Vector Operations

import os
from gravixlayer import GravixLayer

client = GravixLayer()

# Get vector operations for the index
index_id = "your-index-id"
vectors = client.vectors.index(index_id)

# Upsert a vector with text
vector_result = vectors.upsert_text(
    text="This is a sample document for embedding",
    model="baai/bge-large-en-v1.5",
    id="sample-doc-1",
    metadata={
        "title": "Sample Document",
        "category": "example"
    }
)
print(f"Upserted vector: {vector_result.id}")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

// Get vector operations for the index
const indexId = "your-index-id";
const vectors = client.vectors.index(indexId);

// Upsert a vector with text
const vectorResult = await vectors.upsertText(
  "This is a sample document for embedding",
  "baai/bge-large-en-v1.5",
  "sample-doc-1",
  {
    title: "Sample Document",
    category: "example"
  }
);
console.log(`Upserted vector: ${vectorResult.id}`);

import os
from gravixlayer import GravixLayer

client = GravixLayer()
index_id = "your-index-id"

# Get vector operations for specific index
vectors = client.vectors.index(index_id)

# Example 1: Upsert vector with specific ID
vector = vectors.upsert(
    embedding=[0.1, 0.2, 0.3, 0.4, 0.5],
    id="my-vector-1",
    metadata={"title": "Sample Document", "category": "test"}
)
print(f"Upserted vector: {vector.id}")

# Example 2: Upsert text vector (automatic embedding generation)
text_vector = vectors.upsert_text(
    text="This document will be automatically converted to embeddings",
    model="baai/bge-large-en-v1.5",
    id="text-vector-1",
    metadata={"type": "text", "source": "documentation"}
)
print(f"Text vector: {text_vector.id}")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

// Use the existing test index with 1024 dimensions
const indexId = "your-index-id";
const vectors = client.vectors.index(indexId);

const embedding1024 = Array.from({length: 1024}, () => Math.random() * 0.1);

const vector = await vectors.upsert(
  embedding1024,
  `my-vector-${Date.now()}`,
  { title: "Sample Document", category: "test" }
);
console.log(`Upserted vector: ${vector.id}`);

// Example 2: Upsert text vector (automatic embedding generation)
const textVector = await vectors.upsertText(
  "This document will be automatically converted to embeddings",
  "baai/bge-large-en-v1.5",
  `text-vector-${Date.now()}`,
  { type: "text", source: "documentation" }
);
console.log(`Text vector: ${textVector.id}`);

import os
from gravixlayer import GravixLayer

client = GravixLayer()
index_id = "your-index-id"
vectors = client.vectors.index(index_id)

# Get vector details
vector_details = vectors.get("sample-doc-1")
print(f"Vector ID: {vector_details.id}")
print(f"Metadata: {vector_details.metadata}")
print(f"Embedding dimension: {len(vector_details.embedding)}")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

const indexId = "your-index-id";
const vectors = client.vectors.index(indexId);

// Get vector details
const vectorDetails = await vectors.get("sample-doc-1");
console.log(`Vector ID: ${vectorDetails.id}`);
console.log(`Metadata: ${JSON.stringify(vectorDetails.metadata)}`);
console.log(`Embedding dimension: ${vectorDetails.embedding.length}`);

import os
from gravixlayer import GravixLayer

client = GravixLayer()
index_id = "your-index-id"
vectors = client.vectors.index(index_id)

# Update vector metadata
updated_vector = vectors.update(
    "sample-doc-1",
    metadata={"updated": "true", "version": "2.0"}
)
print(f"Updated vector: {updated_vector.id}")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

const indexId = "your-index-id";
const vectors = client.vectors.index(indexId);

// Update vector metadata
const updatedVector = await vectors.update("sample-doc-1", {
  metadata: { updated: "true", version: "2.0" }
});
console.log(`Updated vector: ${updatedVector.id}`);

import os
from gravixlayer import GravixLayer

client = GravixLayer()
index_id = "your-index-id"
vectors = client.vectors.index(index_id)

# Delete a single vector
delete_result = vectors.delete("sample-doc-1")
print(f"Deleted vector: {delete_result}")

# Delete multiple vectors
vector_ids = ["vector1", "vector2","vector3"]
batch_delete_result = vectors.batch_delete(vector_ids)
print(f"Batch delete result: {batch_delete_result}")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

const indexId = "your-index-id";
const vectors = client.vectors.index(indexId);

// Delete a single vector
const deleteResult = await vectors.delete("sample-doc-1");
console.log(`Deleted vector: ${deleteResult}`);

// Delete multiple vectors
console.log("\nBatch deleting vectors...");
const vectorIds = ["my-vector1", "my-vector-2"];
const batchDeleteResult = await vectors.batchDelete(vectorIds);
console.log(`Batch delete result:`, batchDeleteResult);
console.log(`Successfully deleted ${vectorIds.length} vector(s)`);

import os
from gravixlayer import GravixLayer

client = GravixLayer()
index_id = "your-api-key"
vectors = client.vectors.index(index_id)

# List all vectors (returns a dictionary with vector_id as key)
vector_list = vectors.list()
print(f"Total vectors: {len(vector_list.vectors)}")

for vector_id, vector in vector_list.vectors.items():
    print(f"ID: {vector.id}")
    print(f"Metadata: {vector.metadata}")
    print("---")

import { GravixLayer } from 'gravixlayer';

const client = new GravixLayer({
  apiKey: process.env.GRAVIXLAYER_API_KEY,
});

const indexId = "your-api-key";
const vectors = client.vectors.index(indexId);

// List all vectors
console.log("Listing all vectors in index...");
const vectorList = await vectors.list();

// Convert the vectors object to an array since it's a dictionary (Record<string, Vector>)
const vectorArray = Object.values(vectorList.vectors);
console.log(`Total vectors: ${vectorArray.length}\n`);

if (vectorArray.length === 0) {
  console.log("No vectors found in this index.");
} else {
  vectorArray.forEach((vector, index) => {
    console.log(`${index + 1}. Vector ID: ${vector.id}`);
    console.log(`   Metadata: ${JSON.stringify(vector.metadata)}`);
    console.log(`   Embedding dimension: ${vector.embedding.length}`);
    console.log(`   Delete protection: ${vector.delete_protection}`);
    console.log(`   Created: ${vector.created_at}`);
    console.log("---");
  });
}

// You can also get the vector IDs as an array
const vectorIds = Object.keys(vectorList.vectors);
console.log(`\nVector IDs: ${vectorIds.join(', ')}`);