Classify JSON and NDJSON streams

Use sem_classify when each record needs one label from a small list: support route, incident type, moderation bucket, or review theme. The output is bounded to the labels you write in the query, which makes it safer for downstream jq and shell pipelines than free text generation.

Classify a JSON array with no network

Start with --backend mock to validate the jq expression without a model, provider, or API key:

printf '[{"id":1,"text":"billing question"},{"id":2,"text":"bug report"}]' \
  | ajq --backend mock -c '.[] | {id, route: sem_classify(.text; "billing"; "bug"; "feature")}'

Expected output with the mock backend:

{"id":1,"route":"billing"}
{"id":2,"route":"bug"}

sem_classify returns exactly one of the labels from the call site. Keep labels short, mutually exclusive, and stable because they become part of your output contract.

Classify NDJSON one record at a time

ajq processes newline-delimited JSON as independent input frames, so it can classify streams without buffering the whole input:

printf '{"id":1,"text":"billing question"}\n{"id":2,"text":"bug report"}\n' \
  | ajq --backend mock -c '{id, route: sem_classify(.text; "billing"; "bug"; "feature")}'

This emits one compact JSON object per input record, which is convenient for queues, logs, and shell pipelines.

Route webhook events with bounded labels

If a webhook receiver writes each event body as NDJSON, add a stable route before passing the stream to downstream workers:

printf '{"event":"invoice.payment_failed","data":{"message":"billing payment failed"}}\n{"event":"issue.created","data":{"message":"bug report: export crashes"}}\n' \
  | ajq --backend mock -c '. + {route: sem_classify(.data.message; "billing"; "bug"; "other")}'

The command preserves each webhook event and adds a route value drawn from the three labels in the query. Replace the mock backend with a capped real backend when the event text requires semantic classification.

Switch to a real classifier backend

After the mock command produces the shape you need, run the same query with a real backend:

# Local model after `ajq provision`
printf '{"id":1,"text":"billing question"}\n{"id":2,"text":"bug report"}\n' \
  | ajq --backend local --max-calls 25 -c '{id, route: sem_classify(.text; "billing"; "bug"; "feature")}'

# OpenAI-compatible backend, using OPENAI_API_KEY from the environment
printf '{"id":1,"text":"billing question"}\n{"id":2,"text":"bug report"}\n' \
  | ajq --backend openai --model gpt-4.1-mini --max-calls 25 \
      -c '{id, route: sem_classify(.text; "billing"; "bug"; "feature")}'

For paid backends, keep --max-calls at or below your budget. Paid/cloud backends also have a default 100-call guardrail when you do not set one explicitly.

Account for repeated values and cache hits

Semantic classification is cache-keyed by backend, model, operation, label set, and input value. If many records contain the same text, ajq deduplicates the judgements before it calls the backend, and later runs can reuse the persistent cache.

Estimate the distinct judgement count first:

printf '{"text":"billing question"}\n{"text":"billing question"}\n{"text":"bug report"}\n' \
  | ajq --explain '{route: sem_classify(.text; "billing"; "bug"; "feature")}'

Then add --stats to the real run when you want to see post-dedup backend calls and cache hits on stderr.

Related

• Process an NDJSON stream — input framing for JSON, NDJSON, raw lines, and null input.
• Semantic functions reference — bounded classification semantics and limitations.
• Control semantic costs — combine estimates, caps, stats, and cache behavior.
• Backends reference — choose local, mock, Ollama, OpenAI, OpenRouter, or Anthropic.