir,
)
with zipfile.ZipFile(temp_file_path, 'r') as zip_ref:
zip_ref.extractall(path=temp_dir)
# Walk through extracted files and upload them
for root, _, files in os.walk(temp_dir):
for extracted_file in files:
if os.path.join(root, extracted_file) == temp_file_path:
continue
rel_path = os.path.relpath(os.path.join(root, extracted_file), temp_dir)
storage_path = f"{base_path}/{rel_path}"
with open(os.path.join(root, extracted_file), 'rb') as f:
storage.save_file(f, storage_path)
except Exception as e:
current_app.logger.error(
f"Error creating zip archive: {e}", exc_info=True
)
if os.path.exists(zip_output_path):
os.remove(zip_output_path)
raise
return zip_output_path
current_app.logger.error(f"Error extracting zip: {e}", exc_info=True)
# If zip extraction fails, save the original zip file
file_path = f"{base_path}/{safe_file}"
with open(temp_file_path, 'rb') as f:
storage.save_file(f, file_path)
else:
# For non-zip files, save directly
file_path = f"{base_path}/{safe_file}"
with open(temp_file_path, 'rb') as f:
storage.save_file(f, file_path)
try:
zip_temp_path = create_zip_archive(temp_files, dir_name, storage)
with open(zip_temp_path, "rb") as zip_file:
storage.save_file(zip_file, zip_path)
task = ingest.delay(
settings.UPLOAD_FOLDER,
[
".rst",
".md",
".pdf",
".txt",
".docx",
".csv",
".epub",
".html",
".mdx",
".json",
".xlsx",
".pptx",
".png",
".jpg",
".jpeg",
],
job_name,
zip_filename,
user,
dir_name,
safe_user,
)
finally:
# Clean up temporary files
for temp_path in temp_files:
try:
storage.delete_file(temp_path)
except Exception as e:
current_app.logger.error(
f"Error deleting temporary file {temp_path}: {e}",
exc_info=True,
)
# Clean up the zip file if it was created
if zip_temp_path and os.path.exists(zip_temp_path):
os.remove(zip_temp_path)
else: # Keep this else block for single file upload
# For single file
file = files[0]
filename = safe_filename(file.filename)
file_path = f"{base_path}/{filename}"
storage.save_file(file, file_path)
task = ingest.delay(
settings.UPLOAD_FOLDER,
[
".rst",
".md",
".pdf",
".txt",
".docx",
".csv",
".epub",
".html",
".mdx",
".json",
".xlsx",
".pptx",
".png",
".jpg",
".jpeg",
],
job_name,
filename, # Corrected variable for single-file case
user,
dir_name,
safe_user,
)
task = ingest.delay(
settings.UPLOAD_FOLDER,
[
".rst", ".md", ".pdf", ".txt", ".docx", ".csv", ".epub",
".html", ".mdx", ".json", ".xlsx", ".pptx", ".png",
".jpg", ".jpeg",
],
job_name,
user,
file_path=base_path,
filename=dir_name
)
except Exception as err:
current_app.logger.error(f"Error uploading file: {err}", exc_info=True)
return make_response(jsonify({"success": False}), 400)
return make_response(jsonify({"success": True, "task_id": task.id}), 200)
@user_ns.route("/api/manage_source_files")
class ManageSourceFiles(Resource):
@api.expect(
api.model(
"ManageSourceFilesModel",
{
"source_id": fields.String(required=True, description="Source ID to modify"),
"operation": fields.String(required=True, description="Operation: 'add', 'remove', or 'remove_directory'"),
"file_paths": fields.List(fields.String, required=False, description="File paths to remove (for remove operation)"),
"directory_path": fields.String(required=False, description="Directory path to remove (for remove_directory operation)"),
"file": fields.Raw(required=False, description="Files to add (for add operation)"),
"parent_dir": fields.String(required=False, description="Parent directory path relative to source root"),
},
)
)
@api.doc(
description="Add files, remove files, or remove directories from an existing source",
)
def post(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False, "message": "Unauthorized"}), 401)
user = decoded_token.get("sub")
source_id = request.form.get("source_id")
operation = request.form.get("operation")
if not source_id or not operation:
return make_response(
jsonify({"success": False, "message": "source_id and operation are required"}), 400
)
if operation not in ["add", "remove", "remove_directory"]:
return make_response(
jsonify({"success": False, "message": "operation must be 'add', 'remove', or 'remove_directory'"}), 400
)
try:
ObjectId(source_id)
except Exception:
return make_response(
jsonify({"success": False, "message": "Invalid source ID format"}), 400
)
try:
source = sources_collection.find_one({"_id": ObjectId(source_id), "user": user})
if not source:
return make_response(
jsonify({"success": False, "message": "Source not found or access denied"}), 404
)
except Exception as err:
current_app.logger.error(f"Error finding source: {err}", exc_info=True)
return make_response(jsonify({"success": False, "message": "Database error"}), 500)
try:
storage = StorageCreator.get_storage()
source_file_path = source.get("file_path", "")
parent_dir = request.form.get("parent_dir", "")
if parent_dir and (parent_dir.startswith("/") or ".." in parent_dir):
return make_response(
jsonify({"success": False, "message": "Invalid parent directory path"}), 400
)
if operation == "add":
files = request.files.getlist("file")
if not files or all(file.filename == "" for file in files):
return make_response(
jsonify({"success": False, "message": "No files provided for add operation"}), 400
)
added_files = []
target_dir = source_file_path
if parent_dir:
target_dir = f"{source_file_path}/{parent_dir}"
for file in files:
if file.filename:
safe_filename_str = safe_filename(file.filename)
file_path = f"{target_dir}/{safe_filename_str}"
# Save file to storage
storage.save_file(file, file_path)
added_files.append(safe_filename_str)
# Trigger re-ingestion pipeline
from application.api.user.tasks import reingest_source_task
task = reingest_source_task.delay(source_id=source_id, user=user)
return make_response(jsonify({
"success": True,
"message": f"Added {len(added_files)} files",
"added_files": added_files,
"parent_dir": parent_dir,
"reingest_task_id": task.id
}), 200)
elif operation == "remove":
file_paths_str = request.form.get("file_paths")
if not file_paths_str:
return make_response(
jsonify({"success": False, "message": "file_paths required for remove operation"}), 400
)
try:
file_paths = json.loads(file_paths_str) if isinstance(file_paths_str, str) else file_paths_str
except Exception:
return make_response(
jsonify({"success": False, "message": "Invalid file_paths format"}), 400
)
# Remove files from storage and directory structure
removed_files = []
for file_path in file_paths:
full_path = f"{source_file_path}/{file_path}"
# Remove from storage
if storage.file_exists(full_path):
storage.delete_file(full_path)
removed_files.append(file_path)
# Trigger re-ingestion pipeline
from application.api.user.tasks import reingest_source_task
task = reingest_source_task.delay(source_id=source_id, user=user)
return make_response(jsonify({
"success": True,
"message": f"Removed {len(removed_files)} files",
"removed_files": removed_files,
"reingest_task_id": task.id
}), 200)
elif operation == "remove_directory":
directory_path = request.form.get("directory_path")
if not directory_path:
return make_response(
jsonify({"success": False, "message": "directory_path required for remove_directory operation"}), 400
)
# Validate directory path (prevent path traversal)
if directory_path.startswith("/") or ".." in directory_path:
current_app.logger.warning(
f"Invalid directory path attempted for removal. "
f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}"
)
return make_response(
jsonify({"success": False, "message": "Invalid directory path"}), 400
)
full_directory_path = f"{source_file_path}/{directory_path}" if directory_path else source_file_path
if not storage.is_directory(full_directory_path):
current_app.logger.warning(
f"Directory not found or is not a directory for removal. "
f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
f"Full path: {full_directory_path}"
)
return make_response(
jsonify({"success": False, "message": "Directory not found or is not a directory"}), 404
)
success = storage.remove_directory(full_directory_path)
if not success:
current_app.logger.error(
f"Failed to remove directory from storage. "
f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
f"Full path: {full_directory_path}"
)
return make_response(
jsonify({"success": False, "message": "Failed to remove directory"}), 500
)
current_app.logger.info(
f"Successfully removed directory. "
f"User: {user}, Source ID: {source_id}, Directory path: {directory_path}, "
f"Full path: {full_directory_path}"
)
# Trigger re-ingestion pipeline
from application.api.user.tasks import reingest_source_task
task = reingest_source_task.delay(source_id=source_id, user=user)
return make_response(jsonify({
"success": True,
"message": f"Successfully removed directory: {directory_path}",
"removed_directory": directory_path,
"reingest_task_id": task.id
}), 200)
except Exception as err:
error_context = f"operation={operation}, user={user}, source_id={source_id}"
if operation == "remove_directory":
directory_path = request.form.get("directory_path", "")
error_context += f", directory_path={directory_path}"
elif operation == "remove":
file_paths_str = request.form.get("file_paths", "")
error_context += f", file_paths={file_paths_str}"
elif operation == "add":
parent_dir = request.form.get("parent_dir", "")
error_context += f", parent_dir={parent_dir}"
current_app.logger.error(f"Error managing source files: {err} ({error_context})", exc_info=True)
return make_response(jsonify({"success": False, "message": "Operation failed"}), 500)
@user_ns.route("/api/remote")
class UploadRemote(Resource):
@api.expect(
@@ -724,6 +879,42 @@ class UploadRemote(Resource):
source_data = config.get("url")
elif data["source"] == "reddit":
source_data = config
elif data["source"] in ConnectorCreator.get_supported_connectors():
session_token = config.get("session_token")
if not session_token:
return make_response(jsonify({
"success": False,
"error": f"Missing session_token in {data['source']} configuration"
}), 400)
# Process file_ids
file_ids = config.get("file_ids", [])
if isinstance(file_ids, str):
file_ids = [id.strip() for id in file_ids.split(',') if id.strip()]
elif not isinstance(file_ids, list):
file_ids = []
# Process folder_ids
folder_ids = config.get("folder_ids", [])
if isinstance(folder_ids, str):
folder_ids = [id.strip() for id in folder_ids.split(',') if id.strip()]
elif not isinstance(folder_ids, list):
folder_ids = []
config["file_ids"] = file_ids
config["folder_ids"] = folder_ids
task = ingest_connector_task.delay(
job_name=data["name"],
user=decoded_token.get("sub"),
source_type=data["source"],
session_token=session_token,
file_ids=file_ids,
folder_ids=folder_ids,
recursive=config.get("recursive", False),
retriever=config.get("retriever", "classic")
)
return make_response(jsonify({"success": True, "task_id": task.id}), 200)
task = ingest_remote.delay(
source_data=source_data,
job_name=data["name"],
@@ -831,6 +1022,8 @@ class PaginatedSources(Resource):
"tokens": doc.get("tokens", ""),
"retriever": doc.get("retriever", "classic"),
"syncFrequency": doc.get("sync_frequency", ""),
"isNested": bool(doc.get("directory_structure")),
"type": doc.get("type", "file")
}
paginated_docs.append(doc_data)
response = {
@@ -878,6 +1071,8 @@ class CombinedJson(Resource):
"tokens": index.get("tokens", ""),
"retriever": index.get("retriever", "classic"),
"syncFrequency": index.get("sync_frequency", ""),
"is_nested": bool(index.get("directory_structure")),
"type": index.get("type", "file") # Add type field with default "file"
}
)
except Exception as err:
@@ -1124,6 +1319,7 @@ class GetAgent(Resource):
"tool_details": resolve_tool_details(agent.get("tools", [])),
"agent_type": agent.get("agent_type", ""),
"status": agent.get("status", ""),
"json_schema": agent.get("json_schema"),
"created_at": agent.get("createdAt", ""),
"updated_at": agent.get("updatedAt", ""),
"last_used_at": agent.get("lastUsedAt", ""),
@@ -1178,6 +1374,7 @@ class GetAgents(Resource):
"tool_details": resolve_tool_details(agent.get("tools", [])),
"agent_type": agent.get("agent_type", ""),
"status": agent.get("status", ""),
"json_schema": agent.get("json_schema"),
"created_at": agent.get("createdAt", ""),
"updated_at": agent.get("updatedAt", ""),
"last_used_at": agent.get("lastUsedAt", ""),
@@ -1223,6 +1420,9 @@ class CreateAgent(Resource):
"status": fields.String(
required=True, description="Status of the agent (draft or published)"
),
"json_schema": fields.Raw(
required=False, description="JSON schema for enforcing structured output format"
),
},
)
@@ -1241,8 +1441,36 @@ class CreateAgent(Resource):
data["tools"] = json.loads(data["tools"])
except json.JSONDecodeError:
data["tools"] = []
if "json_schema" in data:
try:
data["json_schema"] = json.loads(data["json_schema"])
except json.JSONDecodeError:
data["json_schema"] = None
print(f"Received data: {data}")
# Validate JSON schema if provided
if data.get("json_schema"):
try:
# Basic validation - ensure it's a valid JSON structure
json_schema = data.get("json_schema")
if not isinstance(json_schema, dict):
return make_response(
jsonify({"success": False, "message": "JSON schema must be a valid JSON object"}),
400
)
# Validate that it has either a 'schema' property or is itself a schema
if "schema" not in json_schema and "type" not in json_schema:
return make_response(
jsonify({"success": False, "message": "JSON schema must contain either a 'schema' property or be a valid JSON schema with 'type' property"}),
400
)
except Exception as e:
return make_response(
jsonify({"success": False, "message": f"Invalid JSON schema: {str(e)}"}),
400
)
if data.get("status") not in ["draft", "published"]:
return make_response(
jsonify(
@@ -1299,6 +1527,7 @@ class CreateAgent(Resource):
"tools": data.get("tools", []),
"agent_type": data.get("agent_type", ""),
"status": data.get("status"),
"json_schema": data.get("json_schema"),
"createdAt": datetime.datetime.now(datetime.timezone.utc),
"updatedAt": datetime.datetime.now(datetime.timezone.utc),
"lastUsedAt": None,
@@ -1339,6 +1568,9 @@ class UpdateAgent(Resource):
"status": fields.String(
required=True, description="Status of the agent (draft or published)"
),
"json_schema": fields.Raw(
required=False, description="JSON schema for enforcing structured output format"
),
},
)
@@ -1357,6 +1589,11 @@ class UpdateAgent(Resource):
data["tools"] = json.loads(data["tools"])
except json.JSONDecodeError:
data["tools"] = []
if "json_schema" in data:
try:
data["json_schema"] = json.loads(data["json_schema"])
except json.JSONDecodeError:
data["json_schema"] = None
if not ObjectId.is_valid(agent_id):
return make_response(
@@ -1402,6 +1639,7 @@ class UpdateAgent(Resource):
"tools",
"agent_type",
"status",
"json_schema",
]
for field in allowed_fields:
@@ -1786,10 +2024,20 @@ class SharedAgent(Resource):
else ""
),
"description": shared_agent.get("description", ""),
"source": (
str(source_doc["_id"])
if isinstance(shared_agent.get("source"), DBRef)
and (source_doc := db.dereference(shared_agent.get("source")))
else ""
),
"chunks": shared_agent.get("chunks", "0"),
"retriever": shared_agent.get("retriever", "classic"),
"prompt_id": shared_agent.get("prompt_id", "default"),
"tools": shared_agent.get("tools", []),
"tool_details": resolve_tool_details(shared_agent.get("tools", [])),
"agent_type": shared_agent.get("agent_type", ""),
"status": shared_agent.get("status", ""),
"json_schema": shared_agent.get("json_schema"),
"created_at": shared_agent.get("createdAt", ""),
"updated_at": shared_agent.get("updatedAt", ""),
"shared": shared_agent.get("shared_publicly", False),
@@ -1867,6 +2115,7 @@ class SharedAgents(Resource):
"tool_details": resolve_tool_details(agent.get("tools", [])),
"agent_type": agent.get("agent_type", ""),
"status": agent.get("status", ""),
"json_schema": agent.get("json_schema"),
"created_at": agent.get("createdAt", ""),
"updated_at": agent.get("updatedAt", ""),
"pinned": str(agent["_id"]) in pinned_ids,
@@ -3322,8 +3571,14 @@ class DeleteTool(Resource):
@user_ns.route("/api/get_chunks")
class GetChunks(Resource):
@api.doc(
description="Retrieves all chunks associated with a document",
params={"id": "The document ID"},
description="Retrieves chunks from a document, optionally filtered by file path and search term",
params={
"id": "The document ID",
"page": "Page number for pagination",
"per_page": "Number of chunks per page",
"path": "Optional: Filter chunks by relative file path",
"search": "Optional: Search term to filter chunks by title or content"
},
)
def get(self):
decoded_token = request.decoded_token
@@ -3333,6 +3588,8 @@ class GetChunks(Resource):
doc_id = request.args.get("id")
page = int(request.args.get("page", 1))
per_page = int(request.args.get("per_page", 10))
path = request.args.get("path")
search_term = request.args.get("search", "").strip().lower()
if not ObjectId.is_valid(doc_id):
return make_response(jsonify({"error": "Invalid doc_id"}), 400)
@@ -3344,6 +3601,30 @@ class GetChunks(Resource):
try:
store = get_vector_store(doc_id)
chunks = store.get_chunks()
filtered_chunks = []
for chunk in chunks:
metadata = chunk.get("metadata", {})
# Filter by path if provided
if path:
chunk_source = metadata.get("source", "")
# Check if the chunk's source matches the requested path
if not chunk_source or not chunk_source.endswith(path):
continue
# Filter by search term if provided
if search_term:
text_match = search_term in chunk.get("text", "").lower()
title_match = search_term in metadata.get("title", "").lower()
if not (text_match or title_match):
continue
filtered_chunks.append(chunk)
chunks = filtered_chunks
total_chunks = len(chunks)
start = (page - 1) * per_page
end = start + per_page
@@ -3356,6 +3637,8 @@ class GetChunks(Resource):
"per_page": per_page,
"total": total_chunks,
"chunks": paginated_chunks,
"path": path if path else None,
"search": search_term if search_term else None
}
),
200,
@@ -3364,7 +3647,6 @@ class GetChunks(Resource):
current_app.logger.error(f"Error getting chunks: {e}", exc_info=True)
return make_response(jsonify({"success": False}), 500)
@user_ns.route("/api/add_chunk")
class AddChunk(Resource):
@api.expect(
@@ -3396,6 +3678,8 @@ class AddChunk(Resource):
doc_id = data.get("id")
text = data.get("text")
metadata = data.get("metadata", {})
token_count = num_tokens_from_string(text)
metadata["token_count"] = token_count
if not ObjectId.is_valid(doc_id):
return make_response(jsonify({"error": "Invalid doc_id"}), 400)
@@ -3492,6 +3776,12 @@ class UpdateChunk(Resource):
text = data.get("text")
metadata = data.get("metadata")
if text is not None:
token_count = num_tokens_from_string(text)
if metadata is None:
metadata = {}
metadata["token_count"] = token_count
if not ObjectId.is_valid(doc_id):
return make_response(jsonify({"error": "Invalid doc_id"}), 400)
doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
@@ -3501,31 +3791,45 @@ class UpdateChunk(Resource):
)
try:
store = get_vector_store(doc_id)
chunks = store.get_chunks()
existing_chunk = next((c for c in chunks if c["doc_id"] == chunk_id), None)
if not existing_chunk:
return make_response(jsonify({"error": "Chunk not found"}), 404)
deleted = store.delete_chunk(chunk_id)
if not deleted:
return make_response(
jsonify({"error": "Failed to delete existing chunk"}), 500
)
new_text = text if text is not None else existing_chunk["text"]
new_metadata = (
metadata if metadata is not None else existing_chunk["metadata"]
)
new_chunk_id = store.add_chunk(new_text, new_metadata)
if metadata is not None:
new_metadata = existing_chunk["metadata"].copy()
new_metadata.update(metadata)
else:
new_metadata = existing_chunk["metadata"].copy()
return make_response(
jsonify(
{
"message": "Chunk updated successfully",
"new_chunk_id": new_chunk_id,
}
),
200,
)
if text is not None:
new_metadata["token_count"] = num_tokens_from_string(new_text)
try:
new_chunk_id = store.add_chunk(new_text, new_metadata)
deleted = store.delete_chunk(chunk_id)
if not deleted:
current_app.logger.warning(f"Failed to delete old chunk {chunk_id}, but new chunk {new_chunk_id} was created")
return make_response(
jsonify(
{
"message": "Chunk updated successfully",
"chunk_id": new_chunk_id,
"original_chunk_id": chunk_id,
}
),
200,
)
except Exception as add_error:
current_app.logger.error(f"Failed to add updated chunk: {add_error}")
return make_response(
jsonify({"error": "Failed to update chunk - addition failed"}), 500
)
except Exception as e:
current_app.logger.error(f"Error updating chunk: {e}", exc_info=True)
return make_response(jsonify({"success": False}), 500)
@@ -3538,14 +3842,18 @@ class StoreAttachment(Resource):
"AttachmentModel",
{
"file": fields.Raw(required=True, description="File to upload"),
"api_key": fields.String(
required=False, description="API key (optional)"
),
},
)
)
@api.doc(description="Stores a single attachment without vectorization or training")
@api.doc(
description="Stores a single attachment without vectorization or training. Supports user or API key authentication."
)
def post(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
decoded_token = getattr(request, "decoded_token", None)
api_key = request.form.get("api_key") or request.args.get("api_key")
file = request.files.get("file")
if not file or file.filename == "":
@@ -3553,11 +3861,25 @@ class StoreAttachment(Resource):
jsonify({"status": "error", "message": "Missing file"}),
400,
)
user = safe_filename(decoded_token.get("sub"))
user = None
if decoded_token:
user = safe_filename(decoded_token.get("sub"))
elif api_key:
agent = agents_collection.find_one({"key": api_key})
if not agent:
return make_response(
jsonify({"success": False, "message": "Invalid API key"}), 401
)
user = safe_filename(agent.get("user"))
else:
return make_response(
jsonify({"success": False, "message": "Authentication required"}), 401
)
try:
attachment_id = ObjectId()
original_filename = secure_filename(os.path.basename(file.filename))
original_filename = safe_filename(os.path.basename(file.filename))
relative_path = f"{settings.UPLOAD_FOLDER}/{user}/attachments/{str(attachment_id)}/{original_filename}"
metadata = storage.save_file(file, relative_path)
@@ -3611,3 +3933,66 @@ class ServeImage(Resource):
return make_response(
jsonify({"success": False, "message": "Error retrieving image"}), 500
)
@user_ns.route("/api/directory_structure")
class DirectoryStructure(Resource):
@api.doc(
description="Get the directory structure for a document",
params={"id": "The document ID"},
)
def get(self):
decoded_token = request.decoded_token
if not decoded_token:
return make_response(jsonify({"success": False}), 401)
user = decoded_token.get("sub")
doc_id = request.args.get("id")
if not doc_id:
return make_response(
jsonify({"error": "Document ID is required"}), 400
)
if not ObjectId.is_valid(doc_id):
return make_response(jsonify({"error": "Invalid document ID"}), 400)
try:
doc = sources_collection.find_one({"_id": ObjectId(doc_id), "user": user})
if not doc:
return make_response(
jsonify({"error": "Document not found or access denied"}), 404
)
directory_structure = doc.get("directory_structure", {})
base_path = doc.get("file_path", "")
provider = None
remote_data = doc.get("remote_data")
try:
if isinstance(remote_data, str) and remote_data:
remote_data_obj = json.loads(remote_data)
provider = remote_data_obj.get("provider")
except Exception as e:
current_app.logger.warning(
f"Failed to parse remote_data for doc {doc_id}: {e}")
return make_response(
jsonify({
"success": True,
"directory_structure": directory_structure,
"base_path": base_path,
"provider": provider,
}), 200
)
except Exception as e:
current_app.logger.error(
f"Error retrieving directory structure: {e}", exc_info=True
)
return make_response(
jsonify({"success": False, "error": str(e)}), 500
)

View File

@@ -11,8 +11,8 @@ from application.worker import (
@celery.task(bind=True)
def ingest(self, directory, formats, job_name, filename, user, dir_name, user_dir):
resp = ingest_worker(self, directory, formats, job_name, filename, user, dir_name, user_dir)
def ingest(self, directory, formats, job_name, user, file_path, filename):
resp = ingest_worker(self, directory, formats, job_name, file_path, filename, user)
return resp
@@ -22,6 +22,13 @@ def ingest_remote(self, source_data, job_name, user, loader):
return resp
@celery.task(bind=True)
def reingest_source_task(self, source_id, user):
from application.worker import reingest_source_worker
resp = reingest_source_worker(self, source_id, user)
return resp
@celery.task(bind=True)
def schedule_syncs(self, frequency):
resp = sync_worker(self, frequency)
@@ -40,6 +47,39 @@ def process_agent_webhook(self, agent_id, payload):
return resp
@celery.task(bind=True)
def ingest_connector_task(
self,
job_name,
user,
source_type,
session_token=None,
file_ids=None,
folder_ids=None,
recursive=True,
retriever="classic",
operation_mode="upload",
doc_id=None,
sync_frequency="never"
):
from application.worker import ingest_connector
resp = ingest_connector(
self,
job_name,
user,
source_type,
session_token=session_token,
file_ids=file_ids,
folder_ids=folder_ids,
recursive=recursive,
retriever=retriever,
operation_mode=operation_mode,
doc_id=doc_id,
sync_frequency=sync_frequency
)
return resp
@celery.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
sender.add_periodic_task(

View File

@@ -12,25 +12,26 @@ from application.core.logging_config import setup_logging
setup_logging()
from application.api.answer.routes import answer # noqa: E402
from application.api import api # noqa: E402
from application.api.answer import answer # noqa: E402
from application.api.internal.routes import internal # noqa: E402
from application.api.user.routes import user # noqa: E402
from application.api.connector.routes import connector # noqa: E402
from application.celery_init import celery # noqa: E402
from application.core.settings import settings # noqa: E402
from application.extensions import api # noqa: E402
if platform.system() == "Windows":
import pathlib
pathlib.PosixPath = pathlib.WindowsPath
dotenv.load_dotenv()
app = Flask(__name__)
app.register_blueprint(user)
app.register_blueprint(answer)
app.register_blueprint(internal)
app.register_blueprint(connector)
app.config.update(
UPLOAD_FOLDER="inputs",
CELERY_BROKER_URL=settings.CELERY_BROKER_URL,
@@ -52,7 +53,6 @@ if settings.AUTH_TYPE in ("simple_jwt", "session_jwt") and not settings.JWT_SECR
settings.JWT_SECRET_KEY = new_key
except Exception as e:
raise RuntimeError(f"Failed to setup JWT_SECRET_KEY: {e}")
SIMPLE_JWT_TOKEN = None
if settings.AUTH_TYPE == "simple_jwt":
payload = {"sub": "local"}
@@ -92,7 +92,6 @@ def generate_token():
def authenticate_request():
if request.method == "OPTIONS":
return "", 200
decoded_token = handle_auth(request)
if not decoded_token:
request.decoded_token = None

View File

@@ -10,7 +10,7 @@ current_dir = os.path.dirname(
class Settings(BaseSettings):
AUTH_TYPE: Optional[str] = None
AUTH_TYPE: Optional[str] = None # simple_jwt, session_jwt, or None
LLM_PROVIDER: str = "docsgpt"
LLM_NAME: Optional[str] = (
None # if LLM_PROVIDER is openai, LLM_NAME can be gpt-4 or gpt-3.5-turbo
@@ -30,6 +30,7 @@ class Settings(BaseSettings):
}
UPLOAD_FOLDER: str = "inputs"
PARSE_PDF_AS_IMAGE: bool = False
PARSE_IMAGE_REMOTE: bool = False
VECTOR_STORE: str = (
"faiss" # "faiss" or "elasticsearch" or "qdrant" or "milvus" or "lancedb"
)
@@ -39,6 +40,13 @@ class Settings(BaseSettings):
FALLBACK_LLM_NAME: Optional[str] = None # model name for fallback llm
FALLBACK_LLM_API_KEY: Optional[str] = None # api key for fallback llm
# Google Drive integration
GOOGLE_CLIENT_ID: Optional[str] = None # Replace with your actual Google OAuth client ID
GOOGLE_CLIENT_SECRET: Optional[str] = None# Replace with your actual Google OAuth client secret
CONNECTOR_REDIRECT_BASE_URI: Optional[str] = "http://127.0.0.1:7091/api/connectors/callback"
##append ?provider={provider_name} in your Provider console like http://127.0.0.1:7091/api/connectors/callback?provider=google_drive
# LLM Cache
CACHE_REDIS_URL: str = "redis://localhost:6379/2"
@@ -88,7 +96,9 @@ class Settings(BaseSettings):
QDRANT_HOST: Optional[str] = None
QDRANT_PATH: Optional[str] = None
QDRANT_DISTANCE_FUNC: str = "Cosine"
# PGVector vectorstore config
PGVECTOR_CONNECTION_STRING: Optional[str] = None
# Milvus vectorstore config
MILVUS_COLLECTION_NAME: Optional[str] = "docsgpt"
MILVUS_URI: Optional[str] = "./milvus_local.db" # milvus lite version as default

View File

@@ -1,7 +0,0 @@
from flask_restx import Api
api = Api(
version="1.0",
title="DocsGPT API",
description="API for DocsGPT",
)

View File

@@ -120,6 +120,20 @@ class BaseLLM(ABC):
def _supports_tools(self):
raise NotImplementedError("Subclass must implement _supports_tools method")
def supports_structured_output(self):
"""Check if the LLM supports structured output/JSON schema enforcement"""
return hasattr(self, "_supports_structured_output") and callable(
getattr(self, "_supports_structured_output")
)
def _supports_structured_output(self):
return False
def prepare_structured_output_format(self, json_schema):
"""Prepare structured output format specific to the LLM provider"""
_ = json_schema
return None
def get_supported_attachment_types(self):
"""
Return a list of MIME types supported by this LLM for file uploads.
@@ -127,4 +141,4 @@ class BaseLLM(ABC):
Returns:
list: List of supported MIME types
"""
return [] # Default: no attachments supported
return []

View File

@@ -1,11 +1,13 @@
import json
import logging
from google import genai
from google.genai import types
import logging
import json
from application.core.settings import settings
from application.llm.base import BaseLLM
from application.storage.storage_creator import StorageCreator
from application.core.settings import settings
class GoogleLLM(BaseLLM):
@@ -24,12 +26,12 @@ class GoogleLLM(BaseLLM):
list: List of supported MIME types
"""
return [
'application/pdf',
'image/png',
'image/jpeg',
'image/jpg',
'image/webp',
'image/gif'
"application/pdf",
"image/png",
"image/jpeg",
"image/jpg",
"image/webp",
"image/gif",
]
def prepare_messages_with_attachments(self, messages, attachments=None):
@@ -70,26 +72,30 @@ class GoogleLLM(BaseLLM):
files = []
for attachment in attachments:
mime_type = attachment.get('mime_type')
mime_type = attachment.get("mime_type")
if mime_type in self.get_supported_attachment_types():
try:
file_uri = self._upload_file_to_google(attachment)
logging.info(f"GoogleLLM: Successfully uploaded file, got URI: {file_uri}")
logging.info(
f"GoogleLLM: Successfully uploaded file, got URI: {file_uri}"
)
files.append({"file_uri": file_uri, "mime_type": mime_type})
except Exception as e:
logging.error(f"GoogleLLM: Error uploading file: {e}", exc_info=True)
if 'content' in attachment:
prepared_messages[user_message_index]["content"].append({
"type": "text",
"text": f"[File could not be processed: {attachment.get('path', 'unknown')}]"
})
logging.error(
f"GoogleLLM: Error uploading file: {e}", exc_info=True
)
if "content" in attachment:
prepared_messages[user_message_index]["content"].append(
{
"type": "text",
"text": f"[File could not be processed: {attachment.get('path', 'unknown')}]",
}
)
if files:
logging.info(f"GoogleLLM: Adding {len(files)} files to message")
prepared_messages[user_message_index]["content"].append({
"files": files
})
prepared_messages[user_message_index]["content"].append({"files": files})
return prepared_messages
@@ -103,10 +109,10 @@ class GoogleLLM(BaseLLM):
Returns:
str: Google AI file URI for the uploaded file.
"""
if 'google_file_uri' in attachment:
return attachment['google_file_uri']
if "google_file_uri" in attachment:
return attachment["google_file_uri"]
file_path = attachment.get('path')
file_path = attachment.get("path")
if not file_path:
raise ValueError("No file path provided in attachment")
@@ -116,17 +122,19 @@ class GoogleLLM(BaseLLM):
try:
file_uri = self.storage.process_file(
file_path,
lambda local_path, **kwargs: self.client.files.upload(file=local_path).uri
lambda local_path, **kwargs: self.client.files.upload(
file=local_path
).uri,
)
from application.core.mongo_db import MongoDB
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
attachments_collection = db["attachments"]
if '_id' in attachment:
if "_id" in attachment:
attachments_collection.update_one(
{"_id": attachment['_id']},
{"$set": {"google_file_uri": file_uri}}
{"_id": attachment["_id"]}, {"$set": {"google_file_uri": file_uri}}
)
return file_uri
@@ -166,13 +174,13 @@ class GoogleLLM(BaseLLM):
)
)
elif "files" in item:
for file_data in item["files"]:
parts.append(
types.Part.from_uri(
file_uri=file_data["file_uri"],
mime_type=file_data["mime_type"]
)
for file_data in item["files"]:
parts.append(
types.Part.from_uri(
file_uri=file_data["file_uri"],
mime_type=file_data["mime_type"],
)
)
else:
raise ValueError(
f"Unexpected content dictionary format:{item}"
@@ -231,6 +239,7 @@ class GoogleLLM(BaseLLM):
stream=False,
tools=None,
formatting="openai",
response_schema=None,
**kwargs,
):
client = genai.Client(api_key=self.api_key)
@@ -244,16 +253,21 @@ class GoogleLLM(BaseLLM):
if tools:
cleaned_tools = self._clean_tools_format(tools)
config.tools = cleaned_tools
response = client.models.generate_content(
model=model,
contents=messages,
config=config,
)
# Add response schema for structured output if provided
if response_schema:
config.response_schema = response_schema
config.response_mime_type = "application/json"
response = client.models.generate_content(
model=model,
contents=messages,
config=config,
)
if tools:
return response
else:
response = client.models.generate_content(
model=model, contents=messages, config=config
)
return response.text
def _raw_gen_stream(
@@ -264,6 +278,7 @@ class GoogleLLM(BaseLLM):
stream=True,
tools=None,
formatting="openai",
response_schema=None,
**kwargs,
):
client = genai.Client(api_key=self.api_key)
@@ -278,17 +293,24 @@ class GoogleLLM(BaseLLM):
cleaned_tools = self._clean_tools_format(tools)
config.tools = cleaned_tools
# Add response schema for structured output if provided
if response_schema:
config.response_schema = response_schema
config.response_mime_type = "application/json"
# Check if we have both tools and file attachments
has_attachments = False
for message in messages:
for part in message.parts:
if hasattr(part, 'file_data') and part.file_data is not None:
if hasattr(part, "file_data") and part.file_data is not None:
has_attachments = True
break
if has_attachments:
break
logging.info(f"GoogleLLM: Starting stream generation. Model: {model}, Messages: {json.dumps(messages, default=str)}, Has attachments: {has_attachments}")
logging.info(
f"GoogleLLM: Starting stream generation. Model: {model}, Messages: {json.dumps(messages, default=str)}, Has attachments: {has_attachments}"
)
response = client.models.generate_content_stream(
model=model,
@@ -296,7 +318,6 @@ class GoogleLLM(BaseLLM):
config=config,
)
for chunk in response:
if hasattr(chunk, "candidates") and chunk.candidates:
for candidate in chunk.candidates:
@@ -311,3 +332,75 @@ class GoogleLLM(BaseLLM):
def _supports_tools(self):
return True
def _supports_structured_output(self):
return True
def prepare_structured_output_format(self, json_schema):
if not json_schema:
return None
type_map = {
"object": "OBJECT",
"array": "ARRAY",
"string": "STRING",
"integer": "INTEGER",
"number": "NUMBER",
"boolean": "BOOLEAN",
}
def convert(schema):
if not isinstance(schema, dict):
return schema
result = {}
schema_type = schema.get("type")
if schema_type:
result["type"] = type_map.get(schema_type.lower(), schema_type.upper())
for key in [
"description",
"nullable",
"enum",
"minItems",
"maxItems",
"required",
"propertyOrdering",
]:
if key in schema:
result[key] = schema[key]
if "format" in schema:
format_value = schema["format"]
if schema_type == "string":
if format_value == "date":
result["format"] = "date-time"
elif format_value in ["enum", "date-time"]:
result["format"] = format_value
else:
result["format"] = format_value
if "properties" in schema:
result["properties"] = {
k: convert(v) for k, v in schema["properties"].items()
}
if "propertyOrdering" not in result and result.get("type") == "OBJECT":
result["propertyOrdering"] = list(result["properties"].keys())
if "items" in schema:
result["items"] = convert(schema["items"])
for field in ["anyOf", "oneOf", "allOf"]:
if field in schema:
result[field] = [convert(s) for s in schema[field]]
return result
try:
return convert(json_schema)
except Exception as e:
logging.error(
f"Error preparing structured output format for Google: {e}",
exc_info=True,
)
return None

View File

@@ -1,5 +1,5 @@
import json
import base64
import json
import logging
from application.core.settings import settings
@@ -13,7 +13,10 @@ class OpenAILLM(BaseLLM):
from openai import OpenAI
super().__init__(*args, **kwargs)
if isinstance(settings.OPENAI_BASE_URL, str) and settings.OPENAI_BASE_URL.strip():
if (
isinstance(settings.OPENAI_BASE_URL, str)
and settings.OPENAI_BASE_URL.strip()
):
self.client = OpenAI(api_key=api_key, base_url=settings.OPENAI_BASE_URL)
else:
DEFAULT_OPENAI_API_BASE = "https://api.openai.com/v1"
@@ -73,14 +76,30 @@ class OpenAILLM(BaseLLM):
elif isinstance(item, dict):
content_parts = []
if "text" in item:
content_parts.append({"type": "text", "text": item["text"]})
elif "type" in item and item["type"] == "text" and "text" in item:
content_parts.append(
{"type": "text", "text": item["text"]}
)
elif (
"type" in item
and item["type"] == "text"
and "text" in item
):
content_parts.append(item)
elif "type" in item and item["type"] == "file" and "file" in item:
elif (
"type" in item
and item["type"] == "file"
and "file" in item
):
content_parts.append(item)
elif "type" in item and item["type"] == "image_url" and "image_url" in item:
elif (
"type" in item
and item["type"] == "image_url"
and "image_url" in item
):
content_parts.append(item)
cleaned_messages.append({"role": role, "content": content_parts})
cleaned_messages.append(
{"role": role, "content": content_parts}
)
else:
raise ValueError(
f"Unexpected content dictionary format: {item}"
@@ -98,22 +117,29 @@ class OpenAILLM(BaseLLM):
stream=False,
tools=None,
engine=settings.AZURE_DEPLOYMENT_NAME,
response_format=None,
**kwargs,
):
messages = self._clean_messages_openai(messages)
request_params = {
"model": model,
"messages": messages,
"stream": stream,
**kwargs,
}
if tools:
request_params["tools"] = tools
if response_format:
request_params["response_format"] = response_format
response = self.client.chat.completions.create(**request_params)
if tools:
response = self.client.chat.completions.create(
model=model,
messages=messages,
stream=stream,
tools=tools,
**kwargs,
)
return response.choices[0]
else:
response = self.client.chat.completions.create(
model=model, messages=messages, stream=stream, **kwargs
)
return response.choices[0].message.content
def _raw_gen_stream(
@@ -124,24 +150,32 @@ class OpenAILLM(BaseLLM):
stream=True,
tools=None,
engine=settings.AZURE_DEPLOYMENT_NAME,
response_format=None,
**kwargs,
):
messages = self._clean_messages_openai(messages)
request_params = {
"model": model,
"messages": messages,
"stream": stream,
**kwargs,
}
if tools:
response = self.client.chat.completions.create(
model=model,
messages=messages,
stream=stream,
tools=tools,
**kwargs,
)
else:
response = self.client.chat.completions.create(
model=model, messages=messages, stream=stream, **kwargs
)
request_params["tools"] = tools
if response_format:
request_params["response_format"] = response_format
response = self.client.chat.completions.create(**request_params)
for line in response:
if len(line.choices) > 0 and line.choices[0].delta.content is not None and len(line.choices[0].delta.content) > 0:
if (
len(line.choices) > 0
and line.choices[0].delta.content is not None
and len(line.choices[0].delta.content) > 0
):
yield line.choices[0].delta.content
elif len(line.choices) > 0:
yield line.choices[0]
@@ -149,6 +183,66 @@ class OpenAILLM(BaseLLM):
def _supports_tools(self):
return True
def _supports_structured_output(self):
return True
def prepare_structured_output_format(self, json_schema):
if not json_schema:
return None
try:
def add_additional_properties_false(schema_obj):
if isinstance(schema_obj, dict):
schema_copy = schema_obj.copy()
if schema_copy.get("type") == "object":
schema_copy["additionalProperties"] = False
# Ensure 'required' includes all properties for OpenAI strict mode
if "properties" in schema_copy:
schema_copy["required"] = list(
schema_copy["properties"].keys()
)
for key, value in schema_copy.items():
if key == "properties" and isinstance(value, dict):
schema_copy[key] = {
prop_name: add_additional_properties_false(prop_schema)
for prop_name, prop_schema in value.items()
}
elif key == "items" and isinstance(value, dict):
schema_copy[key] = add_additional_properties_false(value)
elif key in ["anyOf", "oneOf", "allOf"] and isinstance(
value, list
):
schema_copy[key] = [
add_additional_properties_false(sub_schema)
for sub_schema in value
]
return schema_copy
return schema_obj
processed_schema = add_additional_properties_false(json_schema)
result = {
"type": "json_schema",
"json_schema": {
"name": processed_schema.get("name", "response"),
"description": processed_schema.get(
"description", "Structured response"
),
"schema": processed_schema,
"strict": True,
},
}
return result
except Exception as e:
logging.error(f"Error preparing structured output format: {e}")
return None
def get_supported_attachment_types(self):
"""
Return a list of MIME types supported by OpenAI for file uploads.
@@ -157,12 +251,12 @@ class OpenAILLM(BaseLLM):
list: List of supported MIME types
"""
return [
'application/pdf',
'image/png',
'image/jpeg',
'image/jpg',
'image/webp',
'image/gif'
"application/pdf",
"image/png",
"image/jpeg",
"image/jpg",
"image/webp",
"image/gif",
]
def prepare_messages_with_attachments(self, messages, attachments=None):
@@ -202,39 +296,46 @@ class OpenAILLM(BaseLLM):
prepared_messages[user_message_index]["content"] = []
for attachment in attachments:
mime_type = attachment.get('mime_type')
mime_type = attachment.get("mime_type")
if mime_type and mime_type.startswith('image/'):
if mime_type and mime_type.startswith("image/"):
try:
base64_image = self._get_base64_image(attachment)
prepared_messages[user_message_index]["content"].append({
"type": "image_url",
"image_url": {
"url": f"data:{mime_type};base64,{base64_image}"
prepared_messages[user_message_index]["content"].append(
{
"type": "image_url",
"image_url": {
"url": f"data:{mime_type};base64,{base64_image}"
},
}
})
)
except Exception as e:
logging.error(f"Error processing image attachment: {e}", exc_info=True)
if 'content' in attachment:
prepared_messages[user_message_index]["content"].append({
"type": "text",
"text": f"[Image could not be processed: {attachment.get('path', 'unknown')}]"
})
logging.error(
f"Error processing image attachment: {e}", exc_info=True
)
if "content" in attachment:
prepared_messages[user_message_index]["content"].append(
{
"type": "text",
"text": f"[Image could not be processed: {attachment.get('path', 'unknown')}]",
}
)
# Handle PDFs using the file API
elif mime_type == 'application/pdf':
elif mime_type == "application/pdf":
try:
file_id = self._upload_file_to_openai(attachment)
prepared_messages[user_message_index]["content"].append({
"type": "file",
"file": {"file_id": file_id}
})
prepared_messages[user_message_index]["content"].append(
{"type": "file", "file": {"file_id": file_id}}
)
except Exception as e:
logging.error(f"Error uploading PDF to OpenAI: {e}", exc_info=True)
if 'content' in attachment:
prepared_messages[user_message_index]["content"].append({
"type": "text",
"text": f"File content:\n\n{attachment['content']}"
})
if "content" in attachment:
prepared_messages[user_message_index]["content"].append(
{
"type": "text",
"text": f"File content:\n\n{attachment['content']}",
}
)
return prepared_messages
@@ -248,13 +349,13 @@ class OpenAILLM(BaseLLM):
Returns:
str: Base64-encoded image data.
"""
file_path = attachment.get('path')
file_path = attachment.get("path")
if not file_path:
raise ValueError("No file path provided in attachment")
try:
with self.storage.get_file(file_path) as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')
return base64.b64encode(image_file.read()).decode("utf-8")
except FileNotFoundError:
raise FileNotFoundError(f"File not found: {file_path}")
@@ -273,10 +374,10 @@ class OpenAILLM(BaseLLM):
"""
import logging
if 'openai_file_id' in attachment:
return attachment['openai_file_id']
if "openai_file_id" in attachment:
return attachment["openai_file_id"]
file_path = attachment.get('path')
file_path = attachment.get("path")
if not self.storage.file_exists(file_path):
raise FileNotFoundError(f"File not found: {file_path}")
@@ -285,19 +386,18 @@ class OpenAILLM(BaseLLM):
file_id = self.storage.process_file(
file_path,
lambda local_path, **kwargs: self.client.files.create(
file=open(local_path, 'rb'),
purpose="assistants"
).id
file=open(local_path, "rb"), purpose="assistants"
).id,
)
from application.core.mongo_db import MongoDB
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
attachments_collection = db["attachments"]
if '_id' in attachment:
if "_id" in attachment:
attachments_collection.update_one(
{"_id": attachment['_id']},
{"$set": {"openai_file_id": file_id}}
{"_id": attachment["_id"]}, {"$set": {"openai_file_id": file_id}}
)
return file_id
@@ -308,9 +408,7 @@ class OpenAILLM(BaseLLM):
class AzureOpenAILLM(OpenAILLM):
def __init__(
self, api_key, user_api_key, *args, **kwargs
):
def __init__(self, api_key, user_api_key, *args, **kwargs):
super().__init__(api_key)
self.api_base = (settings.OPENAI_API_BASE,)
@@ -321,5 +419,5 @@ class AzureOpenAILLM(OpenAILLM):
self.client = AzureOpenAI(
api_key=api_key,
api_version=settings.OPENAI_API_VERSION,
azure_endpoint=settings.OPENAI_API_BASE
azure_endpoint=settings.OPENAI_API_BASE,
)

