Create an index

This sample demonstrates how to create an index to import or upload documents.

Explore further

For detailed documentation that includes this code sample, see the following:

• Method: projects.locations.ragCorpora.create
• RAG Engine API

Code sample

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Python API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from vertexai.preview import rag
import vertexai

# TODO(developer): Update and un-comment below lines
# PROJECT_ID = "your-project-id"
# display_name = "test_corpus"
# description = "Corpus Description"

# Initialize Vertex AI API once per session
vertexai.init(project=PROJECT_ID, location="us-central1")

# Configure embedding model
embedding_model_config = rag.EmbeddingModelConfig(
    publisher_model="publishers/google/models/text-embedding-004"
)

corpus = rag.create_corpus(
    display_name=display_name,
    description=description,
    embedding_model_config=embedding_model_config,
)
print(corpus)
# Example response:
# RagCorpus(name='projects/1234567890/locations/us-central1/ragCorpora/1234567890',
# display_name='test_corpus', description='Corpus Description', embedding_model_config=...
# ...

What's next

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