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385 Commits

Author SHA1 Message Date
hagen-danswer
0c13c9a106 updates 2024-12-15 15:12:55 -08:00
hagen-danswer
24525ca3d8 all done 2024-12-13 12:18:16 -08:00
hagen-danswer
8b8030a61f Merge pull request #3379 from onyx-dot-app/hagen-initial-branch
refactor
2024-12-12 15:55:22 -08:00
hagen-danswer
f4e8ac1dde 2 graphs down 2024-12-12 15:54:13 -08:00
hagen-danswer
ad4df04159 done with exanded retrieval 2024-12-12 15:20:39 -08:00
hagen-danswer
f5e28e0f54 minor refactor 2024-12-09 11:34:11 -08:00
hagen-danswer
091cb136c4 got core qa graph working 2024-12-07 12:25:54 -08:00
hagen-danswer
56052c5b4b imports 2024-12-07 06:09:57 -08:00
hagen-danswer
617726207b all 3 graphs r done 2024-12-07 06:06:22 -08:00
hagen-danswer
1be58e74b3 Finished primary graph 2024-12-06 11:01:03 -08:00
hagen-danswer
a693c991d7 Merge remote-tracking branch 'origin/agent-search-a' into initial-implementation 2024-12-04 15:42:58 -08:00
hagen-danswer
ef9942b751 Related permission docs to cc_pair to prevent orphan docs (#3336)
* Related permission docs to cc_pair to prevent orphan docs

* added script

* group sync deduping

* logging
2024-12-04 21:00:54 +00:00
pablodanswer
993acec5e9 Update memoization + silence unnecessary errors (#3337)
* update memoization + silence unnecessary errors

* proper org
2024-12-04 20:08:15 +00:00
Weves
b01a1b509a Add basic loadtest script 2024-12-04 10:53:48 -08:00
pablodanswer
4f994124ef remove now unnecessary user loading indicatort log (#3333) 2024-12-04 00:09:22 +00:00
rkuo-danswer
14863bd457 try single threaded playwright testing (#3322) 2024-12-03 23:21:46 +00:00
Yuhong Sun
aa1c4c635a Combining Search and Chat Backend (#3273)
* k

* k

* fix slack issues

* rebase

* k
2024-12-03 22:37:14 +00:00
rkuo-danswer
13f6e8a6b4 disable thread local locking in callbacks (#3319) 2024-12-03 22:32:56 +00:00
pablodanswer
66f47d294c Shared filter utility for clarity (#3270)
* shared filter util

* clearer comment
2024-12-03 19:30:42 +00:00
pablodanswer
0a685bda7d add comments for clarity (#3249) 2024-12-03 19:27:28 +00:00
pablodanswer
23dc8b5dad Search flow improvements (#3314)
* untoggle if no docs

* update

* nits

* nit

* typing

* nit
2024-12-03 18:56:27 +00:00
pablodanswer
cd5f2293ad Temperature (#3310)
* fix temperatures for default llm

* ensure anthropic models don't overflow

* minor cleanup

* k

* k

* k

* fix typing
2024-12-03 17:22:22 +00:00
rkuo-danswer
6c2269e565 refactor celery task names to constants (#3296) 2024-12-03 16:02:17 +00:00
Weves
46315cddf1 Adjust default confulence timezone 2024-12-02 22:25:29 -08:00
rkuo-danswer
5f28a1b0e4 Bugfix/confluence time zone (#3265)
* RedisLock typing

* checkpoint

* put in debug logging

* improve comments

* mypy fixes
2024-12-02 22:23:23 -08:00
rkuo-danswer
9e9b7ed61d Bugfix/connector aborted logging (#3309)
* improve error logging on task failure.

* add db exception hardening to the indexing watchdog

* log on db exception
2024-12-03 02:34:40 +00:00
pablodanswer
3fb2bfefec Update Chromatic Tests (#3300)
* remove / update search tests

* minor update
2024-12-02 23:08:54 +00:00
pablodanswer
7c618c9d17 Unified UI (#3308)
* fix typing

* add filters display
2024-12-02 15:12:13 -08:00
pablodanswer
03e2789392 Text embedding (PDF, TXT) (#3113)
* add text embedding

* post rebase cleanup

* fully functional post rebase

* rm logs

* rm '

* quick clean up

* k
2024-12-02 22:43:53 +00:00
Chris Weaver
2783fa08a3 Update openai version in model server (#3306) 2024-12-02 21:39:10 +00:00
pablodanswer
edeaee93a2 hard refresh on auth (#3305)
* hard refresh on auth

* k

* k

* comment for clarity
2024-12-02 20:12:12 +00:00
hagen-danswer
5385bae100 Add slim connector description (#3303)
* added docs example and test

* updated docs

* needed to make the tests run

* updated docs
2024-12-02 19:52:13 +00:00
pablodanswer
813445ab59 Minor JWT Feature (#3290)
* first pass

* k

* k

* finalize

* minor cleanup

* k

* address

* minor typing updates
2024-12-02 19:14:31 +00:00
pablodanswer
af814823c8 display name + model truncation (#3304) 2024-12-02 18:54:08 +00:00
pablodanswer
607f61eaeb Reusable function for search settings spread operation (#3301)
* combine for clarity once and for all

* remove logs

* k
2024-12-02 17:23:01 +00:00
hagen-danswer
4b28686721 Added Initial Implementation of the Agent Search Graph 2024-12-02 07:16:08 -08:00
pablodanswer
de66f7adb2 Updated chat flow (#3244)
* proper no assistant typing + no assistant modal

* updated chat flow

* k

* updates

* update

* k

* clean up

* fix mystery reorg

* cleanup

* update scroll

* default

* update logs

* push fade

* scroll nit

* finalize tags

* updates

* k

* various updates

* viewport height update

* source types update

* clean up unused components

* minor cleanup

* cleanup complete

* finalize changes

* badge up

* update filters

* small nit

* k

* k

* address comments

* quick unification of icons

* minor date range clarity

* minor nit

* k

* update sidebar line

* update for all screen sizes

* k

* k

* k

* k

* rm shs

* fix memoization

* fix memoization

* slack chat

* k

* k

* build org
2024-12-02 01:58:28 +00:00
Yuhong Sun
3432d932d1 Citation code comments 2024-12-01 14:10:11 -08:00
Yuhong Sun
9bd0cb9eb5 Fix Citation Minor Bugs (#3294) 2024-12-01 13:55:24 -08:00
Chris Weaver
f12eb4a5cf Fix assistant prompt zero-ing (#3293) 2024-11-30 04:45:40 +00:00
Chris Weaver
16863de0aa Improve model token limit detection (#3292)
* Properly find context window for ollama llama

* Better ollama support + upgrade litellm

* Ugprade OpenAI as well

* Fix mypy
2024-11-30 04:42:56 +00:00
Weves
63d1eefee5 Add read_only=True for xlsx parsing 2024-11-28 16:02:02 -08:00
pablodanswer
e338677896 order seeding 2024-11-28 15:41:10 -08:00
hagen-danswer
7be80c4af9 increased the pagination limit for confluence spaces (#3288) 2024-11-28 19:04:38 +00:00
rkuo-danswer
7f1e4a02bf Feature/kill indexing (#3213)
* checkpoint

* add celery termination of the task

* rename to RedisConnectorPermissionSyncPayload, add RedisLock to more places, add get_active_search_settings

* rename payload

* pretty sure these weren't named correctly

* testing in progress

* cleanup

* remove space

* merge fix

* three dots animation on Pausing

* improve messaging when connector is stopped or killed and animate buttons

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-28 05:32:45 +00:00
rkuo-danswer
5be7d27285 use indexing flag in db for manually triggering indexing (#3264)
* use indexing flag in db for manually trigger indexing

* add comment.

* only try to release the lock if we actually succeeded with the lock

* ensure we don't trigger manual indexing on anything but the primary search settings

* comment usage of primary search settings

* run check for indexing immediately after indexing triggers are set

* reorder fix
2024-11-28 01:34:34 +00:00
Weves
fd84b7a768 Remove duplicate API key router 2024-11-27 16:30:59 -08:00
Subash-Mohan
36941ae663 fix: Cannot configure API keys #3191 2024-11-27 16:25:00 -08:00
Matthew Holland
212353ed4a Fixed default feedback options 2024-11-27 16:23:52 -08:00
Richard Kuo (Danswer)
eb8708f770 the word "error" might be throwing off sentry 2024-11-27 14:31:21 -08:00
Chris Weaver
ac448956e9 Add handling for rate limiting (#3280) 2024-11-27 14:22:15 -08:00
pablodanswer
634a0b9398 no stack by default (#3278) 2024-11-27 20:58:21 +00:00
hagen-danswer
09d3e47c03 Perm sync behavior change (#3262)
* Change external permissions behavior

* fixed behavior

* added error handling

* LLM the goat

* comment

* simplify

* fixed

* done

* limits increased

* added a ton of logging

* uhhhh
2024-11-27 20:04:15 +00:00
pablodanswer
9c0cc94f15 refresh router -> refresh assistants (#3271) 2024-11-27 19:11:58 +00:00
hagen-danswer
07dfde2209 add continue in danswer button to slack bot responses (#3239)
* all done except routing

* fixed initial changes

* added backend endpoint for duplicating a chat session from Slack

* got chat duplication routing done

* got login routing working

* improved answer handling

* finished all checks

* finished all!

* made sure it works with google oauth

* dont remove that lol

* fixed weird thing

* bad comments
2024-11-27 18:25:38 +00:00
pablodanswer
28e2b78b2e Fix search dropdown (#3269)
* validate dropdown

* validate

* update organization

* move to utils
2024-11-27 16:10:07 +00:00
Emerson Gomes
0553062ac6 Adds icons for Google Gemini models and custom model icons for L… (#3218)
* Add description for Google Gemini models and custom model icons for LiteLLM (OpenAI) proxied models

* Adds Vertex AI aliases for Claude

---------

Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
2024-11-26 10:13:21 -08:00
hagen-danswer
284e375ba3 Merge pull request #3257 from danswer-ai/minor-perm-sync
Improved logging for confluence doc sync and robust user creation
2024-11-26 09:59:38 -08:00
hagen-danswer
1f2f7d0ac2 Improved logging for confluence doc sync and robust user creation 2024-11-26 08:51:15 -08:00
pablodanswer
2ecc28b57d remove unused stripe promise (#3248) 2024-11-26 01:50:39 +00:00
rkuo-danswer
77cf9b3539 improve messaging and UI around cleanup of leftover index attempts (#3247)
* improve messaging and UI around cleanup of leftover index attempts

* add tag on init
2024-11-25 22:27:14 +00:00
Weves
076ce2ebd0 Saml fix 2024-11-25 09:12:43 -08:00
pablodanswer
b625ee32a7 File handling cleanup (#3240)
* fix google sites connector

* minior cleanup

* rm comments
2024-11-25 04:06:47 +00:00
Richard Kuo (Danswer)
c32b93fcc3 increase indexing worker concurrency to 3 2024-11-24 18:11:58 -08:00
pablodanswer
1c8476072e Assistant cleanup (#3236)
* minor cleanup

* ensure users don't modify built-in attributes of assistants

* update sidebar

* k

* update update flow + assistant creation
2024-11-25 00:13:34 +00:00
Chris Weaver
7573416ca1 Fix API keys for MIT users (#3237) 2024-11-24 16:55:19 -08:00
Yuhong Sun
86d8666481 Add Test Case 2024-11-24 15:42:14 -08:00
Yuhong Sun
8abcde91d4 Fix Test (#3242) 2024-11-24 14:31:28 -08:00
Yuhong Sun
3466451d51 Fix Prompt for Non Function Calling LLMs (#3241) 2024-11-24 14:16:57 -08:00
Yuhong Sun
413891f143 Token Level Log (#3238) 2024-11-23 18:41:50 -08:00
Yuhong Sun
7a0a4d4b79 Remove Deprecated Endpoints (#3235) 2024-11-23 14:44:23 -08:00
Yuhong Sun
a3439605a5 Remove Dead Code (#3234) 2024-11-23 14:31:59 -08:00
pablodanswer
694e79f5e1 minor enforcement of CSV length for internal processing (#3109) 2024-11-23 21:05:30 +00:00
pablodanswer
5dfafc8612 minor calendar cleanup (#3219) 2024-11-23 21:01:05 +00:00
Yuhong Sun
62a4aa10db Refactor Search (#3233) 2024-11-23 13:42:54 -08:00
Yuhong Sun
a357cdc4c9 Remove Dead Code (#3232) 2024-11-23 13:21:27 -08:00
Yuhong Sun
84615abfdd Seeding (#3231) 2024-11-23 13:12:42 -08:00
pablodanswer
8ae6b1960b Bugfix/usage report (#3075)
* fix pagination

* update side

* fixed query history

* minor update

* minor update

* typing
2024-11-23 20:11:39 +00:00
James Jordan
d9b87bbbc2 Fixed 400 error when author of ticket is no longer an active user in a Zendesk account. (#3168) 2024-11-23 12:15:38 -08:00
Sanju Lokuhitige
a0065b01af Update CONTRIBUTING.md (#3112)
fix Formatting and Linting hyperlink
2024-11-23 12:13:23 -08:00
pablodanswer
c5306148a3 Ensure daterange not consistently re rendered (#3229)
* ensure daterange not consistently re rendered

* minor clean up
2024-11-23 19:35:00 +00:00
hagen-danswer
1e17934de4 Merge pull request #3214 from danswer-ai/fix-slack-ui
cleaned up new slack bot creation
2024-11-23 10:53:47 -08:00
pablodanswer
93add96ccc Various Nits (#3228) 2024-11-23 10:53:24 -08:00
rkuo-danswer
3a466a4b08 add minimal retries to confluence probe (#3222)
* add minimal retries to confluence probe

* name variable correctly
2024-11-23 17:11:15 +00:00
hagen-danswer
85cbd9caed Increased slim doc batch size for confluence connector (#3221) 2024-11-23 00:42:15 +00:00
pablodanswer
9dc23bf3e7 revert to previous doc select logic (#3217)
* revert to previous doc select logic

* k
2024-11-22 23:26:53 +00:00
hagen-danswer
e32809f7ca moved it outside 2024-11-22 14:59:58 -08:00
hagen-danswer
3e58f9f8ab fixed ugly stuff 2024-11-22 14:39:55 -08:00
pablodanswer
2381c8d498 Refresh all assistants on assistant refresh (#3216)
* k

* k
2024-11-22 22:38:23 +00:00
hagen-danswer
c6dadb24dc cleaned up new slack bot creation 2024-11-22 11:53:51 -08:00
hagen-danswer
5dc07d4178 Each section is now cleaned before being chunked (#3210)
* Each section is now cleaned before being chunked

* k

---------

Co-authored-by: Yuhong Sun <yuhongsun96@gmail.com>
2024-11-22 19:06:19 +00:00
Chris Weaver
129c8f8faf Add start/end date ability for query history as CSV endpoint (#3211) 2024-11-22 18:29:13 +00:00
pablodanswer
67bfcabbc5 llm provider causing re render in effect (#3205)
* llm provider causing re render in effect

* clean

* unused

* k
2024-11-22 16:53:24 +00:00
rkuo-danswer
9819aa977a implement double check pattern for error conditions (#3201)
* Move unfenced check to check_for_indexing. implement a double check pattern for all indexing error checks

* improved commenting

* exclusions
2024-11-22 04:21:02 +00:00
hagen-danswer
8d5b8a4028 Merge pull request #3202 from danswer-ai/toggled_chat_default
Update default sidebar toggle
2024-11-21 19:53:05 -08:00
pablodanswer
682319d2e9 Bugfix/curator interface (#3198)
* mystery solved

* update config

* update

* update

* update user role

* remove values
2024-11-22 02:33:09 +00:00
hagen-danswer
fe1400aa36 replace deprecated confluence group api endpoint (#3197)
* replace deprecated confluence group api endpoint

* reworked it

* properly escaped the user query

* less passing around is_cloud

* done
2024-11-22 01:51:29 +00:00
pablodanswer
e3573b2bc1 add comment 2024-11-21 17:11:11 -08:00
pablodanswer
35b5c44cc7 update default sidebar toggle 2024-11-21 17:09:56 -08:00
rkuo-danswer
5eddc89b5a merge indexing and heartbeat callbacks (and associated lock reacquisi… (#3178)
* merge indexing and heartbeat callbacks (and associated lock reacquisition). no db updates

* review fixes
2024-11-21 23:48:58 +00:00
hagen-danswer
9a492ceb6d admins cant be set as curator on backend (#3194)
* set-curator

* updated error
2024-11-21 23:33:29 +00:00
rkuo-danswer
3c54ae9de9 Bugfix/redis wait (#3169)
* rename to payload

* log redis info replication on primary worker startup

* fix mypy

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-21 23:11:00 +00:00
pablodanswer
13f08f3ebb Horizontal scrollbar (#3195)
* clean horizontal scrollbar

* account for additional edge case
2024-11-21 22:08:21 +00:00
pablodanswer
bd9f15854f provider fix (#3187)
* clean horizontal scrollbar

* provider fix

* ensure proper migration

* k

* update migration

* Revert "clean horizontal scrollbar"

This reverts commit fa592a1b7a.
2024-11-21 22:08:16 +00:00
pablodanswer
366aa2a8ea quick fix (#3200) 2024-11-21 14:07:55 -08:00
pablodanswer
deee237c7e Sheet update (#3189)
* quick pass

* k

* update sheet

* add multiple sheet stuff

* k

* finalized

* update configuration
2024-11-21 18:07:00 +00:00
hagen-danswer
100b4a0d16 Added Slim connector for Jira (#3181)
* Added Slim connector for Jira

* fixed testing

* more cleanup of Jira connector

* cleanup
2024-11-21 17:00:20 +00:00
rkuo-danswer
70207b4b39 improve web testing (#3162)
* shared admin level test dependency

* change to on - push (recommended by chromatic)

* change playwright reporter to list, name test jobs

* use test tags ... much cleaner

* test vs prod

* try copying templates

* run with localhost?

* revert to dev

* new tests and a bit of refactoring

* add additional checks so that page snapshots reflect loaded state

* more admin tests

* User Management tests

* remaining admin pages

* test search and chat

* await fix and exclude UI that changes with dates.
2024-11-21 04:01:15 +00:00
pablodanswer
50826b6bef Formatting Niceties (#3183)
* search bar formatting

* update styling
2024-11-21 03:11:26 +00:00
pablodanswer
3f648cbc31 Folder clarity (#3180)
* folder clarity

* k
2024-11-21 03:11:17 +00:00
pablodanswer
c875a4774f valid props (#3186) 2024-11-21 01:13:54 +00:00
hagen-danswer
049091eb01 decreased confluence retry times and added more logging (#3184)
* decreased confluence retry times and added more logging

* added check on connector startup

* no retries!

* fr no retries
2024-11-21 00:00:14 +00:00
pablodanswer
3dac24542b silence small error (#3182) 2024-11-20 22:46:38 +00:00
pablodanswer
194dcb593d update slack redirect + token missing check (#3179)
* update slack redirect + token missing check

* reset time
2024-11-20 21:42:54 +00:00
pablodanswer
bf291d0c0a Fix missing json (#3177)
* initial steps

* k

* remove logs

* k

* k
2024-11-20 21:24:43 +00:00
rkuo-danswer
8309f4a802 test overlapping connectors (but using a source that is way too big a… (#3152)
* test overlapping connectors (but using a source that is way too big and slow, fix that next)

* pass thru secrets

* rename

* rename again

* now we are fixing it

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-20 21:12:01 +00:00
pablodanswer
0ff2565125 ensure margin properly applied (#3176)
* ensure margin properly applied

* formatting
2024-11-20 20:04:45 +00:00
hagen-danswer
e89dcd7f84 added logging and bugfixing to conf (#3167)
* standardized escaping of CQL strings

* think i found it

* fix

* should be fixed

* added handling for special linking behavior in confluence

* Update onyx_confluence.py

* Update onyx_confluence.py

---------

Co-authored-by: rkuo-danswer <rkuo@danswer.ai>
2024-11-20 18:40:21 +00:00
pablodanswer
645e7e828e Add Google Tag Manager for Web Cloud Build (#3173)
* add gtm for cloud build

* update github workflow
2024-11-20 17:38:33 +00:00
pablodanswer
2a54f14195 ensure everythigng has a default max height in selectorformfield (#3174) 2024-11-20 17:26:22 +00:00
hagen-danswer
9209fc804b multiple slackbot support (#3077)
* multiple slackbot support

* app_id + tenant_id key

* removed kv store stuff

* fixed up mypy and migration

* got frontend working for multiple slack bots

* some frontend stuff

* alembic fix

* might be valid

* refactor dun

* alembic stuff

* temp frontend stuff

* alembic stuff

* maybe fixed alembic

* maybe dis fix

* im getting mad

* api names changed

* tested

* almost done

* done

* routing nonsense

* done!

* done!!

* fr done

* doneski

* fix alembic migration

* getting mad again

* PLEASE IM BEGGING YOU
2024-11-20 01:49:43 +00:00
rkuo-danswer
b712877701 Merge pull request #3165 from danswer-ai/bugfix/pruning_logs
improve logging around pruning
2024-11-19 13:19:31 -08:00
Richard Kuo (Danswer)
e6df32dcc3 improve logging around pruning 2024-11-19 12:41:21 -08:00
Chris Weaver
eb81258a23 Update README.md
Fix slack link
2024-11-19 08:02:35 -08:00
hagen-danswer
487ef4acc0 Merge pull request #3160 from danswer-ai/add-to-admin-chat-sessions-api
Extend query history API
2024-11-19 07:28:12 -08:00
pablodanswer
9b7cc83eae add new date search filter (#3065)
* add new complicated filters

* clarity updates

* update date range filter
2024-11-19 03:42:42 +00:00
Weves
ce3124f9e4 Extend query history API 2024-11-18 17:50:21 -08:00
rkuo-danswer
e69303e309 add helpful hint on 507 (#3157)
* add helpful hint on 507

* add helpful hint to the direct exception in _index_vespa_chunk
2024-11-19 01:08:32 +00:00
rkuo-danswer
6e698ac84a Hardening deletion when cc pair relationships are left over (#3154)
* more logs

* this fence should be set to None

* type hinting

* reset deletion attempt if conditions are inconsistent

* always clean up in db if we reach reconciliation

* add reset method

* more logging

* harden up error checking
2024-11-19 01:07:59 +00:00
pablodanswer
d69180aeb8 add additional theming options (#3155)
* add additional theming options

* nit

* Update Filters.tsx
2024-11-18 22:56:48 +00:00
rkuo-danswer
aa37051be9 Bugfix/indexing redux (#3151)
* raise indexing lock timeout

* refactor unknown index attempts and redis lock
2024-11-18 22:47:31 +00:00
pablodanswer
a7d95661b3 Add assistant categories (#3064)
* add assistant categories v1

* functionality finalized

* finalize

* update assistant category display

* nit

* add tests

* post rebase update

* minor update to tests

* update typing

* finalize

* typing

* nit

* alembic

* alembic (once again)
2024-11-18 20:33:48 +00:00
Chris Weaver
33ee899408 Long term logs (#3150) 2024-11-18 10:48:03 -08:00
hagen-danswer
954b5b2a56 Made external permissioned users and slack users show diff (#3147)
* Made external permissioned users and slack users show diff

* finished

* Fix typing

* k

* Fix

* k

---------

Co-authored-by: Weves <chrisweaver101@gmail.com>
2024-11-17 01:13:47 +00:00
pablodanswer
521425a4f2 nits + pricing 2024-11-16 16:28:37 -08:00
hagen-danswer
618bc02d54 Fixed int test (#3148) 2024-11-16 18:13:06 +00:00
rkuo-danswer
b7de74fdf8 Feature/playwright tests (#3129)
* initial PoC

* preliminary working config

* first cut at chromatic tests

* first cut at chromatic tests

* fix yaml

* fix yaml again

* use workingDir

* adapt playwright example

* remove env

* fix working directory

* fix more paths

* fix dir

* add playwright setup

* accidentally deleted a step

* update test

* think we don't need home.png right now

* remove unused home.png

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-16 04:26:17 +00:00
hagen-danswer
6e83fe3a39 reworked drive+confluence frontend and implied backend changes (#3143)
* reworked drive+confluence frontend and implied backend changes

* fixed oauth admin tests

* fixed service account tests

* frontend cleanup

* copy change

* details!

* added key

* so good

* whoops!

* fixed mnore treljsertjoslijt

* has issue with boolean form

* should be done
2024-11-16 03:38:30 +00:00
Weves
259fc049b7 Add error message on JSON decode error in CustomTool 2024-11-15 20:00:12 -08:00
rkuo-danswer
7015e6f2ab Bugfix/overlapping connectors (#3138)
* fix tenant logging

* upsert only new/updated docs, but always upsert document to cc pair relationship

* better logging and rough cut at testing
2024-11-16 00:47:52 +00:00
pablodanswer
24be13c015 Improved tokenizer fallback (#3132)
* silence warning

* improved fallback logic

* k

* minor cosmetic update

* minor logic update

* nit
2024-11-14 20:13:29 -08:00
pablodanswer
ddff7ecc3f minor configuration updates (#3134) 2024-11-14 18:09:30 -08:00
Yuhong Sun
97932dc44b Fix Quotes Prompting (#3137) 2024-11-14 17:28:03 -08:00
rkuo-danswer
637b6d9e75 Merge pull request #3135 from danswer-ai/bugfix/helm_ct_python_setup
unnecessary python setup
2024-11-14 14:57:12 -08:00
Richard Kuo (Danswer)
54dc1ac917 unnecessary python setup 2024-11-14 11:14:12 -08:00
rkuo-danswer
21d5cc43f8 Merge pull request #3131 from danswer-ai/bugfix/session_text
use text()
2024-11-13 20:24:14 -08:00
pablodanswer
7c841051ed Cohere (#3111)
* add cohere default

* finalize

* minor improvement

* update

* update

* update configs

* ensure we properly expose name(space) for slackbot

* update config

* config
2024-11-14 01:58:54 +00:00
pablodanswer
6e91964924 minor clarity (#3116) 2024-11-14 01:42:21 +00:00
pablodanswer
facf1d55a0 Cloud improvements (#3099)
* add improved cloud configuration

* fix typing

* finalize slackbot improvements

* minor update

* finalized keda

* moderate slackbot switch

* update some configs

* revert

* include reset engine!
2024-11-13 23:52:52 +00:00
rkuo-danswer
d68f8d6fbc scale indexing sql pool based on concurrency (#3130) 2024-11-13 23:26:13 +00:00
Richard Kuo (Danswer)
65a205d488 use text() 2024-11-13 15:03:21 -08:00
hagen-danswer
485f3f72fa Updated google copy and added non admin oauth support (#3120)
* Updated google copy and added non admin oauth support

* backend update

* accounted for oauth

* further removed class variables

* updated sets
2024-11-13 20:07:10 +00:00
rkuo-danswer
dcbea883ae add creator id to cc pair (#3121)
* add creator id to cc pair

* fix alembic head

* show email instead of UUID

* safer check on email

* make foreign key relationships optional

* always allow creator to edit (per hagen)

* use primary join

* no index_doc_batch spam

* try this again

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-13 19:35:08 +00:00
hagen-danswer
a50a3944b3 Make curators able to create permission synced connectors (#3126)
* Make curators able to create permission synced connectors

* removed editing permission synced connectors for curators

* updated tests to use access type instead of is_public

* update copy
2024-11-13 18:58:23 +00:00
hagen-danswer
60471b6a73 Added support for page within a page in Confluence (#3125) 2024-11-13 16:39:00 +00:00
rkuo-danswer
d703e694ce limited role api keys (#3115)
* in progress PoC

* working limited user, needs routes to be marked next

* make selected endpoint available to limited user role

* xfail on test_slack_prune

* add comment to sync function

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-13 16:15:43 +00:00
hagen-danswer
6066042fef Merge pull request #3124 from danswer-ai/fix-doc-sync
quick fix for google doc sync
2024-11-13 07:30:52 -08:00
hagen-danswer
eb0e20b9e4 quick fix for google doc sync 2024-11-13 07:24:29 -08:00
pablodanswer
490a68773b update organization (#3118)
* update organization

* minor clean up

* add minor clarity

* k

* slight rejigger

* alembic fix

* update paradigm

* delete code!

* delete code

* minor update
2024-11-13 06:45:32 +00:00
rkuo-danswer
227aff1e47 clean up logging in light worker (#3072) 2024-11-13 03:42:02 +00:00
Weves
6e29d1944c Fix widget example 2024-11-12 18:48:44 -08:00
pablodanswer
22189f02c6 Add referral source to cloud on data plane (#3096)
* cloud auth referral source

* minor clarity

* k

* minor modification to be best practice

* typing

* Update ReferralSourceSelector.tsx

* Update ReferralSourceSelector.tsx

---------

Co-authored-by: hagen-danswer <hagen@danswer.ai>
2024-11-13 00:42:25 +00:00
hagen-danswer
fdc4811fce doc sync celery refactor (#3084)
* doc_sync is refactored

* maybe this works

* tested to work!

* mypy fixes

* enabled integration tests

* fixed the test

* added external group sync

* testing should work now

* mypy

* confluence doc id fix

* got group sync working

* addressed feedback

* renamed some vars and fixed mypy

* conf fix?

* added wiki handling to confluence connector

* test fixes

* revert google drive connector

* fixed groups

* hotfix
2024-11-12 23:57:14 +00:00
Chris Weaver
021d0cf314 Support LITELLM_EXTRA_BODY env variable (#3119)
* Support LITELLM_EXTRA_BODY env variable

* Remove unused param

* Add comment
2024-11-12 23:17:44 +00:00
pablodanswer
942e47db29 improved mobile scroll (#3110) 2024-11-12 01:57:49 +00:00
pablodanswer
f4a020b599 moderate component fixes (#3095)
* moderate component fixes

* nit

* nit

* update colors

* k
2024-11-12 00:47:35 +00:00
pablodanswer
5166649eae Cleaner EE fallback for no op (#3106)
* treat async values differently

* cleaner approach

* spacing

* typing
2024-11-11 17:42:14 +00:00
Chris Weaver
ba805f766f New assistants api (#3097) 2024-11-11 07:55:23 -08:00
rkuo-danswer
9d57f34c34 re-enable helm (#3053)
* re-enable helm

* allow manual triggering

* change vespa host

* change vespa chart location

* update Chart.lock

* update ct.yaml with new vespa chart repo

* bump vespa to 0.2.5

* update Chart.lock

* update to vespa 0.2.6

* bump vespa to 0.2.7

* bump to 0.2.8

* bump version

* try appending the ordinal

* try new configmap

* bump vespa

* bump vespa

* add debug to see if we can figure out what ct install thinks is failing

* add debug flag to helm

* try disabling nginx because of KinD

* use helm-extra-set-args

* try command line

* try pointing test connection to the correct service name

* bump vespa to 0.2.12

* update chart.lock

* bump vespa to 0.2.13

* bump vespa to 0.2.14

* bump vespa

* bump vespa

* re-enable chart testing only on changes

* name the check more specifically than "lint-test"

* add some debugging

* try setting remote

* might have to specify chart dirs directly

* add comments

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-10 01:28:39 +00:00
pablodanswer
cc2f584321 Silence auth logs (#3098)
* silence auth logs

* remove unnecessary line

* k
2024-11-09 21:41:11 +00:00
pablodanswer
a1b95df3b8 Robustify cloud deployment + include initial KEDA configuration (#3094)
* robustify cloud deployment + include initial KEDA configuration

* ensure .github changes are passed

* raise exits
2024-11-09 21:26:51 +00:00
pablodanswer
9272d6ebfe Remove ee (#3093)
* move api key to non-ee

* finalize previous migration

* move token rate limit to non-ee

* general cleanup

* update

* update

* finalize

* finalize

* ensure callable

* k
2024-11-09 20:51:36 +00:00
Yuhong Sun
4fb65dcf73 Reenable OpenAI Tokenizer (#3062)
* k

* clean up test embeddings

* nit

* minor update to ensure consistency

* minor organizational update

* minor updates

---------

Co-authored-by: pablodanswer <pablo@danswer.ai>
2024-11-08 22:54:15 +00:00
rkuo-danswer
2bbc5d5d07 fix saving docker logs (#3090) 2024-11-08 19:54:48 +00:00
rkuo-danswer
950b1c38f2 Merge pull request #3080 from danswer-ai/robust_assistant_description
Account for malformatted starter messages
2024-11-08 11:28:19 -08:00
Yuhong Sun
99fbfba32f File Connector Metadata (#3089) 2024-11-08 10:49:59 -08:00
pablodanswer
0a59efe64a account for malformatted starter messages 2024-11-08 10:21:04 -08:00
pablodanswer
cf5d394d39 adjust default postgres schema for slack listener (#3088) 2024-11-08 18:00:44 +00:00
pablodanswer
f6d8f5ca89 Migrate tenant upgrades to data plane (#3051)
* add provisioning on data plane

* functional but scrappy

* minor cleanup

* minor clean up

* k

* simplify

* update provisioning

* improve import logic

* ensure proper conditional

* minor pydantic update

* minor config update

* nit
2024-11-08 17:13:29 +00:00
hagen-danswer
1fb4cdfcc3 Merge pull request #3073 from skylares/fireflies-dev
Fireflies connector
2024-11-08 06:50:22 -08:00
hagen-danswer
ac51469bcb Merge branch 'main' into fireflies-dev 2024-11-07 18:56:37 -08:00
Skylar Kesselring
c25f164e28 Remove linux 2024-11-07 21:51:58 -05:00
Skylar Kesselring
813720905b Fix failure cases 2024-11-07 21:37:41 -05:00
rkuo-danswer
0c45488ac6 wait for db before allowing worker to proceed (reduces error spam on … (#3079)
* wait for db before allowing worker to proceed (reduces error spam on container startup)

* fix session usage

* rework readiness probe logic to be less confusing and word ongoing probes better

* add vespa probe too

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-08 01:25:09 +00:00
Skylar Kesselring
95d9b33c1a Clean up connector 2024-11-07 19:51:40 -05:00
Yuhong Sun
55919f596c PG Dev Max Connections (#3082) 2024-11-07 11:51:23 -08:00
pablodanswer
1d0fb6d012 Evaluate None to default (#3069)
* add sentinel value

* update typing

* clearer

* update comments

* ensure proper attribution
2024-11-07 18:41:42 +00:00
pablodanswer
2b1dbde829 minor improvements (#3081) 2024-11-07 18:35:49 +00:00
hagen-danswer
2758ffd9d5 Google Drive Improvements (#3057)
* Google Drive Improvements

* mypy

* should work!

* variable cleanup

* final fixes
2024-11-07 02:07:35 +00:00
pablodanswer
07a1b49b4f update persona defaults (#3042)
* evaluate None to default

* fix usage report pagination

* update persona defaults

* update user preferences

* k

* validate

* update typing

* nit

* formating nits

* fallback to all assistants

* update ux + spacing

* udpate refresh logic

* minor update to refresh

* nit

* touchup

* update starter message

* update default live assistant logic

---------

Co-authored-by: Yuhong Sun <yuhongsun96@gmail.com>
2024-11-07 00:03:14 +00:00
pablodanswer
43d8daa5bc update redirect 2024-11-06 14:55:32 -08:00
hagen-danswer
faeb9f09f0 Merge pull request #3008 from danswer-ai/horizontal_slack
Add Functional Horizontal scaling for Slack
2024-11-06 14:31:13 -08:00
pablodanswer
25f5c12750 remove print 2024-11-06 13:49:16 -08:00
pablodanswer
2d81710ccc minor udpate 2024-11-06 13:49:16 -08:00
pablodanswer
187a7d2da2 validated approach 2024-11-06 13:49:16 -08:00
pablodanswer
4b152aa3a7 update slack 2024-11-06 13:49:16 -08:00
pablodanswer
06f937cf93 no typing 2024-11-06 13:49:16 -08:00
pablodanswer
5a24ed2947 updated cleanup 2024-11-06 13:49:16 -08:00
pablodanswer
2372e6a5a5 update slack 2024-11-06 13:49:15 -08:00
pablodanswer
3eef4e3992 functioning 2024-11-06 13:47:47 -08:00
pablodanswer
467ce4e3f3 fix usage report pagination 2024-11-06 13:21:00 -08:00
Skylar Kesselring
ee4b334a0a Fix errors and cleanup 2024-11-06 14:01:51 -05:00
pablodanswer
4087292001 evaluate None to default 2024-11-06 09:36:43 -08:00
rkuo-danswer
da6ed5b2b3 Merge pull request #3066 from danswer-ai/bugfix/log-vespa-url
need to see vespa url for container debugging
2024-11-06 00:35:10 -08:00
Richard Kuo
864ac2ac5c need to see vespa url for container debugging 2024-11-06 00:26:55 -08:00
rkuo-danswer
12cb77c80e Merge pull request #3059 from danswer-ai/bugfix/sentry_indexing
add sentry to spawned indexing task
2024-11-05 16:51:23 -08:00
Richard Kuo (Danswer)
583cd14bf4 comment why we need sentry here 2024-11-05 16:46:50 -08:00
Richard Kuo (Danswer)
001fcb3359 fix stale indexing tasks being allowed to run after a restart 2024-11-05 16:39:54 -08:00
Skylar Kesselring
7ff18e0a93 Create connector 2024-11-05 19:28:57 -05:00
Richard Kuo (Danswer)
9ac256e925 Merge branch 'main' of https://github.com/danswer-ai/danswer into bugfix/sentry_indexing 2024-11-05 15:48:23 -08:00
hagen-danswer
08600db41d Merge pull request #3056 from danswer-ai/form_stretch
Improve form
2024-11-05 14:19:11 -08:00
rkuo-danswer
6bf06ac7f7 limit session scope of index attempt (use id's where appropriate as w… (#3049)
* limit session scope of index attempt (use id's where appropriate as well)

* fix session scope

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-05 20:51:43 +00:00
Richard Kuo (Danswer)
5b06b53a3e add sentry to spawned indexing task 2024-11-05 12:30:21 -08:00
pablodanswer
afce57b29f clarity 2024-11-05 10:44:12 -08:00
pablodanswer
257dbecd1d k 2024-11-05 10:24:48 -08:00
pablodanswer
bd6baf39c3 update 2024-11-05 10:23:52 -08:00
pablodanswer
b2c55ebd71 ensure props aligned (#3050)
* ensure props aligned

* k

* k
2024-11-05 16:49:04 +00:00
pablodanswer
dea7a8f697 Clean up tooltips (#3047)
* clean up tooltips

* nit: fix delay duration
2024-11-05 16:48:19 +00:00
pablodanswer
ddae2346ec form 2024-11-05 08:33:03 -08:00
Weves
9032fb4467 Improve background token refresh 2024-11-04 15:00:16 -08:00
rkuo-danswer
b6ecbbcf45 add to async get session as well (#3046) 2024-11-04 20:47:56 +00:00
pablodanswer
1d8e662b79 ensure we reset all (#3048) 2024-11-04 19:48:15 +00:00
pablodanswer
2cb33b1fb4 add default api keys for cloud users (#3044)
* add default api keys for cloud users

* add cohere as well

* naming
2024-11-04 19:11:12 +00:00
hagen-danswer
2cd1e6be00 gmail refactor + permission syncing (#3021)
* initial frontend changes and shared google refactoring

* gmail connector is reworked

* added permission syncing for gmail

* tested!

* Added tests for gmail connector

* fixed tests and mypy

* temp fix

* testing done!

* rename

* test fixes maybe?

* removed irrelevant tests

* anotha one

* refactoring changes

* refactor finished

* maybe these fixes work

* dumps

* final fixes
2024-11-04 18:06:23 +00:00
Weves
8e55566f66 Fix slack bot form + LLM provider form 2024-11-03 17:51:04 -08:00
pablodanswer
bafb95d920 Misc color clean up (#3026)
* misc color clean up

* additional nits

* nit

* nit

* additional minor nits

* ensure tailwind config evaluates properly + update textarea -> input

* ensure tool call renders

* formatting
2024-11-03 23:57:11 +00:00
pablodanswer
c6e8bf2d28 add multiple formats to tools (#3041) 2024-11-03 23:54:19 +00:00
Chris Weaver
c2d04f591d Add drive sections (#3040)
* ADd header support for drive

* Fix mypy

* Comment change

* Improve

* Cleanup

* Add comment
2024-11-03 22:10:45 +00:00
rkuo-danswer
56c3a5ff5b add POSTGRES_IDLE_SESSIONS_TIMEOUT (#3019)
Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-03 21:58:12 +00:00
Yuhong Sun
fac2b100a1 Last Message Too Large Logging (#3039) 2024-11-03 11:24:04 -08:00
pablodanswer
51b79f688a Tool call per message (#3025)
* single tool call per message

* finalize migration

* minor image generation fix

* validate simplify

* k

* remove print

* validated
2024-11-03 10:51:51 -08:00
pablodanswer
a7002dfa1d add CSV display (#3028)
* add CSV display

* add downloading

* restructure

* create portal for modal

* update requirements

* nit
2024-11-03 10:43:05 -08:00
pablodanswer
93d0104d3c slight upgrade to image generation prompts (#3036)
* slight upgrade to prompts

* k

* nit
2024-11-03 10:42:52 -08:00
pablodanswer
46e5ffa3ae add validated + reformatted dynamic beat acquisition (#3006)
* add validated + reformatted dynamic beat acquisition

* validate

* reorg

* nit

* address comments

* update

* typing

* ensure versioned apps capture

* Remove locks (#3017)

* add validated + reformatted dynamic beat acquisition

* initial removal of locks!

* minor

* remove unecessary locks

* update

* nit

* k

* K8s jobs (#3033)

* add k8s configs

* k

* update config

* k

* improved timeouts + worker configs

* improve workers
2024-11-03 10:27:25 -08:00
pablodanswer
d4f38bba8b Revert temporary modifications (#3038)
* Revert temporary modifications

* nit
2024-11-03 10:27:06 -08:00
pablodanswer
19d6b63fd3 temporary update (#3037) 2024-11-03 10:05:33 -08:00
Chris Weaver
938d5788b6 Upgrade to latest NextJS + switch to turbopack (#3027)
* Upgrade to NextJS 15 + use turbopacK

* Remove unintended change

* Update nextjs version

* Remove override

* Upgrade react

* Fix charts

* Style

* Style

* Fix prettier

* slight modification

---------

Co-authored-by: pablodanswer <pablo@danswer.ai>
2024-11-03 02:56:23 +00:00
hagen-danswer
70f703cc0f Merge pull request #3035 from danswer-ai/freshdesk-nit
minor nit
2024-11-02 18:14:52 -07:00
hagen-danswer
8bcf80aa76 minor nit 2024-11-02 18:05:06 -07:00
rkuo-danswer
5f5cc9a724 Feature/redis connector refactor (#2992)
* refactor RedisConnectorDeletion into RedisConnector

* refactor redis stop and deletion

* port pruning

* nest pruning

* port deletion

* port indexing

* refactor into individual files

* refactor redis connector index  to take search settings at init

* move back to debug level log

* refactor doc set and user group (mostly)

* mypy fixes
2024-11-02 19:53:04 +00:00
pablodanswer
e4bb14d4e1 Super user (#2944)
* add super user

* nits
2024-11-02 17:29:23 +00:00
hagen-danswer
5d9b8364ab Merge pull request #3032 from danswer-ai/freshdesk-cleanup
Cleaned up connector
2024-11-02 09:31:22 -07:00
hagen-danswer
83c299ebc8 troll logger statement 2024-11-02 09:09:46 -07:00
hagen-danswer
6b4143cc30 ID fix 2024-11-02 09:08:26 -07:00
hagen-danswer
6e8c88ed71 made id more unique 2024-11-02 09:05:24 -07:00
hagen-danswer
d652cb3141 renamed variables 2024-11-02 09:03:42 -07:00
hagen-danswer
5e444d43f9 Cleaned up connector 2024-11-02 09:01:15 -07:00
hagen-danswer
2e49027beb Merge pull request #2884 from skylares/sky-dev
Add Freshdesk Connector
2024-11-02 08:27:35 -07:00
hagen-danswer
d7bcd32d9a out of scope 2024-11-02 08:21:33 -07:00
hagen-danswer
4a6b8db65f out of scope 2024-11-02 08:20:08 -07:00
hagen-danswer
6f440d126a more mypy fixes 2024-11-02 08:17:53 -07:00
hagen-danswer
013292a0e3 mypy fixes 2024-11-02 08:15:36 -07:00
Richard Kuo
a1ae22ef4a fix run key 2024-11-02 02:23:08 -07:00
Richard Kuo
40beda30a4 try pip-license-checker 2024-11-02 02:20:58 -07:00
Richard Kuo
d3062cacea manual only for now 2024-11-02 00:01:55 -07:00
Richard Kuo
678ed23853 codel permissions? 2024-11-01 22:34:41 -07:00
Richard Kuo
ea2da63cf2 try installing npm deps 2024-11-01 22:09:06 -07:00
Richard Kuo
4fc8a35220 try repo level scan 2024-11-01 21:59:23 -07:00
hagen-danswer
f981106111 Update connector.py 2024-11-01 19:27:03 -07:00
Richard Kuo (Danswer)
5439c33313 don't scan the os packages 2024-11-01 17:24:41 -07:00
Richard Kuo (Danswer)
5e050f8305 we didn't checkout the code, no trivy ignore 2024-11-01 17:16:28 -07:00
Richard Kuo (Danswer)
12c82de78f experimental github action to scan licenses 2024-11-01 17:10:59 -07:00
pablodanswer
645402c71a Tremor -> Shadcn (#2983)
* initialization

* button + input updates

* migrate dividers + buttons

* migrate badges

* minor updates

* migrate cards

* fix compiling

* begin date picker + badge transfer

* remove tremor

* fully swapped

* nits

* list item + configuration updates

* clean build

* update colors

* nits
2024-11-01 23:20:06 +00:00
pablodanswer
772313236f minor foreign key update (#3007) 2024-11-01 21:16:50 +00:00
Chris Weaver
ecf4923a3a Fix answer with specified doc ids (#2703)
* Fix

Fix

Refactor

more

more

fix

refactor

Fix circular imports

Refactor

Move tests around

* Add quote support

* Testing

* More testing

* Fix image generation slowness

* Remove unused exception

* Fix UT

* fix stop generating

* minor typo

* minor logging updates for clarity

---------

Co-authored-by: pablodanswer <pablo@danswer.ai>
2024-11-01 19:50:20 +00:00
pablodanswer
d66b81a902 Feat/certificate (#2998)
* first pass

* simplify

* remove now unneeded COPY command

* minor clean up

* k

* nit
2024-11-01 19:34:52 +00:00
pablodanswer
753293cefb Basic multi tenant api key (#3004)
* basic multi tenant api key

* organization

* nit

* clean
2024-11-01 19:34:51 +00:00
pablodanswer
6d543f3d4f Do not count API keys as users (#3022)
* don't count api keys as users

* typing
2024-11-01 19:34:30 +00:00
hagen-danswer
ccdc09e2d4 Merge pull request #3020 from danswer-ai/gdrive-interface
Add Gdrive Interface
2024-11-01 06:28:56 -07:00
hagen-danswer
4a23c8702d Quicky 2024-11-01 06:27:55 -07:00
rkuo-danswer
dc2dfeb5b8 Fix pywikibot droppings (#2924)
* make pywikibot store its working files in a system provided temp directory

* move the config setting around

---------

Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-11-01 05:59:12 +00:00
hagen-danswer
71d4fb98d3 Refactored Google Drive Connector + Permission Syncing (#2945)
* refactoring changes

* everything working for service account

* works with service account

* combined scopes

* copy change

* oauth prep

* Works for oauth and service account credentials

* mypy

* merge fixes

* Refactor Google Drive connector

* finished backend

* auth changes

* if its stupid but it works, its not stupid

* npm run dev fixes

* addressed change requests

* string fix

* minor fixes and cleanup

* spacing cleanup

* Update connector.py

* everything done

* testing!

* Delete backend/tests/daily/connectors/google_drive/file_generator.py

* cleaned up

---------

Co-authored-by: Chris Weaver <25087905+Weves@users.noreply.github.com>
2024-11-01 02:25:00 +00:00
Yuhong Sun
b34f5862d7 Remove License Issues (#3013)
* k

* k

* k

* k

* k
2024-11-01 00:31:19 +00:00
pablodanswer
0b08bf4e3f Proper tenant reset (#3015)
* add proper tenant reset

* clear comment

* minor formatting
2024-10-31 19:45:35 +00:00
pablodanswer
add87fa1b4 remove endpoint (#3014) 2024-10-31 19:43:15 +00:00
Samarth Mishra
787fdf2e38 Update README.md (#3011) 2024-10-31 10:44:36 -07:00
Weves
4499c630b3 Fix model test action name 2024-10-31 10:12:01 -07:00
hagen-danswer
e3be318781 Update connector.py 2024-10-31 09:50:48 -07:00
rkuo-danswer
231ab3fb5d Feature/indexing logs (#3002)
* improve logging around indexing tasks

* task_logger doesn't work inside the spawned task
2024-10-31 16:43:46 +00:00
Yuhong Sun
ff9d7141a9 Gmail Connector Robustify (#3000) 2024-10-30 20:21:54 -07:00
rkuo-danswer
dba2d67cdb only warmup on index swap (#3003)
* only warmup on index swap

* move conditional
2024-10-31 00:40:03 +00:00
Yuhong Sun
1a7d627949 Disable Mediawiki Tests (#3005) 2024-10-30 17:27:58 -07:00
pablodanswer
f318e302c5 Minor theming (#2993)
* ensure functionality

* naming

* ensure tailwind theme updated

* add comments

* nit

* remove pr

* enforce colors

* update our tailwind config
2024-10-30 23:05:32 +00:00
pablodanswer
7384ca8768 clarity (#3001) 2024-10-30 15:53:26 -07:00
Skylar Kesselring
73ee709801 Fix typing errors 2024-10-30 17:46:04 -04:00
Skylar Kesselring
53d2d333ab Refactor metadata 2024-10-30 17:23:20 -04:00
Chris Weaver
5be457e321 Add alternative auth header (#2999) 2024-10-30 19:10:03 +00:00
pablodanswer
8223dc763d add regeneration clarity (#2986)
* add regeneration clarity

* minor udpate
2024-10-30 18:55:47 +00:00
rkuo-danswer
ea406c55cd add extra tags to pruning logs (#2994)
Co-authored-by: Richard Kuo <rkuo@rkuo.com>
2024-10-30 17:54:29 +00:00
rkuo-danswer
ea80cdce02 init sqlalchemy in child process (#2987) 2024-10-29 18:01:34 +00:00
Weves
40a0f71960 Temp fix to add retries to get_all_vespa_ids_for_document_id 2024-10-29 10:34:42 -07:00
Chris Weaver
fcb94f1173 Tiny logging clarity improvement (#2985) 2024-10-29 16:44:02 +00:00
hagen-danswer
cc40f0d27b fixed label filter (#2978)
* added old error handling to comment fetching

* Not

* properly escaped cql labels

* reverted changes
2024-10-29 16:05:01 +00:00
pablodanswer
75dd103238 add additional configuration options (#2980) 2024-10-29 13:29:39 +00:00
pablodanswer
aafcf7af55 fail gracefully on provider fetch (#2981) 2024-10-29 04:17:53 +00:00
rkuo-danswer
1201ed5ac0 Merge pull request #2979 from danswer-ai/bugfix/redis_scard
missing scard
2024-10-28 16:35:01 -07:00
Richard Kuo (Danswer)
a60613ec11 missing scard 2024-10-28 16:25:08 -07:00
pablodanswer
5640230f5b remove empty directory (#2977) 2024-10-28 16:11:00 -07:00
pablodanswer
11d849b553 add indent to scan_iter (#2948) 2024-10-28 16:08:47 -07:00
pablodanswer
2eefb3c15f add srem and sadd to tenant wrapper (#2973) 2024-10-28 22:20:21 +00:00
pablodanswer
678ba41321 Cleaner initial chat screen (#2528)
* cleaner initial chat screen

* slightly cleaner animation

* cleaner cards

* use display name + minor updates to models

* minor udpate to ui

* remove logs

* update based on feedback

* minor nits

* formatting
2024-10-28 21:39:34 +00:00
pablodanswer
a40082c5da Distinguish users in posthog (#2965)
* distinguish tenants in posthog

* nit
2024-10-28 19:47:26 +00:00
pablodanswer
e5af4681d3 Fix nagging double auth issue (#2960)
* fix nagging double auth issue

* ports
2024-10-28 19:44:45 +00:00
rkuo-danswer
e05846db9f change test port to 8889 (docker desktop is now using port 8888 which blocks the test from working on mac) (#2972) 2024-10-28 18:33:32 +00:00
Skylar Kesselring
195e2c335d Fix per_page count 2024-10-28 12:35:40 -04:00
Skylar Kesselring
1dec69bb82 Fix document time parsing 2024-10-28 12:33:58 -04:00
rkuo-danswer
1d89fea73e Bugfix/celery light backoff (#2880)
* logging cleanup

* raise vespa_timeout to 15 by default

* implement backoff for document index methods specifically

* do not retry on 400 BAD_REQUEST

* handle RetryError

* actually check status code and fix type errors
2024-10-28 16:14:51 +00:00
Skylar Kesselring
075e4f18bc Clean up & comment fetch_tickets 2024-10-28 11:26:37 -04:00
hagen-danswer
52bd1ad8ef Merge pull request #2921 from danswer-ai/feature/reset_indexes
Feature/reset indexes
2024-10-28 06:46:04 -07:00
Yuhong Sun
5062075b8d Backport Test 7 (#2971) 2024-10-27 22:55:35 -07:00
Yuhong Sun
e46facb765 Backport Final 2024-10-27 22:52:52 -07:00
Yuhong Sun
f84e75cee7 Backport Test 6 (#2970) 2024-10-27 22:45:22 -07:00
Yuhong Sun
b2d8e10339 Richard Key 2024-10-27 20:09:42 -07:00
Yuhong Sun
d8ad3e73bf Backport Test 5 (#2969) 2024-10-27 20:07:29 -07:00
Yuhong Sun
e2c4c07c34 Push Tag 2024-10-27 19:56:29 -07:00
Yuhong Sun
7856718db8 k 2024-10-27 19:54:53 -07:00
Yuhong Sun
3d9cc769d9 Backport Test 4 (#2968) 2024-10-27 19:41:04 -07:00
Yuhong Sun
20e8c2287a Add Conditional 2024-10-27 19:39:18 -07:00
Yuhong Sun
57e5264df6 Backport Test (#2967) 2024-10-27 19:31:29 -07:00
Yuhong Sun
4c417b5e3e Revert 2024-10-27 19:12:31 -07:00
Yuhong Sun
9270782c49 Backport Test (#2966) 2024-10-27 19:00:37 -07:00
Yuhong Sun
1a31f1e773 New Credentials GH 2024-10-27 18:58:26 -07:00
Yuhong Sun
e28ba4b55b Backport Test Conn (#2964) 2024-10-27 17:10:31 -07:00
Yuhong Sun
7ddfabed62 Backport Debugging 2024-10-27 17:03:53 -07:00
Yuhong Sun
c7018f7a6c Backport Test (#2963) 2024-10-27 16:55:02 -07:00
Yuhong Sun
0fb6baef2b Echo Merge Commit (#2962) 2024-10-27 16:52:07 -07:00
Yuhong Sun
23988f8c49 Touchup (#2961) 2024-10-27 16:45:11 -07:00
Yuhong Sun
1187849afe Backport Touchup 2024-10-27 16:42:08 -07:00
Yuhong Sun
001801dee0 Add back Backport Tags 2024-10-27 16:37:26 -07:00
Yuhong Sun
4a9966148d Backport Test (#2959) 2024-10-27 16:33:04 -07:00
Yuhong Sun
85c56f9942 Backport Richard 2024-10-27 16:30:15 -07:00
Yuhong Sun
07d76b2954 Notion Child Block Fix (#2953) 2024-10-27 16:25:43 -07:00
Yuhong Sun
2a6c032883 Backport No Tag 2024-10-27 16:19:59 -07:00
Yuhong Sun
e8dfed959e Backport Test (#2958) 2024-10-27 16:06:36 -07:00
Yuhong Sun
1f2be542f0 Backport Test 2024-10-27 15:59:52 -07:00
Yuhong Sun
7dc06bfbe5 Backport Test (#2957) 2024-10-27 15:55:07 -07:00
Yuhong Sun
6f8e7abcbb Backport (#2956) 2024-10-27 15:45:57 -07:00
Yuhong Sun
18dcdd680d GHA Trigger (#2955) 2024-10-27 15:44:41 -07:00
Yuhong Sun
ad3df42b52 Backport Tag Test (#2954) 2024-10-27 15:37:59 -07:00
Yuhong Sun
6568c7805a Update docker-build-push-backend-container-on-tag.yml 2024-10-27 15:31:08 -07:00
Yuhong Sun
fa88c1dba8 Test Workflow Trigger (#2952) 2024-10-27 15:21:17 -07:00
Yuhong Sun
7ea484aee2 Trigger from Workflow (#2951) 2024-10-27 15:18:46 -07:00
hagen-danswer
dc7b367816 Merge pull request #2949 from danswer-ai/avoid_image_confusion
avoid image generation tool confusion
2024-10-27 14:54:24 -07:00
pablodanswer
aea261d49e Ensure build args passed to cloud web images (#2947)
* ensure build args passed to cloud web images

* update web build workflow
2024-10-27 14:52:33 -07:00
Yuhong Sun
f27071cbc5 Harmless Backport Test (#2950) 2024-10-27 14:49:10 -07:00
pablodanswer
31a518a9d1 nit 2024-10-27 13:09:13 -07:00
pablodanswer
01463442ba avoid image generation tool confusion 2024-10-27 13:08:18 -07:00
pablodanswer
53e916552b tenant seeding docs (#2925)
* tenant seeding docs

* k
2024-10-27 18:48:47 +00:00
pablodanswer
179dc418e0 Onboarding nits (#2907)
* temporary stash

* welcome flow

* minor update

* k

* minor updates to welcome flow
2024-10-27 18:48:30 +00:00
pablodanswer
a1bfa7847a a (#2815) 2024-10-27 17:52:55 +00:00
Skylar Kesselring
e5494f9742 Refactor & cleanup code, process tickets in batches 2024-10-27 11:53:50 -04:00
pablodanswer
da3c5e3711 Feat: add clean logging for api routes (#2928)
* feat: add clean logging for api routes

* nit

* `MULTI_TENANT` must be shared config

* nit
2024-10-27 05:15:41 +00:00
Skylar Kesselring
e5d84cae1b Clean up code 2024-10-26 23:06:24 -04:00
Chris Weaver
0c2cc7499f Move user fetching to SS + parallelize some server-side calls (#2932)
* Move user fetching to SS

* Cleanup

* Add more logging

* Small cleanup
2024-10-27 02:54:22 +00:00
pablodanswer
1261d859ac Tenant aware JWT strategy (#2943)
* add tenantJWTSrategy

* nit
2024-10-26 23:27:40 +00:00
pablodanswer
088551a4ef remove rt + home-grown sitemap parsing (#2933)
* remove rt

* nit

* add minor alembic revision

* functional migration

* replace usp

* k

* typing
2024-10-26 21:58:42 +00:00
Yuhong Sun
aa0f307cc7 Backport Test Final (#2942) 2024-10-26 21:52:59 +00:00
Yuhong Sun
e6bef573ba Backport Correct Branch (#2941) 2024-10-26 14:34:24 -07:00
Yuhong Sun
f6f9112b76 Backport Test (#2940) 2024-10-26 14:23:43 -07:00
Yuhong Sun
accdd580d7 Backport Test (#2939) 2024-10-26 13:59:55 -07:00
Yuhong Sun
4bcd65ed92 Harmless Backport Test (#2938) 2024-10-26 13:47:09 -07:00
Yuhong Sun
80f8d7a486 Backport Permissions (#2937) 2024-10-26 13:42:09 -07:00
pablodanswer
e8c28e79c9 ensure proper sentry silencing (#2934)
* ensure proper sentry silencing

* add comments
2024-10-26 20:18:41 +00:00
Yuhong Sun
b4bc6d994d Backport Auth (#2936) 2024-10-26 13:20:02 -07:00
Yuhong Sun
ccc68c5c34 Backport Test (#2935) 2024-10-26 13:09:07 -07:00
pablodanswer
848d86b886 feat: sentry updates (#2929) 2024-10-26 19:06:46 +00:00
Yuhong Sun
c0ab86bac2 Backport Branch Fix (#2931) 2024-10-26 12:04:52 -07:00
Yuhong Sun
8c2138a6ef Backport Test (#2930) 2024-10-26 11:51:03 -07:00
pablodanswer
9def9f0dba add posthog + layout rework (#2926)
* add posthog + layout rework

* remove posthog node

* nit
2024-10-26 18:15:01 +00:00
Skylar Kesselring
8023cafb2b Fixed polling issue with timezone 2024-10-25 23:46:47 -04:00
pablodanswer
5e01d6befb check for index swap (#2922)
* check for index swap

* k

* minor

* k

* nit
2024-10-26 00:26:02 +00:00
hagen-danswer
94edcac36e upgraded claude model strings (#2876)
* upgraded model strings

* trolled

* we do a little trolling

* reeeeeee

* alembic upgrade

* added ignore

* bump litellm

* k

* nit

---------

Co-authored-by: pablodanswer <pablo@danswer.ai>
2024-10-26 00:11:52 +00:00
Richard Kuo (Danswer)
0ed77aa8a7 Merge branch 'main' of https://github.com/danswer-ai/danswer into feature/reset_indexes 2024-10-25 12:00:25 -07:00
pablodanswer
9b147ae437 Tenant integration tests (#2913)
* check for index swap

* initial bones

* kk

* k

* k:

* nit

* nit

* rebase + update

* nit

* minior update

* k

* minor integration test fixes

* nit

* ensure we build test docker image

* remove one space

* k

* ensure we wipe volumes

* remove log

* typo

* nit

* k

* k
2024-10-25 18:47:17 +00:00
Chris Weaver
bd63119684 Fix structured outputs (#2923)
* Fix structured outputs

* Add back rest
2024-10-25 18:19:54 +00:00
Skylar Kesselring
a348caa9b1 Add pagination & Remove req.obj from connectors.tsx 2024-10-25 14:12:11 -04:00
pablodanswer
76415aff41 Ensure proper modal fallback (#2906)
* modal fallback

* nit

* k

* k
2024-10-25 17:59:43 +00:00
Richard Kuo (Danswer)
84d551eda4 Merge branch 'patch-1' of https://github.com/Yash-2707/danswer into feature/reset_indexes 2024-10-25 09:35:45 -07:00
Skylar Kesselring
245adc4d3d Remove 2 month time check & Add time range to fetch and process 2024-10-24 12:42:08 -04:00
Skylar Kesselring
4ad35d76b0 Make ticket fetching a seperate function from processing 2024-10-24 12:25:29 -04:00
Skylar Kesselring
cc1e1c178b Replace html processing library with danswer util 2024-10-24 11:49:11 -04:00
Skylar Kesselring
87b5975091 Remove unnecessary log & Add LoadConnector 2024-10-24 11:38:29 -04:00
Skylar Kesselring
85b56e39c9 Fix Freshdesk connector date parsing for UTC timestamps 2024-10-23 14:01:03 -04:00
Skylar Kesselring
a1680fac2f Implement freshdesk frontend 2024-10-23 12:58:15 -04:00
YASH
8f236a1288 Update reset_indexes.py
Error Handling: Add more specific error handling to make it easier to debug issues.
Configuration Management: Use environment variables or a configuration file for settings like DOCUMENT_INDEX_NAME and DOCUMENT_ID_ENDPOINT.
Logging: Improve logging to include more details about the operations.
Retry Mechanism: Add a retry mechanism for network requests to handle transient errors.
Testing: Add unit tests for the functions to ensure they work as expected
2024-10-22 17:37:07 +05:30
870 changed files with 47840 additions and 28731 deletions

View File

@@ -3,61 +3,61 @@ name: Build and Push Backend Image on Tag
on:
push:
tags:
- '*'
- "*"
env:
REGISTRY_IMAGE: danswer/danswer-backend
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-backend-cloud' || 'danswer/danswer-backend' }}
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
build-and-push:
# TODO: investigate a matrix build like the web container
# TODO: investigate a matrix build like the web container
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Install build-essential
run: |
sudo apt-get update
sudo apt-get install -y build-essential
- name: Backend Image Docker Build and Push
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile
platforms: linux/amd64,linux/arm64
push: true
tags: |
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
- name: Install build-essential
run: |
sudo apt-get update
sudo apt-get install -y build-essential
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
# To run locally: trivy image --severity HIGH,CRITICAL danswer/danswer-backend
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
severity: 'CRITICAL,HIGH'
trivyignores: ./backend/.trivyignore
- name: Backend Image Docker Build and Push
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile
platforms: linux/amd64,linux/arm64
push: true
tags: |
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
with:
# To run locally: trivy image --severity HIGH,CRITICAL danswer/danswer-backend
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
severity: "CRITICAL,HIGH"
trivyignores: ./backend/.trivyignore

View File

@@ -0,0 +1,137 @@
name: Build and Push Cloud Web Image on Tag
# Identical to the web container build, but with correct image tag and build args
on:
push:
tags:
- "*"
env:
REGISTRY_IMAGE: danswer/danswer-web-server-cloud
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
build:
runs-on:
- runs-on
- runner=${{ matrix.platform == 'linux/amd64' && '8cpu-linux-x64' || '8cpu-linux-arm64' }}
- run-id=${{ github.run_id }}
- tag=platform-${{ matrix.platform }}
strategy:
fail-fast: false
matrix:
platform:
- linux/amd64
- linux/arm64
steps:
- name: Prepare
run: |
platform=${{ matrix.platform }}
echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
- name: Checkout
uses: actions/checkout@v4
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY_IMAGE }}
tags: |
type=raw,value=${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
type=raw,value=${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v5
with:
context: ./web
file: ./web/Dockerfile
platforms: ${{ matrix.platform }}
push: true
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
NEXT_PUBLIC_CLOUD_ENABLED=true
NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
NEXT_PUBLIC_GTM_ENABLED=true
# needed due to weird interactions with the builds for different platforms
no-cache: true
labels: ${{ steps.meta.outputs.labels }}
outputs: type=image,name=${{ env.REGISTRY_IMAGE }},push-by-digest=true,name-canonical=true,push=true
- name: Export digest
run: |
mkdir -p /tmp/digests
digest="${{ steps.build.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest
uses: actions/upload-artifact@v4
with:
name: digests-${{ env.PLATFORM_PAIR }}
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
merge:
runs-on: ubuntu-latest
needs:
- build
steps:
- name: Download digests
uses: actions/download-artifact@v4
with:
path: /tmp/digests
pattern: digests-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY_IMAGE }}
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
run: |
docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
$(printf '${{ env.REGISTRY_IMAGE }}@sha256:%s ' *)
- name: Inspect image
run: |
docker buildx imagetools inspect ${{ env.REGISTRY_IMAGE }}:${{ steps.meta.outputs.version }}
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
with:
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
severity: "CRITICAL,HIGH"

View File

@@ -3,53 +3,53 @@ name: Build and Push Model Server Image on Tag
on:
push:
tags:
- '*'
- "*"
env:
REGISTRY_IMAGE: danswer/danswer-model-server
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-model-server-cloud' || 'danswer/danswer-model-server' }}
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
build-and-push:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Model Server Image Docker Build and Push
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64,linux/arm64
push: true
tags: |
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
- name: Model Server Image Docker Build and Push
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64,linux/arm64
push: true
tags: |
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
image-ref: docker.io/danswer/danswer-model-server:${{ github.ref_name }}
severity: 'CRITICAL,HIGH'
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
with:
image-ref: docker.io/danswer/danswer-model-server:${{ github.ref_name }}
severity: "CRITICAL,HIGH"

View File

@@ -0,0 +1,76 @@
# Scan for problematic software licenses
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
name: 'Nightly - Scan licenses'
on:
# schedule:
# - cron: '0 14 * * *' # Runs every day at 6 AM PST / 7 AM PDT / 2 PM UTC
workflow_dispatch: # Allows manual triggering
permissions:
actions: read
contents: read
security-events: write
jobs:
scan-licenses:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
cache: 'pip'
cache-dependency-path: |
backend/requirements/default.txt
backend/requirements/dev.txt
backend/requirements/model_server.txt
- name: Get explicit and transitive dependencies
run: |
python -m pip install --upgrade pip
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
pip freeze > requirements-all.txt
- name: Check python
id: license_check_report
uses: pilosus/action-pip-license-checker@v2
with:
requirements: 'requirements-all.txt'
fail: 'Copyleft'
exclude: '(?i)^(pylint|aio[-_]*).*'
- name: Print report
if: ${{ always() }}
run: echo "${{ steps.license_check_report.outputs.report }}"
- name: Install npm dependencies
working-directory: ./web
run: npm ci
- name: Run Trivy vulnerability scanner in repo mode
uses: aquasecurity/trivy-action@0.28.0
with:
scan-type: fs
scanners: license
format: table
# format: sarif
# output: trivy-results.sarif
severity: HIGH,CRITICAL
# - name: Upload Trivy scan results to GitHub Security tab
# uses: github/codeql-action/upload-sarif@v3
# with:
# sarif_file: trivy-results.sarif

View File

@@ -1,24 +1,34 @@
name: Backport on Merge
# Note this workflow does not trigger the builds, be sure to manually tag the branches to trigger the builds
on:
pull_request:
types: [closed]
types: [closed] # Later we check for merge so only PRs that go in can get backported
permissions:
contents: write
actions: write
jobs:
backport:
if: github.event.pull_request.merged == true
runs-on: ubuntu-latest
env:
GITHUB_TOKEN: ${{ secrets.YUHONG_GH_ACTIONS }}
steps:
- name: Checkout code
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0 # Fetch all history for all branches and tags
ssh-key: "${{ secrets.RKUO_DEPLOY_KEY }}"
fetch-depth: 0
- name: Set up Git
- name: Set up Git user
run: |
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
git config user.name "Richard Kuo [bot]"
git config user.email "rkuo[bot]@danswer.ai"
git fetch --prune
- name: Check for Backport Checkbox
id: checkbox-check
run: |
@@ -36,13 +46,19 @@ jobs:
BRANCHES=$(git for-each-ref --format='%(refname:short)' refs/remotes/origin/release/* | sed 's|origin/release/||' | sort -Vr)
BETA=$(echo "$BRANCHES" | head -n 1)
STABLE=$(echo "$BRANCHES" | head -n 2 | tail -n 1)
echo "beta=$BETA" >> $GITHUB_OUTPUT
echo "stable=$STABLE" >> $GITHUB_OUTPUT
echo "beta=release/$BETA" >> $GITHUB_OUTPUT
echo "stable=release/$STABLE" >> $GITHUB_OUTPUT
# Fetch latest tags for beta and stable
LATEST_BETA_TAG=$(git tag -l "v*.*.0-beta.*" | sort -Vr | head -n 1)
LATEST_STABLE_TAG=$(git tag -l "v*.*.*" | grep -v -- "-beta" | sort -Vr | head -n 1)
# Increment latest beta tag
NEW_BETA_TAG=$(echo $LATEST_BETA_TAG | awk -F '[.-]' '{print $1 "." $2 ".0-beta." ($NF+1)}')
LATEST_BETA_TAG=$(git tag -l "v[0-9]*.[0-9]*.[0-9]*-beta.[0-9]*" | grep -E "^v[0-9]+\.[0-9]+\.[0-9]+-beta\.[0-9]+$" | grep -v -- "-cloud" | sort -Vr | head -n 1)
LATEST_STABLE_TAG=$(git tag -l "v[0-9]*.[0-9]*.[0-9]*" | grep -E "^v[0-9]+\.[0-9]+\.[0-9]+$" | sort -Vr | head -n 1)
# Handle case where no beta tags exist
if [[ -z "$LATEST_BETA_TAG" ]]; then
NEW_BETA_TAG="v1.0.0-beta.1"
else
NEW_BETA_TAG=$(echo $LATEST_BETA_TAG | awk -F '[.-]' '{print $1 "." $2 "." $3 "-beta." ($NF+1)}')
fi
# Increment latest stable tag
NEW_STABLE_TAG=$(echo $LATEST_STABLE_TAG | awk -F '.' '{print $1 "." $2 "." ($3+1)}')
echo "latest_beta_tag=$LATEST_BETA_TAG" >> $GITHUB_OUTPUT
@@ -64,29 +80,45 @@ jobs:
run: |
set -e
echo "Backporting to beta ${{ steps.list-branches.outputs.beta }} and stable ${{ steps.list-branches.outputs.stable }}"
# Echo the merge commit SHA
echo "Merge commit SHA: ${{ github.event.pull_request.merge_commit_sha }}"
# Fetch all history for all branches and tags
git fetch --prune --unshallow
# Checkout the beta branch
git fetch --prune
# Reset and prepare the beta branch
git checkout ${{ steps.list-branches.outputs.beta }}
echo "Last 5 commits on beta branch:"
git log -n 5 --pretty=format:"%H"
echo "" # Newline for formatting
# Cherry-pick the merge commit from the merged PR
git cherry-pick -m 1 ${{ github.event.pull_request.merge_commit_sha }} || {
echo "Cherry-pick to beta failed due to conflicts."
exit 1
}
# Create new beta tag
# Create new beta branch/tag
git tag ${{ steps.list-branches.outputs.new_beta_tag }}
# Push the changes and tag to the beta branch
# Push the changes and tag to the beta branch using PAT
git push origin ${{ steps.list-branches.outputs.beta }}
git push origin ${{ steps.list-branches.outputs.new_beta_tag }}
# Checkout the stable branch
# Reset and prepare the stable branch
git checkout ${{ steps.list-branches.outputs.stable }}
echo "Last 5 commits on stable branch:"
git log -n 5 --pretty=format:"%H"
echo "" # Newline for formatting
# Cherry-pick the merge commit from the merged PR
git cherry-pick -m 1 ${{ github.event.pull_request.merge_commit_sha }} || {
echo "Cherry-pick to stable failed due to conflicts."
exit 1
}
# Create new stable tag
# Create new stable branch/tag
git tag ${{ steps.list-branches.outputs.new_stable_tag }}
# Push the changes and tag to the stable branch
# Push the changes and tag to the stable branch using PAT
git push origin ${{ steps.list-branches.outputs.stable }}
git push origin ${{ steps.list-branches.outputs.new_stable_tag }}

225
.github/workflows/pr-chromatic-tests.yml vendored Normal file
View File

@@ -0,0 +1,225 @@
name: Run Chromatic Tests
concurrency:
group: Run-Chromatic-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
cancel-in-progress: true
on: push
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
jobs:
playwright-tests:
name: Playwright Tests
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
cache: 'pip'
cache-dependency-path: |
backend/requirements/default.txt
backend/requirements/dev.txt
backend/requirements/model_server.txt
- run: |
python -m pip install --upgrade pip
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
- name: Setup node
uses: actions/setup-node@v4
with:
node-version: 22
- name: Install node dependencies
working-directory: ./web
run: npm ci
- name: Install playwright browsers
working-directory: ./web
run: npx playwright install --with-deps
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
# tag every docker image with "test" so that we can spin up the correct set
# of images during testing
# we use the runs-on cache for docker builds
# in conjunction with runs-on runners, it has better speed and unlimited caching
# https://runs-on.com/caching/s3-cache-for-github-actions/
# https://runs-on.com/caching/docker/
# https://github.com/moby/buildkit#s3-cache-experimental
# images are built and run locally for testing purposes. Not pushed.
- name: Build Web Docker image
uses: ./.github/actions/custom-build-and-push
with:
context: ./web
file: ./web/Dockerfile
platforms: linux/amd64
tags: danswer/danswer-web-server:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/web-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/web-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Build Backend Docker image
uses: ./.github/actions/custom-build-and-push
with:
context: ./backend
file: ./backend/Dockerfile
platforms: linux/amd64
tags: danswer/danswer-backend:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Build Model Server Docker image
uses: ./.github/actions/custom-build-and-push
with:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64
tags: danswer/danswer-model-server:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Start Docker containers
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
AUTH_TYPE=basic \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
docker compose -f docker-compose.dev.yml -p danswer-stack up -d
id: start_docker
- name: Wait for service to be ready
run: |
echo "Starting wait-for-service script..."
docker logs -f danswer-stack-api_server-1 &
start_time=$(date +%s)
timeout=300 # 5 minutes in seconds
while true; do
current_time=$(date +%s)
elapsed_time=$((current_time - start_time))
if [ $elapsed_time -ge $timeout ]; then
echo "Timeout reached. Service did not become ready in 5 minutes."
exit 1
fi
# Use curl with error handling to ignore specific exit code 56
response=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8080/health || echo "curl_error")
if [ "$response" = "200" ]; then
echo "Service is ready!"
break
elif [ "$response" = "curl_error" ]; then
echo "Curl encountered an error, possibly exit code 56. Continuing to retry..."
else
echo "Service not ready yet (HTTP status $response). Retrying in 5 seconds..."
fi
sleep 5
done
echo "Finished waiting for service."
- name: Run pytest playwright test init
working-directory: ./backend
env:
PYTEST_IGNORE_SKIP: true
run: pytest -s tests/integration/tests/playwright/test_playwright.py
- name: Run Playwright tests
working-directory: ./web
run: npx playwright test
- uses: actions/upload-artifact@v4
if: always()
with:
# Chromatic automatically defaults to the test-results directory.
# Replace with the path to your custom directory and adjust the CHROMATIC_ARCHIVE_LOCATION environment variable accordingly.
name: test-results
path: ./web/test-results
retention-days: 30
# save before stopping the containers so the logs can be captured
- name: Save Docker logs
if: success() || failure()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
mv docker-compose.log ${{ github.workspace }}/docker-compose.log
- name: Upload logs
if: success() || failure()
uses: actions/upload-artifact@v4
with:
name: docker-logs
path: ${{ github.workspace }}/docker-compose.log
- name: Stop Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
chromatic-tests:
name: Chromatic Tests
needs: playwright-tests
runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Setup node
uses: actions/setup-node@v4
with:
node-version: 22
- name: Install node dependencies
working-directory: ./web
run: npm ci
- name: Download Playwright test results
uses: actions/download-artifact@v4
with:
name: test-results
path: ./web/test-results
- name: Run Chromatic
uses: chromaui/action@latest
with:
playwright: true
projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
workingDir: ./web
env:
CHROMATIC_ARCHIVE_LOCATION: ./test-results

View File

@@ -0,0 +1,72 @@
name: Helm - Lint and Test Charts
on:
merge_group:
pull_request:
branches: [ main ]
workflow_dispatch: # Allows manual triggering
jobs:
helm-chart-check:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,hdd=256,"run-id=${{ github.run_id }}"]
# fetch-depth 0 is required for helm/chart-testing-action
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Helm
uses: azure/setup-helm@v4.2.0
with:
version: v3.14.4
- name: Set up chart-testing
uses: helm/chart-testing-action@v2.6.1
# even though we specify chart-dirs in ct.yaml, it isn't used by ct for the list-changed command...
- name: Run chart-testing (list-changed)
id: list-changed
run: |
echo "default_branch: ${{ github.event.repository.default_branch }}"
changed=$(ct list-changed --remote origin --target-branch ${{ github.event.repository.default_branch }} --chart-dirs deployment/helm/charts)
echo "list-changed output: $changed"
if [[ -n "$changed" ]]; then
echo "changed=true" >> "$GITHUB_OUTPUT"
fi
# rkuo: I don't think we need python?
# - name: Set up Python
# uses: actions/setup-python@v5
# with:
# python-version: '3.11'
# cache: 'pip'
# cache-dependency-path: |
# backend/requirements/default.txt
# backend/requirements/dev.txt
# backend/requirements/model_server.txt
# - run: |
# python -m pip install --upgrade pip
# pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
# lint all charts if any changes were detected
- name: Run chart-testing (lint)
if: steps.list-changed.outputs.changed == 'true'
run: ct lint --config ct.yaml --all
# the following would lint only changed charts, but linting isn't expensive
# run: ct lint --config ct.yaml --target-branch ${{ github.event.repository.default_branch }}
- name: Create kind cluster
if: steps.list-changed.outputs.changed == 'true'
uses: helm/kind-action@v1.10.0
- name: Run chart-testing (install)
if: steps.list-changed.outputs.changed == 'true'
run: ct install --all --helm-extra-set-args="--set=nginx.enabled=false" --debug --config ct.yaml
# the following would install only changed charts, but we only have one chart so
# don't worry about that for now
# run: ct install --target-branch ${{ github.event.repository.default_branch }}

View File

@@ -1,68 +0,0 @@
# This workflow is intentionally disabled while we're still working on it
# It's close to ready, but a race condition needs to be fixed with
# API server and Vespa startup, and it needs to have a way to build/test against
# local containers
name: Helm - Lint and Test Charts
on:
merge_group:
pull_request:
branches: [ main ]
jobs:
lint-test:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,hdd=256,"run-id=${{ github.run_id }}"]
# fetch-depth 0 is required for helm/chart-testing-action
steps:
- name: Checkout code
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Set up Helm
uses: azure/setup-helm@v4.2.0
with:
version: v3.14.4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
cache: 'pip'
cache-dependency-path: |
backend/requirements/default.txt
backend/requirements/dev.txt
backend/requirements/model_server.txt
- run: |
python -m pip install --upgrade pip
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
- name: Set up chart-testing
uses: helm/chart-testing-action@v2.6.1
- name: Run chart-testing (list-changed)
id: list-changed
run: |
changed=$(ct list-changed --target-branch ${{ github.event.repository.default_branch }})
if [[ -n "$changed" ]]; then
echo "changed=true" >> "$GITHUB_OUTPUT"
fi
- name: Run chart-testing (lint)
# if: steps.list-changed.outputs.changed == 'true'
run: ct lint --all --config ct.yaml --target-branch ${{ github.event.repository.default_branch }}
- name: Create kind cluster
# if: steps.list-changed.outputs.changed == 'true'
uses: helm/kind-action@v1.10.0
- name: Run chart-testing (install)
# if: steps.list-changed.outputs.changed == 'true'
run: ct install --all --config ct.yaml
# run: ct install --target-branch ${{ github.event.repository.default_branch }}

