## Support Scheduling Automations (#695)
1. Detect when user intends to schedule a task, aka reminder
- Support new `reminder` output mode to the response type chat actor
- Show examples of selecting the reminder output mode to the response type chat actor
2. Extract schedule time (as cron timestring) and inferred query to run from user message
3. Use APScheduler to call chat with inferred query at scheduled time
## Make Automations Persistent (#714)
- Make scheduled jobs persistent and work in multiple worker setups
- Add new operation Scheduled Job to Operation enum of ProcessLock
## Add UX to Configure Scheduled Tasks (#715)
- Add section in settings page to view, delete your scheduled tasks
- Add API endpoints to get and delete user scheduled tasks
## Make Automations more Robust. Improve UX (#718)
- Decouple Task Run from User Notification
- Make Scheduling more Robust
- Use JSON mode to get parse-able output from chat model
- Make timezone calculation programmatic on server instead of asking chat model
- Use django-apscheduler to handle apscheduler and django interfacing
- Improve automation UX. Move it out into separate top level page
- Allow creating, modifying automations from the automations page
- Infer cron from natural language client side to avoid roundtrip
- Pass user and calling_url to the scheduled chat too when modifying
params of automation
- Update to use user timezone even when update job via API
- Move timezone string to timezone object calculation into the
schedule automation method
- Previously it was a section in the settings page. Move it to
independent, top-level page to improve visibility of feature
- Calculate crontime from natural language on web client before
sending it to to server for saving new/updated schedule to disk.
- Avoids round-trip of call to chat model
- Convert POST /api/automation API endpoint into a direct request for
automation with query_to_run, subject and schedule provided via the
automation page. This allows more granular control to create automation
- Make the POST automations endpoint more robust; runs validation
checks, normalizes parameters
- Make the config page content use the same top level 3-column layout
as the khoj-header-wrapper
This ensures the content is aligned with heading pane width
- Let cards and other settings sections scale to the width of their
grid element. This utilizes more of the screen space and does it
consistently across the different settings pages
- Create new POST API endpoint to create automations
- Use it in the settings page on the web interface to create
new automations
This simplified managing automations from the setting page by allowing
both delete and create from the same page
- Render crontime string in natural language in message & settings UI
- Show more fields in tasks web config UI
- Add link to the tasks settings page in task scheduled chat response
- Improve task variables names
Rename executing_query to query_to_run. scheduling_query to
scheduling_request
- Make timezone aware scheduling programmatic, instead of asking the
chat model to do the conversion. This removes the need for
scratchpad and may let smaller models handle the task as well
- Make chat model infer subject for email. This should make the
notification email more readable
- Improve email by using subject in email subject, task heading. Move
query to email final paragraph, which is where task metadata should
go
- Using inferred_query directly was brittle (like previous job id)
- And process lock id had a limited size, so wouldn't work for larger
inferred query strings
- Pass timezone string from ipapi to khoj via clients
- Pass this data from web, desktop and obsidian clients to server
- Use user tz to render next run time of scheduled task in user tz
This takes the load of the task scheduling chat actor / prompt from
having to artifically differentiate query to create scheduled task
from a scheduled task run.
- The task scheduling actor was having trouble calculating the
timezone. Giving the actor a scratchpad to improve correctness by
thinking step by step
- Add more examples to reduce chances of the inferred query looping to
create another reminder instead of running the query and sharing
results with user
- Improve task scheduling chat actor test with more tests and
by ensuring unexpected words not present in response
There's a difference between running a scheduled task and notifying
the user about the results of running the scheduled task.
Decide to notify the user only when the results of running the
scheduled task satisfy the user's requirements.
Use sync version of send_message_to_model_wrapper for scheduled tasks
- Store scheduled job state in Postgres so job schedules persist
across app restarts
- Use Process Locks to only allow single worker to process a given job
type. This prevents duplicating job runs across all workers
- Detect when user intends to schedule a task, aka reminder
Add new output mode: reminder. Add example of selecting the reminder
output mode
- Extract schedule time (as cron timestring) and inferred query to run
from user message
- Use APScheduler to call chat with inferred query at scheduled time
- Handle reminder scheduling from both websocket and http chat requests
- Support constructing scheduled task using chat history as context
Pass chat history to scheduled query generator for improved context
for scheduled task generation
Previously the make delete API response failed, after deleting token.
Required a page refresh to see that the API token was actually gone.
This was happening because the response type of the delete token API
endpoint isn't a string, so it failed FastAPI response validation
checks.