View File

@@ -136,6 +136,8 @@ def _log_to_mongodb(
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
user_logs_collection = db["stack_logs"]
log_entry = {
"endpoint": endpoint,
@@ -147,6 +149,11 @@ def _log_to_mongodb(
"stacks": stacks,
"timestamp": datetime.datetime.now(datetime.timezone.utc),
}
# clean up text fields to be no longer than 10000 characters
for key, value in log_entry.items():
if isinstance(value, str) and len(value) > 10000:
log_entry[key] = value[:10000]
user_logs_collection.insert_one(log_entry)
logging.debug(f"Logged activity to MongoDB: {activity_id}")

View File

@@ -32,16 +32,7 @@ class Chunker:
header, body = "", text # No header, treat entire text as body
return header, body
def combine_documents(self, doc: Document, next_doc: Document) -> Document:
combined_text = doc.text + " " + next_doc.text
combined_token_count = len(self.encoding.encode(combined_text))
new_doc = Document(
text=combined_text,
doc_id=doc.doc_id,
embedding=doc.embedding,
extra_info={**(doc.extra_info or {}), "token_count": combined_token_count}
)
return new_doc
def split_document(self, doc: Document) -> List[Document]:
split_docs = []
@@ -82,26 +73,11 @@ class Chunker:
processed_docs.append(doc)
i += 1
elif token_count < self.min_tokens:
if i + 1 < len(documents):
next_doc = documents[i + 1]
next_tokens = self.encoding.encode(next_doc.text)
if token_count + len(next_tokens) <= self.max_tokens:
# Combine small documents
combined_doc = self.combine_documents(doc, next_doc)
processed_docs.append(combined_doc)
i += 2
else:
# Keep the small document as is if adding next_doc would exceed max_tokens
doc.extra_info = doc.extra_info or {}
doc.extra_info["token_count"] = token_count
processed_docs.append(doc)
i += 1
else:
# No next document to combine with; add the small document as is
doc.extra_info = doc.extra_info or {}
doc.extra_info["token_count"] = token_count
processed_docs.append(doc)
i += 1
doc.extra_info = doc.extra_info or {}
doc.extra_info["token_count"] = token_count
processed_docs.append(doc)
i += 1
else:
# Split large documents
processed_docs.extend(self.split_document(doc))

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"""
External knowledge base connectors for DocsGPT.
This module contains connectors for external knowledge bases and document storage systems
that require authentication and specialized handling, separate from simple web scrapers.
"""
from .base import BaseConnectorAuth, BaseConnectorLoader
from .connector_creator import ConnectorCreator
from .google_drive import GoogleDriveAuth, GoogleDriveLoader
__all__ = [
'BaseConnectorAuth',
'BaseConnectorLoader',
'ConnectorCreator',
'GoogleDriveAuth',
'GoogleDriveLoader'
]

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"""
Base classes for external knowledge base connectors.
This module provides minimal abstract base classes that define the essential
interface for external knowledge base connectors.
"""
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
from application.parser.schema.base import Document
class BaseConnectorAuth(ABC):
"""
Abstract base class for connector authentication.
Defines the minimal interface that all connector authentication
implementations must follow.
"""
@abstractmethod
def get_authorization_url(self, state: Optional[str] = None) -> str:
"""
Generate authorization URL for OAuth flows.
Args:
state: Optional state parameter for CSRF protection
Returns:
Authorization URL
"""
pass
@abstractmethod
def exchange_code_for_tokens(self, authorization_code: str) -> Dict[str, Any]:
"""
Exchange authorization code for access tokens.
Args:
authorization_code: Authorization code from OAuth callback
Returns:
Dictionary containing token information
"""
pass
@abstractmethod
def refresh_access_token(self, refresh_token: str) -> Dict[str, Any]:
"""
Refresh an expired access token.
Args:
refresh_token: Refresh token
Returns:
Dictionary containing refreshed token information
"""
pass
@abstractmethod
def is_token_expired(self, token_info: Dict[str, Any]) -> bool:
"""
Check if a token is expired.
Args:
token_info: Token information dictionary
Returns:
True if token is expired, False otherwise
"""
pass
class BaseConnectorLoader(ABC):
"""
Abstract base class for connector loaders.
Defines the minimal interface that all connector loader
implementations must follow.
"""
@abstractmethod
def __init__(self, session_token: str):
"""
Initialize the connector loader.
Args:
session_token: Authentication session token
"""
pass
@abstractmethod
def load_data(self, inputs: Dict[str, Any]) -> List[Document]:
"""
Load documents from the external knowledge base.
Args:
inputs: Configuration dictionary containing:
- file_ids: Optional list of specific file IDs to load
- folder_ids: Optional list of folder IDs to browse/download
- limit: Maximum number of items to return
- list_only: If True, return metadata without content
- recursive: Whether to recursively process folders
Returns:
List of Document objects
"""
pass
@abstractmethod
def download_to_directory(self, local_dir: str, source_config: Dict[str, Any] = None) -> Dict[str, Any]:
"""
Download files/folders to a local directory.
Args:
local_dir: Local directory path to download files to
source_config: Configuration for what to download
Returns:
Dictionary containing download results:
- files_downloaded: Number of files downloaded
- directory_path: Path where files were downloaded
- empty_result: Whether no files were downloaded
- source_type: Type of connector
- config_used: Configuration that was used
- error: Error message if download failed (optional)
"""
pass

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from application.parser.connectors.google_drive.loader import GoogleDriveLoader
from application.parser.connectors.google_drive.auth import GoogleDriveAuth
class ConnectorCreator:
"""
Factory class for creating external knowledge base connectors and auth providers.
These are different from remote loaders as they typically require
authentication and connect to external document storage systems.
"""
connectors = {
"google_drive": GoogleDriveLoader,
}
auth_providers = {
"google_drive": GoogleDriveAuth,
}
@classmethod
def create_connector(cls, connector_type, *args, **kwargs):
"""
Create a connector instance for the specified type.
Args:
connector_type: Type of connector to create (e.g., 'google_drive')
*args, **kwargs: Arguments to pass to the connector constructor
Returns:
Connector instance
Raises:
ValueError: If connector type is not supported
"""
connector_class = cls.connectors.get(connector_type.lower())
if not connector_class:
raise ValueError(f"No connector class found for type {connector_type}")
return connector_class(*args, **kwargs)
@classmethod
def create_auth(cls, connector_type):
"""
Create an auth provider instance for the specified connector type.
Args:
connector_type: Type of connector auth to create (e.g., 'google_drive')
Returns:
Auth provider instance
Raises:
ValueError: If connector type is not supported for auth
"""
auth_class = cls.auth_providers.get(connector_type.lower())
if not auth_class:
raise ValueError(f"No auth class found for type {connector_type}")
return auth_class()
@classmethod
def get_supported_connectors(cls):
"""
Get list of supported connector types.
Returns:
List of supported connector type strings
"""
return list(cls.connectors.keys())
@classmethod
def is_supported(cls, connector_type):
"""
Check if a connector type is supported.
Args:
connector_type: Type of connector to check
Returns:
True if supported, False otherwise
"""
return connector_type.lower() in cls.connectors

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"""
Google Drive connector for DocsGPT.
This module provides authentication and document loading capabilities for Google Drive.
"""
from .auth import GoogleDriveAuth
from .loader import GoogleDriveLoader
__all__ = ['GoogleDriveAuth', 'GoogleDriveLoader']

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import logging
import datetime
from typing import Optional, Dict, Any
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import Flow
from googleapiclient.discovery import build
from googleapiclient.errors import HttpError
from application.core.settings import settings
from application.parser.connectors.base import BaseConnectorAuth
class GoogleDriveAuth(BaseConnectorAuth):
"""
Handles Google OAuth 2.0 authentication for Google Drive access.
"""
SCOPES = [
'https://www.googleapis.com/auth/drive.readonly',
'https://www.googleapis.com/auth/drive.metadata.readonly'
]
def __init__(self):
self.client_id = settings.GOOGLE_CLIENT_ID
self.client_secret = settings.GOOGLE_CLIENT_SECRET
self.redirect_uri = f"{settings.CONNECTOR_REDIRECT_BASE_URI}?provider=google_drive"
if not self.client_id or not self.client_secret:
raise ValueError("Google OAuth credentials not configured. Please set GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRET in settings.")
def get_authorization_url(self, state: Optional[str] = None) -> str:
try:
flow = Flow.from_client_config(
{
"web": {
"client_id": self.client_id,
"client_secret": self.client_secret,
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://oauth2.googleapis.com/token",
"redirect_uris": [self.redirect_uri]
}
},
scopes=self.SCOPES
)
flow.redirect_uri = self.redirect_uri
authorization_url, _ = flow.authorization_url(
access_type='offline',
prompt='consent',
include_granted_scopes='true',
state=state
)
return authorization_url
except Exception as e:
logging.error(f"Error generating authorization URL: {e}")
raise
def exchange_code_for_tokens(self, authorization_code: str) -> Dict[str, Any]:
try:
if not authorization_code:
raise ValueError("Authorization code is required")
flow = Flow.from_client_config(
{
"web": {
"client_id": self.client_id,
"client_secret": self.client_secret,
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://oauth2.googleapis.com/token",
"redirect_uris": [self.redirect_uri]
}
},
scopes=self.SCOPES
)
flow.redirect_uri = self.redirect_uri
flow.fetch_token(code=authorization_code)
credentials = flow.credentials
if not credentials.refresh_token:
logging.warning("OAuth flow did not return a refresh_token.")
if not credentials.token:
raise ValueError("OAuth flow did not return an access token")
if not credentials.token_uri:
credentials.token_uri = "https://oauth2.googleapis.com/token"
if not credentials.client_id:
credentials.client_id = self.client_id
if not credentials.client_secret:
credentials.client_secret = self.client_secret
if not credentials.refresh_token:
raise ValueError(
"No refresh token received. This typically happens when offline access wasn't granted. "
)
return {
'access_token': credentials.token,
'refresh_token': credentials.refresh_token,
'token_uri': credentials.token_uri,
'client_id': credentials.client_id,
'client_secret': credentials.client_secret,
'scopes': credentials.scopes,
'expiry': credentials.expiry.isoformat() if credentials.expiry else None
}
except Exception as e:
logging.error(f"Error exchanging code for tokens: {e}")
raise
def refresh_access_token(self, refresh_token: str) -> Dict[str, Any]:
try:
if not refresh_token:
raise ValueError("Refresh token is required")
credentials = Credentials(
token=None,
refresh_token=refresh_token,
token_uri="https://oauth2.googleapis.com/token",
client_id=self.client_id,
client_secret=self.client_secret
)
from google.auth.transport.requests import Request
credentials.refresh(Request())
return {
'access_token': credentials.token,
'refresh_token': refresh_token,
'token_uri': credentials.token_uri,
'client_id': credentials.client_id,
'client_secret': credentials.client_secret,
'scopes': credentials.scopes,
'expiry': credentials.expiry.isoformat() if credentials.expiry else None
}
except Exception as e:
logging.error(f"Error refreshing access token: {e}", exc_info=True)
raise
def create_credentials_from_token_info(self, token_info: Dict[str, Any]) -> Credentials:
from application.core.settings import settings
access_token = token_info.get('access_token')
if not access_token:
raise ValueError("No access token found in token_info")
credentials = Credentials(
token=access_token,
refresh_token=token_info.get('refresh_token'),
token_uri= 'https://oauth2.googleapis.com/token',
client_id=settings.GOOGLE_CLIENT_ID,
client_secret=settings.GOOGLE_CLIENT_SECRET,
scopes=token_info.get('scopes', ['https://www.googleapis.com/auth/drive.readonly'])
)
if not credentials.token:
raise ValueError("Credentials created without valid access token")
return credentials
def build_drive_service(self, credentials: Credentials):
try:
if not credentials:
raise ValueError("No credentials provided")
if not credentials.token and not credentials.refresh_token:
raise ValueError("No access token or refresh token available. User must re-authorize with offline access.")
needs_refresh = credentials.expired or not credentials.token
if needs_refresh:
if credentials.refresh_token:
try:
from google.auth.transport.requests import Request
credentials.refresh(Request())
except Exception as refresh_error:
raise ValueError(f"Failed to refresh credentials: {refresh_error}")
else:
raise ValueError("No access token or refresh token available. User must re-authorize with offline access.")
return build('drive', 'v3', credentials=credentials)
except HttpError as e:
raise ValueError(f"Failed to build Google Drive service: HTTP {e.resp.status}")
except Exception as e:
raise ValueError(f"Failed to build Google Drive service: {str(e)}")
def is_token_expired(self, token_info):
if 'expiry' in token_info and token_info['expiry']:
try:
from dateutil import parser
# Google Drive provides timezone-aware ISO8601 dates
expiry_dt = parser.parse(token_info['expiry'])
current_time = datetime.datetime.now(datetime.timezone.utc)
return current_time >= expiry_dt - datetime.timedelta(seconds=60)
except Exception:
return True
if 'access_token' in token_info and token_info['access_token']:
return False
return True
def get_token_info_from_session(self, session_token: str) -> Dict[str, Any]:
try:
from application.core.mongo_db import MongoDB
from application.core.settings import settings
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
sessions_collection = db["connector_sessions"]
session = sessions_collection.find_one({"session_token": session_token})
if not session:
raise ValueError(f"Invalid session token: {session_token}")
if "token_info" not in session:
raise ValueError("Session missing token information")
token_info = session["token_info"]
if not token_info:
raise ValueError("Invalid token information")
required_fields = ["access_token", "refresh_token"]
missing_fields = [field for field in required_fields if field not in token_info or not token_info.get(field)]
if missing_fields:
raise ValueError(f"Missing required token fields: {missing_fields}")
if 'client_id' not in token_info:
token_info['client_id'] = settings.GOOGLE_CLIENT_ID
if 'client_secret' not in token_info:
token_info['client_secret'] = settings.GOOGLE_CLIENT_SECRET
if 'token_uri' not in token_info:
token_info['token_uri'] = 'https://oauth2.googleapis.com/token'
return token_info
except Exception as e:
raise ValueError(f"Failed to retrieve Google Drive token information: {str(e)}")
def validate_credentials(self, credentials: Credentials) -> bool:
"""
Validate Google Drive credentials by making a test API call.
Args:
credentials: Google credentials object
Returns:
True if credentials are valid, False otherwise
"""
try:
service = self.build_drive_service(credentials)
service.about().get(fields="user").execute()
return True
except HttpError as e:
logging.error(f"HTTP error validating credentials: {e}")
return False
except Exception as e:
logging.error(f"Error validating credentials: {e}")
return False

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"""
Google Drive loader for DocsGPT.
Loads documents from Google Drive using Google Drive API.
"""
import io
import logging
import os
from typing import List, Dict, Any, Optional
from googleapiclient.http import MediaIoBaseDownload
from googleapiclient.errors import HttpError
from application.parser.connectors.base import BaseConnectorLoader
from application.parser.connectors.google_drive.auth import GoogleDriveAuth
from application.parser.schema.base import Document
class GoogleDriveLoader(BaseConnectorLoader):
SUPPORTED_MIME_TYPES = {
'application/pdf': '.pdf',
'application/vnd.google-apps.document': '.docx',
'application/vnd.google-apps.presentation': '.pptx',
'application/vnd.google-apps.spreadsheet': '.xlsx',
'application/vnd.openxmlformats-officedocument.wordprocessingml.document': '.docx',
'application/vnd.openxmlformats-officedocument.presentationml.presentation': '.pptx',
'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': '.xlsx',
'application/msword': '.doc',
'application/vnd.ms-powerpoint': '.ppt',
'application/vnd.ms-excel': '.xls',
'text/plain': '.txt',
'text/csv': '.csv',
'text/html': '.html',
'application/rtf': '.rtf',
'image/jpeg': '.jpg',
'image/jpg': '.jpg',
'image/png': '.png',
}
EXPORT_FORMATS = {
'application/vnd.google-apps.document': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document',
'application/vnd.google-apps.presentation': 'application/vnd.openxmlformats-officedocument.presentationml.presentation',
'application/vnd.google-apps.spreadsheet': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
}
def __init__(self, session_token: str):
self.auth = GoogleDriveAuth()
self.session_token = session_token
token_info = self.auth.get_token_info_from_session(session_token)
self.credentials = self.auth.create_credentials_from_token_info(token_info)
try:
self.service = self.auth.build_drive_service(self.credentials)
except Exception as e:
logging.warning(f"Could not build Google Drive service: {e}")
self.service = None
self.next_page_token = None
def _process_file(self, file_metadata: Dict[str, Any], load_content: bool = True) -> Optional[Document]:
try:
file_id = file_metadata.get('id')
file_name = file_metadata.get('name', 'Unknown')
mime_type = file_metadata.get('mimeType', 'application/octet-stream')
if mime_type not in self.SUPPORTED_MIME_TYPES and not mime_type.startswith('application/vnd.google-apps.'):
return None
if mime_type not in self.SUPPORTED_MIME_TYPES and not mime_type.startswith('application/vnd.google-apps.'):
logging.info(f"Skipping unsupported file type: {mime_type} for file {file_name}")
return None
# Google Drive provides timezone-aware ISO8601 dates
doc_metadata = {
'file_name': file_name,
'mime_type': mime_type,
'size': file_metadata.get('size', None),
'created_time': file_metadata.get('createdTime'),
'modified_time': file_metadata.get('modifiedTime'),
'parents': file_metadata.get('parents', []),
'source': 'google_drive'
}
if not load_content:
return Document(
text="",
doc_id=file_id,
extra_info=doc_metadata
)
content = self._download_file_content(file_id, mime_type)
if content is None:
logging.warning(f"Could not load content for file {file_name} ({file_id})")
return None
return Document(
text=content,
doc_id=file_id,
extra_info=doc_metadata
)
except Exception as e:
logging.error(f"Error processing file: {e}")
return None
def load_data(self, inputs: Dict[str, Any]) -> List[Document]:
session_token = inputs.get('session_token')
if session_token and session_token != self.session_token:
logging.warning("Session token in inputs differs from loader's session token. Using loader's session token.")
self.config = inputs
try:
documents: List[Document] = []
folder_id = inputs.get('folder_id')
file_ids = inputs.get('file_ids', [])
limit = inputs.get('limit', 100)
list_only = inputs.get('list_only', False)
load_content = not list_only
page_token = inputs.get('page_token')
self.next_page_token = None
if file_ids:
# Specific files requested: load them
for file_id in file_ids:
try:
doc = self._load_file_by_id(file_id, load_content=load_content)
if doc:
documents.append(doc)
elif hasattr(self, '_credential_refreshed') and self._credential_refreshed:
self._credential_refreshed = False
logging.info(f"Retrying load of file {file_id} after credential refresh")
doc = self._load_file_by_id(file_id, load_content=load_content)
if doc:
documents.append(doc)
except Exception as e:
logging.error(f"Error loading file {file_id}: {e}")
continue
else:
# Browsing mode: list immediate children of provided folder or root
parent_id = folder_id if folder_id else 'root'
documents = self._list_items_in_parent(parent_id, limit=limit, load_content=load_content, page_token=page_token)
logging.info(f"Loaded {len(documents)} documents from Google Drive")
return documents
except Exception as e:
logging.error(f"Error loading data from Google Drive: {e}", exc_info=True)
raise
def _load_file_by_id(self, file_id: str, load_content: bool = True) -> Optional[Document]:
self._ensure_service()
try:
file_metadata = self.service.files().get(
fileId=file_id,
fields='id,name,mimeType,size,createdTime,modifiedTime,parents'
).execute()
return self._process_file(file_metadata, load_content=load_content)
except HttpError as e:
logging.error(f"HTTP error loading file {file_id}: {e.resp.status} - {e.content}")
if e.resp.status in [401, 403]:
if hasattr(self.credentials, 'refresh_token') and self.credentials.refresh_token:
try:
from google.auth.transport.requests import Request
self.credentials.refresh(Request())
self._ensure_service()
return None
except Exception as refresh_error:
raise ValueError(f"Authentication failed and could not be refreshed: {refresh_error}")
else:
raise ValueError("Authentication failed and cannot be refreshed: missing refresh_token")
return None
except Exception as e:
logging.error(f"Error loading file {file_id}: {e}")
return None
def _list_items_in_parent(self, parent_id: str, limit: int = 100, load_content: bool = False, page_token: Optional[str] = None) -> List[Document]:
self._ensure_service()
documents: List[Document] = []
try:
query = f"'{parent_id}' in parents and trashed=false"
next_token_out: Optional[str] = None
while True:
page_size = 100
if limit:
remaining = max(0, limit - len(documents))
if remaining == 0:
break
page_size = min(100, remaining)
results = self.service.files().list(
q=query,
fields='nextPageToken,files(id,name,mimeType,size,createdTime,modifiedTime,parents)',
pageToken=page_token,
pageSize=page_size
).execute()
items = results.get('files', [])
for item in items:
mime_type = item.get('mimeType')
if mime_type == 'application/vnd.google-apps.folder':
doc_metadata = {
'file_name': item.get('name', 'Unknown'),
'mime_type': mime_type,
'size': item.get('size', None),
'created_time': item.get('createdTime'),
'modified_time': item.get('modifiedTime'),
'parents': item.get('parents', []),
'source': 'google_drive',
'is_folder': True
}
documents.append(Document(text="", doc_id=item.get('id'), extra_info=doc_metadata))
else:
doc = self._process_file(item, load_content=load_content)
if doc:
documents.append(doc)
if limit and len(documents) >= limit:
self.next_page_token = results.get('nextPageToken')
return documents
page_token = results.get('nextPageToken')
next_token_out = page_token
if not page_token:
break
self.next_page_token = next_token_out
return documents
except Exception as e:
logging.error(f"Error listing items under parent {parent_id}: {e}")
return documents
def _download_file_content(self, file_id: str, mime_type: str) -> Optional[str]:
if not self.credentials.token:
logging.warning("No access token in credentials, attempting to refresh")
if hasattr(self.credentials, 'refresh_token') and self.credentials.refresh_token:
try:
from google.auth.transport.requests import Request
self.credentials.refresh(Request())
logging.info("Credentials refreshed successfully")
self._ensure_service()
except Exception as e:
logging.error(f"Failed to refresh credentials: {e}")
raise ValueError("Authentication failed and cannot be refreshed: missing or invalid refresh_token")
else:
logging.error("No access token and no refresh_token available")
raise ValueError("Authentication failed and cannot be refreshed: missing refresh_token")
if self.credentials.expired:
logging.warning("Credentials are expired, attempting to refresh")
if hasattr(self.credentials, 'refresh_token') and self.credentials.refresh_token:
try:
from google.auth.transport.requests import Request
self.credentials.refresh(Request())
logging.info("Credentials refreshed successfully")
self._ensure_service()
except Exception as e:
logging.error(f"Failed to refresh expired credentials: {e}")
raise ValueError("Authentication failed and cannot be refreshed: expired credentials")
else:
logging.error("Credentials expired and no refresh_token available")
raise ValueError("Authentication failed and cannot be refreshed: missing refresh_token")
try:
if mime_type in self.EXPORT_FORMATS:
export_mime_type = self.EXPORT_FORMATS[mime_type]
request = self.service.files().export_media(
fileId=file_id,
mimeType=export_mime_type
)
else:
request = self.service.files().get_media(fileId=file_id)
file_io = io.BytesIO()
downloader = MediaIoBaseDownload(file_io, request)
done = False
while done is False:
try:
_, done = downloader.next_chunk()
except HttpError as e:
logging.error(f"HTTP error downloading file {file_id}: {e.resp.status} - {e.content}")
return None
except Exception as e:
logging.error(f"Error during download of file {file_id}: {e}")
return None
content_bytes = file_io.getvalue()
try:
content = content_bytes.decode('utf-8')
except UnicodeDecodeError:
try:
content = content_bytes.decode('latin-1')
except UnicodeDecodeError:
logging.error(f"Could not decode file {file_id} as text")
return None
return content
except HttpError as e:
logging.error(f"HTTP error downloading file {file_id}: {e.resp.status} - {e.content}")
if e.resp.status in [401, 403]:
logging.error(f"Authentication error downloading file {file_id}")
if hasattr(self.credentials, 'refresh_token') and self.credentials.refresh_token:
logging.info(f"Attempting to refresh credentials for file {file_id}")
try:
from google.auth.transport.requests import Request
self.credentials.refresh(Request())
logging.info("Credentials refreshed successfully")
self._credential_refreshed = True
self._ensure_service()
return None
except Exception as refresh_error:
logging.error(f"Error refreshing credentials: {refresh_error}")
raise ValueError(f"Authentication failed and could not be refreshed: {refresh_error}")
else:
logging.error("Cannot refresh credentials: missing refresh_token")
raise ValueError("Authentication failed and cannot be refreshed: missing refresh_token")
return None
except Exception as e:
logging.error(f"Error downloading file {file_id}: {e}")
return None
def _download_file_to_directory(self, file_id: str, local_dir: str) -> bool:
try:
self._ensure_service()
return self._download_single_file(file_id, local_dir)
except Exception as e:
logging.error(f"Error downloading file {file_id}: {e}", exc_info=True)
return False
def _ensure_service(self):
if not self.service:
try:
self.service = self.auth.build_drive_service(self.credentials)
except Exception as e:
raise ValueError(f"Cannot access Google Drive: {e}")
def _download_single_file(self, file_id: str, local_dir: str) -> bool:
file_metadata = self.service.files().get(
fileId=file_id,
fields='name,mimeType'
).execute()
file_name = file_metadata['name']
mime_type = file_metadata['mimeType']
if mime_type not in self.SUPPORTED_MIME_TYPES and not mime_type.startswith('application/vnd.google-apps.'):
return False
os.makedirs(local_dir, exist_ok=True)
full_path = os.path.join(local_dir, file_name)
if mime_type in self.EXPORT_FORMATS:
export_mime_type = self.EXPORT_FORMATS[mime_type]
request = self.service.files().export_media(
fileId=file_id,
mimeType=export_mime_type
)
extension = self._get_extension_for_mime_type(export_mime_type)
if not full_path.endswith(extension):
full_path += extension
else:
request = self.service.files().get_media(fileId=file_id)
with open(full_path, 'wb') as f:
downloader = MediaIoBaseDownload(f, request)
done = False
while not done:
_, done = downloader.next_chunk()
return True
def _download_folder_recursive(self, folder_id: str, local_dir: str, recursive: bool = True) -> int:
files_downloaded = 0
try:
os.makedirs(local_dir, exist_ok=True)
query = f"'{folder_id}' in parents and trashed=false"
page_token = None
while True:
results = self.service.files().list(
q=query,
fields='nextPageToken, files(id, name, mimeType)',
pageToken=page_token,
pageSize=1000
).execute()
items = results.get('files', [])
logging.info(f"Found {len(items)} items in folder {folder_id}")
for item in items:
item_name = item['name']
item_id = item['id']
mime_type = item['mimeType']
if mime_type == 'application/vnd.google-apps.folder':
if recursive:
# Create subfolder and recurse
subfolder_path = os.path.join(local_dir, item_name)
os.makedirs(subfolder_path, exist_ok=True)
subfolder_files = self._download_folder_recursive(
item_id,
subfolder_path,
recursive
)
files_downloaded += subfolder_files
logging.info(f"Downloaded {subfolder_files} files from subfolder {item_name}")
else:
# Download file
success = self._download_single_file(item_id, local_dir)
if success:
files_downloaded += 1
logging.info(f"Downloaded file: {item_name}")
else:
logging.warning(f"Failed to download file: {item_name}")
page_token = results.get('nextPageToken')
if not page_token:
break
return files_downloaded
except Exception as e:
logging.error(f"Error in _download_folder_recursive for folder {folder_id}: {e}", exc_info=True)
return files_downloaded
def _get_extension_for_mime_type(self, mime_type: str) -> str:
extensions = {
'application/pdf': '.pdf',
'text/plain': '.txt',
'application/vnd.openxmlformats-officedocument.wordprocessingml.document': '.docx',
'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': '.xlsx',
'application/vnd.openxmlformats-officedocument.presentationml.presentation': '.pptx',
'text/html': '.html',
'text/markdown': '.md',
}
return extensions.get(mime_type, '.bin')
def _download_folder_contents(self, folder_id: str, local_dir: str, recursive: bool = True) -> int:
try:
self._ensure_service()
return self._download_folder_recursive(folder_id, local_dir, recursive)
except Exception as e:
logging.error(f"Error downloading folder {folder_id}: {e}", exc_info=True)
return 0
def download_to_directory(self, local_dir: str, source_config: dict = None) -> dict:
if source_config is None:
source_config = {}
config = source_config if source_config else getattr(self, 'config', {})
files_downloaded = 0
try:
folder_ids = config.get('folder_ids', [])
file_ids = config.get('file_ids', [])
recursive = config.get('recursive', True)
self._ensure_service()
if file_ids:
if isinstance(file_ids, str):
file_ids = [file_ids]
for file_id in file_ids:
if self._download_file_to_directory(file_id, local_dir):
files_downloaded += 1
# Process folders
if folder_ids:
if isinstance(folder_ids, str):
folder_ids = [folder_ids]
for folder_id in folder_ids:
try:
folder_metadata = self.service.files().get(
fileId=folder_id,
fields='name'
).execute()
folder_name = folder_metadata.get('name', '')
folder_path = os.path.join(local_dir, folder_name)
os.makedirs(folder_path, exist_ok=True)
folder_files = self._download_folder_recursive(
folder_id,
folder_path,
recursive
)
files_downloaded += folder_files
logging.info(f"Downloaded {folder_files} files from folder {folder_name}")
except Exception as e:
logging.error(f"Error downloading folder {folder_id}: {e}", exc_info=True)
if not file_ids and not folder_ids:
raise ValueError("No folder_ids or file_ids provided for download")
return {
"files_downloaded": files_downloaded,
"directory_path": local_dir,
"empty_result": files_downloaded == 0,
"source_type": "google_drive",
"config_used": config
}
except Exception as e:
return {
"files_downloaded": files_downloaded,
"directory_path": local_dir,
"empty_result": True,
"source_type": "google_drive",
"config_used": config,
"error": str(e)
}

View File

@@ -6,6 +6,21 @@ from application.core.settings import settings
from application.vectorstore.vector_creator import VectorCreator
def sanitize_content(content: str) -> str:
"""
Remove NUL characters that can cause vector store ingestion to fail.
Args:
content (str): Raw content that may contain NUL characters
Returns:
str: Sanitized content with NUL characters removed
"""
if not content:
return content
return content.replace('\x00', '')
@retry(tries=10, delay=60)
def add_text_to_store_with_retry(store, doc, source_id):
"""
@@ -16,6 +31,9 @@ def add_text_to_store_with_retry(store, doc, source_id):
source_id: Unique identifier for the source.
"""
try:
# Sanitize content to remove NUL characters that cause ingestion failures
doc.page_content = sanitize_content(doc.page_content)
doc.metadata["source_id"] = str(source_id)
store.add_texts([doc.page_content], metadatas=[doc.metadata])
except Exception as e:
@@ -46,7 +64,7 @@ def embed_and_store_documents(docs, folder_name, source_id, task_status):
store = VectorCreator.create_vectorstore(
settings.VECTOR_STORE,
docs_init=docs_init,
source_id=folder_name,
source_id=source_id,
embeddings_key=os.getenv("EMBEDDINGS_KEY"),
)
else:

View File

@@ -15,6 +15,7 @@ from application.parser.file.json_parser import JSONParser
from application.parser.file.pptx_parser import PPTXParser
from application.parser.file.image_parser import ImageParser
from application.parser.schema.base import Document
from application.utils import num_tokens_from_string
DEFAULT_FILE_EXTRACTOR: Dict[str, BaseParser] = {
".pdf": PDFParser(),
@@ -141,11 +142,12 @@ class SimpleDirectoryReader(BaseReader):
Returns:
List[Document]: A list of documents.
"""
data: Union[str, List[str]] = ""
data_list: List[str] = []
metadata_list = []
self.file_token_counts = {}
for input_file in self.input_files:
if input_file.suffix in self.file_extractor:
parser = self.file_extractor[input_file.suffix]
@@ -156,24 +158,48 @@ class SimpleDirectoryReader(BaseReader):
# do standard read
with open(input_file, "r", errors=self.errors) as f:
data = f.read()
# Prepare metadata for this file
if self.file_metadata is not None:
file_metadata = self.file_metadata(input_file.name)
# Calculate token count for this file
if isinstance(data, List):
file_tokens = sum(num_tokens_from_string(str(d)) for d in data)
else:
# Provide a default empty metadata
file_metadata = {'title': '', 'store': ''}
# TODO: Find a case with no metadata and check if breaks anything
file_tokens = num_tokens_from_string(str(data))
full_path = str(input_file.resolve())
self.file_token_counts[full_path] = file_tokens
base_metadata = {
'title': input_file.name,
'token_count': file_tokens,
}
if hasattr(self, 'input_dir'):
try:
relative_path = str(input_file.relative_to(self.input_dir))
base_metadata['source'] = relative_path
except ValueError:
base_metadata['source'] = str(input_file)
else:
base_metadata['source'] = str(input_file)
if self.file_metadata is not None:
custom_metadata = self.file_metadata(input_file.name)
base_metadata.update(custom_metadata)
if isinstance(data, List):
# Extend data_list with each item in the data list
data_list.extend([str(d) for d in data])
# For each item in the data list, add the file's metadata to metadata_list
metadata_list.extend([file_metadata for _ in data])
metadata_list.extend([base_metadata for _ in data])
else:
# Add the single piece of data to data_list
data_list.append(str(data))
# Add the file's metadata to metadata_list
metadata_list.append(file_metadata)
metadata_list.append(base_metadata)
# Build directory structure if input_dir is provided
if hasattr(self, 'input_dir'):
self.directory_structure = self.build_directory_structure(self.input_dir)
logging.info("Directory structure built successfully")
else:
self.directory_structure = {}
if concatenate:
return [Document("\n".join(data_list))]
@@ -181,3 +207,48 @@ class SimpleDirectoryReader(BaseReader):
return [Document(d, extra_info=m) for d, m in zip(data_list, metadata_list)]
else:
return [Document(d) for d in data_list]
def build_directory_structure(self, base_path):
"""Build a dictionary representing the directory structure.
Args:
base_path: The base path to start building the structure from.
Returns:
dict: A nested dictionary representing the directory structure.
"""
import mimetypes
def build_tree(path):
"""Helper function to recursively build the directory tree."""
result = {}
for item in path.iterdir():
if self.exclude_hidden and item.name.startswith('.'):
continue
if item.is_dir():
subtree = build_tree(item)
if subtree:
result[item.name] = subtree
else:
if self.required_exts is not None and item.suffix not in self.required_exts:
continue
full_path = str(item.resolve())
file_size_bytes = item.stat().st_size
mime_type = mimetypes.guess_type(item.name)[0] or "application/octet-stream"
file_info = {
"type": mime_type,
"size_bytes": file_size_bytes
}
if hasattr(self, 'file_token_counts') and full_path in self.file_token_counts:
file_info["token_count"] = self.file_token_counts[full_path]
result[item.name] = file_info
return result
return build_tree(Path(base_path))

View File

@@ -8,6 +8,7 @@ import requests
from typing import Dict, Union
from application.parser.file.base_parser import BaseParser
from application.core.settings import settings
class ImageParser(BaseParser):
@@ -18,10 +19,13 @@ class ImageParser(BaseParser):
return {}
def parse_file(self, file: Path, errors: str = "ignore") -> Union[str, list[str]]:
doc2md_service = "https://llm.arc53.com/doc2md"
# alternatively you can use local vision capable LLM
with open(file, "rb") as file_loaded:
files = {'file': file_loaded}
response = requests.post(doc2md_service, files=files)
data = response.json()["markdown"]
if settings.PARSE_IMAGE_REMOTE:
doc2md_service = "https://llm.arc53.com/doc2md"
# alternatively you can use local vision capable LLM
with open(file, "rb") as file_loaded:
files = {'file': file_loaded}
response = requests.post(doc2md_service, files=files)
data = response.json()["markdown"]
else:
data = ""
return data

View File

@@ -6,6 +6,16 @@ from application.parser.remote.github_loader import GitHubLoader
class RemoteCreator:
"""
Factory class for creating remote content loaders.
These loaders fetch content from remote web sources like URLs,
sitemaps, web crawlers, social media platforms, etc.
For external knowledge base connectors (like Google Drive),
use ConnectorCreator instead.
"""
loaders = {
"url": WebLoader,
"sitemap": SitemapLoader,
@@ -18,5 +28,5 @@ class RemoteCreator:
def create_loader(cls, type, *args, **kwargs):
loader_class = cls.loaders.get(type.lower())
if not loader_class:
raise ValueError(f"No LLM class found for type {type}")
raise ValueError(f"No loader class found for type {type}")
return loader_class(*args, **kwargs)

View File

@@ -13,6 +13,9 @@ Flask==3.1.1
faiss-cpu==1.9.0.post1
flask-restx==1.3.0
google-genai==1.3.0
google-api-python-client==2.179.0
google-auth-httplib2==0.2.0
google-auth-oauthlib==1.2.2
gTTS==2.5.4
gunicorn==23.0.0
javalang==0.13.0

View File

View File

@@ -93,3 +93,32 @@ class BaseStorage(ABC):
List[str]: List of file paths
"""
pass
@abstractmethod
def is_directory(self, path: str) -> bool:
"""
Check if a path is a directory.
Args:
path: Path to check
Returns:
bool: True if the path is a directory
"""
pass
@abstractmethod
def remove_directory(self, directory: str) -> bool:
"""
Remove a directory and all its contents.
For local storage, this removes the directory and all files/subdirectories within it.
For S3 storage, this removes all objects with the directory path as a prefix.
Args:
directory: Directory path to remove
Returns:
bool: True if removal was successful, False otherwise
"""
pass

View File

@@ -101,3 +101,40 @@ class LocalStorage(BaseStorage):
raise FileNotFoundError(f"File not found: {full_path}")
return processor_func(local_path=full_path, **kwargs)
def is_directory(self, path: str) -> bool:
"""
Check if a path is a directory in local storage.
Args:
path: Path to check
Returns:
bool: True if the path is a directory, False otherwise
"""
full_path = self._get_full_path(path)
return os.path.isdir(full_path)
def remove_directory(self, directory: str) -> bool:
"""
Remove a directory and all its contents from local storage.
Args:
directory: Directory path to remove
Returns:
bool: True if removal was successful, False otherwise
"""
full_path = self._get_full_path(directory)
if not os.path.exists(full_path):
return False
if not os.path.isdir(full_path):
return False
try:
shutil.rmtree(full_path)
return True
except (OSError, PermissionError):
return False

