Run Pipeline

This runs a specific pipeline.

POST

/v1/pipeline/{PIPELINE_ID}/run

Base URL

The base URL for this API is in the following format:

https://controller.api.${CLOUD_REGION}.zillizcloud.com

📘Notes

You need to replace ${CLOUD_REGION} with the appropriate region for your deployment.
To get the cloud region ID, refer to On Zilliz Cloud Console or List Cloud Regions.

export CLOUD_REGION="gcp-us-west1"
export BASE_URL="https://controller.api.${CLOUD_REGION}.zillizcloud.com"

Parameters

Authorizationstringheaderrequired

The authentication token should be an API key with appropriate privileges.

Example Value: Bearer {{TOKEN}}

PIPELINE_IDstringpathrequired

A valid pipeline ID obtained from either the list-pipelines API endpoints or Zilliz Cloud console.

Example Value: pipe-xxxxxxxxxxxxxxxxx

Request Bodyapplication/json

INGESTION

Data ingestion parameters.

dataoneOfrequired

(To be added soon)

OPTION 1

doc_urlstringrequired

The URL of the document stored on an object storage. You should use a URL that is either not encoded or encoded in UTF-8. Ensure that the URL remains valid for at least one hour.

\{YOUR_PRESERVED_FIELD}string

The metadata field to preserve. The input field name should be consistent with what you defined when creating the Ingestion pipeline and adding the PRESERVE function. The value of this field should also follow the predefined field type.

OPTION 2

text_liststringrequired

The text or text list to ingest.

sourcestring

OPTION 3

image_urlstringrequired

The URL of the image stored on an object storage. You should use a URL that is either not encoded or encoded in UTF-8. Ensure that the URL remains valid for at least one hour.

image_idstringrequired

The ID of the image stored on an object storage.

image_titlestringrequired

The title of the image.

dataobjectrequired

Search data.

query_textstring

A query text. Zilliz Cloud embeds it and use the generated vector embeddings to conduct a search in the target collection. This applies to pipelines of a SEARCHTEXT, a SEARCHDOCCHUNK, or a SEARCHIMAGEBYTEXT type.

query_image_urlstring

The URL of a query image. This applies to pipelines of a SEARCHIMAGEBY_IMAGE type.

paramsobjectrequired

Search parameters.

limitintegerrequired

Total number of records to return.

offsetintegerrequired

Total number of records to skip in the search results.

outputFieldsarrayrequired

A list of fields to output for each match in the search result.

[]outputFieldsstring

A valid output field and should be the one defined in the preserve functions.

filterstringrequired

A boolean expression for Zilliz Cloud to filter records before actual searches.

DELETION

dataobjectrequired

Payload of the deletion request.

expressionstringrequired

A filter expression. This applies to pipelines of the INDEX_TEXT type.

doc_namestringrequired

Name of the document to delete. Note that you can delete document by its name, and all the chunks of the document will be removed. This applies to pipelines of the INDEXDOCCHUNK type.

image_idstringrequired

ID of an image. This applies to pipelines of the INDEX_IMAGE type.

INGEST TEXT

export TOKEN="YOUR_API_KEY"
export PIPELINE_ID="pipe-xxxxxxxxxxxxxxxxx"

curl --request POST \
--url "${BASE_URL}/v1/pipeline/${PIPELINE_ID}/run" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "data": {
        "text_list": [
            "Zilliz Cloud is a fully managed vector database and data services, empowering you to unlock the full potential of unstructured data for your AI applications.",
            "It can store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models."
        ],
        "source": "Zilliz official website"
    }
}'

INGEST DOCUMENT

export TOKEN="YOUR_API_KEY"
export PIPELINE_ID="pipe-xxxxxxxxxxxxxxxxx"

curl --request POST \
--url "${BASE_URL}/v1/pipeline/${PIPELINE_ID}/run" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "data": {
        "doc_url": "https://storage.googleapis.com/example-bucket/zilliz_concept_doc.md?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=example%40example-project.iam.gserviceaccount.com%2F20181026%2Fus-central1%2Fstorage%2Fgoog4_request&X-Goog-Date=20181026T181309Z&X-Goog-Expires=900&X-Goog-SignedHeaders=host&X-Goog-Signature=247a2aa45f169edf4d187d54e7cc46e4731b1e6273242c4f4c39a1d2507a0e58706e25e3a85a7dbb891d62afa8496def8e260c1db863d9ace85ff0a184b894b117fe46d1225c82f2aa19efd52cf21d3e2022b3b868dcc1aca2741951ed5bf3bb25a34f5e9316a2841e8ff4c530b22ceaa1c5ce09c7cbb5732631510c20580e61723f5594de3aea497f195456a2ff2bdd0d13bad47289d8611b6f9cfeef0c46c91a455b94e90a66924f722292d21e24d31dcfb38ce0c0f353ffa5a9756fc2a9f2b40bc2113206a81e324fc4fd6823a29163fa845c8ae7eca1fcf6e5bb48b3200983c56c5ca81fffb151cca7402beddfc4a76b133447032ea7abedc098d2eb14a7",
        "publish_year": 2023
    }
}'

INGEST IMAGE

export TOKEN="YOUR_API_KEY"
export PIPELINE_ID="pipe-xxxxxxxxxxxxxxxxx"

curl --request POST \
--url "${BASE_URL}/v1/pipeline/${PIPELINE_ID}/run" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "data": {
        "image_id": "my-img-123456",
        "image_url": "xxx",
        "image_title": "A cute yellow cat"
    }
}'

Responses200 - application/json

INGEST TEXT

{
    "code": 200,
    "data": {
        "num_entities": 2,
        "usage": {
            "embedding": 63
        },
        "ids": [
            450524927755105900,
            450524927755105900
        ]
    }
}

INGEST DOCUMENT

{
    "code": 200,
    "data": {
        "doc_name": "zilliz_concept_doc.md",
        "usage": {
            "embedding": 1241
        },
        "num_chunks": 3
    }
}

INGEST IMAGE

{
    "code": 200,
    "data": {
        "num_entities": 1,
        "usage": {
            "embedding": 1
        }
    }
}