WEBVTT

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Having discussed several features
about Milvus in the

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earlier chapter,
let's exercise them

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in this chapter.

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We will create a collection,
create indexes,

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populate data, and query
the collection.

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In this video, we will start with
creating a client connection

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to Milvus.

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The notebook for this chapter is
in the file code_03_XX Milvus

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database operations.

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I have the notebook
loaded up here.

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We first need to install
prerequisite packages

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for these exercises.

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PyMilvus

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is the Python SDK for Milvus.

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OpenAI is the library we will use
for OpenAI for both embeddings

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and for LLMs.

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Let's install these
prerequisites now.

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We then move to the first step,
connecting to a Milvus

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database. To connect to Milvus,

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we first need to add a connection
to the list of connections.

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We specify a name for the
collection as learn.

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Then we need to specify
the host, port,

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username, and password
for the connection.

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We have not set up any username
or password yet,

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but this information is optional.

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We store the name of the
connection in a variable

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for future reference.

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Then calling the connect method
will create a connection

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to Milvus.

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Doing a list

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connections shows the list of
connections from this client.

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Let's run this code now.

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Having opened a connection,
we can now perform further

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operations using this connection.