- Tag docker image with `tag_name' on release (i.e tag push)
- Else tag with 'pre' on push to master
- Else tag with 'dev' on push to PR branch
- Only tag the latest release with release tag
Previously the latest commit on master was being tagged with the
latest tag. This doesn't sync with the release cadence of the rest
of Khoj
- PyPi doesn't like to have files that start with numbers, however all of the generated django migration files start with numbers. To accommodate, skip this check.
- Refer to https://pypi.org/project/check-wheel-contents/ for documentation and recommendation
- Add a productionized setup for the Khoj server using `gunicorn` with multiple workers for handling requests
- Add a new Dockerfile meant for production config at `ghcr.io/khoj-ai/khoj:prod`; the existing Docker config should remain the same
- Partition configuration for indexing local data based on user accounts
- Store indexed data in an underlying postgres db using the `pgvector` extension
- Add migrations for all relevant user data and embeddings generation. Very little performance optimization has been done for the lookup time
- Apply filters using SQL queries
- Start removing many server-level configuration settings
- Configure GitHub test actions to run during any PR. Update the test action to run in a containerized environment with a DB.
- Update the Docker image and docker-compose.yml to work with the new application design
* Remove GPT4All dependency in pyproject.toml and use multiplatform builds in the dockerization setup in GH actions
* Move configure_search method into indexer
* Add conditional installation for gpt4all
* Add hint to go to localhost:42110 in the docs. Addresses #477
* Remove PySide, gui option from code
* Remove pyside 6 dependency from code
* Remove workflows which build desktop applications
* Update unit tests and update line in documentation
* Remove additional references to pyinstaller, gui
* Add uninstall steps to normal uninstall instructions
The test workflow fails regularly with an OperationCancelled error.
This is an intermittent failure that gets resolved on running the
failed workflows a few times.
- See if this fixes the issue with the workflows failing to install
system packages
- Make the build desktop app run on changes to the workflow file as well
* Add support for gpt4all's falcon model as an additional conversation processor
- Update the UI pages to allow the user to point to the new endpoints for GPT
- Update the internal schemas to support both GPT4 models and OpenAI
- Add unit tests benchmarking some of the Falcon performance
* Add exc_info to include stack trace in error logs for text processors
* Pull shared functions into utils.py to be used across gpt4 and gpt
* Add migration for new processor conversation schema
* Skip GPT4All actor tests due to typing issues
* Fix Obsidian processor configuration in auto-configure flow
* Rename enable_local_llm to enable_offline_chat
* Add a Github workflow that allows you to build dev versions of Desktop applications
* Add pull_request trigger for testing
* Fix errant open quote in Package Khoj App step
* Nix the release step, since this isn't associated with any tags
- Set retention period for uploaded artifacts to 1 day
* Remove pull_request trigger - limit to manual triggers and pushes to master
- Previously Khoj could only support Python upto 3.10 due to pytorch.
But lots of folks had python 3.11 installed by default on their machines.
This required installing python 3.10 and dealing with virtual envs.
With Torch >= 2.0.1 now able to support python 3.11, at least one
class of installation troubles for Khoj should drop. See
https://github.com/pytorch/pytorch/issues/86566 for reference
- Preliminary testing indicates using the new torch 2.x may reduce
search time by 25% (from 80ms to 60ms on Mac M1)
- Update Docs to not require mentioning python <=3.10 required
- Update Github test workflow to run khoj tests with python 3.11 too
