- Let the specific text_to_jsonl method decide which of the
TextContentConfig fields it needs to convert <text> type to jsonl
- This simplifies extending TextContentConfig for a specific type without
modifying all text_to_jsonl methods
- It keeps the number of args being passed to the `text_to_jsonl'
methods in check
- It's more of a hassle to not let word filter go stale on entry
updates
- Generating index on 120K lines of notes takes 1s. Loading from file
takes 0.2s. For less content load time difference will be even smaller
- Let go of startup time improvement for simplicity for now
- Comparing compiled entries is the appropriately narrow target to
identify entries that need to encode their embedding vectors. Given we
pass the compiled form of the entry to the model for encoding
- Hashing the whole entry along with it's raw form was resulting in a
bunch of entries being marked for updated as LINE: <entry_line_no>
is a string added to each entries raw format.
- This results in an update to a single entry resulting in all entries
below it in the file being marked for update (as all their line
numbers have changed)
- Log performance metrics for steps to convert org entries to jsonl
- Having Tags as sets was returning them in a different order
everytime
- This resulted in spuriously identifying existing entries as new
because their tags ordering changed
- Converting tags to list fixes the issue and identifies updated new
entries for incremental update correctly
- What
- Hash the entries and compare to find new/updated entries
- Reuse embeddings encoded for existing entries
- Only encode embeddings for updated or new entries
- Merge the existing and new entries and embeddings to get the updated
entries, embeddings
- Why
- Given most note text entries are expected to be unchanged
across time. Reusing their earlier encoded embeddings should
significantly speed up embeddings updates
- Previously we were regenerating embeddings for all entries,
even if they had existed in previous runs
- Parsed `level` argument passed to OrgNode during init is expected to
be a string, not an integer
- This was resulting in app failure only when parsing org files with
no headings, like in issue #83, as level is set to string of `*`s
the moment a heading is found in the current file
- Previously we were failing if no valid entries while computing
embeddings. This was obscuring the actual issue of no valid entries
found in the specified content files
- Throwing an exception early with clear message when no entries found
should make clarify the issue to be fixed
- See issue #83 for details
- Default config has `input_files' set to None
- This was being passed to `FileBrowser' on Initialization
- But `FileBrowser' expects `content_files' of list type, not None
- This resulted in an unexpected NoneType failure
- The logging to file code expects the config directory to already be setup
- But parent directory of config file was being set up later in code
- This resulted in app start failing with ~/.khoj dir does not exist error
- Pass file associated with entries in markdown, beancount to json converters
- Add File, Word, Date Filters to Ledger, Markdown Types
- Word, Date Filters were accidently removed from the above types yesterday
- File Filter is the only filter that newly got added
- Filter entries, embeddings by ids satisfying all filters in query
func, after each filter has returned entry ids satisfying their
individual acceptance criteria
- Previously each filter would return a filtered list of entries.
Each filter would be applied on entries filtered by previous filters.
This made the filtering order dependent
- Benefits
- Filters can be applied independent of their order of execution
- Precomputed indexes for each filter is not in danger of running
into index out of bound errors, as filters run on original entries
instead of on entries filtered by filters that have run before it
- Extract entries satisfying filter only once instead of doing
this for each filter
- Costs
- Each filter has to process all entries even if previous filters
may have already marked them as non-satisfactory
- This will help filter query to org content type using file filter
- Do not explicitly specify items being extracted from json of each
entry in text_search as all text search content types do not have
file being set in jsonl converters
- Specify just file name to get all notes associated with file at path
- E.g `query` with `file:"file1.org"` will return `entry1`
if `entry1` is in `file1.org` at `~/notes/file.org`
- Test
- Test converting simple file name filter to regex for path match
- Test file filter with space in file name
- Code Changes
- Use list comprehension and `torch.index_select' methods
- to speed selection of entries, embedding tensors satisfying filter
- avoid deep copy of entries, embeddings
- avoid updating existing lists (of entries, embeddings)
- Use word to entry map and set operations to mark entries satisfying
inclusion, exclusion filters
- Results
- Speed up explicit filtering by two orders of magnitude
- Improve consistency of speed up across inclusion and exclusion filtering
- Only the filter knows when entries, embeddings are to be manipulated.
