Clarifai

Batch process all your records using unstructured-ingest to store unstructured outputs locally on your filesystem and upload those to Clarifai apps.

First start with the installation of clarifai dependencies as shown here.

pip install "unstructured[clarifai]"

Create a clarifai app with base workflow. Find more information in the create clarifai app.

Run Locally

The upstream connector can be any of the ones supported, but for the convenience here, showing a sample command using the upstream local connector.

from unstructured.ingest.connector.clarifai import (
    ClarifaiAccessConfig,
    ClarifaiWriteConfig,
    SimpleClarifaiConfig,
)
from unstructured.ingest.connector.local import SimpleLocalConfig
from unstructured.ingest.interfaces import (
    ChunkingConfig,
    PartitionConfig,
    ProcessorConfig,
    ReadConfig,
)
from unstructured.ingest.runner import LocalRunner
from unstructured.ingest.runner.writers.base_writer import Writer
from unstructured.ingest.runner.writers.clarifai import (
    ClarifaiWriter,
)


def get_writer() -> Writer:
    return ClarifaiWriter(
        connector_config=SimpleClarifaiConfig(
            access_config=ClarifaiAccessConfig(api_key="CLARIFAI_PAT"),
            app_id="CLARIFAI_APP",
            user_id="CLARIFAI_USER_ID",
        ),
        write_config=ClarifaiWriteConfig(),
    )


if __name__ == "__main__":
    writer = get_writer()
    runner = LocalRunner(
        processor_config=ProcessorConfig(
            verbose=True,
            output_dir="local-output-to-clarifai-app",
            num_processes=2,
        ),
        connector_config=SimpleLocalConfig(
            input_path="example-docs/book-war-and-peace-1225p.txt",
        ),
        read_config=ReadConfig(),
        partition_config=PartitionConfig(),
        chunking_config=ChunkingConfig(chunk_elements=True),
        writer=writer,
        writer_kwargs={},
    )
    runner.run()

For a full list of the options the CLI accepts check unstructured-ingest <upstream connector> clarifai --help.

NOTE: Keep in mind that you will need to have all the appropriate extras and dependencies for the file types of the documents contained in your data storage platform if you’re running this locally. You can find more information about this in the installation guide.