03. Spring AI : How to perform Vector Search using Vector Store ?

Generative AI for Java developers : In this video, we will cover how to perform vector search and query documents using simple vector store and Spring AI.

Chapters :
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0:00 Introduction to Vector Search and Available options
1:05 Basic idea about how vector search works
2:52 How to add Spring AI dependencies
3:40 Overview of Spring AI code for Vector Search
7.30 Code output using endpoint
8.14 How to generate output in the embedding format
91.7 Enhancing Vector Search with SerachRequest

How to get started with Spring AI ?
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Please refer more videos related to Spring AI here :
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Please refer the code here :
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Playlist on Azure using Python SDK :
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Interested in Generative AI, Check this Udemy course on Query your custom documents using LlamaIndex :
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Looking for interview guide on Kafka ?
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If you are planning for interview on real time process and looking for tech questions on Kafka and Spring Kafka, look no further and grab your copy of "75 Interview Questions on Kafka and Spring Kafka".

[TechyTacos]

There had been certain updates in the recent version of Spring AI. Please use below while defining the VectorStoreConfig :
@Bean
VectorStore vectorStore(EmbeddingModel embeddingModel){
return new
}

[PrayasPikalmunde]

I was using api key for the first time but i keep on getting 429 error.

[abhijitraval]

I wonder about the use case of this vector search, Is it useful to have your own custom set of data and then generate response out of it.

For example Suppose I’ve 100 travel blogs in my website, and I can store each travel blog as a document in vector store, and then I can create an api endpoint which will return all the documents(blogs) from the vector store where my query(request param) matches??