View File

@@ -13,7 +13,10 @@ on:
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
CONFLUENCE_USER_NAME: ${{ secrets.CONFLUENCE_USER_NAME }}
CONFLUENCE_ACCESS_TOKEN: ${{ secrets.CONFLUENCE_ACCESS_TOKEN }}
jobs:
integration-tests:
# See https://runs-on.com/runners/linux/
@@ -72,7 +75,7 @@ jobs:
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Build integration test Docker image
uses: ./.github/actions/custom-build-and-push
with:
@@ -85,7 +88,58 @@ jobs:
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Start Docker containers
# Start containers for multi-tenant tests
- name: Start Docker containers for multi-tenant tests
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
MULTI_TENANT=true \
AUTH_TYPE=basic \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
docker compose -f docker-compose.dev.yml -p danswer-stack up -d
id: start_docker_multi_tenant
# In practice, `cloud` Auth type would require OAUTH credentials to be set.
- name: Run Multi-Tenant Integration Tests
run: |
echo "Running integration tests..."
docker run --rm --network danswer-stack_default \
--name test-runner \
-e POSTGRES_HOST=relational_db \
-e POSTGRES_USER=postgres \
-e POSTGRES_PASSWORD=password \
-e POSTGRES_DB=postgres \
-e VESPA_HOST=index \
-e REDIS_HOST=cache \
-e API_SERVER_HOST=api_server \
-e OPENAI_API_KEY=${OPENAI_API_KEY} \
-e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
-e TEST_WEB_HOSTNAME=test-runner \
-e AUTH_TYPE=cloud \
-e MULTI_TENANT=true \
danswer/danswer-integration:test \
/app/tests/integration/multitenant_tests
continue-on-error: true
id: run_multitenant_tests
- name: Check multi-tenant test results
run: |
if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
echo "Integration tests failed. Exiting with error."
exit 1
else
echo "All integration tests passed successfully."
fi
- name: Stop multi-tenant Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
- name: Start Docker containers
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
@@ -130,7 +184,7 @@ jobs:
done
echo "Finished waiting for service."
- name: Run integration tests
- name: Run Standard Integration Tests
run: |
echo "Running integration tests..."
docker run --rm --network danswer-stack_default \
@@ -144,8 +198,13 @@ jobs:
-e API_SERVER_HOST=api_server \
-e OPENAI_API_KEY=${OPENAI_API_KEY} \
-e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
-e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
-e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
-e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
-e TEST_WEB_HOSTNAME=test-runner \
danswer/danswer-integration:test
danswer/danswer-integration:test \
/app/tests/integration/tests \
/app/tests/integration/connector_job_tests
continue-on-error: true
id: run_tests
@@ -158,12 +217,18 @@ jobs:
echo "All integration tests passed successfully."
fi
# save before stopping the containers so the logs can be captured
- name: Save Docker logs
if: success() || failure()
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
mv docker-compose.log ${{ github.workspace }}/docker-compose.log
- name: Stop Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
- name: Upload logs
if: success() || failure()

View File

@@ -18,6 +18,14 @@ env:
# Jira
JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}
# Google
GOOGLE_DRIVE_SERVICE_ACCOUNT_JSON_STR: ${{ secrets.GOOGLE_DRIVE_SERVICE_ACCOUNT_JSON_STR }}
GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR_TEST_USER_1: ${{ secrets.GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR_TEST_USER_1 }}
GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR: ${{ secrets.GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR }}
GOOGLE_GMAIL_SERVICE_ACCOUNT_JSON_STR: ${{ secrets.GOOGLE_GMAIL_SERVICE_ACCOUNT_JSON_STR }}
GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR: ${{ secrets.GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR }}
# Slab
SLAB_BOT_TOKEN: ${{ secrets.SLAB_BOT_TOKEN }}
jobs:
connectors-check:

View File

@@ -15,7 +15,7 @@ env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
jobs:
connectors-check:
model-check:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]

1
.gitignore vendored
View File

@@ -7,3 +7,4 @@
.vscode/
*.sw?
/backend/tests/regression/answer_quality/search_test_config.yaml
/web/test-results/

View File

@@ -203,7 +203,7 @@
"--loglevel=INFO",
"--hostname=light@%n",
"-Q",
"vespa_metadata_sync,connector_deletion",
"vespa_metadata_sync,connector_deletion,doc_permissions_upsert",
],
"presentation": {
"group": "2",
@@ -232,7 +232,7 @@
"--loglevel=INFO",
"--hostname=heavy@%n",
"-Q",
"connector_pruning",
"connector_pruning,connector_doc_permissions_sync,connector_external_group_sync",
],
"presentation": {
"group": "2",

View File

@@ -32,7 +32,7 @@ To contribute to this project, please follow the
When opening a pull request, mention related issues and feel free to tag relevant maintainers.
Before creating a pull request please make sure that the new changes conform to the formatting and linting requirements.
See the [Formatting and Linting](#-formatting-and-linting) section for how to run these checks locally.
See the [Formatting and Linting](#formatting-and-linting) section for how to run these checks locally.
### Getting Help 🙋

View File

@@ -1,4 +1,5 @@
<!-- DANSWER_METADATA={"link": "https://github.com/danswer-ai/danswer/blob/main/README.md"} -->
<a name="readme-top"></a>
<h2 align="center">
<a href="https://www.danswer.ai/"> <img width="50%" src="https://github.com/danswer-owners/danswer/blob/1fabd9372d66cd54238847197c33f091a724803b/DanswerWithName.png?raw=true)" /></a>
@@ -11,7 +12,7 @@
<a href="https://docs.danswer.dev/" target="_blank">
<img src="https://img.shields.io/badge/docs-view-blue" alt="Documentation">
</a>
<a href="https://join.slack.com/t/danswer/shared_invite/zt-2lcmqw703-071hBuZBfNEOGUsLa5PXvQ" target="_blank">
<a href="https://join.slack.com/t/danswer/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA" target="_blank">
<img src="https://img.shields.io/badge/slack-join-blue.svg?logo=slack" alt="Slack">
</a>
<a href="https://discord.gg/TDJ59cGV2X" target="_blank">
@@ -127,3 +128,19 @@ To try the Danswer Enterprise Edition:
## 💡 Contributing
Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.
## ⭐Star History
[![Star History Chart](https://api.star-history.com/svg?repos=danswer-ai/danswer&type=Date)](https://star-history.com/#danswer-ai/danswer&Date)
## ✨Contributors
<a href="https://github.com/danswer-ai/danswer/graphs/contributors">
<img alt="contributors" src="https://contrib.rocks/image?repo=danswer-ai/danswer"/>
</a>
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
↑ Back to Top ↑
</a>
</p>

View File

@@ -12,7 +12,6 @@ ARG DANSWER_VERSION=0.8-dev
ENV DANSWER_VERSION=${DANSWER_VERSION} \
DANSWER_RUNNING_IN_DOCKER="true"
ARG CA_CERT_CONTENT=""
RUN echo "DANSWER_VERSION: ${DANSWER_VERSION}"
# Install system dependencies
@@ -39,15 +38,6 @@ RUN apt-get update && \
apt-get clean
# Conditionally write the CA certificate and update certificates
RUN if [ -n "$CA_CERT_CONTENT" ]; then \
echo "Adding custom CA certificate"; \
echo "$CA_CERT_CONTENT" > /usr/local/share/ca-certificates/my-ca.crt && \
chmod 644 /usr/local/share/ca-certificates/my-ca.crt && \
update-ca-certificates; \
else \
echo "No custom CA certificate provided"; \
fi
# Install Python dependencies
# Remove py which is pulled in by retry, py is not needed and is a CVE
@@ -83,11 +73,11 @@ RUN apt-get update && \
rm -rf /var/lib/apt/lists/* && \
rm -f /usr/local/lib/python3.11/site-packages/tornado/test/test.key
# Pre-downloading models for setups with limited egress
RUN python -c "from tokenizers import Tokenizer; \
Tokenizer.from_pretrained('nomic-ai/nomic-embed-text-v1')"
# Pre-downloading NLTK for setups with limited egress
RUN python -c "import nltk; \
nltk.download('stopwords', quiet=True); \

View File

@@ -1,5 +1,5 @@
from sqlalchemy.engine.base import Connection
from typing import Any
from typing import Literal
import asyncio
from logging.config import fileConfig
import logging
@@ -8,8 +8,9 @@ from alembic import context
from sqlalchemy import pool
from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.sql import text
from sqlalchemy.sql.schema import SchemaItem
from danswer.configs.app_configs import MULTI_TENANT
from shared_configs.configs import MULTI_TENANT
from danswer.db.engine import build_connection_string
from danswer.db.models import Base
from celery.backends.database.session import ResultModelBase # type: ignore
@@ -35,7 +36,18 @@ logger = logging.getLogger(__name__)
def include_object(
object: Any, name: str, type_: str, reflected: bool, compare_to: Any
object: SchemaItem,
name: str | None,
type_: Literal[
"schema",
"table",
"column",
"index",
"unique_constraint",
"foreign_key_constraint",
],
reflected: bool,
compare_to: SchemaItem | None,
) -> bool:
"""
Determines whether a database object should be included in migrations.

View File

@@ -0,0 +1,59 @@
"""display custom llm models
Revision ID: 177de57c21c9
Revises: 4ee1287bd26a
Create Date: 2024-11-21 11:49:04.488677
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
from sqlalchemy import and_
revision = "177de57c21c9"
down_revision = "4ee1287bd26a"
branch_labels = None
depends_on = None
depends_on = None
def upgrade() -> None:
conn = op.get_bind()
llm_provider = sa.table(
"llm_provider",
sa.column("id", sa.Integer),
sa.column("provider", sa.String),
sa.column("model_names", postgresql.ARRAY(sa.String)),
sa.column("display_model_names", postgresql.ARRAY(sa.String)),
)
excluded_providers = ["openai", "bedrock", "anthropic", "azure"]
providers_to_update = sa.select(
llm_provider.c.id,
llm_provider.c.model_names,
llm_provider.c.display_model_names,
).where(
and_(
~llm_provider.c.provider.in_(excluded_providers),
llm_provider.c.model_names.isnot(None),
)
)
results = conn.execute(providers_to_update).fetchall()
for provider_id, model_names, display_model_names in results:
if display_model_names is None:
display_model_names = []
combined_model_names = list(set(display_model_names + model_names))
update_stmt = (
llm_provider.update()
.where(llm_provider.c.id == provider_id)
.values(display_model_names=combined_model_names)
)
conn.execute(update_stmt)
def downgrade() -> None:
pass

View File

@@ -0,0 +1,68 @@
"""default chosen assistants to none
Revision ID: 26b931506ecb
Revises: 2daa494a0851
Create Date: 2024-11-12 13:23:29.858995
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "26b931506ecb"
down_revision = "2daa494a0851"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"user", sa.Column("chosen_assistants_new", postgresql.JSONB(), nullable=True)
)
op.execute(
"""
UPDATE "user"
SET chosen_assistants_new =
CASE
WHEN chosen_assistants = '[-2, -1, 0]' THEN NULL
ELSE chosen_assistants
END
"""
)
op.drop_column("user", "chosen_assistants")
op.alter_column(
"user", "chosen_assistants_new", new_column_name="chosen_assistants"
)
def downgrade() -> None:
op.add_column(
"user",
sa.Column(
"chosen_assistants_old",
postgresql.JSONB(),
nullable=False,
server_default="[-2, -1, 0]",
),
)
op.execute(
"""
UPDATE "user"
SET chosen_assistants_old =
CASE
WHEN chosen_assistants IS NULL THEN '[-2, -1, 0]'::jsonb
ELSE chosen_assistants
END
"""
)
op.drop_column("user", "chosen_assistants")
op.alter_column(
"user", "chosen_assistants_old", new_column_name="chosen_assistants"
)

View File

@@ -0,0 +1,30 @@
"""add-group-sync-time
Revision ID: 2daa494a0851
Revises: c0fd6e4da83a
Create Date: 2024-11-11 10:57:22.991157
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "2daa494a0851"
down_revision = "c0fd6e4da83a"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"connector_credential_pair",
sa.Column(
"last_time_external_group_sync",
sa.DateTime(timezone=True),
nullable=True,
),
)
def downgrade() -> None:
op.drop_column("connector_credential_pair", "last_time_external_group_sync")

View File

@@ -0,0 +1,50 @@
"""single tool call per message
Revision ID: 33cb72ea4d80
Revises: 5b29123cd710
Create Date: 2024-11-01 12:51:01.535003
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "33cb72ea4d80"
down_revision = "5b29123cd710"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Step 1: Delete extraneous ToolCall entries
# Keep only the ToolCall with the smallest 'id' for each 'message_id'
op.execute(
sa.text(
"""
DELETE FROM tool_call
WHERE id NOT IN (
SELECT MIN(id)
FROM tool_call
WHERE message_id IS NOT NULL
GROUP BY message_id
);
"""
)
)
# Step 2: Add a unique constraint on message_id
op.create_unique_constraint(
constraint_name="uq_tool_call_message_id",
table_name="tool_call",
columns=["message_id"],
)
def downgrade() -> None:
# Step 1: Drop the unique constraint on message_id
op.drop_constraint(
constraint_name="uq_tool_call_message_id",
table_name="tool_call",
type_="unique",
)

View File

@@ -0,0 +1,45 @@
"""add persona categories
Revision ID: 47e5bef3a1d7
Revises: dfbe9e93d3c7
Create Date: 2024-11-05 18:55:02.221064
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "47e5bef3a1d7"
down_revision = "dfbe9e93d3c7"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Create the persona_category table
op.create_table(
"persona_category",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("name", sa.String(), nullable=False),
sa.Column("description", sa.String(), nullable=True),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("name"),
)
# Add category_id to persona table
op.add_column("persona", sa.Column("category_id", sa.Integer(), nullable=True))
op.create_foreign_key(
"fk_persona_category",
"persona",
"persona_category",
["category_id"],
["id"],
ondelete="SET NULL",
)
def downgrade() -> None:
op.drop_constraint("fk_persona_category", "persona", type_="foreignkey")
op.drop_column("persona", "category_id")
op.drop_table("persona_category")

View File

@@ -0,0 +1,280 @@
"""add_multiple_slack_bot_support
Revision ID: 4ee1287bd26a
Revises: 47e5bef3a1d7
Create Date: 2024-11-06 13:15:53.302644
"""
import logging
from typing import cast
from alembic import op
import sqlalchemy as sa
from sqlalchemy.orm import Session
from danswer.key_value_store.factory import get_kv_store
from danswer.db.models import SlackBot
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "4ee1287bd26a"
down_revision = "47e5bef3a1d7"
branch_labels: None = None
depends_on: None = None
# Configure logging
logger = logging.getLogger("alembic.runtime.migration")
logger.setLevel(logging.INFO)
def upgrade() -> None:
logger.info(f"{revision}: create_table: slack_bot")
# Create new slack_bot table
op.create_table(
"slack_bot",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("name", sa.String(), nullable=False),
sa.Column("enabled", sa.Boolean(), nullable=False, server_default="true"),
sa.Column("bot_token", sa.LargeBinary(), nullable=False),
sa.Column("app_token", sa.LargeBinary(), nullable=False),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("bot_token"),
sa.UniqueConstraint("app_token"),
)
# # Create new slack_channel_config table
op.create_table(
"slack_channel_config",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("slack_bot_id", sa.Integer(), nullable=True),
sa.Column("persona_id", sa.Integer(), nullable=True),
sa.Column("channel_config", postgresql.JSONB(), nullable=False),
sa.Column("response_type", sa.String(), nullable=False),
sa.Column(
"enable_auto_filters", sa.Boolean(), nullable=False, server_default="false"
),
sa.ForeignKeyConstraint(
["slack_bot_id"],
["slack_bot.id"],
),
sa.ForeignKeyConstraint(
["persona_id"],
["persona.id"],
),
sa.PrimaryKeyConstraint("id"),
)
# Handle existing Slack bot tokens first
logger.info(f"{revision}: Checking for existing Slack bot.")
bot_token = None
app_token = None
first_row_id = None
try:
tokens = cast(dict, get_kv_store().load("slack_bot_tokens_config_key"))
except Exception:
logger.warning("No existing Slack bot tokens found.")
tokens = {}
bot_token = tokens.get("bot_token")
app_token = tokens.get("app_token")
if bot_token and app_token:
logger.info(f"{revision}: Found bot and app tokens.")
session = Session(bind=op.get_bind())
new_slack_bot = SlackBot(
name="Slack Bot (Migrated)",
enabled=True,
bot_token=bot_token,
app_token=app_token,
)
session.add(new_slack_bot)
session.commit()
first_row_id = new_slack_bot.id
# Create a default bot if none exists
# This is in case there are no slack tokens but there are channels configured
op.execute(
sa.text(
"""
INSERT INTO slack_bot (name, enabled, bot_token, app_token)
SELECT 'Default Bot', true, '', ''
WHERE NOT EXISTS (SELECT 1 FROM slack_bot)
RETURNING id;
"""
)
)
# Get the bot ID to use (either from existing migration or newly created)
bot_id_query = sa.text(
"""
SELECT COALESCE(
:first_row_id,
(SELECT id FROM slack_bot ORDER BY id ASC LIMIT 1)
) as bot_id;
"""
)
result = op.get_bind().execute(bot_id_query, {"first_row_id": first_row_id})
bot_id = result.scalar()
# CTE (Common Table Expression) that transforms the old slack_bot_config table data
# This splits up the channel_names into their own rows
channel_names_cte = """
WITH channel_names AS (
SELECT
sbc.id as config_id,
sbc.persona_id,
sbc.response_type,
sbc.enable_auto_filters,
jsonb_array_elements_text(sbc.channel_config->'channel_names') as channel_name,
sbc.channel_config->>'respond_tag_only' as respond_tag_only,
sbc.channel_config->>'respond_to_bots' as respond_to_bots,
sbc.channel_config->'respond_member_group_list' as respond_member_group_list,
sbc.channel_config->'answer_filters' as answer_filters,
sbc.channel_config->'follow_up_tags' as follow_up_tags
FROM slack_bot_config sbc
)
"""
# Insert the channel names into the new slack_channel_config table
insert_statement = """
INSERT INTO slack_channel_config (
slack_bot_id,
persona_id,
channel_config,
response_type,
enable_auto_filters
)
SELECT
:bot_id,
channel_name.persona_id,
jsonb_build_object(
'channel_name', channel_name.channel_name,
'respond_tag_only',
COALESCE((channel_name.respond_tag_only)::boolean, false),
'respond_to_bots',
COALESCE((channel_name.respond_to_bots)::boolean, false),
'respond_member_group_list',
COALESCE(channel_name.respond_member_group_list, '[]'::jsonb),
'answer_filters',
COALESCE(channel_name.answer_filters, '[]'::jsonb),
'follow_up_tags',
COALESCE(channel_name.follow_up_tags, '[]'::jsonb)
),
channel_name.response_type,
channel_name.enable_auto_filters
FROM channel_names channel_name;
"""
op.execute(sa.text(channel_names_cte + insert_statement).bindparams(bot_id=bot_id))
# Clean up old tokens if they existed
try:
if bot_token and app_token:
logger.info(f"{revision}: Removing old bot and app tokens.")
get_kv_store().delete("slack_bot_tokens_config_key")
except Exception:
logger.warning("tried to delete tokens in dynamic config but failed")
# Rename the table
op.rename_table(
"slack_bot_config__standard_answer_category",
"slack_channel_config__standard_answer_category",
)
# Rename the column
op.alter_column(
"slack_channel_config__standard_answer_category",
"slack_bot_config_id",
new_column_name="slack_channel_config_id",
)
# Drop the table with CASCADE to handle dependent objects
op.execute("DROP TABLE slack_bot_config CASCADE")
logger.info(f"{revision}: Migration complete.")
def downgrade() -> None:
# Recreate the old slack_bot_config table
op.create_table(
"slack_bot_config",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("persona_id", sa.Integer(), nullable=True),
sa.Column("channel_config", postgresql.JSONB(), nullable=False),
sa.Column("response_type", sa.String(), nullable=False),
sa.Column("enable_auto_filters", sa.Boolean(), nullable=False),
sa.ForeignKeyConstraint(
["persona_id"],
["persona.id"],
),
sa.PrimaryKeyConstraint("id"),
)
# Migrate data back to the old format
# Group by persona_id to combine channel names back into arrays
op.execute(
sa.text(
"""
INSERT INTO slack_bot_config (
persona_id,
channel_config,
response_type,
enable_auto_filters
)
SELECT DISTINCT ON (persona_id)
persona_id,
jsonb_build_object(
'channel_names', (
SELECT jsonb_agg(c.channel_config->>'channel_name')
FROM slack_channel_config c
WHERE c.persona_id = scc.persona_id
),
'respond_tag_only', (channel_config->>'respond_tag_only')::boolean,
'respond_to_bots', (channel_config->>'respond_to_bots')::boolean,
'respond_member_group_list', channel_config->'respond_member_group_list',
'answer_filters', channel_config->'answer_filters',
'follow_up_tags', channel_config->'follow_up_tags'
),
response_type,
enable_auto_filters
FROM slack_channel_config scc
WHERE persona_id IS NOT NULL;
"""
)
)
# Rename the table back
op.rename_table(
"slack_channel_config__standard_answer_category",
"slack_bot_config__standard_answer_category",
)
# Rename the column back
op.alter_column(
"slack_bot_config__standard_answer_category",
"slack_channel_config_id",
new_column_name="slack_bot_config_id",
)
# Try to save the first bot's tokens back to KV store
try:
first_bot = (
op.get_bind()
.execute(
sa.text(
"SELECT bot_token, app_token FROM slack_bot ORDER BY id LIMIT 1"
)
)
.first()
)
if first_bot and first_bot.bot_token and first_bot.app_token:
tokens = {
"bot_token": first_bot.bot_token,
"app_token": first_bot.app_token,
}
get_kv_store().store("slack_bot_tokens_config_key", tokens)
except Exception:
logger.warning("Failed to save tokens back to KV store")
# Drop the new tables in reverse order
op.drop_table("slack_channel_config")
op.drop_table("slack_bot")

View File

@@ -0,0 +1,70 @@
"""nullable search settings for historic index attempts
Revision ID: 5b29123cd710
Revises: 949b4a92a401
Create Date: 2024-10-30 19:37:59.630704
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "5b29123cd710"
down_revision = "949b4a92a401"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Drop the existing foreign key constraint
op.drop_constraint(
"fk_index_attempt_search_settings", "index_attempt", type_="foreignkey"
)
# Modify the column to be nullable
op.alter_column(
"index_attempt", "search_settings_id", existing_type=sa.INTEGER(), nullable=True
)
# Add back the foreign key with ON DELETE SET NULL
op.create_foreign_key(
"fk_index_attempt_search_settings",
"index_attempt",
"search_settings",
["search_settings_id"],
["id"],
ondelete="SET NULL",
)
def downgrade() -> None:
# Warning: This will delete all index attempts that don't have search settings
op.execute(
"""
DELETE FROM index_attempt
WHERE search_settings_id IS NULL
"""
)
# Drop foreign key constraint
op.drop_constraint(
"fk_index_attempt_search_settings", "index_attempt", type_="foreignkey"
)
# Modify the column to be not nullable
op.alter_column(
"index_attempt",
"search_settings_id",
existing_type=sa.INTEGER(),
nullable=False,
)
# Add back the foreign key without ON DELETE SET NULL
op.create_foreign_key(
"fk_index_attempt_search_settings",
"index_attempt",
"search_settings",
["search_settings_id"],
["id"],
)

View File

@@ -0,0 +1,45 @@
"""remove default bot
Revision ID: 6d562f86c78b
Revises: 177de57c21c9
Create Date: 2024-11-22 11:51:29.331336
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "6d562f86c78b"
down_revision = "177de57c21c9"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
sa.text(
"""
DELETE FROM slack_bot
WHERE name = 'Default Bot'
AND bot_token = ''
AND app_token = ''
AND NOT EXISTS (
SELECT 1 FROM slack_channel_config
WHERE slack_channel_config.slack_bot_id = slack_bot.id
)
"""
)
)
def downgrade() -> None:
op.execute(
sa.text(
"""
INSERT INTO slack_bot (name, enabled, bot_token, app_token)
SELECT 'Default Bot', true, '', ''
WHERE NOT EXISTS (SELECT 1 FROM slack_bot)
RETURNING id;
"""
)
)

View File

@@ -9,8 +9,8 @@ from alembic import op
import sqlalchemy as sa
from danswer.db.models import IndexModelStatus
from danswer.search.enums import RecencyBiasSetting
from danswer.search.enums import SearchType
from danswer.context.search.enums import RecencyBiasSetting
from danswer.context.search.enums import SearchType
# revision identifiers, used by Alembic.
revision = "776b3bbe9092"

View File

@@ -0,0 +1,35 @@
"""add web ui option to slack config
Revision ID: 93560ba1b118
Revises: 6d562f86c78b
Create Date: 2024-11-24 06:36:17.490612
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "93560ba1b118"
down_revision = "6d562f86c78b"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add show_continue_in_web_ui with default False to all existing channel_configs
op.execute(
"""
UPDATE slack_channel_config
SET channel_config = channel_config || '{"show_continue_in_web_ui": false}'::jsonb
WHERE NOT channel_config ? 'show_continue_in_web_ui'
"""
)
def downgrade() -> None:
# Remove show_continue_in_web_ui from all channel_configs
op.execute(
"""
UPDATE slack_channel_config
SET channel_config = channel_config - 'show_continue_in_web_ui'
"""
)

View File

@@ -0,0 +1,72 @@
"""remove rt
Revision ID: 949b4a92a401
Revises: 1b10e1fda030
Create Date: 2024-10-26 13:06:06.937969
"""
from alembic import op
from sqlalchemy.orm import Session
from sqlalchemy import text
# Import your models and constants
from danswer.db.models import (
Connector,
ConnectorCredentialPair,
Credential,
IndexAttempt,
)
# revision identifiers, used by Alembic.
revision = "949b4a92a401"
down_revision = "1b10e1fda030"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Deletes all RequestTracker connectors and associated data
bind = op.get_bind()
session = Session(bind=bind)
# Get connectors using raw SQL
result = bind.execute(
text("SELECT id FROM connector WHERE source = 'requesttracker'")
)
connector_ids = [row[0] for row in result]
if connector_ids:
cc_pairs_to_delete = (
session.query(ConnectorCredentialPair)
.filter(ConnectorCredentialPair.connector_id.in_(connector_ids))
.all()
)
cc_pair_ids = [cc_pair.id for cc_pair in cc_pairs_to_delete]
if cc_pair_ids:
session.query(IndexAttempt).filter(
IndexAttempt.connector_credential_pair_id.in_(cc_pair_ids)
).delete(synchronize_session=False)
session.query(ConnectorCredentialPair).filter(
ConnectorCredentialPair.id.in_(cc_pair_ids)
).delete(synchronize_session=False)
credential_ids = [cc_pair.credential_id for cc_pair in cc_pairs_to_delete]
if credential_ids:
session.query(Credential).filter(Credential.id.in_(credential_ids)).delete(
synchronize_session=False
)
session.query(Connector).filter(Connector.id.in_(connector_ids)).delete(
synchronize_session=False
)
session.commit()
def downgrade() -> None:
# No-op downgrade as we cannot restore deleted data
pass

View File

@@ -0,0 +1,30 @@
"""add creator to cc pair
Revision ID: 9cf5c00f72fe
Revises: 26b931506ecb
Create Date: 2024-11-12 15:16:42.682902
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "9cf5c00f72fe"
down_revision = "26b931506ecb"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"connector_credential_pair",
sa.Column(
"creator_id",
sa.UUID(as_uuid=True),
nullable=True,
),
)
def downgrade() -> None:
op.drop_column("connector_credential_pair", "creator_id")

View File

@@ -0,0 +1,36 @@
"""Combine Search and Chat
Revision ID: 9f696734098f
Revises: a8c2065484e6
Create Date: 2024-11-27 15:32:19.694972
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "9f696734098f"
down_revision = "a8c2065484e6"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.alter_column("chat_session", "description", nullable=True)
op.drop_column("chat_session", "one_shot")
op.drop_column("slack_channel_config", "response_type")
def downgrade() -> None:
op.execute("UPDATE chat_session SET description = '' WHERE description IS NULL")
op.alter_column("chat_session", "description", nullable=False)
op.add_column(
"chat_session",
sa.Column("one_shot", sa.Boolean(), nullable=False, server_default=sa.false()),
)
op.add_column(
"slack_channel_config",
sa.Column(
"response_type", sa.String(), nullable=False, server_default="citations"
),
)

View File

@@ -0,0 +1,27 @@
"""add auto scroll to user model
Revision ID: a8c2065484e6
Revises: abe7378b8217
Create Date: 2024-11-22 17:34:09.690295
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "a8c2065484e6"
down_revision = "abe7378b8217"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"user",
sa.Column("auto_scroll", sa.Boolean(), nullable=True, server_default=None),
)
def downgrade() -> None:
op.drop_column("user", "auto_scroll")

View File

@@ -0,0 +1,30 @@
"""add indexing trigger to cc_pair
Revision ID: abe7378b8217
Revises: 6d562f86c78b
Create Date: 2024-11-26 19:09:53.481171
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "abe7378b8217"
down_revision = "93560ba1b118"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"connector_credential_pair",
sa.Column(
"indexing_trigger",
sa.Enum("UPDATE", "REINDEX", name="indexingmode", native_enum=False),
nullable=True,
),
)
def downgrade() -> None:
op.drop_column("connector_credential_pair", "indexing_trigger")

View File

@@ -31,6 +31,12 @@ def upgrade() -> None:
def downgrade() -> None:
# First, update any null values to a default value
op.execute(
"UPDATE connector_credential_pair SET last_attempt_status = 'NOT_STARTED' WHERE last_attempt_status IS NULL"
)
# Then, make the column non-nullable
op.alter_column(
"connector_credential_pair",
"last_attempt_status",

View File

@@ -288,6 +288,15 @@ def upgrade() -> None:
def downgrade() -> None:
# NOTE: you will lose all chat history. This is to satisfy the non-nullable constraints
# below
op.execute("DELETE FROM chat_feedback")
op.execute("DELETE FROM chat_message__search_doc")
op.execute("DELETE FROM document_retrieval_feedback")
op.execute("DELETE FROM document_retrieval_feedback")
op.execute("DELETE FROM chat_message")
op.execute("DELETE FROM chat_session")
op.drop_constraint(
"chat_feedback__chat_message_fk", "chat_feedback", type_="foreignkey"
)

View File

@@ -0,0 +1,48 @@
"""remove description from starter messages
Revision ID: b72ed7a5db0e
Revises: 33cb72ea4d80
Create Date: 2024-11-03 15:55:28.944408
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "b72ed7a5db0e"
down_revision = "33cb72ea4d80"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
sa.text(
"""
UPDATE persona
SET starter_messages = (
SELECT jsonb_agg(elem - 'description')
FROM jsonb_array_elements(starter_messages) elem
)
WHERE starter_messages IS NOT NULL
AND jsonb_typeof(starter_messages) = 'array'
"""
)
)
def downgrade() -> None:
op.execute(
sa.text(
"""
UPDATE persona
SET starter_messages = (
SELECT jsonb_agg(elem || '{"description": ""}')
FROM jsonb_array_elements(starter_messages) elem
)
WHERE starter_messages IS NOT NULL
AND jsonb_typeof(starter_messages) = 'array'
"""
)
)

View File

@@ -0,0 +1,29 @@
"""add recent assistants
Revision ID: c0fd6e4da83a
Revises: b72ed7a5db0e
Create Date: 2024-11-03 17:28:54.916618
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "c0fd6e4da83a"
down_revision = "b72ed7a5db0e"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"user",
sa.Column(
"recent_assistants", postgresql.JSONB(), server_default="[]", nullable=False
),
)
def downgrade() -> None:
op.drop_column("user", "recent_assistants")

View File

@@ -23,6 +23,56 @@ def upgrade() -> None:
def downgrade() -> None:
# Delete chat messages and feedback first since they reference chat sessions
# Get chat messages from sessions with null persona_id
chat_messages_query = """
SELECT id
FROM chat_message
WHERE chat_session_id IN (
SELECT id
FROM chat_session
WHERE persona_id IS NULL
)
"""
# Delete dependent records first
op.execute(
f"""
DELETE FROM document_retrieval_feedback
WHERE chat_message_id IN (
{chat_messages_query}
)
"""
)
op.execute(
f"""
DELETE FROM chat_message__search_doc
WHERE chat_message_id IN (
{chat_messages_query}
)
"""
)
# Delete chat messages
op.execute(
"""
DELETE FROM chat_message
WHERE chat_session_id IN (
SELECT id
FROM chat_session
WHERE persona_id IS NULL
)
"""
)
# Now we can safely delete the chat sessions
op.execute(
"""
DELETE FROM chat_session
WHERE persona_id IS NULL
"""
)
op.alter_column(
"chat_session",
"persona_id",

View File

@@ -0,0 +1,42 @@
"""extended_role_for_non_web
Revision ID: dfbe9e93d3c7
Revises: 9cf5c00f72fe
Create Date: 2024-11-16 07:54:18.727906
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "dfbe9e93d3c7"
down_revision = "9cf5c00f72fe"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
"""
UPDATE "user"
SET role = 'EXT_PERM_USER'
WHERE has_web_login = false
"""
)
op.drop_column("user", "has_web_login")
def downgrade() -> None:
op.add_column(
"user",
sa.Column("has_web_login", sa.Boolean(), nullable=False, server_default="true"),
)
op.execute(
"""
UPDATE "user"
SET has_web_login = false,
role = 'BASIC'
WHERE role IN ('SLACK_USER', 'EXT_PERM_USER')
"""
)

View File

@@ -1,5 +1,6 @@
import asyncio
from logging.config import fileConfig
from typing import Literal
from sqlalchemy import pool
from sqlalchemy.engine import Connection
@@ -37,8 +38,15 @@ EXCLUDE_TABLES = {"kombu_queue", "kombu_message"}
def include_object(
object: SchemaItem,
name: str,
type_: str,
name: str | None,
type_: Literal[
"schema",
"table",
"column",
"index",
"unique_constraint",
"foreign_key_constraint",
],
reflected: bool,
compare_to: SchemaItem | None,
) -> bool:

View File

@@ -16,6 +16,46 @@ class ExternalAccess:
is_public: bool
@dataclass(frozen=True)
class DocExternalAccess:
"""
This is just a class to wrap the external access and the document ID
together. It's used for syncing document permissions to Redis.
"""
external_access: ExternalAccess
# The document ID
doc_id: str
def to_dict(self) -> dict:
return {
"external_access": {
"external_user_emails": list(self.external_access.external_user_emails),
"external_user_group_ids": list(
self.external_access.external_user_group_ids
),
"is_public": self.external_access.is_public,
},
"doc_id": self.doc_id,
}
@classmethod
def from_dict(cls, data: dict) -> "DocExternalAccess":
external_access = ExternalAccess(
external_user_emails=set(
data["external_access"].get("external_user_emails", [])
),
external_user_group_ids=set(
data["external_access"].get("external_user_group_ids", [])
),
is_public=data["external_access"]["is_public"],
)
return cls(
external_access=external_access,
doc_id=data["doc_id"],
)
@dataclass(frozen=True)
class DocumentAccess(ExternalAccess):
# User emails for Danswer users, None indicates admin

View File

@@ -0,0 +1,100 @@
from langgraph.graph import END
from langgraph.graph import START
from langgraph.graph import StateGraph
from danswer.agent_search.answer_query.nodes.answer_check import answer_check
from danswer.agent_search.answer_query.nodes.answer_generation import answer_generation
from danswer.agent_search.answer_query.nodes.format_answer import format_answer
from danswer.agent_search.answer_query.states import AnswerQueryInput
from danswer.agent_search.answer_query.states import AnswerQueryOutput
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.expanded_retrieval.graph_builder import (
expanded_retrieval_graph_builder,
)
def answer_query_graph_builder() -> StateGraph:
graph = StateGraph(
state_schema=AnswerQueryState,
input=AnswerQueryInput,
output=AnswerQueryOutput,
)
### Add nodes ###
expanded_retrieval = expanded_retrieval_graph_builder().compile()
graph.add_node(
node="expanded_retrieval_for_initial_decomp",
action=expanded_retrieval,
)
graph.add_node(
node="answer_check",
action=answer_check,
)
graph.add_node(
node="answer_generation",
action=answer_generation,
)
graph.add_node(
node="format_answer",
action=format_answer,
)
### Add edges ###
graph.add_edge(
start_key=START,
end_key="expanded_retrieval_for_initial_decomp",
)
graph.add_edge(
start_key="expanded_retrieval_for_initial_decomp",
end_key="answer_generation",
)
graph.add_edge(
start_key="answer_generation",
end_key="answer_check",
)
graph.add_edge(
start_key="answer_check",
end_key="format_answer",
)
graph.add_edge(
start_key="format_answer",
end_key=END,
)
return graph
if __name__ == "__main__":
from danswer.db.engine import get_session_context_manager
from danswer.llm.factory import get_default_llms
from danswer.context.search.models import SearchRequest
graph = answer_query_graph_builder()
compiled_graph = graph.compile()
primary_llm, fast_llm = get_default_llms()
search_request = SearchRequest(
query="Who made Excel and what other products did they make?",
)
with get_session_context_manager() as db_session:
inputs = AnswerQueryInput(
search_request=search_request,
primary_llm=primary_llm,
fast_llm=fast_llm,
db_session=db_session,
query_to_answer="Who made Excel?",
)
output = compiled_graph.invoke(
input=inputs,
# debug=True,
# subgraphs=True,
)
print(output)
# for namespace, chunk in compiled_graph.stream(
# input=inputs,
# # debug=True,
# subgraphs=True,
# ):
# print(namespace)
# print(chunk)

View File

@@ -0,0 +1,30 @@
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import QACheckOutput
from danswer.agent_search.shared_graph_utils.prompts import BASE_CHECK_PROMPT
def answer_check(state: AnswerQueryState) -> QACheckOutput:
msg = [
HumanMessage(
content=BASE_CHECK_PROMPT.format(
question=state["search_request"].query,
base_answer=state["answer"],
)
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
response_str = merge_message_runs(response, chunk_separator="")[0].content
return QACheckOutput(
answer_quality=response_str,
)

View File

@@ -0,0 +1,32 @@
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import QAGenerationOutput
from danswer.agent_search.shared_graph_utils.prompts import BASE_RAG_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
def answer_generation(state: AnswerQueryState) -> QAGenerationOutput:
query = state["query_to_answer"]
docs = state["reordered_documents"]
print(f"Number of verified retrieval docs: {len(docs)}")
msg = [
HumanMessage(
content=BASE_RAG_PROMPT.format(question=query, context=format_docs(docs))
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
answer_str = merge_message_runs(response, chunk_separator="")[0].content
return QAGenerationOutput(
answer=answer_str,
)

View File

@@ -0,0 +1,16 @@
from danswer.agent_search.answer_query.states import AnswerQueryOutput
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import SearchAnswerResults
def format_answer(state: AnswerQueryState) -> AnswerQueryOutput:
return AnswerQueryOutput(
decomp_answer_results=[
SearchAnswerResults(
query=state["query_to_answer"],
quality=state["answer_quality"],
answer=state["answer"],
documents=state["reordered_documents"],
)
],
)

View File

@@ -0,0 +1,45 @@
from typing import Annotated
from typing import TypedDict
from pydantic import BaseModel
from danswer.agent_search.core_state import PrimaryState
from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
from danswer.context.search.models import InferenceSection
class SearchAnswerResults(BaseModel):
query: str
answer: str
quality: str
documents: Annotated[list[InferenceSection], dedup_inference_sections]
class QACheckOutput(TypedDict, total=False):
answer_quality: str
class QAGenerationOutput(TypedDict, total=False):
answer: str
class ExpandedRetrievalOutput(TypedDict):
reordered_documents: Annotated[list[InferenceSection], dedup_inference_sections]
class AnswerQueryState(
PrimaryState,
QACheckOutput,
QAGenerationOutput,
ExpandedRetrievalOutput,
total=True,
):
query_to_answer: str
class AnswerQueryInput(PrimaryState, total=True):
query_to_answer: str
class AnswerQueryOutput(TypedDict):
decomp_answer_results: list[SearchAnswerResults]

View File

@@ -0,0 +1,15 @@
from typing import TypedDict
from sqlalchemy.orm import Session
from danswer.context.search.models import SearchRequest
from danswer.llm.interfaces import LLM
class PrimaryState(TypedDict, total=False):
search_request: SearchRequest
primary_llm: LLM
fast_llm: LLM
# a single session for the entire agent search
# is fine if we are only reading
db_session: Session

View File

@@ -0,0 +1,114 @@
from typing import Any
from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import COMBINED_CONTEXT
from danswer.agent_search.shared_graph_utils.prompts import MODIFIED_RAG_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
from danswer.agent_search.shared_graph_utils.utils import normalize_whitespace
# aggregate sub questions and answers
def deep_answer_generation(state: MainState) -> dict[str, Any]:
"""
Generate answer
Args:
state (messages): The current state
Returns:
dict: The updated state with re-phrased question
"""
print("---DEEP GENERATE---")
question = state["original_question"]
docs = state["deduped_retrieval_docs"]
deep_answer_context = state["core_answer_dynamic_context"]
print(f"Number of verified retrieval docs - deep: {len(docs)}")
combined_context = normalize_whitespace(
COMBINED_CONTEXT.format(
deep_answer_context=deep_answer_context, formated_docs=format_docs(docs)
)
)
msg = [
HumanMessage(
content=MODIFIED_RAG_PROMPT.format(
question=question, combined_context=combined_context
)
)
]
# Grader
model = state["fast_llm"]
response = model.invoke(msg)
return {
"deep_answer": response.content,
}
def final_stuff(state: MainState) -> dict[str, Any]:
"""
Invokes the agent model to generate a response based on the current state. Given
the question, it will decide to retrieve using the retriever tool, or simply end.
Args:
state (messages): The current state
Returns:
dict: The updated state with the agent response appended to messages
"""
print("---FINAL---")
messages = state["log_messages"]
time_ordered_messages = [x.pretty_repr() for x in messages]
time_ordered_messages.sort()
print("Message Log:")
print("\n".join(time_ordered_messages))
initial_sub_qas = state["initial_sub_qas"]
initial_sub_qa_list = []
for initial_sub_qa in initial_sub_qas:
if initial_sub_qa["sub_answer_check"] == "yes":
initial_sub_qa_list.append(
f' Question:\n {initial_sub_qa["sub_question"]}\n --\n Answer:\n {initial_sub_qa["sub_answer"]}\n -----'
)
initial_sub_qa_context = "\n".join(initial_sub_qa_list)
base_answer = state["base_answer"]
print(f"Final Base Answer:\n{base_answer}")
print("--------------------------------")
print(f"Initial Answered Sub Questions:\n{initial_sub_qa_context}")
print("--------------------------------")
if not state.get("deep_answer"):
print("No Deep Answer was required")
return {}
deep_answer = state["deep_answer"]
sub_qas = state["sub_qas"]
sub_qa_list = []
for sub_qa in sub_qas:
if sub_qa["sub_answer_check"] == "yes":
sub_qa_list.append(
f' Question:\n {sub_qa["sub_question"]}\n --\n Answer:\n {sub_qa["sub_answer"]}\n -----'
)
sub_qa_context = "\n".join(sub_qa_list)
print(f"Final Base Answer:\n{base_answer}")
print("--------------------------------")
print(f"Final Deep Answer:\n{deep_answer}")
print("--------------------------------")
print("Sub Questions and Answers:")
print(sub_qa_context)
return {}

