Hi!
I was not able to reproduce this. Here is the code I used:
import weaviate, { Collection, WeaviateClient, generateUuid5 } from 'weaviate-client';
// Connect to Weaviate
// The client performs I/O during initialisation so these methods all return promises
// You can either await them or use .then() to handle the result
// This is the simplest way to connect to Weaviate
// const client: WeaviateClient = await weaviate.connectToLocal();
// weaviate.connectToLocal().then((client) => { ... });
async function runFullExample() {
const client = await weaviate.connectToLocal({
host: process.env.WEAVIATE_HOST || 'localhost',
port: parseInt(process.env.WEAVIATE_PORT || '8080'),
grpcPort: parseInt(process.env.WEAVIATE_GRPC_PORT || '50051'),
headers: { 'X-OpenAI-Api-Key': process.env.OPENAI_API_KEY as string }, // Replace with your inference API key
});
const cleanRun = true; // change this to false if you don't want to delete the collection each run
initCollection(client, "Geo", cleanRun)
.then(importData)
.then(async (collection) => {
await RemoveGeoPropertyValue(
collection
);
});
// We use promise chaining here because each step depends on the successful completion of the previous step
// The data won't import successfully unless the collection has been created
// Likewise we can't show the data unless it has been imported
// To ensure there are no race conditions, we chain the promises together guaranteeing that each step is completed before the next one starts
}
////// Helper functions for runFullExample //////
function collectionExists(client: WeaviateClient, collection_name:string): Promise<boolean> {
// Check if the collection already exists
return client.collections.exists(collection_name);
}
function getCollection(client: WeaviateClient, collection_name:string): Collection {
return client.collections.get(collection_name);
}
async function createCollection(client: WeaviateClient, collection_name:string): Promise<Collection> {
// let's create the class
const collection = await client.collections.create({
name: collection_name,
properties: [
{
name: 'city',
dataType: 'text',
},
{
name: 'location',
dataType: 'geoCoordinates',
},
],
});
console.log(`Successfully created collection: ${collection.name}!`);
return collection;
}
function deleteCollection(client: WeaviateClient, collection_name:string) {
// Delete the collection if it already exists
return collectionExists(client, collection_name).then((exists) =>
exists ? client.collections.delete(collection_name) : Promise.resolve()
);
}
async function importData(collection: Collection): Promise<Collection> {
// Here we import our data using the `.insertMany` method
// This method batches the data for us in the background
// first, let's grab our Jeopardy Questions from the interwebs
const res = await collection.data.insertMany([
{
properties: {"city": "Belo Horizonte", "location": {"latitude": -19.912998, "longitude": -43.940933}},
id: generateUuid5("belo horizonte")
},
{
properties: {"city": "Amsterdam", "location": {"latitude": 52.3676, "longitude": 4.9041}},
id: generateUuid5("amsterdam")
}
]);
if (res.hasErrors) {
throw new Error(`Failed to import data: ${JSON.stringify(res.errors, null, 2)}`);
}
return collection;
}
function initCollection(client: WeaviateClient, collection_name:string, cleanRun: boolean): Promise<Collection> {
// Here we initialise the collection
// We can either delete the collection and create it from scratch
// Or we can check if it exists and create it if it doesn't
// The `cleanRun` parameter allows us to choose between these two options
if (cleanRun) {
console.log('Cleaning and creating collection anew');
return deleteCollection(client, collection_name).then(() => createCollection(client, collection_name));
} else {
console.log('Creating collection if it does not exist');
return collectionExists(client, collection_name).then((exists) =>
exists ? Promise.resolve(getCollection(client, collection_name)) : createCollection(client, collection_name)
);
}
}
function RemoveGeoPropertyValue(collection: Collection) {
// run RAG/Generative Search query with a prompt to apply to each object returned by the near text query
collection.query.fetchObjects().then(r=>{
// print our objects
console.log(JSON.stringify(r, null, 4));
// update the first object
collection.data.update({
id: generateUuid5("belo horizonte"),
properties: {
location: null
},
}).then(r2=>{
collection.query.fetchObjects().then(r3=>{
// print all objects
console.log(JSON.stringify(r3, null, 4));
})
})
})
}
runFullExample();
Let me know if this helps 
