Faiss on Ubuntu22.04 (x86-64) with support by Hfimg

AWS-Marketplace

https://aws.amazon.com/marketplace/pp/prodview-ja3sjfwjjqw7w

Usage Instructions

1.Activate the conda environment

conda activate faiss_env

2.Testing Faiss

cd Faiss_test

2.1.Querying version number

2.2.Basic vector indexing operations

2.3.Efficient vector similarity search on GPU

*Note

Testing this example requires a GPU instance type, which is recommended to be changed to g4dn.xlarge or higher performance GPU instance type.

3.JupyterLab

1.JupyterLab is a web-based integrated development environment (IDE)
that supports multiple programming languages (such as Python, R, Julia, etc.)
and provides an interactive working environment where users can write code,
run programs, view results, and make data visualizations.

2.Collaboration between JupyterLab and Faiss

In data science and machine learning projects, JupyterLab serves as
the primary development environment, while Faiss is utilized for
efficient similarity search on large-scale datasets.
Below are some common scenarios where they collaborate:

<1>Data Preprocessing: In JupyterLab, code is written in Python (or other supported programming languages)
to load, clean, and transform data, preparing the dataset for model training or similarity search.

<2>Index Construction: Faiss is used to construct indexes on the preprocessed dataset.
This is accomplished by calling Faiss's API within JupyterLab,
converting the dataset into a format suitable for efficient searching.

<3>Similarity Search: Code is written in JupyterLab to perform similarity searches.

This involves utilizing the search methods provided by Faiss
to find the vectors most similar to a given query vector,

with the results viewed and analyzed in JupyterLab's interactive environment.

<4>Results Analysis and Visualization: Libraries such as Matplotlib and Plotly are utilized within

JupyterLab to create data visualizations, providing a more
intuitive understanding of search results and model performance.

Visit https://:8888/lab to view the application.

The following JupyterLab logo is displayed:

In the JupyterLab dialog, enter the server instance ID

instance ID = i-02142129e02022167

- `conda deactivate`
- `conda info --envs` or `conda env list`