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import json
import re
from datetime import datetime
from typing import Any
from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import DEEP_DECOMPOSE_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_entity_term_extraction
from danswer.agent_search.shared_graph_utils.utils import generate_log_message
def decompose(state: MainState) -> dict[str, Any]:
""" """
node_start_time = datetime.now()
question = state["original_question"]
base_answer = state["base_answer"]
# get the entity term extraction dict and properly format it
entity_term_extraction_dict = state["retrieved_entities_relationships"][
"retrieved_entities_relationships"
]
entity_term_extraction_str = format_entity_term_extraction(
entity_term_extraction_dict
)
initial_question_answers = state["initial_sub_qas"]
addressed_question_list = [
x["sub_question"]
for x in initial_question_answers
if x["sub_answer_check"] == "yes"
]
failed_question_list = [
x["sub_question"]
for x in initial_question_answers
if x["sub_answer_check"] == "no"
]
msg = [
HumanMessage(
content=DEEP_DECOMPOSE_PROMPT.format(
question=question,
entity_term_extraction_str=entity_term_extraction_str,
base_answer=base_answer,
answered_sub_questions="\n - ".join(addressed_question_list),
failed_sub_questions="\n - ".join(failed_question_list),
),
)
]
# Grader
model = state["fast_llm"]
response = model.invoke(msg)
cleaned_response = re.sub(r"```json\n|\n```", "", response.pretty_repr())
parsed_response = json.loads(cleaned_response)
sub_questions_dict = {}
for sub_question_nr, sub_question_dict in enumerate(
parsed_response["sub_questions"]
):
sub_question_dict["answered"] = False
sub_question_dict["verified"] = False
sub_questions_dict[sub_question_nr] = sub_question_dict
return {
"decomposed_sub_questions_dict": sub_questions_dict,
"log_messages": generate_log_message(
message="deep - decompose",
node_start_time=node_start_time,
graph_start_time=state["graph_start_time"],
),
}

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import json
import re
from typing import Any
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import ENTITY_TERM_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
def entity_term_extraction(state: MainState) -> dict[str, Any]:
"""Extract entities and terms from the question and context"""
question = state["original_question"]
docs = state["deduped_retrieval_docs"]
doc_context = format_docs(docs)
msg = [
HumanMessage(
content=ENTITY_TERM_PROMPT.format(question=question, context=doc_context),
)
]
fast_llm = state["fast_llm"]
# Grader
llm_response_list = list(
fast_llm.stream(
prompt=msg,
)
)
llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
cleaned_response = re.sub(r"```json\n|\n```", "", llm_response)
parsed_response = json.loads(cleaned_response)
return {
"retrieved_entities_relationships": parsed_response,
}

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from typing import Any
from danswer.agent_search.main.states import MainState
# aggregate sub questions and answers
def sub_qa_level_aggregator(state: MainState) -> dict[str, Any]:
sub_qas = state["sub_qas"]
dynamic_context_list = [
"Below you will find useful information to answer the original question:"
]
checked_sub_qas = []
for core_answer_sub_qa in sub_qas:
question = core_answer_sub_qa["sub_question"]
answer = core_answer_sub_qa["sub_answer"]
verified = core_answer_sub_qa["sub_answer_check"]
if verified == "yes":
dynamic_context_list.append(
f"Question:\n{question}\n\nAnswer:\n{answer}\n\n---\n\n"
)
checked_sub_qas.append({"sub_question": question, "sub_answer": answer})
dynamic_context = "\n".join(dynamic_context_list)
return {
"core_answer_dynamic_context": dynamic_context,
"checked_sub_qas": checked_sub_qas,
}

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from typing import Any
from danswer.agent_search.main.states import MainState
def sub_qa_manager(state: MainState) -> dict[str, Any]:
""" """
sub_questions_dict = state["decomposed_sub_questions_dict"]
sub_questions = {}
for sub_question_nr, sub_question_dict in sub_questions_dict.items():
sub_questions[sub_question_nr] = sub_question_dict["sub_question"]
return {
"sub_questions": sub_questions,
"num_new_question_iterations": 0,
}

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from collections.abc import Hashable
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from langgraph.types import Send
from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import RetrieveInput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
from danswer.agent_search.shared_graph_utils.prompts import REWRITE_PROMPT_MULTI
from danswer.llm.interfaces import LLM
def parallel_retrieval_edge(state: ExpandedRetrievalInput) -> list[Send | Hashable]:
print(f"parallel_retrieval_edge state: {state.keys()}")
# This should be better...
question = state.get("query_to_answer") or state["search_request"].query
llm: LLM = state["fast_llm"]
msg = [
HumanMessage(
content=REWRITE_PROMPT_MULTI.format(question=question),
)
]
llm_response_list = list(
llm.stream(
prompt=msg,
)
)
llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
print(f"llm_response: {llm_response}")
rewritten_queries = llm_response.split("\n")
print(f"rewritten_queries: {rewritten_queries}")
return [
Send(
"doc_retrieval",
RetrieveInput(query_to_retrieve=query, **state),
)
for query in rewritten_queries
]

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from langgraph.graph import END
from langgraph.graph import START
from langgraph.graph import StateGraph
from danswer.agent_search.expanded_retrieval.edges import parallel_retrieval_edge
from danswer.agent_search.expanded_retrieval.nodes.doc_reranking import doc_reranking
from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import doc_retrieval
from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
doc_verification,
)
from danswer.agent_search.expanded_retrieval.nodes.verification_kickoff import (
verification_kickoff,
)
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def expanded_retrieval_graph_builder() -> StateGraph:
graph = StateGraph(
state_schema=ExpandedRetrievalState,
input=ExpandedRetrievalInput,
output=ExpandedRetrievalOutput,
)
### Add nodes ###
graph.add_node(
node="doc_retrieval",
action=doc_retrieval,
)
graph.add_node(
node="verification_kickoff",
action=verification_kickoff,
)
graph.add_node(
node="doc_verification",
action=doc_verification,
)
graph.add_node(
node="doc_reranking",
action=doc_reranking,
)
### Add edges ###
graph.add_conditional_edges(
source=START,
path=parallel_retrieval_edge,
path_map=["doc_retrieval"],
)
graph.add_edge(
start_key="doc_retrieval",
end_key="verification_kickoff",
)
graph.add_edge(
start_key="doc_verification",
end_key="doc_reranking",
)
graph.add_edge(
start_key="doc_reranking",
end_key=END,
)
return graph
if __name__ == "__main__":
from danswer.db.engine import get_session_context_manager
from danswer.llm.factory import get_default_llms
from danswer.context.search.models import SearchRequest
graph = expanded_retrieval_graph_builder()
compiled_graph = graph.compile()
primary_llm, fast_llm = get_default_llms()
search_request = SearchRequest(
query="Who made Excel and what other products did they make?",
)
with get_session_context_manager() as db_session:
inputs = ExpandedRetrievalInput(
search_request=search_request,
primary_llm=primary_llm,
fast_llm=fast_llm,
db_session=db_session,
query_to_answer="Who made Excel?",
)
for thing in compiled_graph.stream(inputs, debug=True):
print(thing)

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from danswer.agent_search.expanded_retrieval.states import DocRerankingOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def doc_reranking(state: ExpandedRetrievalState) -> DocRerankingOutput:
print(f"doc_reranking state: {state.keys()}")
verified_documents = state["verified_documents"]
reranked_documents = verified_documents
return DocRerankingOutput(reranked_documents=reranked_documents)

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from danswer.agent_search.expanded_retrieval.states import DocRetrievalOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
from danswer.context.search.models import InferenceSection
from danswer.context.search.models import SearchRequest
from danswer.context.search.pipeline import SearchPipeline
from danswer.db.engine import get_session_context_manager
class RetrieveInput(ExpandedRetrievalState):
query_to_retrieve: str
def doc_retrieval(state: RetrieveInput) -> DocRetrievalOutput:
# def doc_retrieval(state: RetrieveInput) -> Command[Literal["doc_verification"]]:
"""
Retrieve documents
Args:
state (dict): The current graph state
Returns:
state (dict): New key added to state, documents, that contains retrieved documents
"""
print(f"doc_retrieval state: {state.keys()}")
state["query_to_retrieve"]
documents: list[InferenceSection] = []
llm = state["primary_llm"]
fast_llm = state["fast_llm"]
# db_session = state["db_session"]
query_to_retrieve = state["search_request"].query
with get_session_context_manager() as db_session1:
documents = SearchPipeline(
search_request=SearchRequest(
query=query_to_retrieve,
),
user=None,
llm=llm,
fast_llm=fast_llm,
db_session=db_session1,
).reranked_sections
print(f"retrieved documents: {len(documents)}")
return DocRetrievalOutput(
retrieved_documents=documents,
)

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from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.expanded_retrieval.states import DocVerificationOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
from danswer.agent_search.shared_graph_utils.models import BinaryDecision
from danswer.agent_search.shared_graph_utils.prompts import VERIFIER_PROMPT
from danswer.context.search.models import InferenceSection
class DocVerificationInput(ExpandedRetrievalState, total=True):
doc_to_verify: InferenceSection
def doc_verification(state: DocVerificationInput) -> DocVerificationOutput:
"""
Check whether the document is relevant for the original user question
Args:
state (VerifierState): The current state
Returns:
dict: ict: The updated state with the final decision
"""
print(f"doc_verification state: {state.keys()}")
original_query = state["search_request"].query
doc_to_verify = state["doc_to_verify"]
document_content = doc_to_verify.combined_content
msg = [
HumanMessage(
content=VERIFIER_PROMPT.format(
question=original_query, document_content=document_content
)
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
response_string = merge_message_runs(response, chunk_separator="")[0].content
# Convert string response to proper dictionary format
decision_dict = {"decision": response_string.lower()}
formatted_response = BinaryDecision.model_validate(decision_dict)
print(f"Verdict: {formatted_response.decision}")
verified_documents = []
if formatted_response.decision == "yes":
verified_documents.append(doc_to_verify)
return DocVerificationOutput(
verified_documents=verified_documents,
)

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from typing import Literal
from langgraph.types import Command
from langgraph.types import Send
from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
DocVerificationInput,
)
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def verification_kickoff(
state: ExpandedRetrievalState,
) -> Command[Literal["doc_verification"]]:
print(f"verification_kickoff state: {state.keys()}")
documents = state["retrieved_documents"]
return Command(
update={},
goto=[
Send(
node="doc_verification",
arg=DocVerificationInput(doc_to_verify=doc, **state),
)
for doc in documents
],
)

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from typing import Annotated
from typing import TypedDict
from danswer.agent_search.core_state import PrimaryState
from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
from danswer.context.search.models import InferenceSection
class DocRetrievalOutput(TypedDict, total=False):
retrieved_documents: Annotated[list[InferenceSection], dedup_inference_sections]
class DocVerificationOutput(TypedDict, total=False):
verified_documents: Annotated[list[InferenceSection], dedup_inference_sections]
class DocRerankingOutput(TypedDict, total=False):
reranked_documents: Annotated[list[InferenceSection], dedup_inference_sections]
class ExpandedRetrievalState(
PrimaryState,
DocRetrievalOutput,
DocVerificationOutput,
DocRerankingOutput,
total=True,
):
query_to_answer: str
class ExpandedRetrievalInput(PrimaryState, total=True):
query_to_answer: str
class ExpandedRetrievalOutput(TypedDict):
reordered_documents: Annotated[list[InferenceSection], dedup_inference_sections]

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from collections.abc import Hashable
from langgraph.types import Send
from danswer.agent_search.answer_query.states import AnswerQueryInput
from danswer.agent_search.main.states import MainState
def parallelize_decompozed_answer_queries(state: MainState) -> list[Send | Hashable]:
return [
Send(
"answer_query",
AnswerQueryInput(
**state,
query_to_answer=query,
),
)
for query in state["initial_decomp_queries"]
]
# def continue_to_answer_sub_questions(state: QAState) -> Union[Hashable, list[Hashable]]:
# # Routes re-written queries to the (parallel) retrieval steps
# # Notice the 'Send()' API that takes care of the parallelization
# return [
# Send(
# "sub_answers_graph",
# ResearchQAState(
# sub_question=sub_question["sub_question_str"],
# sub_question_nr=sub_question["sub_question_nr"],
# graph_start_time=state["graph_start_time"],
# primary_llm=state["primary_llm"],
# fast_llm=state["fast_llm"],
# ),
# )
# for sub_question in state["sub_questions"]
# ]
# def continue_to_deep_answer(state: QAState) -> Union[Hashable, list[Hashable]]:
# print("---GO TO DEEP ANSWER OR END---")
# base_answer = state["base_answer"]
# question = state["original_question"]
# BASE_CHECK_MESSAGE = [
# HumanMessage(
# content=BASE_CHECK_PROMPT.format(question=question, base_answer=base_answer)
# )
# ]
# model = state["fast_llm"]
# response = model.invoke(BASE_CHECK_MESSAGE)
# print(f"CAN WE CONTINUE W/O GENERATING A DEEP ANSWER? - {response.pretty_repr()}")
# if response.pretty_repr() == "no":
# return "decompose"
# else:
# return "end"

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from langgraph.graph import END
from langgraph.graph import START
from langgraph.graph import StateGraph
from danswer.agent_search.answer_query.graph_builder import answer_query_graph_builder
from danswer.agent_search.expanded_retrieval.graph_builder import (
expanded_retrieval_graph_builder,
)
from danswer.agent_search.main.edges import parallelize_decompozed_answer_queries
from danswer.agent_search.main.nodes.base_decomp import main_decomp_base
from danswer.agent_search.main.nodes.generate_initial_answer import (
generate_initial_answer,
)
from danswer.agent_search.main.states import MainInput
from danswer.agent_search.main.states import MainState
def main_graph_builder() -> StateGraph:
graph = StateGraph(
state_schema=MainState,
input=MainInput,
)
### Add nodes ###
graph.add_node(
node="base_decomp",
action=main_decomp_base,
)
answer_query_subgraph = answer_query_graph_builder().compile()
graph.add_node(
node="answer_query",
action=answer_query_subgraph,
)
expanded_retrieval_subgraph = expanded_retrieval_graph_builder().compile()
graph.add_node(
node="expanded_retrieval",
action=expanded_retrieval_subgraph,
)
graph.add_node(
node="generate_initial_answer",
action=generate_initial_answer,
)
### Add edges ###
graph.add_edge(
start_key=START,
end_key="expanded_retrieval",
)
graph.add_edge(
start_key=START,
end_key="base_decomp",
)
graph.add_conditional_edges(
source="base_decomp",
path=parallelize_decompozed_answer_queries,
path_map=["answer_query"],
)
graph.add_edge(
start_key=["answer_query", "expanded_retrieval"],
end_key="generate_initial_answer",
)
graph.add_edge(
start_key="generate_initial_answer",
end_key=END,
)
return graph
if __name__ == "__main__":
from danswer.db.engine import get_session_context_manager
from danswer.llm.factory import get_default_llms
from danswer.context.search.models import SearchRequest
graph = main_graph_builder()
compiled_graph = graph.compile()
primary_llm, fast_llm = get_default_llms()
search_request = SearchRequest(
query="If i am familiar with the function that I need, how can I type it into a cell?",
)
with get_session_context_manager() as db_session:
inputs = MainInput(
search_request=search_request,
primary_llm=primary_llm,
fast_llm=fast_llm,
db_session=db_session,
)
for thing in compiled_graph.stream(
input=inputs,
# stream_mode="debug",
# debug=True,
subgraphs=True,
):
# print(thing)
print()
print()

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from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import BaseDecompOutput
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import INITIAL_DECOMPOSITION_PROMPT
from danswer.agent_search.shared_graph_utils.utils import clean_and_parse_list_string
def main_decomp_base(state: MainState) -> BaseDecompOutput:
question = state["search_request"].query
msg = [
HumanMessage(
content=INITIAL_DECOMPOSITION_PROMPT.format(question=question),
)
]
# Get the rewritten queries in a defined format
model = state["fast_llm"]
response = model.invoke(msg)
content = response.pretty_repr()
list_of_subquestions = clean_and_parse_list_string(content)
decomp_list: list[str] = [
sub_question["sub_question"].strip() for sub_question in list_of_subquestions
]
return BaseDecompOutput(
initial_decomp_queries=decomp_list,
)

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from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import InitialAnswerOutput
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import INITIAL_RAG_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
def generate_initial_answer(state: MainState) -> InitialAnswerOutput:
print("---GENERATE INITIAL---")
question = state["search_request"].query
docs = state["documents"]
decomp_answer_results = state["decomp_answer_results"]
good_qa_list: list[str] = []
_SUB_QUESTION_ANSWER_TEMPLATE = """
Sub-Question:\n - {sub_question}\n --\nAnswer:\n - {sub_answer}\n\n
"""
for decomp_answer_result in decomp_answer_results:
if (
decomp_answer_result.quality.lower() == "yes"
and len(decomp_answer_result.answer) > 0
and decomp_answer_result.answer != "I don't know"
):
good_qa_list.append(
_SUB_QUESTION_ANSWER_TEMPLATE.format(
sub_question=decomp_answer_result.query,
sub_answer=decomp_answer_result.answer,
)
)
sub_question_answer_str = "\n\n------\n\n".join(good_qa_list)
msg = [
HumanMessage(
content=INITIAL_RAG_PROMPT.format(
question=question,
context=format_docs(docs),
answered_sub_questions=sub_question_answer_str,
)
)
]
# Grader
model = state["fast_llm"]
response = model.invoke(msg)
answer = response.pretty_repr()
print(answer)
return InitialAnswerOutput(initial_answer=answer)

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from operator import add
from typing import Annotated
from typing import TypedDict
from danswer.agent_search.answer_query.states import SearchAnswerResults
from danswer.agent_search.core_state import PrimaryState
from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
from danswer.context.search.models import InferenceSection
class BaseDecompOutput(TypedDict, total=False):
initial_decomp_queries: list[str]
class InitialAnswerOutput(TypedDict, total=False):
initial_answer: str
class MainState(
PrimaryState,
BaseDecompOutput,
InitialAnswerOutput,
total=True,
):
documents: Annotated[list[InferenceSection], dedup_inference_sections]
decomp_answer_results: Annotated[list[SearchAnswerResults], add]
class MainInput(PrimaryState, total=True):
pass
class MainOutput(TypedDict):
"""
This is not used because defining the output only matters for filtering the output of
a .invoke() call but we are streaming so we just yield the entire state.
"""

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from danswer.agent_search.primary_graph.graph_builder import build_core_graph
from danswer.llm.answering.answer import AnswerStream
from danswer.llm.interfaces import LLM
from danswer.tools.tool import Tool
def run_graph(
query: str,
llm: LLM,
tools: list[Tool],
) -> AnswerStream:
graph = build_core_graph()
inputs = {
"original_query": query,
"messages": [],
"tools": tools,
"llm": llm,
}
compiled_graph = graph.compile()
output = compiled_graph.invoke(input=inputs)
yield from output
if __name__ == "__main__":
pass
# run_graph("What is the capital of France?", llm, [])

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from typing import Literal
from pydantic import BaseModel
# Pydantic models for structured outputs
class RewrittenQueries(BaseModel):
rewritten_queries: list[str]
class BinaryDecision(BaseModel):
decision: Literal["yes", "no"]

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from danswer.context.search.models import InferenceSection
from danswer.llm.answering.prune_and_merge import _merge_sections
def dedup_inference_sections(
list1: list[InferenceSection], list2: list[InferenceSection]
) -> list[InferenceSection]:
deduped = _merge_sections(list1 + list2)
return deduped

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REWRITE_PROMPT_MULTI_ORIGINAL = """ \n
Please convert an initial user question into a 2-3 more appropriate short and pointed search queries for retrievel from a
document store. Particularly, try to think about resolving ambiguities and make the search queries more specific,
enabling the system to search more broadly.
Also, try to make the search queries not redundant, i.e. not too similar! \n\n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Formulate the queries separated by '--' (Do not say 'Query 1: ...', just write the querytext): """
REWRITE_PROMPT_MULTI = """ \n
Please create a list of 2-3 sample documents that could answer an original question. Each document
should be about as long as the original question. \n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Formulate the sample documents separated by '--' (Do not say 'Document 1: ...', just write the text): """
BASE_RAG_PROMPT = """ \n
You are an assistant for question-answering tasks. Use the context provided below - and only the
provided context - to answer the question. If you don't know the answer or if the provided context is
empty, just say "I don't know". Do not use your internal knowledge!
Again, only use the provided context and do not use your internal knowledge! If you cannot answer the
question based on the context, say "I don't know". It is a matter of life and death that you do NOT
use your internal knowledge, just the provided information!
Use three sentences maximum and keep the answer concise.
answer concise.\nQuestion:\n {question} \nContext:\n {context} \n\n
\n\n
Answer:"""
BASE_CHECK_PROMPT = """ \n
Please check whether 1) the suggested answer seems to fully address the original question AND 2)the
original question requests a simple, factual answer, and there are no ambiguities, judgements,
aggregations, or any other complications that may require extra context. (I.e., if the question is
somewhat addressed, but the answer would benefit from more context, then answer with 'no'.)
Please only answer with 'yes' or 'no' \n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Here is the proposed answer:
\n ------- \n
{base_answer}
\n ------- \n
Please answer with yes or no:"""
VERIFIER_PROMPT = """ \n
Please check whether the document seems to be relevant for the answer of the question. Please
only answer with 'yes' or 'no' \n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Here is the document text:
\n ------- \n
{document_content}
\n ------- \n
Please answer with yes or no:"""
INITIAL_DECOMPOSITION_PROMPT_BASIC = """ \n
Please decompose an initial user question into not more than 4 appropriate sub-questions that help to
answer the original question. The purpose for this decomposition is to isolate individulal entities
(i.e., 'compare sales of company A and company B' -> 'what are sales for company A' + 'what are sales
for company B'), split ambiguous terms (i.e., 'what is our success with company A' -> 'what are our
sales with company A' + 'what is our market share with company A' + 'is company A a reference customer
for us'), etc. Each sub-question should be realistically be answerable by a good RAG system. \n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Please formulate your answer as a list of subquestions:
Answer:
"""
REWRITE_PROMPT_SINGLE = """ \n
Please convert an initial user question into a more appropriate search query for retrievel from a
document store. \n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Formulate the query: """
MODIFIED_RAG_PROMPT = """You are an assistant for question-answering tasks. Use the context provided below
- and only this context - to answer the question. If you don't know the answer, just say "I don't know".
Use three sentences maximum and keep the answer concise.
Pay also particular attention to the sub-questions and their answers, at least it may enrich the answer.
Again, only use the provided context and do not use your internal knowledge! If you cannot answer the
question based on the context, say "I don't know". It is a matter of life and death that you do NOT
use your internal knowledge, just the provided information!
\nQuestion: {question}
\nContext: {combined_context} \n
Answer:"""
ORIG_DEEP_DECOMPOSE_PROMPT = """ \n
An initial user question needs to be answered. An initial answer has been provided but it wasn't quite
good enough. Also, some sub-questions had been answered and this information has been used to provide
the initial answer. Some other subquestions may have been suggested based on little knowledge, but they
were not directly answerable. Also, some entities, relationships and terms are givenm to you so that
you have an idea of how the avaiolable data looks like.
Your role is to generate 3-5 new sub-questions that would help to answer the initial question,
considering:
1) The initial question
2) The initial answer that was found to be unsatisfactory
3) The sub-questions that were answered
4) The sub-questions that were suggested but not answered
5) The entities, relationships and terms that were extracted from the context
The individual questions should be answerable by a good RAG system.
So a good idea would be to use the sub-questions to resolve ambiguities and/or to separate the
question for different entities that may be involved in the original question, but in a way that does
not duplicate questions that were already tried.
Additional Guidelines:
- The sub-questions should be specific to the question and provide richer context for the question,
resolve ambiguities, or address shortcoming of the initial answer
- Each sub-question - when answered - should be relevant for the answer to the original question
- The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
other complications that may require extra context.
- The sub-questions MUST have the full context of the original question so that it can be executed by
a RAG system independently without the original question available
(Example:
- initial question: "What is the capital of France?"
- bad sub-question: "What is the name of the river there?"
- good sub-question: "What is the name of the river that flows through Paris?"
- For each sub-question, please provide a short explanation for why it is a good sub-question. So
generate a list of dictionaries with the following format:
[{{"sub_question": <sub-question>, "explanation": <explanation>, "search_term": <rewrite the
sub-question using as a search phrase for the document store>}}, ...]
\n\n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Here is the initial sub-optimal answer:
\n ------- \n
{base_answer}
\n ------- \n
Here are the sub-questions that were answered:
\n ------- \n
{answered_sub_questions}
\n ------- \n
Here are the sub-questions that were suggested but not answered:
\n ------- \n
{failed_sub_questions}
\n ------- \n
And here are the entities, relationships and terms extracted from the context:
\n ------- \n
{entity_term_extraction_str}
\n ------- \n
Please generate the list of good, fully contextualized sub-questions that would help to address the
main question. Again, please find questions that are NOT overlapping too much with the already answered
sub-questions or those that already were suggested and failed.
In other words - what can we try in addition to what has been tried so far?
Please think through it step by step and then generate the list of json dictionaries with the following
format:
{{"sub_questions": [{{"sub_question": <sub-question>,
"explanation": <explanation>,
"search_term": <rewrite the sub-question using as a search phrase for the document store>}},
...]}} """
DEEP_DECOMPOSE_PROMPT = """ \n
An initial user question needs to be answered. An initial answer has been provided but it wasn't quite
good enough. Also, some sub-questions had been answered and this information has been used to provide
the initial answer. Some other subquestions may have been suggested based on little knowledge, but they
were not directly answerable. Also, some entities, relationships and terms are givenm to you so that
you have an idea of how the avaiolable data looks like.
Your role is to generate 4-6 new sub-questions that would help to answer the initial question,
considering:
1) The initial question
2) The initial answer that was found to be unsatisfactory
3) The sub-questions that were answered
4) The sub-questions that were suggested but not answered
5) The entities, relationships and terms that were extracted from the context
The individual questions should be answerable by a good RAG system.
So a good idea would be to use the sub-questions to resolve ambiguities and/or to separate the
question for different entities that may be involved in the original question, but in a way that does
not duplicate questions that were already tried.
Additional Guidelines:
- The sub-questions should be specific to the question and provide richer context for the question,
resolve ambiguities, or address shortcoming of the initial answer
- Each sub-question - when answered - should be relevant for the answer to the original question
- The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
other complications that may require extra context.
- The sub-questions MUST have the full context of the original question so that it can be executed by
a RAG system independently without the original question available
(Example:
- initial question: "What is the capital of France?"
- bad sub-question: "What is the name of the river there?"
- good sub-question: "What is the name of the river that flows through Paris?"
- For each sub-question, please also provide a search term that can be used to retrieve relevant
documents from a document store.
\n\n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Here is the initial sub-optimal answer:
\n ------- \n
{base_answer}
\n ------- \n
Here are the sub-questions that were answered:
\n ------- \n
{answered_sub_questions}
\n ------- \n
Here are the sub-questions that were suggested but not answered:
\n ------- \n
{failed_sub_questions}
\n ------- \n
And here are the entities, relationships and terms extracted from the context:
\n ------- \n
{entity_term_extraction_str}
\n ------- \n
Please generate the list of good, fully contextualized sub-questions that would help to address the
main question. Again, please find questions that are NOT overlapping too much with the already answered
sub-questions or those that already were suggested and failed.
In other words - what can we try in addition to what has been tried so far?
Generate the list of json dictionaries with the following format:
{{"sub_questions": [{{"sub_question": <sub-question>,
"search_term": <rewrite the sub-question using as a search phrase for the document store>}},
...]}} """
DECOMPOSE_PROMPT = """ \n
For an initial user question, please generate at 5-10 individual sub-questions whose answers would help
\n to answer the initial question. The individual questions should be answerable by a good RAG system.
So a good idea would be to \n use the sub-questions to resolve ambiguities and/or to separate the
question for different entities that may be involved in the original question.
In order to arrive at meaningful sub-questions, please also consider the context retrieved from the
document store, expressed as entities, relationships and terms. You can also think about the types
mentioned in brackets
Guidelines:
- The sub-questions should be specific to the question and provide richer context for the question,
and or resolve ambiguities
- Each sub-question - when answered - should be relevant for the answer to the original question
- The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
other complications that may require extra context.
- The sub-questions MUST have the full context of the original question so that it can be executed by
a RAG system independently without the original question available
(Example:
- initial question: "What is the capital of France?"
- bad sub-question: "What is the name of the river there?"
- good sub-question: "What is the name of the river that flows through Paris?"
- For each sub-question, please provide a short explanation for why it is a good sub-question. So
generate a list of dictionaries with the following format:
[{{"sub_question": <sub-question>, "explanation": <explanation>, "search_term": <rewrite the
sub-question using as a search phrase for the document store>}}, ...]
\n\n
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
And here are the entities, relationships and terms extracted from the context:
\n ------- \n
{entity_term_extraction_str}
\n ------- \n
Please generate the list of good, fully contextualized sub-questions that would help to address the
main question. Don't be too specific unless the original question is specific.
Please think through it step by step and then generate the list of json dictionaries with the following
format:
{{"sub_questions": [{{"sub_question": <sub-question>,
"explanation": <explanation>,
"search_term": <rewrite the sub-question using as a search phrase for the document store>}},
...]}} """
#### Consolidations
COMBINED_CONTEXT = """-------
Below you will find useful information to answer the original question. First, you see a number of
sub-questions with their answers. This information should be considered to be more focussed and
somewhat more specific to the original question as it tries to contextualized facts.
After that will see the documents that were considered to be relevant to answer the original question.
Here are the sub-questions and their answers:
\n\n {deep_answer_context} \n\n
\n\n Here are the documents that were considered to be relevant to answer the original question:
\n\n {formated_docs} \n\n
----------------
"""
SUB_QUESTION_EXPLANATION_RANKER_PROMPT = """-------
Below you will find a question that we ultimately want to answer (the original question) and a list of
motivations in arbitrary order for generated sub-questions that are supposed to help us answering the
original question. The motivations are formatted as <motivation number>: <motivation explanation>.
(Again, the numbering is arbitrary and does not necessarily mean that 1 is the most relevant
motivation and 2 is less relevant.)
Please rank the motivations in order of relevance for answering the original question. Also, try to
ensure that the top questions do not duplicate too much, i.e. that they are not too similar.
Ultimately, create a list with the motivation numbers where the number of the most relevant
motivations comes first.
Here is the original question:
\n\n {original_question} \n\n
\n\n Here is the list of sub-question motivations:
\n\n {sub_question_explanations} \n\n
----------------
Please think step by step and then generate the ranked list of motivations.
Please format your answer as a json object in the following format:
{{"reasonning": <explain your reasoning for the ranking>,
"ranked_motivations": <ranked list of motivation numbers>}}
"""
INITIAL_DECOMPOSITION_PROMPT = """ \n
Please decompose an initial user question into 2 or 3 appropriate sub-questions that help to
answer the original question. The purpose for this decomposition is to isolate individulal entities
(i.e., 'compare sales of company A and company B' -> 'what are sales for company A' + 'what are sales
for company B'), split ambiguous terms (i.e., 'what is our success with company A' -> 'what are our
sales with company A' + 'what is our market share with company A' + 'is company A a reference customer
for us'), etc. Each sub-question should be realistically be answerable by a good RAG system. \n
For each sub-question, please also create one search term that can be used to retrieve relevant
documents from a document store.
Here is the initial question:
\n ------- \n
{question}
\n ------- \n
Please formulate your answer as a list of json objects with the following format:
[{{"sub_question": <sub-question>, "search_term": <search term>}}, ...]
Answer:
"""
INITIAL_RAG_PROMPT = """ \n
You are an assistant for question-answering tasks. Use the information provided below - and only the
provided information - to answer the provided question.
The information provided below consists of:
1) a number of answered sub-questions - these are very important(!) and definitely should be
considered to answer the question.
2) a number of documents that were also deemed relevant for the question.
If you don't know the answer or if the provided information is empty or insufficient, just say
"I don't know". Do not use your internal knowledge!
Again, only use the provided informationand do not use your internal knowledge! It is a matter of life
and death that you do NOT use your internal knowledge, just the provided information!
Try to keep your answer concise.
And here is the question and the provided information:
\n
\nQuestion:\n {question}
\nAnswered Sub-questions:\n {answered_sub_questions}
\nContext:\n {context} \n\n
\n\n
Answer:"""
ENTITY_TERM_PROMPT = """ \n
Based on the original question and the context retieved from a dataset, please generate a list of
entities (e.g. companies, organizations, industries, products, locations, etc.), terms and concepts
(e.g. sales, revenue, etc.) that are relevant for the question, plus their relations to each other.
\n\n
Here is the original question:
\n ------- \n
{question}
\n ------- \n
And here is the context retrieved:
\n ------- \n
{context}
\n ------- \n
Please format your answer as a json object in the following format:
{{"retrieved_entities_relationships": {{
"entities": [{{
"entity_name": <assign a name for the entity>,
"entity_type": <specify a short type name for the entity, such as 'company', 'location',...>
}}],
"relationships": [{{
"name": <assign a name for the relationship>,
"type": <specify a short type name for the relationship, such as 'sales_to', 'is_location_of',...>,
"entities": [<related entity name 1>, <related entity name 2>]
}}],
"terms": [{{
"term_name": <assign a name for the term>,
"term_type": <specify a short type name for the term, such as 'revenue', 'market_share',...>,
"similar_to": <list terms that are similar to this term>
}}]
}}
}}
"""

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@@ -0,0 +1,101 @@
import ast
import json
import re
from collections.abc import Sequence
from datetime import datetime
from datetime import timedelta
from typing import Any
from danswer.context.search.models import InferenceSection
def normalize_whitespace(text: str) -> str:
"""Normalize whitespace in text to single spaces and strip leading/trailing whitespace."""
import re
return re.sub(r"\s+", " ", text.strip())
# Post-processing
def format_docs(docs: Sequence[InferenceSection]) -> str:
return "\n\n".join(doc.combined_content for doc in docs)
def clean_and_parse_list_string(json_string: str) -> list[dict]:
# Remove any prefixes/labels before the actual JSON content
json_string = re.sub(r"^.*?(?=\[)", "", json_string, flags=re.DOTALL)
# Remove markdown code block markers and any newline prefixes
cleaned_string = re.sub(r"```json\n|\n```", "", json_string)
cleaned_string = cleaned_string.replace("\\n", " ").replace("\n", " ")
cleaned_string = " ".join(cleaned_string.split())
# Try parsing with json.loads first, fall back to ast.literal_eval
try:
return json.loads(cleaned_string)
except json.JSONDecodeError:
try:
return ast.literal_eval(cleaned_string)
except (ValueError, SyntaxError) as e:
raise ValueError(f"Failed to parse JSON string: {cleaned_string}") from e
def clean_and_parse_json_string(json_string: str) -> dict[str, Any]:
# Remove markdown code block markers and any newline prefixes
cleaned_string = re.sub(r"```json\n|\n```", "", json_string)
cleaned_string = cleaned_string.replace("\\n", " ").replace("\n", " ")
cleaned_string = " ".join(cleaned_string.split())
# Parse the cleaned string into a Python dictionary
return json.loads(cleaned_string)
def format_entity_term_extraction(entity_term_extraction_dict: dict[str, Any]) -> str:
entities = entity_term_extraction_dict["entities"]
terms = entity_term_extraction_dict["terms"]
relationships = entity_term_extraction_dict["relationships"]
entity_strs = ["\nEntities:\n"]
for entity in entities:
entity_str = f"{entity['entity_name']} ({entity['entity_type']})"
entity_strs.append(entity_str)
entity_str = "\n - ".join(entity_strs)
relationship_strs = ["\n\nRelationships:\n"]
for relationship in relationships:
relationship_str = f"{relationship['name']} ({relationship['type']}): {relationship['entities']}"
relationship_strs.append(relationship_str)
relationship_str = "\n - ".join(relationship_strs)
term_strs = ["\n\nTerms:\n"]
for term in terms:
term_str = f"{term['term_name']} ({term['term_type']}): similar to {term['similar_to']}"
term_strs.append(term_str)
term_str = "\n - ".join(term_strs)
return "\n".join(entity_strs + relationship_strs + term_strs)
def _format_time_delta(time: timedelta) -> str:
seconds_from_start = f"{((time).seconds):03d}"
microseconds_from_start = f"{((time).microseconds):06d}"
return f"{seconds_from_start}.{microseconds_from_start}"
def generate_log_message(
message: str,
node_start_time: datetime,
graph_start_time: datetime | None = None,
) -> str:
current_time = datetime.now()
if graph_start_time is not None:
graph_time_str = _format_time_delta(current_time - graph_start_time)
else:
graph_time_str = "N/A"
node_time_str = _format_time_delta(current_time - node_start_time)
return f"{graph_time_str} ({node_time_str} s): {message}"

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@@ -0,0 +1,89 @@
import secrets
import uuid
from urllib.parse import quote
from urllib.parse import unquote
from fastapi import Request
from passlib.hash import sha256_crypt
from pydantic import BaseModel
from danswer.auth.schemas import UserRole
from danswer.configs.app_configs import API_KEY_HASH_ROUNDS
_API_KEY_HEADER_NAME = "Authorization"
# NOTE for others who are curious: In the context of a header, "X-" often refers
# to non-standard, experimental, or custom headers in HTTP or other protocols. It
# indicates that the header is not part of the official standards defined by
# organizations like the Internet Engineering Task Force (IETF).
_API_KEY_HEADER_ALTERNATIVE_NAME = "X-Danswer-Authorization"
_BEARER_PREFIX = "Bearer "
_API_KEY_PREFIX = "dn_"
_API_KEY_LEN = 192
class ApiKeyDescriptor(BaseModel):
api_key_id: int
api_key_display: str
api_key: str | None = None # only present on initial creation
api_key_name: str | None = None
api_key_role: UserRole
user_id: uuid.UUID
def generate_api_key(tenant_id: str | None = None) -> str:
# For backwards compatibility, if no tenant_id, generate old style key
if not tenant_id:
return _API_KEY_PREFIX + secrets.token_urlsafe(_API_KEY_LEN)
encoded_tenant = quote(tenant_id) # URL encode the tenant ID
return f"{_API_KEY_PREFIX}{encoded_tenant}.{secrets.token_urlsafe(_API_KEY_LEN)}"
def extract_tenant_from_api_key_header(request: Request) -> str | None:
"""Extract tenant ID from request. Returns None if auth is disabled or invalid format."""
raw_api_key_header = request.headers.get(
_API_KEY_HEADER_ALTERNATIVE_NAME
) or request.headers.get(_API_KEY_HEADER_NAME)
if not raw_api_key_header or not raw_api_key_header.startswith(_BEARER_PREFIX):
return None
api_key = raw_api_key_header[len(_BEARER_PREFIX) :].strip()
if not api_key.startswith(_API_KEY_PREFIX):
return None
parts = api_key[len(_API_KEY_PREFIX) :].split(".", 1)
if len(parts) != 2:
return None
tenant_id = parts[0]
return unquote(tenant_id) if tenant_id else None
def hash_api_key(api_key: str) -> str:
# NOTE: no salt is needed, as the API key is randomly generated
# and overlaps are impossible
return sha256_crypt.hash(api_key, salt="", rounds=API_KEY_HASH_ROUNDS)
def build_displayable_api_key(api_key: str) -> str:
if api_key.startswith(_API_KEY_PREFIX):
api_key = api_key[len(_API_KEY_PREFIX) :]
return _API_KEY_PREFIX + api_key[:4] + "********" + api_key[-4:]
def get_hashed_api_key_from_request(request: Request) -> str | None:
raw_api_key_header = request.headers.get(
_API_KEY_HEADER_ALTERNATIVE_NAME
) or request.headers.get(_API_KEY_HEADER_NAME)
if raw_api_key_header is None:
return None
if raw_api_key_header.startswith(_BEARER_PREFIX):
raw_api_key_header = raw_api_key_header[len(_BEARER_PREFIX) :].strip()
return hash_api_key(raw_api_key_header)

View File

@@ -2,8 +2,8 @@ from typing import cast
from danswer.configs.constants import KV_USER_STORE_KEY
from danswer.key_value_store.factory import get_kv_store
from danswer.key_value_store.interface import JSON_ro
from danswer.key_value_store.interface import KvKeyNotFoundError
from danswer.utils.special_types import JSON_ro
def get_invited_users() -> list[str]:

View File

@@ -23,7 +23,9 @@ def load_no_auth_user_preferences(store: KeyValueStore) -> UserPreferences:
)
return UserPreferences(**preferences_data)
except KvKeyNotFoundError:
return UserPreferences(chosen_assistants=None, default_model=None)
return UserPreferences(
chosen_assistants=None, default_model=None, auto_scroll=True
)
def fetch_no_auth_user(store: KeyValueStore) -> UserInfo:

