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#SQL

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SQL is a standard language for storing, manipulating and retrieving data in relational databases.

You need to install the application first. If not installed, please refer to the previous article

Application demonstration

After successfully running the iris image vector search application, some data needs to be stored to support image retrieval as it is not initialized in the library.

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DNA Similarity and Classification was developed as a REST API utilizing InterSystems Vector Search technology to investigate genetic similarities and efficiently classify DNA sequences. This is an application that utilizes artificial intelligence techniques, such as machine learning, enhanced by vector search capabilities, to classify genetic families and identify known similar DNAs from an unknown input DNA.

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Hi Community,

In this article, I will introduce my application iris-VectorLab along with step by step guide to performing vector operations.

IRIS-VectorLab is a web application that demonstrates the functionality of Vector Search with the help of embedded python. It leverages the functionality of the Python framework SentenceTransformers for state-of-the-art sentence embeddings.

Application Features

  • Text to Embeddings Translation.
  • VECTOR-typed Data Insertion.
  • View Vector Data
  • Perform Vector Search by using VECTOR_DOT_PRODUCT and VECTOR_COSINE functions.
  • Demonstrate the difference between normal and vector search
  • HuggingFace Text generation with the help of GPT2 LLM (Large Language Model) model and Hugging Face pipeline

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Hi Community,

In this article, I will introduce my application iris-image-vector-search.
The image vector retrieval demo uses IRIS Embedded Python and OpenAI CLIP model to convert images into 512 dimensional vector data. Through the new feature of Vector Search, VECTOR-COSINE is used to calculate similarity and display high similarity images.

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