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Merge pull request #2963 from auslin-aot/changelog/fwf-5342-changelog-updates-v7.3.0
Changelog for v7.3.0 release
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CHANGELOG.md

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## 7.3.0 - Date To be updated
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`Modified`
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**forms-flow-web**
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* Form.io token fetching logic has been moved to the service micro-frontend.
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`Fixed`
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* Sorting is now available for all columns on the review task listing page.
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* Fixed minor issues in Reviewer & Analyze Submissions page.
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* Fixed PDF generation issue with a generic custom theme.
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*Upgrade notes:*
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**forms-flow-bpm**
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* Fixed security vulnerabilities
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## 7.2.0 - To be updated
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`Known Issues`
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* Select boxes are not displayed in the review filter search and analyze-submission side filter due to existing limitations.
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* If a new major version of a form is created after the Task filter is configured on the reviewer page, the filter will continue retrieving submissions from the previous form version. The new version will only be reflected once the form is reselected in the filter.
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* In single domain instances, Reviewer action may fail. As a quick fix refer [here](https://aottech.atlassian.net/browse/FWF-5201?focusedCommentId=32131).
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* A fix has been implemented allowing users with only the “Manage Advanced Flows” permission to publish subflows and DMNs.
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In a multitenant environment, this change may apply to existing tenants only after creating a new tenant or adding authorizations in the Camunda deployment. Refer [here](https://aottech.atlassian.net/browse/FWF-5304?focusedCommentId=32506)
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* When editing filters in the reviewer page, unchecking or checking one variable (e.g., name) causes another variable (task) to be unintentionally affected.
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* Deploying workflows(subflows) with a Message Start Event fails if another deployed workflow already uses the same message name. This results in a Camunda deployment error indicating a duplicate message event subscription.
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## 7.2.0 - 2025-08-14
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forms-flow-data-analysis-api/README.md

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![Python](https://img.shields.io/badge/Python-3.11.7-blue) ![Flask](https://img.shields.io/badge/Flask-3.1.1-blue) ![postgres](https://img.shields.io/badge/postgres-13.0-blue)
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![Transformers](https://img.shields.io/badge/Transformers-4.54.1-blue)
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![Torch](https://img.shields.io/badge/Torch-2.7.1-blue)
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![Torch](https://img.shields.io/badge/Torch-2.8.0-blue)
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Sentiment Analysisis used to understand the sentiments of the customer for products, movies, and other such things, whether they feel positive, negative, or neutral about it. BERT is a very good pre-trained language model which helps machines learn excellent representations of text with respect to context in many natural language tasks.
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forms-flow-data-analysis-api/model_training/README.md

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## How to train on your own dataset
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![Python](https://img.shields.io/badge/python-3.11.7-blue) ![Transformers](https://img.shields.io/badge/Transformers-4.25.1-blue) ![Torch](https://img.shields.io/badge/torch-1.13.1-blue)
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![Python](https://img.shields.io/badge/python-3.11.7-blue) ![Transformers](https://img.shields.io/badge/Transformers-4.54.1-blue) ![Torch](https://img.shields.io/badge/torch-2.8.0-blue)
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Transformers provides APIs to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you time from training a model from scratch. The models can be used across different modalities.
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It is built using Python :snake: .

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