View File

@@ -130,3 +130,77 @@ class S3Storage(BaseStorage):
except Exception as e:
logging.error(f"Error processing S3 file {path}: {e}", exc_info=True)
raise
def is_directory(self, path: str) -> bool:
"""
Check if a path is a directory in S3 storage.
In S3, directories are virtual concepts. A path is considered a directory
if there are objects with the path as a prefix.
Args:
path: Path to check
Returns:
bool: True if the path is a directory, False otherwise
"""
# Ensure path ends with a slash if not empty
if path and not path.endswith('/'):
path += '/'
response = self.s3.list_objects_v2(
Bucket=self.bucket_name,
Prefix=path,
MaxKeys=1
)
return 'Contents' in response
def remove_directory(self, directory: str) -> bool:
"""
Remove a directory and all its contents from S3 storage.
In S3, this removes all objects with the directory path as a prefix.
Since S3 doesn't have actual directories, this effectively removes
all files within the virtual directory structure.
Args:
directory: Directory path to remove
Returns:
bool: True if removal was successful, False otherwise
"""
# Ensure directory ends with a slash if not empty
if directory and not directory.endswith('/'):
directory += '/'
try:
# Get all objects with the directory prefix
objects_to_delete = []
paginator = self.s3.get_paginator('list_objects_v2')
pages = paginator.paginate(Bucket=self.bucket_name, Prefix=directory)
for page in pages:
if 'Contents' in page:
for obj in page['Contents']:
objects_to_delete.append({'Key': obj['Key']})
if not objects_to_delete:
return False
batch_size = 1000
for i in range(0, len(objects_to_delete), batch_size):
batch = objects_to_delete[i:i + batch_size]
response = self.s3.delete_objects(
Bucket=self.bucket_name,
Delete={'Objects': batch}
)
if 'Errors' in response and response['Errors']:
return False
return True
except ClientError:
return False

View File

@@ -6,6 +6,7 @@ import uuid
import tiktoken
from flask import jsonify, make_response
from werkzeug.utils import secure_filename
from application.core.settings import settings
@@ -19,6 +20,17 @@ def get_encoding():
return _encoding
def get_gpt_model() -> str:
"""Get the appropriate GPT model based on provider"""
model_map = {
"openai": "gpt-4o-mini",
"anthropic": "claude-2",
"groq": "llama3-8b-8192",
"novita": "deepseek/deepseek-r1",
}
return settings.LLM_NAME or model_map.get(settings.LLM_PROVIDER, "")
def safe_filename(filename):
"""
Creates a safe filename that preserves the original extension.
@@ -32,15 +44,14 @@ def safe_filename(filename):
"""
if not filename:
return str(uuid.uuid4())
_, extension = os.path.splitext(filename)
safe_name = secure_filename(filename)
# If secure_filename returns just the extension or an empty string
if not safe_name or safe_name == extension.lstrip("."):
return f"{str(uuid.uuid4())}{extension}"
return safe_name
@@ -68,7 +79,6 @@ def count_tokens_docs(docs):
docs_content = ""
for doc in docs:
docs_content += doc.page_content
tokens = num_tokens_from_string(docs_content)
return tokens
@@ -97,13 +107,11 @@ def validate_required_fields(data, required_fields):
missing_fields.append(field)
elif not data[field]:
empty_fields.append(field)
errors = []
if missing_fields:
errors.append(f"Missing required fields: {', '.join(missing_fields)}")
if empty_fields:
errors.append(f"Empty values in required fields: {', '.join(empty_fields)}")
if errors:
return make_response(
jsonify({"success": False, "message": " | ".join(errors)}), 400
@@ -132,7 +140,6 @@ def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
if not history:
return []
trimmed_history = []
tokens_current_history = 0
@@ -141,18 +148,15 @@ def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
if "prompt" in message and "response" in message:
tokens_batch += num_tokens_from_string(message["prompt"])
tokens_batch += num_tokens_from_string(message["response"])
if "tool_calls" in message:
for tool_call in message["tool_calls"]:
tool_call_string = f"Tool: {tool_call.get('tool_name')} | Action: {tool_call.get('action_name')} | Args: {tool_call.get('arguments')} | Response: {tool_call.get('result')}"
tokens_batch += num_tokens_from_string(tool_call_string)
if tokens_current_history + tokens_batch < max_token_limit:
tokens_current_history += tokens_batch
trimmed_history.insert(0, message)
else:
break
return trimmed_history

View File

@@ -1,5 +1,6 @@
import os
import tempfile
import io
from langchain_community.vectorstores import FAISS
@@ -66,8 +67,37 @@ class FaissStore(BaseVectorStore):
def add_texts(self, *args, **kwargs):
return self.docsearch.add_texts(*args, **kwargs)
def save_local(self, *args, **kwargs):
return self.docsearch.save_local(*args, **kwargs)
def _save_to_storage(self):
"""
Save the FAISS index to storage using temporary directory pattern.
Works consistently for both local and S3 storage.
"""
with tempfile.TemporaryDirectory() as temp_dir:
self.docsearch.save_local(temp_dir)
faiss_path = os.path.join(temp_dir, "index.faiss")
pkl_path = os.path.join(temp_dir, "index.pkl")
with open(faiss_path, "rb") as f_faiss:
faiss_data = f_faiss.read()
with open(pkl_path, "rb") as f_pkl:
pkl_data = f_pkl.read()
storage_path = get_vectorstore(self.source_id)
self.storage.save_file(io.BytesIO(faiss_data), f"{storage_path}/index.faiss")
self.storage.save_file(io.BytesIO(pkl_data), f"{storage_path}/index.pkl")
return True
def save_local(self, path=None):
if path:
os.makedirs(path, exist_ok=True)
self.docsearch.save_local(path)
self._save_to_storage()
return True
def delete_index(self, *args, **kwargs):
return self.docsearch.delete(*args, **kwargs)
@@ -103,13 +133,17 @@ class FaissStore(BaseVectorStore):
return chunks
def add_chunk(self, text, metadata=None):
"""Add a new chunk and save to storage."""
metadata = metadata or {}
doc = Document(text=text, extra_info=metadata).to_langchain_format()
doc_id = self.docsearch.add_documents([doc])
self.save_local(self.path)
self._save_to_storage()
return doc_id
def delete_chunk(self, chunk_id):
"""Delete a chunk and save to storage."""
self.delete_index([chunk_id])
self.save_local(self.path)
self._save_to_storage()
return True

View File

@@ -0,0 +1,303 @@
import logging
from typing import List, Optional, Any, Dict
from application.core.settings import settings
from application.vectorstore.base import BaseVectorStore
from application.vectorstore.document_class import Document
class PGVectorStore(BaseVectorStore):
def __init__(
self,
source_id: str = "",
embeddings_key: str = "embeddings",
table_name: str = "documents",
vector_column: str = "embedding",
text_column: str = "text",
metadata_column: str = "metadata",
connection_string: str = None,
):
super().__init__()
# Store the source_id for use in add_chunk
self._source_id = str(source_id).replace("application/indexes/", "").rstrip("/")
self._embeddings_key = embeddings_key
self._table_name = table_name
self._vector_column = vector_column
self._text_column = text_column
self._metadata_column = metadata_column
self._embedding = self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key)
# Use provided connection string or fall back to settings
self._connection_string = connection_string or getattr(settings, 'PGVECTOR_CONNECTION_STRING', None)
if not self._connection_string:
raise ValueError(
"PostgreSQL connection string is required. "
"Set PGVECTOR_CONNECTION_STRING in settings or pass connection_string parameter."
)
try:
import psycopg2
from psycopg2.extras import Json
import pgvector.psycopg2
except ImportError:
raise ImportError(
"Could not import required packages. "
"Please install with `pip install psycopg2-binary pgvector`."
)
self._psycopg2 = psycopg2
self._Json = Json
self._pgvector = pgvector.psycopg2
self._connection = None
self._ensure_table_exists()
def _get_connection(self):
"""Get or create database connection"""
if self._connection is None or self._connection.closed:
self._connection = self._psycopg2.connect(self._connection_string)
# Register pgvector types
self._pgvector.register_vector(self._connection)
return self._connection
def _ensure_table_exists(self):
"""Create table and enable pgvector extension if they don't exist"""
conn = self._get_connection()
cursor = conn.cursor()
try:
# Enable pgvector extension
cursor.execute("CREATE EXTENSION IF NOT EXISTS vector;")
# Get embedding dimension
embedding_dim = getattr(self._embedding, 'dimension', 1536) # Default to OpenAI dimension
# Create table with vector column
create_table_query = f"""
CREATE TABLE IF NOT EXISTS {self._table_name} (
id SERIAL PRIMARY KEY,
{self._text_column} TEXT NOT NULL,
{self._vector_column} vector({embedding_dim}),
{self._metadata_column} JSONB,
source_id TEXT NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
"""
cursor.execute(create_table_query)
# Create index for vector similarity search
index_query = f"""
CREATE INDEX IF NOT EXISTS {self._table_name}_{self._vector_column}_idx
ON {self._table_name} USING ivfflat ({self._vector_column} vector_cosine_ops)
WITH (lists = 100);
"""
cursor.execute(index_query)
# Create index for source_id filtering
source_index_query = f"""
CREATE INDEX IF NOT EXISTS {self._table_name}_source_id_idx
ON {self._table_name} (source_id);
"""
cursor.execute(source_index_query)
conn.commit()
except Exception as e:
conn.rollback()
logging.error(f"Error creating table: {e}")
raise
finally:
cursor.close()
def search(self, question: str, k: int = 2, *args, **kwargs) -> List[Document]:
"""Search for similar documents using vector similarity"""
query_vector = self._embedding.embed_query(question)
conn = self._get_connection()
cursor = conn.cursor()
try:
# Use cosine distance for similarity search with proper vector formatting
search_query = f"""
SELECT {self._text_column}, {self._metadata_column},
({self._vector_column} <=> %s::vector) as distance
FROM {self._table_name}
WHERE source_id = %s
ORDER BY {self._vector_column} <=> %s::vector
LIMIT %s;
"""
cursor.execute(search_query, (query_vector, self._source_id, query_vector, k))
results = cursor.fetchall()
documents = []
for text, metadata, distance in results:
metadata = metadata or {}
documents.append(Document(page_content=text, metadata=metadata))
return documents
except Exception as e:
logging.error(f"Error searching documents: {e}", exc_info=True)
return []
finally:
cursor.close()
def add_texts(
self,
texts: List[str],
metadatas: Optional[List[Dict[str, Any]]] = None,
*args,
**kwargs,
) -> List[str]:
"""Add texts with their embeddings to the vector store"""
if not texts:
return []
embeddings = self._embedding.embed_documents(texts)
metadatas = metadatas or [{}] * len(texts)
conn = self._get_connection()
cursor = conn.cursor()
try:
insert_query = f"""
INSERT INTO {self._table_name} ({self._text_column}, {self._vector_column}, {self._metadata_column}, source_id)
VALUES (%s, %s, %s, %s)
RETURNING id;
"""
inserted_ids = []
for text, embedding, metadata in zip(texts, embeddings, metadatas):
cursor.execute(
insert_query,
(text, embedding, self._Json(metadata), self._source_id)
)
inserted_id = cursor.fetchone()[0]
inserted_ids.append(str(inserted_id))
conn.commit()
return inserted_ids
except Exception as e:
conn.rollback()
logging.error(f"Error adding texts: {e}")
raise
finally:
cursor.close()
def delete_index(self, *args, **kwargs):
"""Delete all documents for this source_id"""
conn = self._get_connection()
cursor = conn.cursor()
try:
delete_query = f"DELETE FROM {self._table_name} WHERE source_id = %s;"
cursor.execute(delete_query, (self._source_id,))
conn.commit()
except Exception as e:
conn.rollback()
logging.error(f"Error deleting index: {e}")
raise
finally:
cursor.close()
def save_local(self, *args, **kwargs):
"""No-op for PostgreSQL - data is already persisted"""
pass
def get_chunks(self) -> List[Dict[str, Any]]:
"""Get all chunks for this source_id"""
conn = self._get_connection()
cursor = conn.cursor()
try:
select_query = f"""
SELECT id, {self._text_column}, {self._metadata_column}
FROM {self._table_name}
WHERE source_id = %s;
"""
cursor.execute(select_query, (self._source_id,))
results = cursor.fetchall()
chunks = []
for doc_id, text, metadata in results:
chunks.append({
"doc_id": str(doc_id),
"text": text,
"metadata": metadata or {}
})
return chunks
except Exception as e:
logging.error(f"Error getting chunks: {e}")
return []
finally:
cursor.close()
def add_chunk(self, text: str, metadata: Optional[Dict[str, Any]] = None) -> str:
"""Add a single chunk to the vector store"""
metadata = metadata or {}
# Create a copy to avoid modifying the original metadata
final_metadata = metadata.copy()
# Ensure the source_id is in the metadata so the chunk can be found by filters
final_metadata["source_id"] = self._source_id
embeddings = self._embedding.embed_documents([text])
if not embeddings:
raise ValueError("Could not generate embedding for chunk")
conn = self._get_connection()
cursor = conn.cursor()
try:
insert_query = f"""
INSERT INTO {self._table_name} ({self._text_column}, {self._vector_column}, {self._metadata_column}, source_id)
VALUES (%s, %s, %s, %s)
RETURNING id;
"""
cursor.execute(
insert_query,
(text, embeddings[0], self._Json(final_metadata), self._source_id)
)
inserted_id = cursor.fetchone()[0]
conn.commit()
return str(inserted_id)
except Exception as e:
conn.rollback()
logging.error(f"Error adding chunk: {e}")
raise
finally:
cursor.close()
def delete_chunk(self, chunk_id: str) -> bool:
"""Delete a specific chunk by its ID"""
conn = self._get_connection()
cursor = conn.cursor()
try:
delete_query = f"DELETE FROM {self._table_name} WHERE id = %s AND source_id = %s;"
cursor.execute(delete_query, (int(chunk_id), self._source_id))
deleted_count = cursor.rowcount
conn.commit()
return deleted_count > 0
except Exception as e:
conn.rollback()
logging.error(f"Error deleting chunk: {e}")
return False
finally:
cursor.close()
def __del__(self):
"""Close database connection when object is destroyed"""
if hasattr(self, '_connection') and self._connection and not self._connection.closed:
self._connection.close()

View File

@@ -1,5 +1,7 @@
import logging
from application.vectorstore.base import BaseVectorStore
from application.core.settings import settings
from application.vectorstore.document_class import Document
class QdrantStore(BaseVectorStore):
@@ -7,18 +9,22 @@ class QdrantStore(BaseVectorStore):
from qdrant_client import models
from langchain_community.vectorstores.qdrant import Qdrant
# Store the source_id for use in add_chunk
self._source_id = str(source_id).replace("application/indexes/", "").rstrip("/")
self._filter = models.Filter(
must=[
models.FieldCondition(
key="metadata.source_id",
match=models.MatchValue(value=source_id.replace("application/indexes/", "").rstrip("/")),
match=models.MatchValue(value=self._source_id),
)
]
)
embedding=self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key)
self._docsearch = Qdrant.construct_instance(
["TEXT_TO_OBTAIN_EMBEDDINGS_DIMENSION"],
embedding=self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key),
embedding=embedding,
collection_name=settings.QDRANT_COLLECTION_NAME,
location=settings.QDRANT_LOCATION,
url=settings.QDRANT_URL,
@@ -32,6 +38,32 @@ class QdrantStore(BaseVectorStore):
path=settings.QDRANT_PATH,
distance_func=settings.QDRANT_DISTANCE_FUNC,
)
try:
collections = self._docsearch.client.get_collections()
collection_exists = settings.QDRANT_COLLECTION_NAME in [
collection.name for collection in collections.collections
]
if not collection_exists:
self._docsearch.client.recreate_collection(
collection_name=settings.QDRANT_COLLECTION_NAME,
vectors_config=models.VectorParams(size=embedding.client[1].word_embedding_dimension, distance=models.Distance.COSINE),
)
# Ensure the required index exists for metadata.source_id
try:
self._docsearch.client.create_payload_index(
collection_name=settings.QDRANT_COLLECTION_NAME,
field_name="metadata.source_id",
field_schema=models.PayloadSchemaType.KEYWORD,
)
except Exception as index_error:
# Index might already exist, which is fine
if "already exists" not in str(index_error).lower():
logging.warning(f"Could not create index for metadata.source_id: {index_error}")
except Exception as e:
logging.warning(f"Could not check for collection: {e}")
def search(self, *args, **kwargs):
return self._docsearch.similarity_search(filter=self._filter, *args, **kwargs)
@@ -46,3 +78,59 @@ class QdrantStore(BaseVectorStore):
return self._docsearch.client.delete(
collection_name=settings.QDRANT_COLLECTION_NAME, points_selector=self._filter
)
def get_chunks(self):
try:
chunks = []
offset = None
while True:
records, offset = self._docsearch.client.scroll(
collection_name=settings.QDRANT_COLLECTION_NAME,
scroll_filter=self._filter,
limit=10,
with_payload=True,
with_vectors=False,
offset=offset,
)
for record in records:
doc_id = record.id
text = record.payload.get("page_content")
metadata = record.payload.get("metadata")
chunks.append(
{"doc_id": doc_id, "text": text, "metadata": metadata}
)
if offset is None:
break
return chunks
except Exception as e:
logging.error(f"Error getting chunks: {e}", exc_info=True)
return []
def add_chunk(self, text, metadata=None):
import uuid
metadata = metadata or {}
# Create a copy to avoid modifying the original metadata
final_metadata = metadata.copy()
# Ensure the source_id is in the metadata so the chunk can be found by filters
final_metadata["source_id"] = self._source_id
doc = Document(page_content=text, metadata=final_metadata)
# Generate a unique ID for the document
doc_id = str(uuid.uuid4())
doc.id = doc_id
doc_ids = self._docsearch.add_documents([doc])
return doc_ids[0] if doc_ids else doc_id
def delete_chunk(self, chunk_id):
try:
self._docsearch.client.delete(
collection_name=settings.QDRANT_COLLECTION_NAME,
points_selector=[chunk_id],
)
return True
except Exception as e:
logging.error(f"Error deleting chunk: {e}", exc_info=True)
return False

View File

@@ -3,6 +3,7 @@ from application.vectorstore.elasticsearch import ElasticsearchStore
from application.vectorstore.milvus import MilvusStore
from application.vectorstore.mongodb import MongoDBVectorStore
from application.vectorstore.qdrant import QdrantStore
from application.vectorstore.pgvector import PGVectorStore
class VectorCreator:
@@ -12,6 +13,7 @@ class VectorCreator:
"mongodb": MongoDBVectorStore,
"qdrant": QdrantStore,
"milvus": MilvusStore,
"pgvector": PGVectorStore
}
@classmethod

View File

@@ -6,6 +6,7 @@ import os
import shutil
import string
import tempfile
from typing import Any, Dict
import zipfile
from collections import Counter
@@ -16,11 +17,12 @@ from bson.dbref import DBRef
from bson.objectid import ObjectId
from application.agents.agent_creator import AgentCreator
from application.api.answer.routes import get_prompt
from application.api.answer.services.stream_processor import get_prompt
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.parser.chunking import Chunker
from application.parser.connectors.connector_creator import ConnectorCreator
from application.parser.embedding_pipeline import embed_and_store_documents
from application.parser.file.bulk import SimpleDirectoryReader
from application.parser.remote.remote_creator import RemoteCreator
@@ -35,17 +37,22 @@ db = mongo[settings.MONGO_DB_NAME]
sources_collection = db["sources"]
# Constants
MIN_TOKENS = 150
MAX_TOKENS = 1250
RECURSION_DEPTH = 2
# Define a function to extract metadata from a given filename.
def metadata_from_filename(title):
return {"title": title}
# Define a function to generate a random string of a given length.
def generate_random_string(length):
return "".join([string.ascii_letters[i % 52] for i in range(length)])
@@ -68,7 +75,6 @@ def extract_zip_recursive(zip_path, extract_to, current_depth=0, max_depth=5):
if current_depth > max_depth:
logging.warning(f"Reached maximum recursion depth of {max_depth}")
return
try:
with zipfile.ZipFile(zip_path, "r") as zip_ref:
zip_ref.extractall(extract_to)
@@ -76,12 +82,13 @@ def extract_zip_recursive(zip_path, extract_to, current_depth=0, max_depth=5):
except Exception as e:
logging.error(f"Error extracting zip file {zip_path}: {e}", exc_info=True)
return
# Check for nested zip files and extract them
for root, dirs, files in os.walk(extract_to):
for file in files:
if file.endswith(".zip"):
# If a nested zip file is found, extract it recursively
file_path = os.path.join(root, file)
extract_zip_recursive(file_path, root, current_depth + 1, max_depth)
@@ -98,11 +105,23 @@ def download_file(url, params, dest_path):
def upload_index(full_path, file_data):
files = None
try:
if settings.VECTOR_STORE == "faiss":
faiss_path = full_path + "/index.faiss"
pkl_path = full_path + "/index.pkl"
if not os.path.exists(faiss_path):
logging.error(f"FAISS index file not found: {faiss_path}")
raise FileNotFoundError(f"FAISS index file not found: {faiss_path}")
if not os.path.exists(pkl_path):
logging.error(f"FAISS pickle file not found: {pkl_path}")
raise FileNotFoundError(f"FAISS pickle file not found: {pkl_path}")
files = {
"file_faiss": open(full_path + "/index.faiss", "rb"),
"file_pkl": open(full_path + "/index.pkl", "rb"),
"file_faiss": open(faiss_path, "rb"),
"file_pkl": open(pkl_path, "rb"),
}
response = requests.post(
urljoin(settings.API_URL, "/api/upload_index"),
@@ -114,11 +133,11 @@ def upload_index(full_path, file_data):
urljoin(settings.API_URL, "/api/upload_index"), data=file_data
)
response.raise_for_status()
except requests.RequestException as e:
except (requests.RequestException, FileNotFoundError) as e:
logging.error(f"Error uploading index: {e}")
raise
finally:
if settings.VECTOR_STORE == "faiss":
if settings.VECTOR_STORE == "faiss" and files is not None:
for file in files.values():
file.close()
@@ -139,7 +158,7 @@ def run_agent_logic(agent_config, input_data):
user_api_key = agent_config["key"]
agent_type = agent_config.get("agent_type", "classic")
decoded_token = {"sub": agent_config.get("user")}
prompt = get_prompt(prompt_id)
prompt = get_prompt(prompt_id, db["prompts"])
agent = AgentCreator.create_agent(
agent_type,
endpoint="webhook",
@@ -178,7 +197,6 @@ def run_agent_logic(agent_config, input_data):
tool_calls.extend(line["tool_calls"])
elif "thought" in line:
thought += line["thought"]
result = {
"answer": response_full,
"sources": source_log_docs,
@@ -193,8 +211,11 @@ def run_agent_logic(agent_config, input_data):
# Define the main function for ingesting and processing documents.
def ingest_worker(
self, directory, formats, job_name, filename, user, dir_name=None, user_dir=None, retriever="classic"
self, directory, formats, job_name, file_path, filename, user,
retriever="classic"
):
"""
Ingest and process documents.
@@ -204,10 +225,9 @@ def ingest_worker(
directory (str): Specifies the directory for ingesting ('inputs' or 'temp').
formats (list of str): List of file extensions to consider for ingestion (e.g., [".rst", ".md"]).
job_name (str): Name of the job for this ingestion task (original, unsanitized).
filename (str): Name of the file to be ingested.
file_path (str): Complete file path to use consistently throughout the pipeline.
filename (str): Original unsanitized filename provided by the user.
user (str): Identifier for the user initiating the ingestion (original, unsanitized).
dir_name (str, optional): Sanitized directory name for filesystem operations.
user_dir (str, optional): Sanitized user ID for filesystem operations.
retriever (str): Type of retriever to use for processing the documents.
Returns:
@@ -218,38 +238,59 @@ def ingest_worker(
limit = None
exclude = True
sample = False
storage = StorageCreator.get_storage()
full_path = os.path.join(directory, user_dir, dir_name)
source_file_path = os.path.join(full_path, filename)
logging.info(f"Ingest file: {full_path}", extra={"user": user, "job": job_name})
logging.info(f"Ingest path: {file_path}", extra={"user": user, "job": job_name})
# Create temporary working directory
with tempfile.TemporaryDirectory() as temp_dir:
try:
os.makedirs(temp_dir, exist_ok=True)
# Download file from storage to temp directory
temp_file_path = os.path.join(temp_dir, filename)
file_data = storage.get_file(source_file_path)
if storage.is_directory(file_path):
# Handle directory case
logging.info(f"Processing directory: {file_path}")
files_list = storage.list_files(file_path)
for storage_file_path in files_list:
if storage.is_directory(storage_file_path):
continue
# Create relative path structure in temp directory
rel_path = os.path.relpath(storage_file_path, file_path)
local_file_path = os.path.join(temp_dir, rel_path)
os.makedirs(os.path.dirname(local_file_path), exist_ok=True)
# Download file
try:
file_data = storage.get_file(storage_file_path)
with open(local_file_path, "wb") as f:
f.write(file_data.read())
except Exception as e:
logging.error(f"Error downloading file {storage_file_path}: {e}")
continue
else:
# Handle single file case
temp_filename = os.path.basename(file_path)
temp_file_path = os.path.join(temp_dir, temp_filename)
file_data = storage.get_file(file_path)
with open(temp_file_path, "wb") as f:
f.write(file_data.read())
with open(temp_file_path, "wb") as f:
f.write(file_data.read())
# Handle zip files
if temp_filename.endswith(".zip"):
logging.info(f"Extracting zip file: {temp_filename}")
extract_zip_recursive(
temp_file_path, temp_dir, current_depth=0, max_depth=RECURSION_DEPTH
)
self.update_state(state="PROGRESS", meta={"current": 1})
# Handle zip files
if filename.endswith(".zip"):
logging.info(f"Extracting zip file: {filename}")
extract_zip_recursive(
temp_file_path, temp_dir, current_depth=0, max_depth=RECURSION_DEPTH
)
if sample:
logging.info(f"Sample mode enabled. Using {limit} documents.")
reader = SimpleDirectoryReader(
input_dir=temp_dir,
input_files=input_files,
@@ -259,6 +300,9 @@ def ingest_worker(
file_metadata=metadata_from_filename,
)
raw_docs = reader.load_data()
directory_structure = getattr(reader, 'directory_structure', {})
logging.info(f"Directory structure from reader: {directory_structure}")
chunker = Chunker(
chunking_strategy="classic_chunk",
@@ -285,22 +329,21 @@ def ingest_worker(
for i in range(min(5, len(raw_docs))):
logging.info(f"Sample document {i}: {raw_docs[i]}")
file_data = {
"name": job_name, # Use original job_name
"name": job_name,
"file": filename,
"user": user, # Use original user
"user": user,
"tokens": tokens,
"retriever": retriever,
"id": str(id),
"type": "local",
"original_file_path": source_file_path,
"file_path": file_path,
"directory_structure": json.dumps(directory_structure),
}
upload_index(vector_store_path, file_data)
except Exception as e:
logging.error(f"Error in ingest_worker: {e}", exc_info=True)
raise
return {
"directory": directory,
"formats": formats,
@@ -311,6 +354,252 @@ def ingest_worker(
}
def reingest_source_worker(self, source_id, user):
"""
Re-ingestion worker that handles incremental updates by:
1. Adding chunks from newly added files
2. Removing chunks from deleted files
Args:
self: Task instance
source_id: ID of the source to re-ingest
user: User identifier
Returns:
dict: Information about the re-ingestion task
"""
try:
from application.vectorstore.vector_creator import VectorCreator
self.update_state(state="PROGRESS", meta={"current": 10, "status": "Initializing re-ingestion scan"})
source = sources_collection.find_one({"_id": ObjectId(source_id), "user": user})
if not source:
raise ValueError(f"Source {source_id} not found or access denied")
storage = StorageCreator.get_storage()
source_file_path = source.get("file_path", "")
self.update_state(state="PROGRESS", meta={"current": 20, "status": "Scanning current files"})
with tempfile.TemporaryDirectory() as temp_dir:
# Download all files from storage to temp directory, preserving directory structure
if storage.is_directory(source_file_path):
files_list = storage.list_files(source_file_path)
for storage_file_path in files_list:
if storage.is_directory(storage_file_path):
continue
rel_path = os.path.relpath(storage_file_path, source_file_path)
local_file_path = os.path.join(temp_dir, rel_path)
os.makedirs(os.path.dirname(local_file_path), exist_ok=True)
# Download file
try:
file_data = storage.get_file(storage_file_path)
with open(local_file_path, "wb") as f:
f.write(file_data.read())
except Exception as e:
logging.error(f"Error downloading file {storage_file_path}: {e}")
continue
reader = SimpleDirectoryReader(
input_dir=temp_dir,
recursive=True,
required_exts=[
".rst", ".md", ".pdf", ".txt", ".docx", ".csv", ".epub",
".html", ".mdx", ".json", ".xlsx", ".pptx", ".png",
".jpg", ".jpeg",
],
exclude_hidden=True,
file_metadata=metadata_from_filename,
)
reader.load_data()
directory_structure = reader.directory_structure
logging.info(f"Directory structure built with token counts: {directory_structure}")
try:
old_directory_structure = source.get("directory_structure") or {}
if isinstance(old_directory_structure, str):
try:
old_directory_structure = json.loads(old_directory_structure)
except Exception:
old_directory_structure = {}
def _flatten_directory_structure(struct, prefix=""):
files = set()
if isinstance(struct, dict):
for name, meta in struct.items():
current_path = os.path.join(prefix, name) if prefix else name
if isinstance(meta, dict) and ("type" in meta and "size_bytes" in meta):
files.add(current_path)
elif isinstance(meta, dict):
files |= _flatten_directory_structure(meta, current_path)
return files
old_files = _flatten_directory_structure(old_directory_structure)
new_files = _flatten_directory_structure(directory_structure)
added_files = sorted(new_files - old_files)
removed_files = sorted(old_files - new_files)
if added_files:
logging.info(f"Files added since last ingest: {added_files}")
else:
logging.info("No files added since last ingest.")
if removed_files:
logging.info(f"Files removed since last ingest: {removed_files}")
else:
logging.info("No files removed since last ingest.")
except Exception as e:
logging.error(f"Error comparing directory structures: {e}", exc_info=True)
added_files = []
removed_files = []
try:
if not added_files and not removed_files:
logging.info("No changes detected.")
return {
"source_id": source_id,
"user": user,
"status": "no_changes",
"added_files": [],
"removed_files": [],
}
vector_store = VectorCreator.create_vectorstore(
settings.VECTOR_STORE,
source_id,
settings.EMBEDDINGS_KEY,
)
self.update_state(state="PROGRESS", meta={"current": 40, "status": "Processing file changes"})
# 1) Delete chunks from removed files
deleted = 0
if removed_files:
try:
for ch in vector_store.get_chunks() or []:
metadata = ch.get("metadata", {}) if isinstance(ch, dict) else getattr(ch, "metadata", {})
raw_source = metadata.get("source")
source_file = str(raw_source) if raw_source else ""
if source_file in removed_files:
cid = ch.get("doc_id")
if cid:
try:
vector_store.delete_chunk(cid)
deleted += 1
except Exception as de:
logging.error(f"Failed deleting chunk {cid}: {de}")
logging.info(f"Deleted {deleted} chunks from {len(removed_files)} removed files")
except Exception as e:
logging.error(f"Error during deletion of removed file chunks: {e}", exc_info=True)
# 2) Add chunks from new files
added = 0
if added_files:
try:
# Build list of local files for added files only
added_local_files = []
for rel_path in added_files:
local_path = os.path.join(temp_dir, rel_path)
if os.path.isfile(local_path):
added_local_files.append(local_path)
if added_local_files:
reader_new = SimpleDirectoryReader(
input_files=added_local_files,
exclude_hidden=True,
errors="ignore",
file_metadata=metadata_from_filename,
)
raw_docs_new = reader_new.load_data()
chunker_new = Chunker(
chunking_strategy="classic_chunk",
max_tokens=MAX_TOKENS,
min_tokens=MIN_TOKENS,
duplicate_headers=False,
)
chunked_new = chunker_new.chunk(documents=raw_docs_new)
for file_path, token_count in reader_new.file_token_counts.items():
try:
rel_path = os.path.relpath(file_path, start=temp_dir)
path_parts = rel_path.split(os.sep)
current_dir = directory_structure
for part in path_parts[:-1]:
if part in current_dir and isinstance(current_dir[part], dict):
current_dir = current_dir[part]
else:
break
filename = path_parts[-1]
if filename in current_dir and isinstance(current_dir[filename], dict):
current_dir[filename]["token_count"] = token_count
logging.info(f"Updated token count for {rel_path}: {token_count}")
except Exception as e:
logging.warning(f"Could not update token count for {file_path}: {e}")
for d in chunked_new:
meta = dict(d.extra_info or {})
try:
raw_src = meta.get("source")
if isinstance(raw_src, str) and os.path.isabs(raw_src):
meta["source"] = os.path.relpath(raw_src, start=temp_dir)
except Exception:
pass
vector_store.add_chunk(d.text, metadata=meta)
added += 1
logging.info(f"Added {added} chunks from {len(added_files)} new files")
except Exception as e:
logging.error(f"Error during ingestion of new files: {e}", exc_info=True)
# 3) Update source directory structure timestamp
try:
total_tokens = sum(reader.file_token_counts.values())
sources_collection.update_one(
{"_id": ObjectId(source_id)},
{
"$set": {
"directory_structure": directory_structure,
"date": datetime.datetime.now(),
"tokens": total_tokens
}
},
)
except Exception as e:
logging.error(f"Error updating directory_structure in DB: {e}", exc_info=True)
self.update_state(state="PROGRESS", meta={"current": 100, "status": "Re-ingestion completed"})
return {
"source_id": source_id,
"user": user,
"status": "completed",
"added_files": added_files,
"removed_files": removed_files,
"chunks_added": added,
"chunks_deleted": deleted,
}
except Exception as e:
logging.error(f"Error while processing file changes: {e}", exc_info=True)
raise
except Exception as e:
logging.error(f"Error in reingest_source_worker: {e}", exc_info=True)
raise
def remote_worker(
self,
source_data,
@@ -326,7 +615,6 @@ def remote_worker(
full_path = os.path.join(directory, user, name_job)
if not os.path.exists(full_path):
os.makedirs(full_path)
self.update_state(state="PROGRESS", meta={"current": 1})
try:
logging.info("Initializing remote loader with type: %s", loader)
@@ -353,7 +641,6 @@ def remote_worker(
raise ValueError("doc_id must be provided for sync operation.")
id = ObjectId(doc_id)
embed_and_store_documents(docs, full_path, id, self)
self.update_state(state="PROGRESS", meta={"current": 100})
file_data = {
@@ -364,18 +651,18 @@ def remote_worker(
"id": str(id),
"type": loader,
"remote_data": source_data,
"sync_frequency": sync_frequency,
"sync_frequency": sync_frequency
}
upload_index(full_path, file_data)
if operation_mode == "sync":
file_data["last_sync"] = datetime.datetime.now()
upload_index(full_path, file_data)
except Exception as e:
logging.error("Error in remote_worker task: %s", str(e), exc_info=True)
raise
finally:
if os.path.exists(full_path):
shutil.rmtree(full_path)
logging.info("remote_worker task completed successfully")
return {"urls": source_data, "name_job": name_job, "user": user, "limited": False}
@@ -425,10 +712,9 @@ def sync_worker(self, frequency):
self, source_data, name, user, source_type, frequency, retriever, doc_id
)
sync_counts["total_sync_count"] += 1
sync_counts[
sync_counts[
"sync_success" if resp["status"] == "success" else "sync_failure"
] += 1
return {
key: sync_counts[key]
for key in ["total_sync_count", "sync_success", "sync_failure"]
@@ -463,11 +749,15 @@ def attachment_worker(self, file_info, user):
input_files=[local_path], exclude_hidden=True, errors="ignore"
)
.load_data()[0]
.text,
.text,
)
token_count = num_tokens_from_string(content)
if token_count > 100000:
content = content[:250000]
token_count = num_tokens_from_string(content)
self.update_state(
state="PROGRESS", meta={"current": 80, "status": "Storing in database"}
)
@@ -503,7 +793,6 @@ def attachment_worker(self, file_info, user):
"mime_type": mime_type,
"metadata": metadata,
}
except Exception as e:
logging.error(
f"Error processing file {filename}: {e}",
@@ -539,7 +828,6 @@ def agent_webhook_worker(self, agent_id, payload):
except Exception as e:
logging.error(f"Error processing agent webhook: {e}", exc_info=True)
return {"status": "error", "error": str(e)}
self.update_state(state="PROGRESS", meta={"current": 50})
try:
result = run_agent_logic(agent_config, input_data)
@@ -552,3 +840,174 @@ def agent_webhook_worker(self, agent_id, payload):
f"Webhook processed for agent {agent_id}", extra={"agent_id": agent_id}
)
return {"status": "success", "result": result}
def ingest_connector(
self,
job_name: str,
user: str,
source_type: str,
session_token=None,
file_ids=None,
folder_ids=None,
recursive=True,
retriever: str = "classic",
operation_mode: str = "upload",
doc_id=None,
sync_frequency: str = "never",
) -> Dict[str, Any]:
"""
Ingestion for internal knowledge bases (GoogleDrive, etc.).
Args:
job_name: Name of the ingestion job
user: User identifier
source_type: Type of remote source ("google_drive", "dropbox", etc.)
session_token: Authentication token for the service
file_ids: List of file IDs to download
folder_ids: List of folder IDs to download
recursive: Whether to recursively download folders
retriever: Type of retriever to use
operation_mode: "upload" for initial ingestion, "sync" for incremental sync
doc_id: Document ID for sync operations (required when operation_mode="sync")
sync_frequency: How often to sync ("never", "daily", "weekly", "monthly")
"""
logging.info(f"Starting remote ingestion from {source_type} for user: {user}, job: {job_name}")
self.update_state(state="PROGRESS", meta={"current": 1})
with tempfile.TemporaryDirectory() as temp_dir:
try:
# Step 1: Initialize the appropriate loader
self.update_state(state="PROGRESS", meta={"current": 10, "status": "Initializing connector"})
if not session_token:
raise ValueError(f"{source_type} connector requires session_token")
if not ConnectorCreator.is_supported(source_type):
raise ValueError(f"Unsupported connector type: {source_type}. Supported types: {ConnectorCreator.get_supported_connectors()}")
remote_loader = ConnectorCreator.create_connector(source_type, session_token)
# Create a clean config for storage
api_source_config = {
"file_ids": file_ids or [],
"folder_ids": folder_ids or [],
"recursive": recursive
}
# Step 2: Download files to temp directory
self.update_state(state="PROGRESS", meta={"current": 20, "status": "Downloading files"})
download_info = remote_loader.download_to_directory(
temp_dir,
api_source_config
)
if download_info.get("empty_result", False) or not download_info.get("files_downloaded", 0):
logging.warning(f"No files were downloaded from {source_type}")
# Create empty result directly instead of calling a separate method
return {
"name": job_name,
"user": user,
"tokens": 0,
"type": source_type,
"source_config": api_source_config,
"directory_structure": "{}",
}
# Step 3: Use SimpleDirectoryReader to process downloaded files
self.update_state(state="PROGRESS", meta={"current": 40, "status": "Processing files"})
reader = SimpleDirectoryReader(
input_dir=temp_dir,
recursive=True,
required_exts=[
".rst", ".md", ".pdf", ".txt", ".docx", ".csv", ".epub",
".html", ".mdx", ".json", ".xlsx", ".pptx", ".png",
".jpg", ".jpeg",
],
exclude_hidden=True,
file_metadata=metadata_from_filename,
)
raw_docs = reader.load_data()
directory_structure = getattr(reader, 'directory_structure', {})
# Step 4: Process documents (chunking, embedding, etc.)
self.update_state(state="PROGRESS", meta={"current": 60, "status": "Processing documents"})
chunker = Chunker(
chunking_strategy="classic_chunk",
max_tokens=MAX_TOKENS,
min_tokens=MIN_TOKENS,
duplicate_headers=False,
)
raw_docs = chunker.chunk(documents=raw_docs)
# Preserve source information in document metadata
for doc in raw_docs:
if hasattr(doc, 'extra_info') and doc.extra_info:
source = doc.extra_info.get('source')
if source and os.path.isabs(source):
# Convert absolute path to relative path
doc.extra_info['source'] = os.path.relpath(source, start=temp_dir)
docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
if operation_mode == "upload":
id = ObjectId()
elif operation_mode == "sync":
if not doc_id or not ObjectId.is_valid(doc_id):
logging.error("Invalid doc_id provided for sync operation: %s", doc_id)
raise ValueError("doc_id must be provided for sync operation.")
id = ObjectId(doc_id)
else:
raise ValueError(f"Invalid operation_mode: {operation_mode}")
vector_store_path = os.path.join(temp_dir, "vector_store")
os.makedirs(vector_store_path, exist_ok=True)
self.update_state(state="PROGRESS", meta={"current": 80, "status": "Storing documents"})
embed_and_store_documents(docs, vector_store_path, id, self)
tokens = count_tokens_docs(docs)
# Step 6: Upload index files
file_data = {
"user": user,
"name": job_name,
"tokens": tokens,
"retriever": retriever,
"id": str(id),
"type": "connector",
"remote_data": json.dumps({
"provider": source_type,
**api_source_config
}),
"directory_structure": json.dumps(directory_structure),
"sync_frequency": sync_frequency
}
if operation_mode == "sync":
file_data["last_sync"] = datetime.datetime.now()
else:
file_data["last_sync"] = datetime.datetime.now()
upload_index(vector_store_path, file_data)
# Ensure we mark the task as complete
self.update_state(state="PROGRESS", meta={"current": 100, "status": "Complete"})
logging.info(f"Remote ingestion completed: {job_name}")
return {
"user": user,
"name": job_name,
"tokens": tokens,
"type": source_type,
"id": str(id),
"status": "complete"
}
except Exception as e:
logging.error(f"Error during remote ingestion: {e}", exc_info=True)
raise

View File

@@ -0,0 +1,74 @@
name: docsgpt-oss
services:
frontend:
image: arc53/docsgpt-fe:develop
environment:
- VITE_API_HOST=http://localhost:7091
- VITE_API_STREAMING=$VITE_API_STREAMING
ports:
- "5173:5173"
depends_on:
- backend
backend:
user: root
image: arc53/docsgpt:develop
environment:
- API_KEY=$API_KEY
- EMBEDDINGS_KEY=$API_KEY
- LLM_PROVIDER=$LLM_PROVIDER
- LLM_NAME=$LLM_NAME
- CELERY_BROKER_URL=redis://redis:6379/0
- CELERY_RESULT_BACKEND=redis://redis:6379/1
- MONGO_URI=mongodb://mongo:27017/docsgpt
- CACHE_REDIS_URL=redis://redis:6379/2
- OPENAI_BASE_URL=$OPENAI_BASE_URL
ports:
- "7091:7091"
volumes:
- ../application/indexes:/app/indexes
- ../application/inputs:/app/inputs
- ../application/vectors:/app/vectors
depends_on:
- redis
- mongo
worker:
user: root
image: arc53/docsgpt:develop
command: celery -A application.app.celery worker -l INFO -B
environment:
- API_KEY=$API_KEY
- EMBEDDINGS_KEY=$API_KEY
- LLM_PROVIDER=$LLM_PROVIDER
- LLM_NAME=$LLM_NAME
- CELERY_BROKER_URL=redis://redis:6379/0
- CELERY_RESULT_BACKEND=redis://redis:6379/1
- MONGO_URI=mongodb://mongo:27017/docsgpt
- API_URL=http://backend:7091
- CACHE_REDIS_URL=redis://redis:6379/2
volumes:
- ../application/indexes:/app/indexes
- ../application/inputs:/app/inputs
- ../application/vectors:/app/vectors
depends_on:
- redis
- mongo
redis:
image: redis:6-alpine
ports:
- 6379:6379
mongo:
image: mongo:6
ports:
- 27017:27017
volumes:
- mongodb_data_container:/data/db
volumes:
mongodb_data_container:

