kagiPro Enrich Endpoint Guide • kagiPro

Enrich Endpoint: Context Discovery for Web and News

The Enrich API is useful when a plain search result list is not enough and you want curated context for a topic.

In kagiPro, this is split into two constructors:

query_enrich_web() for web context.
query_enrich_news() for news context.

The execution flow is identical for both.

Create the connection once

library(kagiPro)

conn <- kagi_connection(
  api_key = function() keyring::key_get("API_kagi")
)

Build web and news enrich queries

Assume you are tracking biodiversity policy from institutional sources.

q_web <- query_enrich_web(
  query = "open data portals",
  site = "gov",
  expand = FALSE
)

q_news <- query_enrich_news(
  query = "biodiversity policy",
  expand = FALSE
)

Both constructors return named lists, so single and batch execution share the same interface.

Execute a focused run for each enrich type

out_web <- "enrich_web"
dir.create(out_web, recursive = TRUE, showWarnings = FALSE)

kagi_request(
  connection = conn,
  query = q_web[[1]],
  output = out_web,
  overwrite = TRUE
)

out_news <- "enrich_news"
dir.create(out_news, recursive = TRUE, showWarnings = FALSE)

kagi_request(
  connection = conn,
  query = q_news[[1]],
  output = out_news,
  overwrite = TRUE
)

At this stage you have two independent JSON collections, one for web context and one for news context.

Move to a thematic batch workload

For recurring monitoring, prepare a topic vector and run it as a batch.

q_news_batch <- query_enrich_news(
  query = c("biodiversity", "ecosystem restoration", "nature finance"),
  expand = TRUE
)

kagi_request(
  connection = conn,
  query = q_news_batch,
  output = "enrich_news_batch",
  overwrite = TRUE,
  workers = 2
)

This pattern is well suited for weekly or monthly trend snapshots.

Handle request failures without losing the whole run

If you want long jobs to continue when one request fails:

kagi_request(
  connection = conn,
  query = q_news_batch,
  output = "enrich_news_batch_safe",
  overwrite = TRUE,
  workers = 2,
  error_mode = "write_dummy"
)

Failed requests are written as dummy JSON with data = null plus an error block, and the function emits warnings.

Convert enrich output to parquet

kagi_request_parquet(
  input_json = "enrich_news_batch",
  output = "enrich_news_batch_parquet",
  overwrite = TRUE
)

Use parquet when you want to join enrich data with other tables or build reproducible reports.

Operational recommendations

Keep web and news outputs in separate directories.
Start with workers = 1 during debugging, then increase.
Keep raw JSON as the source of truth, and regenerate parquet as needed.