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Enrich Bright Data Target with Datastreamer Cultural Reference Recognition Model
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Bright Data Target
Collect and extract product listings on Target's eCommerce site using keywords. Returns matching product listings that include the pricing, title, description, rating, images, specifications, reviews, and more.
About Datastreamer Cultural Reference Recognition Model
Movies, songs, memes, books, and other cultural references can be detected with this LLM-powered model 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.
Quickly enrich Bright Data Target with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Bright Data Target
Web data is the starting point for any pipeline. You can use any number of data sources to power your Pipelines. You can use web data from our partner network, your own systems, or any web data.
Step 2
Add Datastreamer Cultural Reference Recognition Model to enrich
Boost your web data capabilities by applying a wide range of operations—enrich, augment, join, structure, filter, store, search, and more. With Datastreamer, you get access to hundreds of plug-and-play tools to power your workflows.
Step 3
That's it! You have just connected Bright Data Target and Datastreamer Cultural Reference Recognition Model
Datastreamer makes working with web data simpler than ever. Easily enhance your Pipelines with new features and finally eliminate the operational roadblocks that once held you back.