View File

@@ -37,33 +37,33 @@ While modifying `settings.py` offers more flexibility, it's generally recommende
Here are some of the most fundamental settings you'll likely want to configure:
- **`LLM_PROVIDER`**: This setting determines which Large Language Model (LLM) provider DocsGPT will use. It tells DocsGPT which API to interact with.
- **`LLM_PROVIDER`**: This setting determines which Large Language Model (LLM) provider DocsGPT will use. It tells DocsGPT which API to interact with.
- **Common values:**
- `docsgpt`: Use the DocsGPT Public API Endpoint (simple and free, as offered in `setup.sh` option 1).
- `openai`: Use OpenAI's API (requires an API key).
- `google`: Use Google's Vertex AI or Gemini models.
- `anthropic`: Use Anthropic's Claude models.
- `groq`: Use Groq's models.
- `huggingface`: Use HuggingFace Inference API.
- `azure_openai`: Use Azure OpenAI Service.
- `openai` (when using local inference engines like Ollama, Llama.cpp, TGI, etc.): This signals DocsGPT to use an OpenAI-compatible API format, even if the actual LLM is running locally.
- **Common values:**
- `docsgpt`: Use the DocsGPT Public API Endpoint (simple and free, as offered in `setup.sh` option 1).
- `openai`: Use OpenAI's API (requires an API key).
- `google`: Use Google's Vertex AI or Gemini models.
- `anthropic`: Use Anthropic's Claude models.
- `groq`: Use Groq's models.
- `huggingface`: Use HuggingFace Inference API.
- `azure_openai`: Use Azure OpenAI Service.
- `openai` (when using local inference engines like Ollama, Llama.cpp, TGI, etc.): This signals DocsGPT to use an OpenAI-compatible API format, even if the actual LLM is running locally.
- **`LLM_NAME`**: Specifies the specific model to use from the chosen LLM provider. The available models depend on the `LLM_PROVIDER` you've selected.
- **`LLM_NAME`**: Specifies the specific model to use from the chosen LLM provider. The available models depend on the `LLM_PROVIDER` you've selected.
- **Examples:**
- For `LLM_PROVIDER=openai`: `gpt-4o`
- For `LLM_PROVIDER=google`: `gemini-2.0-flash`
- For local models (e.g., Ollama): `llama3.2:1b` (or any model name available in your setup).
- **Examples:**
- For `LLM_PROVIDER=openai`: `gpt-4o`
- For `LLM_PROVIDER=google`: `gemini-2.0-flash`
- For local models (e.g., Ollama): `llama3.2:1b` (or any model name available in your setup).
- **`EMBEDDINGS_NAME`**: This setting defines which embedding model DocsGPT will use to generate vector embeddings for your documents. Embeddings are numerical representations of text that allow DocsGPT to understand the semantic meaning of your documents for efficient search and retrieval.
- **`EMBEDDINGS_NAME`**: This setting defines which embedding model DocsGPT will use to generate vector embeddings for your documents. Embeddings are numerical representations of text that allow DocsGPT to understand the semantic meaning of your documents for efficient search and retrieval.
- **Default value:** `huggingface_sentence-transformers/all-mpnet-base-v2` (a good general-purpose embedding model).
- **Other options:** You can explore other embedding models from Hugging Face Sentence Transformers or other providers if needed.
- **Default value:** `huggingface_sentence-transformers/all-mpnet-base-v2` (a good general-purpose embedding model).
- **Other options:** You can explore other embedding models from Hugging Face Sentence Transformers or other providers if needed.
- **`API_KEY`**: Required for most cloud-based LLM providers. This is your authentication key to access the LLM provider's API. You'll need to obtain this key from your chosen provider's platform.
- **`API_KEY`**: Required for most cloud-based LLM providers. This is your authentication key to access the LLM provider's API. You'll need to obtain this key from your chosen provider's platform.
- **`OPENAI_BASE_URL`**: Specifically used when `LLM_PROVIDER` is set to `openai` but you are connecting to a local inference engine (like Ollama, Llama.cpp, etc.) that exposes an OpenAI-compatible API. This setting tells DocsGPT where to find your local LLM server.
- **`OPENAI_BASE_URL`**: Specifically used when `LLM_PROVIDER` is set to `openai` but you are connecting to a local inference engine (like Ollama, Llama.cpp, etc.) that exposes an OpenAI-compatible API. This setting tells DocsGPT where to find your local LLM server.
## Configuration Examples
@@ -93,51 +93,82 @@ OPENAI_BASE_URL=http://host.docker.internal:11434/v1 # Default Ollama API URL wi
EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2 # You can also run embeddings locally if needed
```
In this case, even though you are using Ollama locally, `LLM_PROVIDER` is set to `openai` because Ollama (and many other local inference engines) are designed to be API-compatible with OpenAI. `OPENAI_BASE_URL` points DocsGPT to the local Ollama server.
In this case, even though you are using Ollama locally, `LLM_PROVIDER` is set to `openai` because Ollama (and many other local inference engines) are designed to be API-compatible with OpenAI. `OPENAI_BASE_URL` points DocsGPT to the local Ollama server.
## Authentication Settings
DocsGPT includes a JWT (JSON Web Token) based authentication feature for managing sessions or securing local deployments while allowing access.
- **`AUTH_TYPE`**: This setting in your `.env` file or `settings.py` determines the authentication method.
- **Possible values:**
- `None` (or not set): No authentication is used.
- `simple_jwt`: A single, long-lived JWT token is generated and used for all authenticated requests. This is useful for securing a local deployment with a shared secret.
- `session_jwt`: Unique JWT tokens are generated for sessions, typically for individual users or temporary access.
- If `AUTH_TYPE` is set to `simple_jwt` or `session_jwt`, then a `JWT_SECRET_KEY` is required.
- **`JWT_SECRET_KEY`**: This is a crucial secret key used to sign and verify JWTs.
- It can be set directly in your `.env` file or `settings.py`.
- **Automatic Key Generation**: If `AUTH_TYPE` is `simple_jwt` or `session_jwt` and `JWT_SECRET_KEY` is _not_ set in your environment variables or `settings.py`, DocsGPT will attempt to:
1. Read the key from a file named `.jwt_secret_key` in the project's root directory.
2. If the file doesn't exist, it will generate a new 32-byte random key, save it to `.jwt_secret_key`, and use it for the session. This ensures that the key persists across application restarts.
- **Security Note**: It's vital to keep this key secure. If you set it manually, choose a strong, random string.
### `AUTH_TYPE` Overview
**How it works:**
The `AUTH_TYPE` setting in your `.env` file or `settings.py` determines the authentication method used by DocsGPT. This allows you to control how users authenticate with your DocsGPT instance.
- When `AUTH_TYPE` is set to `simple_jwt`, a token is generated at startup (if not already present or configured) and printed to the console. This token should be included in the `Authorization` header of your API requests as a Bearer token (e.g., `Authorization: Bearer YOUR_SIMPLE_JWT_TOKEN`).
- When `AUTH_TYPE` is set to `session_jwt`:
- Clients can request a new token from the `/api/generate_token` endpoint.
- This token should then be included in the `Authorization` header for subsequent requests.
- The backend verifies the JWT token provided in the `Authorization` header for protected routes.
- The `/api/config` endpoint can be used to check the current `auth_type` and whether authentication is required.
| Value | Description |
| ------------- | ------------------------------------------------------------------------------------------- |
| `None` | No authentication is used. Anyone can access the app. |
| `simple_jwt` | A single, long-lived JWT token is generated at startup. All requests use this shared token. |
| `session_jwt` | Unique JWT tokens are generated for each session/user. |
**Frontend Token Input for `simple_jwt`:**
#### How to Configure
<img
src="/jwt-input.png"
alt="Frontend prompt for JWT Token"
style={{
width: '500px',
maxWidth: '100%',
display: 'block',
margin: '1em auto'
}}
Add the following to your `.env` file (or set in `settings.py`):
```env
# No authentication (default)
AUTH_TYPE=None
# OR: Simple JWT (shared token)
AUTH_TYPE=simple_jwt
JWT_SECRET_KEY=your_secret_key_here
# OR: Session JWT (per-user/session tokens)
AUTH_TYPE=session_jwt
JWT_SECRET_KEY=your_secret_key_here
```
- If `AUTH_TYPE` is set to `simple_jwt` or `session_jwt`, a `JWT_SECRET_KEY` is required.
- If `JWT_SECRET_KEY` is not set, DocsGPT will generate one and store it in `.jwt_secret_key` in the project root.
#### How Each Method Works
- **None**: No authentication. All API and UI access is open.
- **simple_jwt**:
- A single JWT token is generated at startup and printed to the console.
- Use this token in the `Authorization` header for all API requests:
```http
Authorization: Bearer <SIMPLE_JWT_TOKEN>
```
- The frontend will prompt for this token if not already set.
- **session_jwt**:
- Clients can request a new token from `/api/generate_token`.
- Use the received token in the `Authorization` header for subsequent requests.
- Each user/session gets a unique token.
#### Security Notes
- Always keep your `JWT_SECRET_KEY` secure and private.
- If you set it manually, use a strong, random string.
- If not set, DocsGPT will generate a secure key and persist it in `.jwt_secret_key`.
#### Checking Current Auth Type
- Use the `/api/config` endpoint to check the current `auth_type` and whether authentication is required.
#### Frontend Token Input for `simple_jwt`
If you have configured `AUTH_TYPE=simple_jwt`, the DocsGPT frontend will prompt you to enter the JWT token if it's not already set or is invalid. Paste the `SIMPLE_JWT_TOKEN` (printed to your console when the backend starts) into this field to access the application.
<img
src="/jwt-input.png"
alt="Frontend prompt for JWT Token"
style={{
width: "500px",
maxWidth: "100%",
display: "block",
margin: "1em auto",
}}
/>
If you have configured `AUTH_TYPE=simple_jwt`, the DocsGPT frontend will prompt you to enter the JWT token if it's not already set or is invalid. You'll need to paste the `SIMPLE_JWT_TOKEN` (which is printed to your console when the backend starts) into this field to access the application.
## Exploring More Settings
These are just the basic settings to get you started. The `settings.py` file contains many more advanced options that you can explore to further customize DocsGPT, such as:
@@ -147,4 +178,4 @@ These are just the basic settings to get you started. The `settings.py` file con
- Cache settings (`CACHE_REDIS_URL`)
- And many more!
For a complete list of available settings and their descriptions, refer to the `settings.py` file in `application/core`. Remember to restart your Docker containers after making changes to your `.env` file or `settings.py` for the changes to take effect.
For a complete list of available settings and their descriptions, refer to the `settings.py` file in `application/core`. Remember to restart your Docker containers after making changes to your `.env` file or `settings.py` for the changes to take effect.

View File

@@ -60,7 +60,7 @@ const config = {
GitHub
</a>
{' | '}
<a href="https://www.blog.docsgpt.cloud/" target="_blank">
<a href="https://blog.docsgpt.cloud/" target="_blank">
Blog
</a>
</div>

View File

@@ -5,6 +5,8 @@
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0,viewport-fit=cover" />
<meta name="apple-mobile-web-app-capable" content="yes">
<meta name="theme-color" content="#fbfbfb" media="(prefers-color-scheme: light)" />
<meta name="theme-color" content="#161616" media="(prefers-color-scheme: dark)" />
<title>DocsGPT</title>
<link rel="shortcut icon" type="image/x-icon" href="/favicon.ico" />
</head>

View File

@@ -55,7 +55,7 @@
"postcss": "^8.4.49",
"prettier": "^3.5.3",
"prettier-plugin-tailwindcss": "^0.6.13",
"tailwindcss": "^4.1.10",
"tailwindcss": "^4.1.11",
"typescript": "^5.8.3",
"vite": "^6.3.5",
"vite-plugin-svgr": "^4.3.0"
@@ -1696,6 +1696,13 @@
"tailwindcss": "4.1.10"
}
},
"node_modules/@tailwindcss/node/node_modules/tailwindcss": {
"version": "4.1.10",
"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.10.tgz",
"integrity": "sha512-P3nr6WkvKV/ONsTzj6Gb57sWPMX29EPNPopo7+FcpkQaNsrNpZ1pv8QmrYI2RqEKD7mlGqLnGovlcYnBK0IqUA==",
"dev": true,
"license": "MIT"
},
"node_modules/@tailwindcss/oxide": {
"version": "4.1.10",
"resolved": "https://registry.npmjs.org/@tailwindcss/oxide/-/oxide-4.1.10.tgz",
@@ -1908,6 +1915,66 @@
"node": ">=14.0.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/core": {
"version": "1.4.3",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"@emnapi/wasi-threads": "1.0.2",
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/runtime": {
"version": "1.4.3",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/wasi-threads": {
"version": "1.0.2",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@napi-rs/wasm-runtime": {
"version": "0.2.10",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"@emnapi/core": "^1.4.3",
"@emnapi/runtime": "^1.4.3",
"@tybys/wasm-util": "^0.9.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@tybys/wasm-util": {
"version": "0.9.0",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/tslib": {
"version": "2.8.0",
"dev": true,
"inBundle": true,
"license": "0BSD",
"optional": true
},
"node_modules/@tailwindcss/oxide-win32-arm64-msvc": {
"version": "4.1.10",
"resolved": "https://registry.npmjs.org/@tailwindcss/oxide-win32-arm64-msvc/-/oxide-win32-arm64-msvc-4.1.10.tgz",
@@ -1956,6 +2023,13 @@
"tailwindcss": "4.1.10"
}
},
"node_modules/@tailwindcss/postcss/node_modules/tailwindcss": {
"version": "4.1.10",
"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.10.tgz",
"integrity": "sha512-P3nr6WkvKV/ONsTzj6Gb57sWPMX29EPNPopo7+FcpkQaNsrNpZ1pv8QmrYI2RqEKD7mlGqLnGovlcYnBK0IqUA==",
"dev": true,
"license": "MIT"
},
"node_modules/@types/babel__core": {
"version": "7.20.5",
"resolved": "https://registry.npmjs.org/@types/babel__core/-/babel__core-7.20.5.tgz",
@@ -10402,9 +10476,9 @@
}
},
"node_modules/tailwindcss": {
"version": "4.1.10",
"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.10.tgz",
"integrity": "sha512-P3nr6WkvKV/ONsTzj6Gb57sWPMX29EPNPopo7+FcpkQaNsrNpZ1pv8QmrYI2RqEKD7mlGqLnGovlcYnBK0IqUA==",
"version": "4.1.11",
"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.11.tgz",
"integrity": "sha512-2E9TBm6MDD/xKYe+dvJZAmg3yxIEDNRc0jwlNyDg/4Fil2QcSLjFKGVff0lAf1jjeaArlG/M75Ey/EYr/OJtBA==",
"dev": true,
"license": "MIT"
},

View File

@@ -66,7 +66,7 @@
"postcss": "^8.4.49",
"prettier": "^3.5.3",
"prettier-plugin-tailwindcss": "^0.6.13",
"tailwindcss": "^4.1.10",
"tailwindcss": "^4.1.11",
"typescript": "^5.8.3",
"vite": "^6.3.5",
"vite-plugin-svgr": "^4.3.0"

View File

@@ -20,6 +20,7 @@ import {
setSelectedAgent,
} from '../preferences/preferenceSlice';
import PromptsModal from '../preferences/PromptsModal';
import Prompts from '../settings/Prompts';
import { UserToolType } from '../settings/types';
import AgentPreview from './AgentPreview';
import { Agent } from './types';
@@ -46,10 +47,11 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
source: '',
chunks: '',
retriever: '',
prompt_id: '',
prompt_id: 'default',
tools: [],
agent_type: '',
status: '',
json_schema: undefined,
});
const [imageFile, setImageFile] = useState<File | null>(null);
const [prompts, setPrompts] = useState<
@@ -71,6 +73,9 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
const [hasChanges, setHasChanges] = useState(false);
const [draftLoading, setDraftLoading] = useState(false);
const [publishLoading, setPublishLoading] = useState(false);
const [jsonSchemaText, setJsonSchemaText] = useState('');
const [jsonSchemaValid, setJsonSchemaValid] = useState(true);
const [isJsonSchemaExpanded, setIsJsonSchemaExpanded] = useState(false);
const initialAgentRef = useRef<Agent | null>(null);
const sourceAnchorButtonRef = useRef<HTMLButtonElement>(null);
@@ -112,9 +117,15 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
];
const isPublishable = () => {
return (
agent.name && agent.description && agent.prompt_id && agent.agent_type
);
const hasRequiredFields =
agent.name && agent.description && agent.prompt_id && agent.agent_type;
const isJsonSchemaValidOrEmpty =
jsonSchemaText.trim() === '' || jsonSchemaValid;
return hasRequiredFields && isJsonSchemaValidOrEmpty;
};
const isJsonSchemaInvalid = () => {
return jsonSchemaText.trim() !== '' && !jsonSchemaValid;
};
const handleUpload = useCallback((files: File[]) => {
@@ -152,6 +163,10 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
formData.append('tools', JSON.stringify(agent.tools));
else formData.append('tools', '[]');
if (agent.json_schema) {
formData.append('json_schema', JSON.stringify(agent.json_schema));
}
try {
setDraftLoading(true);
const response =
@@ -193,6 +208,10 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
formData.append('tools', JSON.stringify(agent.tools));
else formData.append('tools', '[]');
if (agent.json_schema) {
formData.append('json_schema', JSON.stringify(agent.json_schema));
}
try {
setPublishLoading(true);
const response =
@@ -225,6 +244,22 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
}
};
const validateAndSetJsonSchema = (text: string) => {
setJsonSchemaText(text);
if (text.trim() === '') {
setAgent({ ...agent, json_schema: undefined });
setJsonSchemaValid(true);
return;
}
try {
const parsed = JSON.parse(text);
setAgent({ ...agent, json_schema: parsed });
setJsonSchemaValid(true);
} catch (error) {
setJsonSchemaValid(false);
}
};
useEffect(() => {
const getTools = async () => {
const response = await userService.getUserTools(token);
@@ -263,6 +298,11 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
setSelectedSourceIds(new Set([data.retriever]));
if (data.tools) setSelectedToolIds(new Set(data.tools));
if (data.status === 'draft') setEffectiveMode('draft');
if (data.json_schema) {
const jsonText = JSON.stringify(data.json_schema, null, 2);
setJsonSchemaText(jsonText);
setJsonSchemaValid(true);
}
setAgent(data);
initialAgentRef.current = data;
};
@@ -316,10 +356,17 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
setHasChanges(false);
return;
}
const initialJsonSchemaText = initialAgentRef.current.json_schema
? JSON.stringify(initialAgentRef.current.json_schema, null, 2)
: '';
const isChanged =
!isEqual(agent, initialAgentRef.current) || imageFile !== null;
!isEqual(agent, initialAgentRef.current) ||
imageFile !== null ||
jsonSchemaText !== initialJsonSchemaText;
setHasChanges(isChanged);
}, [agent, dispatch, effectiveMode, imageFile]);
}, [agent, dispatch, effectiveMode, imageFile, jsonSchemaText]);
return (
<div className="p-4 md:p-12">
<div className="flex items-center gap-3 px-4">
@@ -355,7 +402,10 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
)}
{modeConfig[effectiveMode].showSaveDraft && (
<button
className="hover:bg-vi</button>olets-are-blue border-violets-are-blue text-violets-are-blue hover:bg-violets-are-blue w-28 rounded-3xl border border-solid py-2 text-sm font-medium transition-colors hover:text-white"
disabled={isJsonSchemaInvalid()}
className={`border-violets-are-blue text-violets-are-blue hover:bg-violets-are-blue w-28 rounded-3xl border border-solid py-2 text-sm font-medium transition-colors hover:text-white ${
isJsonSchemaInvalid() ? 'cursor-not-allowed opacity-30' : ''
}`}
onClick={handleSaveDraft}
>
<span className="flex items-center justify-center transition-all duration-200">
@@ -504,32 +554,32 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
</div>
</div>
<div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
<h2 className="text-lg font-semibold">Prompt</h2>
<div className="mt-3 flex flex-wrap items-center gap-1">
<div className="flex flex-wrap items-end gap-1">
<div className="min-w-20 grow basis-full sm:basis-0">
<Dropdown
options={prompts.map((prompt) => ({
label: prompt.name,
value: prompt.id,
}))}
selectedValue={
agent.prompt_id
? prompts.filter(
(prompt) => prompt.id === agent.prompt_id,
)[0]?.name || null
: null
<Prompts
prompts={prompts}
selectedPrompt={
prompts.find((prompt) => prompt.id === agent.prompt_id) ||
prompts[0]
}
onSelect={(option: { label: string; value: string }) =>
setAgent({ ...agent, prompt_id: option.value })
onSelectPrompt={(name, id, type) =>
setAgent({ ...agent, prompt_id: id })
}
size="w-full"
rounded="3xl"
border="border"
buttonClassName="bg-white dark:bg-[#222327] border-silver dark:border-[#7E7E7E]"
optionsClassName="bg-white dark:bg-[#383838] border-silver dark:border-[#7E7E7E] dark:border-[#7E7E7E] dark:bg-dark-charcoal"
placeholderClassName="text-gray-400 dark:text-silver"
placeholder="Select a prompt"
contentSize="text-sm"
setPrompts={setPrompts}
title="Prompt"
titleClassName="text-lg font-semibold dark:text-[#E0E0E0]"
showAddButton={false}
dropdownProps={{
size: 'w-full',
rounded: '3xl',
border: 'border',
buttonClassName:
'bg-white dark:bg-[#222327] border-silver dark:border-[#7E7E7E]',
optionsClassName:
'bg-white dark:bg-[#383838] border-silver dark:border-[#7E7E7E]',
placeholderClassName: 'text-gray-400 dark:text-silver',
contentSize: 'text-sm',
}}
/>
</div>
<button
@@ -601,6 +651,78 @@ export default function NewAgent({ mode }: { mode: 'new' | 'edit' | 'draft' }) {
/>
</div>
</div>
<div className="rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
<button
onClick={() => setIsJsonSchemaExpanded(!isJsonSchemaExpanded)}
className="flex w-full items-center justify-between text-left focus:outline-none"
>
<div>
<h2 className="text-lg font-semibold">Advanced</h2>
</div>
<div className="ml-4 flex items-center">
<svg
className={`h-5 w-5 transform transition-transform duration-200 ${
isJsonSchemaExpanded ? 'rotate-180' : ''
}`}
fill="none"
stroke="currentColor"
viewBox="0 0 24 24"
>
<path
strokeLinecap="round"
strokeLinejoin="round"
strokeWidth={2}
d="M19 9l-7 7-7-7"
/>
</svg>
</div>
</button>
{isJsonSchemaExpanded && (
<div className="mt-3">
<div>
<h2 className="text-sm font-medium">JSON response schema</h2>
<p className="mt-1 text-xs text-gray-600 dark:text-gray-400">
Define a JSON schema to enforce structured output format
</p>
</div>
<textarea
value={jsonSchemaText}
onChange={(e) => validateAndSetJsonSchema(e.target.value)}
placeholder={`{
"type": "object",
"properties": {
"name": {"type": "string"},
"email": {"type": "string"}
},
"required": ["name", "email"],
"additionalProperties": false
}`}
rows={9}
className={`border-silver text-jet dark:bg-raisin-black dark:text-bright-gray mt-2 w-full rounded-2xl border bg-white px-4 py-3 font-mono text-sm outline-hidden dark:border-[#7E7E7E]`}
/>
{jsonSchemaText.trim() !== '' && (
<div
className={`mt-2 flex items-center gap-2 text-sm ${
jsonSchemaValid
? 'text-green-600 dark:text-green-400'
: 'text-red-600 dark:text-red-400'
}`}
>
<span
className={`h-4 w-4 bg-contain bg-center bg-no-repeat ${
jsonSchemaValid
? "bg-[url('/src/assets/circle-check.svg')]"
: "bg-[url('/src/assets/circle-x.svg')]"
}`}
/>
{jsonSchemaValid
? 'Valid JSON'
: 'Invalid JSON - fix to enable saving'}
</div>
)}
</div>
)}
</div>
</div>
<div className="col-span-3 flex flex-col gap-3 rounded-[30px] bg-[#F6F6F6] px-6 py-3 dark:bg-[#383838] dark:text-[#E0E0E0]">
<h2 className="text-lg font-semibold">Preview</h2>

View File

@@ -57,12 +57,11 @@ export const fetchPreviewAnswer = createAsyncThunk<
signal,
state.preference.token,
state.preference.selectedDocs!,
state.agentPreview.queries,
null, // No conversation ID for previews
state.preference.prompt.id,
state.preference.chunks,
state.preference.token_limit,
(event) => {
(event: MessageEvent) => {
const data = JSON.parse(event.data);
const targetIndex = indx ?? state.agentPreview.queries.length - 1;
@@ -97,6 +96,17 @@ export const fetchPreviewAnswer = createAsyncThunk<
message: data.error,
}),
);
} else if (data.type === 'structured_answer') {
dispatch(
updateStreamingQuery({
index: targetIndex,
query: {
response: data.answer,
structured: data.structured,
schema: data.schema,
},
}),
);
} else {
dispatch(
updateStreamingQuery({
@@ -118,7 +128,6 @@ export const fetchPreviewAnswer = createAsyncThunk<
signal,
state.preference.token,
state.preference.selectedDocs!,
state.agentPreview.queries,
null, // No conversation ID for previews
state.preference.prompt.id,
state.preference.chunks,
@@ -203,6 +212,14 @@ export const agentPreviewSlice = createSlice({
state.queries[index].response =
(state.queries[index].response || '') + query.response;
}
if (query.structured !== undefined) {
state.queries[index].structured = query.structured;
}
if (query.schema !== undefined) {
state.queries[index].schema = query.schema;
}
},
updateThought(
state,

View File

@@ -26,4 +26,5 @@ export type Agent = {
created_at?: string;
updated_at?: string;
last_used_at?: string;
json_schema?: object;
};

View File

@@ -38,13 +38,25 @@ const endpoints = {
UPDATE_TOOL_STATUS: '/api/update_tool_status',
UPDATE_TOOL: '/api/update_tool',
DELETE_TOOL: '/api/delete_tool',
GET_CHUNKS: (docId: string, page: number, per_page: number) =>
`/api/get_chunks?id=${docId}&page=${page}&per_page=${per_page}`,
SYNC_CONNECTOR: '/api/connectors/sync',
GET_CHUNKS: (
docId: string,
page: number,
per_page: number,
path?: string,
search?: string,
) =>
`/api/get_chunks?id=${docId}&page=${page}&per_page=${per_page}${
path ? `&path=${encodeURIComponent(path)}` : ''
}${search ? `&search=${encodeURIComponent(search)}` : ''}`,
ADD_CHUNK: '/api/add_chunk',
DELETE_CHUNK: (docId: string, chunkId: string) =>
`/api/delete_chunk?id=${docId}&chunk_id=${chunkId}`,
UPDATE_CHUNK: '/api/update_chunk',
STORE_ATTACHMENT: '/api/store_attachment',
DIRECTORY_STRUCTURE: (docId: string) =>
`/api/directory_structure?id=${docId}`,
MANAGE_SOURCE_FILES: '/api/manage_source_files',
},
CONVERSATION: {
ANSWER: '/api/answer',

View File

@@ -1,5 +1,6 @@
import apiClient from '../client';
import endpoints from '../endpoints';
import { getSessionToken } from '../../utils/providerUtils';
const userService = {
getConfig: (): Promise<any> => apiClient.get(endpoints.USER.CONFIG, null),
@@ -86,8 +87,10 @@ const userService = {
page: number,
perPage: number,
token: string | null,
path?: string,
search?: string,
): Promise<any> =>
apiClient.get(endpoints.USER.GET_CHUNKS(docId, page, perPage), token),
apiClient.get(endpoints.USER.GET_CHUNKS(docId, page, perPage, path, search), token),
addChunk: (data: any, token: string | null): Promise<any> =>
apiClient.post(endpoints.USER.ADD_CHUNK, data, token),
deleteChunk: (
@@ -98,6 +101,22 @@ const userService = {
apiClient.delete(endpoints.USER.DELETE_CHUNK(docId, chunkId), token),
updateChunk: (data: any, token: string | null): Promise<any> =>
apiClient.put(endpoints.USER.UPDATE_CHUNK, data, token),
getDirectoryStructure: (docId: string, token: string | null): Promise<any> =>
apiClient.get(endpoints.USER.DIRECTORY_STRUCTURE(docId), token),
manageSourceFiles: (data: FormData, token: string | null): Promise<any> =>
apiClient.postFormData(endpoints.USER.MANAGE_SOURCE_FILES, data, token),
syncConnector: (docId: string, provider: string, token: string | null): Promise<any> => {
const sessionToken = getSessionToken(provider);
return apiClient.post(
endpoints.USER.SYNC_CONNECTOR,
{
source_id: docId,
session_token: sessionToken,
provider: provider
},
token
);
},
};
export default userService;

View File

@@ -0,0 +1,4 @@
<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M6 7.5C6 7.36739 5.94732 7.24021 5.85355 7.14645C5.75979 7.05268 5.63261 7 5.5 7H4.5C4.36739 7 4.24021 7.05268 4.14645 7.14645C4.05268 7.24021 4 7.36739 4 7.5V8.5C4 8.63261 4.05268 8.75979 4.14645 8.85355C4.24021 8.94732 4.36739 9 4.5 9H5.5C5.63261 9 5.75979 8.94732 5.85355 8.85355C5.94732 8.75979 6 8.63261 6 8.5V7.5ZM6 10.5C6 10.3674 5.94732 10.2402 5.85355 10.1464C5.75979 10.0527 5.63261 10 5.5 10H4.5C4.36739 10 4.24021 10.0527 4.14645 10.1464C4.05268 10.2402 4 10.3674 4 10.5V11.5C4 11.6326 4.05268 11.7598 4.14645 11.8536C4.24021 11.9473 4.36739 12 4.5 12H5.5C5.63261 12 5.75979 11.9473 5.85355 11.8536C5.94732 11.7598 6 11.6326 6 11.5V10.5ZM7.5 7H8.5C8.63261 7 8.75979 7.05268 8.85355 7.14645C8.94732 7.24021 9 7.36739 9 7.5V8.5C9 8.63261 8.94732 8.75979 8.85355 8.85355C8.75979 8.94732 8.63261 9 8.5 9H7.5C7.36739 9 7.24021 8.94732 7.14645 8.85355C7.05268 8.75979 7 8.63261 7 8.5V7.5C7 7.36739 7.05268 7.24021 7.14645 7.14645C7.24021 7.05268 7.36739 7 7.5 7ZM8.5 10H7.5C7.36739 10 7.24021 10.0527 7.14645 10.1464C7.05268 10.2402 7 10.3674 7 10.5V11.5C7 11.6326 7.05268 11.7598 7.14645 11.8536C7.24021 11.9473 7.36739 12 7.5 12H8.5C8.63261 12 8.75979 11.9473 8.85355 11.8536C8.94732 11.7598 9 11.6326 9 11.5V10.5C9 10.3674 8.94732 10.2402 8.85355 10.1464C8.75979 10.0527 8.63261 10 8.5 10ZM10 7.5C10 7.36739 10.0527 7.24021 10.1464 7.14645C10.2402 7.05268 10.3674 7 10.5 7H11.5C11.6326 7 11.7598 7.05268 11.8536 7.14645C11.9473 7.24021 12 7.36739 12 7.5V8.5C12 8.63261 11.9473 8.75979 11.8536 8.85355C11.7598 8.94732 11.6326 9 11.5 9H10.5C10.3674 9 10.2402 8.94732 10.1464 8.85355C10.0527 8.75979 10 8.63261 10 8.5V7.5Z" fill="#848484"/>
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</svg>

After

Width:  |  Height:  |  Size: 2.6 KiB

View File

@@ -0,0 +1,3 @@
<svg width="14" height="10" viewBox="0 0 14 10" fill="none" xmlns="http://www.w3.org/2000/svg">
<path fill-rule="evenodd" clip-rule="evenodd" d="M7 0C8.8144 0 10.4902 0.332143 11.739 0.898571C12.362 1.18143 12.9108 1.53643 13.3119 1.96714C13.7172 2.4 14 2.94429 14 3.57143V6.42857C14 7.05571 13.7172 7.59929 13.3119 8.03286C12.9108 8.46357 12.3627 8.81857 11.739 9.10143C10.4902 9.66786 8.8144 10 7 10C5.1856 10 3.5098 9.66786 2.261 9.10143C1.638 8.81857 1.0892 8.46357 0.6881 8.03286C0.2828 7.6 0 7.05571 0 6.42857V3.57143C0 2.94429 0.2828 2.40071 0.6881 1.96714C1.0892 1.53643 1.6373 1.18143 2.261 0.898571C3.5098 0.332143 5.1856 0 7 0ZM12.6 5.77143C12.3375 5.94714 12.047 6.10429 11.739 6.24429C10.4902 6.81071 8.8144 7.14286 7 7.14286C5.1856 7.14286 3.5098 6.81071 2.261 6.24429C1.96243 6.10966 1.67456 5.95157 1.4 5.77143V6.42857C1.4 6.59071 1.47 6.79857 1.7024 7.04857C1.9383 7.30143 2.3128 7.56214 2.8294 7.79643C3.8612 8.26429 5.3354 8.57143 7 8.57143C8.6646 8.57143 10.1388 8.26429 11.1706 7.79643C11.6872 7.56214 12.0617 7.30143 12.2976 7.04857C12.5307 6.79857 12.6 6.59071 12.6 6.42857V5.77143ZM7 1.42857C5.3347 1.42857 3.8612 1.73571 2.8294 2.20357C2.3128 2.43786 1.9383 2.69857 1.7024 2.95143C1.4693 3.20143 1.4 3.40929 1.4 3.57143C1.4 3.73357 1.47 3.94143 1.7024 4.19143C1.9383 4.44429 2.3128 4.705 2.8294 4.93929C3.8612 5.40714 5.3354 5.71429 7 5.71429C8.6646 5.71429 10.1388 5.40714 11.1706 4.93929C11.6872 4.705 12.0617 4.44429 12.2976 4.19143C12.5307 3.94143 12.6 3.73357 12.6 3.57143C12.6 3.40929 12.53 3.20143 12.2976 2.95143C12.0617 2.69857 11.6872 2.43786 11.1706 2.20357C10.1388 1.73643 8.6646 1.42857 7 1.42857Z" fill="#848484"/>
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import React, { useState, useEffect, useRef } from 'react';
import { useSelector } from 'react-redux';
import { useTranslation } from 'react-i18next';
import { selectToken } from '../preferences/preferenceSlice';
import { useDarkTheme, useLoaderState, useMediaQuery, useOutsideAlerter } from '../hooks';
import userService from '../api/services/userService';
import ArrowLeft from '../assets/arrow-left.svg';
import NoFilesIcon from '../assets/no-files.svg';
import NoFilesDarkIcon from '../assets/no-files-dark.svg';
import OutlineSource from '../assets/outline-source.svg';
import SkeletonLoader from './SkeletonLoader';
import ConfirmationModal from '../modals/ConfirmationModal';
import { ActiveState } from '../models/misc';
import { ChunkType } from '../settings/types';
import Pagination from './DocumentPagination';
import FileIcon from '../assets/file.svg';
import FolderIcon from '../assets/folder.svg';
import SearchIcon from '../assets/search.svg';
interface LineNumberedTextareaProps {
value: string;
onChange: (value: string) => void;
placeholder?: string;
ariaLabel?: string;
className?: string;
editable?: boolean;
onDoubleClick?: () => void;
}
const LineNumberedTextarea: React.FC<LineNumberedTextareaProps> = ({
value,
onChange,
placeholder,
ariaLabel,
className = '',
editable = true,
onDoubleClick
}) => {
const { isMobile } = useMediaQuery();
const handleChange = (e: React.ChangeEvent<HTMLTextAreaElement>) => {
onChange(e.target.value);
};
const lineHeight = 19.93;
const contentLines = value.split('\n').length;
const heightOffset = isMobile ? 200 : 300;
const minLinesForDisplay = Math.ceil((typeof window !== 'undefined' ? window.innerHeight - heightOffset : 600) / lineHeight);
const totalLines = Math.max(contentLines, minLinesForDisplay);
return (
<div className={`relative w-full ${className}`}>
<div
className="absolute left-0 top-0 w-8 lg:w-12 text-right text-gray-500 dark:text-gray-400 text-xs lg:text-sm font-mono leading-[19.93px] select-none pr-2 lg:pr-3 pointer-events-none"
style={{
height: `${totalLines * lineHeight}px`
}}
>
{Array.from({ length: totalLines }, (_, i) => (
<div
key={i + 1}
className="flex items-center justify-end h-[19.93px] leading-[19.93px]"
>
{i + 1}
</div>
))}
</div>
<textarea
className={`w-full resize-none bg-transparent dark:text-white font-['Inter'] text-[13.68px] leading-[19.93px] text-[#18181B] outline-none border-none pl-8 lg:pl-12 overflow-hidden ${isMobile ? 'min-h-[calc(100vh-200px)]' : 'min-h-[calc(100vh-300px)]'} ${!editable ? 'select-none' : ''}`}
value={value}
onChange={editable ? handleChange : undefined}
onDoubleClick={onDoubleClick}
placeholder={placeholder}
aria-label={ariaLabel}
rows={totalLines}
readOnly={!editable}
style={{
height: `${totalLines * lineHeight}px`
}}
/>
</div>
);
};
interface SearchResult {
path: string;
isFile: boolean;
}
interface ChunksProps {
documentId: string;
documentName?: string;
handleGoBack: () => void;
path?: string;
onFileSearch?: (query: string) => SearchResult[];
onFileSelect?: (path: string) => void;
}
const Chunks: React.FC<ChunksProps> = ({
documentId,
documentName,
handleGoBack,
path,
onFileSearch,
onFileSelect,
}) => {
const [fileSearchQuery, setFileSearchQuery] = useState('');
const [fileSearchResults, setFileSearchResults] = useState<SearchResult[]>([]);
const searchDropdownRef = useRef<HTMLDivElement>(null);
const { t } = useTranslation();
const token = useSelector(selectToken);
const [isDarkTheme] = useDarkTheme();
const [paginatedChunks, setPaginatedChunks] = useState<ChunkType[]>([]);
const [page, setPage] = useState(1);
const [perPage, setPerPage] = useState(5);
const [totalChunks, setTotalChunks] = useState(0);
const [loading, setLoading] = useLoaderState(true);
const [searchTerm, setSearchTerm] = useState<string>('');
const [editingChunk, setEditingChunk] = useState<ChunkType | null>(null);
const [editingTitle, setEditingTitle] = useState('');
const [editingText, setEditingText] = useState('');
const [isAddingChunk, setIsAddingChunk] = useState(false);
const [deleteModalState, setDeleteModalState] = useState<ActiveState>('INACTIVE');
const [chunkToDelete, setChunkToDelete] = useState<ChunkType | null>(null);
const [isEditing, setIsEditing] = useState(false);
const pathParts = path ? path.split('/') : [];
const fetchChunks = () => {
setLoading(true);
try {
userService
.getDocumentChunks(documentId, page, perPage, token, path, searchTerm)
.then((response) => {
if (!response.ok) {
setLoading(false);
setPaginatedChunks([]);
throw new Error('Failed to fetch chunks data');
}
return response.json();
})
.then((data) => {
setPage(data.page);
setPerPage(data.per_page);
setTotalChunks(data.total);
setPaginatedChunks(data.chunks);
setLoading(false);
})
.catch((error) => {
setLoading(false);
setPaginatedChunks([]);
});
} catch (e) {
setLoading(false);
setPaginatedChunks([]);
}
};
const handleAddChunk = (title: string, text: string) => {
if (!text.trim()) {
return;
}
try {
const metadata = {
source: path || documentName,
source_id: documentId,
title: title,
};
userService
.addChunk(
{
id: documentId,
text: text,
metadata: metadata,
},
token,
)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to add chunk');
}
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
const handleUpdateChunk = (title: string, text: string, chunk: ChunkType) => {
if (!text.trim()) {
return;
}
const originalTitle = chunk.metadata?.title || '';
const originalText = chunk.text || '';
if (title === originalTitle && text === originalText) {
return;
}
try {
userService
.updateChunk(
{
id: documentId,
chunk_id: chunk.doc_id,
text: text,
metadata: {
title: title,
},
},
token,
)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to update chunk');
}
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
const handleDeleteChunk = (chunk: ChunkType) => {
try {
userService
.deleteChunk(documentId, chunk.doc_id, token)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to delete chunk');
}
setEditingChunk(null);
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
const confirmDeleteChunk = (chunk: ChunkType) => {
setChunkToDelete(chunk);
setDeleteModalState('ACTIVE');
};
const handleConfirmedDelete = () => {
if (chunkToDelete) {
handleDeleteChunk(chunkToDelete);
setDeleteModalState('INACTIVE');
setChunkToDelete(null);
}
};
const handleCancelDelete = () => {
setDeleteModalState('INACTIVE');
setChunkToDelete(null);
};
useEffect(() => {
const delayDebounceFn = setTimeout(() => {
if (page !== 1) {
setPage(1);
} else {
fetchChunks();
}
}, 300);
return () => clearTimeout(delayDebounceFn);
}, [searchTerm]);
useEffect(() => {
!loading && fetchChunks();
}, [page, perPage, path]);
useEffect(() => {
setSearchTerm('');
setPage(1);
}, [path]);
const filteredChunks = paginatedChunks;
const renderPathNavigation = () => {
return (
<div className="mb-0 min-h-[38px] flex flex-col sm:flex-row sm:items-center sm:justify-between text-base gap-2">
<div className="flex w-full items-center sm:w-auto">
<button
className="mr-3 flex h-[29px] w-[29px] items-center justify-center rounded-full border p-2 text-sm text-gray-400 dark:border-0 dark:bg-[#28292D] dark:text-gray-500 dark:hover:bg-[#2E2F34] transition-all duration-200 font-medium"
onClick={editingChunk ? () => setEditingChunk(null) : isAddingChunk ? () => setIsAddingChunk(false) : handleGoBack}
>
<img src={ArrowLeft} alt="left-arrow" className="h-3 w-3" />
</button>
<div className="flex items-center flex-wrap">
{/* Removed the directory icon */}
<span className="text-[#7D54D1] font-semibold break-words">
{documentName}
</span>
{pathParts.length > 0 && (
<>
<span className="mx-1 text-gray-500 flex-shrink-0">/</span>
{pathParts.map((part, index) => (
<React.Fragment key={index}>
<span className={`break-words ${
index < pathParts.length - 1
? 'text-[#7D54D1] font-medium'
: 'text-gray-700 dark:text-gray-300'
