# <a href="https://nnext.ai/"><img src="https://d3g1vr8yw3euzd.cloudfront.net/nnext-ultra-wide-tingle.png" alt="NNext Python Client"></a>
## About
The NNext Python Client.
NNext is a
* ⚡ blazingly fast
* 🔍 nearest-neighbors vector search engine
<a href="https://twitter.com/intent/follow?screen_name=nnextai"><img src="https://img.shields.io/badge/Follow-nnextai-blue.svg?style=flat&logo=twitter"></a>
[Installation](#installation) | [Quick Start](#quick-start) | [Documentation](#documentation)
## Installation
To install the pynnext client, activate a virtual environment, and install via pip:
### Supported Python Versions
```shell
Python >= 3.7, < 3.11
```
#### Mac/Linux
```shell
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install nnext
```
#### Windows
```shell
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install nnext
```
## Quick Start
In order start interacting with NNext, you need to obtain a client
here [https://console.nnext.ai/](https://console.nnext.ai/).
Here's a quick example showcasing how you can create an index, insert vectors/documents and search among them via NNext.
Let's begin by installing the Connecting to NNext.
```sql
SELECT images.uid,
images.name,
images.vector < - > 'VECTOR(0.19, 0.81, 0.75, 0.11)'::vector AS dist
FROM nnext-public-data.images.laion
ORDER BY
dist
LIMIT 100
```
```python
import nnext
nnclient = nnext.NNextClient(api_key="NNEXT_API_KEY")
# Perform a query.
QUERY = """
SELECT images.uid, images.name,
images.vector <-> 'VECTOR(0.19, 0.81, 0.75, 0.11)'::vector AS dist
FROM nnext-public-data.images.laion
ORDER BY
dist
LIMIT 100;
"""
query_job = nnclient.query(QUERY) # API request
rows = query_job.result() # Waits for query to finish
for row in rows:
print(row.name)
```
## Documentation
More documentation is available here here [https://nnext.ai/docs](https://nnext.ai/docs).:
<a href="https://nnext.ai/docs" target="_blank" rel="noopener noreferrer"><img src="https://d3g1vr8yw3euzd.cloudfront.net/3.png" height="100"></a>
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"description": "# <a href=\"https://nnext.ai/\"><img src=\"https://d3g1vr8yw3euzd.cloudfront.net/nnext-ultra-wide-tingle.png\" alt=\"NNext Python Client\"></a>\n\n## About\n\nThe NNext Python Client.\n\nNNext is a\n\n* \u26a1 blazingly fast\n* \ud83d\udd0d nearest-neighbors vector search engine\n\n<a href=\"https://twitter.com/intent/follow?screen_name=nnextai\"><img src=\"https://img.shields.io/badge/Follow-nnextai-blue.svg?style=flat&logo=twitter\"></a>\n\n[Installation](#installation) | [Quick Start](#quick-start) | [Documentation](#documentation)\n\n## Installation\n\nTo install the pynnext client, activate a virtual environment, and install via pip:\n\n### Supported Python Versions\n\n```shell\nPython >= 3.7, < 3.11\n```\n\n#### Mac/Linux\n\n```shell\npip install virtualenv\nvirtualenv <your-env>\nsource <your-env>/bin/activate\n<your-env>/bin/pip install nnext\n```\n\n#### Windows\n\n```shell\npip install virtualenv\nvirtualenv <your-env>\n<your-env>\\Scripts\\activate\n<your-env>\\Scripts\\pip.exe install nnext\n```\n\n## Quick Start\n\nIn order start interacting with NNext, you need to obtain a client\nhere [https://console.nnext.ai/](https://console.nnext.ai/).\n\nHere's a quick example showcasing how you can create an index, insert vectors/documents and search among them via NNext.\n\nLet's begin by installing the Connecting to NNext.\n\n```sql\nSELECT images.uid,\n images.name,\n images.vector < - > 'VECTOR(0.19, 0.81, 0.75, 0.11)'::vector AS dist\nFROM nnext-public-data.images.laion\nORDER BY\n dist\n LIMIT 100\n```\n\n```python\nimport nnext\n\nnnclient = nnext.NNextClient(api_key=\"NNEXT_API_KEY\")\n\n# Perform a query.\nQUERY = \"\"\"\n SELECT images.uid, images.name,\n images.vector <-> 'VECTOR(0.19, 0.81, 0.75, 0.11)'::vector AS dist\n FROM nnext-public-data.images.laion\n ORDER BY\n dist\n LIMIT 100;\n \"\"\"\nquery_job = nnclient.query(QUERY) # API request\nrows = query_job.result() # Waits for query to finish\n\nfor row in rows:\n print(row.name)\n```\n\n## Documentation\n\nMore documentation is available here here [https://nnext.ai/docs](https://nnext.ai/docs).:\n\n<a href=\"https://nnext.ai/docs\" target=\"_blank\" rel=\"noopener noreferrer\"><img src=\"https://d3g1vr8yw3euzd.cloudfront.net/3.png\" height=\"100\"></a>\n\n",
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