So move the responsibility to deep copy before manipulating entries,
embeddings to the filters
- Create deep copy in filters. Avoids creating deep copy of entries,
embeddings when filter results are being loaded from cache etc
- Do not run the more expensive explicit filter until the word to be
filtered is completed by user. This requires an end sequence marker
to identify end of explicit word filter to trigger filtering
- Space isn't a good enough delimiter as the explicit filter could be
at the end of the query in which case no space
- Stop passing verbose flag around app methods
- Minor remap of verbosity levels to match python logging framework levels
- verbose = 0 maps to logging.WARN
- verbose = 1 maps to logging.INFO
- verbose >=2 maps to logging.DEBUG
- Minor clean-up of app: unused modules, conversation file opening
- This also pushes the updated URL state to history
- Allows jumping back to the web interface after clicking on an image
and having the type set to image search
- Previously type would get reset to the default search type on
jumping back
- CLIP doesn't need full size images for generating embeddings with
decent search results. The sentence transformers docs use images
scaled to 640px width
- Benefits
- Normalize image sizes
- Increase image embeddings generation speed
- Decrease memory usage while generating embeddings from images
- 5e6625a Fix file browser to not add empty line when no file/dir selected
- 8098b8c Bring main window to Top when open from System Tray
- 1c122a8 Place window near top so buttons are not hidden by OS bottom bar
- dfe2546 Set Khoj Icon on Main Desktop Window
- 1b1f8f9 Move Splash screen text below icon. Set the text color to black
- 450f644 Fix path to remove shared libraries when packaging the Windows app
- When no file selected in file browser an empty line/entry gets added
to input entries list
- Bug got introduced due to insufficient update on change to add
instead of insert
- Update is_none_or_empty helper method to also check for empty string
- It is a non-user configurable, app state that is set on app start
- Reduce passing unneeded arguments around. Just set device where
required by looking for ML compute device in global state
- Note: Support for MPS in Pytorch is currently in v1.13.0 nightly builds
- Users will have to wait for PyTorch MPS support to land in stable builds
- Until then the code can be tweaked and tested to make use of the GPU
acceleration on newer Macs
- Pass device to load models onto from app state.
- SentenceTransformer models accept device to load models onto during initialization
- Pass device to load corpus embeddings onto from app state
- CLIP Image score and XMP metadata score are not combining well.
When combined they give non sensical results. Enable only once
figure how best to combine the two.
- Show scores with higher precision for image search
- Image search scores seem to be mostly be between 0.2 - 0.3 for some reason
- Higher precision scores make it easier to understand the quality
of returned results perceived by the model itself
- Allows adding multiple image directories via GUI
- Allow adding multiple files in different directories via GUI
- Previously users couldn't add multiple directories via GUI
They'd have to manually append to input field if multiple files, directories
- To clear/overwrite is much easier.
The user can just select text to delete in input area
- Issue
Fix configuring image search from Desktop GUI. It was broken before.
The Desktop GUI was updating input-files field under content-type > image.
This field is not used for image search. So image search couldn't be
configured from the Desktop GUI
- Fix
- Set input-directories when field of search type image is set from GUI
- Otherwise set input-files field in config
- Show a helpful error message in the GUI to the user, instead of the
crashing if loading config fails, for e.g if file wasn't found
- Collate GUI errors into an ErrorType enum class
- Remove previous error messages before showing the new one
Previously if the embeddings were already there only the khoj.yml
config file would get updated. The embeddings would remain old.
1. This results in a stale app state where the config doesn't
match the embeddings
2. Currently the user cannot update their config from the config
screen. They'd have to use a combination of config screen and web
interface>regenerate button to trigger it or delete their ~/.khoj dir
This commit should resolve the above issues
- Prevent immediate overwrite of re-ranked results by
incremental-search without rerank triggered via post-command-hook.