}`}>
{part}
</span>
{index < pathParts.length - 1 && (
<span className="mx-1 text-gray-500 flex-shrink-0">/</span>
)}
</React.Fragment>
))}
</>
)}
</div>
</div>
<div className="flex flex-row flex-nowrap items-center gap-2 w-full sm:w-auto justify-end mt-2 sm:mt-0 overflow-x-auto">
{editingChunk ? (
!isEditing ? (
<>
<button
className="bg-purple-30 hover:bg-violets-are-blue flex h-[38px] min-w-[108px] items-center justify-center rounded-full px-4 text-[14px] whitespace-nowrap text-white font-medium"
onClick={() => setIsEditing(true)}
>
{t('modals.chunk.edit')}
</button>
<button
className="rounded-full border border-solid border-red-500 px-4 py-1 text-[14px] text-nowrap text-red-500 hover:bg-red-500 hover:text-white h-[38px] min-w-[108px] flex items-center justify-center font-medium"
onClick={() => {
confirmDeleteChunk(editingChunk);
}}
>
{t('modals.chunk.delete')}
</button>
</>
) : (
<>
<button
onClick={() => {
setIsEditing(false);
}}
className="dark:text-light-gray cursor-pointer rounded-full px-4 py-1 text-sm font-medium hover:bg-gray-100 dark:bg-transparent dark:hover:bg-[#767183]/50 text-nowrap h-[38px] min-w-[108px] flex items-center justify-center"
>
{t('modals.chunk.cancel')}
</button>
<button
onClick={() => {
if (editingText.trim()) {
const hasChanges = editingTitle !== (editingChunk?.metadata?.title || '') ||
editingText !== (editingChunk?.text || '');
if (hasChanges) {
handleUpdateChunk(editingTitle, editingText, editingChunk);
}
setIsEditing(false);
setEditingChunk(null);
}
}}
disabled={!editingText.trim() || (editingTitle === (editingChunk?.metadata?.title || '') && editingText === (editingChunk?.text || ''))}
className={`text-nowrap rounded-full px-4 py-1 text-[14px] text-white transition-all flex items-center justify-center h-[38px] min-w-[108px] font-medium ${
editingText.trim() && (editingTitle !== (editingChunk?.metadata?.title || '') || editingText !== (editingChunk?.text || ''))
? 'bg-purple-30 hover:bg-violets-are-blue cursor-pointer'
: 'bg-gray-400 cursor-not-allowed'
}`}
>
{t('modals.chunk.save')}
</button>
</>
)
) : isAddingChunk ? (
<>
<button
onClick={() => setIsAddingChunk(false)}
className="dark:text-light-gray cursor-pointer rounded-full px-4 py-1 text-sm font-medium hover:bg-gray-100 dark:bg-transparent dark:hover:bg-[#767183]/50 text-nowrap h-[38px] min-w-[108px] flex items-center justify-center"
>
{t('modals.chunk.cancel')}
</button>
<button
onClick={() => {
if (editingText.trim()) {
handleAddChunk(editingTitle, editingText);
setIsAddingChunk(false);
}
}}
disabled={!editingText.trim()}
className={`text-nowrap rounded-full px-4 py-1 text-[14px] text-white transition-all flex items-center justify-center h-[38px] min-w-[108px] font-medium ${
editingText.trim()
? 'bg-purple-30 hover:bg-violets-are-blue cursor-pointer'
: 'bg-gray-400 cursor-not-allowed'
}`}
>
{t('modals.chunk.add')}
</button>
</>
) : null}
</div>
</div>
);
};
// File search handling
const handleFileSearchChange = (query: string) => {
setFileSearchQuery(query);
if (query.trim() && onFileSearch) {
const results = onFileSearch(query);
setFileSearchResults(results);
} else {
setFileSearchResults([]);
}
};
const handleSearchResultClick = (result: SearchResult) => {
if (!onFileSelect) return;
if (result.isFile) {
onFileSelect(result.path);
} else {
// For directories, navigate to the directory and return to file tree
onFileSelect(result.path);
handleGoBack();
}
setFileSearchQuery('');
setFileSearchResults([]);
};
useOutsideAlerter(
searchDropdownRef,
() => {
setFileSearchQuery('');
setFileSearchResults([]);
},
[], // No additional dependencies
false // Don't handle escape key
);
const renderFileSearch = () => {
return (
<div className="relative" ref={searchDropdownRef}>
<div className="relative flex items-center">
<div className="absolute left-3 pointer-events-none">
<img src={SearchIcon} alt="Search" className="w-4 h-4" />
</div>
<input
type="text"
value={fileSearchQuery}
onChange={(e) => handleFileSearchChange(e.target.value)}
placeholder={t('settings.sources.searchFiles')}
className={`w-full h-[38px] border border-[#D1D9E0] pl-10 pr-4 py-2 dark:border-[#6A6A6A]
${fileSearchQuery
? 'rounded-t-[6px]'
: 'rounded-[6px]'
}
bg-transparent focus:outline-none dark:text-[#E0E0E0] transition-all duration-200`}
/>
</div>
{fileSearchQuery && (
<div className="absolute z-10 max-h-[calc(100vh-200px)] w-full overflow-hidden rounded-b-[6px] border border-t-0 border-[#D1D9E0] bg-white shadow-lg dark:border-[#6A6A6A] dark:bg-[#1F2023]">
<div className="max-h-[calc(100vh-200px)] overflow-y-auto overflow-x-hidden">
{fileSearchResults.length === 0 ? (
<div className="py-2 text-center text-sm text-gray-500 dark:text-gray-400">
{t('settings.sources.noResults')}
</div>
) : (
fileSearchResults.map((result, index) => (
<div
key={index}
title={result.path}
onClick={() => handleSearchResultClick(result)}
className={`flex cursor-pointer items-center px-3 py-2 hover:bg-[#ECEEEF] dark:hover:bg-[#27282D] ${
index !== fileSearchResults.length - 1
? 'border-b border-[#D1D9E0] dark:border-[#6A6A6A]'
: ''
}`}
>
<img
src={result.isFile ? FileIcon : FolderIcon}
alt={result.isFile ? 'File' : 'Folder'}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="text-sm dark:text-[#E0E0E0] truncate">
{result.path.split('/').pop() || result.path}
</span>
</div>
))
)}
</div>
</div>
)}
</div>
);
};
return (
<div className="flex flex-col">
<div className="mb-2">
{renderPathNavigation()}
</div>
<div className="flex gap-4">
{onFileSearch && onFileSelect && (
<div className="hidden lg:block w-[198px]">
{renderFileSearch()}
</div>
)}
{/* Right side: Chunks content */}
<div className="flex-1">
{!editingChunk && !isAddingChunk ? (
<>
<div className="mb-3 flex flex-col sm:flex-row items-start sm:items-center justify-between gap-3">
<div className="flex-1 w-full flex items-center border border-[#D1D9E0] dark:border-[#6A6A6A] rounded-md overflow-hidden h-[38px]">
<div className="px-4 flex items-center text-gray-700 dark:text-[#E0E0E0] font-medium whitespace-nowrap h-full">
{totalChunks > 999999
? `${(totalChunks / 1000000).toFixed(2)}M`
: totalChunks > 999
? `${(totalChunks / 1000).toFixed(2)}K`
: totalChunks} {t('settings.sources.chunks')}
</div>
<div className="h-full w-[1px] bg-[#D1D9E0] dark:bg-[#6A6A6A]"></div>
<div className="flex-1 h-full">
<input
type="text"
placeholder={t('settings.sources.searchPlaceholder')}
value={searchTerm}
onChange={(e) => setSearchTerm(e.target.value)}
className="w-full h-full px-3 py-2 bg-transparent border-none outline-none font-normal text-[13.56px] leading-[100%] dark:text-[#E0E0E0]"
/>
</div>
</div>
<button
className="bg-purple-30 hover:bg-violets-are-blue flex h-[38px] w-full sm:w-auto min-w-[108px] items-center justify-center rounded-full px-4 text-[14px] whitespace-normal text-white shrink-0 font-medium"
title={t('settings.sources.addChunk')}
onClick={() => {
setIsAddingChunk(true);
setEditingTitle('');
setEditingText('');
}}
>
{t('settings.sources.addChunk')}
</button>
</div>
{loading ? (
<div className="w-full grid grid-cols-1 sm:[grid-template-columns:repeat(auto-fit,minmax(400px,1fr))] gap-4 justify-items-start">
<SkeletonLoader component="chunkCards" count={perPage} />
</div>
) : (
<div className="w-full grid grid-cols-1 sm:[grid-template-columns:repeat(auto-fit,minmax(400px,1fr))] gap-4 justify-items-start">
{filteredChunks.length === 0 ? (
<div className="col-span-full w-full min-h-[50vh] flex flex-col items-center justify-center text-center text-gray-500 dark:text-gray-400">
<img
src={isDarkTheme ? NoFilesDarkIcon : NoFilesIcon}
alt={t('settings.sources.noChunksAlt')}
className="mx-auto mb-2 h-24 w-24"
/>
{t('settings.sources.noChunks')}
</div>
) : (
filteredChunks.map((chunk, index) => (
<div
key={index}
className="transform transition-transform duration-200 hover:scale-105 relative flex h-[197px] flex-col justify-between rounded-[5.86px] border border-[#D1D9E0] dark:border-[#6A6A6A] overflow-hidden cursor-pointer w-full max-w-[487px]"
onClick={() => {
setEditingChunk(chunk);
setEditingTitle(chunk.metadata?.title || '');
setEditingText(chunk.text || '');
}}
>
<div className="w-full">
<div className="flex w-full items-center justify-between border-b border-[#D1D9E0] bg-[#F6F8FA] dark:bg-[#27282D] dark:border-[#6A6A6A] px-4 py-3">
<div className="text-[#59636E] text-sm dark:text-[#E0E0E0]">
{chunk.metadata.token_count ? chunk.metadata.token_count.toLocaleString() : '-'} {t('settings.sources.tokensUnit')}
</div>
</div>
<div className="px-4 pt-3 pb-6">
<p className="font-['Inter'] text-[13.68px] leading-[19.93px] text-[#18181B] dark:text-[#E0E0E0] line-clamp-6 font-normal">
{chunk.text}
</p>
</div>
</div>
</div>
))
)}
</div>
)}
</>
) : isAddingChunk ? (
<div className="w-full">
<div className="relative border border-[#D1D9E0] dark:border-[#6A6A6A] rounded-lg overflow-hidden">
<LineNumberedTextarea
value={editingText}
onChange={setEditingText}
ariaLabel={t('modals.chunk.promptText')}
editable={true}
/>
</div>
</div>
) : editingChunk && (
<div className="w-full">
<div className="relative flex flex-col rounded-[5.86px] border border-[#D1D9E0] dark:border-[#6A6A6A] overflow-hidden w-full">
<div className="flex w-full items-center justify-between border-b border-[#D1D9E0] bg-[#F6F8FA] dark:bg-[#27282D] dark:border-[#6A6A6A] px-4 py-3">
<div className="text-[#59636E] text-sm dark:text-[#E0E0E0]">
{editingChunk.metadata.token_count ? editingChunk.metadata.token_count.toLocaleString() : '-'} {t('settings.sources.tokensUnit')}
</div>
</div>
<div className="p-4 overflow-hidden">
<LineNumberedTextarea
value={isEditing ? editingText : editingChunk.text}
onChange={setEditingText}
ariaLabel={t('modals.chunk.promptText')}
editable={isEditing}
onDoubleClick={() => {
if (!isEditing) {
setIsEditing(true);
setEditingTitle(editingChunk.metadata.title || '');
setEditingText(editingChunk.text);
}
}}
/>
</div>
</div>
</div>
)}
{!loading && totalChunks > perPage && !editingChunk && !isAddingChunk && (
<Pagination
currentPage={page}
totalPages={Math.ceil(totalChunks / perPage)}
rowsPerPage={perPage}
onPageChange={setPage}
onRowsPerPageChange={(rows) => {
setPerPage(rows);
setPage(1);
}}
/>
)}
</div>
</div>
{/* Delete Confirmation Modal */}
<ConfirmationModal
message={t('modals.chunk.deleteConfirmation')}
modalState={deleteModalState}
setModalState={setDeleteModalState}
handleSubmit={handleConfirmedDelete}
handleCancel={handleCancelDelete}
submitLabel={t('modals.chunk.delete')}
variant="danger"
/>
</div>
);
};
export default Chunks;

View File

@@ -0,0 +1,112 @@
import React, { useRef } from 'react';
import { useSelector } from 'react-redux';
import { selectToken } from '../preferences/preferenceSlice';
interface ConnectorAuthProps {
provider: string;
onSuccess: (data: { session_token: string; user_email: string }) => void;
onError: (error: string) => void;
label?: string;
}
const providerLabel = (provider: string) => {
const map: Record<string, string> = {
google_drive: 'Google Drive',
};
return map[provider] || provider.replace(/_/g, ' ');
};
const ConnectorAuth: React.FC<ConnectorAuthProps> = ({ provider, onSuccess, onError, label }) => {
const token = useSelector(selectToken);
const completedRef = useRef(false);
const intervalRef = useRef<number | null>(null);
const cleanup = () => {
if (intervalRef.current) {
clearInterval(intervalRef.current);
intervalRef.current = null;
}
window.removeEventListener('message', handleAuthMessage as any);
};
const handleAuthMessage = (event: MessageEvent) => {
const successGeneric = event.data?.type === 'connector_auth_success';
const successProvider = event.data?.type === `${provider}_auth_success` || event.data?.type === 'google_drive_auth_success';
const errorProvider = event.data?.type === `${provider}_auth_error` || event.data?.type === 'google_drive_auth_error';
if (successGeneric || successProvider) {
completedRef.current = true;
cleanup();
onSuccess({
session_token: event.data.session_token,
user_email: event.data.user_email || 'Connected User',
});
} else if (errorProvider) {
completedRef.current = true;
cleanup();
onError(event.data.error || 'Authentication failed');
}
};
const handleAuth = async () => {
try {
completedRef.current = false;
cleanup();
const apiHost = import.meta.env.VITE_API_HOST;
const authResponse = await fetch(`${apiHost}/api/connectors/auth?provider=${provider}`, {
headers: { Authorization: `Bearer ${token}` },
});
if (!authResponse.ok) {
throw new Error(`Failed to get authorization URL: ${authResponse.status}`);
}
const authData = await authResponse.json();
if (!authData.success || !authData.authorization_url) {
throw new Error(authData.error || 'Failed to get authorization URL');
}
const authWindow = window.open(
authData.authorization_url,
`${provider}-auth`,
'width=500,height=600,scrollbars=yes,resizable=yes'
);
if (!authWindow) {
throw new Error('Failed to open authentication window. Please allow popups.');
}
window.addEventListener('message', handleAuthMessage as any);
const checkClosed = window.setInterval(() => {
if (authWindow.closed) {
clearInterval(checkClosed);
window.removeEventListener('message', handleAuthMessage as any);
if (!completedRef.current) {
onError('Authentication was cancelled');
}
}
}, 1000);
intervalRef.current = checkClosed;
} catch (error) {
onError(error instanceof Error ? error.message : 'Authentication failed');
}
};
const buttonLabel = label || `Connect ${providerLabel(provider)}`;
return (
<button
onClick={handleAuth}
className="w-full flex items-center justify-center gap-2 rounded-lg bg-blue-500 px-4 py-3 text-white hover:bg-blue-600 transition-colors"
>
<svg className="h-5 w-5" viewBox="0 0 24 24">
<path fill="currentColor" d="M6.28 3l5.72 10H24l-5.72-10H6.28zm11.44 0L12 13l5.72 10H24L18.28 3h-.56zM0 13l5.72 10h5.72L5.72 13H0z"/>
</svg>
{buttonLabel}
</button>
);
};
export default ConnectorAuth;

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@@ -0,0 +1,733 @@
import React, { useState, useRef, useEffect } from 'react';
import { useTranslation } from 'react-i18next';
import { useSelector } from 'react-redux';
import { formatBytes } from '../utils/stringUtils';
import { selectToken } from '../preferences/preferenceSlice';
import Chunks from './Chunks';
import ContextMenu, { MenuOption } from './ContextMenu';
import userService from '../api/services/userService';
import FileIcon from '../assets/file.svg';
import FolderIcon from '../assets/folder.svg';
import ArrowLeft from '../assets/arrow-left.svg';
import ThreeDots from '../assets/three-dots.svg';
import EyeView from '../assets/eye-view.svg';
import SyncIcon from '../assets/sync.svg';
import { useOutsideAlerter } from '../hooks';
interface FileNode {
type?: string;
token_count?: number;
size_bytes?: number;
[key: string]: any;
}
interface DirectoryStructure {
[key: string]: FileNode;
}
interface ConnectorTreeComponentProps {
docId: string;
sourceName: string;
onBackToDocuments: () => void;
}
interface SearchResult {
name: string;
path: string;
isFile: boolean;
}
const ConnectorTreeComponent: React.FC<ConnectorTreeComponentProps> = ({
docId,
sourceName,
onBackToDocuments,
}) => {
const { t } = useTranslation();
const [loading, setLoading] = useState<boolean>(true);
const [error, setError] = useState<string | null>(null);
const [directoryStructure, setDirectoryStructure] =
useState<DirectoryStructure | null>(null);
const [currentPath, setCurrentPath] = useState<string[]>([]);
const token = useSelector(selectToken);
const [activeMenuId, setActiveMenuId] = useState<string | null>(null);
const menuRefs = useRef<{
[key: string]: React.RefObject<HTMLDivElement | null>;
}>({});
const [selectedFile, setSelectedFile] = useState<{
id: string;
name: string;
} | null>(null);
const [searchQuery, setSearchQuery] = useState('');
const [searchResults, setSearchResults] = useState<SearchResult[]>([]);
const searchDropdownRef = useRef<HTMLDivElement>(null);
const [isSyncing, setIsSyncing] = useState<boolean>(false);
const [syncProgress, setSyncProgress] = useState<number>(0);
const [sourceProvider, setSourceProvider] = useState<string>('');
const [syncDone, setSyncDone] = useState<boolean>(false);
useOutsideAlerter(
searchDropdownRef,
() => {
setSearchQuery('');
setSearchResults([]);
},
[],
false,
);
const handleFileClick = (fileName: string) => {
const fullPath = [...currentPath, fileName].join('/');
setSelectedFile({
id: fullPath,
name: fileName,
});
};
const handleSync = async () => {
if (isSyncing) return;
const provider = sourceProvider;
setIsSyncing(true);
setSyncProgress(0);
try {
const response = await userService.syncConnector(docId, provider, token);
const data = await response.json();
if (data.success) {
console.log('Sync started successfully:', data.task_id);
setSyncProgress(10);
// Poll task status using userService
const maxAttempts = 30;
const pollInterval = 2000;
for (let attempt = 0; attempt < maxAttempts; attempt++) {
try {
const statusResponse = await userService.getTaskStatus(
data.task_id,
token,
);
const statusData = await statusResponse.json();
console.log(
`Task status (attempt ${attempt + 1}):`,
statusData.status,
);
if (statusData.status === 'SUCCESS') {
setSyncProgress(100);
console.log('Sync completed successfully');
// Refresh directory structure
try {
const refreshResponse = await userService.getDirectoryStructure(
docId,
token,
);
const refreshData = await refreshResponse.json();
if (refreshData && refreshData.directory_structure) {
setDirectoryStructure(refreshData.directory_structure);
setCurrentPath([]);
}
if (refreshData && refreshData.provider) {
setSourceProvider(refreshData.provider);
}
setSyncDone(true);
setTimeout(() => setSyncDone(false), 5000);
} catch (err) {
console.error('Error refreshing directory structure:', err);
}
break;
} else if (statusData.status === 'FAILURE') {
console.error('Sync task failed:', statusData.result);
break;
} else if (statusData.status === 'PROGRESS') {
const progress = Number(
statusData.result && statusData.result.current != null
? statusData.result.current
: statusData.meta && statusData.meta.current != null
? statusData.meta.current
: 0,
);
setSyncProgress(Math.max(10, progress));
}
await new Promise((resolve) => setTimeout(resolve, pollInterval));
} catch (error) {
console.error('Error polling task status:', error);
break;
}
}
} else {
console.error('Sync failed:', data.error);
}
} catch (err) {
console.error('Error syncing connector:', err);
} finally {
setIsSyncing(false);
setSyncProgress(0);
}
};
useEffect(() => {
const fetchDirectoryStructure = async () => {
try {
setLoading(true);
const directoryResponse = await userService.getDirectoryStructure(
docId,
token,
);
const directoryData = await directoryResponse.json();
if (directoryData && directoryData.directory_structure) {
setDirectoryStructure(directoryData.directory_structure);
} else {
setError('Invalid response format');
}
if (directoryData && directoryData.provider) {
setSourceProvider(directoryData.provider);
}
} catch (err) {
setError('Failed to load source information');
console.error(err);
} finally {
setLoading(false);
}
};
if (docId) {
fetchDirectoryStructure();
}
}, [docId, token]);
const navigateToDirectory = (dirName: string) => {
setCurrentPath([...currentPath, dirName]);
};
const navigateUp = () => {
setCurrentPath(currentPath.slice(0, -1));
};
const getCurrentDirectory = (): DirectoryStructure => {
if (!directoryStructure) return {};
let current = directoryStructure;
for (const dir of currentPath) {
if (current[dir] && !current[dir].type) {
current = current[dir] as DirectoryStructure;
} else {
return {};
}
}
return current;
};
const getMenuRef = (id: string) => {
if (!menuRefs.current[id]) {
menuRefs.current[id] = React.createRef();
}
return menuRefs.current[id];
};
const handleMenuClick = (
e: React.MouseEvent<HTMLButtonElement>,
id: string,
) => {
e.stopPropagation();
setActiveMenuId(activeMenuId === id ? null : id);
};
const getActionOptions = (
name: string,
isFile: boolean,
_itemId: string,
): MenuOption[] => {
const options: MenuOption[] = [];
options.push({
icon: EyeView,
label: t('settings.sources.view'),
onClick: (event: React.SyntheticEvent) => {
event.stopPropagation();
if (isFile) {
handleFileClick(name);
} else {
navigateToDirectory(name);
}
},
iconWidth: 18,
iconHeight: 18,
variant: 'primary',
});
return options;
};
const calculateDirectoryStats = (
structure: DirectoryStructure,
): { totalSize: number; totalTokens: number } => {
let totalSize = 0;
let totalTokens = 0;
Object.entries(structure).forEach(([_, node]) => {
if (node.type) {
// It's a file
totalSize += node.size_bytes || 0;
totalTokens += node.token_count || 0;
} else {
// It's a directory, recurse
const stats = calculateDirectoryStats(node);
totalSize += stats.totalSize;
totalTokens += stats.totalTokens;
}
});
return { totalSize, totalTokens };
};
const handleBackNavigation = () => {
if (selectedFile) {
setSelectedFile(null);
} else if (currentPath.length === 0) {
if (onBackToDocuments) {
onBackToDocuments();
}
} else {
navigateUp();
}
};
const renderPathNavigation = () => {
return (
<div className="mb-0 flex min-h-[38px] flex-col gap-2 text-base sm:flex-row sm:items-center sm:justify-between">
{/* Left side with path navigation */}
<div className="flex w-full items-center sm:w-auto">
<button
className="mr-3 flex h-[29px] w-[29px] items-center justify-center rounded-full border p-2 text-sm font-medium text-gray-400 dark:border-0 dark:bg-[#28292D] dark:text-gray-500 dark:hover:bg-[#2E2F34]"
onClick={handleBackNavigation}
>
<img src={ArrowLeft} alt="left-arrow" className="h-3 w-3" />
</button>
<div className="flex flex-wrap items-center">
<span className="font-semibold break-words text-[#7D54D1]">
{sourceName}
</span>
{currentPath.length > 0 && (
<>
<span className="mx-1 flex-shrink-0 text-gray-500">/</span>
{currentPath.map((dir, index) => (
<React.Fragment key={index}>
<span className="break-words text-gray-700 dark:text-[#E0E0E0]">
{dir}
</span>
{index < currentPath.length - 1 && (
<span className="mx-1 flex-shrink-0 text-gray-500">
/
</span>
)}
</React.Fragment>
))}
</>
)}
</div>
</div>
<div className="relative mt-2 flex w-full flex-row flex-nowrap items-center justify-end gap-2 sm:mt-0 sm:w-auto">
{renderFileSearch()}
{/* Sync button */}
<button
onClick={handleSync}
disabled={isSyncing}
className={`flex h-[38px] min-w-[108px] items-center justify-center rounded-full px-4 text-[14px] font-medium whitespace-nowrap transition-colors ${
isSyncing
? 'cursor-not-allowed bg-gray-300 text-gray-600 dark:bg-gray-600 dark:text-gray-400'
: 'bg-purple-30 hover:bg-violets-are-blue text-white'
}`}
title={
isSyncing
? `${t('settings.sources.syncing')} ${syncProgress}%`
: syncDone
? 'Done'
: t('settings.sources.sync')
}
>
<img
src={SyncIcon}
alt={t('settings.sources.sync')}
className={`mr-2 h-4 w-4 brightness-0 invert filter ${isSyncing ? 'animate-spin' : ''}`}
/>
{isSyncing
? `${syncProgress}%`
: syncDone
? 'Done'
: t('settings.sources.sync')}
</button>
</div>
</div>
);
};
const renderFileTree = (directory: DirectoryStructure) => {
if (!directory) return [];
// Create parent directory row
const parentRow =
currentPath.length > 0
? [
<tr
key="parent-dir"
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={navigateUp}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex items-center">
<img
src={FolderIcon}
alt={t('settings.sources.parentFolderAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
..
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
-
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
-
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4"></td>
</tr>,
]
: [];
// Sort entries: directories first, then files, both alphabetically
const sortedEntries = Object.entries(directory).sort(
([nameA, nodeA], [nameB, nodeB]) => {
const isFileA = !!nodeA.type;
const isFileB = !!nodeB.type;
if (isFileA !== isFileB) {
return isFileA ? 1 : -1; // Directories first
}
return nameA.localeCompare(nameB); // Alphabetical within each group
},
);
// Process directories
const directoryRows = sortedEntries
.filter(([_, node]) => !node.type)
.map(([name, node]) => {
const itemId = `dir-${name}`;
const menuRef = getMenuRef(itemId);
// Calculate directory stats
const dirStats = calculateDirectoryStats(node as DirectoryStructure);
return (
<tr
key={itemId}
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={() => navigateToDirectory(name)}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex min-w-0 items-center">
<img
src={FolderIcon}
alt={t('settings.sources.folderAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
{name}
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{dirStats.totalTokens > 0
? dirStats.totalTokens.toLocaleString()
: '-'}
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{dirStats.totalSize > 0 ? formatBytes(dirStats.totalSize) : '-'}
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4">
<div ref={menuRef} className="relative">
<button
onClick={(e) => handleMenuClick(e, itemId)}
className="inline-flex h-[35px] w-[24px] shrink-0 items-center justify-center rounded-md font-medium transition-colors hover:bg-[#EBEBEB] dark:hover:bg-[#26272E]"
aria-label={t('settings.sources.menuAlt')}
>
<img
src={ThreeDots}
alt={t('settings.sources.menuAlt')}
className="opacity-60 hover:opacity-100"
/>
</button>
<ContextMenu
isOpen={activeMenuId === itemId}
setIsOpen={(isOpen) =>
setActiveMenuId(isOpen ? itemId : null)
}
options={getActionOptions(name, false, itemId)}
anchorRef={menuRef}
position="bottom-left"
offset={{ x: -4, y: 4 }}
/>
</div>
</td>
</tr>
);
});
// Process files
const fileRows = sortedEntries
.filter(([_, node]) => !!node.type)
.map(([name, node]) => {
const itemId = `file-${name}`;
const menuRef = getMenuRef(itemId);
return (
<tr
key={itemId}
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={() => handleFileClick(name)}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex min-w-0 items-center">
<img
src={FileIcon}
alt={t('settings.sources.fileAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
{name}
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{node.token_count?.toLocaleString() || '-'}
</td>
<td className="px-2 py-2 text-sm md:px-4 dark:text-[#E0E0E0]">
{node.size_bytes ? formatBytes(node.size_bytes) : '-'}
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4">
<div ref={menuRef} className="relative">
<button
onClick={(e) => handleMenuClick(e, itemId)}
className="inline-flex h-[35px] w-[24px] shrink-0 items-center justify-center rounded-md font-medium transition-colors hover:bg-[#EBEBEB] dark:hover:bg-[#26272E]"
aria-label={t('settings.sources.menuAlt')}
>
<img
src={ThreeDots}
alt={t('settings.sources.menuAlt')}
className="opacity-60 hover:opacity-100"
/>
</button>
<ContextMenu
isOpen={activeMenuId === itemId}
setIsOpen={(isOpen) =>
setActiveMenuId(isOpen ? itemId : null)
}
options={getActionOptions(name, true, itemId)}
anchorRef={menuRef}
position="bottom-left"
offset={{ x: -4, y: 4 }}
/>
</div>
</td>
</tr>
);
});
return [...parentRow, ...directoryRows, ...fileRows];
};
const searchFiles = (
query: string,
structure: DirectoryStructure,
currentPath: string[] = [],
): SearchResult[] => {
let results: SearchResult[] = [];
Object.entries(structure).forEach(([name, node]) => {
const fullPath = [...currentPath, name].join('/');
if (name.toLowerCase().includes(query.toLowerCase())) {
results.push({
name,
path: fullPath,
isFile: !!node.type,
});
}
if (!node.type) {
// If it's a directory, search recursively
results = [
...results,
...searchFiles(query, node as DirectoryStructure, [
...currentPath,
name,
]),
];
}
});
return results;
};
const handleSearchSelect = (result: SearchResult) => {
if (result.isFile) {
const pathParts = result.path.split('/');
const fileName = pathParts.pop() || '';
setCurrentPath(pathParts);
setSelectedFile({
id: result.path,
name: fileName,
});
} else {
setCurrentPath(result.path.split('/'));
setSelectedFile(null);
}
setSearchQuery('');
setSearchResults([]);
};
const renderFileSearch = () => {
return (
<div className="relative w-52" ref={searchDropdownRef}>
<input
type="text"
value={searchQuery}
onChange={(e) => {
setSearchQuery(e.target.value);
if (directoryStructure) {
setSearchResults(searchFiles(e.target.value, directoryStructure));
}
}}
placeholder={t('settings.sources.searchFiles')}
className={`h-[38px] w-full border border-[#D1D9E0] px-4 py-2 dark:border-[#6A6A6A] ${searchQuery ? 'rounded-t-[24px]' : 'rounded-[24px]'} bg-transparent focus:outline-none dark:text-[#E0E0E0]`}
/>
{searchQuery && (
<div className="absolute top-full right-0 left-0 z-10 max-h-[calc(100vh-200px)] w-full overflow-hidden rounded-b-[12px] border border-t-0 border-[#D1D9E0] bg-white shadow-lg transition-all duration-200 dark:border-[#6A6A6A] dark:bg-[#1F2023]">
<div className="max-h-[calc(100vh-200px)] overflow-x-hidden overflow-y-auto overscroll-contain">
{searchResults.length === 0 ? (
<div className="py-2 text-center text-sm text-gray-500 dark:text-gray-400">
{t('settings.sources.noResults')}
</div>
) : (
searchResults.map((result, index) => (
<div
key={index}
onClick={() => handleSearchSelect(result)}
title={result.path}
className={`flex min-w-0 cursor-pointer items-center px-3 py-2 hover:bg-[#ECEEEF] dark:hover:bg-[#27282D] ${
index !== searchResults.length - 1
? 'border-b border-[#D1D9E0] dark:border-[#6A6A6A]'
: ''
}`}
>
<img
src={result.isFile ? FileIcon : FolderIcon}
alt={
result.isFile
? t('settings.sources.fileAlt')
: t('settings.sources.folderAlt')
}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="flex-1 truncate text-sm dark:text-[#E0E0E0]">
{result.path.split('/').pop() || result.path}
</span>
</div>
))
)}
</div>
</div>
)}
</div>
);
};
const handleFileSearch = (searchQuery: string) => {
if (directoryStructure) {
return searchFiles(searchQuery, directoryStructure);
}
return [];
};
const handleFileSelect = (path: string) => {
const pathParts = path.split('/');
const fileName = pathParts.pop() || '';
setCurrentPath(pathParts);
setSelectedFile({
id: path,
name: fileName,
});
};
const currentDirectory = getCurrentDirectory();
const navigateToPath = (index: number) => {
setCurrentPath(currentPath.slice(0, index + 1));
};
return (
<div>
{selectedFile ? (
<div className="flex">
<div className="flex-1">
<Chunks
documentId={docId}
documentName={sourceName}
handleGoBack={() => setSelectedFile(null)}
path={selectedFile.id}
onFileSearch={handleFileSearch}
onFileSelect={handleFileSelect}
/>
</div>
</div>
) : (
<div className="flex w-full max-w-full flex-col overflow-hidden">
<div className="mb-2">{renderPathNavigation()}</div>
<div className="w-full">
<div className="overflow-x-auto rounded-[6px] border border-[#D1D9E0] dark:border-[#6A6A6A]">
<table className="w-full min-w-[600px] table-auto bg-transparent">
<thead className="bg-gray-100 dark:bg-[#27282D]">
<tr className="border-b border-[#D1D9E0] dark:border-[#6A6A6A]">
<th className="min-w-[200px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.fileName')}
</th>
<th className="min-w-[80px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.tokens')}
</th>
<th className="min-w-[80px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.size')}
</th>
<th className="w-10 px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]"></th>
</tr>
</thead>
<tbody>{renderFileTree(getCurrentDirectory())}</tbody>
</table>
</div>
</div>
</div>
)}
</div>
);
};
export default ConnectorTreeComponent;

View File

@@ -82,14 +82,14 @@ export default function ContextMenu({
// Adjust position based on specified position
switch (position) {
case 'bottom-left':
left = rect.left + scrollX - offset.x;
left = rect.right + scrollX - menuWidth + offset.x;
break;
case 'top-right':
top = rect.top + scrollY - offset.y - menuHeight;
break;
case 'top-left':
top = rect.top + scrollY - offset.y - menuHeight;
left = rect.left + scrollX - offset.x;
left = rect.right + scrollX - menuWidth + offset.x;
break;
// bottom-right is default
}

View File

@@ -3,8 +3,9 @@ import React from 'react';
import Arrow2 from '../assets/dropdown-arrow.svg';
import Edit from '../assets/edit.svg';
import Trash from '../assets/trash.svg';
import { DropdownOption, DropdownProps } from './types/Dropdown.types';
function Dropdown({
function Dropdown<T extends DropdownOption>({
options,
selectedValue,
onSelect,
@@ -20,36 +21,7 @@ function Dropdown({
placeholder,
placeholderClassName = 'text-gray-500 dark:text-gray-400',
contentSize = 'text-base',
}: {
options:
| string[]
| { name: string; id: string; type: string }[]
| { label: string; value: string }[]
| { value: number; description: string }[];
selectedValue:
| string
| { label: string; value: string }
| { value: number; description: string }
| { name: string; id: string; type: string }
| null;
onSelect:
| ((value: string) => void)
| ((value: { name: string; id: string; type: string }) => void)
| ((value: { label: string; value: string }) => void)
| ((value: { value: number; description: string }) => void);
size?: string;
rounded?: 'xl' | '3xl';
buttonClassName?: string;
optionsClassName?: string;
border?: 'border' | 'border-2';
showEdit?: boolean;
onEdit?: (value: { name: string; id: string; type: string }) => void;
showDelete?: boolean | ((option: any) => boolean);
onDelete?: (value: string) => void;
placeholder?: string;
placeholderClassName?: string;
contentSize?: string;
}) {
}: DropdownProps<T>) {
const dropdownRef = React.useRef<HTMLDivElement>(null);
const [isOpen, setIsOpen] = React.useState(false);
const borderRadius = rounded === 'xl' ? 'rounded-xl' : 'rounded-3xl';

View File

@@ -0,0 +1,882 @@
import React, { useState, useRef, useEffect } from 'react';
import { useTranslation } from 'react-i18next';
import { useSelector } from 'react-redux';
import { selectToken } from '../preferences/preferenceSlice';
import { formatBytes } from '../utils/stringUtils';
import Chunks from './Chunks';
import ContextMenu, { MenuOption } from './ContextMenu';
import userService from '../api/services/userService';
import FileIcon from '../assets/file.svg';
import FolderIcon from '../assets/folder.svg';
import ArrowLeft from '../assets/arrow-left.svg';
import ThreeDots from '../assets/three-dots.svg';
import EyeView from '../assets/eye-view.svg';
import OutlineSource from '../assets/outline-source.svg';
import Trash from '../assets/red-trash.svg';
import SearchIcon from '../assets/search.svg';
import { useOutsideAlerter } from '../hooks';
import ConfirmationModal from '../modals/ConfirmationModal';
interface FileNode {
type?: string;
token_count?: number;
size_bytes?: number;
[key: string]: any;
}
interface DirectoryStructure {
[key: string]: FileNode;
}
interface FileTreeComponentProps {
docId: string;
sourceName: string;
onBackToDocuments: () => void;
}
interface SearchResult {
name: string;
path: string;
isFile: boolean;
}
const FileTreeComponent: React.FC<FileTreeComponentProps> = ({
docId,
sourceName,
onBackToDocuments,
}) => {
const { t } = useTranslation();
const [loading, setLoading] = useState<boolean>(true);
const [error, setError] = useState<string | null>(null);
const [directoryStructure, setDirectoryStructure] =
useState<DirectoryStructure | null>(null);
const [currentPath, setCurrentPath] = useState<string[]>([]);
const token = useSelector(selectToken);
const [activeMenuId, setActiveMenuId] = useState<string | null>(null);
const menuRefs = useRef<{
[key: string]: React.RefObject<HTMLDivElement | null>;
}>({});
const [selectedFile, setSelectedFile] = useState<{
id: string;
name: string;
} | null>(null);
const [searchQuery, setSearchQuery] = useState('');
const [searchResults, setSearchResults] = useState<SearchResult[]>([]);
const searchDropdownRef = useRef<HTMLDivElement>(null);
const currentOpRef = useRef<null | 'add' | 'remove' | 'remove_directory'>(
null,
);
const [deleteModalState, setDeleteModalState] = useState<
'ACTIVE' | 'INACTIVE'
>('INACTIVE');
const [itemToDelete, setItemToDelete] = useState<{
name: string;
isFile: boolean;
} | null>(null);
type QueuedOperation = {
operation: 'add' | 'remove' | 'remove_directory';
files?: File[];
filePath?: string;
directoryPath?: string;
parentDirPath?: string;
};
const opQueueRef = useRef<QueuedOperation[]>([]);
const processingRef = useRef(false);
const [queueLength, setQueueLength] = useState(0);
useOutsideAlerter(
searchDropdownRef,
() => {
setSearchQuery('');
setSearchResults([]);
},
[],
false,
);
const handleFileClick = (fileName: string) => {
const fullPath = [...currentPath, fileName].join('/');
setSelectedFile({
id: fullPath,
name: fileName,
});
};
useEffect(() => {
const fetchDirectoryStructure = async () => {
try {
setLoading(true);
const response = await userService.getDirectoryStructure(docId, token);
const data = await response.json();
if (data && data.directory_structure) {
setDirectoryStructure(data.directory_structure);
} else {
setError('Invalid response format');
}
} catch (err) {
setError('Failed to load directory structure');
console.error(err);
} finally {
setLoading(false);
}
};
if (docId) {
fetchDirectoryStructure();
}
}, [docId, token]);
const navigateToDirectory = (dirName: string) => {
setCurrentPath((prev) => [...prev, dirName]);
};
const navigateUp = () => {
setCurrentPath((prev) => prev.slice(0, -1));
};
const getCurrentDirectory = (): DirectoryStructure => {
if (!directoryStructure) return {};
let structure = directoryStructure;
if (typeof structure === 'string') {
try {
structure = JSON.parse(structure);
} catch (e) {
console.error(
'Error parsing directory structure in getCurrentDirectory:',
e,
);
return {};
}
}
if (typeof structure !== 'object' || structure === null) {
return {};
}
let current: any = structure;
for (const dir of currentPath) {
if (
current[dir] &&
typeof current[dir] === 'object' &&
!current[dir].type
) {
current = current[dir];
} else {
return {};
}
}
return current;
};
const handleBackNavigation = () => {
if (selectedFile) {
setSelectedFile(null);
} else if (currentPath.length === 0) {
if (onBackToDocuments) {
onBackToDocuments();
}
} else {
navigateUp();
}
};
const getMenuRef = (itemId: string) => {
if (!menuRefs.current[itemId]) {
menuRefs.current[itemId] = React.createRef<HTMLDivElement>();
}
return menuRefs.current[itemId];
};
const handleMenuClick = (e: React.MouseEvent, itemId: string) => {
e.preventDefault();
e.stopPropagation();
if (activeMenuId === itemId) {
setActiveMenuId(null);
return;
}
setActiveMenuId(itemId);
};
const getActionOptions = (
name: string,
isFile: boolean,
_itemId: string,
): MenuOption[] => {
const options: MenuOption[] = [];
options.push({
icon: EyeView,
label: t('settings.sources.view'),
onClick: (event: React.SyntheticEvent) => {
event.stopPropagation();
if (isFile) {
handleFileClick(name);
} else {
navigateToDirectory(name);
}
},
iconWidth: 18,
iconHeight: 18,
variant: 'primary',
});
options.push({
