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changes.mady.by.user Saurabh Jain

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changes.mady.by.user Nathan Gosse

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Squirro 3.7.0 was released .

Table of Contents

What’s New

  • You can now install and run docker on production instances.

  • The PDF-OCR step now includes optional Confidence scoring, which can be enabled at the cost of performance.

  • Added the option within the Data Loader to delete nargs entry (multi-value fields).

  • Added a new libNLP step to call spaCy running as a Squirro NLP service.

  • Created a Binary Documents pipeline for new projects.

  • Added a HFQuestionAnswering processor that can run Hugging Face question-answering pipelines for inference.

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  • Improved the performance of PDF document ingestion for pipeline workflows which include ML models.

  • [Search] Productize search service. For now exposes endpoints to help debugging the output of the squirro-query-syntax parsing pipeline.

  • Added information about sender and recipients to the attachments items in the Exchange data loader plugin.

  • Added bulk_labeling functions to handle this types of operation.

  • React widgets will now fetch data only if they are in a visible dashboard section layer.

  • Moves all steps calling external services.

  • Added endpoint for creating bulk labeling.

  • Upgraded React to v18

  • Clicking on a community typeahead suggestion will now redirect the user to the selected community.

  • Implemented an NLP step for bulk labeling.

  • Added handling config for the bulk labeling step.

  • The “PDF Cannot Be Displayed” error message is more generic and tries better to show a working file link.

  • Increased the clickable area for the subscribe button in the Communities List widget.

  • Added creation date for proximity rule.

  • Added a link to the Squirro Monitoring space to the Squirro Spaces popover with current project being selected in the dashboard filter.

  • Squirro now uses tika-pdf-sentences by default for speedier PDF Sentences Tokenization.

  • Search Query-Processing: Analyzed query tokens that might contain valid sub-tokens are now additionally re-written to perform exact phrase matching. NewYork => ("NewYork"~0 OR NewYork). This enables sub-word matching on New, and York individually relying on the configured SearchAnalyzer (subword-delimiter) - but will additionally match the exact phrase NewYork as well.

  • Implemented a ML endpoint for creating ml job which automatically creates labels.

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