How to Build a Scalable In-Document Retriever Using a Few Lines Of Code

Author(s): Julia

Originally published on Towards AI.

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In recent years, the alarming rate of species extinction has captured the attention of conservationists, scientists, and the general public alike. With over 1 million species currently facing the threat of extinction, it has never been more crucial to gather, analyze, and utilize information about endangered species. 🌍

In this article, we’ll explore how to build a retriever that can efficiently query a dataset containing vital information about endangered species using the Haystack framework. This retriever can help researchers and conservationists quickly find the information they need to take action.

We will use this dataset from Kaggle. The dataset contains a comprehensive list of endangered species, including the following key attributes:

Species Name: The scientific name of the species 🐾Common Name: The name commonly used to refer to the species 🦒Type: The category of the species (e.g., Plant, Mammal, Reptile) 🌿Location(s): The geographic areas where the species can be found 📍Estimated Population: An estimate of the species’ population size 📊Threats: The challenges and threats that endanger the species ⚠️

This dataset serves as a rich resource for understanding the current status and threats facing various species.

The primary goal… Read the full blog for free on Medium.

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Published via Towards AI