View File

@@ -13,12 +13,24 @@ class UserRole(str, Enum):
groups they are curators of
- Global Curator can perform admin actions
for all groups they are a member of
- Limited can access a limited set of basic api endpoints
- Slack are users that have used danswer via slack but dont have a web login
- External permissioned users that have been picked up during the external permissions sync process but don't have a web login
"""
LIMITED = "limited"
BASIC = "basic"
ADMIN = "admin"
CURATOR = "curator"
GLOBAL_CURATOR = "global_curator"
SLACK_USER = "slack_user"
EXT_PERM_USER = "ext_perm_user"
def is_web_login(self) -> bool:
return self not in [
UserRole.SLACK_USER,
UserRole.EXT_PERM_USER,
]
class UserStatus(str, Enum):
@@ -33,10 +45,8 @@ class UserRead(schemas.BaseUser[uuid.UUID]):
class UserCreate(schemas.BaseUserCreate):
role: UserRole = UserRole.BASIC
has_web_login: bool | None = True
tenant_id: str | None = None
class UserUpdate(schemas.BaseUserUpdate):
role: UserRole
has_web_login: bool | None = True

View File

@@ -48,20 +48,19 @@ from httpx_oauth.integrations.fastapi import OAuth2AuthorizeCallback
from httpx_oauth.oauth2 import BaseOAuth2
from httpx_oauth.oauth2 import OAuth2Token
from pydantic import BaseModel
from sqlalchemy import select
from sqlalchemy.orm import attributes
from sqlalchemy.orm import Session
from sqlalchemy import text
from sqlalchemy.ext.asyncio import AsyncSession
from danswer.auth.api_key import get_hashed_api_key_from_request
from danswer.auth.invited_users import get_invited_users
from danswer.auth.schemas import UserCreate
from danswer.auth.schemas import UserRole
from danswer.auth.schemas import UserUpdate
from danswer.configs.app_configs import AUTH_TYPE
from danswer.configs.app_configs import DISABLE_AUTH
from danswer.configs.app_configs import DISABLE_VERIFICATION
from danswer.configs.app_configs import EMAIL_FROM
from danswer.configs.app_configs import MULTI_TENANT
from danswer.configs.app_configs import REQUIRE_EMAIL_VERIFICATION
from danswer.configs.app_configs import SECRET_JWT_KEY
from danswer.configs.app_configs import SESSION_EXPIRE_TIME_SECONDS
from danswer.configs.app_configs import SMTP_PASS
from danswer.configs.app_configs import SMTP_PORT
@@ -75,26 +74,28 @@ from danswer.configs.constants import AuthType
from danswer.configs.constants import DANSWER_API_KEY_DUMMY_EMAIL_DOMAIN
from danswer.configs.constants import DANSWER_API_KEY_PREFIX
from danswer.configs.constants import UNNAMED_KEY_PLACEHOLDER
from danswer.db.api_key import fetch_user_for_api_key
from danswer.db.auth import get_access_token_db
from danswer.db.auth import get_default_admin_user_emails
from danswer.db.auth import get_user_count
from danswer.db.auth import get_user_db
from danswer.db.auth import SQLAlchemyUserAdminDB
from danswer.db.engine import get_async_session
from danswer.db.engine import get_async_session_with_tenant
from danswer.db.engine import get_session
from danswer.db.engine import get_session_with_tenant
from danswer.db.engine import get_sqlalchemy_engine
from danswer.db.models import AccessToken
from danswer.db.models import OAuthAccount
from danswer.db.models import User
from danswer.db.models import UserTenantMapping
from danswer.db.users import get_user_by_email
from danswer.server.utils import BasicAuthenticationError
from danswer.utils.logger import setup_logger
from danswer.utils.telemetry import optional_telemetry
from danswer.utils.telemetry import RecordType
from danswer.utils.variable_functionality import fetch_ee_implementation_or_noop
from danswer.utils.variable_functionality import fetch_versioned_implementation
from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
from shared_configs.configs import async_return_default_schema
from shared_configs.configs import MULTI_TENANT
from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
logger = setup_logger()
@@ -133,7 +134,9 @@ def get_display_email(email: str | None, space_less: bool = False) -> str:
def user_needs_to_be_verified() -> bool:
# all other auth types besides basic should require users to be
# verified
return AUTH_TYPE != AuthType.BASIC or REQUIRE_EMAIL_VERIFICATION
return not DISABLE_VERIFICATION and (
AUTH_TYPE != AuthType.BASIC or REQUIRE_EMAIL_VERIFICATION
)
def verify_email_is_invited(email: str) -> None:
@@ -186,20 +189,6 @@ def verify_email_domain(email: str) -> None:
)
def get_tenant_id_for_email(email: str) -> str:
if not MULTI_TENANT:
return POSTGRES_DEFAULT_SCHEMA
# Implement logic to get tenant_id from the mapping table
with Session(get_sqlalchemy_engine()) as db_session:
result = db_session.execute(
select(UserTenantMapping.tenant_id).where(UserTenantMapping.email == email)
)
tenant_id = result.scalar_one_or_none()
if tenant_id is None:
raise exceptions.UserNotExists()
return tenant_id
def send_user_verification_email(
user_email: str,
token: str,
@@ -228,25 +217,26 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
reset_password_token_secret = USER_AUTH_SECRET
verification_token_secret = USER_AUTH_SECRET
user_db: SQLAlchemyUserDatabase[User, uuid.UUID]
async def create(
self,
user_create: schemas.UC | UserCreate,
safe: bool = False,
request: Optional[Request] = None,
) -> User:
try:
tenant_id = (
get_tenant_id_for_email(user_create.email)
if MULTI_TENANT
else POSTGRES_DEFAULT_SCHEMA
)
except exceptions.UserNotExists:
raise HTTPException(status_code=401, detail="User not found")
referral_source = None
if request is not None:
referral_source = request.cookies.get("referral_source", None)
if not tenant_id:
raise HTTPException(
status_code=401, detail="User does not belong to an organization"
)
tenant_id = await fetch_ee_implementation_or_noop(
"danswer.server.tenants.provisioning",
"get_or_create_tenant_id",
async_return_default_schema,
)(
email=user_create.email,
referral_source=referral_source,
)
async with get_async_session_with_tenant(tenant_id) as db_session:
token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
@@ -254,7 +244,9 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
verify_email_is_invited(user_create.email)
verify_email_domain(user_create.email)
if MULTI_TENANT:
tenant_user_db = SQLAlchemyUserAdminDB(db_session, User, OAuthAccount)
tenant_user_db = SQLAlchemyUserAdminDB[User, uuid.UUID](
db_session, User, OAuthAccount
)
self.user_db = tenant_user_db
self.database = tenant_user_db
@@ -267,20 +259,15 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
user_create.role = UserRole.ADMIN
else:
user_create.role = UserRole.BASIC
user = None
try:
user = await super().create(user_create, safe=safe, request=request) # type: ignore
except exceptions.UserAlreadyExists:
user = await self.get_by_email(user_create.email)
# Handle case where user has used product outside of web and is now creating an account through web
if (
not user.has_web_login
and hasattr(user_create, "has_web_login")
and user_create.has_web_login
):
if not user.role.is_web_login() and user_create.role.is_web_login():
user_update = UserUpdate(
password=user_create.password,
has_web_login=True,
role=user_create.role,
is_verified=user_create.is_verified,
)
@@ -288,34 +275,13 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
else:
raise exceptions.UserAlreadyExists()
CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
finally:
CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
return user
async def on_after_login(
self,
user: User,
request: Request | None = None,
response: Response | None = None,
) -> None:
if response is None or not MULTI_TENANT:
return
tenant_id = get_tenant_id_for_email(user.email)
tenant_token = jwt.encode(
{"tenant_id": tenant_id}, SECRET_JWT_KEY, algorithm="HS256"
)
response.set_cookie(
key="tenant_details",
value=tenant_token,
httponly=True,
secure=WEB_DOMAIN.startswith("https"),
samesite="lax",
)
async def oauth_callback(
self: "BaseUserManager[models.UOAP, models.ID]",
self,
oauth_name: str,
access_token: str,
account_id: str,
@@ -326,20 +292,24 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
*,
associate_by_email: bool = False,
is_verified_by_default: bool = False,
) -> models.UOAP:
# Get tenant_id from mapping table
try:
tenant_id = (
get_tenant_id_for_email(account_email)
if MULTI_TENANT
else POSTGRES_DEFAULT_SCHEMA
)
except exceptions.UserNotExists:
raise HTTPException(status_code=401, detail="User not found")
) -> User:
referral_source = None
if request:
referral_source = getattr(request.state, "referral_source", None)
tenant_id = await fetch_ee_implementation_or_noop(
"danswer.server.tenants.provisioning",
"get_or_create_tenant_id",
async_return_default_schema,
)(
email=account_email,
referral_source=referral_source,
)
if not tenant_id:
raise HTTPException(status_code=401, detail="User not found")
# Proceed with the tenant context
token = None
async with get_async_session_with_tenant(tenant_id) as db_session:
token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
@@ -348,9 +318,11 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
verify_email_domain(account_email)
if MULTI_TENANT:
tenant_user_db = SQLAlchemyUserAdminDB(db_session, User, OAuthAccount)
tenant_user_db = SQLAlchemyUserAdminDB[User, uuid.UUID](
db_session, User, OAuthAccount
)
self.user_db = tenant_user_db
self.database = tenant_user_db # type: ignore
self.database = tenant_user_db
oauth_account_dict = {
"oauth_name": oauth_name,
@@ -386,9 +358,13 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
}
user = await self.user_db.create(user_dict)
user = await self.user_db.add_oauth_account(
user, oauth_account_dict
)
# Explicitly set the Postgres schema for this session to ensure
# OAuth account creation happens in the correct tenant schema
await db_session.execute(text(f'SET search_path = "{tenant_id}"'))
# Add OAuth account
await self.user_db.add_oauth_account(user, oauth_account_dict)
await self.on_after_register(user, request)
else:
@@ -398,7 +374,11 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
and existing_oauth_account.oauth_name == oauth_name
):
user = await self.user_db.update_oauth_account(
user, existing_oauth_account, oauth_account_dict
user,
# NOTE: OAuthAccount DOES implement the OAuthAccountProtocol
# but the type checker doesn't know that :(
existing_oauth_account, # type: ignore
oauth_account_dict,
)
# NOTE: Most IdPs have very short expiry times, and we don't want to force the user to
@@ -411,16 +391,15 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
)
# Handle case where user has used product outside of web and is now creating an account through web
if not user.has_web_login: # type: ignore
if not user.role.is_web_login():
await self.user_db.update(
user,
{
"is_verified": is_verified_by_default,
"has_web_login": True,
"role": UserRole.BASIC,
},
)
user.is_verified = is_verified_by_default
user.has_web_login = True # type: ignore
# this is needed if an organization goes from `TRACK_EXTERNAL_IDP_EXPIRY=true` to `false`
# otherwise, the oidc expiry will always be old, and the user will never be able to login
@@ -468,7 +447,13 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
email = credentials.username
# Get tenant_id from mapping table
tenant_id = get_tenant_id_for_email(email)
tenant_id = await fetch_ee_implementation_or_noop(
"danswer.server.tenants.provisioning",
"get_or_create_tenant_id",
async_return_default_schema,
)(
email=email,
)
if not tenant_id:
# User not found in mapping
self.password_helper.hash(credentials.password)
@@ -489,11 +474,8 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
self.password_helper.hash(credentials.password)
return None
has_web_login = attributes.get_attribute(user, "has_web_login")
if not has_web_login:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
if not user.role.is_web_login():
raise BasicAuthenticationError(
detail="NO_WEB_LOGIN_AND_HAS_NO_PASSWORD",
)
@@ -523,8 +505,33 @@ cookie_transport = CookieTransport(
)
def get_jwt_strategy() -> JWTStrategy:
return JWTStrategy(
# This strategy is used to add tenant_id to the JWT token
class TenantAwareJWTStrategy(JWTStrategy):
async def _create_token_data(self, user: User, impersonate: bool = False) -> dict:
tenant_id = await fetch_ee_implementation_or_noop(
"danswer.server.tenants.provisioning",
"get_or_create_tenant_id",
async_return_default_schema,
)(
email=user.email,
)
data = {
"sub": str(user.id),
"aud": self.token_audience,
"tenant_id": tenant_id,
}
return data
async def write_token(self, user: User) -> str:
data = await self._create_token_data(user)
return generate_jwt(
data, self.encode_key, self.lifetime_seconds, algorithm=self.algorithm
)
def get_jwt_strategy() -> TenantAwareJWTStrategy:
return TenantAwareJWTStrategy(
secret=USER_AUTH_SECRET,
lifetime_seconds=SESSION_EXPIRE_TIME_SECONDS,
)
@@ -598,7 +605,7 @@ optional_fastapi_current_user = fastapi_users.current_user(active=True, optional
async def optional_user_(
request: Request,
user: User | None,
db_session: Session,
async_db_session: AsyncSession,
) -> User | None:
"""NOTE: `request` and `db_session` are not used here, but are included
for the EE version of this function."""
@@ -607,13 +614,21 @@ async def optional_user_(
async def optional_user(
request: Request,
db_session: Session = Depends(get_session),
async_db_session: AsyncSession = Depends(get_async_session),
user: User | None = Depends(optional_fastapi_current_user),
) -> User | None:
versioned_fetch_user = fetch_versioned_implementation(
"danswer.auth.users", "optional_user_"
)
return await versioned_fetch_user(request, user, db_session)
user = await versioned_fetch_user(request, user, async_db_session)
# check if an API key is present
if user is None:
hashed_api_key = get_hashed_api_key_from_request(request)
if hashed_api_key:
user = await fetch_user_for_api_key(hashed_api_key, async_db_session)
return user
async def double_check_user(
@@ -625,14 +640,12 @@ async def double_check_user(
return None
if user is None:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User is not authenticated.",
)
if user_needs_to_be_verified() and not user.is_verified:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User is not verified.",
)
@@ -641,8 +654,7 @@ async def double_check_user(
and user.oidc_expiry < datetime.now(timezone.utc)
and not include_expired
):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User's OIDC token has expired.",
)
@@ -655,12 +667,26 @@ async def current_user_with_expired_token(
return await double_check_user(user, include_expired=True)
async def current_user(
async def current_limited_user(
user: User | None = Depends(optional_user),
) -> User | None:
return await double_check_user(user)
async def current_user(
user: User | None = Depends(optional_user),
) -> User | None:
user = await double_check_user(user)
if not user:
return None
if user.role == UserRole.LIMITED:
raise BasicAuthenticationError(
detail="Access denied. User role is LIMITED. BASIC or higher permissions are required.",
)
return user
async def current_curator_or_admin_user(
user: User | None = Depends(current_user),
) -> User | None:
@@ -668,15 +694,13 @@ async def current_curator_or_admin_user(
return None
if not user or not hasattr(user, "role"):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User is not authenticated or lacks role information.",
)
allowed_roles = {UserRole.GLOBAL_CURATOR, UserRole.CURATOR, UserRole.ADMIN}
if user.role not in allowed_roles:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User is not a curator or admin.",
)
@@ -688,8 +712,7 @@ async def current_admin_user(user: User | None = Depends(current_user)) -> User
return None
if not user or not hasattr(user, "role") or user.role != UserRole.ADMIN:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
raise BasicAuthenticationError(
detail="Access denied. User must be an admin to perform this action.",
)
@@ -717,8 +740,6 @@ def generate_state_token(
# refer to https://github.com/fastapi-users/fastapi-users/blob/42ddc241b965475390e2bce887b084152ae1a2cd/fastapi_users/fastapi_users.py#L91
def create_danswer_oauth_router(
oauth_client: BaseOAuth2,
backend: AuthenticationBackend,
@@ -768,15 +789,22 @@ def get_oauth_router(
response_model=OAuth2AuthorizeResponse,
)
async def authorize(
request: Request, scopes: List[str] = Query(None)
request: Request,
scopes: List[str] = Query(None),
) -> OAuth2AuthorizeResponse:
referral_source = request.cookies.get("referral_source", None)
if redirect_url is not None:
authorize_redirect_url = redirect_url
else:
authorize_redirect_url = str(request.url_for(callback_route_name))
next_url = request.query_params.get("next", "/")
state_data: Dict[str, str] = {"next_url": next_url}
state_data: Dict[str, str] = {
"next_url": next_url,
"referral_source": referral_source or "default_referral",
}
state = generate_state_token(state_data, state_secret)
authorization_url = await oauth_client.get_authorization_url(
authorize_redirect_url,
@@ -835,8 +863,11 @@ def get_oauth_router(
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST)
next_url = state_data.get("next_url", "/")
referral_source = state_data.get("referral_source", None)
# Authenticate user
request.state.referral_source = referral_source
# Proceed to authenticate or create the user
try:
user = await user_manager.oauth_callback(
oauth_client.name,
@@ -878,7 +909,25 @@ def get_oauth_router(
redirect_response.status_code = response.status_code
if hasattr(response, "media_type"):
redirect_response.media_type = response.media_type
return redirect_response
return router
async def api_key_dep(
request: Request, async_db_session: AsyncSession = Depends(get_async_session)
) -> User | None:
if AUTH_TYPE == AuthType.DISABLED:
return None
hashed_api_key = get_hashed_api_key_from_request(request)
if not hashed_api_key:
raise HTTPException(status_code=401, detail="Missing API key")
if hashed_api_key:
user = await fetch_user_for_api_key(hashed_api_key, async_db_session)
if user is None:
raise HTTPException(status_code=401, detail="Invalid API key")
return user

View File

@@ -3,6 +3,7 @@ import multiprocessing
import time
from typing import Any
import requests
import sentry_sdk
from celery import Task
from celery.app import trace
@@ -10,24 +11,32 @@ from celery.exceptions import WorkerShutdown
from celery.states import READY_STATES
from celery.utils.log import get_task_logger
from celery.worker import strategy # type: ignore
from redis.lock import Lock as RedisLock
from sentry_sdk.integrations.celery import CeleryIntegration
from sqlalchemy import text
from sqlalchemy.orm import Session
from danswer.background.celery.apps.task_formatters import CeleryTaskColoredFormatter
from danswer.background.celery.apps.task_formatters import CeleryTaskPlainFormatter
from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorPruning
from danswer.background.celery.celery_redis import RedisDocumentSet
from danswer.background.celery.celery_redis import RedisUserGroup
from danswer.background.celery.celery_utils import celery_is_worker_primary
from danswer.configs.constants import DanswerRedisLocks
from danswer.db.engine import get_all_tenant_ids
from danswer.db.engine import get_sqlalchemy_engine
from danswer.document_index.vespa_constants import VESPA_CONFIG_SERVER_URL
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
from danswer.redis.redis_connector_delete import RedisConnectorDelete
from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
from danswer.redis.redis_connector_ext_group_sync import RedisConnectorExternalGroupSync
from danswer.redis.redis_connector_prune import RedisConnectorPrune
from danswer.redis.redis_document_set import RedisDocumentSet
from danswer.redis.redis_pool import get_redis_client
from danswer.redis.redis_usergroup import RedisUserGroup
from danswer.utils.logger import ColoredFormatter
from danswer.utils.logger import PlainFormatter
from danswer.utils.logger import setup_logger
from shared_configs.configs import SENTRY_DSN
logger = setup_logger()
task_logger = get_task_logger(__name__)
@@ -36,7 +45,7 @@ if SENTRY_DSN:
sentry_sdk.init(
dsn=SENTRY_DSN,
integrations=[CeleryIntegration()],
traces_sample_rate=0.5,
traces_sample_rate=0.1,
)
logger.info("Sentry initialized")
else:
@@ -107,29 +116,43 @@ def on_task_postrun(
if task_id.startswith(RedisDocumentSet.PREFIX):
document_set_id = RedisDocumentSet.get_id_from_task_id(task_id)
if document_set_id is not None:
rds = RedisDocumentSet(int(document_set_id))
rds = RedisDocumentSet(tenant_id, int(document_set_id))
r.srem(rds.taskset_key, task_id)
return
if task_id.startswith(RedisUserGroup.PREFIX):
usergroup_id = RedisUserGroup.get_id_from_task_id(task_id)
if usergroup_id is not None:
rug = RedisUserGroup(int(usergroup_id))
rug = RedisUserGroup(tenant_id, int(usergroup_id))
r.srem(rug.taskset_key, task_id)
return
if task_id.startswith(RedisConnectorDeletion.PREFIX):
cc_pair_id = RedisConnectorDeletion.get_id_from_task_id(task_id)
if task_id.startswith(RedisConnectorDelete.PREFIX):
cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
if cc_pair_id is not None:
rcd = RedisConnectorDeletion(int(cc_pair_id))
r.srem(rcd.taskset_key, task_id)
RedisConnectorDelete.remove_from_taskset(int(cc_pair_id), task_id, r)
return
if task_id.startswith(RedisConnectorPruning.SUBTASK_PREFIX):
cc_pair_id = RedisConnectorPruning.get_id_from_task_id(task_id)
if task_id.startswith(RedisConnectorPrune.SUBTASK_PREFIX):
cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
if cc_pair_id is not None:
rcp = RedisConnectorPruning(int(cc_pair_id))
r.srem(rcp.taskset_key, task_id)
RedisConnectorPrune.remove_from_taskset(int(cc_pair_id), task_id, r)
return
if task_id.startswith(RedisConnectorPermissionSync.SUBTASK_PREFIX):
cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
if cc_pair_id is not None:
RedisConnectorPermissionSync.remove_from_taskset(
int(cc_pair_id), task_id, r
)
return
if task_id.startswith(RedisConnectorExternalGroupSync.SUBTASK_PREFIX):
cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
if cc_pair_id is not None:
RedisConnectorExternalGroupSync.remove_from_taskset(
int(cc_pair_id), task_id, r
)
return
@@ -139,77 +162,154 @@ def on_celeryd_init(sender: Any = None, conf: Any = None, **kwargs: Any) -> None
def wait_for_redis(sender: Any, **kwargs: Any) -> None:
"""Waits for redis to become ready subject to a hardcoded timeout.
Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
r = get_redis_client(tenant_id=None)
WAIT_INTERVAL = 5
WAIT_LIMIT = 60
ready = False
time_start = time.monotonic()
logger.info("Redis: Readiness check starting.")
logger.info("Redis: Readiness probe starting.")
while True:
try:
if r.ping():
ready = True
break
except Exception:
pass
time_elapsed = time.monotonic() - time_start
logger.info(
f"Redis: Ping failed. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
)
if time_elapsed > WAIT_LIMIT:
msg = (
f"Redis: Readiness check did not succeed within the timeout "
f"({WAIT_LIMIT} seconds). Exiting..."
)
logger.error(msg)
raise WorkerShutdown(msg)
break
logger.info(
f"Redis: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
)
time.sleep(WAIT_INTERVAL)
logger.info("Redis: Readiness check succeeded. Continuing...")
if not ready:
msg = (
f"Redis: Readiness probe did not succeed within the timeout "
f"({WAIT_LIMIT} seconds). Exiting..."
)
logger.error(msg)
raise WorkerShutdown(msg)
logger.info("Redis: Readiness probe succeeded. Continuing...")
return
def wait_for_db(sender: Any, **kwargs: Any) -> None:
"""Waits for the db to become ready subject to a hardcoded timeout.
Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
WAIT_INTERVAL = 5
WAIT_LIMIT = 60
ready = False
time_start = time.monotonic()
logger.info("Database: Readiness probe starting.")
while True:
try:
with Session(get_sqlalchemy_engine()) as db_session:
result = db_session.execute(text("SELECT NOW()")).scalar()
if result:
ready = True
break
except Exception:
pass
time_elapsed = time.monotonic() - time_start
if time_elapsed > WAIT_LIMIT:
break
logger.info(
f"Database: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
)
time.sleep(WAIT_INTERVAL)
if not ready:
msg = (
f"Database: Readiness probe did not succeed within the timeout "
f"({WAIT_LIMIT} seconds). Exiting..."
)
logger.error(msg)
raise WorkerShutdown(msg)
logger.info("Database: Readiness probe succeeded. Continuing...")
return
def wait_for_vespa(sender: Any, **kwargs: Any) -> None:
"""Waits for Vespa to become ready subject to a hardcoded timeout.
Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
WAIT_INTERVAL = 5
WAIT_LIMIT = 60
ready = False
time_start = time.monotonic()
logger.info("Vespa: Readiness probe starting.")
while True:
try:
response = requests.get(f"{VESPA_CONFIG_SERVER_URL}/state/v1/health")
response.raise_for_status()
response_dict = response.json()
if response_dict["status"]["code"] == "up":
ready = True
break
except Exception:
pass
time_elapsed = time.monotonic() - time_start
if time_elapsed > WAIT_LIMIT:
break
logger.info(
f"Vespa: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
)
time.sleep(WAIT_INTERVAL)
if not ready:
msg = (
f"Vespa: Readiness probe did not succeed within the timeout "
f"({WAIT_LIMIT} seconds). Exiting..."
)
logger.error(msg)
raise WorkerShutdown(msg)
logger.info("Vespa: Readiness probe succeeded. Continuing...")
return
def on_secondary_worker_init(sender: Any, **kwargs: Any) -> None:
logger.info("Running as a secondary celery worker.")
# Set up variables for waiting on primary worker
WAIT_INTERVAL = 5
WAIT_LIMIT = 60
logger.info("Running as a secondary celery worker.")
logger.info("Waiting for all tenant primary workers to be ready...")
r = get_redis_client(tenant_id=None)
time_start = time.monotonic()
logger.info("Waiting for primary worker to be ready...")
while True:
tenant_ids = get_all_tenant_ids()
# Check if we have a primary worker lock for each tenant
all_tenants_ready = all(
get_redis_client(tenant_id=tenant_id).exists(
DanswerRedisLocks.PRIMARY_WORKER
)
for tenant_id in tenant_ids
)
if all_tenants_ready:
if r.exists(DanswerRedisLocks.PRIMARY_WORKER):
break
time_elapsed = time.monotonic() - time_start
ready_tenants = sum(
1
for tenant_id in tenant_ids
if get_redis_client(tenant_id=tenant_id).exists(
DanswerRedisLocks.PRIMARY_WORKER
)
)
logger.info(
f"Not all tenant primary workers are ready yet. "
f"Ready tenants: {ready_tenants}/{len(tenant_ids)} "
f"elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
f"Primary worker is not ready yet. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
)
if time_elapsed > WAIT_LIMIT:
msg = (
f"Not all tenant primary workers were ready within the timeout "
f"Primary worker was not ready within the timeout. "
f"({WAIT_LIMIT} seconds). Exiting..."
)
logger.error(msg)
@@ -217,7 +317,7 @@ def on_secondary_worker_init(sender: Any, **kwargs: Any) -> None:
time.sleep(WAIT_INTERVAL)
logger.info("All tenant primary workers are ready. Continuing...")
logger.info("Wait for primary worker completed successfully. Continuing...")
return
@@ -229,26 +329,20 @@ def on_worker_shutdown(sender: Any, **kwargs: Any) -> None:
if not celery_is_worker_primary(sender):
return
if not hasattr(sender, "primary_worker_locks"):
if not sender.primary_worker_lock:
return
for tenant_id, lock in sender.primary_worker_locks.items():
try:
if lock and lock.owned():
logger.debug(f"Attempting to release lock for tenant {tenant_id}")
try:
lock.release()
logger.debug(f"Successfully released lock for tenant {tenant_id}")
except Exception as e:
logger.error(
f"Failed to release lock for tenant {tenant_id}. Error: {str(e)}"
)
finally:
sender.primary_worker_locks[tenant_id] = None
except Exception as e:
logger.error(
f"Error checking lock status for tenant {tenant_id}. Error: {str(e)}"
)
logger.info("Releasing primary worker lock.")
lock: RedisLock = sender.primary_worker_lock
try:
if lock.owned():
try:
lock.release()
sender.primary_worker_lock = None
except Exception:
logger.exception("Failed to release primary worker lock")
except Exception:
logger.exception("Failed to check if primary worker lock is owned")
def on_setup_logging(

View File

@@ -3,26 +3,162 @@ from typing import Any
from celery import Celery
from celery import signals
from celery.beat import PersistentScheduler # type: ignore
from celery.signals import beat_init
import danswer.background.celery.apps.app_base as app_base
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import POSTGRES_CELERY_BEAT_APP_NAME
from danswer.db.engine import get_all_tenant_ids
from danswer.db.engine import SqlEngine
from danswer.utils.logger import setup_logger
from danswer.utils.variable_functionality import fetch_versioned_implementation
from shared_configs.configs import IGNORED_SYNCING_TENANT_LIST
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
logger = setup_logger(__name__)
celery_app = Celery(__name__)
celery_app.config_from_object("danswer.background.celery.configs.beat")
class DynamicTenantScheduler(PersistentScheduler):
def __init__(self, *args: Any, **kwargs: Any) -> None:
logger.info("Initializing DynamicTenantScheduler")
super().__init__(*args, **kwargs)
self._reload_interval = timedelta(minutes=2)
self._last_reload = self.app.now() - self._reload_interval
# Let the parent class handle store initialization
self.setup_schedule()
self._update_tenant_tasks()
logger.info(f"Set reload interval to {self._reload_interval}")
def setup_schedule(self) -> None:
logger.info("Setting up initial schedule")
super().setup_schedule()
logger.info("Initial schedule setup complete")
def tick(self) -> float:
retval = super().tick()
now = self.app.now()
if (
self._last_reload is None
or (now - self._last_reload) > self._reload_interval
):
logger.info("Reload interval reached, initiating tenant task update")
self._update_tenant_tasks()
self._last_reload = now
logger.info("Tenant task update completed, reset reload timer")
return retval
def _update_tenant_tasks(self) -> None:
logger.info("Starting tenant task update process")
try:
logger.info("Fetching all tenant IDs")
tenant_ids = get_all_tenant_ids()
logger.info(f"Found {len(tenant_ids)} tenants")
logger.info("Fetching tasks to schedule")
tasks_to_schedule = fetch_versioned_implementation(
"danswer.background.celery.tasks.beat_schedule", "get_tasks_to_schedule"
)
new_beat_schedule: dict[str, dict[str, Any]] = {}
current_schedule = self.schedule.items()
existing_tenants = set()
for task_name, _ in current_schedule:
if "-" in task_name:
existing_tenants.add(task_name.split("-")[-1])
logger.info(f"Found {len(existing_tenants)} existing tenants in schedule")
for tenant_id in tenant_ids:
if (
IGNORED_SYNCING_TENANT_LIST
and tenant_id in IGNORED_SYNCING_TENANT_LIST
):
logger.info(
f"Skipping tenant {tenant_id} as it is in the ignored syncing list"
)
continue
if tenant_id not in existing_tenants:
logger.info(f"Processing new tenant: {tenant_id}")
for task in tasks_to_schedule():
task_name = f"{task['name']}-{tenant_id}"
logger.debug(f"Creating task configuration for {task_name}")
new_task = {
"task": task["task"],
"schedule": task["schedule"],
"kwargs": {"tenant_id": tenant_id},
}
if options := task.get("options"):
logger.debug(f"Adding options to task {task_name}: {options}")
new_task["options"] = options
new_beat_schedule[task_name] = new_task
if self._should_update_schedule(current_schedule, new_beat_schedule):
logger.info(
"Schedule update required",
extra={
"new_tasks": len(new_beat_schedule),
"current_tasks": len(current_schedule),
},
)
# Create schedule entries
entries = {}
for name, entry in new_beat_schedule.items():
entries[name] = self.Entry(
name=name,
app=self.app,
task=entry["task"],
schedule=entry["schedule"],
options=entry.get("options", {}),
kwargs=entry.get("kwargs", {}),
)
# Update the schedule using the scheduler's methods
self.schedule.clear()
self.schedule.update(entries)
# Ensure changes are persisted
self.sync()
logger.info("Schedule update completed successfully")
else:
logger.info("Schedule is up to date, no changes needed")
except (AttributeError, KeyError):
logger.exception("Failed to process task configuration")
except Exception:
logger.exception("Unexpected error updating tenant tasks")
def _should_update_schedule(
self, current_schedule: dict, new_schedule: dict
) -> bool:
"""Compare schedules to determine if an update is needed."""
logger.debug("Comparing current and new schedules")
current_tasks = set(name for name, _ in current_schedule)
new_tasks = set(new_schedule.keys())
needs_update = current_tasks != new_tasks
logger.debug(f"Schedule update needed: {needs_update}")
return needs_update
@beat_init.connect
def on_beat_init(sender: Any, **kwargs: Any) -> None:
logger.info("beat_init signal received.")
# Celery beat shouldn't touch the db at all. But just setting a low minimum here.
SqlEngine.set_app_name(POSTGRES_CELERY_BEAT_APP_NAME)
SqlEngine.init_engine(pool_size=2, max_overflow=0)
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
@@ -33,67 +169,4 @@ def on_setup_logging(
app_base.on_setup_logging(loglevel, logfile, format, colorize, **kwargs)
#####
# Celery Beat (Periodic Tasks) Settings
#####
tenant_ids = get_all_tenant_ids()
tasks_to_schedule = [
{
"name": "check-for-vespa-sync",
"task": "check_for_vespa_sync_task",
"schedule": timedelta(seconds=5),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-connector-deletion",
"task": "check_for_connector_deletion_task",
"schedule": timedelta(seconds=60),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-indexing",
"task": "check_for_indexing",
"schedule": timedelta(seconds=10),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-prune",
"task": "check_for_pruning",
"schedule": timedelta(seconds=10),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "kombu-message-cleanup",
"task": "kombu_message_cleanup_task",
"schedule": timedelta(seconds=3600),
"options": {"priority": DanswerCeleryPriority.LOWEST},
},
{
"name": "monitor-vespa-sync",
"task": "monitor_vespa_sync",
"schedule": timedelta(seconds=5),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
]
# Build the celery beat schedule dynamically
beat_schedule = {}
for tenant_id in tenant_ids:
for task in tasks_to_schedule:
task_name = f"{task['name']}-{tenant_id}" # Unique name for each scheduled task
beat_schedule[task_name] = {
"task": task["task"],
"schedule": task["schedule"],
"options": task["options"],
"kwargs": {"tenant_id": tenant_id}, # Must pass tenant_id as an argument
}
# Include any existing beat schedules
existing_beat_schedule = celery_app.conf.beat_schedule or {}
beat_schedule.update(existing_beat_schedule)
# Update the Celery app configuration once
celery_app.conf.beat_schedule = beat_schedule
celery_app.conf.beat_scheduler = DynamicTenantScheduler

View File

@@ -13,6 +13,7 @@ import danswer.background.celery.apps.app_base as app_base
from danswer.configs.constants import POSTGRES_CELERY_WORKER_HEAVY_APP_NAME
from danswer.db.engine import SqlEngine
from danswer.utils.logger import setup_logger
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
@@ -58,9 +59,15 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
logger.info(f"Multiprocessing start method: {multiprocessing.get_start_method()}")
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_HEAVY_APP_NAME)
SqlEngine.init_engine(pool_size=8, max_overflow=0)
SqlEngine.init_engine(pool_size=4, max_overflow=12)
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
app_base.wait_for_db(sender, **kwargs)
app_base.wait_for_vespa(sender, **kwargs)
app_base.on_secondary_worker_init(sender, **kwargs)
@@ -84,5 +91,7 @@ def on_setup_logging(
celery_app.autodiscover_tasks(
[
"danswer.background.celery.tasks.pruning",
"danswer.background.celery.tasks.doc_permission_syncing",
"danswer.background.celery.tasks.external_group_syncing",
]
)

View File

@@ -6,20 +6,15 @@ from celery import signals
from celery import Task
from celery.signals import celeryd_init
from celery.signals import worker_init
from celery.signals import worker_process_init
from celery.signals import worker_ready
from celery.signals import worker_shutdown
from sqlalchemy.orm import Session
import danswer.background.celery.apps.app_base as app_base
from danswer.configs.constants import POSTGRES_CELERY_WORKER_INDEXING_APP_NAME
from danswer.db.engine import SqlEngine
from danswer.db.search_settings import get_current_search_settings
from danswer.db.swap_index import check_index_swap
from danswer.natural_language_processing.search_nlp_models import EmbeddingModel
from danswer.natural_language_processing.search_nlp_models import warm_up_bi_encoder
from danswer.utils.logger import setup_logger
from shared_configs.configs import INDEXING_MODEL_SERVER_HOST
from shared_configs.configs import MODEL_SERVER_PORT
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
@@ -65,30 +60,15 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
logger.info(f"Multiprocessing start method: {multiprocessing.get_start_method()}")
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_APP_NAME)
SqlEngine.init_engine(pool_size=8, max_overflow=0)
SqlEngine.init_engine(pool_size=sender.concurrency, max_overflow=sender.concurrency)
# TODO: why is this necessary for the indexer to do?
engine = SqlEngine.get_engine()
with Session(engine) as db_session:
check_index_swap(db_session=db_session)
search_settings = get_current_search_settings(db_session)
# So that the first time users aren't surprised by really slow speed of first
# batch of documents indexed
if search_settings.provider_type is None:
logger.notice("Running a first inference to warm up embedding model")
embedding_model = EmbeddingModel.from_db_model(
search_settings=search_settings,
server_host=INDEXING_MODEL_SERVER_HOST,
server_port=MODEL_SERVER_PORT,
)
warm_up_bi_encoder(
embedding_model=embedding_model,
)
logger.notice("First inference complete.")
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
app_base.wait_for_db(sender, **kwargs)
app_base.wait_for_vespa(sender, **kwargs)
app_base.on_secondary_worker_init(sender, **kwargs)
@@ -102,6 +82,11 @@ def on_worker_shutdown(sender: Any, **kwargs: Any) -> None:
app_base.on_worker_shutdown(sender, **kwargs)
@worker_process_init.connect
def init_worker(**kwargs: Any) -> None:
SqlEngine.reset_engine()
@signals.setup_logging.connect
def on_setup_logging(
loglevel: Any, logfile: Any, format: Any, colorize: Any, **kwargs: Any

View File

@@ -13,6 +13,7 @@ import danswer.background.celery.apps.app_base as app_base
from danswer.configs.constants import POSTGRES_CELERY_WORKER_LIGHT_APP_NAME
from danswer.db.engine import SqlEngine
from danswer.utils.logger import setup_logger
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
@@ -59,8 +60,13 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_LIGHT_APP_NAME)
SqlEngine.init_engine(pool_size=sender.concurrency, max_overflow=8)
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
app_base.wait_for_db(sender, **kwargs)
app_base.wait_for_vespa(sender, **kwargs)
app_base.on_secondary_worker_init(sender, **kwargs)
@@ -85,5 +91,7 @@ celery_app.autodiscover_tasks(
[
"danswer.background.celery.tasks.shared",
"danswer.background.celery.tasks.vespa",
"danswer.background.celery.tasks.connector_deletion",
"danswer.background.celery.tasks.doc_permission_syncing",
]
)

