Generate responses using the RAG file

This sample demonstrates how to generate the content using a RAG file.

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

Code sample


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
from vertexai.preview.generative_models import GenerativeModel, Tool
import vertexai

# TODO(developer): Update and un-comment below lines
# project_id = "PROJECT_ID"
# rag_corpus_id = "9183965540115283968" # Only one corpus is supported at this time

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

rag_retrieval_tool = Tool.from_retrieval(
                    rag_corpus=rag_corpus_id,  # Currently only 1 corpus is allowed.
                    # Supply IDs from `rag.list_files()`.
                    # rag_file_ids=["rag-file-1", "rag-file-2", ...],
            similarity_top_k=3,  # Optional
            vector_distance_threshold=0.5,  # Optional

rag_model = GenerativeModel(
    model_name="gemini-1.0-pro-002", tools=[rag_retrieval_tool]
response = rag_model.generate_content("Why is the sky blue?")

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