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The configuration assumes you have already created deployments of the following names in the Azure OpenAI Studio
Deployment Name: gpt-35-turbo-16k with the model gpt-35-turbo-16k
Deployment Name: text-embedding-ada-002 with the model text-embedding-ada-002
NOTE: Spring configuration properties currently use the property-name model instead of deployment-name so don't get confused. Spring AI will be renaming the property in the future to avoid confusion. See here for more information.
For the chat, the configuration in application.properties should contain the following
The default value for the embedding model is text-embedding-ada-002, but if you wanted to change it you would set the configuration in application.properties as shown below.
The workshop consists of six examples, each with a dedicated README file.
All six workshop examples are organized into individual Java packages within this project. In each package, you'll find a Spring @RestController class that serves as the entry point for showcasing the discussed functionality.
To interact with the @RestController, you will be using the http utility as a user-friendly alternative to curl.
Detailed instructions and exercises for each example can be found in their respective README files:
1-README-tell-me-a-joke.md
2-README-prompt-templating.md
3-README-prompt-roles.md
4-README-output-parser.md
5-README-stuff-prompt.md
6-README-retrieval-augmented-generation.md
These guides will walk you through the workshop exercises.
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Workshop material for Spring AI and Azure OpenAI Service