I have made a composite index as per the firebase docs

 gcloud alpha firestore indexes composite create \
--project=[Insert Project Name Here]
--collection-group=elements --query-scope=COLLECTION \
--field-config=vector-config='{"dimension":"1536","flat": "{}"}',field-path=embedding

That works fine and I can see it clearly under gcloud firestore indexes composite describe [Insert Index Name Here]

Then I try to query the database using an onCall function.

export const vectorSearch = functions.https.onCall(async (data, context) => {
  const { query, quantity } = data;

  if (!query) {
    throw new functions.https.HttpsError('failed-precondition', 'query is required');
  }

  if (!quantity) {
    throw new functions.https.HttpsError('failed-precondition', 'quantity is required');
  }

  try {
    console.log(`Creating embedding for ${query}`)
    const embeddingResponse = await openai.embeddings.create({
      model: "text-embedding-3-small",
      input: query,
      encoding_format: "float",
    });

    const embedding = embeddingResponse.data[0].embedding;
    console.log(`Embedding:`, embedding)

    const vectorQuery: VectorQuery = firestore.collection('elements').findNearest('embedding', FieldValue.vector(embedding), {
      limit: quantity,
      distanceMeasure: 'COSINE'
    });

    const snapshot: VectorQuerySnapshot = await vectorQuery.get();
    console.log(`Snapshot:`, snapshot)

    const formattedData: any = {};
    snapshot.docs.forEach((doc) => {
      formattedData[doc.id] = doc.data();
    });

    return { docs: formattedData };
  } catch (error) {
    console.error('Error querying database:', error);
    throw new functions.https.HttpsError('internal', 'Error querying database');
  }
});

The Problem

When I call this function, I get no entries despite having documents under the relevant collection. I don't get any errors - just no documents appear in the response. However I should be seeing the number of documents I specified in the quantity field. Why is this?

I was storing each embedding field as an array in my firestore database.

[0.1, 0.2, 0.3]

I should have been storing each embedding as a type of vector.

FieldValue.vector([0.1, 0.2, 0.3])

Firebase ignored the fields that weren't a vector, so the index for the search was empty and therefore no documents were returned.