Query foundational generative AI models from notebooks in Oracle AI Data Platform Workbench to score sentiment and summarize supplier reviews. Explore more Oracle AI Data Platform Workbench resources at the links below.
In this demo, you learn how to query foundational generative AI models directly from a notebook in Oracle AI Data Platform Workbench using Oracle Cloud Infrastructure Generative AI service models. The walkthrough shows how to open a workspace notebook with the master catalog, browse the available foundational models, and confirm key requirements, including having use permission on the base model and running your workbench in the same region as the selected generative AI model.
Next, you see how to select a model and drag it into a notebook cell to populate the correct reference syntax. You then construct a query against a dataframe of supplier reviews, define an output column for results, and write a prompt to score sentiment on a one to 10 scale. The demo also shows how to classify reviews as negative, neutral, or positive, and how to generate a one-sentence summary for longer reviews using the same query pattern.
Finally, you learn how to switch to a different model, rerun the notebook, and validate that the results still meet your analysis goals. This approach helps your team analyze feedback at scale, automate sentiment scoring, and generate text summaries without leaving Oracle AI Data Platform Workbench.
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