SDK

TypeScript and Python SDKs for the Query API

Programmatically access and search your Raindrop data. Build dashboards, create eval sets, export data, or integrate Raindrop into your workflows.

Installation

npm install @raindrop-ai/query

pip install raindrop-query

Quick Start

import { RaindropQuery } from "@raindrop-ai/query";

const client = new RaindropQuery({
  apiKey: process.env.RAINDROP_QUERY_API_KEY,
});

// Semantic search user inputs for frustration
const results = await client.events.search({
  query: "frustration about load times",
  mode: "semantic",
  searchIn: "user_input,assistant_output",
});

import os
from raindrop_query import RaindropQuery

client = RaindropQuery(api_key=os.environ["RAINDROP_QUERY_API_KEY"])

# Semantic search user inputs for frustration
results = client.events.search(
  query="frustration about load times",
  mode="semantic",
  search_in="user_input"
)

Get your Query API key here (this is different from the write key used for ingestion).

Common Patterns

List Signals

const response = await client.signals.list({ limit: 10 });

// Returns: { data: [...], meta: { cursor, has_more } }
const signals = response.data;

Get Events for a Signal

const signal = signals[0];

// Get count
const count = await client.events.count({ signal: signal.id });

// Get the actual events
const events = await client.events.list({
  signal: signal.id,
  limit: 100,
});

Event Counts Over Time

const timeseries = await client.events.timeseries({
  signal: signal.id,
  timestamp: { gte: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000).toISOString() },
  interval: "day",
});

Error Handling

import { RaindropQuery, SDKValidationError } from "@raindrop-ai/query";

try {
  const events = await client.events.list();
} catch (error) {
  if (error instanceof SDKValidationError) {
    console.error("Invalid request:", error.message);
  }
}