View File

@@ -1,5 +1,6 @@
import multiprocessing
from typing import Any
from typing import cast
from celery import bootsteps # type: ignore
from celery import Celery
@@ -10,25 +11,33 @@ from celery.signals import celeryd_init
from celery.signals import worker_init
from celery.signals import worker_ready
from celery.signals import worker_shutdown
from redis.lock import Lock as RedisLock
import danswer.background.celery.apps.app_base as app_base
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorIndexing
from danswer.background.celery.celery_redis import RedisConnectorPruning
from danswer.background.celery.celery_redis import RedisConnectorStop
from danswer.background.celery.celery_redis import RedisDocumentSet
from danswer.background.celery.celery_redis import RedisUserGroup
from danswer.background.celery.celery_utils import celery_is_worker_primary
from danswer.background.celery.tasks.indexing.tasks import (
get_unfenced_index_attempt_ids,
)
from danswer.configs.constants import CELERY_PRIMARY_WORKER_LOCK_TIMEOUT
from danswer.configs.constants import DanswerRedisLocks
from danswer.configs.constants import POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME
from danswer.db.engine import get_all_tenant_ids
from danswer.db.engine import get_session_with_default_tenant
from danswer.db.engine import SqlEngine
from danswer.db.index_attempt import get_index_attempt
from danswer.db.index_attempt import mark_attempt_canceled
from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
from danswer.redis.redis_connector_delete import RedisConnectorDelete
from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
from danswer.redis.redis_connector_ext_group_sync import RedisConnectorExternalGroupSync
from danswer.redis.redis_connector_index import RedisConnectorIndex
from danswer.redis.redis_connector_prune import RedisConnectorPrune
from danswer.redis.redis_connector_stop import RedisConnectorStop
from danswer.redis.redis_document_set import RedisDocumentSet
from danswer.redis.redis_pool import get_redis_client
from danswer.redis.redis_usergroup import RedisUserGroup
from danswer.utils.logger import setup_logger
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
@@ -75,108 +84,98 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME)
SqlEngine.init_engine(pool_size=8, max_overflow=0)
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
app_base.wait_for_db(sender, **kwargs)
app_base.wait_for_vespa(sender, **kwargs)
logger.info("Running as the primary celery worker.")
sender.primary_worker_locks = {}
# This is singleton work that should be done on startup exactly once
# by the primary worker
tenant_ids = get_all_tenant_ids()
for tenant_id in tenant_ids:
r = get_redis_client(tenant_id=tenant_id)
# by the primary worker. This is unnecessary in the multi tenant scenario
r = get_redis_client(tenant_id=None)
# For the moment, we're assuming that we are the only primary worker
# that should be running.
# TODO: maybe check for or clean up another zombie primary worker if we detect it
r.delete(DanswerRedisLocks.PRIMARY_WORKER)
# Log the role and slave count - being connected to a slave or slave count > 0 could be problematic
info: dict[str, Any] = cast(dict, r.info("replication"))
role: str = cast(str, info.get("role"))
connected_slaves: int = info.get("connected_slaves", 0)
# this process wide lock is taken to help other workers start up in order.
# it is planned to use this lock to enforce singleton behavior on the primary
# worker, since the primary worker does redis cleanup on startup, but this isn't
# implemented yet.
lock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
)
logger.info(
f"Redis INFO REPLICATION: role={role} connected_slaves={connected_slaves}"
)
logger.info("Primary worker lock: Acquire starting.")
acquired = lock.acquire(blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2)
if acquired:
logger.info("Primary worker lock: Acquire succeeded.")
else:
logger.error("Primary worker lock: Acquire failed!")
raise WorkerShutdown("Primary worker lock could not be acquired!")
# For the moment, we're assuming that we are the only primary worker
# that should be running.
# TODO: maybe check for or clean up another zombie primary worker if we detect it
r.delete(DanswerRedisLocks.PRIMARY_WORKER)
# tacking on our own user data to the sender
sender.primary_worker_locks[tenant_id] = lock
# this process wide lock is taken to help other workers start up in order.
# it is planned to use this lock to enforce singleton behavior on the primary
# worker, since the primary worker does redis cleanup on startup, but this isn't
# implemented yet.
# As currently designed, when this worker starts as "primary", we reinitialize redis
# to a clean state (for our purposes, anyway)
r.delete(DanswerRedisLocks.CHECK_VESPA_SYNC_BEAT_LOCK)
r.delete(DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK)
# set thread_local=False since we don't control what thread the periodic task might
# reacquire the lock with
lock: RedisLock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
thread_local=False,
)
r.delete(RedisConnectorCredentialPair.get_taskset_key())
r.delete(RedisConnectorCredentialPair.get_fence_key())
logger.info("Primary worker lock: Acquire starting.")
acquired = lock.acquire(blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2)
if acquired:
logger.info("Primary worker lock: Acquire succeeded.")
else:
logger.error("Primary worker lock: Acquire failed!")
raise WorkerShutdown("Primary worker lock could not be acquired!")
for key in r.scan_iter(RedisDocumentSet.TASKSET_PREFIX + "*"):
r.delete(key)
# tacking on our own user data to the sender
sender.primary_worker_lock = lock
for key in r.scan_iter(RedisDocumentSet.FENCE_PREFIX + "*"):
r.delete(key)
# As currently designed, when this worker starts as "primary", we reinitialize redis
# to a clean state (for our purposes, anyway)
r.delete(DanswerRedisLocks.CHECK_VESPA_SYNC_BEAT_LOCK)
r.delete(DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK)
for key in r.scan_iter(RedisUserGroup.TASKSET_PREFIX + "*"):
r.delete(key)
r.delete(RedisConnectorCredentialPair.get_taskset_key())
r.delete(RedisConnectorCredentialPair.get_fence_key())
for key in r.scan_iter(RedisUserGroup.FENCE_PREFIX + "*"):
r.delete(key)
RedisDocumentSet.reset_all(r)
for key in r.scan_iter(RedisConnectorDeletion.TASKSET_PREFIX + "*"):
r.delete(key)
RedisUserGroup.reset_all(r)
for key in r.scan_iter(RedisConnectorDeletion.FENCE_PREFIX + "*"):
r.delete(key)
RedisConnectorDelete.reset_all(r)
for key in r.scan_iter(RedisConnectorPruning.TASKSET_PREFIX + "*"):
r.delete(key)
RedisConnectorPrune.reset_all(r)
for key in r.scan_iter(RedisConnectorPruning.GENERATOR_COMPLETE_PREFIX + "*"):
r.delete(key)
RedisConnectorIndex.reset_all(r)
for key in r.scan_iter(RedisConnectorPruning.GENERATOR_PROGRESS_PREFIX + "*"):
r.delete(key)
RedisConnectorStop.reset_all(r)
for key in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
r.delete(key)
RedisConnectorPermissionSync.reset_all(r)
for key in r.scan_iter(RedisConnectorIndexing.TASKSET_PREFIX + "*"):
r.delete(key)
RedisConnectorExternalGroupSync.reset_all(r)
for key in r.scan_iter(RedisConnectorIndexing.GENERATOR_COMPLETE_PREFIX + "*"):
r.delete(key)
# mark orphaned index attempts as failed
with get_session_with_default_tenant() as db_session:
unfenced_attempt_ids = get_unfenced_index_attempt_ids(db_session, r)
for attempt_id in unfenced_attempt_ids:
attempt = get_index_attempt(db_session, attempt_id)
if not attempt:
continue
for key in r.scan_iter(RedisConnectorIndexing.GENERATOR_PROGRESS_PREFIX + "*"):
r.delete(key)
for key in r.scan_iter(RedisConnectorIndexing.FENCE_PREFIX + "*"):
r.delete(key)
for key in r.scan_iter(RedisConnectorStop.FENCE_PREFIX + "*"):
r.delete(key)
# @worker_process_init.connect
# def on_worker_process_init(sender: Any, **kwargs: Any) -> None:
# """This only runs inside child processes when the worker is in pool=prefork mode.
# This may be technically unnecessary since we're finding prefork pools to be
# unstable and currently aren't planning on using them."""
# logger.info("worker_process_init signal received.")
# SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_CHILD_APP_NAME)
# SqlEngine.init_engine(pool_size=5, max_overflow=0)
# # https://stackoverflow.com/questions/43944787/sqlalchemy-celery-with-scoped-session-error
# SqlEngine.get_engine().dispose(close=False)
failure_reason = (
f"Canceling leftover index attempt found on startup: "
f"index_attempt={attempt.id} "
f"cc_pair={attempt.connector_credential_pair_id} "
f"search_settings={attempt.search_settings_id}"
)
logger.warning(failure_reason)
mark_attempt_canceled(attempt.id, db_session, failure_reason)
@worker_ready.connect
@@ -229,52 +228,36 @@ class HubPeriodicTask(bootsteps.StartStopStep):
if not celery_is_worker_primary(worker):
return
if not hasattr(worker, "primary_worker_locks"):
if not hasattr(worker, "primary_worker_lock"):
return
# Retrieve all tenant IDs
tenant_ids = get_all_tenant_ids()
lock: RedisLock = worker.primary_worker_lock
for tenant_id in tenant_ids:
lock = worker.primary_worker_locks.get(tenant_id)
if not lock:
continue # Skip if no lock for this tenant
r = get_redis_client(tenant_id=None)
r = get_redis_client(tenant_id=tenant_id)
if lock.owned():
task_logger.debug("Reacquiring primary worker lock.")
lock.reacquire()
else:
task_logger.warning(
"Full acquisition of primary worker lock. "
"Reasons could be worker restart or lock expiration."
)
lock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
)
if lock.owned():
task_logger.debug(
f"Reacquiring primary worker lock for tenant {tenant_id}."
)
lock.reacquire()
task_logger.info("Primary worker lock: Acquire starting.")
acquired = lock.acquire(
blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2
)
if acquired:
task_logger.info("Primary worker lock: Acquire succeeded.")
worker.primary_worker_lock = lock
else:
task_logger.warning(
f"Full acquisition of primary worker lock for tenant {tenant_id}. "
"Reasons could be worker restart or lock expiration."
)
lock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
)
task_logger.info(
f"Primary worker lock for tenant {tenant_id}: Acquire starting."
)
acquired = lock.acquire(
blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2
)
if acquired:
task_logger.info(
f"Primary worker lock for tenant {tenant_id}: Acquire succeeded."
)
worker.primary_worker_locks[tenant_id] = lock
else:
task_logger.error(
f"Primary worker lock for tenant {tenant_id}: Acquire failed!"
)
raise TimeoutError(
f"Primary worker lock for tenant {tenant_id} could not be acquired!"
)
task_logger.error("Primary worker lock: Acquire failed!")
raise TimeoutError("Primary worker lock could not be acquired!")
except Exception:
task_logger.exception("Periodic task failed.")
@@ -293,6 +276,8 @@ celery_app.autodiscover_tasks(
"danswer.background.celery.tasks.connector_deletion",
"danswer.background.celery.tasks.indexing",
"danswer.background.celery.tasks.periodic",
"danswer.background.celery.tasks.doc_permission_syncing",
"danswer.background.celery.tasks.external_group_syncing",
"danswer.background.celery.tasks.pruning",
"danswer.background.celery.tasks.shared",
"danswer.background.celery.tasks.vespa",

View File

@@ -1,568 +1,10 @@
# These are helper objects for tracking the keys we need to write in redis
import time
from abc import ABC
from abc import abstractmethod
from typing import cast
from uuid import uuid4
import redis
from celery import Celery
from redis import Redis
from sqlalchemy.orm import Session
from danswer.background.celery.configs.base import CELERY_SEPARATOR
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryQueues
from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
from danswer.db.document import construct_document_select_for_connector_credential_pair
from danswer.db.document import (
construct_document_select_for_connector_credential_pair_by_needs_sync,
)
from danswer.db.document_set import construct_document_select_by_docset
from danswer.utils.variable_functionality import fetch_versioned_implementation
from danswer.utils.variable_functionality import global_version
class RedisObjectHelper(ABC):
PREFIX = "base"
FENCE_PREFIX = PREFIX + "_fence"
TASKSET_PREFIX = PREFIX + "_taskset"
def __init__(self, id: str):
self._id: str = id
@property
def task_id_prefix(self) -> str:
return f"{self.PREFIX}_{self._id}"
@property
def fence_key(self) -> str:
# example: documentset_fence_1
return f"{self.FENCE_PREFIX}_{self._id}"
@property
def taskset_key(self) -> str:
# example: documentset_taskset_1
return f"{self.TASKSET_PREFIX}_{self._id}"
@staticmethod
def get_id_from_fence_key(key: str) -> str | None:
"""
Extracts the object ID from a fence key in the format `PREFIX_fence_X`.
Args:
key (str): The fence key string.
Returns:
Optional[int]: The extracted ID if the key is in the correct format, otherwise None.
"""
parts = key.split("_")
if len(parts) != 3:
return None
object_id = parts[2]
return object_id
@staticmethod
def get_id_from_task_id(task_id: str) -> str | None:
"""
Extracts the object ID from a task ID string.
This method assumes the task ID is formatted as `prefix_objectid_suffix`, where:
- `prefix` is an arbitrary string (e.g., the name of the task or entity),
- `objectid` is the ID you want to extract,
- `suffix` is another arbitrary string (e.g., a UUID).
Example:
If the input `task_id` is `documentset_1_cbfdc96a-80ca-4312-a242-0bb68da3c1dc`,
this method will return the string `"1"`.
Args:
task_id (str): The task ID string from which to extract the object ID.
Returns:
str | None: The extracted object ID if the task ID is in the correct format, otherwise None.
"""
# example: task_id=documentset_1_cbfdc96a-80ca-4312-a242-0bb68da3c1dc
parts = task_id.split("_")
if len(parts) != 3:
return None
object_id = parts[1]
return object_id
@abstractmethod
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock,
tenant_id: str | None,
) -> int | None:
pass
class RedisDocumentSet(RedisObjectHelper):
PREFIX = "documentset"
FENCE_PREFIX = PREFIX + "_fence"
TASKSET_PREFIX = PREFIX + "_taskset"
def __init__(self, id: int) -> None:
super().__init__(str(id))
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock,
tenant_id: str | None,
) -> int | None:
last_lock_time = time.monotonic()
async_results = []
stmt = construct_document_select_by_docset(int(self._id), current_only=False)
for doc in db_session.scalars(stmt).yield_per(1):
current_time = time.monotonic()
if current_time - last_lock_time >= (
CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
):
lock.reacquire()
last_lock_time = current_time
# celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
# the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
# we prefix the task id so it's easier to keep track of who created the task
# aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
# add to the set BEFORE creating the task.
redis_client.sadd(self.taskset_key, custom_task_id)
result = celery_app.send_task(
"vespa_metadata_sync_task",
kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
task_id=custom_task_id,
priority=DanswerCeleryPriority.LOW,
)
async_results.append(result)
return len(async_results)
class RedisUserGroup(RedisObjectHelper):
PREFIX = "usergroup"
FENCE_PREFIX = PREFIX + "_fence"
TASKSET_PREFIX = PREFIX + "_taskset"
def __init__(self, id: int) -> None:
super().__init__(str(id))
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock,
tenant_id: str | None,
) -> int | None:
last_lock_time = time.monotonic()
async_results = []
if not global_version.is_ee_version():
return 0
try:
construct_document_select_by_usergroup = fetch_versioned_implementation(
"danswer.db.user_group",
"construct_document_select_by_usergroup",
)
except ModuleNotFoundError:
return 0
stmt = construct_document_select_by_usergroup(int(self._id))
for doc in db_session.scalars(stmt).yield_per(1):
current_time = time.monotonic()
if current_time - last_lock_time >= (
CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
):
lock.reacquire()
last_lock_time = current_time
# celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
# the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
# we prefix the task id so it's easier to keep track of who created the task
# aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
# add to the set BEFORE creating the task.
redis_client.sadd(self.taskset_key, custom_task_id)
result = celery_app.send_task(
"vespa_metadata_sync_task",
kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
task_id=custom_task_id,
priority=DanswerCeleryPriority.LOW,
)
async_results.append(result)
return len(async_results)
class RedisConnectorCredentialPair(RedisObjectHelper):
"""This class is used to scan documents by cc_pair in the db and collect them into
a unified set for syncing.
It differs from the other redis helpers in that the taskset used spans
all connectors and is not per connector."""
PREFIX = "connectorsync"
FENCE_PREFIX = PREFIX + "_fence"
TASKSET_PREFIX = PREFIX + "_taskset"
def __init__(self, id: int) -> None:
super().__init__(str(id))
@classmethod
def get_fence_key(cls) -> str:
return RedisConnectorCredentialPair.FENCE_PREFIX
@classmethod
def get_taskset_key(cls) -> str:
return RedisConnectorCredentialPair.TASKSET_PREFIX
@property
def taskset_key(self) -> str:
"""Notice that this is intentionally reusing the same taskset for all
connector syncs"""
# example: connector_taskset
return f"{self.TASKSET_PREFIX}"
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock,
tenant_id: str | None,
) -> int | None:
last_lock_time = time.monotonic()
async_results = []
cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
if not cc_pair:
return None
stmt = construct_document_select_for_connector_credential_pair_by_needs_sync(
cc_pair.connector_id, cc_pair.credential_id
)
for doc in db_session.scalars(stmt).yield_per(1):
current_time = time.monotonic()
if current_time - last_lock_time >= (
CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
):
lock.reacquire()
last_lock_time = current_time
# celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
# the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
# we prefix the task id so it's easier to keep track of who created the task
# aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
# add to the tracking taskset in redis BEFORE creating the celery task.
# note that for the moment we are using a single taskset key, not differentiated by cc_pair id
redis_client.sadd(
RedisConnectorCredentialPair.get_taskset_key(), custom_task_id
)
# Priority on sync's triggered by new indexing should be medium
result = celery_app.send_task(
"vespa_metadata_sync_task",
kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
task_id=custom_task_id,
priority=DanswerCeleryPriority.MEDIUM,
)
async_results.append(result)
return len(async_results)
class RedisConnectorDeletion(RedisObjectHelper):
PREFIX = "connectordeletion"
FENCE_PREFIX = PREFIX + "_fence"
TASKSET_PREFIX = PREFIX + "_taskset"
def __init__(self, id: int) -> None:
super().__init__(str(id))
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock,
tenant_id: str | None,
) -> int | None:
"""Returns None if the cc_pair doesn't exist.
Otherwise, returns an int with the number of generated tasks."""
last_lock_time = time.monotonic()
async_results = []
cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
if not cc_pair:
return None
stmt = construct_document_select_for_connector_credential_pair(
cc_pair.connector_id, cc_pair.credential_id
)
for doc in db_session.scalars(stmt).yield_per(1):
current_time = time.monotonic()
if current_time - last_lock_time >= (
CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
):
lock.reacquire()
last_lock_time = current_time
# celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
# the actual redis key is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
# we prefix the task id so it's easier to keep track of who created the task
# aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
# add to the tracking taskset in redis BEFORE creating the celery task.
# note that for the moment we are using a single taskset key, not differentiated by cc_pair id
redis_client.sadd(self.taskset_key, custom_task_id)
# Priority on sync's triggered by new indexing should be medium
result = celery_app.send_task(
"document_by_cc_pair_cleanup_task",
kwargs=dict(
document_id=doc.id,
connector_id=cc_pair.connector_id,
credential_id=cc_pair.credential_id,
tenant_id=tenant_id,
),
queue=DanswerCeleryQueues.CONNECTOR_DELETION,
task_id=custom_task_id,
priority=DanswerCeleryPriority.MEDIUM,
)
async_results.append(result)
return len(async_results)
class RedisConnectorPruning(RedisObjectHelper):
"""Celery will kick off a long running generator task to crawl the connector and
find any missing docs, which will each then get a new cleanup task. The progress of
those tasks will then be monitored to completion.
Example rough happy path order:
Check connectorpruning_fence_1
Send generator task with id connectorpruning+generator_1_{uuid}
generator runs connector with callbacks that increment connectorpruning_generator_progress_1
generator creates many subtasks with id connectorpruning+sub_1_{uuid}
in taskset connectorpruning_taskset_1
on completion, generator sets connectorpruning_generator_complete_1
celery postrun removes subtasks from taskset
monitor beat task cleans up when taskset reaches 0 items
"""
PREFIX = "connectorpruning"
FENCE_PREFIX = PREFIX + "_fence" # a fence for the entire pruning process
GENERATOR_TASK_PREFIX = PREFIX + "+generator"
TASKSET_PREFIX = PREFIX + "_taskset" # stores a list of prune tasks id's
SUBTASK_PREFIX = PREFIX + "+sub"
GENERATOR_PROGRESS_PREFIX = (
PREFIX + "_generator_progress"
) # a signal that contains generator progress
GENERATOR_COMPLETE_PREFIX = (
PREFIX + "_generator_complete"
) # a signal that the generator has finished
def __init__(self, id: int) -> None:
super().__init__(str(id))
self.documents_to_prune: set[str] = set()
@property
def generator_task_id_prefix(self) -> str:
return f"{self.GENERATOR_TASK_PREFIX}_{self._id}"
@property
def generator_progress_key(self) -> str:
# example: connectorpruning_generator_progress_1
return f"{self.GENERATOR_PROGRESS_PREFIX}_{self._id}"
@property
def generator_complete_key(self) -> str:
# example: connectorpruning_generator_complete_1
return f"{self.GENERATOR_COMPLETE_PREFIX}_{self._id}"
@property
def subtask_id_prefix(self) -> str:
return f"{self.SUBTASK_PREFIX}_{self._id}"
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock | None,
tenant_id: str | None,
) -> int | None:
last_lock_time = time.monotonic()
async_results = []
cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
if not cc_pair:
return None
for doc_id in self.documents_to_prune:
current_time = time.monotonic()
if lock and current_time - last_lock_time >= (
CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
):
lock.reacquire()
last_lock_time = current_time
# celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
# the actual redis key is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
# we prefix the task id so it's easier to keep track of who created the task
# aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
custom_task_id = f"{self.subtask_id_prefix}_{uuid4()}"
# add to the tracking taskset in redis BEFORE creating the celery task.
# note that for the moment we are using a single taskset key, not differentiated by cc_pair id
redis_client.sadd(self.taskset_key, custom_task_id)
# Priority on sync's triggered by new indexing should be medium
result = celery_app.send_task(
"document_by_cc_pair_cleanup_task",
kwargs=dict(
document_id=doc_id,
connector_id=cc_pair.connector_id,
credential_id=cc_pair.credential_id,
tenant_id=tenant_id,
),
queue=DanswerCeleryQueues.CONNECTOR_DELETION,
task_id=custom_task_id,
priority=DanswerCeleryPriority.MEDIUM,
)
async_results.append(result)
return len(async_results)
def is_pruning(self, redis_client: Redis) -> bool:
"""A single example of a helper method being refactored into the redis helper"""
if redis_client.exists(self.fence_key):
return True
return False
class RedisConnectorIndexing(RedisObjectHelper):
"""Celery will kick off a long running indexing task to crawl the connector and
find any new or updated docs docs, which will each then get a new sync task or be
indexed inline.
ID should be a concatenation of cc_pair_id and search_setting_id, delimited by "/".
e.g. "2/5"
"""
PREFIX = "connectorindexing"
FENCE_PREFIX = PREFIX + "_fence" # a fence for the entire indexing process
GENERATOR_TASK_PREFIX = PREFIX + "+generator"
TASKSET_PREFIX = PREFIX + "_taskset" # stores a list of prune tasks id's
SUBTASK_PREFIX = PREFIX + "+sub"
GENERATOR_LOCK_PREFIX = "da_lock:indexing"
GENERATOR_PROGRESS_PREFIX = (
PREFIX + "_generator_progress"
) # a signal that contains generator progress
GENERATOR_COMPLETE_PREFIX = (
PREFIX + "_generator_complete"
) # a signal that the generator has finished
def __init__(self, cc_pair_id: int, search_settings_id: int) -> None:
super().__init__(f"{cc_pair_id}/{search_settings_id}")
@property
def generator_lock_key(self) -> str:
return f"{self.GENERATOR_LOCK_PREFIX}_{self._id}"
@property
def generator_task_id_prefix(self) -> str:
return f"{self.GENERATOR_TASK_PREFIX}_{self._id}"
@property
def generator_progress_key(self) -> str:
# example: connectorpruning_generator_progress_1
return f"{self.GENERATOR_PROGRESS_PREFIX}_{self._id}"
@property
def generator_complete_key(self) -> str:
# example: connectorpruning_generator_complete_1
return f"{self.GENERATOR_COMPLETE_PREFIX}_{self._id}"
@property
def subtask_id_prefix(self) -> str:
return f"{self.SUBTASK_PREFIX}_{self._id}"
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock | None,
tenant_id: str | None,
) -> int | None:
return None
def is_indexing(self, redis_client: Redis) -> bool:
"""A single example of a helper method being refactored into the redis helper"""
if redis_client.exists(self.fence_key):
return True
return False
class RedisConnectorStop(RedisObjectHelper):
"""Used to signal any running tasks for a connector to stop. We should refactor
connector related redis helpers into a single class.
"""
PREFIX = "connectorstop"
FENCE_PREFIX = PREFIX + "_fence" # a fence for the entire indexing process
TASKSET_PREFIX = PREFIX + "_taskset" # stores a list of prune tasks id's
def __init__(self, id: int) -> None:
super().__init__(str(id))
def generate_tasks(
self,
celery_app: Celery,
db_session: Session,
redis_client: Redis,
lock: redis.lock.Lock | None,
tenant_id: str | None,
) -> int | None:
return None
def celery_get_queue_length(queue: str, r: Redis) -> int:

View File

@@ -4,8 +4,6 @@ from typing import Any
from sqlalchemy.orm import Session
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.indexing.run_indexing import RunIndexingCallbackInterface
from danswer.configs.app_configs import MAX_PRUNING_DOCUMENT_RETRIEVAL_PER_MINUTE
from danswer.connectors.cross_connector_utils.rate_limit_wrapper import (
rate_limit_builder,
@@ -18,7 +16,8 @@ from danswer.connectors.models import Document
from danswer.db.connector_credential_pair import get_connector_credential_pair
from danswer.db.enums import TaskStatus
from danswer.db.models import TaskQueueState
from danswer.redis.redis_pool import get_redis_client
from danswer.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from danswer.redis.redis_connector import RedisConnector
from danswer.server.documents.models import DeletionAttemptSnapshot
from danswer.utils.logger import setup_logger
@@ -41,14 +40,14 @@ def _get_deletion_status(
if not cc_pair:
return None
rcd = RedisConnectorDeletion(cc_pair.id)
r = get_redis_client(tenant_id=tenant_id)
if not r.exists(rcd.fence_key):
redis_connector = RedisConnector(tenant_id, cc_pair.id)
if not redis_connector.delete.fenced:
return None
return TaskQueueState(
task_id="", task_name=rcd.fence_key, status=TaskStatus.STARTED
task_id="",
task_name=redis_connector.delete.fence_key,
status=TaskStatus.STARTED,
)
@@ -79,10 +78,10 @@ def document_batch_to_ids(
def extract_ids_from_runnable_connector(
runnable_connector: BaseConnector,
callback: RunIndexingCallbackInterface | None = None,
callback: IndexingHeartbeatInterface | None = None,
) -> set[str]:
"""
If the PruneConnector hasnt been implemented for the given connector, just pull
If the SlimConnector hasnt been implemented for the given connector, just pull
all docs using the load_from_state and grab out the IDs.
Optionally, a callback can be passed to handle the length of each document batch.
@@ -112,10 +111,15 @@ def extract_ids_from_runnable_connector(
for doc_batch in doc_batch_generator:
if callback:
if callback.should_stop():
raise RuntimeError("Stop signal received")
callback.progress(len(doc_batch))
raise RuntimeError(
"extract_ids_from_runnable_connector: Stop signal detected"
)
all_connector_doc_ids.update(doc_batch_processing_func(doc_batch))
if callback:
callback.progress("extract_ids_from_runnable_connector", len(doc_batch))
return all_connector_doc_ids

View File

@@ -0,0 +1,61 @@
from datetime import timedelta
from typing import Any
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryTask
tasks_to_schedule = [
{
"name": "check-for-vespa-sync",
"task": DanswerCeleryTask.CHECK_FOR_VESPA_SYNC_TASK,
"schedule": timedelta(seconds=20),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-connector-deletion",
"task": DanswerCeleryTask.CHECK_FOR_CONNECTOR_DELETION,
"schedule": timedelta(seconds=20),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-indexing",
"task": DanswerCeleryTask.CHECK_FOR_INDEXING,
"schedule": timedelta(seconds=15),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-prune",
"task": DanswerCeleryTask.CHECK_FOR_PRUNING,
"schedule": timedelta(seconds=15),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "kombu-message-cleanup",
"task": DanswerCeleryTask.KOMBU_MESSAGE_CLEANUP_TASK,
"schedule": timedelta(seconds=3600),
"options": {"priority": DanswerCeleryPriority.LOWEST},
},
{
"name": "monitor-vespa-sync",
"task": DanswerCeleryTask.MONITOR_VESPA_SYNC,
"schedule": timedelta(seconds=5),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-doc-permissions-sync",
"task": DanswerCeleryTask.CHECK_FOR_DOC_PERMISSIONS_SYNC,
"schedule": timedelta(seconds=30),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
{
"name": "check-for-external-group-sync",
"task": DanswerCeleryTask.CHECK_FOR_EXTERNAL_GROUP_SYNC,
"schedule": timedelta(seconds=20),
"options": {"priority": DanswerCeleryPriority.HIGH},
},
]
def get_tasks_to_schedule() -> list[dict[str, Any]]:
return tasks_to_schedule

View File

@@ -1,30 +1,25 @@
from datetime import datetime
from datetime import timezone
import redis
from celery import Celery
from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from redis import Redis
from redis.lock import Lock as RedisLock
from sqlalchemy.orm import Session
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorIndexing
from danswer.background.celery.celery_redis import RedisConnectorPruning
from danswer.background.celery.celery_redis import RedisConnectorStop
from danswer.background.celery.tasks.shared.RedisConnectorDeletionFenceData import (
RedisConnectorDeletionFenceData,
)
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
from danswer.db.connector_credential_pair import get_connector_credential_pairs
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import ConnectorCredentialPairStatus
from danswer.db.search_settings import get_all_search_settings
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_delete import RedisConnectorDeletePayload
from danswer.redis.redis_pool import get_redis_client
@@ -34,7 +29,7 @@ class TaskDependencyError(RuntimeError):
@shared_task(
name="check_for_connector_deletion_task",
name=DanswerCeleryTask.CHECK_FOR_CONNECTOR_DELETION,
soft_time_limit=JOB_TIMEOUT,
trail=False,
bind=True,
@@ -42,7 +37,7 @@ class TaskDependencyError(RuntimeError):
def check_for_connector_deletion_task(self: Task, *, tenant_id: str | None) -> None:
r = get_redis_client(tenant_id=tenant_id)
lock_beat = r.lock(
lock_beat: RedisLock = r.lock(
DanswerRedisLocks.CHECK_CONNECTOR_DELETION_BEAT_LOCK,
timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
)
@@ -62,26 +57,26 @@ def check_for_connector_deletion_task(self: Task, *, tenant_id: str | None) -> N
# try running cleanup on the cc_pair_ids
for cc_pair_id in cc_pair_ids:
with get_session_with_tenant(tenant_id) as db_session:
rcs = RedisConnectorStop(cc_pair_id)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
try:
try_generate_document_cc_pair_cleanup_tasks(
self.app, cc_pair_id, db_session, r, lock_beat, tenant_id
self.app, cc_pair_id, db_session, lock_beat, tenant_id
)
except TaskDependencyError as e:
# this means we wanted to start deleting but dependent tasks were running
# Leave a stop signal to clear indexing and pruning tasks more quickly
task_logger.info(str(e))
r.set(rcs.fence_key, cc_pair_id)
redis_connector.stop.set_fence(True)
else:
# clear the stop signal if it exists ... no longer needed
r.delete(rcs.fence_key)
redis_connector.stop.set_fence(False)
except SoftTimeLimitExceeded:
task_logger.info(
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception("Unexpected exception")
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
@@ -91,8 +86,7 @@ def try_generate_document_cc_pair_cleanup_tasks(
app: Celery,
cc_pair_id: int,
db_session: Session,
r: Redis,
lock_beat: redis.lock.Lock,
lock_beat: RedisLock,
tenant_id: str | None,
) -> int | None:
"""Returns an int if syncing is needed. The int represents the number of sync tasks generated.
@@ -106,10 +100,10 @@ def try_generate_document_cc_pair_cleanup_tasks(
lock_beat.reacquire()
rcd = RedisConnectorDeletion(cc_pair_id)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
# don't generate sync tasks if tasks are still pending
if r.exists(rcd.fence_key):
if redis_connector.delete.fenced:
return None
# we need to load the state of the object inside the fence
@@ -123,47 +117,55 @@ def try_generate_document_cc_pair_cleanup_tasks(
return None
# set a basic fence to start
fence_value = RedisConnectorDeletionFenceData(
fence_payload = RedisConnectorDeletePayload(
num_tasks=None,
submitted=datetime.now(timezone.utc),
)
r.set(rcd.fence_key, fence_value.model_dump_json())
redis_connector.delete.set_fence(fence_payload)
try:
# do not proceed if connector indexing or connector pruning are running
search_settings_list = get_all_search_settings(db_session)
for search_settings in search_settings_list:
rci = RedisConnectorIndexing(cc_pair_id, search_settings.id)
if r.get(rci.fence_key):
redis_connector_index = redis_connector.new_index(search_settings.id)
if redis_connector_index.fenced:
raise TaskDependencyError(
f"Connector deletion - Delayed (indexing in progress): "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings.id}"
)
rcp = RedisConnectorPruning(cc_pair_id)
if r.get(rcp.fence_key):
if redis_connector.prune.fenced:
raise TaskDependencyError(
f"Connector deletion - Delayed (pruning in progress): "
f"cc_pair={cc_pair_id}"
)
if redis_connector.permissions.fenced:
raise TaskDependencyError(
f"Connector deletion - Delayed (permissions in progress): "
f"cc_pair={cc_pair_id}"
)
# add tasks to celery and build up the task set to monitor in redis
r.delete(rcd.taskset_key)
redis_connector.delete.taskset_clear()
# Add all documents that need to be updated into the queue
task_logger.info(
f"RedisConnectorDeletion.generate_tasks starting. cc_pair={cc_pair_id}"
)
tasks_generated = rcd.generate_tasks(app, db_session, r, lock_beat, tenant_id)
tasks_generated = redis_connector.delete.generate_tasks(
app, db_session, lock_beat
)
if tasks_generated is None:
raise ValueError("RedisConnectorDeletion.generate_tasks returned None")
except TaskDependencyError:
r.delete(rcd.fence_key)
redis_connector.delete.set_fence(None)
raise
except Exception:
task_logger.exception("Unexpected exception")
r.delete(rcd.fence_key)
redis_connector.delete.set_fence(None)
return None
else:
# Currently we are allowing the sync to proceed with 0 tasks.
@@ -178,7 +180,7 @@ def try_generate_document_cc_pair_cleanup_tasks(
)
# set this only after all tasks have been added
fence_value.num_tasks = tasks_generated
r.set(rcd.fence_key, fence_value.model_dump_json())
fence_payload.num_tasks = tasks_generated
redis_connector.delete.set_fence(fence_payload)
return tasks_generated

View File

@@ -0,0 +1,345 @@
from datetime import datetime
from datetime import timedelta
from datetime import timezone
from uuid import uuid4
from celery import Celery
from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from redis import Redis
from redis.lock import Lock as RedisLock
from danswer.access.models import DocExternalAccess
from danswer.background.celery.apps.app_base import task_logger
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import CELERY_PERMISSIONS_SYNC_LOCK_TIMEOUT
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryQueues
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.configs.constants import DocumentSource
from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
from danswer.db.document import upsert_document_by_connector_credential_pair
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import AccessType
from danswer.db.enums import ConnectorCredentialPairStatus
from danswer.db.models import ConnectorCredentialPair
from danswer.db.users import batch_add_ext_perm_user_if_not_exists
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_doc_perm_sync import (
RedisConnectorPermissionSyncPayload,
)
from danswer.redis.redis_pool import get_redis_client
from danswer.utils.logger import doc_permission_sync_ctx
from danswer.utils.logger import setup_logger
from ee.danswer.db.connector_credential_pair import get_all_auto_sync_cc_pairs
from ee.danswer.db.document import upsert_document_external_perms
from ee.danswer.external_permissions.sync_params import DOC_PERMISSION_SYNC_PERIODS
from ee.danswer.external_permissions.sync_params import DOC_PERMISSIONS_FUNC_MAP
logger = setup_logger()
DOCUMENT_PERMISSIONS_UPDATE_MAX_RETRIES = 3
# 5 seconds more than RetryDocumentIndex STOP_AFTER+MAX_WAIT
LIGHT_SOFT_TIME_LIMIT = 105
LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
def _is_external_doc_permissions_sync_due(cc_pair: ConnectorCredentialPair) -> bool:
"""Returns boolean indicating if external doc permissions sync is due."""
if cc_pair.access_type != AccessType.SYNC:
return False
# skip doc permissions sync if not active
if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
return False
if cc_pair.status == ConnectorCredentialPairStatus.DELETING:
return False
# If the last sync is None, it has never been run so we run the sync
last_perm_sync = cc_pair.last_time_perm_sync
if last_perm_sync is None:
return True
source_sync_period = DOC_PERMISSION_SYNC_PERIODS.get(cc_pair.connector.source)
# If RESTRICTED_FETCH_PERIOD[source] is None, we always run the sync.
if not source_sync_period:
return True
# If the last sync is greater than the full fetch period, we run the sync
next_sync = last_perm_sync + timedelta(seconds=source_sync_period)
if datetime.now(timezone.utc) >= next_sync:
return True
return False
@shared_task(
name=DanswerCeleryTask.CHECK_FOR_DOC_PERMISSIONS_SYNC,
soft_time_limit=JOB_TIMEOUT,
bind=True,
)
def check_for_doc_permissions_sync(self: Task, *, tenant_id: str | None) -> None:
r = get_redis_client(tenant_id=tenant_id)
lock_beat = r.lock(
DanswerRedisLocks.CHECK_CONNECTOR_DOC_PERMISSIONS_SYNC_BEAT_LOCK,
timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
)
try:
# these tasks should never overlap
if not lock_beat.acquire(blocking=False):
return
# get all cc pairs that need to be synced
cc_pair_ids_to_sync: list[int] = []
with get_session_with_tenant(tenant_id) as db_session:
cc_pairs = get_all_auto_sync_cc_pairs(db_session)
for cc_pair in cc_pairs:
if _is_external_doc_permissions_sync_due(cc_pair):
cc_pair_ids_to_sync.append(cc_pair.id)
for cc_pair_id in cc_pair_ids_to_sync:
tasks_created = try_creating_permissions_sync_task(
self.app, cc_pair_id, r, tenant_id
)
if not tasks_created:
continue
task_logger.info(f"Doc permissions sync queued: cc_pair={cc_pair_id}")
except SoftTimeLimitExceeded:
task_logger.info(
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
def try_creating_permissions_sync_task(
app: Celery,
cc_pair_id: int,
r: Redis,
tenant_id: str | None,
) -> int | None:
"""Returns an int if syncing is needed. The int represents the number of sync tasks generated.
Returns None if no syncing is required."""
redis_connector = RedisConnector(tenant_id, cc_pair_id)
LOCK_TIMEOUT = 30
lock: RedisLock = r.lock(
DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_generate_permissions_sync_tasks",
timeout=LOCK_TIMEOUT,
)
acquired = lock.acquire(blocking_timeout=LOCK_TIMEOUT / 2)
if not acquired:
return None
try:
if redis_connector.permissions.fenced:
return None
if redis_connector.delete.fenced:
return None
if redis_connector.prune.fenced:
return None
redis_connector.permissions.generator_clear()
redis_connector.permissions.taskset_clear()
custom_task_id = f"{redis_connector.permissions.generator_task_key}_{uuid4()}"
result = app.send_task(
DanswerCeleryTask.CONNECTOR_PERMISSION_SYNC_GENERATOR_TASK,
kwargs=dict(
cc_pair_id=cc_pair_id,
tenant_id=tenant_id,
),
queue=DanswerCeleryQueues.CONNECTOR_DOC_PERMISSIONS_SYNC,
task_id=custom_task_id,
priority=DanswerCeleryPriority.HIGH,
)
# set a basic fence to start
payload = RedisConnectorPermissionSyncPayload(
started=None, celery_task_id=result.id
)
redis_connector.permissions.set_fence(payload)
except Exception:
task_logger.exception(f"Unexpected exception: cc_pair={cc_pair_id}")
return None
finally:
if lock.owned():
lock.release()
return 1
@shared_task(
name=DanswerCeleryTask.CONNECTOR_PERMISSION_SYNC_GENERATOR_TASK,
acks_late=False,
soft_time_limit=JOB_TIMEOUT,
track_started=True,
trail=False,
bind=True,
)
def connector_permission_sync_generator_task(
self: Task,
cc_pair_id: int,
tenant_id: str | None,
) -> None:
"""
Permission sync task that handles document permission syncing for a given connector credential pair
This task assumes that the task has already been properly fenced
"""
doc_permission_sync_ctx_dict = doc_permission_sync_ctx.get()
doc_permission_sync_ctx_dict["cc_pair_id"] = cc_pair_id
doc_permission_sync_ctx_dict["request_id"] = self.request.id
doc_permission_sync_ctx.set(doc_permission_sync_ctx_dict)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
r = get_redis_client(tenant_id=tenant_id)
lock = r.lock(
DanswerRedisLocks.CONNECTOR_DOC_PERMISSIONS_SYNC_LOCK_PREFIX
+ f"_{redis_connector.id}",
timeout=CELERY_PERMISSIONS_SYNC_LOCK_TIMEOUT,
)
acquired = lock.acquire(blocking=False)
if not acquired:
task_logger.warning(
f"Permission sync task already running, exiting...: cc_pair={cc_pair_id}"
)
return None
try:
with get_session_with_tenant(tenant_id) as db_session:
cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
if cc_pair is None:
raise ValueError(
f"No connector credential pair found for id: {cc_pair_id}"
)
source_type = cc_pair.connector.source
doc_sync_func = DOC_PERMISSIONS_FUNC_MAP.get(source_type)
if doc_sync_func is None:
raise ValueError(
f"No doc sync func found for {source_type} with cc_pair={cc_pair_id}"
)
logger.info(f"Syncing docs for {source_type} with cc_pair={cc_pair_id}")
payload = redis_connector.permissions.payload
if not payload:
raise ValueError(f"No fence payload found: cc_pair={cc_pair_id}")
payload.started = datetime.now(timezone.utc)
redis_connector.permissions.set_fence(payload)
document_external_accesses: list[DocExternalAccess] = doc_sync_func(cc_pair)
task_logger.info(
f"RedisConnector.permissions.generate_tasks starting. cc_pair={cc_pair_id}"
)
tasks_generated = redis_connector.permissions.generate_tasks(
celery_app=self.app,
lock=lock,
new_permissions=document_external_accesses,
source_string=source_type,
connector_id=cc_pair.connector.id,
credential_id=cc_pair.credential.id,
)
if tasks_generated is None:
return None
task_logger.info(
f"RedisConnector.permissions.generate_tasks finished. "
f"cc_pair={cc_pair_id} tasks_generated={tasks_generated}"
)
redis_connector.permissions.generator_complete = tasks_generated
except Exception as e:
task_logger.exception(f"Failed to run permission sync: cc_pair={cc_pair_id}")
redis_connector.permissions.generator_clear()
redis_connector.permissions.taskset_clear()
redis_connector.permissions.set_fence(None)
raise e
finally:
if lock.owned():
lock.release()
@shared_task(
name=DanswerCeleryTask.UPDATE_EXTERNAL_DOCUMENT_PERMISSIONS_TASK,
soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
time_limit=LIGHT_TIME_LIMIT,
max_retries=DOCUMENT_PERMISSIONS_UPDATE_MAX_RETRIES,
bind=True,
)
def update_external_document_permissions_task(
self: Task,
tenant_id: str | None,
serialized_doc_external_access: dict,
source_string: str,
connector_id: int,
credential_id: int,
) -> bool:
document_external_access = DocExternalAccess.from_dict(
serialized_doc_external_access
)
doc_id = document_external_access.doc_id
external_access = document_external_access.external_access
try:
with get_session_with_tenant(tenant_id) as db_session:
# Add the users to the DB if they don't exist
batch_add_ext_perm_user_if_not_exists(
db_session=db_session,
emails=list(external_access.external_user_emails),
)
# Then we upsert the document's external permissions in postgres
created_new_doc = upsert_document_external_perms(
db_session=db_session,
doc_id=doc_id,
external_access=external_access,
source_type=DocumentSource(source_string),
)
if created_new_doc:
# If a new document was created, we associate it with the cc_pair
upsert_document_by_connector_credential_pair(
db_session=db_session,
connector_id=connector_id,
credential_id=credential_id,
document_ids=[doc_id],
)
logger.debug(
f"Successfully synced postgres document permissions for {doc_id}"
)
return True
except Exception:
logger.exception("Error Syncing Document Permissions")
return False

