The nlpcloud-tagger plugin will add new tags to a file. It runs in an auto-managed cloud stack. Steamship handles API Keys, scaling, and asynchronous tasking.

To use it, first create a new file:

# Create a Steamship client # NOTE: When developing a package, just use `self.client` client = Steamship(workspace="my-unique-name") # Upload a file file = File.create(client, content="Contents of your file..")

Your file is now saved to Steamship as raw bytes. Let's convert it to Steamship's standardized Block format.

# Create an instance of a blockifier. For this example we'll assume Markdown. blockifier = client.use_plugin('markdown-blockifier-default') # Blockify the file blockify_task = file.blockify(blockifier.handle) # Wait for completion of the task. blockify_task.wait()

Now that we've blockified the file, we can tag it.

# Create an instance of this tagger tagger = client.use_plugin('nlpcloud-tagger') # Tag the file tag_task = file.tag(tagger.handle) # Wait for completion of the task. tag_task.wait()

Now that we've tagged the file, we can query it's contents.

Building Agents with nlpcloud-tagger

Agents built with the Steamship SDK can be deployed to production-ready APIs with a single command.

  • Horizontal scaling and multi-tenancy is built-in.
  • Metering and chaining across AI providers is handled automatically.
  • Data storage & query across text, vectors, and model output is supported.

The best way to get started is with our Agent Guidebook.