- This triggers right after the reranking results are rendered, so
user never ends up seeing them
- Add docstrings, mention args in them. Make docstring crisper
- prefix funcs, variables with khoj--
- Require emacs >27.1 for json-parse-buffer
- Use lexical binding
- Add quickstart docs to elisp file itself
- Bump version of khoj.el
- What
- Convert the config screen into the main application window
with configuration as just one of the functionality it provides
- Rename config screen to main window to match new designation
- Why
- System Tray isn't available everywhere (e.g Linux)
- This requires moving functionality into a normal window for cross-compat
- What
- On Linux
- Show Configure Screen, even if not first run experience
- Do no show system tray on Linux
- Quit app on closing Configure Screen
- On Windows, Mac
- Show Configure screen only if first run experience
- Show system tray always
- Do not quit app on closing Configure Screen
- Why
- Configure screen is the only GUI element on Linux. So closing it
should close the application
- On Windows, Mac the system tray exists, so app should not be closed
on closing configure screen
- Start evolving configure screen away from just being a configure screen
- Update Window Title to just say Khoj
- Allow Opening Web Interface to Search from Khoj configure screen
- Rename "Start" Button to more accurate "Configure"
- Disable Search button on first run and while configuring app
- Issue
- In the previous form, updates to self.current_config would update
default_config as python does a shallow copy
- So self.current_config is just referencing the values of default_config
- Hence updates to current_config updates the default_config values too
- This is not what we want
- Fix
- Deep copy the default_config values. Now updates to
self.current_config wouldn't affect the default_config
- Generating embeddings takes time
- If user enables a content type and clicks start.
The app starts to generate embeddings when loading the new settings
- Run this function in a separate thread to keep config screen responsive
- But disable start button to prevent re-entrant threads
- Also show a minimal visual indication that the app is saving state
- Convert Input Fields into PlainTextEdit
- Display Each Selected File on a Separate Line in Field
- Set Height of FileBrowser Input Field based on Number of Lines/Files
- This fixes the field expanding when configure screen is expanded
- Allows for reusability of the labelled text field
- Simplifies the logic to save settings for conversation processor
- Avoid having to pass the khoj_sample.yml data file into pip, native apps
- Packaging data files into python packages is annoying.
- There's `MANIFEST.in`, `data_files` and `package_data` in setup.py
- Bdist, wheel, generated source tarball use different set of these fields
and put the data files in different locations
- Rather just code the default config into a constant. Avoid
pointless file reads as well this way
- Assume path is absolute in yaml util module while saving, loading file
- This follows same convention as jsonl. Which just operates on
passed file path, assuming it is of appropriate form.
Responsibility to put it in appropriate form is on the caller, for now
- Include khoj_sample.yml in pip package to load default config from
- Create khoj config directory if it doesn't exist
- Load config from khoj_sample.yml if khoj.yml config doesn't exist
Conflicts:
- src/main.py
- router functions have moved to router
- move logic to handle null query perf timer variables into
router.py
- set main.py to current branch, not master
- If a user manually edits the input file lines, clicking start should
use that. Currently it just looks at the files selected last via file
browser
- We want to allow users to manually enter file paths in field. Which
is why the field hasn't been set to read-only
- Track current (saved/loaded) config separate from the new config (to
be written) when user clicks Start
- Fallback to using default config when no config for the specific
content type or processor is specified in khoj.yml
- Earlier were only loading default config on first run, not after
- Create Child CheckBox, LineEdit classes for Processor Widgets
- Create ProcessorType, similar to SearchType
- Track ProcessorType the widgets are associated with
- Simplify update, save, load of config based on type
- Update configuration to use by the backend, while app is running
- Trigger after user hits start button with their config.
The config gets written to khoj.yml file first, then the updated
config is loaded onto memory
- Decouple configuring backend from starting server.
Backend search and processors can be configured after the backend
server has started
- Set global state in main instead of in configure_server method.
This allows the app to start even if configure_server exits early in
the first run scenario, where no config available to configure server
- Now start server, even if no config, before GUI started in main
- This refactor of app startup flow will allow users to configure
backend using the configure screen after server start
- Only pass processor config arg required by configure_processor. Not
the unused full config object
- Type arguments passed to methods configure processors
- Import json for use by conversation processor to load logs
- Results get priority screen real estate
- Allows quick speed key based traversal of results as cursor
on switching to buffer is at top level heading
- E.g C-x o n n o 2 jumps to entry in actual file of second result
- Unlike before when it is at the #+STARTUP org buffer customization
settings
- Only allow adding files with appropriate file extension for each search type
- e.g .org for org-mode search, directory for image search
- Extract file paths added to config and enablement state of each search type
- This extracted state will be used to populate the khoj.yml config file
- Simplifies the configure screen layout and allows it to be of constant width
- It was buggy, the configure screen would dynamically expand but not
restore back to original size on disabling search type after enable
- Follow convention, two hyphens indicate variable private to library
- Defcustom are user configurable variables. So they should have single -
- Use khoj-results-count variable directly in code
- Make config_file an optional arg. It defaults to default khoj config dir
- Return args.config as None if no config_file explicitly passed by user
- Parent can use args.config = None as signal to trigger first run experience