icon: Trash,
label: t('convTile.delete'),
onClick: (event: React.SyntheticEvent) => {
event.stopPropagation();
confirmDeleteItem(name, isFile);
},
iconWidth: 18,
iconHeight: 18,
variant: 'danger',
});
return options;
};
const confirmDeleteItem = (name: string, isFile: boolean) => {
setItemToDelete({ name, isFile });
setDeleteModalState('ACTIVE');
setActiveMenuId(null);
};
const handleConfirmedDelete = async () => {
if (itemToDelete) {
await handleDeleteFile(itemToDelete.name, itemToDelete.isFile);
setDeleteModalState('INACTIVE');
setItemToDelete(null);
}
};
const handleCancelDelete = () => {
setDeleteModalState('INACTIVE');
setItemToDelete(null);
};
const manageSource = async (
operation: 'add' | 'remove' | 'remove_directory',
files?: File[] | null,
filePath?: string,
directoryPath?: string,
parentDirPath?: string,
) => {
currentOpRef.current = operation;
try {
const formData = new FormData();
formData.append('source_id', docId);
formData.append('operation', operation);
if (operation === 'add' && files && files.length) {
formData.append('parent_dir', parentDirPath ?? currentPath.join('/'));
for (let i = 0; i < files.length; i++) {
formData.append('file', files[i]);
}
} else if (operation === 'remove' && filePath) {
const filePaths = JSON.stringify([filePath]);
formData.append('file_paths', filePaths);
} else if (operation === 'remove_directory' && directoryPath) {
formData.append('directory_path', directoryPath);
}
const response = await userService.manageSourceFiles(formData, token);
const result = await response.json();
if (result.success && result.reingest_task_id) {
if (operation === 'add') {
console.log('Files uploaded successfully:', result.added_files);
} else if (operation === 'remove') {
console.log('Files deleted successfully:', result.removed_files);
} else if (operation === 'remove_directory') {
console.log(
'Directory deleted successfully:',
result.removed_directory,
);
}
console.log('Reingest task started:', result.reingest_task_id);
const maxAttempts = 30;
const pollInterval = 2000;
for (let attempt = 0; attempt < maxAttempts; attempt++) {
try {
const statusResponse = await userService.getTaskStatus(
result.reingest_task_id,
token,
);
const statusData = await statusResponse.json();
console.log(
`Task status (attempt ${attempt + 1}):`,
statusData.status,
);
if (statusData.status === 'SUCCESS') {
console.log('Task completed successfully');
const structureResponse = await userService.getDirectoryStructure(
docId,
token,
);
const structureData = await structureResponse.json();
if (structureData && structureData.directory_structure) {
setDirectoryStructure(structureData.directory_structure);
currentOpRef.current = null;
return true;
}
break;
} else if (statusData.status === 'FAILURE') {
console.error('Task failed');
break;
}
await new Promise((resolve) => setTimeout(resolve, pollInterval));
} catch (error) {
console.error('Error polling task status:', error);
break;
}
}
} else {
throw new Error(
`Failed to ${operation} ${operation === 'remove_directory' ? 'directory' : 'file(s)'}`,
);
}
} catch (error) {
const actionText =
operation === 'add'
? 'uploading'
: operation === 'remove_directory'
? 'deleting directory'
: 'deleting file(s)';
const errorText =
operation === 'add'
? 'upload'
: operation === 'remove_directory'
? 'delete directory'
: 'delete file(s)';
console.error(`Error ${actionText}:`, error);
setError(`Failed to ${errorText}`);
} finally {
currentOpRef.current = null;
}
return false;
};
const processQueue = async () => {
if (processingRef.current) return;
processingRef.current = true;
try {
while (opQueueRef.current.length > 0) {
const nextOp = opQueueRef.current.shift()!;
setQueueLength(opQueueRef.current.length);
await manageSource(
nextOp.operation,
nextOp.files,
nextOp.filePath,
nextOp.directoryPath,
nextOp.parentDirPath,
);
}
} finally {
processingRef.current = false;
}
};
const enqueueOperation = (op: QueuedOperation) => {
opQueueRef.current.push(op);
setQueueLength(opQueueRef.current.length);
if (!processingRef.current) {
void processQueue();
}
};
const handleAddFile = () => {
const fileInput = document.createElement('input');
fileInput.type = 'file';
fileInput.multiple = true;
fileInput.accept =
'.rst,.md,.pdf,.txt,.docx,.csv,.epub,.html,.mdx,.json,.xlsx,.pptx,.png,.jpg,.jpeg';
fileInput.onchange = async (event) => {
const fileList = (event.target as HTMLInputElement).files;
if (!fileList || fileList.length === 0) return;
const files = Array.from(fileList);
enqueueOperation({
operation: 'add',
files,
parentDirPath: currentPath.join('/'),
});
};
fileInput.click();
};
const handleDeleteFile = async (name: string, isFile: boolean) => {
// Construct the full path to the file or directory
const itemPath = [...currentPath, name].join('/');
if (isFile) {
enqueueOperation({ operation: 'remove', filePath: itemPath });
} else {
enqueueOperation({
operation: 'remove_directory',
directoryPath: itemPath,
});
}
};
const renderPathNavigation = () => {
return (
<div className="mb-0 min-h-[38px] flex flex-col gap-2 text-base sm:flex-row sm:items-center sm:justify-between">
{/* Left side with path navigation */}
<div className="flex w-full items-center sm:w-auto">
<button
className="mr-3 flex h-[29px] w-[29px] items-center justify-center rounded-full border p-2 text-sm text-gray-400 dark:border-0 dark:bg-[#28292D] dark:text-gray-500 dark:hover:bg-[#2E2F34] font-medium"
onClick={handleBackNavigation}
>
<img src={ArrowLeft} alt="left-arrow" className="h-3 w-3" />
</button>
<div className="flex flex-wrap items-center">
<span className="text-[#7D54D1] font-semibold break-words">
{sourceName}
</span>
{currentPath.length > 0 && (
<>
<span className="mx-1 flex-shrink-0 text-gray-500">/</span>
{currentPath.map((dir, index) => (
<React.Fragment key={index}>
<span className="break-words text-gray-700 dark:text-gray-300">
{dir}
</span>
{index < currentPath.length - 1 && (
<span className="mx-1 flex-shrink-0 text-gray-500">
/
</span>
)}
</React.Fragment>
))}
</>
)}
{selectedFile && (
<>
<span className="mx-1 flex-shrink-0 text-gray-500">/</span>
<span className="break-words text-gray-700 dark:text-gray-300">
{selectedFile.name}
</span>
</>
)}
</div>
</div>
<div className="flex relative flex-row flex-nowrap items-center gap-2 w-full sm:w-auto justify-end mt-2 sm:mt-0">
{processingRef.current && (
<div className="text-sm text-gray-500">
{currentOpRef.current === 'add'
? t('settings.sources.uploadingFilesTitle')
: t('settings.sources.deletingTitle')}
</div>
)}
{renderFileSearch()}
{/* Add file button */}
{!processingRef.current && (
<button
onClick={handleAddFile}
className="bg-purple-30 hover:bg-violets-are-blue flex h-[38px] min-w-[108px] items-center justify-center rounded-full px-4 text-[14px] whitespace-nowrap text-white font-medium"
title={t('settings.sources.addFile')}
>
{t('settings.sources.addFile')}
</button>
)}
</div>
</div>
);
};
const calculateDirectoryStats = (
structure: DirectoryStructure,
): { totalSize: number; totalTokens: number } => {
let totalSize = 0;
let totalTokens = 0;
Object.entries(structure).forEach(([_, node]) => {
if (node.type) {
// It's a file
totalSize += node.size_bytes || 0;
totalTokens += node.token_count || 0;
} else {
// It's a directory, recurse
const stats = calculateDirectoryStats(node);
totalSize += stats.totalSize;
totalTokens += stats.totalTokens;
}
});
return { totalSize, totalTokens };
};
const renderFileTree = (structure: DirectoryStructure): React.ReactNode[] => {
// Separate directories and files
const entries = Object.entries(structure);
const directories = entries.filter(([_, node]) => !node.type);
const files = entries.filter(([_, node]) => node.type);
// Create parent directory row
const parentRow =
currentPath.length > 0
? [
<tr
key="parent-dir"
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={navigateUp}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex items-center">
<img
src={FolderIcon}
alt={t('settings.sources.parentFolderAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
..
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
-
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
-
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4"></td>
</tr>,
]
: [];
// Render directories first, then files
return [
...parentRow,
...directories.map(([name, node]) => {
const itemId = `dir-${name}`;
const menuRef = getMenuRef(itemId);
const dirStats = calculateDirectoryStats(node as DirectoryStructure);
return (
<tr
key={itemId}
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={() => navigateToDirectory(name)}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex min-w-0 items-center">
<img
src={FolderIcon}
alt={t('settings.sources.folderAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
{name}
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{dirStats.totalTokens > 0
? dirStats.totalTokens.toLocaleString()
: '-'}
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{dirStats.totalSize > 0 ? formatBytes(dirStats.totalSize) : '-'}
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4">
<div ref={menuRef} className="relative">
<button
onClick={(e) => handleMenuClick(e, itemId)}
className="inline-flex h-[35px] w-[24px] shrink-0 items-center justify-center rounded-md transition-colors hover:bg-[#EBEBEB] dark:hover:bg-[#26272E] font-medium"
aria-label={t('settings.sources.menuAlt')}
>
<img
src={ThreeDots}
alt={t('settings.sources.menuAlt')}
className="opacity-60 hover:opacity-100"
/>
</button>
<ContextMenu
isOpen={activeMenuId === itemId}
setIsOpen={(isOpen) =>
setActiveMenuId(isOpen ? itemId : null)
}
options={getActionOptions(name, false, itemId)}
anchorRef={menuRef}
position="bottom-left"
offset={{ x: -4, y: 4 }}
/>
</div>
</td>
</tr>
);
}),
...files.map(([name, node]) => {
const itemId = `file-${name}`;
const menuRef = getMenuRef(itemId);
return (
<tr
key={itemId}
className="cursor-pointer border-b border-[#D1D9E0] hover:bg-[#ECEEEF] dark:border-[#6A6A6A] dark:hover:bg-[#27282D]"
onClick={() => handleFileClick(name)}
>
<td className="px-2 py-2 lg:px-4">
<div className="flex min-w-0 items-center">
<img
src={FileIcon}
alt={t('settings.sources.fileAlt')}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="truncate text-sm dark:text-[#E0E0E0]">
{name}
</span>
</div>
</td>
<td className="px-2 py-2 text-sm lg:px-4 dark:text-[#E0E0E0]">
{node.token_count?.toLocaleString() || '-'}
</td>
<td className="px-2 py-2 text-sm md:px-4 dark:text-[#E0E0E0]">
{node.size_bytes ? formatBytes(node.size_bytes) : '-'}
</td>
<td className="w-10 px-2 py-2 text-sm lg:px-4">
<div ref={menuRef} className="relative">
<button
onClick={(e) => handleMenuClick(e, itemId)}
className="inline-flex h-[35px] w-[24px] shrink-0 items-center justify-center rounded-md transition-colors hover:bg-[#EBEBEB] dark:hover:bg-[#26272E] font-medium"
aria-label={t('settings.sources.menuAlt')}
>
<img
src={ThreeDots}
alt={t('settings.sources.menuAlt')}
className="opacity-60 hover:opacity-100"
/>
</button>
<ContextMenu
isOpen={activeMenuId === itemId}
setIsOpen={(isOpen) =>
setActiveMenuId(isOpen ? itemId : null)
}
options={getActionOptions(name, true, itemId)}
anchorRef={menuRef}
position="bottom-left"
offset={{ x: -4, y: 4 }}
/>
</div>
</td>
</tr>
);
}),
];
};
const currentDirectory = getCurrentDirectory();
const searchFiles = (
query: string,
structure: DirectoryStructure,
currentPath: string[] = [],
): SearchResult[] => {
let results: SearchResult[] = [];
Object.entries(structure).forEach(([name, node]) => {
const fullPath = [...currentPath, name].join('/');
if (name.toLowerCase().includes(query.toLowerCase())) {
results.push({
name,
path: fullPath,
isFile: !!node.type,
});
}
if (!node.type) {
// If it's a directory, search recursively
results = [
...results,
...searchFiles(query, node as DirectoryStructure, [
...currentPath,
name,
]),
];
}
});
return results;
};
const handleSearchSelect = (result: SearchResult) => {
if (result.isFile) {
const pathParts = result.path.split('/');
const fileName = pathParts.pop() || '';
setCurrentPath(pathParts);
setSelectedFile({
id: result.path,
name: fileName,
});
} else {
setCurrentPath(result.path.split('/'));
setSelectedFile(null);
}
setSearchQuery('');
setSearchResults([]);
};
const renderFileSearch = () => {
return (
<div className="relative w-52" ref={searchDropdownRef}>
<input
type="text"
value={searchQuery}
onChange={(e) => {
setSearchQuery(e.target.value);
if (directoryStructure) {
setSearchResults(searchFiles(e.target.value, directoryStructure));
}
}}
placeholder={t('settings.sources.searchFiles')}
className={`w-full h-[38px] border border-[#D1D9E0] px-4 py-2 dark:border-[#6A6A6A]
${searchQuery ? 'rounded-t-[24px]' : 'rounded-[24px]'}
bg-transparent focus:outline-none dark:text-[#E0E0E0]`}
/>
{searchQuery && (
<div className="absolute top-full left-0 right-0 z-10 max-h-[calc(100vh-200px)] w-full overflow-hidden rounded-b-[12px] border border-t-0 border-[#D1D9E0] bg-white shadow-lg dark:border-[#6A6A6A] dark:bg-[#1F2023] transition-all duration-200">
<div className="max-h-[calc(100vh-200px)] overflow-y-auto overflow-x-hidden overscroll-contain">
{searchResults.length === 0 ? (
<div className="py-2 text-center text-sm text-gray-500 dark:text-gray-400">
{t('settings.sources.noResults')}
</div>
) : (
searchResults.map((result, index) => (
<div
key={index}
onClick={() => handleSearchSelect(result)}
title={result.path}
className={`flex min-w-0 cursor-pointer items-center px-3 py-2 hover:bg-[#ECEEEF] dark:hover:bg-[#27282D] ${index !== searchResults.length - 1
? 'border-b border-[#D1D9E0] dark:border-[#6A6A6A]'
: ''
}`}
>
<img
src={result.isFile ? FileIcon : FolderIcon}
alt={
result.isFile
? t('settings.sources.fileAlt')
: t('settings.sources.folderAlt')
}
className="mr-2 h-4 w-4 flex-shrink-0"
/>
<span className="text-sm dark:text-[#E0E0E0] truncate flex-1">
{result.path.split('/').pop() || result.path}
</span>
</div>
))
)}
</div>
</div>
)}
</div>
);
};
const handleFileSearch = (searchQuery: string) => {
if (directoryStructure) {
return searchFiles(searchQuery, directoryStructure);
}
return [];
};
const handleFileSelect = (path: string) => {
const pathParts = path.split('/');
const fileName = pathParts.pop() || '';
setCurrentPath(pathParts);
setSelectedFile({
id: path,
name: fileName,
});
};
return (
<div>
{selectedFile ? (
<div className="flex">
<div className="flex-1">
<Chunks
documentId={docId}
documentName={sourceName}
handleGoBack={() => setSelectedFile(null)}
path={selectedFile.id}
onFileSearch={handleFileSearch}
onFileSelect={handleFileSelect}
/>
</div>
</div>
) : (
<div className="flex w-full max-w-full flex-col overflow-hidden">
<div className="mb-2">{renderPathNavigation()}</div>
<div className="w-full">
<div className="overflow-x-auto rounded-[6px] border border-[#D1D9E0] dark:border-[#6A6A6A]">
<table className="w-full min-w-[600px] table-auto bg-transparent">
<thead className="bg-gray-100 dark:bg-[#27282D]">
<tr className="border-b border-[#D1D9E0] dark:border-[#6A6A6A]">
<th className="min-w-[200px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.fileName')}
</th>
<th className="min-w-[80px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.tokens')}
</th>
<th className="min-w-[80px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
{t('settings.sources.size')}
</th>
<th className="w-[60px] px-2 py-3 text-left text-sm font-medium text-gray-700 lg:px-4 dark:text-[#59636E]">
<span className="sr-only">
{t('settings.sources.actions')}
</span>
</th>
</tr>
</thead>
<tbody className="[&>tr:last-child]:border-b-0">
{renderFileTree(currentDirectory)}
</tbody>
</table>
</div>
</div>
</div>
)}
<ConfirmationModal
message={
itemToDelete?.isFile
? t('settings.sources.confirmDelete')
: t('settings.sources.deleteDirectoryWarning', { name: itemToDelete?.name })
}
modalState={deleteModalState}
setModalState={setDeleteModalState}
handleSubmit={handleConfirmedDelete}
handleCancel={handleCancelDelete}
submitLabel={t('convTile.delete')}
variant="danger"
/>
</div>
);
};
export default FileTreeComponent;

View File

@@ -1,6 +1,6 @@
import React from 'react';
interface DocumentHeadProps {
interface HeadProps {
title?: string;
description?: string;
keywords?: string;
@@ -13,7 +13,7 @@ interface DocumentHeadProps {
children?: React.ReactNode;
}
export function DocumentHead({
export function Head({
title,
description,
keywords,
@@ -24,7 +24,7 @@ export function DocumentHead({
twitterTitle,
twitterDescription,
children,
}: DocumentHeadProps) {
}: HeadProps) {
return (
<>
{title && <title>{title}</title>}

View File

@@ -16,7 +16,9 @@ const MermaidRenderer: React.FC<MermaidRendererProps> = ({
isLoading,
}) => {
const [isDarkTheme] = useDarkTheme();
const diagramId = useRef(`mermaid-${crypto.randomUUID()}`);
const diagramId = useRef(
`mermaid-${Date.now()}-${Math.random().toString(36).substring(2)}`,
);
const status = useSelector(selectStatus);
const [error, setError] = useState<string | null>(null);
const [showCode, setShowCode] = useState<boolean>(false);

View File

@@ -10,7 +10,7 @@ const useTabs = () => {
const { t } = useTranslation();
const tabs = [
t('settings.general.label'),
t('settings.documents.label'),
t('settings.sources.label'),
t('settings.analytics.label'),
t('settings.logs.label'),
t('settings.tools.label'),

View File

@@ -8,7 +8,9 @@ interface SkeletonLoaderProps {
| 'logs'
| 'table'
| 'chatbot'
| 'dropdown';
| 'dropdown'
| 'chunkCards'
| 'sourceCards';
}
const SkeletonLoader: React.FC<SkeletonLoaderProps> = ({
@@ -182,6 +184,62 @@ const SkeletonLoader: React.FC<SkeletonLoaderProps> = ({
</>
);
const renderChunkCards = () => (
<>
{Array.from({ length: count }).map((_, index) => (
<div
key={`chunk-skel-${index}`}
className="relative flex h-[197px] flex-col rounded-[5.86px] border border-[#D1D9E0] dark:border-[#6A6A6A] overflow-hidden w-full max-w-[487px] animate-pulse"
>
<div className="w-full">
<div className="flex w-full items-center justify-between border-b border-[#D1D9E0] bg-[#F6F8FA] dark:bg-[#27282D] dark:border-[#6A6A6A] px-4 py-3">
<div className="h-4 bg-gray-300 dark:bg-gray-600 rounded w-20"></div>
</div>
<div className="px-4 pt-4 pb-6 space-y-3">
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-full"></div>
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-11/12"></div>
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-5/6"></div>
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-4/5"></div>
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-3/4"></div>
<div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-2/3"></div>
</div>
</div>
</div>
))}
</>
);
const renderSourceCards = () => (
<>
{Array.from({ length: count }).map((_, idx) => (
<div
key={`source-skel-${idx}`}
className="flex h-[130px] w-full flex-col rounded-2xl bg-[#F9F9F9] dark:bg-[#383838] p-3 animate-pulse"
>
<div className="w-full flex-1">
<div className="flex w-full items-center justify-between gap-2">
<div className="flex-1">
<div className="h-[13px] w-full rounded bg-gray-200 dark:bg-gray-700"></div>
</div>
<div className="w-6 h-6 rounded bg-gray-200 dark:bg-gray-700"></div>
</div>
</div>
<div className="flex flex-col items-start justify-start gap-1 pt-3">
<div className="flex items-center gap-2 mb-1">
<div className="w-3 h-3 rounded bg-gray-200 dark:bg-gray-700"></div>
<div className="h-[12px] w-20 rounded bg-gray-200 dark:bg-gray-700"></div>
</div>
<div className="flex items-center gap-2">
<div className="w-3 h-3 rounded bg-gray-200 dark:bg-gray-700"></div>
<div className="h-[12px] w-16 rounded bg-gray-200 dark:bg-gray-700"></div>
</div>
</div>
</div>
))}
</>
);
const componentMap = {
table: renderTable,
chatbot: renderChatbot,
@@ -189,8 +247,11 @@ const SkeletonLoader: React.FC<SkeletonLoaderProps> = ({
logs: renderLogs,
default: renderDefault,
analysis: renderAnalysis,
chunkCards: renderChunkCards,
sourceCards: renderSourceCards,
};
const render = componentMap[component] || componentMap.default;
return <>{render()}</>;

View File

@@ -158,7 +158,7 @@ function SourceDropdown({
</div>
)}
<ConfirmationModal
message={t('settings.documents.deleteWarning', {
message={t('settings.sources.deleteWarning', {
name: documentToDelete?.name,
})}
modalState={deleteModalState}

View File

@@ -135,7 +135,7 @@ export default function SourcesPopup({
type="text"
value={searchTerm}
onChange={(e) => setSearchTerm(e.target.value)}
placeholder={t('settings.documents.searchPlaceholder')}
placeholder={t('settings.sources.searchPlaceholder')}
borderVariant="thin"
className="mb-4"
labelBgClassName="bg-lotion dark:bg-charleston-green-2"
@@ -203,11 +203,11 @@ export default function SourcesPopup({
<div className="shrink-0 px-4 py-4 opacity-75 transition-opacity duration-200 hover:opacity-100 md:px-6">
<a
href="/settings/documents"
href="/settings/sources"
className="text-violets-are-blue inline-flex items-center gap-2 text-base font-medium"
onClick={onClose}
>
{t('settings.documents.goToDocuments')}
{t('settings.sources.goToSources')}
<img src={RedirectIcon} alt="Redirect" className="h-3 w-3" />
</a>
</div>
@@ -217,7 +217,7 @@ export default function SourcesPopup({
onClick={handleUploadClick}
className="border-violets-are-blue text-violets-are-blue hover:bg-violets-are-blue w-auto rounded-full border px-4 py-2 text-[14px] font-medium transition-colors duration-200 hover:text-white"
>
{t('settings.documents.uploadNew')}
{t('settings.sources.uploadNew')}
</button>
</div>
</div>

View File

@@ -0,0 +1,45 @@
export type DropdownOptionBase = {
id?: string;
type?: string;
};
export type StringOption = string;
export type NameIdOption = { name: string; id: string } & DropdownOptionBase;
export type LabelValueOption = {
label: string;
value: string;
} & DropdownOptionBase;
export type ValueDescriptionOption = {
value: number;
description: string;
} & DropdownOptionBase;
export type DropdownOption =
| StringOption
| NameIdOption
| LabelValueOption
| ValueDescriptionOption;
export type DropdownSelectedValue = DropdownOption | null;
export type OnSelectHandler<T extends DropdownOption = DropdownOption> = (
value: T,
) => void;
export interface DropdownProps<T extends DropdownOption = DropdownOption> {
options: T[];
selectedValue: DropdownSelectedValue;
onSelect: OnSelectHandler<T>;
size?: string;
rounded?: 'xl' | '3xl';
buttonClassName?: string;
optionsClassName?: string;
border?: 'border' | 'border-2';
showEdit?: boolean;
onEdit?: (value: NameIdOption) => void;
showDelete?: boolean | ((option: T) => boolean);
onDelete?: (id: string) => void;
placeholder?: string;
placeholderClassName?: string;
contentSize?: string;
}

View File

@@ -92,8 +92,7 @@ const ConversationBubble = forwardRef<
const [editInputBox, setEditInputBox] = useState<string>('');
const messageRef = useRef<HTMLDivElement>(null);
const [shouldShowToggle, setShouldShowToggle] = useState(false);
const [isLikeClicked, setIsLikeClicked] = useState(false);
const [isDislikeClicked, setIsDislikeClicked] = useState(false);
const [activeTooltip, setActiveTooltip] = useState<number | null>(null);
const [isSidebarOpen, setIsSidebarOpen] = useState<boolean>(false);
const editableQueryRef = useRef<HTMLDivElement>(null);
@@ -550,104 +549,71 @@ const ConversationBubble = forwardRef<
)}
{message && (
<div className="my-2 ml-2 flex justify-start">
<div
className={`relative mr-2 block items-center justify-center lg:invisible ${type !== 'ERROR' ? 'lg:group-hover:visible' : 'hidden'}`}
>
<div>
<CopyButton textToCopy={message} />
</div>
</div>
<div
className={`relative mr-2 block items-center justify-center lg:invisible ${type !== 'ERROR' ? 'lg:group-hover:visible' : 'hidden'}`}
>
<div>
<SpeakButton text={message} />
</div>
</div>
{type === 'ERROR' && (
{type === 'ERROR' ? (
<div className="relative mr-2 block items-center justify-center">
<div>{retryBtn}</div>
</div>
)}
{handleFeedback && (
) : (
<>
<div
className={`relative mr-2 flex items-center justify-center ${
feedback === 'LIKE' || isLikeClicked
? 'visible'
: 'lg:invisible'
} ${type !== 'ERROR' ? 'lg:group-hover:visible' : ''} ${feedback === 'DISLIKE' && type !== 'ERROR' ? 'hidden' : ''}`}
>
<div>
<div
className={`flex items-center justify-center rounded-full p-2 ${
isLikeHovered
? 'dark:bg-purple-taupe bg-[#EEEEEE]'
: 'bg-white-3000 dark:bg-transparent'
}`}
>
<Like
className={`cursor-pointer ${
isLikeClicked || feedback === 'LIKE'
? 'fill-white-3000 stroke-purple-30 dark:fill-transparent'
: 'stroke-gray-4000 fill-none'
}`}
onClick={() => {
if (feedback === undefined || feedback === null) {
handleFeedback?.('LIKE');
setIsLikeClicked(true);
setIsDislikeClicked(false);
} else if (feedback === 'LIKE') {
handleFeedback?.(null);
setIsLikeClicked(false);
setIsDislikeClicked(false);
}
}}
onMouseEnter={() => setIsLikeHovered(true)}
onMouseLeave={() => setIsLikeHovered(false)}
></Like>
</div>
</div>
<div className="relative mr-2 block items-center justify-center">
<CopyButton textToCopy={message} />
</div>
<div className="relative mr-2 block items-center justify-center">
<SpeakButton text={message} />
</div>
{handleFeedback && (
<>
<div className="relative mr-2 flex items-center justify-center">
<div>
<div
className={`flex items-center justify-center rounded-full p-2 ${
isLikeHovered
? 'dark:bg-purple-taupe bg-[#EEEEEE]'
: 'bg-white-3000 dark:bg-transparent'
}`}
>
<Like
className={`${feedback === 'LIKE' ? 'fill-white-3000 stroke-purple-30 dark:fill-transparent' : 'stroke-gray-4000 fill-none'} cursor-pointer`}
onClick={() => {
if (feedback === 'LIKE') {
handleFeedback?.(null);
} else {
handleFeedback?.('LIKE');
}
}}
onMouseEnter={() => setIsLikeHovered(true)}
onMouseLeave={() => setIsLikeHovered(false)}
></Like>
</div>
</div>
</div>
<div
className={`relative mr-2 flex items-center justify-center ${
feedback === 'DISLIKE' || isLikeClicked
? 'visible'
: 'lg:invisible'
} ${type !== 'ERROR' ? 'lg:group-hover:visible' : ''} ${feedback === 'LIKE' && type !== 'ERROR' ? 'hidden' : ''}`}
>
<div>
<div
className={`flex items-center justify-center rounded-full p-2 ${
isDislikeHovered
? 'dark:bg-purple-taupe bg-[#EEEEEE]'
: 'bg-white-3000 dark:bg-transparent'
}`}
>
<Dislike
className={`cursor-pointer ${
isDislikeClicked || feedback === 'DISLIKE'
? 'fill-white-3000 stroke-red-2000 dark:fill-transparent'
: 'stroke-gray-4000 fill-none'
}`}
onClick={() => {
if (feedback === undefined || feedback === null) {
handleFeedback?.('DISLIKE');
setIsDislikeClicked(true);
setIsLikeClicked(false);
} else if (feedback === 'DISLIKE') {
handleFeedback?.(null);
setIsLikeClicked(false);
setIsDislikeClicked(false);
}
}}
onMouseEnter={() => setIsDislikeHovered(true)}
onMouseLeave={() => setIsDislikeHovered(false)}
></Dislike>
<div className="relative mr-2 flex items-center justify-center">
<div>
<div
className={`flex items-center justify-center rounded-full p-2 ${
isDislikeHovered
? 'dark:bg-purple-taupe bg-[#EEEEEE]'
: 'bg-white-3000 dark:bg-transparent'
}`}
>
<Dislike
className={`${feedback === 'DISLIKE' ? 'fill-white-3000 stroke-red-2000 dark:fill-transparent' : 'stroke-gray-4000 fill-none'} cursor-pointer`}
onClick={() => {
if (feedback === 'DISLIKE') {
handleFeedback?.(null);
} else {
handleFeedback?.('DISLIKE');
}
}}
onMouseEnter={() => setIsDislikeHovered(true)}
onMouseLeave={() => setIsDislikeHovered(false)}
></Dislike>
</div>
</div>
</div>
</div>
</div>
</>
)}
</>
)}
</div>

View File

@@ -23,7 +23,7 @@ import {
updateQuery,
} from './sharedConversationSlice';
import { selectCompletedAttachments } from '../upload/uploadSlice';
import { DocumentHead } from '../components/DocumentHead';
import { Head as DocumentHead } from '../components/Head';
export const SharedConversation = () => {
const navigate = useNavigate();

View File

@@ -8,7 +8,6 @@ export function handleFetchAnswer(
signal: AbortSignal,
token: string | null,
selectedDocs: Doc | null,
history: Array<any> = [],
conversationId: string | null,
promptId: string | null,
chunks: string,
@@ -37,16 +36,8 @@ export function handleFetchAnswer(
title: any;
}
> {
history = history.map((item) => {
return {
prompt: item.prompt,
response: item.response,
tool_calls: item.tool_calls,
};
});
const payload: RetrievalPayload = {
question: question,
history: JSON.stringify(history),
conversation_id: conversationId,
prompt_id: promptId,
chunks: chunks,
@@ -94,7 +85,6 @@ export function handleFetchAnswerSteaming(
signal: AbortSignal,
token: string | null,
selectedDocs: Doc | null,
history: Array<any> = [],
conversationId: string | null,
promptId: string | null,
chunks: string,
@@ -105,17 +95,8 @@ export function handleFetchAnswerSteaming(
attachments?: string[],
save_conversation = true,
): Promise<Answer> {
history = history.map((item) => {
return {
prompt: item.prompt,
response: item.response,
thought: item.thought,
tool_calls: item.tool_calls,
};
});
const payload: RetrievalPayload = {
question: question,
history: JSON.stringify(history),
conversation_id: conversationId,
prompt_id: promptId,
chunks: chunks,
@@ -192,20 +173,11 @@ export function handleSearch(
token: string | null,
selectedDocs: Doc | null,
conversation_id: string | null,
history: Array<any> = [],
chunks: string,
token_limit: number,
) {
history = history.map((item) => {
return {
prompt: item.prompt,
response: item.response,
tool_calls: item.tool_calls,
};
});
const payload: RetrievalPayload = {
question: question,
history: JSON.stringify(history),
conversation_id: conversation_id,
chunks: chunks,
token_limit: token_limit,

View File

@@ -33,6 +33,8 @@ export interface Answer {
thought: string;
sources: { title: string; text: string; source: string }[];
tool_calls: ToolCallsType[];
structured?: boolean;
schema?: object;
}
export interface Query {
@@ -46,13 +48,14 @@ export interface Query {
tool_calls?: ToolCallsType[];
error?: string;
attachments?: { id: string; fileName: string }[];
structured?: boolean;
schema?: object;
}
export interface RetrievalPayload {
question: string;
active_docs?: string;
retriever?: string;
history: string;
conversation_id: string | null;
prompt_id?: string | null;
chunks: string;

View File

@@ -57,7 +57,6 @@ export const fetchAnswer = createAsyncThunk<
signal,
state.preference.token,
state.preference.selectedDocs!,
state.conversation.queries,
currentConversationId,
state.preference.prompt.id,
state.preference.chunks,
@@ -131,6 +130,18 @@ export const fetchAnswer = createAsyncThunk<
message: data.error,
}),
);
} else if (data.type === 'structured_answer') {
dispatch(
updateStreamingQuery({
conversationId: currentConversationId,
index: targetIndex,
query: {
response: data.answer,
structured: data.structured,
schema: data.schema,
},
}),
);
} else {
dispatch(
updateStreamingQuery({
@@ -153,7 +164,6 @@ export const fetchAnswer = createAsyncThunk<
signal,
state.preference.token,
state.preference.selectedDocs!,
state.conversation.queries,
state.conversation.conversationId,
state.preference.prompt.id,
state.preference.chunks,
@@ -252,6 +262,14 @@ export const conversationSlice = createSlice({
state.queries[index].response =
(state.queries[index].response || '') + query.response;
}
if (query.structured !== undefined) {
state.queries[index].structured = query.structured;
}
if (query.schema !== undefined) {
state.queries[index].schema = query.schema;
}
},
updateConversationId(
state,

View File

@@ -133,10 +133,10 @@ layer(base);
}
@utility table-default {
@apply block w-full table-auto justify-center overflow-auto rounded-xl border border-silver text-center dark:border-silver/40 dark:text-bright-gray;
@apply border-silver dark:border-silver/40 dark:text-bright-gray block w-full table-auto justify-center overflow-auto rounded-xl border text-center;
& th {
@apply text-nowrap p-4 font-normal text-gray-400;
@apply p-4 font-normal text-nowrap text-gray-400;
}
& th {
@@ -148,7 +148,7 @@ layer(base);
}
& td {
@apply w-full border-t border-silver px-4 py-2 dark:border-silver/40;
@apply border-silver dark:border-silver/40 w-full border-t px-4 py-2;
}
& td:last-child {
@@ -208,483 +208,482 @@ layer(base);
}
}
@layer base{
@layer base {
/*! normalize.css v8.0.1 | MIT License | github.com/necolas/normalize.css */
/* Document
/* Document
========================================================================== */
/**
/**
* 1. Correct the line height in all browsers.
* 2. Prevent adjustments of font size after orientation changes in iOS.
*/
html {
line-height: 1.15; /* 1 */
-webkit-text-size-adjust: 100%; /* 2 */
min-height: 100vh;
overflow-x: hidden;
}
html {
line-height: 1.15; /* 1 */
-webkit-text-size-adjust: 100%; /* 2 */
min-height: 100vh;
overflow-x: hidden;
}
/* Sections
/* Sections
========================================================================== */
/**
/**
* Remove the margin in all browsers.
*/
body {
margin: 0;
min-height: var(--viewport-height);
overflow-x: hidden;
font-family: 'Inter', sans-serif;
}
/*
body {
margin: 0;
min-height: var(--viewport-height);
overflow-x: hidden;
font-family: 'Inter', sans-serif;
}
/*
Avoid over-scrolling in mobile browsers
*/
@media only screen and (max-width: 500px) {
body,
html {
min-height: var(--viewport-height);
position: fixed;
width: 100%;
@media only screen and (max-width: 500px) {
body,
html {
min-height: var(--viewport-height);
position: fixed;
width: 100%;
}
}
}
/**
/**
* Render the `main` element consistently in IE.
*/
main {
display: block;
}
main {
display: block;
}
/**
/**
* Correct the font size and margin on `h1` elements within `section` and
* `article` contexts in Chrome, Firefox, and Safari.
*/
h1 {
font-size: 2em;
margin: 0.67em 0;
}
h1 {
font-size: 2em;
margin: 0.67em 0;
}
/* Grouping content
/* Grouping content
========================================================================== */
/**
/**
* 1. Add the correct box sizing in Firefox.
* 2. Show the overflow in Edge and IE.
*/
hr {
box-sizing: content-box; /* 1 */
height: 0; /* 1 */
overflow: visible; /* 2 */
}
hr {
box-sizing: content-box; /* 1 */
height: 0; /* 1 */
overflow: visible; /* 2 */
}
/**
/**
* 1. Correct the inheritance and scaling of font size in all browsers.
* 2. Correct the odd `em` font sizing in all browsers.
*/
pre {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
pre {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
/* Text-level semantics
/* Text-level semantics
========================================================================== */
/**
/**
* Remove the gray background on active links in IE 10.
*/
a {
background-color: transparent;
}
a {
background-color: transparent;
}
/**
/**
* 1. Remove the bottom border in Chrome 57-
* 2. Add the correct text decoration in Chrome, Edge, IE, Opera, and Safari.
*/
abbr[title] {
border-bottom: none; /* 1 */
text-decoration: underline; /* 2 */
text-decoration: underline dotted; /* 2 */
}
abbr[title] {
border-bottom: none; /* 1 */
text-decoration: underline; /* 2 */
text-decoration: underline dotted; /* 2 */
}
/**
/**
* Add the correct font weight in Chrome, Edge, and Safari.
*/
b,
strong {
font-weight: bolder;
}
b,
strong {
font-weight: bolder;
}
/**
/**
* 1. Correct the inheritance and scaling of font size in all browsers.
* 2. Correct the odd `em` font sizing in all browsers.
*/
code,
kbd,
samp {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
code,
kbd,
samp {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
/**
/**
* Add the correct font size in all browsers.
*/
small {
font-size: 80%;
}
small {
font-size: 80%;
}
/**
/**
* Prevent `sub` and `sup` elements from affecting the line height in
* all browsers.
*/
sub,
sup {
font-size: 75%;
line-height: 0;
position: relative;
vertical-align: baseline;
}
sub,
sup {
font-size: 75%;
line-height: 0;
position: relative;
vertical-align: baseline;
}
sub {
bottom: -0.25em;
}
sub {
bottom: -0.25em;
}
sup {
top: -0.5em;
}
sup {
top: -0.5em;
}
/* Embedded content
/* Embedded content
========================================================================== */
/**
/**
* Remove the border on images inside links in IE 10.
*/
img {
border-style: none;
}
img {
border-style: none;
}
/* Forms
/* Forms
========================================================================== */
/**
/**
* 1. Change the font styles in all browsers.
* 2. Remove the margin in Firefox and Safari.
*/
button,
input,
optgroup,
select,
textarea {
font-family: inherit; /* 1 */
font-size: 100%; /* 1 */
line-height: 1.15; /* 1 */
margin: 0; /* 2 */
}
button,
input,
optgroup,
select,
textarea {
font-family: inherit; /* 1 */
font-size: 100%; /* 1 */
line-height: 1.15; /* 1 */
margin: 0; /* 2 */
}
/**
/**
* Show the overflow in IE.
* 1. Show the overflow in Edge.
*/
button,
input {
/* 1 */
overflow: visible;
}
button,
input {
/* 1 */
overflow: visible;
}
/**
/**
* Remove the inheritance of text transform in Edge, Firefox, and IE.
* 1. Remove the inheritance of text transform in Firefox.
*/
button,
select {
/* 1 */
text-transform: none;
}
button,
select {
/* 1 */
text-transform: none;
}
/**
/**
* Correct the inability to style clickable types in iOS and Safari.
*/
button,
[type='button'],
[type='reset'],
[type='submit'] {
-webkit-appearance: button;
cursor: pointer;
}
button,
[type='button'],
[type='reset'],
[type='submit'] {
-webkit-appearance: button;
cursor: pointer;
}
/**
/**
* Remove the inner border and padding in Firefox.
*/
button::-moz-focus-inner,
[type='button']::-moz-focus-inner,
[type='reset']::-moz-focus-inner,
[type='submit']::-moz-focus-inner {
border-style: none;
padding: 0;
}
button::-moz-focus-inner,
[type='button']::-moz-focus-inner,
[type='reset']::-moz-focus-inner,
[type='submit']::-moz-focus-inner {
border-style: none;
padding: 0;
}
/**
/**
* Restore the focus styles unset by the previous rule.
*/
button:-moz-focusring,
[type='button']:-moz-focusring,
[type='reset']:-moz-focusring,
[type='submit']:-moz-focusring {
outline: 1px dotted ButtonText;
}
button:-moz-focusring,
[type='button']:-moz-focusring,
[type='reset']:-moz-focusring,
[type='submit']:-moz-focusring {
outline: 1px dotted ButtonText;
}
/**
/**
* Correct the padding in Firefox.
*/
fieldset {
padding: 0.35em 0.75em 0.625em;
}
fieldset {
padding: 0.35em 0.75em 0.625em;
}
/**
/**
* 1. Correct the text wrapping in Edge and IE.
* 2. Correct the color inheritance from `fieldset` elements in IE.
* 3. Remove the padding so developers are not caught out when they zero out
* `fieldset` elements in all browsers.
*/
legend {
box-sizing: border-box; /* 1 */
color: inherit; /* 2 */
display: table; /* 1 */
max-width: 100%; /* 1 */
padding: 0; /* 3 */
white-space: normal; /* 1 */
}
legend {
box-sizing: border-box; /* 1 */
color: inherit; /* 2 */
display: table; /* 1 */
max-width: 100%; /* 1 */
padding: 0; /* 3 */
white-space: normal; /* 1 */
}
/**
/**
* Add the correct vertical alignment in Chrome, Firefox, and Opera.
*/
progress {
vertical-align: baseline;
}
progress {
vertical-align: baseline;
}
/**
/**
* Remove the default vertical scrollbar in IE 10+.