View File

@@ -0,0 +1,298 @@
from datetime import datetime
from datetime import timedelta
from datetime import timezone
from uuid import uuid4
from celery import Celery
from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from redis import Redis
from redis.lock import Lock as RedisLock
from danswer.background.celery.apps.app_base import task_logger
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import CELERY_EXTERNAL_GROUP_SYNC_LOCK_TIMEOUT
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryQueues
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.db.connector import mark_cc_pair_as_external_group_synced
from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import AccessType
from danswer.db.enums import ConnectorCredentialPairStatus
from danswer.db.models import ConnectorCredentialPair
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_ext_group_sync import (
RedisConnectorExternalGroupSyncPayload,
)
from danswer.redis.redis_pool import get_redis_client
from danswer.utils.logger import setup_logger
from ee.danswer.db.connector_credential_pair import get_all_auto_sync_cc_pairs
from ee.danswer.db.connector_credential_pair import get_cc_pairs_by_source
from ee.danswer.db.external_perm import ExternalUserGroup
from ee.danswer.db.external_perm import replace_user__ext_group_for_cc_pair
from ee.danswer.external_permissions.sync_params import EXTERNAL_GROUP_SYNC_PERIODS
from ee.danswer.external_permissions.sync_params import GROUP_PERMISSIONS_FUNC_MAP
from ee.danswer.external_permissions.sync_params import (
GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC,
)
logger = setup_logger()
EXTERNAL_GROUPS_UPDATE_MAX_RETRIES = 3
# 5 seconds more than RetryDocumentIndex STOP_AFTER+MAX_WAIT
LIGHT_SOFT_TIME_LIMIT = 105
LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
def _is_external_group_sync_due(cc_pair: ConnectorCredentialPair) -> bool:
"""Returns boolean indicating if external group sync is due."""
if cc_pair.access_type != AccessType.SYNC:
return False
# skip external group sync if not active
if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
return False
if cc_pair.status == ConnectorCredentialPairStatus.DELETING:
return False
# If there is not group sync function for the connector, we don't run the sync
# This is fine because all sources dont necessarily have a concept of groups
if not GROUP_PERMISSIONS_FUNC_MAP.get(cc_pair.connector.source):
return False
# If the last sync is None, it has never been run so we run the sync
last_ext_group_sync = cc_pair.last_time_external_group_sync
if last_ext_group_sync is None:
return True
source_sync_period = EXTERNAL_GROUP_SYNC_PERIODS.get(cc_pair.connector.source)
# If EXTERNAL_GROUP_SYNC_PERIODS is None, we always run the sync.
if not source_sync_period:
return True
# If the last sync is greater than the full fetch period, we run the sync
next_sync = last_ext_group_sync + timedelta(seconds=source_sync_period)
if datetime.now(timezone.utc) >= next_sync:
return True
return False
@shared_task(
name=DanswerCeleryTask.CHECK_FOR_EXTERNAL_GROUP_SYNC,
soft_time_limit=JOB_TIMEOUT,
bind=True,
)
def check_for_external_group_sync(self: Task, *, tenant_id: str | None) -> None:
r = get_redis_client(tenant_id=tenant_id)
lock_beat = r.lock(
DanswerRedisLocks.CHECK_CONNECTOR_EXTERNAL_GROUP_SYNC_BEAT_LOCK,
timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
)
try:
# these tasks should never overlap
if not lock_beat.acquire(blocking=False):
return
cc_pair_ids_to_sync: list[int] = []
with get_session_with_tenant(tenant_id) as db_session:
cc_pairs = get_all_auto_sync_cc_pairs(db_session)
# We only want to sync one cc_pair per source type in
# GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC
for source in GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC:
# These are ordered by cc_pair id so the first one is the one we want
cc_pairs_to_dedupe = get_cc_pairs_by_source(
db_session, source, only_sync=True
)
# We only want to sync one cc_pair per source type
# in GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC so we dedupe here
for cc_pair_to_remove in cc_pairs_to_dedupe[1:]:
cc_pairs = [
cc_pair
for cc_pair in cc_pairs
if cc_pair.id != cc_pair_to_remove.id
]
for cc_pair in cc_pairs:
if _is_external_group_sync_due(cc_pair):
cc_pair_ids_to_sync.append(cc_pair.id)
for cc_pair_id in cc_pair_ids_to_sync:
tasks_created = try_creating_external_group_sync_task(
self.app, cc_pair_id, r, tenant_id
)
if not tasks_created:
continue
task_logger.info(f"External group sync queued: cc_pair={cc_pair_id}")
except SoftTimeLimitExceeded:
task_logger.info(
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
def try_creating_external_group_sync_task(
app: Celery,
cc_pair_id: int,
r: Redis,
tenant_id: str | None,
) -> int | None:
"""Returns an int if syncing is needed. The int represents the number of sync tasks generated.
Returns None if no syncing is required."""
redis_connector = RedisConnector(tenant_id, cc_pair_id)
LOCK_TIMEOUT = 30
lock = r.lock(
DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_generate_external_group_sync_tasks",
timeout=LOCK_TIMEOUT,
)
acquired = lock.acquire(blocking_timeout=LOCK_TIMEOUT / 2)
if not acquired:
return None
try:
# Dont kick off a new sync if the previous one is still running
if redis_connector.external_group_sync.fenced:
return None
redis_connector.external_group_sync.generator_clear()
redis_connector.external_group_sync.taskset_clear()
custom_task_id = f"{redis_connector.external_group_sync.taskset_key}_{uuid4()}"
result = app.send_task(
DanswerCeleryTask.CONNECTOR_EXTERNAL_GROUP_SYNC_GENERATOR_TASK,
kwargs=dict(
cc_pair_id=cc_pair_id,
tenant_id=tenant_id,
),
queue=DanswerCeleryQueues.CONNECTOR_EXTERNAL_GROUP_SYNC,
task_id=custom_task_id,
priority=DanswerCeleryPriority.HIGH,
)
payload = RedisConnectorExternalGroupSyncPayload(
started=datetime.now(timezone.utc),
celery_task_id=result.id,
)
redis_connector.external_group_sync.set_fence(payload)
except Exception:
task_logger.exception(
f"Unexpected exception while trying to create external group sync task: cc_pair={cc_pair_id}"
)
return None
finally:
if lock.owned():
lock.release()
return 1
@shared_task(
name=DanswerCeleryTask.CONNECTOR_EXTERNAL_GROUP_SYNC_GENERATOR_TASK,
acks_late=False,
soft_time_limit=JOB_TIMEOUT,
track_started=True,
trail=False,
bind=True,
)
def connector_external_group_sync_generator_task(
self: Task,
cc_pair_id: int,
tenant_id: str | None,
) -> None:
"""
Permission sync task that handles external group syncing for a given connector credential pair
This task assumes that the task has already been properly fenced
"""
redis_connector = RedisConnector(tenant_id, cc_pair_id)
r = get_redis_client(tenant_id=tenant_id)
lock: RedisLock = r.lock(
DanswerRedisLocks.CONNECTOR_EXTERNAL_GROUP_SYNC_LOCK_PREFIX
+ f"_{redis_connector.id}",
timeout=CELERY_EXTERNAL_GROUP_SYNC_LOCK_TIMEOUT,
)
try:
acquired = lock.acquire(blocking=False)
if not acquired:
task_logger.warning(
f"External group sync task already running, exiting...: cc_pair={cc_pair_id}"
)
return None
with get_session_with_tenant(tenant_id) as db_session:
cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
if cc_pair is None:
raise ValueError(
f"No connector credential pair found for id: {cc_pair_id}"
)
source_type = cc_pair.connector.source
ext_group_sync_func = GROUP_PERMISSIONS_FUNC_MAP.get(source_type)
if ext_group_sync_func is None:
raise ValueError(
f"No external group sync func found for {source_type} for cc_pair: {cc_pair_id}"
)
logger.info(
f"Syncing external groups for {source_type} for cc_pair: {cc_pair_id}"
)
external_user_groups: list[ExternalUserGroup] = ext_group_sync_func(cc_pair)
logger.info(
f"Syncing {len(external_user_groups)} external user groups for {source_type}"
)
replace_user__ext_group_for_cc_pair(
db_session=db_session,
cc_pair_id=cc_pair.id,
group_defs=external_user_groups,
source=cc_pair.connector.source,
)
logger.info(
f"Synced {len(external_user_groups)} external user groups for {source_type}"
)
mark_cc_pair_as_external_group_synced(db_session, cc_pair.id)
except Exception as e:
task_logger.exception(
f"Failed to run external group sync: cc_pair={cc_pair_id}"
)
redis_connector.external_group_sync.generator_clear()
redis_connector.external_group_sync.taskset_clear()
raise e
finally:
# we always want to clear the fence after the task is done or failed so it doesn't get stuck
redis_connector.external_group_sync.set_fence(None)
if lock.owned():
lock.release()

View File

@@ -2,93 +2,171 @@ from datetime import datetime
from datetime import timezone
from http import HTTPStatus
from time import sleep
from typing import cast
from uuid import uuid4
import redis
import sentry_sdk
from celery import Celery
from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from redis import Redis
from redis.exceptions import LockError
from redis.lock import Lock as RedisLock
from sqlalchemy.orm import Session
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorIndexing
from danswer.background.celery.celery_redis import RedisConnectorStop
from danswer.background.celery.tasks.shared.RedisConnectorIndexingFenceData import (
RedisConnectorIndexingFenceData,
)
from danswer.background.indexing.job_client import SimpleJobClient
from danswer.background.indexing.run_indexing import run_indexing_entrypoint
from danswer.background.indexing.run_indexing import RunIndexingCallbackInterface
from danswer.configs.app_configs import DISABLE_INDEX_UPDATE_ON_SWAP
from danswer.configs.constants import CELERY_INDEXING_LOCK_TIMEOUT
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryQueues
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.configs.constants import DocumentSource
from danswer.db.connector import mark_ccpair_with_indexing_trigger
from danswer.db.connector_credential_pair import fetch_connector_credential_pairs
from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
from danswer.db.engine import get_db_current_time
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import ConnectorCredentialPairStatus
from danswer.db.enums import IndexingMode
from danswer.db.enums import IndexingStatus
from danswer.db.enums import IndexModelStatus
from danswer.db.index_attempt import create_index_attempt
from danswer.db.index_attempt import delete_index_attempt
from danswer.db.index_attempt import get_all_index_attempts_by_status
from danswer.db.index_attempt import get_index_attempt
from danswer.db.index_attempt import get_last_attempt_for_cc_pair
from danswer.db.index_attempt import mark_attempt_canceled
from danswer.db.index_attempt import mark_attempt_failed
from danswer.db.models import ConnectorCredentialPair
from danswer.db.models import IndexAttempt
from danswer.db.models import SearchSettings
from danswer.db.search_settings import get_active_search_settings
from danswer.db.search_settings import get_current_search_settings
from danswer.db.search_settings import get_secondary_search_settings
from danswer.db.swap_index import check_index_swap
from danswer.indexing.indexing_heartbeat import IndexingHeartbeatInterface
from danswer.natural_language_processing.search_nlp_models import EmbeddingModel
from danswer.natural_language_processing.search_nlp_models import warm_up_bi_encoder
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_index import RedisConnectorIndex
from danswer.redis.redis_connector_index import RedisConnectorIndexPayload
from danswer.redis.redis_pool import get_redis_client
from danswer.utils.logger import setup_logger
from danswer.utils.variable_functionality import global_version
from shared_configs.configs import INDEXING_MODEL_SERVER_HOST
from shared_configs.configs import INDEXING_MODEL_SERVER_PORT
from shared_configs.configs import MULTI_TENANT
from shared_configs.configs import SENTRY_DSN
logger = setup_logger()
class RunIndexingCallback(RunIndexingCallbackInterface):
class IndexingCallback(IndexingHeartbeatInterface):
def __init__(
self,
stop_key: str,
generator_progress_key: str,
redis_lock: redis.lock.Lock,
redis_lock: RedisLock,
redis_client: Redis,
):
super().__init__()
self.redis_lock: redis.lock.Lock = redis_lock
self.redis_lock: RedisLock = redis_lock
self.stop_key: str = stop_key
self.generator_progress_key: str = generator_progress_key
self.redis_client = redis_client
self.started: datetime = datetime.now(timezone.utc)
self.redis_lock.reacquire()
self.last_tag: str = "IndexingCallback.__init__"
self.last_lock_reacquire: datetime = datetime.now(timezone.utc)
def should_stop(self) -> bool:
if self.redis_client.exists(self.stop_key):
return True
return False
def progress(self, amount: int) -> None:
self.redis_lock.reacquire()
def progress(self, tag: str, amount: int) -> None:
try:
self.redis_lock.reacquire()
self.last_tag = tag
self.last_lock_reacquire = datetime.now(timezone.utc)
except LockError:
logger.exception(
f"IndexingCallback - lock.reacquire exceptioned. "
f"lock_timeout={self.redis_lock.timeout} "
f"start={self.started} "
f"last_tag={self.last_tag} "
f"last_reacquired={self.last_lock_reacquire} "
f"now={datetime.now(timezone.utc)}"
)
raise
self.redis_client.incrby(self.generator_progress_key, amount)
def get_unfenced_index_attempt_ids(db_session: Session, r: redis.Redis) -> list[int]:
"""Gets a list of unfenced index attempts. Should not be possible, so we'd typically
want to clean them up.
Unfenced = attempt not in terminal state and fence does not exist.
"""
unfenced_attempts: list[int] = []
# inner/outer/inner double check pattern to avoid race conditions when checking for
# bad state
# inner = index_attempt in non terminal state
# outer = r.fence_key down
# check the db for index attempts in a non terminal state
attempts: list[IndexAttempt] = []
attempts.extend(
get_all_index_attempts_by_status(IndexingStatus.NOT_STARTED, db_session)
)
attempts.extend(
get_all_index_attempts_by_status(IndexingStatus.IN_PROGRESS, db_session)
)
for attempt in attempts:
fence_key = RedisConnectorIndex.fence_key_with_ids(
attempt.connector_credential_pair_id, attempt.search_settings_id
)
# if the fence is down / doesn't exist, possible error but not confirmed
if r.exists(fence_key):
continue
# Between the time the attempts are first looked up and the time we see the fence down,
# the attempt may have completed and taken down the fence normally.
# We need to double check that the index attempt is still in a non terminal state
# and matches the original state, which confirms we are really in a bad state.
attempt_2 = get_index_attempt(db_session, attempt.id)
if not attempt_2:
continue
if attempt.status != attempt_2.status:
continue
unfenced_attempts.append(attempt.id)
return unfenced_attempts
@shared_task(
name="check_for_indexing",
name=DanswerCeleryTask.CHECK_FOR_INDEXING,
soft_time_limit=300,
bind=True,
)
def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
tasks_created = 0
locked = False
r = get_redis_client(tenant_id=tenant_id)
lock_beat = r.lock(
lock_beat: RedisLock = r.lock(
DanswerRedisLocks.CHECK_INDEXING_BEAT_LOCK,
timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
)
@@ -98,29 +176,49 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
if not lock_beat.acquire(blocking=False):
return None
locked = True
# check for search settings swap
with get_session_with_tenant(tenant_id=tenant_id) as db_session:
old_search_settings = check_index_swap(db_session=db_session)
current_search_settings = get_current_search_settings(db_session)
# So that the first time users aren't surprised by really slow speed of first
# batch of documents indexed
if current_search_settings.provider_type is None and not MULTI_TENANT:
if old_search_settings:
embedding_model = EmbeddingModel.from_db_model(
search_settings=current_search_settings,
server_host=INDEXING_MODEL_SERVER_HOST,
server_port=INDEXING_MODEL_SERVER_PORT,
)
# only warm up if search settings were changed
warm_up_bi_encoder(
embedding_model=embedding_model,
)
# gather cc_pair_ids
cc_pair_ids: list[int] = []
with get_session_with_tenant(tenant_id) as db_session:
lock_beat.reacquire()
cc_pairs = fetch_connector_credential_pairs(db_session)
for cc_pair_entry in cc_pairs:
cc_pair_ids.append(cc_pair_entry.id)
# kick off index attempts
for cc_pair_id in cc_pair_ids:
lock_beat.reacquire()
redis_connector = RedisConnector(tenant_id, cc_pair_id)
with get_session_with_tenant(tenant_id) as db_session:
# Get the primary search settings
primary_search_settings = get_current_search_settings(db_session)
search_settings = [primary_search_settings]
# Check for secondary search settings
secondary_search_settings = get_secondary_search_settings(db_session)
if secondary_search_settings is not None:
# If secondary settings exist, add them to the list
search_settings.append(secondary_search_settings)
for search_settings_instance in search_settings:
rci = RedisConnectorIndexing(
cc_pair_id, search_settings_instance.id
search_settings_list: list[SearchSettings] = get_active_search_settings(
db_session
)
for search_settings_instance in search_settings_list:
redis_connector_index = redis_connector.new_index(
search_settings_instance.id
)
if r.exists(rci.fence_key):
if redis_connector_index.fenced:
continue
cc_pair = get_connector_credential_pair_from_id(
@@ -132,40 +230,95 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
last_attempt = get_last_attempt_for_cc_pair(
cc_pair.id, search_settings_instance.id, db_session
)
search_settings_primary = False
if search_settings_instance.id == search_settings_list[0].id:
search_settings_primary = True
if not _should_index(
cc_pair=cc_pair,
last_index=last_attempt,
search_settings_instance=search_settings_instance,
secondary_index_building=len(search_settings) > 1,
search_settings_primary=search_settings_primary,
secondary_index_building=len(search_settings_list) > 1,
db_session=db_session,
):
continue
reindex = False
if search_settings_instance.id == search_settings_list[0].id:
# the indexing trigger is only checked and cleared with the primary search settings
if cc_pair.indexing_trigger is not None:
if cc_pair.indexing_trigger == IndexingMode.REINDEX:
reindex = True
task_logger.info(
f"Connector indexing manual trigger detected: "
f"cc_pair={cc_pair.id} "
f"search_settings={search_settings_instance.id} "
f"indexing_mode={cc_pair.indexing_trigger}"
)
mark_ccpair_with_indexing_trigger(
cc_pair.id, None, db_session
)
# using a task queue and only allowing one task per cc_pair/search_setting
# prevents us from starving out certain attempts
attempt_id = try_creating_indexing_task(
self.app,
cc_pair,
search_settings_instance,
False,
reindex,
db_session,
r,
tenant_id,
)
if attempt_id:
task_logger.info(
f"Indexing queued: cc_pair_id={cc_pair.id} index_attempt_id={attempt_id}"
f"Connector indexing queued: "
f"index_attempt={attempt_id} "
f"cc_pair={cc_pair.id} "
f"search_settings={search_settings_instance.id}"
)
tasks_created += 1
# Fail any index attempts in the DB that don't have fences
# This shouldn't ever happen!
with get_session_with_tenant(tenant_id) as db_session:
unfenced_attempt_ids = get_unfenced_index_attempt_ids(db_session, r)
for attempt_id in unfenced_attempt_ids:
lock_beat.reacquire()
attempt = get_index_attempt(db_session, attempt_id)
if not attempt:
continue
failure_reason = (
f"Unfenced index attempt found in DB: "
f"index_attempt={attempt.id} "
f"cc_pair={attempt.connector_credential_pair_id} "
f"search_settings={attempt.search_settings_id}"
)
task_logger.error(failure_reason)
mark_attempt_failed(
attempt.id, db_session, failure_reason=failure_reason
)
except SoftTimeLimitExceeded:
task_logger.info(
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception("Unexpected exception")
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
if locked:
if lock_beat.owned():
lock_beat.release()
else:
task_logger.error(
"check_for_indexing - Lock not owned on completion: "
f"tenant={tenant_id}"
)
return tasks_created
@@ -174,6 +327,7 @@ def _should_index(
cc_pair: ConnectorCredentialPair,
last_index: IndexAttempt | None,
search_settings_instance: SearchSettings,
search_settings_primary: bool,
secondary_index_building: bool,
db_session: Session,
) -> bool:
@@ -238,6 +392,11 @@ def _should_index(
):
return False
if search_settings_primary:
if cc_pair.indexing_trigger is not None:
# if a manual indexing trigger is on the cc pair, honor it for primary search settings
return True
# if no attempt has ever occurred, we should index regardless of refresh_freq
if not last_index:
return True
@@ -270,10 +429,11 @@ def try_creating_indexing_task(
"""
LOCK_TIMEOUT = 30
index_attempt_id: int | None = None
# we need to serialize any attempt to trigger indexing since it can be triggered
# either via celery beat or manually (API call)
lock = r.lock(
lock: RedisLock = r.lock(
DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_creating_indexing_task",
timeout=LOCK_TIMEOUT,
)
@@ -283,15 +443,15 @@ def try_creating_indexing_task(
return None
try:
rci = RedisConnectorIndexing(cc_pair.id, search_settings.id)
redis_connector = RedisConnector(tenant_id, cc_pair.id)
redis_connector_index = redis_connector.new_index(search_settings.id)
# skip if already indexing
if r.exists(rci.fence_key):
if redis_connector_index.fenced:
return None
# skip indexing if the cc_pair is deleting
rcd = RedisConnectorDeletion(cc_pair.id)
if r.exists(rcd.fence_key):
if redis_connector.delete.fenced:
return None
db_session.refresh(cc_pair)
@@ -299,19 +459,17 @@ def try_creating_indexing_task(
return None
# add a long running generator task to the queue
r.delete(rci.generator_complete_key)
r.delete(rci.taskset_key)
custom_task_id = f"{rci.generator_task_id_prefix}_{uuid4()}"
redis_connector_index.generator_clear()
# set a basic fence to start
fence_value = RedisConnectorIndexingFenceData(
payload = RedisConnectorIndexPayload(
index_attempt_id=None,
started=None,
submitted=datetime.now(timezone.utc),
celery_task_id=None,
)
r.set(rci.fence_key, fence_value.model_dump_json())
redis_connector_index.set_fence(payload)
# create the index attempt for tracking purposes
# code elsewhere checks for index attempts without an associated redis key
@@ -324,8 +482,12 @@ def try_creating_indexing_task(
db_session=db_session,
)
custom_task_id = redis_connector_index.generate_generator_task_id()
# when the task is sent, we have yet to finish setting up the fence
# therefore, the task must contain code that blocks until the fence is ready
result = celery_app.send_task(
"connector_indexing_proxy_task",
DanswerCeleryTask.CONNECTOR_INDEXING_PROXY_TASK,
kwargs=dict(
index_attempt_id=index_attempt_id,
cc_pair_id=cc_pair.id,
@@ -340,12 +502,20 @@ def try_creating_indexing_task(
raise RuntimeError("send_task for connector_indexing_proxy_task failed.")
# now fill out the fence with the rest of the data
fence_value.index_attempt_id = index_attempt_id
fence_value.celery_task_id = result.id
r.set(rci.fence_key, fence_value.model_dump_json())
payload.index_attempt_id = index_attempt_id
payload.celery_task_id = result.id
redis_connector_index.set_fence(payload)
except Exception:
r.delete(rci.fence_key)
task_logger.exception("Unexpected exception")
task_logger.exception(
f"try_creating_indexing_task - Unexpected exception: "
f"tenant={tenant_id} "
f"cc_pair={cc_pair.id} "
f"search_settings={search_settings.id}"
)
if index_attempt_id is not None:
delete_index_attempt(db_session, index_attempt_id)
redis_connector_index.set_fence(None)
return None
finally:
if lock.owned():
@@ -354,19 +524,34 @@ def try_creating_indexing_task(
return index_attempt_id
@shared_task(name="connector_indexing_proxy_task", acks_late=False, track_started=True)
@shared_task(
name=DanswerCeleryTask.CONNECTOR_INDEXING_PROXY_TASK,
bind=True,
acks_late=False,
track_started=True,
)
def connector_indexing_proxy_task(
self: Task,
index_attempt_id: int,
cc_pair_id: int,
search_settings_id: int,
tenant_id: str | None,
) -> None:
"""celery tasks are forked, but forking is unstable. This proxies work to a spawned task."""
task_logger.info(
f"Indexing watchdog - starting: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
if not self.request.id:
task_logger.error("self.request.id is None!")
client = SimpleJobClient()
job = client.submit(
connector_indexing_task,
connector_indexing_task_wrapper,
index_attempt_id,
cc_pair_id,
search_settings_id,
@@ -376,32 +561,138 @@ def connector_indexing_proxy_task(
)
if not job:
task_logger.info(
f"Indexing watchdog - spawn failed: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
return
task_logger.info(
f"Indexing watchdog - spawn succeeded: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
redis_connector_index = redis_connector.new_index(search_settings_id)
while True:
sleep(10)
with get_session_with_tenant(tenant_id) as db_session:
index_attempt = get_index_attempt(
db_session=db_session, index_attempt_id=index_attempt_id
sleep(5)
if self.request.id and redis_connector_index.terminating(self.request.id):
task_logger.warning(
"Indexing watchdog - termination signal detected: "
f"attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
# do nothing for ongoing jobs that haven't been stopped
if not job.done():
if not index_attempt:
continue
try:
with get_session_with_tenant(tenant_id) as db_session:
mark_attempt_canceled(
index_attempt_id,
db_session,
"Connector termination signal detected",
)
finally:
# if the DB exceptions, we'll just get an unfriendly failure message
# in the UI instead of the cancellation message
logger.exception(
"Indexing watchdog - transient exception marking index attempt as canceled: "
f"attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
if not index_attempt.is_finished():
continue
job.cancel()
if job.status == "error":
logger.error(job.exception())
job.release()
break
if not job.done():
# if the spawned task is still running, restart the check once again
# if the index attempt is not in a finished status
try:
with get_session_with_tenant(tenant_id) as db_session:
index_attempt = get_index_attempt(
db_session=db_session, index_attempt_id=index_attempt_id
)
if not index_attempt:
continue
if not index_attempt.is_finished():
continue
except Exception:
# if the DB exceptioned, just restart the check.
# polling the index attempt status doesn't need to be strongly consistent
logger.exception(
"Indexing watchdog - transient exception looking up index attempt: "
f"attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
continue
if job.status == "error":
task_logger.error(
"Indexing watchdog - spawned task exceptioned: "
f"attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id} "
f"error={job.exception()}"
)
job.release()
break
task_logger.info(
f"Indexing watchdog - finished: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
return
def connector_indexing_task_wrapper(
index_attempt_id: int,
cc_pair_id: int,
search_settings_id: int,
tenant_id: str | None,
is_ee: bool,
) -> int | None:
"""Just wraps connector_indexing_task so we can log any exceptions before
re-raising it."""
result: int | None = None
try:
result = connector_indexing_task(
index_attempt_id,
cc_pair_id,
search_settings_id,
tenant_id,
is_ee,
)
except:
logger.exception(
f"connector_indexing_task exceptioned: "
f"tenant={tenant_id} "
f"index_attempt={index_attempt_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
raise
return result
def connector_indexing_task(
index_attempt_id: int,
cc_pair_id: int,
@@ -420,79 +711,102 @@ def connector_indexing_task(
Returns None if the task did not run (possibly due to a conflict).
Otherwise, returns an int >= 0 representing the number of indexed docs.
NOTE: if an exception is raised out of this task, the primary worker will detect
that the task transitioned to a "READY" state but the generator_complete_key doesn't exist.
This will cause the primary worker to abort the indexing attempt and clean up.
"""
attempt = None
n_final_progress = 0
# Since connector_indexing_proxy_task spawns a new process using this function as
# the entrypoint, we init Sentry here.
if SENTRY_DSN:
sentry_sdk.init(
dsn=SENTRY_DSN,
traces_sample_rate=0.1,
)
logger.info("Sentry initialized")
else:
logger.debug("Sentry DSN not provided, skipping Sentry initialization")
logger.info(
f"Indexing spawned task starting: "
f"attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
attempt_found = False
n_final_progress: int | None = None
redis_connector = RedisConnector(tenant_id, cc_pair_id)
redis_connector_index = redis_connector.new_index(search_settings_id)
r = get_redis_client(tenant_id=tenant_id)
rcd = RedisConnectorDeletion(cc_pair_id)
if r.exists(rcd.fence_key):
if redis_connector.delete.fenced:
raise RuntimeError(
f"Indexing will not start because connector deletion is in progress: "
f"attempt={index_attempt_id} "
f"cc_pair={cc_pair_id} "
f"fence={rcd.fence_key}"
f"fence={redis_connector.delete.fence_key}"
)
rcs = RedisConnectorStop(cc_pair_id)
if r.exists(rcs.fence_key):
if redis_connector.stop.fenced:
raise RuntimeError(
f"Indexing will not start because a connector stop signal was detected: "
f"attempt={index_attempt_id} "
f"cc_pair={cc_pair_id} "
f"fence={rcs.fence_key}"
f"fence={redis_connector.stop.fence_key}"
)
rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
while True:
# read related data and evaluate/print task progress
fence_value = cast(bytes, r.get(rci.fence_key))
if fence_value is None:
task_logger.info(
f"connector_indexing_task: fence_value not found: fence={rci.fence_key}"
if not redis_connector_index.fenced: # The fence must exist
raise ValueError(
f"connector_indexing_task - fence not found: fence={redis_connector_index.fence_key}"
)
raise RuntimeError(f"Fence not found: fence={rci.fence_key}")
try:
fence_json = fence_value.decode("utf-8")
fence_data = RedisConnectorIndexingFenceData.model_validate_json(
cast(str, fence_json)
)
except ValueError:
task_logger.exception(
f"connector_indexing_task: fence_data not decodeable: fence={rci.fence_key}"
)
raise
payload = redis_connector_index.payload # The payload must exist
if not payload:
raise ValueError("connector_indexing_task: payload invalid or not found")
if fence_data.index_attempt_id is None or fence_data.celery_task_id is None:
task_logger.info(
f"connector_indexing_task - Waiting for fence: fence={rci.fence_key}"
if payload.index_attempt_id is None or payload.celery_task_id is None:
logger.info(
f"connector_indexing_task - Waiting for fence: fence={redis_connector_index.fence_key}"
)
sleep(1)
continue
task_logger.info(
f"connector_indexing_task - Fence found, continuing...: fence={rci.fence_key}"
if payload.index_attempt_id != index_attempt_id:
raise ValueError(
f"connector_indexing_task - id mismatch. Task may be left over from previous run.: "
f"task_index_attempt={index_attempt_id} "
f"payload_index_attempt={payload.index_attempt_id}"
)
logger.info(
f"connector_indexing_task - Fence found, continuing...: fence={redis_connector_index.fence_key}"
)
break
lock = r.lock(
rci.generator_lock_key,
# set thread_local=False since we don't control what thread the indexing/pruning
# might run our callback with
lock: RedisLock = r.lock(
redis_connector_index.generator_lock_key,
timeout=CELERY_INDEXING_LOCK_TIMEOUT,
thread_local=False,
)
acquired = lock.acquire(blocking=False)
if not acquired:
task_logger.warning(
logger.warning(
f"Indexing task already running, exiting...: "
f"cc_pair={cc_pair_id} search_settings={search_settings_id}"
f"index_attempt={index_attempt_id} cc_pair={cc_pair_id} search_settings={search_settings_id}"
)
# r.set(rci.generator_complete_key, HTTPStatus.CONFLICT.value)
return None
fence_data.started = datetime.now(timezone.utc)
r.set(rci.fence_key, fence_data.model_dump_json())
payload.started = datetime.now(timezone.utc)
redis_connector_index.set_fence(payload)
try:
with get_session_with_tenant(tenant_id) as db_session:
@@ -501,6 +815,7 @@ def connector_indexing_task(
raise ValueError(
f"Index attempt not found: index_attempt={index_attempt_id}"
)
attempt_found = True
cc_pair = get_connector_credential_pair_from_id(
cc_pair_id=cc_pair_id,
@@ -520,43 +835,52 @@ def connector_indexing_task(
f"Credential not found: cc_pair={cc_pair_id} credential={cc_pair.credential_id}"
)
rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
# define a callback class
callback = IndexingCallback(
redis_connector.stop.fence_key,
redis_connector_index.generator_progress_key,
lock,
r,
)
# define a callback class
callback = RunIndexingCallback(
rcs.fence_key, rci.generator_progress_key, lock, r
)
logger.info(
f"Indexing spawned task running entrypoint: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
run_indexing_entrypoint(
index_attempt_id,
tenant_id,
cc_pair_id,
is_ee,
callback=callback,
)
run_indexing_entrypoint(
index_attempt_id,
tenant_id,
cc_pair_id,
is_ee,
callback=callback,
)
# get back the total number of indexed docs and return it
generator_progress_value = r.get(rci.generator_progress_key)
if generator_progress_value is not None:
try:
n_final_progress = int(cast(int, generator_progress_value))
except ValueError:
pass
r.set(rci.generator_complete_key, HTTPStatus.OK.value)
# get back the total number of indexed docs and return it
n_final_progress = redis_connector_index.get_progress()
redis_connector_index.set_generator_complete(HTTPStatus.OK.value)
except Exception as e:
task_logger.exception(f"Indexing failed: cc_pair={cc_pair_id}")
if attempt:
logger.exception(
f"Indexing spawned task failed: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
if attempt_found:
with get_session_with_tenant(tenant_id) as db_session:
mark_attempt_failed(attempt, db_session, failure_reason=str(e))
mark_attempt_failed(index_attempt_id, db_session, failure_reason=str(e))
r.delete(rci.generator_lock_key)
r.delete(rci.generator_progress_key)
r.delete(rci.taskset_key)
r.delete(rci.fence_key)
raise e
finally:
if lock.owned():
lock.release()
logger.info(
f"Indexing spawned task finished: attempt={index_attempt_id} "
f"tenant={tenant_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id}"
)
return n_final_progress

View File

@@ -13,12 +13,13 @@ from sqlalchemy.orm import Session
from danswer.background.celery.apps.app_base import task_logger
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import PostgresAdvisoryLocks
from danswer.db.engine import get_session_with_tenant
@shared_task(
name="kombu_message_cleanup_task",
name=DanswerCeleryTask.KOMBU_MESSAGE_CLEANUP_TASK,
soft_time_limit=JOB_TIMEOUT,
bind=True,
base=AbortableTask,

View File

@@ -8,14 +8,12 @@ from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from redis import Redis
from redis.lock import Lock as RedisLock
from sqlalchemy.orm import Session
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorPruning
from danswer.background.celery.celery_redis import RedisConnectorStop
from danswer.background.celery.celery_utils import extract_ids_from_runnable_connector
from danswer.background.celery.tasks.indexing.tasks import RunIndexingCallback
from danswer.background.celery.tasks.indexing.tasks import IndexingCallback
from danswer.configs.app_configs import ALLOW_SIMULTANEOUS_PRUNING
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import CELERY_PRUNING_LOCK_TIMEOUT
@@ -23,6 +21,7 @@ from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
from danswer.configs.constants import DanswerCeleryPriority
from danswer.configs.constants import DanswerCeleryQueues
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.connectors.factory import instantiate_connector
from danswer.connectors.models import InputType
@@ -33,14 +32,52 @@ from danswer.db.document import get_documents_for_connector_credential_pair
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import ConnectorCredentialPairStatus
from danswer.db.models import ConnectorCredentialPair
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_pool import get_redis_client
from danswer.utils.logger import pruning_ctx
from danswer.utils.logger import setup_logger
logger = setup_logger()
def _is_pruning_due(cc_pair: ConnectorCredentialPair) -> bool:
"""Returns boolean indicating if pruning is due.
Next pruning time is calculated as a delta from the last successful prune, or the
last successful indexing if pruning has never succeeded.
TODO(rkuo): consider whether we should allow pruning to be immediately rescheduled
if pruning fails (which is what it does now). A backoff could be reasonable.
"""
# skip pruning if no prune frequency is set
# pruning can still be forced via the API which will run a pruning task directly
if not cc_pair.connector.prune_freq:
return False
# skip pruning if not active
if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
return False
# skip pruning if the next scheduled prune time hasn't been reached yet
last_pruned = cc_pair.last_pruned
if not last_pruned:
if not cc_pair.last_successful_index_time:
# if we've never indexed, we can't prune
return False
# if never pruned, use the last time the connector indexed successfully
last_pruned = cc_pair.last_successful_index_time
next_prune = last_pruned + timedelta(seconds=cc_pair.connector.prune_freq)
if datetime.now(timezone.utc) < next_prune:
return False
return True
@shared_task(
name="check_for_pruning",
name=DanswerCeleryTask.CHECK_FOR_PRUNING,
soft_time_limit=JOB_TIMEOUT,
bind=True,
)
@@ -70,7 +107,7 @@ def check_for_pruning(self: Task, *, tenant_id: str | None) -> None:
if not cc_pair:
continue
if not is_pruning_due(cc_pair, db_session, r):
if not _is_pruning_due(cc_pair):
continue
tasks_created = try_creating_prune_generator_task(
@@ -79,59 +116,18 @@ def check_for_pruning(self: Task, *, tenant_id: str | None) -> None:
if not tasks_created:
continue
task_logger.info(f"Pruning queued: cc_pair_id={cc_pair.id}")
task_logger.info(f"Pruning queued: cc_pair={cc_pair.id}")
except SoftTimeLimitExceeded:
task_logger.info(
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception("Unexpected exception")
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
def is_pruning_due(
cc_pair: ConnectorCredentialPair,
db_session: Session,
r: Redis,
) -> bool:
"""Returns an int if pruning is triggered.
The int represents the number of prune tasks generated (in this case, only one
because the task is a long running generator task.)
Returns None if no pruning is triggered (due to not being needed or
other reasons such as simultaneous pruning restrictions.
Checks for scheduling related conditions, then delegates the rest of the checks to
try_creating_prune_generator_task.
"""
# skip pruning if no prune frequency is set
# pruning can still be forced via the API which will run a pruning task directly
if not cc_pair.connector.prune_freq:
return False
# skip pruning if not active
if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
return False
# skip pruning if the next scheduled prune time hasn't been reached yet
last_pruned = cc_pair.last_pruned
if not last_pruned:
if not cc_pair.last_successful_index_time:
# if we've never indexed, we can't prune
return False
# if never pruned, use the last time the connector indexed successfully
last_pruned = cc_pair.last_successful_index_time
next_prune = last_pruned + timedelta(seconds=cc_pair.connector.prune_freq)
if datetime.now(timezone.utc) < next_prune:
return False
return True
def try_creating_prune_generator_task(
celery_app: Celery,
cc_pair: ConnectorCredentialPair,
@@ -146,8 +142,11 @@ def try_creating_prune_generator_task(
is used to trigger prunes immediately, e.g. via the web ui.
"""
redis_connector = RedisConnector(tenant_id, cc_pair.id)
if not ALLOW_SIMULTANEOUS_PRUNING:
for key in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
count = redis_connector.prune.get_active_task_count()
if count > 0:
return None
LOCK_TIMEOUT = 30
@@ -164,15 +163,16 @@ def try_creating_prune_generator_task(
return None
try:
rcp = RedisConnectorPruning(cc_pair.id)
# skip pruning if already pruning
if r.exists(rcp.fence_key):
if redis_connector.prune.fenced:
return None
# skip pruning if the cc_pair is deleting
rcd = RedisConnectorDeletion(cc_pair.id)
if r.exists(rcd.fence_key):
if redis_connector.delete.fenced:
return None
# skip pruning if doc permissions sync is running
if redis_connector.permissions.fenced:
return None
db_session.refresh(cc_pair)
@@ -180,13 +180,13 @@ def try_creating_prune_generator_task(
return None
# add a long running generator task to the queue
r.delete(rcp.generator_complete_key)
r.delete(rcp.taskset_key)
redis_connector.prune.generator_clear()
redis_connector.prune.taskset_clear()
custom_task_id = f"{rcp.generator_task_id_prefix}_{uuid4()}"
custom_task_id = f"{redis_connector.prune.generator_task_key}_{uuid4()}"
celery_app.send_task(
"connector_pruning_generator_task",
DanswerCeleryTask.CONNECTOR_PRUNING_GENERATOR_TASK,
kwargs=dict(
cc_pair_id=cc_pair.id,
connector_id=cc_pair.connector_id,
@@ -199,9 +199,9 @@ def try_creating_prune_generator_task(
)
# set this only after all tasks have been added
r.set(rcp.fence_key, 1)
redis_connector.prune.set_fence(True)
except Exception:
task_logger.exception("Unexpected exception")
task_logger.exception(f"Unexpected exception: cc_pair={cc_pair.id}")
return None
finally:
if lock.owned():
@@ -211,7 +211,7 @@ def try_creating_prune_generator_task(
@shared_task(
name="connector_pruning_generator_task",
name=DanswerCeleryTask.CONNECTOR_PRUNING_GENERATOR_TASK,
acks_late=False,
soft_time_limit=JOB_TIMEOUT,
track_started=True,
@@ -229,13 +229,23 @@ def connector_pruning_generator_task(
and compares those IDs to locally stored documents and deletes all locally stored IDs missing
from the most recently pulled document ID list"""
pruning_ctx_dict = pruning_ctx.get()
pruning_ctx_dict["cc_pair_id"] = cc_pair_id
pruning_ctx_dict["request_id"] = self.request.id
pruning_ctx.set(pruning_ctx_dict)
task_logger.info(f"Pruning generator starting: cc_pair={cc_pair_id}")
redis_connector = RedisConnector(tenant_id, cc_pair_id)
r = get_redis_client(tenant_id=tenant_id)
rcp = RedisConnectorPruning(cc_pair_id)
lock = r.lock(
DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{rcp._id}",
# set thread_local=False since we don't control what thread the indexing/pruning
# might run our callback with
lock: RedisLock = r.lock(
DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{redis_connector.id}",
timeout=CELERY_PRUNING_LOCK_TIMEOUT,
thread_local=False,
)
acquired = lock.acquire(blocking=False)
@@ -259,6 +269,11 @@ def connector_pruning_generator_task(
)
return
task_logger.info(
f"Pruning generator running connector: "
f"cc_pair={cc_pair_id} "
f"connector_source={cc_pair.connector.source}"
)
runnable_connector = instantiate_connector(
db_session,
cc_pair.connector.source,
@@ -267,11 +282,13 @@ def connector_pruning_generator_task(
cc_pair.credential,
)
rcs = RedisConnectorStop(cc_pair_id)
callback = RunIndexingCallback(
rcs.fence_key, rcp.generator_progress_key, lock, r
callback = IndexingCallback(
redis_connector.stop.fence_key,
redis_connector.prune.generator_progress_key,
lock,
r,
)
# a list of docs in the source
all_connector_doc_ids: set[str] = extract_ids_from_runnable_connector(
runnable_connector, callback
@@ -293,36 +310,34 @@ def connector_pruning_generator_task(
task_logger.info(
f"Pruning set collected: "
f"cc_pair={cc_pair_id} "
f"docs_to_remove={len(doc_ids_to_remove)} "
f"doc_source={cc_pair.connector.source}"
f"connector_source={cc_pair.connector.source} "
f"docs_to_remove={len(doc_ids_to_remove)}"
)
rcp.documents_to_prune = set(doc_ids_to_remove)
task_logger.info(
f"RedisConnectorPruning.generate_tasks starting. cc_pair_id={cc_pair_id}"
f"RedisConnector.prune.generate_tasks starting. cc_pair={cc_pair_id}"
)
tasks_generated = rcp.generate_tasks(
self.app, db_session, r, None, tenant_id
tasks_generated = redis_connector.prune.generate_tasks(
set(doc_ids_to_remove), self.app, db_session, None
)
if tasks_generated is None:
return None
task_logger.info(
f"RedisConnectorPruning.generate_tasks finished. "
f"RedisConnector.prune.generate_tasks finished. "
f"cc_pair={cc_pair_id} tasks_generated={tasks_generated}"
)
r.set(rcp.generator_complete_key, tasks_generated)
redis_connector.prune.generator_complete = tasks_generated
except Exception as e:
task_logger.exception(
f"Failed to run pruning: cc_pair={cc_pair_id} connector={connector_id}"
)
r.delete(rcp.generator_progress_key)
r.delete(rcp.taskset_key)
r.delete(rcp.fence_key)
redis_connector.prune.reset()
raise e
finally:
if lock.owned():
lock.release()
task_logger.info(f"Pruning generator finished: cc_pair={cc_pair_id}")

