Quickstart

pip install datagate

npm install datagate

from datagate import DatagateClient

client = DatagateClient(api_key="dg_live_...")

datasets = await client.list_datasets()
for ds in datasets:
    print(f"{ds.name} — {ds.price_per_chunk} {ds.currency}/chunk")
    if ds.metadata_schema:
        for field in ds.metadata_schema:
            print(f"  Filter: {field['name']} ({field['type']})")

import { DatagateClient } from "datagate";

const client = new DatagateClient({ apiKey: "dg_live_..." });

const datasets = await client.listDatasets();
for (const ds of datasets) {
  console.log(`${ds.name} — ${ds.price_per_chunk} ${ds.currency}/chunk`);
  if (ds.metadata_schema) {
    for (const field of ds.metadata_schema) {
      console.log(`  Filter: ${field.name} (${field.type})`);
    }
  }
}

response = await client.query(
    text="machine learning transformers",
    dataset_ids=[ds.id for ds in datasets if ds.queryable],
    top_k=5,
)

for result in response.results:
    print(f"[{result.score:.4f}] {result.metadata}")

await client.close()

const response = await client.query({
  text: "machine learning transformers",
  datasetIds: datasets.filter((ds) => ds.queryable).map((ds) => ds.id),
  topK: 5,
});

for (const result of response.results) {
  console.log(`[${result.score.toFixed(4)}]`, result.metadata);
}

response = await client.query(
    text="privacy regulations",
    dataset_ids=["ds-aaa", "ds-bbb"],
    filters={
        "ds-aaa": {"year": {"$gte": 2023}},
        "ds-bbb": {"category": {"$eq": "legal"}},
    },
)

const response = await client.query({
  text: "privacy regulations",
  datasetIds: ["ds-aaa", "ds-bbb"],
  filters: {
    "ds-aaa": { year: { $gte: 2023 } },
    "ds-bbb": { category: { $eq: "legal" } },
  },
});