*/
textarea {
overflow: auto;
}
textarea {
overflow: auto;
}
/**
/**
* 1. Add the correct box sizing in IE 10.
* 2. Remove the padding in IE 10.
*/
[type='checkbox'],
[type='radio'] {
box-sizing: border-box; /* 1 */
padding: 0; /* 2 */
}
[type='checkbox'],
[type='radio'] {
box-sizing: border-box; /* 1 */
padding: 0; /* 2 */
}
/**
/**
* Correct the cursor style of increment and decrement buttons in Chrome.
*/
[type='number']::-webkit-inner-spin-button,
[type='number']::-webkit-outer-spin-button {
height: auto;
}
[type='number']::-webkit-inner-spin-button,
[type='number']::-webkit-outer-spin-button {
height: auto;
}
/**
/**
* 1. Correct the odd appearance in Chrome and Safari.
* 2. Correct the outline style in Safari.
*/
[type='search'] {
-webkit-appearance: textfield; /* 1 */
outline-offset: -2px; /* 2 */
}
[type='search'] {
-webkit-appearance: textfield; /* 1 */
outline-offset: -2px; /* 2 */
}
/**
/**
* Remove the inner padding in Chrome and Safari on macOS.
*/
[type='search']::-webkit-search-decoration {
-webkit-appearance: none;
}
[type='search']::-webkit-search-decoration {
-webkit-appearance: none;
}
/**
/**
* 1. Correct the inability to style clickable types in iOS and Safari.
* 2. Change font properties to `inherit` in Safari.
*/
::-webkit-file-upload-button {
-webkit-appearance: button; /* 1 */
font: inherit; /* 2 */
}
::-webkit-file-upload-button {
-webkit-appearance: button; /* 1 */
font: inherit; /* 2 */
}
/* Interactive
/* Interactive
========================================================================== */
/*
/*
* Add the correct display in Edge, IE 10+, and Firefox.
*/
details {
display: block;
}
details {
display: block;
}
/*
/*
* Add the correct display in all browsers.
*/
summary {
display: list-item;
}
summary {
display: list-item;
}
/* Misc
/* Misc
========================================================================== */
/**
/**
* Add the correct display in IE 10+.
*/
template {
display: none;
}
template {
display: none;
}
/**
/**
* Add the correct display in IE 10.
*/
[hidden] {
display: none;
}
[contentEditable]:empty:before {
content: attr(placeholder);
color: #9ca3af;
opacity: 1;
}
/* third container laylout for Firefox */
@-moz-document url-prefix() {
.firefox {
padding: 32px;
[hidden] {
display: none;
}
}
/* For screens with a maximum width of 768px (mobile) */
@media (max-width: 768px) {
.firefox {
padding: 16px;
[contentEditable]:empty:before {
content: attr(placeholder);
color: #9ca3af;
opacity: 1;
}
}
@font-face {
font-family: 'Inter';
font-weight: 100 200 300 400 500 600 700 800 900;
src: url('/fonts/Inter-Variable.ttf');
}
/* third container laylout for Firefox */
@-moz-document url-prefix() {
.firefox {
padding: 32px;
}
}
@font-face {
font-family: 'IBMPlexMono-Medium';
font-weight: 500;
src: url('/fonts/IBMPlexMono-Medium.ttf');
}
/* For screens with a maximum width of 768px (mobile) */
@media (max-width: 768px) {
.firefox {
padding: 16px;
}
}
::-webkit-scrollbar {
width: 10;
}
/* Light mode specific autofill styles */
input:-webkit-autofill,
input:-webkit-autofill:hover,
input:-webkit-autofill:focus,
input:-webkit-autofill:active {
-webkit-text-fill-color: #343541 !important;
-webkit-box-shadow: 0 0 0 30px transparent inset !important;
transition: background-color 5000s ease-in-out 0s;
caret-color: #343541;
}
@font-face {
font-family: 'Inter';
font-weight: 100 200 300 400 500 600 700 800 900;
src: url('/fonts/Inter-Variable.ttf');
}
/* Dark mode specific autofill styles */
.dark input:-webkit-autofill,
.dark input:-webkit-autofill:hover,
.dark input:-webkit-autofill:focus,
.dark input:-webkit-autofill:active {
-webkit-text-fill-color: #e5e7eb !important;
-webkit-box-shadow: 0 0 0 30px transparent inset !important;
background-color: transparent !important;
caret-color: #e5e7eb;
}
@font-face {
font-family: 'IBMPlexMono-Medium';
font-weight: 500;
src: url('/fonts/IBMPlexMono-Medium.ttf');
}
/* Additional autocomplete dropdown styles for dark mode */
.dark input:-webkit-autofill::first-line {
color: #e5e7eb;
}
::-webkit-scrollbar {
width: 10;
}
/* Light mode specific autofill styles */
input:-webkit-autofill,
input:-webkit-autofill:hover,
input:-webkit-autofill:focus,
input:-webkit-autofill:active {
-webkit-text-fill-color: #343541 !important;
-webkit-box-shadow: 0 0 0 30px transparent inset !important;
transition: background-color 5000s ease-in-out 0s;
caret-color: #343541;
}
.inputbox-style {
resize: none;
padding-left: 36px;
padding-right: 36px;
}
/* Dark mode specific autofill styles */
.dark input:-webkit-autofill,
.dark input:-webkit-autofill:hover,
.dark input:-webkit-autofill:focus,
.dark input:-webkit-autofill:active {
-webkit-text-fill-color: #e5e7eb !important;
-webkit-box-shadow: 0 0 0 30px transparent inset !important;
background-color: transparent !important;
caret-color: #e5e7eb;
}
.bottom-safe {
bottom: env(safe-area-inset-bottom, 0);
}
/* Additional autocomplete dropdown styles for dark mode */
.dark input:-webkit-autofill::first-line {
color: #e5e7eb;
}
.ellipsis-text {
overflow: hidden;
display: -webkit-box;
-webkit-line-clamp: 3;
-webkit-box-orient: vertical;
text-overflow: ellipsis;
}
.inputbox-style {
resize: none;
padding-left: 36px;
padding-right: 36px;
}
.logs-table {
font-family: 'IBMPlexMono-Medium', system-ui;
}
.bottom-safe {
bottom: env(safe-area-inset-bottom, 0);
}
.fade-in {
animation: fadeIn 0.5s ease-in-out;
}
.ellipsis-text {
overflow: hidden;
display: -webkit-box;
-webkit-line-clamp: 3;
-webkit-box-orient: vertical;
text-overflow: ellipsis;
}
@keyframes fadeIn {
0% {
.logs-table {
font-family: 'IBMPlexMono-Medium', system-ui;
}
.fade-in {
animation: fadeIn 0.5s ease-in-out;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
.fade-in-bubble {
opacity: 0;
transform: translateY(10px);
animation: fadeInUp 0.5s forwards;
}
100% {
opacity: 1;
@keyframes fadeInUp {
to {
opacity: 1;
transform: translateY(0);
}
}
}
.fade-in-bubble {
opacity: 0;
transform: translateY(10px);
animation: fadeInUp 0.5s forwards;
}
@keyframes fadeInUp {
to {
opacity: 1;
transform: translateY(0);
}
}
}

View File

@@ -52,19 +52,22 @@
"default": "Default",
"add": "Add"
},
"documents": {
"title": "This table contains all the documents that are available to you and those you have uploaded",
"label": "Documents",
"name": "Document Name",
"sources": {
"title": "Here you can manage all of the source file that are available to you and those you have uploaded.",
"label": "Sources",
"name": "Source Name",
"date": "Vector Date",
"type": "Type",
"tokenUsage": "Token Usage",
"noData": "No existing Documents",
"noData": "No existing Sources",
"searchPlaceholder": "Search...",
"addNew": "Add New",
"addSource": "Add Source",
"addChunk": "Add Chunk",
"preLoaded": "Pre-loaded",
"private": "Private",
"sync": "Sync",
"syncing": "Syncing...",
"syncFrequency": {
"never": "Never",
"daily": "Daily",
@@ -74,12 +77,32 @@
"actions": "Actions",
"view": "View",
"deleteWarning": "Are you sure you want to delete \"{{name}}\"?",
"backToAll": "Back to all documents",
"confirmDelete": "Are you sure you want to delete this file? This action cannot be undone.",
"backToAll": "Back to all sources",
"chunks": "Chunks",
"noChunks": "No chunks found",
"noChunksAlt": "No chunks found",
"goToDocuments": "Go to Documents",
"uploadNew": "Upload new"
"goToSources": "Go to Sources",
"uploadNew": "Upload new",
"searchFiles": "Search files...",
"noResults": "No results found",
"fileName": "Name",
"tokens": "Tokens",
"size": "Size",
"fileAlt": "File",
"folderAlt": "Folder",
"parentFolderAlt": "Parent folder",
"menuAlt": "Menu",
"tokensUnit": "tokens",
"editAlt": "Edit",
"uploading": "Uploading…",
"deleting": "Deleting…",
"queued": "Queued: {{count}}",
"addFile": "Add file",
"uploadingFilesTitle": "Uploading files...",
"deletingTitle": "Deleting...",
"deleteDirectoryWarning": "Are you sure you want to delete the directory \"{{name}}\" and all its contents? This action cannot be undone.",
"searchAlt": "Search"
},
"apiKeys": {
"label": "Chatbots",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "Add Chunk",
"edit": "Edit Chunk",
"edit": "Edit",
"title": "Title",
"enterTitle": "Enter title",
"bodyText": "Body text",
"promptText": "Prompt Text",
"update": "Update",
"save": "Save",
"close": "Close",
"cancel": "Cancel",
"delete": "Delete",
"deleteConfirmation": "Are you sure you want to delete this chunk?"
}

View File

@@ -52,19 +52,22 @@
"default": "Predeterminado",
"addNew": "Añadir Nuevo"
},
"documents": {
"title": "Esta tabla contiene todos los documentos que están disponibles para ti y los que has subido",
"label": "Documentos",
"name": "Nombre del Documento",
"sources": {
"title": "Aquí puedes gestionar todos los archivos fuente que están disponibles para ti y los que has subido.",
"label": "Fuentes",
"name": "Nombre de la Fuente",
"date": "Fecha de Vector",
"type": "Tipo",
"tokenUsage": "Uso de Tokens",
"noData": "No hay documentos existentes",
"noData": "No hay fuentes existentes",
"searchPlaceholder": "Buscar...",
"addNew": "Agregar Nuevo",
"addSource": "Agregar Fuente",
"addChunk": "Agregar Fragmento",
"preLoaded": "Precargado",
"private": "Privado",
"sync": "Sincronizar",
"syncing": "Sincronizando...",
"syncFrequency": {
"never": "Nunca",
"daily": "Diario",
@@ -74,12 +77,32 @@
"actions": "Acciones",
"view": "Ver",
"deleteWarning": "¿Estás seguro de que deseas eliminar \"{{name}}\"?",
"backToAll": "Volver a todos los documentos",
"confirmDelete": "¿Estás seguro de que deseas eliminar este archivo? Esta acción no se puede deshacer.",
"backToAll": "Volver a todas las fuentes",
"chunks": "Fragmentos",
"noChunks": "No se encontraron fragmentos",
"noChunksAlt": "No se encontraron fragmentos",
"goToDocuments": "Ir a Documentos",
"uploadNew": "Subir nuevo"
"goToSources": "Ir a Fuentes",
"uploadNew": "Subir nuevo",
"searchFiles": "Buscar archivos...",
"noResults": "No se encontraron resultados",
"fileName": "Nombre",
"tokens": "Tokens",
"size": "Tamaño",
"fileAlt": "Archivo",
"folderAlt": "Carpeta",
"parentFolderAlt": "Carpeta padre",
"menuAlt": "Menú",
"tokensUnit": "tokens",
"editAlt": "Editar",
"uploading": "Subiendo…",
"deleting": "Eliminando…",
"queued": "En cola: {{count}}",
"addFile": "Añadir archivo",
"uploadingFilesTitle": "Subiendo archivos...",
"deletingTitle": "Eliminando...",
"deleteDirectoryWarning": "¿Está seguro de que desea eliminar el directorio \"{{name}}\" y todo su contenido? Esta acción no se puede deshacer.",
"searchAlt": "Buscar"
},
"apiKeys": {
"label": "Chatbots",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "Agregar Fragmento",
"edit": "Editar Fragmento",
"edit": "Editar",
"title": "Título",
"enterTitle": "Ingresar título",
"bodyText": "Texto del cuerpo",
"promptText": "Texto del prompt",
"update": "Actualizar",
"save": "Guardar",
"close": "Cerrar",
"cancel": "Cancelar",
"delete": "Eliminar",
"deleteConfirmation": "¿Estás seguro de que deseas eliminar este fragmento?"
}

View File

@@ -52,19 +52,22 @@
"default": "デフォルト",
"add": "追加"
},
"documents": {
"title": "この表には、利用可能なすべてのドキュメントとアップロードしたドキュメントが含まれています",
"label": "ドキュメント",
"name": "ドキュメント名",
"sources": {
"title": "ここでは、利用可能なすべてのソースファイルとアップロードしたファイルを管理できます",
"label": "ソース",
"name": "ソース名",
"date": "ベクトル日付",
"type": "タイプ",
"tokenUsage": "トークン使用量",
"noData": "既存のドキュメントがありません",
"noData": "既存のソースがありません",
"searchPlaceholder": "検索...",
"addNew": "新規追加",
"addSource": "ソースを追加",
"addChunk": "チャンクを追加",
"preLoaded": "プリロード済み",
"private": "プライベート",
"sync": "同期",
"syncing": "同期中...",
"syncFrequency": {
"never": "なし",
"daily": "毎日",
@@ -74,12 +77,32 @@
"actions": "アクション",
"view": "表示",
"deleteWarning": "\"{{name}}\"を削除してもよろしいですか?",
"backToAll": "すべてのドキュメントに戻る",
"confirmDelete": "このファイルを削除してもよろしいですか?この操作は元に戻せません。",
"backToAll": "すべてのソースに戻る",
"chunks": "チャンク",
"noChunks": "チャンクが見つかりません",
"noChunksAlt": "チャンクが見つかりません",
"goToDocuments": "ドキュメントへ移動",
"uploadNew": "新規アップロード"
"goToSources": "ソースへ移動",
"uploadNew": "新規アップロード",
"searchFiles": "ファイルを検索...",
"noResults": "結果が見つかりません",
"fileName": "名前",
"tokens": "トークン",
"size": "サイズ",
"fileAlt": "ファイル",
"folderAlt": "フォルダ",
"parentFolderAlt": "親フォルダ",
"menuAlt": "メニュー",
"tokensUnit": "トークン",
"editAlt": "編集",
"uploading": "アップロード中…",
"deleting": "削除中…",
"queued": "キュー: {{count}}",
"addFile": "ファイルを追加",
"uploadingFilesTitle": "ファイルをアップロード中...",
"deletingTitle": "削除中...",
"deleteDirectoryWarning": "ディレクトリ \"{{name}}\" とその内容をすべて削除してもよろしいですか?この操作は元に戻せません。",
"searchAlt": "検索"
},
"apiKeys": {
"label": "チャットボット",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "チャンクを追加",
"edit": "チャンクを編集",
"edit": "編集",
"title": "タイトル",
"enterTitle": "タイトルを入力",
"bodyText": "本文",
"promptText": "プロンプトテキスト",
"update": "更新",
"save": "保存",
"close": "閉じる",
"cancel": "キャンセル",
"delete": "削除",
"deleteConfirmation": "このチャンクを削除してもよろしいですか?"
}

View File

@@ -52,19 +52,22 @@
"default": "По умолчанию",
"add": "Добавить"
},
"documents": {
"title": "Эта таблица содержит все документы, которые доступны вам и те, которые вы загрузили",
"label": "Документы",
"name": "Название документа",
"sources": {
"title": "Здесь вы можете управлять всеми исходными файлами, которые доступны вам и которые вы загрузили.",
"label": "Источники",
"name": "Название источника",
"date": "Дата вектора",
"type": "Тип",
"tokenUsage": "Использование токена",
"noData": "Нет существующих документов",
"noData": "Нет существующих источников",
"searchPlaceholder": "Поиск...",
"addNew": "добавить новый",
"addSource": "Добавить источник",
"addChunk": "Добавить фрагмент",
"preLoaded": "Предзагруженный",
"private": "Частный",
"sync": "Синхронизация",
"syncing": "Синхронизация...",
"syncFrequency": {
"never": "Никогда",
"daily": "Ежедневно",
@@ -74,12 +77,32 @@
"actions": "Действия",
"view": "Просмотр",
"deleteWarning": "Вы уверены, что хотите удалить \"{{name}}\"?",
"backToAll": "Вернуться ко всем документам",
"confirmDelete": "Вы уверены, что хотите удалить этот файл? Это действие нельзя отменить.",
"backToAll": "Вернуться ко всем источникам",
"chunks": "Фрагменты",
"noChunks": "Фрагменты не найдены",
"noChunksAlt": "Фрагменты не найдены",
"goToDocuments": "Перейти к документам",
"uploadNew": "Загрузить новый"
"goToSources": "Перейти к источникам",
"uploadNew": "Загрузить новый",
"searchFiles": "Поиск файлов...",
"noResults": "Результаты не найдены",
"fileName": "Имя",
"tokens": "Токены",
"size": "Размер",
"fileAlt": "Файл",
"folderAlt": "Папка",
"parentFolderAlt": "Родительская папка",
"menuAlt": "Меню",
"tokensUnit": "токенов",
"editAlt": "Редактировать",
"uploading": "Загрузка…",
"deleting": "Удаление…",
"queued": "В очереди: {{count}}",
"addFile": "Добавить файл",
"uploadingFilesTitle": "Загрузка файлов...",
"deletingTitle": "Удаление...",
"deleteDirectoryWarning": "Вы уверены, что хотите удалить каталог \"{{name}}\" и все его содержимое? Это действие нельзя отменить.",
"searchAlt": "Поиск"
},
"apiKeys": {
"label": "API ключи",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "Добавить фрагмент",
"edit": "Редактировать фрагмент",
"edit": "Редактировать",
"title": "Заголовок",
"enterTitle": "Введите заголовок",
"bodyText": "Текст",
"promptText": "Текст подсказки",
"update": "Обновить",
"save": "Сохранить",
"close": "Закрыть",
"cancel": "Отмена",
"delete": "Удалить",
"deleteConfirmation": "Вы уверены, что хотите удалить этот фрагмент?"
}

View File

@@ -52,19 +52,22 @@
"default": "預設",
"add": "添加"
},
"documents": {
"title": "此表格包含所有可供您使用的文件以及您上傳的文件",
"label": "文件",
"name": "文件名稱",
"sources": {
"title": "在這裡您可以管理所有可用的來源檔案以及您上傳的檔案。",
"label": "來源",
"name": "來源名稱",
"date": "向量日期",
"type": "類型",
"tokenUsage": "Token 使用量",
"noData": "沒有現有的文件",
"noData": "沒有現有的來源",
"searchPlaceholder": "搜尋...",
"addNew": "新增文件",
"addSource": "新增來源",
"addChunk": "新增區塊",
"preLoaded": "預載入",
"private": "私人",
"sync": "同步",
"syncing": "同步中...",
"syncFrequency": {
"never": "從不",
"daily": "每天",
@@ -74,12 +77,32 @@
"actions": "操作",
"view": "查看",
"deleteWarning": "您確定要刪除 \"{{name}}\" 嗎?",
"backToAll": "返回所有文件",
"confirmDelete": "您確定要刪除此檔案嗎?此操作無法復原。",
"backToAll": "返回所有來源",
"chunks": "文本塊",
"noChunks": "未找到文本塊",
"noChunksAlt": "未找到文本塊",
"goToDocuments": "前往文件",
"uploadNew": "上傳新文件"
"goToSources": "前往來源",
"uploadNew": "上傳新文件",
"searchFiles": "搜尋檔案...",
"noResults": "未找到結果",
"fileName": "名稱",
"tokens": "Token",
"size": "大小",
"fileAlt": "檔案",
"folderAlt": "資料夾",
"parentFolderAlt": "上層資料夾",
"menuAlt": "選單",
"tokensUnit": "Token",
"editAlt": "編輯",
"uploading": "正在上傳…",
"deleting": "正在刪除…",
"queued": "已排隊:{{count}}",
"addFile": "新增檔案",
"uploadingFilesTitle": "正在上傳檔案...",
"deletingTitle": "正在刪除...",
"deleteDirectoryWarning": "您確定要刪除目錄 \"{{name}}\" 及其所有內容嗎?此操作無法復原。",
"searchAlt": "搜尋"
},
"apiKeys": {
"label": "聊天機器人",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "新增區塊",
"edit": "編輯區塊",
"edit": "編輯",
"title": "標題",
"enterTitle": "輸入標題",
"bodyText": "內文",
"promptText": "提示文字",
"update": "更新",
"save": "儲存",
"close": "關閉",
"cancel": "取消",
"delete": "刪除",
"deleteConfirmation": "您確定要刪除此區塊嗎?"
}

View File

@@ -52,19 +52,22 @@
"default": "默认",
"add": "添加"
},
"documents": {
"title": "此表格包含所有可供您使用的文档以及您上传的文",
"label": "文档",
"name": "文件名称",
"sources": {
"title": "在这里您可以管理所有可用的源文件以及您上传的文件。",
"label": "来源",
"name": "来源名称",
"date": "向量日期",
"type": "类型",
"tokenUsage": "令牌使用",
"noData": "没有现有的文档",
"noData": "没有现有的来源",
"searchPlaceholder": "搜索...",
"addNew": "添加新文档",
"addSource": "添加来源",
"addChunk": "添加块",
"preLoaded": "预加载",
"private": "私有",
"sync": "同步",
"syncing": "同步中...",
"syncFrequency": {
"never": "从不",
"daily": "每天",
@@ -74,12 +77,32 @@
"actions": "操作",
"view": "查看",
"deleteWarning": "您确定要删除 \"{{name}}\" 吗?",
"backToAll": "返回所有文档",
"confirmDelete": "您确定要删除此文件吗?此操作无法撤销。",
"backToAll": "返回所有来源",
"chunks": "文本块",
"noChunks": "未找到文本块",
"noChunksAlt": "未找到文本块",
"goToDocuments": "前往文档",
"uploadNew": "上传新文档"
"goToSources": "前往来源",
"uploadNew": "上传新文档",
"searchFiles": "搜索文件...",
"noResults": "未找到结果",
"fileName": "名称",
"tokens": "令牌",
"size": "大小",
"fileAlt": "文件",
"folderAlt": "文件夹",
"parentFolderAlt": "父文件夹",
"menuAlt": "菜单",
"tokensUnit": "令牌",
"editAlt": "编辑",
"uploading": "正在上传…",
"deleting": "正在删除…",
"queued": "已排队:{{count}}",
"addFile": "添加文件",
"uploadingFilesTitle": "正在上传文件...",
"deletingTitle": "正在删除...",
"deleteDirectoryWarning": "确定要删除目录 \"{{name}}\" 及其所有内容吗?此操作无法撤销。",
"searchAlt": "搜索"
},
"apiKeys": {
"label": "聊天机器人",
@@ -250,13 +273,14 @@
},
"chunk": {
"add": "添加块",
"edit": "编辑",
"edit": "编辑",
"title": "标题",
"enterTitle": "输入标题",
"bodyText": "正文",
"promptText": "提示文本",
"update": "更新",
"save": "保存",
"close": "关闭",
"cancel": "取消",
"delete": "删除",
"deleteConfirmation": "您确定要删除此块吗?"
}

View File

@@ -12,6 +12,7 @@ export type Doc = {
type?: string;
retriever?: string;
syncFrequency?: string;
isNested?: boolean;
};
export type GetDocsResponse = {

View File

@@ -1,788 +0,0 @@
import React, { useCallback, useEffect, useRef, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useDispatch, useSelector } from 'react-redux';
import userService from '../api/services/userService';
import ArrowLeft from '../assets/arrow-left.svg';
import caretSort from '../assets/caret-sort.svg';
import Edit from '../assets/edit.svg';
import EyeView from '../assets/eye-view.svg';
import NoFilesDarkIcon from '../assets/no-files-dark.svg';
import NoFilesIcon from '../assets/no-files.svg';
import Trash from '../assets/red-trash.svg';
import SyncIcon from '../assets/sync.svg';
import ThreeDots from '../assets/three-dots.svg';
import ContextMenu, { MenuOption } from '../components/ContextMenu';
import Pagination from '../components/DocumentPagination';
import DropdownMenu from '../components/DropdownMenu';
import Input from '../components/Input';
import SkeletonLoader from '../components/SkeletonLoader';
import Spinner from '../components/Spinner';
import { useDarkTheme, useLoaderState } from '../hooks';
import ChunkModal from '../modals/ChunkModal';
import ConfirmationModal from '../modals/ConfirmationModal';
import { ActiveState, Doc, DocumentsProps } from '../models/misc';
import { getDocs, getDocsWithPagination } from '../preferences/preferenceApi';
import {
selectToken,
setPaginatedDocuments,
setSourceDocs,
} from '../preferences/preferenceSlice';
import Upload from '../upload/Upload';
import { formatDate } from '../utils/dateTimeUtils';
import { ChunkType } from './types';
const formatTokens = (tokens: number): string => {
const roundToTwoDecimals = (num: number): string => {
return (Math.round((num + Number.EPSILON) * 100) / 100).toString();
};
if (tokens >= 1_000_000_000) {
return roundToTwoDecimals(tokens / 1_000_000_000) + 'b';
} else if (tokens >= 1_000_000) {
return roundToTwoDecimals(tokens / 1_000_000) + 'm';
} else if (tokens >= 1_000) {
return roundToTwoDecimals(tokens / 1_000) + 'k';
} else {
return tokens.toString();
}
};
export default function Documents({
paginatedDocuments,
handleDeleteDocument,
}: DocumentsProps) {
const { t } = useTranslation();
const dispatch = useDispatch();
const token = useSelector(selectToken);
const [searchTerm, setSearchTerm] = useState<string>('');
const [modalState, setModalState] = useState<ActiveState>('INACTIVE');
const [isOnboarding, setIsOnboarding] = useState<boolean>(false);
const [loading, setLoading] = useLoaderState(false);
const [sortField, setSortField] = useState<'date' | 'tokens'>('date');
const [sortOrder, setSortOrder] = useState<'asc' | 'desc'>('desc');
// Pagination
const [currentPage, setCurrentPage] = useState<number>(1);
const [rowsPerPage, setRowsPerPage] = useState<number>(10);
const [totalPages, setTotalPages] = useState<number>(1);
const [activeMenuId, setActiveMenuId] = useState<string | null>(null);
const menuRefs = useRef<{
[key: string]: React.RefObject<HTMLDivElement | null>;
}>({});
// Create or get a ref for each document wrapper div (not the td)
const getMenuRef = (docId: string) => {
if (!menuRefs.current[docId]) {
menuRefs.current[docId] = React.createRef<HTMLDivElement>();
}
return menuRefs.current[docId];
};
const handleMenuClick = (e: React.MouseEvent, docId: string) => {
e.preventDefault();
e.stopPropagation();
const isAnyMenuOpen =
(syncMenuState.isOpen && syncMenuState.docId === docId) ||
activeMenuId === docId;
if (isAnyMenuOpen) {
setSyncMenuState((prev) => ({ ...prev, isOpen: false, docId: null }));
setActiveMenuId(null);
return;
}
setActiveMenuId(docId);
};
useEffect(() => {
const handleClickOutside = (event: MouseEvent) => {
if (activeMenuId) {
const activeRef = menuRefs.current[activeMenuId];
if (
activeRef?.current &&
!activeRef.current.contains(event.target as Node)
) {
setActiveMenuId(null);
}
}
};
document.addEventListener('mousedown', handleClickOutside);
return () => document.removeEventListener('mousedown', handleClickOutside);
}, [activeMenuId]);
const currentDocuments = paginatedDocuments ?? [];
const syncOptions = [
{ label: t('settings.documents.syncFrequency.never'), value: 'never' },
{ label: t('settings.documents.syncFrequency.daily'), value: 'daily' },
{ label: t('settings.documents.syncFrequency.weekly'), value: 'weekly' },
{ label: t('settings.documents.syncFrequency.monthly'), value: 'monthly' },
];
const [showDocumentChunks, setShowDocumentChunks] = useState<Doc>();
const [isMenuOpen, setIsMenuOpen] = useState(false);
const [syncMenuState, setSyncMenuState] = useState<{
isOpen: boolean;
docId: string | null;
document: Doc | null;
}>({
isOpen: false,
docId: null,
document: null,
});
const refreshDocs = useCallback(
(
field: 'date' | 'tokens' | undefined,
pageNumber?: number,
rows?: number,
) => {
const page = pageNumber ?? currentPage;
const rowsPerPg = rows ?? rowsPerPage;
// If field is undefined, (Pagination or Search) use the current sortField
const newSortField = field ?? sortField;
// If field is undefined, (Pagination or Search) use the current sortOrder
const newSortOrder =
field === sortField
? sortOrder === 'asc'
? 'desc'
: 'asc'
: sortOrder;
// If field is defined, update the sortField and sortOrder
if (field) {
setSortField(newSortField);
setSortOrder(newSortOrder);
}
setLoading(true);
getDocsWithPagination(
newSortField,
newSortOrder,
page,
rowsPerPg,
searchTerm,
token,
)
.then((data) => {
dispatch(setPaginatedDocuments(data ? data.docs : []));
setTotalPages(data ? data.totalPages : 0);
})
.catch((error) => console.error(error))
.finally(() => {
setLoading(false);
});
},
[currentPage, rowsPerPage, sortField, sortOrder, searchTerm],
);
const handleManageSync = (doc: Doc, sync_frequency: string) => {
setLoading(true);
userService
.manageSync({ source_id: doc.id, sync_frequency }, token)
.then(() => {
return getDocs(token);
})
.then((data) => {
dispatch(setSourceDocs(data));
return getDocsWithPagination(
sortField,
sortOrder,
currentPage,
rowsPerPage,
searchTerm,
token,
);
})
.then((paginatedData) => {
dispatch(
setPaginatedDocuments(paginatedData ? paginatedData.docs : []),
);
setTotalPages(paginatedData ? paginatedData.totalPages : 0);
})
.catch((error) => console.error('Error in handleManageSync:', error))
.finally(() => {
setLoading(false);
});
};
const [documentToDelete, setDocumentToDelete] = useState<{
index: number;
document: Doc;
} | null>(null);
const [deleteModalState, setDeleteModalState] =
useState<ActiveState>('INACTIVE');
const handleDeleteConfirmation = (index: number, document: Doc) => {
setDocumentToDelete({ index, document });
setDeleteModalState('ACTIVE');
};
const handleConfirmedDelete = () => {
if (documentToDelete) {
handleDeleteDocument(documentToDelete.index, documentToDelete.document);
setDeleteModalState('INACTIVE');
setDocumentToDelete(null);
}
};
const getActionOptions = (index: number, document: Doc): MenuOption[] => {
const actions: MenuOption[] = [
{
icon: EyeView,
label: t('settings.documents.view'),
onClick: () => {
setShowDocumentChunks(document);
},
iconWidth: 18,
iconHeight: 18,
variant: 'primary',
},
];
if (document.syncFrequency) {
actions.push({
icon: SyncIcon,
label: t('settings.documents.sync'),
onClick: () => {
setSyncMenuState({
isOpen: true,
docId: document.id ?? null,
document: document,
});
},
iconWidth: 14,
iconHeight: 14,
variant: 'primary',
});
}
actions.push({
icon: Trash,
label: t('convTile.delete'),
onClick: () => {
handleDeleteConfirmation(index, document);
},
iconWidth: 18,
iconHeight: 18,
variant: 'danger',
});
return actions;
};
useEffect(() => {
refreshDocs(undefined, 1, rowsPerPage);
}, [searchTerm]);
return showDocumentChunks ? (
<DocumentChunks
document={showDocumentChunks}
handleGoBack={() => {
setShowDocumentChunks(undefined);
}}
/>
) : (
<div className="mt-8 flex w-full max-w-full flex-col overflow-hidden">
<div className="relative flex grow flex-col">
<div className="mb-6">
<h2 className="text-sonic-silver text-base font-medium">
{t('settings.documents.title')}
</h2>
</div>
<div className="mb-6 flex flex-col items-start justify-between gap-3 sm:flex-row sm:items-center">
<div className="w-full sm:w-auto">
<label htmlFor="document-search-input" className="sr-only">
{t('settings.documents.searchPlaceholder')}
</label>
<Input
maxLength={256}
placeholder={t('settings.documents.searchPlaceholder')}
name="Document-search-input"
type="text"
id="document-search-input"
value={searchTerm}
onChange={(e) => {
setSearchTerm(e.target.value);
setCurrentPage(1);
}}
borderVariant="thin"
/>
</div>
<button
className="bg-purple-30 hover:bg-violets-are-blue flex h-[32px] min-w-[108px] items-center justify-center rounded-full px-4 text-sm whitespace-normal text-white"
title={t('settings.documents.addNew')}
onClick={() => {
setIsOnboarding(false);
setModalState('ACTIVE');
}}
>
{t('settings.documents.addNew')}
</button>
</div>
<div className="relative w-full">
<div className="dark:border-silver/40 overflow-hidden rounded-md border border-gray-300">
<div className="table-scroll overflow-x-auto">
<table className="w-full table-auto">
<thead>
<tr className="dark:border-silver/40 border-b border-gray-300">
<th className="text-sonic-silver w-[45%] px-4 py-3 text-left text-xs font-medium">
{t('settings.documents.name')}
</th>
<th className="text-sonic-silver w-[30%] px-4 py-3 text-left text-xs font-medium">
<div className="flex items-center justify-start">
{t('settings.documents.date')}
<img
className="ml-2 cursor-pointer"
onClick={() => refreshDocs('date')}
src={caretSort}
alt="sort"
/>
</div>
</th>
<th className="text-sonic-silver w-[15%] px-4 py-3 text-left text-xs font-medium">
<div className="flex items-center justify-start">
<span className="hidden sm:inline">
{t('settings.documents.tokenUsage')}
</span>
<span className="sm:hidden">
{t('settings.documents.tokenUsage')}
</span>
<img
className="ml-2 cursor-pointer"
onClick={() => refreshDocs('tokens')}
src={caretSort}
alt="sort"
/>
</div>
</th>
<th className="sr-only w-[10%] px-4 py-3">
{t('settings.documents.actions')}
</th>
</tr>
</thead>
<tbody className="dark:divide-silver/40 divide-y divide-gray-300">
{loading ? (
<SkeletonLoader component="table" />
) : !currentDocuments?.length ? (
<tr>
<td
colSpan={4}
className="bg-transparent py-4 text-center text-gray-700 dark:text-neutral-200"
>
{t('settings.documents.noData')}
</td>
</tr>
) : (
currentDocuments.map((document, index) => {
const docId = document.id ? document.id.toString() : '';
return (
<tr key={docId} className="group transition-colors">
<td
className="max-w-0 min-w-48 truncate px-4 py-4 text-sm font-semibold text-gray-700 group-hover:bg-gray-50 dark:text-[#E0E0E0] dark:group-hover:bg-gray-800/50"
title={document.name}
>
{document.name}
</td>
<td className="px-4 py-4 text-sm whitespace-nowrap text-gray-700 group-hover:bg-gray-50 dark:text-[#E0E0E0] dark:group-hover:bg-gray-800/50">
{document.date ? formatDate(document.date) : ''}
</td>
<td className="px-4 py-4 text-sm whitespace-nowrap text-gray-700 group-hover:bg-gray-50 dark:text-[#E0E0E0] dark:group-hover:bg-gray-800/50">
{document.tokens
? formatTokens(+document.tokens)
: ''}
</td>
<td
className="px-4 py-4 text-right group-hover:bg-gray-50 dark:group-hover:bg-gray-800/50"
onClick={(e) => e.stopPropagation()}
>
<div
ref={getMenuRef(docId)}
className="relative flex items-center justify-end gap-3"
>
{document.syncFrequency && (
<DropdownMenu
name={t('settings.documents.sync')}
options={syncOptions}
onSelect={(value: string) => {
handleManageSync(document, value);
}}
defaultValue={document.syncFrequency}
icon={SyncIcon}
isOpen={
syncMenuState.docId === docId &&
syncMenuState.isOpen
}
onOpenChange={(isOpen) => {
setSyncMenuState((prev) => ({
...prev,
isOpen,
docId: isOpen ? docId : null,
document: isOpen ? document : null,
}));
}}
anchorRef={getMenuRef(docId)}
position="bottom-left"
offset={{ x: 24, y: -24 }}
className="min-w-[120px]"
/>
)}
<button
onClick={(e) => handleMenuClick(e, docId)}
className="inline-flex h-8 w-8 shrink-0 items-center justify-center rounded-full transition-colors hover:bg-gray-100 dark:hover:bg-gray-700"
aria-label="Open menu"
data-testid={`menu-button-${docId}`}
>
<img
src={ThreeDots}
alt={t('convTile.menu')}
className="h-4 w-4 opacity-60 hover:opacity-100"
/>
</button>
<ContextMenu
isOpen={activeMenuId === docId}
setIsOpen={(isOpen) => {
setActiveMenuId(isOpen ? docId : null);
}}
options={getActionOptions(index, document)}
anchorRef={getMenuRef(docId)}
position="bottom-left"
offset={{ x: 48, y: 0 }}
className="z-50"
/>
</div>
</td>
</tr>
);
})
)}
</tbody>
</table>
</div>
</div>
</div>
</div>
<div className="mt-auto pt-4">
<Pagination
currentPage={currentPage}
totalPages={totalPages}
rowsPerPage={rowsPerPage}
onPageChange={(page) => {
setCurrentPage(page);
refreshDocs(undefined, page, rowsPerPage);
}}
onRowsPerPageChange={(rows) => {
setRowsPerPage(rows);
setCurrentPage(1);
refreshDocs(undefined, 1, rows);
}}
/>
</div>
{modalState === 'ACTIVE' && (
<Upload
receivedFile={[]}
setModalState={setModalState}
isOnboarding={isOnboarding}
renderTab={null}
close={() => setModalState('INACTIVE')}
onSuccessfulUpload={() =>
refreshDocs(undefined, currentPage, rowsPerPage)
}
/>
)}
{deleteModalState === 'ACTIVE' && documentToDelete && (
<ConfirmationModal
message={t('settings.documents.deleteWarning', {
name: documentToDelete.document.name,
})}
modalState={deleteModalState}
setModalState={setDeleteModalState}
handleSubmit={handleConfirmedDelete}
handleCancel={() => {
setDeleteModalState('INACTIVE');
setDocumentToDelete(null);
}}
submitLabel={t('convTile.delete')}
variant="danger"
/>
)}
</div>
);
}
function DocumentChunks({
document,
handleGoBack,
}: {
document: Doc;
handleGoBack: () => void;
}) {
const { t } = useTranslation();
const token = useSelector(selectToken);
const [isDarkTheme] = useDarkTheme();
const [paginatedChunks, setPaginatedChunks] = useState<ChunkType[]>([]);
const [page, setPage] = useState(1);
const [perPage, setPerPage] = useState(5);
const [totalChunks, setTotalChunks] = useState(0);
const [loading, setLoading] = useLoaderState(true);
const [searchTerm, setSearchTerm] = useState<string>('');
const [addModal, setAddModal] = useState<ActiveState>('INACTIVE');
const [editModal, setEditModal] = useState<{
state: ActiveState;
chunk: ChunkType | null;
}>({ state: 'INACTIVE', chunk: null });
const fetchChunks = () => {
setLoading(true);
try {
userService
.getDocumentChunks(document.id ?? '', page, perPage, token)
.then((response) => {
if (!response.ok) {
setLoading(false);
setPaginatedChunks([]);
throw new Error('Failed to fetch chunks data');
}
return response.json();
})
.then((data) => {
setPage(data.page);
setPerPage(data.per_page);
setTotalChunks(data.total);
setPaginatedChunks(data.chunks);
setLoading(false);
});
} catch (e) {
console.log(e);
setLoading(false);
}
};
const handleAddChunk = (title: string, text: string) => {
try {
userService
.addChunk(
{
id: document.id ?? '',
text: text,
metadata: {
title: title,
},
},
token,
)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to add chunk');
}
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
const handleUpdateChunk = (title: string, text: string, chunk: ChunkType) => {
try {
userService
.updateChunk(
{
id: document.id ?? '',
chunk_id: chunk.doc_id,
text: text,
metadata: {
title: title,
},
},
token,
)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to update chunk');
}
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
const handleDeleteChunk = (chunk: ChunkType) => {
try {
userService
.deleteChunk(document.id ?? '', chunk.doc_id, token)
.then((response) => {
if (!response.ok) {
throw new Error('Failed to delete chunk');
}
setEditModal({ state: 'INACTIVE', chunk: null });
fetchChunks();
});
} catch (e) {
console.log(e);
}
};
React.useEffect(() => {
fetchChunks();
}, [page, perPage]);
return (
<div className="mt-8 flex flex-col">
<div className="text-eerie-black dark:text-bright-gray mb-3 flex items-center gap-3 text-sm">
<button
className="rounded-full border p-3 text-sm text-gray-400 dark:border-0 dark:bg-[#28292D] dark:text-gray-500 dark:hover:bg-[#2E2F34]"
onClick={handleGoBack}
>
<img src={ArrowLeft} alt="left-arrow" className="h-3 w-3" />
</button>
<p className="mt-px">{t('settings.documents.backToAll')}</p>
</div>
<div className="my-3 flex items-center justify-between gap-1">
<div className="text-eerie-black dark:text-bright-gray flex w-full items-center gap-2 sm:w-auto">
<p className="hidden text-2xl font-semibold sm:flex">{`${totalChunks} ${t('settings.documents.chunks')}`}</p>
<label htmlFor="chunk-search-input" className="sr-only">
{t('settings.documents.searchPlaceholder')}
</label>
<Input
maxLength={256}
placeholder={t('settings.documents.searchPlaceholder')}
name="chunk-search-input"
type="text"
id="chunk-search-input"
value={searchTerm}
onChange={(e) => {
setSearchTerm(e.target.value);
}}
borderVariant="thin"
/>
</div>
<button
className="bg-purple-30 hover:bg-violets-are-blue flex h-[32px] min-w-[108px] items-center justify-center rounded-full px-4 text-sm whitespace-normal text-white"
title={t('settings.documents.addNew')}
onClick={() => setAddModal('ACTIVE')}
>
{t('settings.documents.addNew')}
</button>
</div>
{loading ? (
<div className="grid grid-cols-1 gap-6 sm:grid-cols-2 lg:grid-cols-3">
<div className="col-span-2 mt-24 flex h-32 items-center justify-center lg:col-span-3">
<Spinner />
</div>
</div>
) : (
<div className="grid grid-cols-1 gap-6 sm:grid-cols-2 lg:grid-cols-3">
{paginatedChunks.filter((chunk) => {
if (!chunk.metadata?.title) return true;
return chunk.metadata.title
.toLowerCase()
.includes(searchTerm.toLowerCase());
}).length === 0 ? (
<div className="col-span-2 mt-24 text-center text-gray-500 lg:col-span-3 dark:text-gray-400">
<img
src={isDarkTheme ? NoFilesDarkIcon : NoFilesIcon}
alt={t('settings.documents.noChunksAlt')}
className="mx-auto mb-2 h-24 w-24"
/>
{t('settings.documents.noChunks')}
</div>
) : (
paginatedChunks
.filter((chunk) => {
if (!chunk.metadata?.title) return true;
return chunk.metadata.title
.toLowerCase()
.includes(searchTerm.toLowerCase());
})
.map((chunk, index) => (
<div
key={index}
className="border-silver dark:border-silver/40 relative flex h-56 w-full flex-col justify-between rounded-2xl border p-6"
>
<div className="w-full">
<div className="flex w-full items-center justify-between">
<button
aria-label={'edit'}
onClick={() => {
setEditModal({
state: 'ACTIVE',
chunk: chunk,
});
}}
className="absolute top-3 right-3 h-4 w-4 cursor-pointer"
>
<img
alt={'edit'}
src={Edit}
className="opacity-60 hover:opacity-100"
/>
</button>
</div>
<div className="mt-[9px]">
<p className="ellipsis-text text-eerie-black h-12 text-sm leading-relaxed font-semibold break-words dark:text-[#EEEEEE]">
{chunk.metadata?.title ?? 'Untitled'}
</p>
<p className="mt-1 h-[110px] overflow-y-auto pr-1 text-[13px] leading-relaxed break-words text-gray-600 dark:text-gray-400">
{chunk.text}
</p>
</div>
</div>
</div>
))
)}
</div>
)}
{!loading &&
paginatedChunks.filter((chunk) => {
if (!chunk.metadata?.title) return true;
return chunk.metadata.title
.toLowerCase()
.includes(searchTerm.toLowerCase());
}).length !== 0 && (
<div className="mt-10 flex w-full items-center justify-center">
<Pagination
currentPage={page}
totalPages={Math.ceil(totalChunks / perPage)}
rowsPerPage={perPage}
onPageChange={(page) => {
setPage(page);
}}
onRowsPerPageChange={(rows) => {
setPerPage(rows);
setPage(1);
}}
/>
</div>
)}
<ChunkModal
type="ADD"
modalState={addModal}
setModalState={setAddModal}
handleSubmit={handleAddChunk}
/>
{editModal.chunk && (
<ChunkModal
type="EDIT"
modalState={editModal.state}
setModalState={(state) =>
setEditModal((prev) => ({ ...prev, state }))
}
handleSubmit={(title, text) => {
handleUpdateChunk(title, text, editModal.chunk as ChunkType);
}}
originalText={editModal.chunk?.text ?? ''}
originalTitle={editModal.chunk?.metadata?.title ?? ''}
handleDelete={() => {
handleDeleteChunk(editModal.chunk as ChunkType);
}}
/>
)}
</div>
);
}

View File

@@ -88,7 +88,7 @@ export default function General() {
{' '}
<div className="flex flex-col gap-4">
{' '}