View File

@@ -1,8 +0,0 @@
from datetime import datetime
from pydantic import BaseModel
class RedisConnectorDeletionFenceData(BaseModel):
num_tasks: int | None
submitted: datetime

View File

@@ -1,10 +0,0 @@
from datetime import datetime
from pydantic import BaseModel
class RedisConnectorIndexingFenceData(BaseModel):
index_attempt_id: int | None
started: datetime | None
submitted: datetime
celery_task_id: str | None

View File

@@ -0,0 +1,40 @@
import httpx
from tenacity import retry
from tenacity import retry_if_exception_type
from tenacity import stop_after_delay
from tenacity import wait_random_exponential
from danswer.document_index.interfaces import DocumentIndex
from danswer.document_index.interfaces import VespaDocumentFields
class RetryDocumentIndex:
"""A wrapper class to help with specific retries against Vespa involving
read timeouts.
wait_random_exponential implements full jitter as per this article:
https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/"""
MAX_WAIT = 30
# STOP_AFTER + MAX_WAIT should be slightly less (5?) than the celery soft_time_limit
STOP_AFTER = 70
def __init__(self, index: DocumentIndex):
self.index: DocumentIndex = index
@retry(
retry=retry_if_exception_type(httpx.ReadTimeout),
wait=wait_random_exponential(multiplier=1, max=MAX_WAIT),
stop=stop_after_delay(STOP_AFTER),
)
def delete_single(self, doc_id: str) -> int:
return self.index.delete_single(doc_id)
@retry(
retry=retry_if_exception_type(httpx.ReadTimeout),
wait=wait_random_exponential(multiplier=1, max=MAX_WAIT),
stop=stop_after_delay(STOP_AFTER),
)
def update_single(self, doc_id: str, fields: VespaDocumentFields) -> int:
return self.index.update_single(doc_id, fields)

View File

@@ -1,9 +1,15 @@
from http import HTTPStatus
import httpx
from celery import shared_task
from celery import Task
from celery.exceptions import SoftTimeLimitExceeded
from tenacity import RetryError
from danswer.access.access import get_access_for_document
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.tasks.shared.RetryDocumentIndex import RetryDocumentIndex
from danswer.configs.constants import DanswerCeleryTask
from danswer.db.document import delete_document_by_connector_credential_pair__no_commit
from danswer.db.document import delete_documents_complete__no_commit
from danswer.db.document import get_document
@@ -20,12 +26,17 @@ from danswer.server.documents.models import ConnectorCredentialPairIdentifier
DOCUMENT_BY_CC_PAIR_CLEANUP_MAX_RETRIES = 3
# 5 seconds more than RetryDocumentIndex STOP_AFTER+MAX_WAIT
LIGHT_SOFT_TIME_LIMIT = 105
LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
@shared_task(
name="document_by_cc_pair_cleanup_task",
bind=True,
soft_time_limit=45,
time_limit=60,
name=DanswerCeleryTask.DOCUMENT_BY_CC_PAIR_CLEANUP_TASK,
soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
time_limit=LIGHT_TIME_LIMIT,
max_retries=DOCUMENT_BY_CC_PAIR_CLEANUP_MAX_RETRIES,
bind=True,
)
def document_by_cc_pair_cleanup_task(
self: Task,
@@ -49,7 +60,7 @@ def document_by_cc_pair_cleanup_task(
connector / credential pair from the access list
(6) delete all relevant entries from postgres
"""
task_logger.info(f"tenant_id={tenant_id} document_id={document_id}")
task_logger.debug(f"Task start: tenant={tenant_id} doc={document_id}")
try:
with get_session_with_tenant(tenant_id) as db_session:
@@ -57,17 +68,19 @@ def document_by_cc_pair_cleanup_task(
chunks_affected = 0
curr_ind_name, sec_ind_name = get_both_index_names(db_session)
document_index = get_default_document_index(
doc_index = get_default_document_index(
primary_index_name=curr_ind_name, secondary_index_name=sec_ind_name
)
retry_index = RetryDocumentIndex(doc_index)
count = get_document_connector_count(db_session, document_id)
if count == 1:
# count == 1 means this is the only remaining cc_pair reference to the doc
# delete it from vespa and the db
action = "delete"
chunks_affected = document_index.delete_single(document_id)
chunks_affected = retry_index.delete_single(document_id)
delete_documents_complete__no_commit(
db_session=db_session,
document_ids=[document_id],
@@ -97,9 +110,7 @@ def document_by_cc_pair_cleanup_task(
)
# update Vespa. OK if doc doesn't exist. Raises exception otherwise.
chunks_affected = document_index.update_single(
document_id, fields=fields
)
chunks_affected = retry_index.update_single(document_id, fields=fields)
# there are still other cc_pair references to the doc, so just resync to Vespa
delete_document_by_connector_credential_pair__no_commit(
@@ -118,19 +129,43 @@ def document_by_cc_pair_cleanup_task(
db_session.commit()
task_logger.info(
f"tenant_id={tenant_id} "
f"document_id={document_id} "
f"tenant={tenant_id} "
f"doc={document_id} "
f"action={action} "
f"refcount={count} "
f"chunks={chunks_affected}"
)
except SoftTimeLimitExceeded:
task_logger.info(
f"SoftTimeLimitExceeded exception. tenant_id={tenant_id} doc_id={document_id}"
f"SoftTimeLimitExceeded exception. tenant={tenant_id} doc={document_id}"
)
return False
except Exception as e:
task_logger.exception("Unexpected exception")
except Exception as ex:
if isinstance(ex, RetryError):
task_logger.warning(
f"Tenacity retry failed: num_attempts={ex.last_attempt.attempt_number}"
)
# only set the inner exception if it is of type Exception
e_temp = ex.last_attempt.exception()
if isinstance(e_temp, Exception):
e = e_temp
else:
e = ex
if isinstance(e, httpx.HTTPStatusError):
if e.response.status_code == HTTPStatus.BAD_REQUEST:
task_logger.exception(
f"Non-retryable HTTPStatusError: "
f"tenant={tenant_id} "
f"doc={document_id} "
f"status={e.response.status_code}"
)
return False
task_logger.exception(
f"Unexpected exception: tenant={tenant_id} doc={document_id}"
)
if self.request.retries < DOCUMENT_BY_CC_PAIR_CLEANUP_MAX_RETRIES:
# Still retrying. Exponential backoff from 2^4 to 2^6 ... i.e. 16, 32, 64
@@ -139,11 +174,21 @@ def document_by_cc_pair_cleanup_task(
else:
# This is the last attempt! mark the document as dirty in the db so that it
# eventually gets fixed out of band via stale document reconciliation
task_logger.info(
f"Max retries reached. Marking doc as dirty for reconciliation: "
f"tenant_id={tenant_id} document_id={document_id}"
task_logger.warning(
f"Max celery task retries reached. Marking doc as dirty for reconciliation: "
f"tenant={tenant_id} doc={document_id}"
)
with get_session_with_tenant(tenant_id):
with get_session_with_tenant(tenant_id) as db_session:
# delete the cc pair relationship now and let reconciliation clean it up
# in vespa
delete_document_by_connector_credential_pair__no_commit(
db_session=db_session,
document_id=document_id,
connector_credential_pair_identifier=ConnectorCredentialPairIdentifier(
connector_id=connector_id,
credential_id=credential_id,
),
)
mark_document_as_modified(document_id, db_session)
return False

View File

@@ -4,7 +4,7 @@ from datetime import timezone
from http import HTTPStatus
from typing import cast
import redis
import httpx
from celery import Celery
from celery import shared_task
from celery import Task
@@ -12,28 +12,23 @@ from celery.exceptions import SoftTimeLimitExceeded
from celery.result import AsyncResult
from celery.states import READY_STATES
from redis import Redis
from redis.lock import Lock as RedisLock
from sqlalchemy.orm import Session
from tenacity import RetryError
from danswer.access.access import get_access_for_document
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_redis import celery_get_queue_length
from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
from danswer.background.celery.celery_redis import RedisConnectorDeletion
from danswer.background.celery.celery_redis import RedisConnectorIndexing
from danswer.background.celery.celery_redis import RedisConnectorPruning
from danswer.background.celery.celery_redis import RedisDocumentSet
from danswer.background.celery.celery_redis import RedisUserGroup
from danswer.background.celery.tasks.shared.RedisConnectorDeletionFenceData import (
RedisConnectorDeletionFenceData,
)
from danswer.background.celery.tasks.shared.RedisConnectorIndexingFenceData import (
RedisConnectorIndexingFenceData,
)
from danswer.background.celery.tasks.shared.RetryDocumentIndex import RetryDocumentIndex
from danswer.background.celery.tasks.shared.tasks import LIGHT_SOFT_TIME_LIMIT
from danswer.background.celery.tasks.shared.tasks import LIGHT_TIME_LIMIT
from danswer.configs.app_configs import JOB_TIMEOUT
from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
from danswer.configs.constants import DanswerCeleryQueues
from danswer.configs.constants import DanswerCeleryTask
from danswer.configs.constants import DanswerRedisLocks
from danswer.db.connector import fetch_connector_by_id
from danswer.db.connector import mark_cc_pair_as_permissions_synced
from danswer.db.connector import mark_ccpair_as_pruned
from danswer.db.connector_credential_pair import add_deletion_failure_message
from danswer.db.connector_credential_pair import (
@@ -54,15 +49,24 @@ from danswer.db.document_set import mark_document_set_as_synced
from danswer.db.engine import get_session_with_tenant
from danswer.db.enums import IndexingStatus
from danswer.db.index_attempt import delete_index_attempts
from danswer.db.index_attempt import get_all_index_attempts_by_status
from danswer.db.index_attempt import get_index_attempt
from danswer.db.index_attempt import mark_attempt_failed
from danswer.db.models import DocumentSet
from danswer.db.models import IndexAttempt
from danswer.document_index.document_index_utils import get_both_index_names
from danswer.document_index.factory import get_default_document_index
from danswer.document_index.interfaces import VespaDocumentFields
from danswer.redis.redis_connector import RedisConnector
from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
from danswer.redis.redis_connector_delete import RedisConnectorDelete
from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
from danswer.redis.redis_connector_doc_perm_sync import (
RedisConnectorPermissionSyncPayload,
)
from danswer.redis.redis_connector_index import RedisConnectorIndex
from danswer.redis.redis_connector_prune import RedisConnectorPrune
from danswer.redis.redis_document_set import RedisDocumentSet
from danswer.redis.redis_pool import get_redis_client
from danswer.redis.redis_usergroup import RedisUserGroup
from danswer.utils.logger import setup_logger
from danswer.utils.variable_functionality import fetch_versioned_implementation
from danswer.utils.variable_functionality import (
@@ -77,7 +81,7 @@ logger = setup_logger()
# celery auto associates tasks created inside another task,
# which bloats the result metadata considerably. trail=False prevents this.
@shared_task(
name="check_for_vespa_sync_task",
name=DanswerCeleryTask.CHECK_FOR_VESPA_SYNC_TASK,
soft_time_limit=JOB_TIMEOUT,
trail=False,
bind=True,
@@ -152,7 +156,7 @@ def check_for_vespa_sync_task(self: Task, *, tenant_id: str | None) -> None:
"Soft time limit exceeded, task is being terminated gracefully."
)
except Exception:
task_logger.exception("Unexpected exception")
task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
finally:
if lock_beat.owned():
lock_beat.release()
@@ -162,7 +166,7 @@ def try_generate_stale_document_sync_tasks(
celery_app: Celery,
db_session: Session,
r: Redis,
lock_beat: redis.lock.Lock,
lock_beat: RedisLock,
tenant_id: str | None,
) -> int | None:
# the fence is up, do nothing
@@ -180,30 +184,34 @@ def try_generate_stale_document_sync_tasks(
f"Stale documents found (at least {stale_doc_count}). Generating sync tasks by cc pair."
)
task_logger.info("RedisConnector.generate_tasks starting by cc_pair.")
task_logger.info(
"RedisConnector.generate_tasks starting by cc_pair. "
"Documents spanning multiple cc_pairs will only be synced once."
)
docs_to_skip: set[str] = set()
# rkuo: we could technically sync all stale docs in one big pass.
# but I feel it's more understandable to group the docs by cc_pair
total_tasks_generated = 0
cc_pairs = get_connector_credential_pairs(db_session)
for cc_pair in cc_pairs:
rc = RedisConnectorCredentialPair(cc_pair.id)
tasks_generated = rc.generate_tasks(
celery_app, db_session, r, lock_beat, tenant_id
)
rc = RedisConnectorCredentialPair(tenant_id, cc_pair.id)
rc.set_skip_docs(docs_to_skip)
result = rc.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
if tasks_generated is None:
if result is None:
continue
if tasks_generated == 0:
if result[1] == 0:
continue
task_logger.info(
f"RedisConnector.generate_tasks finished for single cc_pair. "
f"cc_pair_id={cc_pair.id} tasks_generated={tasks_generated}"
f"cc_pair={cc_pair.id} tasks_generated={result[0]} tasks_possible={result[1]}"
)
total_tasks_generated += tasks_generated
total_tasks_generated += result[0]
task_logger.info(
f"RedisConnector.generate_tasks finished for all cc_pairs. total_tasks_generated={total_tasks_generated}"
@@ -218,15 +226,15 @@ def try_generate_document_set_sync_tasks(
document_set_id: int,
db_session: Session,
r: Redis,
lock_beat: redis.lock.Lock,
lock_beat: RedisLock,
tenant_id: str | None,
) -> int | None:
lock_beat.reacquire()
rds = RedisDocumentSet(document_set_id)
rds = RedisDocumentSet(tenant_id, document_set_id)
# don't generate document set sync tasks if tasks are still pending
if r.exists(rds.fence_key):
if rds.fenced:
return None
# don't generate sync tasks if we're up to date
@@ -246,12 +254,11 @@ def try_generate_document_set_sync_tasks(
)
# Add all documents that need to be updated into the queue
tasks_generated = rds.generate_tasks(
celery_app, db_session, r, lock_beat, tenant_id
)
if tasks_generated is None:
result = rds.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
if result is None:
return None
tasks_generated = result[0]
# Currently we are allowing the sync to proceed with 0 tasks.
# It's possible for sets/groups to be generated initially with no entries
# and they still need to be marked as up to date.
@@ -260,11 +267,11 @@ def try_generate_document_set_sync_tasks(
task_logger.info(
f"RedisDocumentSet.generate_tasks finished. "
f"document_set_id={document_set.id} tasks_generated={tasks_generated}"
f"document_set={document_set.id} tasks_generated={tasks_generated}"
)
# set this only after all tasks have been added
r.set(rds.fence_key, tasks_generated)
rds.set_fence(tasks_generated)
return tasks_generated
@@ -273,15 +280,14 @@ def try_generate_user_group_sync_tasks(
usergroup_id: int,
db_session: Session,
r: Redis,
lock_beat: redis.lock.Lock,
lock_beat: RedisLock,
tenant_id: str | None,
) -> int | None:
lock_beat.reacquire()
rug = RedisUserGroup(usergroup_id)
# don't generate sync tasks if tasks are still pending
if r.exists(rug.fence_key):
rug = RedisUserGroup(tenant_id, usergroup_id)
if rug.fenced:
# don't generate sync tasks if tasks are still pending
return None
# race condition with the monitor/cleanup function if we use a cached result!
@@ -303,12 +309,11 @@ def try_generate_user_group_sync_tasks(
task_logger.info(
f"RedisUserGroup.generate_tasks starting. usergroup_id={usergroup.id}"
)
tasks_generated = rug.generate_tasks(
celery_app, db_session, r, lock_beat, tenant_id
)
if tasks_generated is None:
result = rug.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
if result is None:
return None
tasks_generated = result[0]
# Currently we are allowing the sync to proceed with 0 tasks.
# It's possible for sets/groups to be generated initially with no entries
# and they still need to be marked as up to date.
@@ -317,11 +322,11 @@ def try_generate_user_group_sync_tasks(
task_logger.info(
f"RedisUserGroup.generate_tasks finished. "
f"usergroup_id={usergroup.id} tasks_generated={tasks_generated}"
f"usergroup={usergroup.id} tasks_generated={tasks_generated}"
)
# set this only after all tasks have been added
r.set(rug.fence_key, tasks_generated)
rug.set_fence(tasks_generated)
return tasks_generated
@@ -347,7 +352,7 @@ def monitor_connector_taskset(r: Redis) -> None:
def monitor_document_set_taskset(
key_bytes: bytes, r: Redis, db_session: Session
tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
) -> None:
fence_key = key_bytes.decode("utf-8")
document_set_id_str = RedisDocumentSet.get_id_from_fence_key(fence_key)
@@ -357,16 +362,12 @@ def monitor_document_set_taskset(
document_set_id = int(document_set_id_str)
rds = RedisDocumentSet(document_set_id)
fence_value = r.get(rds.fence_key)
if fence_value is None:
rds = RedisDocumentSet(tenant_id, document_set_id)
if not rds.fenced:
return
try:
initial_count = int(cast(int, fence_value))
except ValueError:
task_logger.error("The value is not an integer.")
initial_count = rds.payload
if initial_count is None:
return
count = cast(int, r.scard(rds.taskset_key))
@@ -394,48 +395,38 @@ def monitor_document_set_taskset(
f"Successfully synced document set: document_set={document_set_id}"
)
r.delete(rds.taskset_key)
r.delete(rds.fence_key)
rds.reset()
def monitor_connector_deletion_taskset(
key_bytes: bytes, r: Redis, tenant_id: str | None
tenant_id: str | None, key_bytes: bytes, r: Redis
) -> None:
fence_key = key_bytes.decode("utf-8")
cc_pair_id_str = RedisConnectorDeletion.get_id_from_fence_key(fence_key)
cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
if cc_pair_id_str is None:
task_logger.warning(f"could not parse cc_pair_id from {fence_key}")
return
cc_pair_id = int(cc_pair_id_str)
rcd = RedisConnectorDeletion(cc_pair_id)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
# read related data and evaluate/print task progress
fence_value = cast(bytes, r.get(rcd.fence_key))
if fence_value is None:
fence_data = redis_connector.delete.payload
if not fence_data:
task_logger.warning(
f"Connector deletion - fence payload invalid: cc_pair={cc_pair_id}"
)
return
try:
fence_json = fence_value.decode("utf-8")
fence_data = RedisConnectorDeletionFenceData.model_validate_json(
cast(str, fence_json)
)
except ValueError:
task_logger.exception(
"monitor_ccpair_indexing_taskset: fence_data not decodeable."
)
raise
# the fence is setting up but isn't ready yet
if fence_data.num_tasks is None:
# the fence is setting up but isn't ready yet
return
count = cast(int, r.scard(rcd.taskset_key))
remaining = redis_connector.delete.get_remaining()
task_logger.info(
f"Connector deletion progress: cc_pair={cc_pair_id} remaining={count} initial={fence_data.num_tasks}"
f"Connector deletion progress: cc_pair={cc_pair_id} remaining={remaining} initial={fence_data.num_tasks}"
)
if count > 0:
if remaining > 0:
return
with get_session_with_tenant(tenant_id) as db_session:
@@ -451,11 +442,22 @@ def monitor_connector_deletion_taskset(
db_session, cc_pair.connector_id, cc_pair.credential_id
)
if len(doc_ids) > 0:
# if this happens, documents somehow got added while deletion was in progress. Likely a bug
# gating off pruning and indexing work before deletion starts
# NOTE(rkuo): if this happens, documents somehow got added while
# deletion was in progress. Likely a bug gating off pruning and indexing
# work before deletion starts.
task_logger.warning(
f"Connector deletion - documents still found after taskset completion: "
f"cc_pair={cc_pair_id} num={len(doc_ids)}"
"Connector deletion - documents still found after taskset completion. "
"Clearing the current deletion attempt and allowing deletion to restart: "
f"cc_pair={cc_pair_id} "
f"docs_deleted={fence_data.num_tasks} "
f"docs_remaining={len(doc_ids)}"
)
# We don't want to waive off why we get into this state, but resetting
# our attempt and letting the deletion restart is a good way to recover
redis_connector.delete.reset()
raise RuntimeError(
"Connector deletion - documents still found after taskset completion"
)
# clean up the rest of the related Postgres entities
@@ -519,15 +521,14 @@ def monitor_connector_deletion_taskset(
f"docs_deleted={fence_data.num_tasks}"
)
r.delete(rcd.taskset_key)
r.delete(rcd.fence_key)
redis_connector.delete.reset()
def monitor_ccpair_pruning_taskset(
key_bytes: bytes, r: Redis, db_session: Session
tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
) -> None:
fence_key = key_bytes.decode("utf-8")
cc_pair_id_str = RedisConnectorPruning.get_id_from_fence_key(fence_key)
cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
if cc_pair_id_str is None:
task_logger.warning(
f"monitor_ccpair_pruning_taskset: could not parse cc_pair_id from {fence_key}"
@@ -536,46 +537,76 @@ def monitor_ccpair_pruning_taskset(
cc_pair_id = int(cc_pair_id_str)
rcp = RedisConnectorPruning(cc_pair_id)
fence_value = r.get(rcp.fence_key)
if fence_value is None:
redis_connector = RedisConnector(tenant_id, cc_pair_id)
if not redis_connector.prune.fenced:
return
generator_value = r.get(rcp.generator_complete_key)
if generator_value is None:
initial = redis_connector.prune.generator_complete
if initial is None:
return
try:
initial_count = int(cast(int, generator_value))
except ValueError:
task_logger.error("The value is not an integer.")
return
count = cast(int, r.scard(rcp.taskset_key))
remaining = redis_connector.prune.get_remaining()
task_logger.info(
f"Connector pruning progress: cc_pair_id={cc_pair_id} remaining={count} initial={initial_count}"
f"Connector pruning progress: cc_pair={cc_pair_id} remaining={remaining} initial={initial}"
)
if count > 0:
if remaining > 0:
return
mark_ccpair_as_pruned(int(cc_pair_id), db_session)
task_logger.info(
f"Successfully pruned connector credential pair. cc_pair_id={cc_pair_id}"
f"Successfully pruned connector credential pair. cc_pair={cc_pair_id}"
)
r.delete(rcp.taskset_key)
r.delete(rcp.generator_progress_key)
r.delete(rcp.generator_complete_key)
r.delete(rcp.fence_key)
redis_connector.prune.taskset_clear()
redis_connector.prune.generator_clear()
redis_connector.prune.set_fence(False)
def monitor_ccpair_permissions_taskset(
tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
) -> None:
fence_key = key_bytes.decode("utf-8")
cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
if cc_pair_id_str is None:
task_logger.warning(
f"monitor_ccpair_permissions_taskset: could not parse cc_pair_id from {fence_key}"
)
return
cc_pair_id = int(cc_pair_id_str)
redis_connector = RedisConnector(tenant_id, cc_pair_id)
if not redis_connector.permissions.fenced:
return
initial = redis_connector.permissions.generator_complete
if initial is None:
return
remaining = redis_connector.permissions.get_remaining()
task_logger.info(
f"Permissions sync progress: cc_pair={cc_pair_id} remaining={remaining} initial={initial}"
)
if remaining > 0:
return
payload: RedisConnectorPermissionSyncPayload | None = (
redis_connector.permissions.payload
)
start_time: datetime | None = payload.started if payload else None
mark_cc_pair_as_permissions_synced(db_session, int(cc_pair_id), start_time)
task_logger.info(f"Successfully synced permissions for cc_pair={cc_pair_id}")
redis_connector.permissions.reset()
def monitor_ccpair_indexing_taskset(
key_bytes: bytes, r: Redis, db_session: Session
tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
) -> None:
# if the fence doesn't exist, there's nothing to do
fence_key = key_bytes.decode("utf-8")
composite_id = RedisConnectorIndexing.get_id_from_fence_key(fence_key)
composite_id = RedisConnector.get_id_from_fence_key(fence_key)
if composite_id is None:
task_logger.warning(
f"monitor_ccpair_indexing_taskset: could not parse composite_id from {fence_key}"
@@ -590,103 +621,94 @@ def monitor_ccpair_indexing_taskset(
cc_pair_id = int(parts[0])
search_settings_id = int(parts[1])
rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
# read related data and evaluate/print task progress
fence_value = cast(bytes, r.get(rci.fence_key))
if fence_value is None:
redis_connector = RedisConnector(tenant_id, cc_pair_id)
redis_connector_index = redis_connector.new_index(search_settings_id)
if not redis_connector_index.fenced:
return
try:
fence_json = fence_value.decode("utf-8")
fence_data = RedisConnectorIndexingFenceData.model_validate_json(
cast(str, fence_json)
payload = redis_connector_index.payload
if not payload:
return
elapsed_submitted = datetime.now(timezone.utc) - payload.submitted
progress = redis_connector_index.get_progress()
if progress is not None:
task_logger.info(
f"Connector indexing progress: cc_pair={cc_pair_id} "
f"search_settings={search_settings_id} "
f"progress={progress} "
f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
)
except ValueError:
task_logger.exception(
"monitor_ccpair_indexing_taskset: fence_data not decodeable."
)
raise
elapsed_submitted = datetime.now(timezone.utc) - fence_data.submitted
generator_progress_value = r.get(rci.generator_progress_key)
if generator_progress_value is not None:
try:
progress_count = int(cast(int, generator_progress_value))
task_logger.info(
f"Connector indexing progress: cc_pair_id={cc_pair_id} "
f"search_settings_id={search_settings_id} "
f"progress={progress_count} "
f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
)
except ValueError:
task_logger.error(
"monitor_ccpair_indexing_taskset: generator_progress_value is not an integer."
)
if fence_data.index_attempt_id is None or fence_data.celery_task_id is None:
if payload.index_attempt_id is None or payload.celery_task_id is None:
# the task is still setting up
return
# Read result state BEFORE generator_complete_key to avoid a race condition
# never use any blocking methods on the result from inside a task!
result: AsyncResult = AsyncResult(fence_data.celery_task_id)
result_state = result.state
result: AsyncResult = AsyncResult(payload.celery_task_id)
generator_complete_value = r.get(rci.generator_complete_key)
if generator_complete_value is None:
if result_state in READY_STATES:
# IF the task state is READY, THEN generator_complete should be set
# if it isn't, then the worker crashed
task_logger.info(
f"Connector indexing aborted: "
f"cc_pair_id={cc_pair_id} "
f"search_settings_id={search_settings_id} "
f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
)
# inner/outer/inner double check pattern to avoid race conditions when checking for
# bad state
index_attempt = get_index_attempt(db_session, fence_data.index_attempt_id)
if index_attempt:
mark_attempt_failed(
index_attempt=index_attempt,
db_session=db_session,
failure_reason="Connector indexing aborted or exceptioned.",
# inner = get_completion / generator_complete not signaled
# outer = result.state in READY state
status_int = redis_connector_index.get_completion()
if status_int is None: # inner signal not set ... possible error
task_state = result.state
if (
task_state in READY_STATES
): # outer signal in terminal state ... possible error
# Now double check!
if redis_connector_index.get_completion() is None:
# inner signal still not set (and cannot change when outer result_state is READY)
# Task is finished but generator complete isn't set.
# We have a problem! Worker may have crashed.
task_result = str(result.result)
task_traceback = str(result.traceback)
msg = (
f"Connector indexing aborted or exceptioned: "
f"attempt={payload.index_attempt_id} "
f"celery_task={payload.celery_task_id} "
f"cc_pair={cc_pair_id} "
f"search_settings={search_settings_id} "
f"elapsed_submitted={elapsed_submitted.total_seconds():.2f} "
f"result.state={task_state} "
f"result.result={task_result} "
f"result.traceback={task_traceback}"
)
task_logger.warning(msg)
r.delete(rci.generator_lock_key)
r.delete(rci.taskset_key)
r.delete(rci.generator_progress_key)
r.delete(rci.generator_complete_key)
r.delete(rci.fence_key)
index_attempt = get_index_attempt(db_session, payload.index_attempt_id)
if index_attempt:
if (
index_attempt.status != IndexingStatus.CANCELED
and index_attempt.status != IndexingStatus.FAILED
):
mark_attempt_failed(
index_attempt_id=payload.index_attempt_id,
db_session=db_session,
failure_reason=msg,
)
redis_connector_index.reset()
return
status_enum = HTTPStatus.INTERNAL_SERVER_ERROR
try:
status_value = int(cast(int, generator_complete_value))
status_enum = HTTPStatus(status_value)
except ValueError:
task_logger.error(
f"monitor_ccpair_indexing_taskset: "
f"generator_complete_value=f{generator_complete_value} could not be parsed."
)
status_enum = HTTPStatus(status_int)
task_logger.info(
f"Connector indexing finished: cc_pair_id={cc_pair_id} "
f"search_settings_id={search_settings_id} "
f"Connector indexing finished: cc_pair={cc_pair_id} "
f"search_settings={search_settings_id} "
f"progress={progress} "
f"status={status_enum.name} "
f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
)
r.delete(rci.generator_lock_key)
r.delete(rci.taskset_key)
r.delete(rci.generator_progress_key)
r.delete(rci.generator_complete_key)
r.delete(rci.fence_key)
redis_connector_index.reset()
@shared_task(name="monitor_vespa_sync", soft_time_limit=300, bind=True)
@shared_task(name=DanswerCeleryTask.MONITOR_VESPA_SYNC, soft_time_limit=300, bind=True)
def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
"""This is a celery beat task that monitors and finalizes metadata sync tasksets.
It scans for fence values and then gets the counts of any associated tasksets.
@@ -695,11 +717,11 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
This task lock timeout is CELERY_METADATA_SYNC_BEAT_LOCK_TIMEOUT seconds, so don't
do anything too expensive in this function!
Returns True if the task actually did work, False
Returns True if the task actually did work, False if it exited early to prevent overlap
"""
r = get_redis_client(tenant_id=tenant_id)
lock_beat: redis.lock.Lock = r.lock(
lock_beat: RedisLock = r.lock(
DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK,
timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
)
@@ -711,7 +733,7 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
# print current queue lengths
r_celery = self.app.broker_connection().channel().client # type: ignore
n_celery = celery_get_queue_length("celery", r)
n_celery = celery_get_queue_length("celery", r_celery)
n_indexing = celery_get_queue_length(
DanswerCeleryQueues.CONNECTOR_INDEXING, r_celery
)
@@ -724,49 +746,33 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
n_pruning = celery_get_queue_length(
DanswerCeleryQueues.CONNECTOR_PRUNING, r_celery
)
n_permissions_sync = celery_get_queue_length(
DanswerCeleryQueues.CONNECTOR_DOC_PERMISSIONS_SYNC, r_celery
)
task_logger.info(
f"Queue lengths: celery={n_celery} "
f"indexing={n_indexing} "
f"sync={n_sync} "
f"deletion={n_deletion} "
f"pruning={n_pruning}"
f"pruning={n_pruning} "
f"permissions_sync={n_permissions_sync} "
)
# do some cleanup before clearing fences
# check the db for any outstanding index attempts
with get_session_with_tenant(tenant_id) as db_session:
attempts: list[IndexAttempt] = []
attempts.extend(
get_all_index_attempts_by_status(IndexingStatus.NOT_STARTED, db_session)
)
attempts.extend(
get_all_index_attempts_by_status(IndexingStatus.IN_PROGRESS, db_session)
)
for a in attempts:
# if attempts exist in the db but we don't detect them in redis, mark them as failed
rci = RedisConnectorIndexing(
a.connector_credential_pair_id, a.search_settings_id
)
failure_reason = f"Unknown index attempt {a.id}. Might be left over from a process restart."
if not r.exists(rci.fence_key):
mark_attempt_failed(a, db_session, failure_reason=failure_reason)
lock_beat.reacquire()
if r.exists(RedisConnectorCredentialPair.get_fence_key()):
monitor_connector_taskset(r)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisConnectorDeletion.FENCE_PREFIX + "*"):
for key_bytes in r.scan_iter(RedisConnectorDelete.FENCE_PREFIX + "*"):
lock_beat.reacquire()
monitor_connector_deletion_taskset(key_bytes, r, tenant_id)
monitor_connector_deletion_taskset(tenant_id, key_bytes, r)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisDocumentSet.FENCE_PREFIX + "*"):
lock_beat.reacquire()
with get_session_with_tenant(tenant_id) as db_session:
monitor_document_set_taskset(key_bytes, r, db_session)
monitor_document_set_taskset(tenant_id, key_bytes, r, db_session)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisUserGroup.FENCE_PREFIX + "*"):
@@ -777,19 +783,25 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
noop_fallback,
)
with get_session_with_tenant(tenant_id) as db_session:
monitor_usergroup_taskset(key_bytes, r, db_session)
monitor_usergroup_taskset(tenant_id, key_bytes, r, db_session)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
for key_bytes in r.scan_iter(RedisConnectorPrune.FENCE_PREFIX + "*"):
lock_beat.reacquire()
with get_session_with_tenant(tenant_id) as db_session:
monitor_ccpair_pruning_taskset(key_bytes, r, db_session)
monitor_ccpair_pruning_taskset(tenant_id, key_bytes, r, db_session)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisConnectorIndexing.FENCE_PREFIX + "*"):
for key_bytes in r.scan_iter(RedisConnectorIndex.FENCE_PREFIX + "*"):
lock_beat.reacquire()
with get_session_with_tenant(tenant_id) as db_session:
monitor_ccpair_indexing_taskset(key_bytes, r, db_session)
monitor_ccpair_indexing_taskset(tenant_id, key_bytes, r, db_session)
lock_beat.reacquire()
for key_bytes in r.scan_iter(RedisConnectorPermissionSync.FENCE_PREFIX + "*"):
lock_beat.reacquire()
with get_session_with_tenant(tenant_id) as db_session:
monitor_ccpair_permissions_taskset(tenant_id, key_bytes, r, db_session)
# uncomment for debugging if needed
# r_celery = celery_app.broker_connection().channel().client
@@ -807,24 +819,24 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
@shared_task(
name="vespa_metadata_sync_task",
name=DanswerCeleryTask.VESPA_METADATA_SYNC_TASK,
bind=True,
soft_time_limit=45,
time_limit=60,
soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
time_limit=LIGHT_TIME_LIMIT,
max_retries=3,
)
def vespa_metadata_sync_task(
self: Task, document_id: str, tenant_id: str | None
) -> bool:
task_logger.info(f"document_id={document_id}")
try:
with get_session_with_tenant(tenant_id) as db_session:
curr_ind_name, sec_ind_name = get_both_index_names(db_session)
document_index = get_default_document_index(
doc_index = get_default_document_index(
primary_index_name=curr_ind_name, secondary_index_name=sec_ind_name
)
retry_index = RetryDocumentIndex(doc_index)
doc = get_document(document_id, db_session)
if not doc:
return False
@@ -846,19 +858,45 @@ def vespa_metadata_sync_task(
)
# update Vespa. OK if doc doesn't exist. Raises exception otherwise.
chunks_affected = document_index.update_single(document_id, fields=fields)
chunks_affected = retry_index.update_single(document_id, fields)
# update db last. Worst case = we crash right before this and
# the sync might repeat again later
mark_document_as_synced(document_id, db_session)
task_logger.info(
f"document_id={document_id} action=sync chunks={chunks_affected}"
f"tenant={tenant_id} doc={document_id} action=sync chunks={chunks_affected}"
)
except SoftTimeLimitExceeded:
task_logger.info(f"SoftTimeLimitExceeded exception. doc_id={document_id}")
except Exception as e:
task_logger.exception("Unexpected exception")
task_logger.info(
f"SoftTimeLimitExceeded exception. tenant={tenant_id} doc={document_id}"
)
except Exception as ex:
if isinstance(ex, RetryError):
task_logger.warning(
f"Tenacity retry failed: num_attempts={ex.last_attempt.attempt_number}"
)
# only set the inner exception if it is of type Exception
e_temp = ex.last_attempt.exception()
if isinstance(e_temp, Exception):
e = e_temp
else:
e = ex
if isinstance(e, httpx.HTTPStatusError):
if e.response.status_code == HTTPStatus.BAD_REQUEST:
task_logger.exception(
f"Non-retryable HTTPStatusError: "
f"tenant={tenant_id} "
f"doc={document_id} "
f"status={e.response.status_code}"
)
return False
task_logger.exception(
f"Unexpected exception: tenant={tenant_id} doc={document_id}"
)
# Exponential backoff from 2^4 to 2^6 ... i.e. 16, 32, 64
countdown = 2 ** (self.request.retries + 4)

View File

@@ -1,8 +1,8 @@
"""Factory stub for running celery worker / celery beat."""
from danswer.utils.variable_functionality import fetch_versioned_implementation
from celery import Celery
from danswer.background.celery.apps.beat import celery_app
from danswer.utils.variable_functionality import set_is_ee_based_on_env_variable
set_is_ee_based_on_env_variable()
app = fetch_versioned_implementation(
"danswer.background.celery.apps.beat", "celery_app"
)
app: Celery = celery_app

View File

@@ -1,8 +1,10 @@
"""Factory stub for running celery worker / celery beat."""
from celery import Celery
from danswer.utils.variable_functionality import fetch_versioned_implementation
from danswer.utils.variable_functionality import set_is_ee_based_on_env_variable
set_is_ee_based_on_env_variable()
app = fetch_versioned_implementation(
app: Celery = fetch_versioned_implementation(
"danswer.background.celery.apps.primary", "celery_app"
)

View File

@@ -11,7 +11,8 @@ from typing import Any
from typing import Literal
from typing import Optional
from danswer.db.engine import get_sqlalchemy_engine
from danswer.configs.constants import POSTGRES_CELERY_WORKER_INDEXING_CHILD_APP_NAME
from danswer.db.engine import SqlEngine
from danswer.utils.logger import setup_logger
logger = setup_logger()
@@ -28,16 +29,26 @@ JobStatusType = (
def _initializer(
func: Callable, args: list | tuple, kwargs: dict[str, Any] | None = None
) -> Any:
"""Ensure the parent proc's database connections are not touched
in the new connection pool
"""Initialize the child process with a fresh SQLAlchemy Engine.
Based on the recommended approach in the SQLAlchemy docs found:
Based on SQLAlchemy's recommendations to handle multiprocessing:
https://docs.sqlalchemy.org/en/20/core/pooling.html#using-connection-pools-with-multiprocessing-or-os-fork
"""
if kwargs is None:
kwargs = {}
get_sqlalchemy_engine().dispose(close=False)
logger.info("Initializing spawned worker child process.")
# Reset the engine in the child process
SqlEngine.reset_engine()
# Optionally set a custom app name for database logging purposes
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_CHILD_APP_NAME)
# Initialize a new engine with desired parameters
SqlEngine.init_engine(pool_size=4, max_overflow=12, pool_recycle=60)
# Proceed with executing the target function
return func(*args, **kwargs)

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