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opened 2026-05-01 04:36:22 -05:00 by GiteaMirror
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📋 Pull Request Information
Original PR: https://github.com/actualbudget/actual/pull/7657
Author: @espoirMur
Created: 4/29/2026
Status: 🔄 Open
Base:
master← Head:apply-ml-categorization📝 Commits (9)
242d082updtate docker imagec5fa082Merge branch 'master' of https://github.com/actualbudget/actual495adacadd ml transaction rule5c82da8wip integrate ml model0ec33b7fix the prediction flowac14387kimi implementation of service workers55c113dfix the output thing0a375c4fix the modal the modal works now correctly.a819fd2apply the feedback from the ai📊 Changes
20 files changed (+1009 additions, -29 deletions)
View changed files
➕
ml-models/classifier.onnx(+0 -0)➕
ml-models/classifier_classes.npy(+0 -0)📝
package.json(+1 -0)📝
packages/desktop-client/package.json(+4 -1)📝
packages/desktop-client/src/components/Modals.tsx(+4 -0)➕
packages/desktop-client/src/components/modals/MLCategorizationModal.tsx(+274 -0)📝
packages/desktop-client/src/components/transactions/SelectedTransactionsButton.tsx(+20 -2)📝
packages/desktop-client/src/modals/modalsSlice.ts(+7 -0)➕
packages/desktop-client/src/workers/ml-categorization.client.ts(+101 -0)➕
packages/desktop-client/src/workers/ml-categorization.worker.ts(+261 -0)📝
packages/desktop-client/vite.config.mts(+15 -1)📝
packages/loot-core/src/platform/server/asyncStorage/index.ts(+58 -23)📝
packages/loot-core/src/platform/server/fs/index.ts(+4 -0)📝
packages/loot-core/src/server/accounts/sync.ts(+4 -0)📝
packages/sync-server/docker-compose.yml(+1 -1)📝
packages/sync-server/docker/alpine.Dockerfile(+1 -0)📝
packages/sync-server/docker/ubuntu.Dockerfile(+1 -0)📝
packages/sync-server/src/app.ts(+29 -1)➕
tsconfig.tsnode.json(+8 -0)📝
yarn.lock(+216 -0)📄 Description
Description
Yes!
So thank you for this amazing product, I was working with it for a couple of day and I notice for some of my transaction the rules are not being apply correctly.
I though It would be nicer to have a ML model that is trained on the notes to predict the category of the other upcoming notes.
My ideas was to have it categorize the transaction after the rules are applied, all the transaction that are left at that stage , you can select them and apply the ML Categorization to it.
So I vibe coded this stuff, I am not a front end engineer, I did javascript a long time ago.
Approach! (Overview of the Architecture)
I start with an ONNX pipeline that is trained for trasnsaction classification.
The ML Inference uses a web worker which is the same approach used by the database operations(I think.. 🤔).
The ML models and the class files are served via http(They are not big models, I didn't want to go with big model as small models can perform inference here). I don't need a big model that requires a GPU for this that is why I am using (WASM).
The inference is done both on the main thread and the server backend thread.
I am thinking we can load the model in the local storage and leave it there. But that for the future.
When you select all uncategorized transaction, it open a modal that show the predicted transaction by the model, the user can check the transaction and validate them. (But this seems to be like double work). I am thinking of showing the predicted categories on the same page as the uncategorized transaction and forget about the modal, please let me know what you guys think of this.
How to Test
yarn start:server-dev(serves model files on port 5006)yarn start(port 3001)Related issue(s)
Let me know what you think I will share more instruction on how to test later, and fix the remaining bugs.
Testing
Checklist
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.