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pgml-cms/docs/api/client-sdk/tutorials/semantic-search-1.md

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This tutorial demonstrates using the `pgml` SDK to create a collection, add documents, build a pipeline for vector search, make a sample query, and archive the collection when finished. In this tutorial we use [hkunlp/instructor-base](https://huggingface.co/hkunlp/instructor-base), a more advanced embeddings model that takes parameters when doing embedding and recall.
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[Link to full JavaScript implementation](../../../../../pgml-sdks/pgml/javascript/examples/question\_answering.js)
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[Link to full JavaScript implementation](https://github.com/postgresml/postgresml/blob/master/pgml-sdks/pgml/javascript/examples/question_answering.js)
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[Link to full Python implementation](../../../../../pgml-sdks/pgml/python/examples/question\_answering.py)
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[Link to full Python implementation](https://github.com/postgresml/postgresml/blob/master/pgml-sdks/pgml/python/examples/question_answering.py)
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## Imports and Setup
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The SDK is imported and environment variables are loaded.
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{% tabs %}
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{% tab title="JavasScript" %}
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{% tab title="JavaScript" %}
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```js
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const pgml = require("pgml");
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require("dotenv").config();

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