LanceDB

pip install netra-sdk lancedb

npm install netra-sdk vectordb

from netra import Netra
import lancedb
import os

# Initialize Netra
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    trace_content=True
)

# Connect to LanceDB - automatically traced
db = lancedb.connect("./lancedb")
table = db.create_table("my_table", [
    {"id": 1, "vector": [0.1, 0.2], "text": "Sample"}
])

import { Netra } from "netra-sdk";
import * as vectordb from "vectordb";

// Initialize Netra
await Netra.init({
  headers: `x-api-key=${process.env.NETRA_API_KEY}`,
  traceContent: true
});

// Connect to LanceDB - automatically traced
const db = await vectordb.connect("./lancedb");
const table = await db.createTable("my_table", [
  { id: 1, vector: [0.1, 0.2], text: "Sample" }
]);

from netra.decorators import task
from netra import SpanWrapper

@task()
def create_table(db, name: str, data: list):
    span = SpanWrapper("lancedb-create-table", {
        "table.name": name,
        "data.count": len(data)
    }).start()
    
    table = db.create_table(name, data)
    span.end()
    
    return table

import { task, SpanWrapper } from "netra-sdk";

@task()
async function createTable(db: any, name: string, data: any[]) {
  const span = new SpanWrapper("lancedb-create-table", {
    "table.name": name,
    "data.count": data.length
  }).start();
  
  const table = await db.createTable(name, data);
  span.end();
  
  return table;
}

from netra.decorators import task
from netra import SpanWrapper, ActionModel

@task()
def add_vectors(table, data: list):
    span = SpanWrapper("lancedb-add", {
        "vectors.count": len(data)
    }).start()
    
    table.add(data)
    
    span.set_action([ActionModel(
        action="insert",
        action_type="database.insert",
        success=True,
        affected_records=[{"id": str(d["id"])} for d in data],
        metadata={"table": table.name}
    )])
    span.set_attribute("status", "success")
    span.end()

import { task, SpanWrapper, ActionModel } from "netra-sdk";

@task()
async function addVectors(table: any, data: any[]) {
  const span = new SpanWrapper("lancedb-add", {
    "vectors.count": data.length
  }).start();
  
  await table.add(data);
  
  span.setAction([{
    action: "insert",
    action_type: "database.insert",
    success: true,
    affected_records: data.map(d => ({ id: String(d.id) })),
    metadata: { table: table.name }
  }]);
  span.setAttribute("status", "success");
  span.end();
}

from netra.decorators import workflow
from netra import SpanWrapper

@workflow()
def search_vectors(table, query: list[float], limit: int = 5):
    span = SpanWrapper("lancedb-search", {
        "query.size": len(query),
        "limit": limit
    }).start()
    
    results = table.search(query).limit(limit).to_list()
    
    span.set_attribute("results.count", len(results))
    span.end()
    
    return results

import { workflow, SpanWrapper } from "netra-sdk";

@workflow()
async function searchVectors(table: any, query: number[], limit: number = 5) {
  const span = new SpanWrapper("lancedb-search", {
    "query.size": query.length,
    "limit": limit
  }).start();
  
  const results = await table
    .search(query)
    .limit(limit)
    .execute();
  
  span.setAttribute("results.count", results.length);
  span.end();
  
  return results;
}

from netra.decorators import task
from netra import SpanWrapper

@task()
def filter_search(table, query: list[float], filter: str):
    span = SpanWrapper("lancedb-filter-search", {
        "filter": filter
    }).start()
    
    results = table.search(query).where(filter).limit(10).to_list()
    
    span.set_attribute("results.count", len(results))
    span.end()
    
    return results

import { task, SpanWrapper } from "netra-sdk";

@task()
async function filterSearch(table: any, query: number[], filter: string) {
  const span = new SpanWrapper("lancedb-filter-search", {
    "filter": filter
  }).start();
  
  const results = await table
    .search(query)
    .where(filter)
    .limit(10)
    .execute();
  
  span.setAttribute("results.count", results.length);
  span.end();
  
  return results;
}