/query Command

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Examples

The /query command assists in generating queries from a natural language against a connected MongoDB cluster. The MongoDB Extension for Github Copilot provides underlying schema information of the relevant collections to GitHub Copilot to generate a response. If you do not specify a collection in your prompt, the chat prompts you to select a relevant collection.

When the LLM generates a query, you can open the query in a playground file or run the query directly in your collection.

Examples

Generate a Query

Consider the users collection in the Mflix Sample Database. Each document in the collection has the following structure:

{
   _id: {
      "$oid": "59b99db4cfa9a34dcd7885b6"
   },
   name: "Kayden Washington",
   email: "KW@email.com",
   password: "11222021"
}

Once you connect to the deployment that contains the users collection, you can ask the GitHub Copilot chat to generate a query that finds the document in the users collection that has the name value of Kayden Washington.

@MongoDB /query In the sample_mflix database, find a document in the
users collection with the name of Kayden Washington.

The GitHub Copilot Chat uses the MongoDB Extension for Github Copilot to generate the following query using knowledge of your database schema:

use(`sample_mflix`);
db.getCollection('users').findOne({ name: 'Kayden Washington' });

Once the MongoDB Extension for Github Copilot generates the query, you can choose to run the query directly or open the query in a playground.

Screenshot of copilot generating a query

click to enlarge

Build an Aggregation Pipeline

You can also use the MongoDB Extension for Github Copilot to build aggregation pipelines. Consider the users collection in the Mflix Sample Database. Each document in the collection has the following structure:

{
   _id: {
      "$oid": "59b99db4cfa9a34dcd7885b6"
   },
   name: "Kayden Washington",
   email: "KW@email.com",
   password: "11222021"
}

Once you connect to the deployment that contains the users collection, you can ask the GitHub Copilot chat to generate an aggregation pipeline.

@MongoDB /query Generate an aggregation pipeline on the users
collection that first sorts documents alphabetically by name and then
removes the password field from each document.

The MongoDB Extension for Github Copilot generates the following aggregation pipeline:

use('sample_mflix');
db.getCollection('users').aggregate([
   { $sort: { name: 1 } },
   { $project: { password: 0 } }
]);

Once the MongoDB Extension for Github Copilot generates the query, you can choose to run the pipeline directly or open the pipeline in a playground.

Screenshot of copilot generating an aggregation pipeline

click to enlarge

You can also iteratively build on your aggregation pipeline:

@MongoDB /query Add a stage to my pipeline that adds a username field
to each document containing the user's email without the
email domain.

The MongoDB Extension for Github Copilot returns the following aggregation pipeline:

use('sample_mflix');
db.getCollection('users').aggregate([
   { $sort: { name: 1 } },
   { $project: { password: 0 } },
   { $addFields: { username: { $arrayElemAt: [{ $split: ["$email", "@"] }, 0] } } }
]);

Screenshot of copilot iteratively building on an aggregation pipeline

click to enlarge

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