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Batch process all your records to store structured outputs in a Weaviate database.

The requirements are as follows.

Weaviate requires the collection to have a data schema before you add data. At minimum, this schema must contain the record_id property, as follows:

{
    "class": "Elements",
    "properties": [
        {
            "name": "record_id",
            "dataType": ["text"]
        }
    ]
}

Weaviate generates any additional properties based on the incoming data.

If you have specific schema requirements, you can define the schema manually. Unstructured cannot provide a schema that is guaranteed to work for everyone in all circumstances. This is because these schemas will vary based on your source files’ types; how you want Unstructured to partition, chunk, and generate embeddings; any custom post-processing code that you run; and other factors.

You can adapt the following collection schema example for your own specific schema requirements:

{
    "class": "Elements",
    "properties": [
        {
            "name": "record_id",
            "dataType": ["text"]
        },
        {
            "name": "element_id",
            "dataType": ["text"]
        },
        {
            "name": "text",
            "dataType": ["text"]
        },
        {
            "name": "embeddings",
            "dataType": ["number[]"]
        },
        {
            "name": "metadata",
            "dataType": ["object"],
            "nestedProperties": [
                {
                    "name": "parent_id",
                    "dataType": ["text"]
                },
                {
                    "name": "page_number",
                    "dataType": ["text"]
                },
                {
                    "name": "is_continuation",
                    "dataType": ["boolean"]
                },
                {
                    "name": "orig_elements",
                    "dataType": ["text"]
                }
            ]
        }
    ]
}

See also :

The Weaviate connector dependencies:

CLI, Python
pip install "unstructured-ingest[weaviate]"

You might also need to install additional dependencies, depending on your needs. Learn more.

The following environment variables:

  • For Weaviate installed locally, WEAVIATE_COLLECTION - The name of the target collection in the instance, represented by --collection (CLI) or collection (Python).

  • For Embedded Weaviate:

    • WEAVIATE_HOST - The connection URL to the instance, represented by --hostname (CLI) or hostname (Python).
    • WEAVIATE_COLLECTION - The name of the target collection in the instance, represented by --collection (CLI) or collection (Python).
  • For Weaviate Cloud:

    • WEAVIATE_CLUSTER_URL - THE REST endpoint for the Weaviate database cluster, represented by --cluster-url (CLI) or cluster_url (Python).

    • WEAVIATE_API_KEY - The API key for the database cluster, represented by --api-key (CLI) or api_key (Python).

      For the CLI, the --api-key option here is part of the weaviate-cloud command. For Python, the api_key parameter here is part of the CloudWeaviateAccessConfig object.
    • WEAVIATE_COLLECTION - The name of the target collection in the database, represented by --collection (CLI) or collection (Python).

These environment variables:

  • UNSTRUCTURED_API_KEY - Your Unstructured API key value.
  • UNSTRUCTURED_API_URL - Your Unstructured API URL.

Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The source connector can be any of the ones supported. This example uses the local source connector: