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Collect from a subset of instances that Open Measures users have identified as dangerous or worth investigating. From there, Open Measures crawl these instances for posts and user profiles, while identifying the Fediverse site where the content was posted.
Detect emotion within content, such as fear, happiness, sadness, disgust, etc. It is able to process content in over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
How Datastreamer works
Quickly enrich Open Measures Fediverse with Datastreamer Emotion Detection Classifier with a Datstreamer Pipeline.
In modern enterprise architecture, web data fuels integration pipelines by bridging internal systems with external data sources such as partner networks and publicly accessible web content.
Take your web data further. From enrichment to filtering and everything in between, Datastreamer’s vast library of operations helps you act on your data fast—with no coding required.
Datastreamer takes the pain out of web data workflows. Seamlessly scale your Pipelines and resolve persistent operational challenges with ease.
Add Datastreamer components to your data stack and explore its full capabilities