<label className="text-base font-medium text-jet dark:text-bright-gray">
<label className="text-jet dark:text-bright-gray text-base font-medium">
{t('settings.general.selectTheme')}
</label>
<Dropdown
@@ -106,7 +106,7 @@ export default function General() {
/>
</div>
<div className="flex flex-col gap-4">
<label className="text-base font-medium text-jet dark:text-bright-gray">
<label className="text-jet dark:text-bright-gray text-base font-medium">
{t('settings.general.selectLanguage')}
</label>
<Dropdown
@@ -124,7 +124,7 @@ export default function General() {
/>
</div>
<div className="flex flex-col gap-4">
<label className="text-base font-medium text-jet dark:text-bright-gray">
<label className="text-jet dark:text-bright-gray text-base font-medium">
{t('settings.general.chunks')}
</label>
<Dropdown
@@ -137,7 +137,7 @@ export default function General() {
/>
</div>
<div className="flex flex-col gap-4">
<label className="text-base font-medium text-jet dark:text-bright-gray">
<label className="text-jet dark:text-bright-gray text-base font-medium">
{t('settings.general.convHistory')}
</label>
<Dropdown
@@ -169,13 +169,14 @@ export default function General() {
dispatch(setPrompt({ name: name, id: id, type: type }))
}
setPrompts={setPrompts}
dropdownProps={{ size: 'w-56', rounded: '3xl', border: 'border' }}
/>
</div>
<hr className="my-4 w-[calc(min(665px,100%))] border-t border-silver dark:border-silver/40" />
<hr className="border-silver dark:border-silver/40 my-4 w-[calc(min(665px,100%))] border-t" />
<div className="flex flex-col gap-2">
<button
title={t('settings.general.deleteAllLabel')}
className="flex w-fit cursor-pointer items-center justify-between rounded-3xl border border-solid border-rosso-corsa bg-transparent px-5 py-3 text-sm font-medium tracking-[0.015em] text-rosso-corsa transition-colors hover:bg-rosso-corsa hover:font-bold hover:tracking-normal hover:text-white"
className="border-rosso-corsa text-rosso-corsa hover:bg-rosso-corsa flex w-fit cursor-pointer items-center justify-between rounded-3xl border border-solid bg-transparent px-5 py-3 text-sm font-medium tracking-[0.015em] transition-colors hover:font-bold hover:tracking-normal hover:text-white"
onClick={() => dispatch(setModalStateDeleteConv('ACTIVE'))}
>
{t('settings.general.deleteAllBtn')}

View File

@@ -4,17 +4,29 @@ import { useSelector } from 'react-redux';
import userService from '../api/services/userService';
import Dropdown from '../components/Dropdown';
import { DropdownProps } from '../components/types/Dropdown.types';
import ConfirmationModal from '../modals/ConfirmationModal';
import { ActiveState, PromptProps } from '../models/misc';
import { selectToken } from '../preferences/preferenceSlice';
import PromptsModal from '../preferences/PromptsModal';
import ConfirmationModal from '../modals/ConfirmationModal';
type ExtendedPromptProps = PromptProps & {
title?: string;
titleClassName?: string;
dropdownProps?: Partial<DropdownProps>;
showAddButton?: boolean;
};
export default function Prompts({
prompts,
selectedPrompt,
onSelectPrompt,
setPrompts,
}: PromptProps) {
title,
titleClassName = 'dark:text-bright-gray font-medium',
dropdownProps = {},
showAddButton = true,
}: ExtendedPromptProps) {
const handleSelectPrompt = ({
name,
id,
@@ -27,6 +39,7 @@ export default function Prompts({
setEditPromptName(name);
onSelectPrompt(name, id, type);
};
const token = useSelector(selectToken);
const [newPromptName, setNewPromptName] = React.useState('');
const [newPromptContent, setNewPromptContent] = React.useState('');
@@ -164,18 +177,19 @@ export default function Prompts({
return (
<>
<div>
<div className="flex flex-col gap-4">
<p className="font-medium dark:text-bright-gray">
{t('settings.general.prompt')}
<div className="flex flex-col gap-3">
<p className={titleClassName}>
{title ? title : t('settings.general.prompt')}
</p>
<div className="flex flex-row items-baseline justify-start gap-6">
<div className="flex flex-row flex-wrap items-baseline justify-start gap-6">
<Dropdown
options={prompts}
selectedValue={selectedPrompt.name}
options={prompts.map((prompt: any) =>
typeof prompt === 'string'
? { name: prompt, id: prompt, type: '' }
: prompt,
)}
selectedValue={selectedPrompt ? selectedPrompt.name : ''}
onSelect={handleSelectPrompt}
size="w-56"
rounded="3xl"
border="border"
showEdit
showDelete={(prompt) => prompt.type !== 'public'}
onEdit={({
@@ -185,26 +199,29 @@ export default function Prompts({
}: {
id: string;
name: string;
type: string;
type?: string;
}) => {
setModalType('EDIT');
setEditPromptName(name);
handleFetchPromptContent(id);
setCurrentPromptEdit({ id: id, name: name, type: type });
setCurrentPromptEdit({ id: id, name: name, type: type ?? '' });
setModalState('ACTIVE');
}}
onDelete={handleDeletePrompt}
placeholder={'Select a prompt'}
{...dropdownProps}
/>
<button
className="h-10 w-20 rounded-3xl border border-solid border-violets-are-blue text-sm text-violets-are-blue transition-colors hover:bg-violets-are-blue hover:text-white"
onClick={() => {
setModalType('ADD');
setModalState('ACTIVE');
}}
>
{t('settings.general.add')}
</button>
{showAddButton && (
<button
className="border-violets-are-blue text-violets-are-blue hover:bg-violets-are-blue h-10 w-20 rounded-3xl border border-solid text-sm transition-colors hover:text-white"
onClick={() => {
setModalType('ADD');
setModalState('ACTIVE');
}}
>
{t('settings.general.add')}
</button>
)}
</div>
</div>
</div>

View File

@@ -0,0 +1,519 @@
import React, { useCallback, useEffect, useRef, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useDispatch, useSelector } from 'react-redux';
import userService from '../api/services/userService';
import EyeView from '../assets/eye-view.svg';
import NoFilesIcon from '../assets/no-files.svg';
import NoFilesDarkIcon from '../assets/no-files-dark.svg';
import Trash from '../assets/red-trash.svg';
import SyncIcon from '../assets/sync.svg';
import ThreeDots from '../assets/three-dots.svg';
import CalendarIcon from '../assets/calendar.svg';
import DiscIcon from '../assets/disc.svg';
import ContextMenu, { MenuOption } from '../components/ContextMenu';
import Pagination from '../components/DocumentPagination';
import DropdownMenu from '../components/DropdownMenu';
import SkeletonLoader from '../components/SkeletonLoader';
import { useDarkTheme, useLoaderState } from '../hooks';
import ConfirmationModal from '../modals/ConfirmationModal';
import { ActiveState, Doc, DocumentsProps } from '../models/misc';
import { getDocs, getDocsWithPagination } from '../preferences/preferenceApi';
import {
selectToken,
setPaginatedDocuments,
setSourceDocs,
} from '../preferences/preferenceSlice';
import Upload from '../upload/Upload';
import { formatDate } from '../utils/dateTimeUtils';
import FileTreeComponent from '../components/FileTreeComponent';
import ConnectorTreeComponent from '../components/ConnectorTreeComponent';
import Chunks from '../components/Chunks';
const formatTokens = (tokens: number): string => {
const roundToTwoDecimals = (num: number): string => {
return (Math.round((num + Number.EPSILON) * 100) / 100).toString();
};
if (tokens >= 1_000_000_000) {
return roundToTwoDecimals(tokens / 1_000_000_000) + 'b';
} else if (tokens >= 1_000_000) {
return roundToTwoDecimals(tokens / 1_000_000) + 'm';
} else if (tokens >= 1_000) {
return roundToTwoDecimals(tokens / 1_000) + 'k';
} else {
return tokens.toString();
}
};
export default function Sources({
paginatedDocuments,
handleDeleteDocument,
}: DocumentsProps) {
const { t } = useTranslation();
const [isDarkTheme] = useDarkTheme();
const dispatch = useDispatch();
const token = useSelector(selectToken);
const [searchTerm, setSearchTerm] = useState<string>('');
const [debouncedSearchTerm, setDebouncedSearchTerm] = useState<string>('');
const [modalState, setModalState] = useState<ActiveState>('INACTIVE');
const [isOnboarding, setIsOnboarding] = useState<boolean>(false);
const [loading, setLoading] = useLoaderState(false);
const [sortField, setSortField] = useState<'date' | 'tokens'>('date');
const [sortOrder, setSortOrder] = useState<'asc' | 'desc'>('desc');
// Pagination
const [currentPage, setCurrentPage] = useState<number>(1);
const [rowsPerPage, setRowsPerPage] = useState<number>(10);
const [totalPages, setTotalPages] = useState<number>(1);
const [activeMenuId, setActiveMenuId] = useState<string | null>(null);
const menuRefs = useRef<{
[key: string]: React.RefObject<HTMLDivElement | null>;
}>({});
// Create or get a ref for each document wrapper div (not the td)
const getMenuRef = (docId: string) => {
if (!menuRefs.current[docId]) {
menuRefs.current[docId] = React.createRef<HTMLDivElement>();
}
return menuRefs.current[docId];
};
const handleMenuClick = (e: React.MouseEvent, docId: string) => {
e.preventDefault();
e.stopPropagation();
const isAnyMenuOpen =
(syncMenuState.isOpen && syncMenuState.docId === docId) ||
activeMenuId === docId;
if (isAnyMenuOpen) {
setSyncMenuState((prev) => ({ ...prev, isOpen: false, docId: null }));
setActiveMenuId(null);
return;
}
setActiveMenuId(docId);
};
const currentDocuments = paginatedDocuments ?? [];
const syncOptions = [
{ label: t('settings.sources.syncFrequency.never'), value: 'never' },
{ label: t('settings.sources.syncFrequency.daily'), value: 'daily' },
{ label: t('settings.sources.syncFrequency.weekly'), value: 'weekly' },
{ label: t('settings.sources.syncFrequency.monthly'), value: 'monthly' },
];
const [documentToView, setDocumentToView] = useState<Doc>();
const [isMenuOpen, setIsMenuOpen] = useState(false);
const [syncMenuState, setSyncMenuState] = useState<{
isOpen: boolean;
docId: string | null;
document: Doc | null;
}>({
isOpen: false,
docId: null,
document: null,
});
useEffect(() => {
const timer = setTimeout(() => {
setDebouncedSearchTerm(searchTerm);
}, 500);
return () => clearTimeout(timer);
}, [searchTerm]);
const refreshDocs = useCallback(
(
field: 'date' | 'tokens' | undefined,
pageNumber?: number,
rows?: number,
) => {
const page = pageNumber ?? currentPage;
const rowsPerPg = rows ?? rowsPerPage;
// If field is undefined, (Pagination or Search) use the current sortField
const newSortField = field ?? sortField;
// If field is undefined, (Pagination or Search) use the current sortOrder
const newSortOrder =
field === sortField
? sortOrder === 'asc'
? 'desc'
: 'asc'
: sortOrder;
// If field is defined, update the sortField and sortOrder
if (field) {
setSortField(newSortField);
setSortOrder(newSortOrder);
}
setLoading(true);
getDocsWithPagination(
newSortField,
newSortOrder,
page,
rowsPerPg,
debouncedSearchTerm,
token,
)
.then((data) => {
dispatch(setPaginatedDocuments(data ? data.docs : []));
setTotalPages(data ? data.totalPages : 0);
})
.catch((error) => console.error(error))
.finally(() => {
setLoading(false);
});
},
[currentPage, rowsPerPage, sortField, sortOrder, debouncedSearchTerm],
);
const handleManageSync = (doc: Doc, sync_frequency: string) => {
setLoading(true);
userService
.manageSync({ source_id: doc.id, sync_frequency }, token)
.then(() => {
return getDocs(token);
})
.then((data) => {
dispatch(setSourceDocs(data));
return getDocsWithPagination(
sortField,
sortOrder,
currentPage,
rowsPerPage,
searchTerm,
token,
);
})
.then((paginatedData) => {
dispatch(
setPaginatedDocuments(paginatedData ? paginatedData.docs : []),
);
setTotalPages(paginatedData ? paginatedData.totalPages : 0);
})
.catch((error) => console.error('Error in handleManageSync:', error))
.finally(() => {
setLoading(false);
});
};
const [documentToDelete, setDocumentToDelete] = useState<{
index: number;
document: Doc;
} | null>(null);
const [deleteModalState, setDeleteModalState] =
useState<ActiveState>('INACTIVE');
const handleDeleteConfirmation = (index: number, document: Doc) => {
setDocumentToDelete({ index, document });
setDeleteModalState('ACTIVE');
};
const handleConfirmedDelete = () => {
if (documentToDelete) {
handleDeleteDocument(documentToDelete.index, documentToDelete.document);
setDeleteModalState('INACTIVE');
setDocumentToDelete(null);
}
};
const getActionOptions = (index: number, document: Doc): MenuOption[] => {
const actions: MenuOption[] = [
{
icon: EyeView,
label: t('settings.sources.view'),
onClick: () => {
setDocumentToView(document);
},
iconWidth: 18,
iconHeight: 18,
variant: 'primary',
},
];
if (document.syncFrequency) {
actions.push({
icon: SyncIcon,
label: t('settings.sources.sync'),
onClick: () => {
setSyncMenuState({
isOpen: true,
docId: document.id ?? null,
document: document,
});
},
iconWidth: 14,
iconHeight: 14,
variant: 'primary',
});
}
actions.push({
icon: Trash,
label: t('convTile.delete'),
onClick: () => {
handleDeleteConfirmation(index, document);
},
iconWidth: 18,
iconHeight: 18,
variant: 'danger',
});
return actions;
};
useEffect(() => {
refreshDocs(undefined, 1, rowsPerPage);
}, [debouncedSearchTerm]);
return documentToView ? (
<div className="mt-8 flex flex-col">
{documentToView.isNested ? (
documentToView.type === 'connector' ? (
<ConnectorTreeComponent
docId={documentToView.id || ''}
sourceName={documentToView.name}
onBackToDocuments={() => setDocumentToView(undefined)}
/>
) : (
<FileTreeComponent
docId={documentToView.id || ''}
sourceName={documentToView.name}
onBackToDocuments={() => setDocumentToView(undefined)}
/>
)
) : (
<Chunks
documentId={documentToView.id || ''}
documentName={documentToView.name}
handleGoBack={() => setDocumentToView(undefined)}
/>
)}
</div>
) : (
<div className="mt-8 flex w-full max-w-full flex-col overflow-hidden">
<div className="relative flex grow flex-col">
<div className="mb-6">
<h2 className="text-sonic-silver text-base font-medium">
{t('settings.sources.title')}
</h2>
</div>
<div className="mb-6 flex flex-col items-start justify-between gap-3 sm:flex-row sm:items-center">
<div className="w-full sm:w-auto">
<label htmlFor="document-search-input" className="sr-only">
{t('settings.sources.searchPlaceholder')}
</label>
<div className="relative w-[280px]">
<input
maxLength={256}
placeholder={t('settings.sources.searchPlaceholder')}
name="Document-search-input"
type="text"
id="document-search-input"
value={searchTerm}
onChange={(e) => {
setSearchTerm(e.target.value);
setCurrentPage(1);
}}
className="w-full h-[32px] rounded-full border border-silver dark:border-silver/40 bg-transparent px-3 text-sm text-jet dark:text-bright-gray placeholder:text-gray-400 dark:placeholder:text-gray-500 outline-none focus:border-silver dark:focus:border-silver/60"
/>
</div>
</div>
<button
className="bg-purple-30 hover:bg-violets-are-blue flex h-[38px] min-w-[108px] items-center justify-center rounded-full px-4 text-[14px] whitespace-normal text-white"
title={t('settings.sources.addSource')}
onClick={() => {
setIsOnboarding(false);
setModalState('ACTIVE');
}}
>
{t('settings.sources.addSource')}
</button>
</div>
<div className="relative w-full">
{loading ? (
<div className="w-full grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 xl:grid-cols-4 gap-6 px-2 py-4">
<SkeletonLoader component="sourceCards" count={rowsPerPage} />
</div>
) : !currentDocuments?.length ? (
<div className="flex flex-col items-center justify-center py-12">
<img
src={isDarkTheme ? NoFilesDarkIcon : NoFilesIcon}
alt={t('settings.sources.noData')}
className="mx-auto mb-6 h-32 w-32"
/>
<p className="text-center text-lg text-gray-500 dark:text-gray-400">
{t('settings.sources.noData')}
</p>
</div>
) : (
<div className="w-full grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 xl:grid-cols-4 gap-6 px-2 py-4">
{currentDocuments.map((document, index) => {
const docId = document.id ? document.id.toString() : '';
return (
<div key={docId} className="relative">
<div
className={`flex h-[130px] w-full flex-col rounded-2xl bg-[#F9F9F9] p-3 transition-all duration-200 dark:bg-[#383838] ${
activeMenuId === docId || syncMenuState.docId === docId
? 'scale-[1.05]'
: 'hover:scale-[1.05]'
}`}
>
<div className="w-full flex-1">
<div className="flex w-full items-center justify-between gap-2">
<h3
className="font-inter dark:text-bright-gray line-clamp-3 text-[13px] leading-[18px] font-semibold break-words text-[#18181B]"
title={document.name}
>
{document.name}
</h3>
<div
ref={getMenuRef(docId)}
className="relative flex items-center justify-end"
>
{document.syncFrequency && (
<DropdownMenu
name={t('settings.sources.sync')}
options={syncOptions}
onSelect={(value: string) => {
handleManageSync(document, value);
}}
defaultValue={document.syncFrequency}
icon={SyncIcon}
isOpen={
syncMenuState.docId === docId &&
syncMenuState.isOpen
}
onOpenChange={(isOpen) => {
setSyncMenuState((prev) => ({
...prev,
isOpen,
docId: isOpen ? docId : null,
document: isOpen ? document : null,
}));
}}
anchorRef={getMenuRef(docId)}
position="bottom-left"
offset={{ x: -8, y: 8 }}
className="min-w-[120px]"
/>
)}
<button
onClick={(e) => {
e.stopPropagation();
handleMenuClick(e, docId);
}}
className="inline-flex h-[35px] w-[24px] shrink-0 items-center justify-center rounded-md transition-colors hover:bg-[#EBEBEB] dark:hover:bg-[#26272E]"
aria-label={t('settings.sources.menuAlt')}
data-testid={`menu-button-${docId}`}
>
<img
src={ThreeDots}
alt={t('settings.sources.menuAlt')}
className="opacity-60 hover:opacity-100"
/>
</button>
</div>
</div>
</div>
<div className="flex flex-col items-start justify-start gap-1">
<div className="flex items-center gap-2">
<img
src={CalendarIcon}
alt=""
className="w-[14px] h-[14px]"
/>
<span className="font-inter text-[12px] leading-[18px] font-[500] text-[#848484] dark:text-[#848484]">
{document.date ? formatDate(document.date) : ''}
</span>
</div>
<div className="flex items-center gap-2">
<img
src={DiscIcon}
alt=""
className="w-[14px] h-[14px]"
/>
<span className="font-inter text-[12px] leading-[18px] font-[500] text-[#848484] dark:text-[#848484]">
{document.tokens
? formatTokens(+document.tokens)
: ''}
</span>
</div>
</div>
</div>
<ContextMenu
isOpen={activeMenuId === docId}
setIsOpen={(isOpen) => {
setActiveMenuId(isOpen ? docId : null);
}}
options={getActionOptions(index, document)}
anchorRef={getMenuRef(docId)}
position="bottom-left"
offset={{ x: -8, y: 8 }}
className="z-50"
/>
</div>
);
})}
</div>
)}
</div>
</div>
{currentDocuments.length > 0 && totalPages > 1 && (
<div className="mt-auto pt-4">
<Pagination
currentPage={currentPage}
totalPages={totalPages}
rowsPerPage={rowsPerPage}
onPageChange={(page) => {
setCurrentPage(page);
refreshDocs(undefined, page, rowsPerPage);
}}
onRowsPerPageChange={(rows) => {
setRowsPerPage(rows);
setCurrentPage(1);
refreshDocs(undefined, 1, rows);
}}
/>
</div>
)}
{modalState === 'ACTIVE' && (
<Upload
receivedFile={[]}
setModalState={setModalState}
isOnboarding={isOnboarding}
renderTab={null}
close={() => setModalState('INACTIVE')}
onSuccessfulUpload={() =>
refreshDocs(undefined, currentPage, rowsPerPage)
}
/>
)}
{deleteModalState === 'ACTIVE' && documentToDelete && (
<ConfirmationModal
message={t('settings.sources.deleteWarning', {
name: documentToDelete.document.name,
})}
modalState={deleteModalState}
setModalState={setDeleteModalState}
handleSubmit={handleConfirmedDelete}
handleCancel={() => {
setDeleteModalState('INACTIVE');
setDocumentToDelete(null);
}}
submitLabel={t('convTile.delete')}
variant="danger"
/>
)}
</div>
);
}

View File

@@ -21,7 +21,7 @@ import {
setSourceDocs,
} from '../preferences/preferenceSlice';
import Analytics from './Analytics';
import Documents from './Documents';
import Sources from './Sources';
import General from './General';
import Logs from './Logs';
import Tools from './Tools';
@@ -38,8 +38,8 @@ export default function Settings() {
const getActiveTabFromPath = () => {
const path = location.pathname;
if (path.includes('/settings/documents'))
return t('settings.documents.label');
if (path.includes('/settings/sources'))
return t('settings.sources.label');
if (path.includes('/settings/analytics'))
return t('settings.analytics.label');
if (path.includes('/settings/logs')) return t('settings.logs.label');
@@ -53,8 +53,8 @@ export default function Settings() {
const handleTabChange = (tab: string) => {
setActiveTab(tab);
if (tab === t('settings.general.label')) navigate('/settings');
else if (tab === t('settings.documents.label'))
navigate('/settings/documents');
else if (tab === t('settings.sources.label'))
navigate('/settings/sources');
else if (tab === t('settings.analytics.label'))
navigate('/settings/analytics');
else if (tab === t('settings.logs.label')) navigate('/settings/logs');
@@ -113,9 +113,9 @@ export default function Settings() {
<Routes>
<Route index element={<General />} />
<Route
path="documents"
path="sources"
element={
<Documents
<Sources
paginatedDocuments={paginatedDocuments}
handleDeleteDocument={handleDeleteClick}
/>

View File

@@ -4,6 +4,9 @@ import { useTranslation } from 'react-i18next';
import { useDispatch, useSelector } from 'react-redux';
import userService from '../api/services/userService';
import { getSessionToken, setSessionToken, removeSessionToken } from '../utils/providerUtils';
import { formatDate } from '../utils/dateTimeUtils';
import { formatBytes } from '../utils/stringUtils';
import FileUpload from '../assets/file_upload.svg';
import WebsiteCollect from '../assets/website_collect.svg';
import Dropdown from '../components/Dropdown';
@@ -25,6 +28,9 @@ import {
IngestorFormSchemas,
IngestorType,
} from './types/ingestor';
import FileIcon from '../assets/file.svg';
import FolderIcon from '../assets/folder.svg';
import ConnectorAuth from '../components/ConnectorAuth';
function Upload({
receivedFile = [],
@@ -48,6 +54,21 @@ function Upload({
const [activeTab, setActiveTab] = useState<string | null>(renderTab);
const [showAdvancedOptions, setShowAdvancedOptions] = useState(false);
// Google Drive state
const [isGoogleDriveConnected, setIsGoogleDriveConnected] = useState(false);
const [googleDriveFiles, setGoogleDriveFiles] = useState<any[]>([]);
const [selectedFiles, setSelectedFiles] = useState<string[]>([]);
const [isLoadingFiles, setIsLoadingFiles] = useState(false);
const [isAuthenticating, setIsAuthenticating] = useState(false);
const [userEmail, setUserEmail] = useState<string>('');
const [authError, setAuthError] = useState<string>('');
const [currentFolderId, setCurrentFolderId] = useState<string | null>(null);
const [folderPath, setFolderPath] = useState<Array<{id: string | null, name: string}>>([{id: null, name: 'My Drive'}]);
const [nextPageToken, setNextPageToken] = useState<string | null>(null);
const [hasMoreFiles, setHasMoreFiles] = useState<boolean>(false);
const scrollContainerRef = useRef<HTMLDivElement | null>(null);
const renderFormFields = () => {
const schema = IngestorFormSchemas[ingestor.type];
if (!schema) return null;
@@ -204,6 +225,7 @@ function Upload({
{ label: 'Link', value: 'url' },
{ label: 'GitHub', value: 'github' },
{ label: 'Reddit', value: 'reddit' },
{ label: 'Google Drive', value: 'google_drive' },
];
const sourceDocs = useSelector(selectSourceDocs);
@@ -315,8 +337,7 @@ function Upload({
data?.find(
(d: Doc) => d.type?.toLowerCase() === 'local',
),
),
);
));
});
setProgress(
(progress) =>
@@ -428,29 +449,32 @@ function Upload({
formData.append('user', 'local');
formData.append('source', ingestor.type);
const defaultConfig = IngestorDefaultConfigs[ingestor.type].config;
let configData;
const mergedConfig = { ...defaultConfig, ...ingestor.config };
const filteredConfig = Object.entries(mergedConfig).reduce(
(acc, [key, value]) => {
const field = IngestorFormSchemas[ingestor.type].find(
(f) => f.name === key,
);
// Include the field if:
// 1. It's required, or
// 2. It's optional and has a non-empty value
if (
field?.required ||
(value !== undefined && value !== null && value !== '')
) {
acc[key] = value;
}
return acc;
},
{} as Record<string, any>,
);
if (ingestor.type === 'google_drive') {
const sessionToken = getSessionToken(ingestor.type);
formData.append('data', JSON.stringify(filteredConfig));
const selectedItems = googleDriveFiles.filter(file => selectedFiles.includes(file.id));
const selectedFolderIds = selectedItems
.filter(item => item.type === 'application/vnd.google-apps.folder' || item.isFolder)
.map(folder => folder.id);
const selectedFileIds = selectedItems
.filter(item => item.type !== 'application/vnd.google-apps.folder' && !item.isFolder)
.map(file => file.id);
configData = {
file_ids: selectedFileIds,
folder_ids: selectedFolderIds,
recursive: ingestor.config.recursive,
session_token: sessionToken || null
};
} else {
configData = { ...ingestor.config };
}
formData.append('data', JSON.stringify(configData));
const apiHost: string = import.meta.env.VITE_API_HOST;
const xhr = new XMLHttpRequest();
@@ -477,6 +501,171 @@ function Upload({
xhr.setRequestHeader('Authorization', `Bearer ${token}`);
xhr.send(formData);
};
useEffect(() => {
if (ingestor.type === 'google_drive') {
const sessionToken = getSessionToken(ingestor.type);
if (sessionToken) {
// Auto-authenticate if session token exists
setIsGoogleDriveConnected(true);
setAuthError('');
// Fetch user email and files using the existing session token
fetchUserEmailAndLoadFiles(sessionToken);
}
}
}, [ingestor.type]);
const fetchUserEmailAndLoadFiles = async (sessionToken: string) => {
try {
const apiHost = import.meta.env.VITE_API_HOST;
const validateResponse = await fetch(`${apiHost}/api/connectors/validate-session`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${token}`
},
body: JSON.stringify({ provider: 'google_drive', session_token: sessionToken })
});
if (!validateResponse.ok) {
removeSessionToken(ingestor.type);
setIsGoogleDriveConnected(false);
setAuthError('Session expired. Please reconnect to Google Drive.');
return;
}
const validateData = await validateResponse.json();
if (validateData.success) {
setUserEmail(validateData.user_email || 'Connected User');
// reset pagination state and files
setGoogleDriveFiles([]);
setNextPageToken(null);
setHasMoreFiles(false);
loadGoogleDriveFiles(sessionToken, null, null, false);
} else {
removeSessionToken(ingestor.type);
setIsGoogleDriveConnected(false);
setAuthError(validateData.error || 'Session expired. Please reconnect your Google Drive account and make sure to grant offline access.');
}
} catch (error) {
console.error('Error validating Google Drive session:', error);
setAuthError('Failed to validate session. Please reconnect.');
setIsGoogleDriveConnected(false);
}
};
const loadGoogleDriveFiles = async (
sessionToken: string,
folderId?: string | null,
pageToken?: string | null,
append: boolean = false,
) => {
setIsLoadingFiles(true);
try {
const apiHost = import.meta.env.VITE_API_HOST;
const requestBody: any = {
session_token: sessionToken,
limit: 10,
};
if (folderId) {
requestBody.folder_id = folderId;
}
if (pageToken) {
requestBody.page_token = pageToken;
}
const filesResponse = await fetch(`${apiHost}/api/connectors/files`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${token}`
},
body: JSON.stringify({ ...requestBody, provider: 'google_drive' })
});
if (!filesResponse.ok) {
throw new Error(`Failed to load files: ${filesResponse.status}`);
}
const filesData = await filesResponse.json();
if (filesData.success && Array.isArray(filesData.files)) {
setGoogleDriveFiles(prev => append ? [...prev, ...filesData.files] : filesData.files);
setNextPageToken(filesData.next_page_token || null);
setHasMoreFiles(Boolean(filesData.has_more));
} else {
throw new Error(filesData.error || 'Failed to load files');
}
} catch (error) {
console.error('Error loading Google Drive files:', error);
setAuthError(error instanceof Error ? error.message : 'Failed to load files. Please make sure your Google Drive account is properly connected and you granted offline access during authorization.');
} finally {
setIsLoadingFiles(false);
}
};
// Handle file selection
const handleFileSelect = (fileId: string) => {
setSelectedFiles(prev => {
if (prev.includes(fileId)) {
return prev.filter(id => id !== fileId);
} else {
return [...prev, fileId];
}
});
};
const handleFolderClick = (folderId: string, folderName: string) => {
const sessionToken = getSessionToken(ingestor.type);
if (sessionToken) {
setCurrentFolderId(folderId);
setFolderPath(prev => [...prev, {id: folderId, name: folderName}]);
setGoogleDriveFiles([]);
setNextPageToken(null);
setHasMoreFiles(false);
setSelectedFiles([]);
loadGoogleDriveFiles(sessionToken, folderId, null, false);
}
};
const navigateBack = (index: number) => {
const sessionToken = getSessionToken(ingestor.type);
if (sessionToken) {
const newPath = folderPath.slice(0, index + 1);
const targetFolderId = newPath[newPath.length - 1]?.id;
setCurrentFolderId(targetFolderId as string | null);
setFolderPath(newPath);
setGoogleDriveFiles([]);
setNextPageToken(null);
setHasMoreFiles(false);
setSelectedFiles([]);
loadGoogleDriveFiles(sessionToken, targetFolderId ?? null, null, false);
}
};
const handleSelectAll = () => {
if (selectedFiles.length === googleDriveFiles.length) {
setSelectedFiles([]);
} else {
setSelectedFiles(googleDriveFiles.map(file => file.id));
}
};
const { getRootProps, getInputProps, isDragActive } = useDropzone({
onDrop,
multiple: true,
@@ -515,6 +704,10 @@ function Upload({
if (!remoteName?.trim()) {
return true;
}
if (ingestor.type === 'google_drive') {
return !isGoogleDriveConnected || selectedFiles.length === 0;
}
const formFields: FormField[] = IngestorFormSchemas[ingestor.type];
for (const field of formFields) {
if (field.required) {
@@ -636,7 +829,7 @@ function Upload({
{files.map((file) => (
<p
key={file.name}
className="text-gray-6000 truncate overflow-hidden text-ellipsis"
className="text-gray-6000 dark:text-[#ececf1] truncate overflow-hidden text-ellipsis"
title={file.name}
>
{file.name}
@@ -679,6 +872,202 @@ function Upload({
required={true}
labelBgClassName="bg-white dark:bg-charleston-green-2"
/>
{ingestor.type === 'google_drive' && (
<div className="space-y-4">
{authError && (
<div className="rounded-lg border border-red-200 bg-red-50 p-3 dark:border-red-600 dark:bg-red-900/20">
<p className="text-sm text-red-600 dark:text-red-400">
{authError}
</p>
</div>
)}
{!isGoogleDriveConnected ? (
<ConnectorAuth
provider="google_drive"
onSuccess={(data) => {
setUserEmail(data.user_email);
setIsGoogleDriveConnected(true);
setIsAuthenticating(false);
setAuthError('');
if (data.session_token) {
setSessionToken(ingestor.type, data.session_token);
loadGoogleDriveFiles(data.session_token, null);
}
}}
onError={(error) => {
setAuthError(error);
setIsAuthenticating(false);
setIsGoogleDriveConnected(false);
}}
/>
) : (
<div className="space-y-4">
{/* Connection Status */}
<div className="w-full flex items-center justify-between rounded-lg bg-green-500 px-4 py-2 text-white text-sm">
<div className="flex items-center gap-2">
<svg className="h-4 w-4" viewBox="0 0 24 24">
<path fill="currentColor" d="M9 16.17L4.83 12l-1.42 1.41L9 19 21 7l-1.41-1.41z"/>
</svg>
<span>Connected as {userEmail}</span>
</div>
<button
onClick={() => {
removeSessionToken(ingestor.type);
setIsGoogleDriveConnected(false);
setGoogleDriveFiles([]);
setSelectedFiles([]);
setUserEmail('');
setAuthError('');
const apiHost = import.meta.env.VITE_API_HOST;
fetch(`${apiHost}/api/connectors/disconnect`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${token}`
},
body: JSON.stringify({ provider: ingestor.type, session_token: getSessionToken(ingestor.type) })
}).catch(err => console.error('Error disconnecting from Google Drive:', err));
}}
className="text-white hover:text-gray-200 text-xs underline"
>
Disconnect
</button>
</div>
{/* File Browser */}
<div className="border border-gray-200 rounded-lg dark:border-gray-600">
<div className="p-3 border-b border-gray-200 dark:border-gray-600 bg-gray-50 dark:bg-gray-800 rounded-t-lg">
{/* Breadcrumb navigation */}
<div className="flex items-center gap-1 mb-2">
{folderPath.map((path, index) => (
<div key={path.id || 'root'} className="flex items-center gap-1">
{index > 0 && <span className="text-gray-400">/</span>}
<button
onClick={() => navigateBack(index)}
className="text-sm text-blue-600 hover:text-blue-800 dark:text-blue-400 hover:underline"
disabled={index === folderPath.length - 1}
>
{path.name}
</button>
</div>
))}
</div>
<div className="flex items-center justify-between">
<h4 className="text-sm font-medium text-gray-700 dark:text-gray-300">
Select Files from Google Drive
</h4>
{googleDriveFiles.length > 0 && (
<button
onClick={handleSelectAll}
className="text-xs text-blue-600 hover:text-blue-800 dark:text-blue-400"
>
{selectedFiles.length === googleDriveFiles.length ? 'Deselect All' : 'Select All'}
</button>
)}
</div>
{selectedFiles.length > 0 && (
<p className="text-xs text-gray-500 mt-1">
{selectedFiles.length} file{selectedFiles.length !== 1 ? 's' : ''} selected
</p>
)}
</div>
<div className="max-h-72 overflow-y-auto" ref={scrollContainerRef}>
{isLoadingFiles && googleDriveFiles.length === 0 ? (
<div className="p-4 text-center">
<div className="inline-flex items-center gap-2 text-sm text-gray-600 dark:text-gray-400">
<div className="h-4 w-4 animate-spin rounded-full border-2 border-blue-500 border-t-transparent"></div>
Loading files...
</div>
</div>
) : googleDriveFiles.length === 0 ? (
<div className="p-4 text-center text-sm text-gray-500 dark:text-gray-400">
No files found in your Google Drive
</div>
) : (
<>
<div className="divide-y divide-gray-200 dark:divide-gray-600">
{googleDriveFiles.map((file) => (
<div
key={file.id}
className={`p-3 transition-colors ${
selectedFiles.includes(file.id) ? 'bg-blue-50 dark:bg-blue-900/20' : ''
}`}
>
<div className="flex items-center gap-3">
<div className="flex-shrink-0">
<input
type="checkbox"
checked={selectedFiles.includes(file.id)}
onChange={() => handleFileSelect(file.id)}
className="h-4 w-4 text-blue-600 rounded border-gray-300 focus:ring-blue-500"
/>
</div>
{file.type === 'application/vnd.google-apps.folder' || file.isFolder ? (
<div
className="text-lg cursor-pointer hover:text-blue-600"
onClick={() => handleFolderClick(file.id, file.name)}
>
<img src={FolderIcon} alt="Folder" className="h-6 w-6" />
</div>
) : (
<div className="text-lg">
<img src={FileIcon} alt="File" className="h-6 w-6" />
</div>
)}
<div className="flex-1 min-w-0">
<p
className={`text-sm font-medium truncate dark:text-[#ececf1] ${
file.type === 'application/vnd.google-apps.folder' || file.isFolder
? 'cursor-pointer hover:text-blue-600'
: ''
}`}
onClick={() => {
if (file.type === 'application/vnd.google-apps.folder' || file.isFolder) {
handleFolderClick(file.id, file.name);
}
}}
>
{file.name}
</p>
<p className="text-xs text-gray-500 dark:text-gray-400">
{file.size && `${formatBytes(file.size)}`}Modified {formatDate(file.modifiedTime)}
</p>
</div>
</div>
</div>
))}
</div>
<div className="p-4 flex items-center justify-center border-t border-gray-100 dark:border-gray-800">
{isLoadingFiles && (
<div className="inline-flex items-center gap-2 text-sm text-gray-600 dark:text-gray-400">
<div className="h-4 w-4 animate-spin rounded-full border-2 border-blue-500 border-t-transparent"></div>
Loading more files...
</div>
)}
{!hasMoreFiles && !isLoadingFiles && (
<span className="text-sm text-gray-500 dark:text-gray-400">All files loaded</span>
)}
</div>
</>
)}
</div>
<div className="hidden" aria-hidden="true">
</div>
</div>
</div>
)}
</div>
)}
{renderFormFields()}
{IngestorFormSchemas[ingestor.type].some(
(field) => field.advanced,
@@ -719,7 +1108,10 @@ function Upload({
: 'bg-purple-30 hover:bg-violets-are-blue cursor-pointer text-white'
}`}
>
{t('modals.uploadDoc.train')}
{ingestor.type === 'google_drive' && selectedFiles.length > 0
? `Train with ${selectedFiles.length} file${selectedFiles.length !== 1 ? 's' : ''}`
: t('modals.uploadDoc.train')
}
</button>
)}
</div>
@@ -727,6 +1119,30 @@ function Upload({
);
}
useEffect(() => {
const scrollContainer = scrollContainerRef.current;
const handleScroll = () => {
if (!scrollContainer) return;
const { scrollTop, scrollHeight, clientHeight } = scrollContainer;
const isNearBottom = scrollHeight - scrollTop - clientHeight < 50;
if (isNearBottom && hasMoreFiles && !isLoadingFiles && nextPageToken) {
const sessionToken = getSessionToken(ingestor.type);
if (sessionToken) {
loadGoogleDriveFiles(sessionToken, currentFolderId, nextPageToken, true);
}
}
};
scrollContainer?.addEventListener('scroll', handleScroll);
return () => {
scrollContainer?.removeEventListener('scroll', handleScroll);
};
}, [hasMoreFiles, isLoadingFiles, nextPageToken, currentFolderId, ingestor.type]);
return (
<WrapperModal
isPerformingTask={progress !== undefined && progress.percentage < 100}

View File

@@ -22,7 +22,14 @@ export interface UrlIngestorConfig extends BaseIngestorConfig {
url: string;
}
export type IngestorType = 'crawler' | 'github' | 'reddit' | 'url';
export interface GoogleDriveIngestorConfig extends BaseIngestorConfig {
folder_id?: string;
file_ids?: string;
recursive?: boolean;
token_info?: any;
}
export type IngestorType = 'crawler' | 'github' | 'reddit' | 'url' | 'google_drive';
export interface IngestorConfig {
type: IngestorType;
@@ -31,7 +38,8 @@ export interface IngestorConfig {
| RedditIngestorConfig
| GithubIngestorConfig
| CrawlerIngestorConfig
| UrlIngestorConfig;
| UrlIngestorConfig
| GoogleDriveIngestorConfig;
}
export type IngestorFormData = {
@@ -109,6 +117,14 @@ export const IngestorFormSchemas: Record<IngestorType, FormField[]> = {
required: true,
},
],
google_drive: [
{
name: 'recursive',
label: 'Include subfolders',
type: 'boolean',
required: false,
},
],
};
export const IngestorDefaultConfigs: Record<
@@ -143,4 +159,12 @@ export const IngestorDefaultConfigs: Record<
repo_url: '',
} as GithubIngestorConfig,
},
google_drive: {
name: '',
config: {
folder_id: '',
file_ids: '',
recursive: true,
} as GoogleDriveIngestorConfig,
},
};

View File

@@ -34,6 +34,20 @@ export function formatDate(dateString: string): string {
day: 'numeric',
year: 'numeric',
});
} else if (
/^[A-Za-z]{3}, \d{2} [A-Za-z]{3} \d{4} \d{2}:\d{2}:\d{2} GMT$/.test(
dateString,
)
) {
// Format: "Fri, 08 Jul 2025 06:00:00 GMT"
const dateTime = new Date(dateString);
return dateTime.toLocaleDateString('en-US', {
month: 'short',
day: 'numeric',
year: 'numeric',
hour: '2-digit',
minute: '2-digit',
});
} else {
return dateString;
}

View File

@@ -0,0 +1,17 @@
/**
* Utility functions for managing session tokens for different cloud service providers.
* Follows the convention: {provider}_session_token
*/
export const getSessionToken = (provider: string): string | null => {
return localStorage.getItem(`${provider}_session_token`);
};
export const setSessionToken = (provider: string, token: string): void => {
localStorage.setItem(`${provider}_session_token`, token);
};
export const removeSessionToken = (provider: string): void => {
localStorage.removeItem(`${provider}_session_token`);
};

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