We now import check-ins and tagged places, so, mainly location-related data.
Some of the concepts still need a good mapping to the project, e.g. whether to put the coordinates as the item (i.e. "I was here") or with the entity (i.e. "this place is here").
The code that imported post attachments is some of the oldest code in the base, about 10 years ago. Back then, an item could have both text and file contents, and we just combined all the various attachment data for an attachment into one related item. Now, we properly treat them as separate.
Still need to add posts in groups and FB stories.
This will be a long-time WIP, but we now support full timestamps with local time offsets, absolute ones with UTC times only, and wall times only.
Several other fixes/enhancements. Making an effort to display time zone in time displays throughout the app.
Can now try to infer time zones during import, which is the default setting.
This will take a while to fully implement but it's a good start. Just have to be really careful about date crafting/manipulation/parsing.
I don't love that the type has to be stored in the table... it would be great if we could infer it, but I don't know how that would work for strings that look like another type.
Fixed several bugs introduced by the pipeline refactoring.
Updated goexif2 fork to use my latest commit which fixes not being able to find EXIF data on some JPEG images.
Embeddings now refer to the item they are for, rather than an item referring to a single embedding. This allows items to have multiple embeddings if necessary, which gives us some flexibility when models change/improve, etc.
Also reworked the Python server to use a smaller model (base siglip2 instead of so400m) so that it will fit on more GPUs, including my 4070; as well as a new "DeviceManager" that ChatGPT helped me figure out, to choose GPU when it has enough memory for it, as conditions change.
* Major processor refactor
- New processing pipeline, vastly simplified
- Several edge case bug fixes related to Google Photos (but applies generally too)
- Major import speed improvements
- UI bug fixes
- Update dependencies
The previous 3-phase pipeline would first check for an existing row in the DB, then decide what to do (insert, update, skip, etc.), then would download data file, then would update the row and apply lots of logic to see if the row was a duplicate, etc. Very messy, actually. The reason was to avoid downloading files that may not need to be downloaded.
In practice, the data almost always needs to be downloaded, and I had to keep hacking on the pipeline to handle edge cases related to concurrency and not having the data in many cases while making decisions regarding the item/row. I was able to get all the tests to pass until the final boss, an edge case bug in Google Photos -- but a very important one that happened to be exposed by my wedding album, of all things -- exhibited, I was unable to fix the problem without a rewrite of the processor.
The problem was that Google Photos splits the data and metadata into separate files, and sometimes separate archives. The filename is in the metadata, and worse yet, there are duplicates if the media appears in different albums/folders, where the only way to know they're a duplicate is by filename+content. Retrieval keys just weren't enough to solve this, and I narrowed it down to a design flaw in the processor. That flaw was downloading the data files in phase 2, after making the decisions about how to handle the item in phase 1, then having to re-apply decision logic in phase 3.
The new processing pipeline downloads the data up front in phase 1 (and there's a phase 0 that splits out some validation/sanitization logic, but is of no major consequence). This can run concurrently for the whole batch. Then in phase 2, we obtain an exclusive write lock on the DB and, now that we have ALL the item information available, we can check for existing row, make decisions on what to do, even rename/move the data file if needed, all in one phase, rather than split across 2 separate phases.
This simpler pipeline still has lots of nuance, but in my testing, imports run much faster! And the code is easy to reason about.
On my system (which is quite fast), I was able to import most kinds of data at a rate of over 2,000 items per second. And for media like Google Photos, it's a 10x increase from before thanks to the concurrency in phase 1: up from about 3-5/second to around 30-50/second, depending on file size.
An import of about 200,000 text messages, including media attachments, finished in about 2 minutes.
My Google Photos library, which used to take almost a whole day, now takes only a couple hours to import. And that's over USB.
Also fixed several other minor bugs/edge cases.
This is a WIP. Some more cleanup and fixes are coming. For example, my solution to fix the Google Photos import bug is currently hard-coded (it happens to work for everything else so far, but is not a good general solution). So I need to implement a general fix for that before this is ready to merge.
* Round out a few corners; fix some bugs
* Appease linter
* Try to fix linter again
* See if this works
* Try again
* See what actually fixed it
* See if allow list is necessary for replace in go.mod
* Ok fine just move it into place
* Refine retrieval keys a bit
* One more test
This is useful if a My Timeline subfolder is (sort-of) implicitly created for the user, and the user doesn't realize that is where their timeline is. They should be able to select the same folder to open the timeline as they did to create it.
* Revise location processing and place entities
- New, more dynamic, recursive clustering algorithm
- Place entities are globally unique by name
- Higher spatial tolerance for coordinate attributes if entity name is the same (i.e. don't insert new attribute row for coordinate if it's sort of close to another row for that attribute -- but if name is different, then points have to be closer to not insert new attribute row)
There is still a bug where clustering is too aggressive on some data. Looking into it...
* Fix overly aggressive clustering
(...lots of commits that fixed the CI environment which changed things without warning...)
* lint: bump golangci-lint version
- Bumps the version of golangci-lint that's used in the Github Action to be the most recent version (as installed with eg. `brew install golangci-lint` — v2.1.6)
- Migrates the `.golangci.toml` file, and manually moves the comments over
- `errchkjson` appears to work now, so added that back into the linter (the `forbidigo` and `goheader` linters I've left commented out)
* lint: remove checkers we don't like
Removes two static checkers that cause code changes we don't like.
* lint: remove old lint declaration
apparently `gosimple` isn't available any more, so I've removed its `nolint` declaration here.
* lint: swap location of `nolint:goconst`
This _seems_ to be an unstable declaration, because of he parallel & undeterministic nature of the linter. If this keeps causing trouble we can either remove the goconst linter, or change _both_ of these lines to hold `//nolint:goconst,nolintlint`.
Coordinates are arbitrary precision floats, so it is silly to compare, say, 35.320366666667 against 35.320367 and have them not be equal. I have yet to test this, but it should speed up importing duplicate location points since it will skip coordinates that are within about 1 meter of each other.
- Somehow I totally forgot to relate sidecar motion photos in Google Photos. (They don't use sidecars on Google phones.)
- Item page now displays entities in the picture even without face coordinates
- Quick unit tests for a function related to Google Takeout archives
- We now combine existing metadata with new according to the update policy, instead of either writing all or none of incoming metadata. This merging happens before the DB update query and is a bit of a special case as the policy is applied per-key.
- Special handling for corrupted timestamp in Google Photos data. This is a singular case I haven't observed more of, but seems like a reasonable heuristic. There might be thousands more out there, who knows.
- Fix job creation time (milliseconds)
- Hopefully make repeated imports faster by skipping duplicate items more intelligently based on update policies.
This is useful on the gallery page where we do NOT want to show motion pictures. We will also need to block motion pictures from being displayed as separate items on other UI views when they do show non-root items.
The sorting can help imports go faster if we put DB-heavy sources first, when the database is still small.
The data source names were also standardized to use snake_case like most other word-IDs in the app.
- Obfuscation mode enabled would set a fake phone number in smsbackuprestore's DS options, which led to bad data. Now, the UI does not auto-fill that value. But that means we need...
- SMS Backup & Restore: Phone number can now be inferred from repo owner in the backend, if ds opt phone number is empty. This works even with obfuscation enabled.
- Aborting a scheduled job before it starts now stays aborted. (Unless you manually restart it.)
- Added a data validation error modal for DS options on the import page. For now, if smsbackuprestore has no phone number set, and the timeline repo owner doesn't have a phone number, an error will be shown.
