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Copyright (c) 2025 Oracle and/or its affiliates.
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The Universal Permissive License (UPL), Version 1.0
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Subject to the condition set forth below, permission is hereby granted to any
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person obtaining a copy of this software, associated documentation and/or data
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(collectively the "Software"), free of charge and under any and all copyright
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rights in the Software, and any and all patent rights owned or freely
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licensable by each licensor hereunder covering either (i) the unmodified
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Software as contributed to or provided by such licensor, or (ii) the Larger
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Works (as defined below), to deal in both
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(a) the Software, and
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(b) any piece of software and/or hardware listed in the lrgrwrks.txt file if
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one is included with the Software (each a "Larger Work" to which the Software
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is contributed by such licensors),
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without restriction, including without limitation the rights to copy, create
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derivative works of, display, perform, and distribute the Software and make,
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use, sell, offer for sale, import, export, have made, and have sold the
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Software and the Larger Work(s), and to sublicense the foregoing rights on
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either these or other terms.
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This license is subject to the following condition:
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The above copyright notice and either this complete permission notice or at
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a minimum a reference to the UPL must be included in all copies or
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substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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# RAG Wikipedia
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This package provides an end-to-end example of performing vector search and Retrieval-Augmented Generation (RAG) from an OCI Data Science Notebook Session using Wikipedia's Artificial Intelligence page.
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Reviewed: 2025.11.27
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# When to use this asset?
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Use this asset as support material when wanting to showcase Oracle AI Vector Search within Oracle AI Database 26ai. The asset includes explanations along with advanced RAG techniques, including:
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1. Comparing rule-based and semantic-based text splitters
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2. Connecting to the Oracle AI Database 26ai and creating vector-enabled tables
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3. Running hybrid search (keyword + vector similarity)
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4. Applying rerankers to improve retrieved context
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# Prerequisites
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To use this package, you need:
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- Basic Python knowledge
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- Access to an OCI Data Science Notebook Session
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- An Oracle AI Database 26ai or 23ai with Vector Search enabled
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- Required IAM permissions for Data Science and Database access
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- A configured database wallet or secure connection details
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# Environment
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Run the examples in a Jupyter Notebook inside an OCI Data Science Notebook Session.
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# License
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Copyright (c) 2025 Oracle and/or its affiliates.
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Licensed under the Universal Permissive License (UPL), Version 1.0.
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See [LICENSE](https://github.com/oracle-devrel/technology-engineering/blob/main/LICENSE) for more details.

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