Oracle Cloud Infrastructure 2026 Generative AI Professional
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Oracle Cloud Infrastructure 2026 Generative AI Professional

1Z0-1127-26

Master generative AI implementation on Oracle Cloud Infrastructure, focusing on Large Language Models, RAG architectures, and building advanced AI-driven applications.

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Sample Oracle Cloud Infrastructure 2026 Generative AI Professional exam question

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MasterImplement RAG using OCI Generative AI Service

Evaluate the ingestion snippet used on OCI to build a RAG index. It indexes a whole policy manual as one embedding, and downstream prompts receive only coarse context. Which missing operation explains the poor granularity of model answers?

python
from langchain_community.embeddings import OCIGenAIEmbeddings
from langchain_community.vectorstores import OpenSearchVectorSearch
from langchain_core.documents import Document

embedding_model = OCIGenAIEmbeddings(
    model_id='cohere.embed-english-v3.0',
    service_endpoint='https://inference.generativeai.uk-london-1.oci.oraclecloud.com',
    compartment_id='ocid1.compartment.oc1..example'
)

pdf_full_text = 'Long policy manual text...'

doc = Document(page_content=pdf_full_text, metadata={'source': 'policy-v1.pdf'})
vector_store = OpenSearchVectorSearch.from_documents(
    documents=[doc],
    embedding=embedding_model,
    opensearch_url='https://search-example.oci.oraclecloud.com',
    index_name='policy_kb'
)

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