Import RAG files from Google Drive or Cloud Storage

This sample demonstrates how to import RAG files asynchronously from Google Drive or Cloud Storage.

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"
# corpus_name = "projects/{PROJECT_ID}/locations/us-central1/ragCorpora/{rag_corpus_id}"

# Supports Google Cloud Storage and Google Drive Links
# paths = ["https://drive.google.com/file/d/123", "gs://my_bucket/my_files_dir"]

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

response = await rag.import_files_async(
    corpus_name=corpus_name,
    paths=paths,
    chunk_size=512,  # Optional
    chunk_overlap=100,  # Optional
    max_embedding_requests_per_min=900,  # Optional
)

result = await response.result()
print(f"Imported {result.imported_rag_files_count} files.")
# Example response:
# Imported 2 files.

What's next

To search and filter code samples for other Google Cloud products, see the Google Cloud sample browser.