> For the complete documentation index, see [llms.txt](https://docs.envector.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.envector.io/1.4.x/sdk-user-guide/insert/inserting-with-metadata.md).

# Inserting with Metadata

You can insert vectors together with metadata.\
Metadata should be provided as a list of strings. If `metadata_encryption=True` is enabled in the index configuration, the metadata will be encrypted before being stored.

> **Note**: When `metadata_encryption=True`, metadata is also protected with **end-to-end encryption**.\
> This means encryption happens on the client side and only clients with the secret key can decrypt it, ensuring that sensitive metadata is never exposed to the server.

Example

<pre class="language-python"><code class="lang-python">import numpy as np
import pyenvector as ev

ev.init(address="localhost:50050", key_path="keys", key_id="example")

index = ev.create_index("example_index", dim=512)

vecs = np.random.rand(100, 512)
# Normalize vectors for inner product metric
vecs = vecs / np.linalg.norm(vecs, axis=1, keepdims=True)

metadatas = [f"metadata_{i}" for i in range(100)]

index.insert(vecs, metadata=metadatas)
# Output: 
# Index(
#    IndexConfig(
<strong>#        index_name="example_index",
</strong>#        dim=512,
#        key_path='keys',
#        key_id='example',
#    ),
#  num_entities=100,
#  cipher=&#x3C;pyenvector.crypto.cipher.Cipher object at 0x7f1776199d60>
#)
</code></pre>


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