parallel-data-enrichment

Data Enrichment

Enrich: $ARGUMENTS

Before starting

Inform the user that enrichment may take several minutes depending on the number of rows and fields requested.

Optional: Suggest output columns

If the user gave a vague intent ("enrich these companies with useful info") and you're not sure what columns to add, ask the API for a suggestion before kicking off the run:

parallel-cli enrich suggest "Find CEO and recent funding info" --json

The response is an envelope: {title, processor, enriched_columns, warnings}. Extract just the enriched_columns array (not the whole envelope) and pass it as the value of --enriched-columns on enrich run, in place of --intent. These flags are alternative ways to specify what to enrich. If suggest returned a processor, pass it explicitly via --processor on the run call. Skip this section if the user already specified the fields they want.

enrich suggest requires parallel-cli ≥ 0.3.0. If only that command is missing, skip the optional suggestion step and use --intent in step 1. Do not classify authentication, API or invalid-input failures as an older CLI. An intent-based run itself requests a suggestion; explicit columns default to core-fast, while intent can select another processor unless --processor overrides it.

Step 1: Start the enrichment

Use ONE of these command patterns (substitute user's actual data):

For inline data:

parallel-cli enrich run --data '[{"company": "Google"}, {"company": "Microsoft"}]' --intent "CEO name and founding year" --target "output.csv" --no-wait --json

For CSV file:

parallel-cli enrich run --source-type csv --source "input.csv" --target "output.csv" --source-columns '[{"name": "company", "description": "Company name"}]' --intent "CEO name and founding year" --no-wait --json

If this is a follow-up to a previous research task and you have its interaction_id, add context chaining:

parallel-cli enrich run --data '...' --intent "..." --target "output.csv" --no-wait --json --previous-interaction-id "$INTERACTION_ID"

This reuses the prior Task's context. Context chaining is unavailable for Zero Data Retention (ZDR) accounts, so omit the flag there and include the needed context explicitly. Enrichment does not return a new interaction_id; retain the prior Task ID for later follow-ups. A taskgroup_id or Search/Extract session_id is not a Task interaction ID.

IMPORTANT: Always include --no-wait so the command returns immediately instead of blocking.

Save the --json output's taskgroup_id, url and num_runs immediately. There is no interaction_id field. If creation is interrupted or its response is lost, inspect whether the group was created before submitting another run. Immediately tell the user:

• Enrichment has been kicked off
• The monitoring URL where they can track progress

The group runs server-side; polling can resume later using its saved ID.

Step 2: Poll for results

Pick a persistent, run-specific output path (e.g., enrichment-acme-tgrp-<id>.json). Polling overwrites its output file, so inspect any existing file and use a new path unless replacement is intended. The output is JSON regardless of extension: an array of rows with input and either output or error. Async polling does not include basis or per-row interaction IDs; do not invent citations or context IDs.

parallel-cli enrich poll "$TASKGROUP_ID" --timeout 60 --output "enrichment-<descriptive-name>-<group-id>.json"

Important:

• Keep polls bounded; --timeout 60 allows progress updates between waits.
• The --target from step 1 is unused in --no-wait mode. Only --output here determines where results are saved, and the file is always JSON.
• A completed group can include failed rows. Count rows containing output separately from rows containing error and compare their total with num_runs; an empty or incomplete file is not successful enrichment of the entire input.

If polling times out or is interrupted

Timeout exit 5 or interruption ends the local wait. Check group state before saying it is still running:

parallel-cli enrich status "$TASKGROUP_ID" --json

Inspect is_active, status_counts and num_runs. Resume the same poll for an active group, or retrieve results for an inactive group and report failures or unresolved rows. Do not recreate the group on a timeout or automatically rerun failed rows. A local file-write failure can be retried with the same group ID and a writable output path.

If the user requested CSV

Convert the saved JSON locally into a separate CSV. Preserve every original input column and row, including duplicate and failed rows; keep enrichment fields separate from conflicting input names and include an error column for failures. Do not assume streamed rows match original input order or guess a join when row identity is ambiguous. Validate the row count and leave the input CSV untouched. This is local conversion, not a CSV produced by async polling; report both JSON and CSV paths.

Response format

After step 1: Share the monitoring URL (for tracking progress).

After step 2:

1. Report successful, failed and total row counts, with any missing results called out.
2. Preview a few successful rows and a representative failure if present, without claiming all rows succeeded.
3. Tell the user the full path to the output file

After completion, link the saved output rather than repeating the monitoring URL.

Setup

If parallel-cli is not found, install and authenticate:

/parallel:parallel-cli-setup

For authentication or API errors, inspect the returned message. A 403 can indicate permissions, account policy or billing; it does not prove low balance. Check parallel-cli auth --json and its authenticated boolean when relevant without exposing credentials. Only a billing-specific error warrants a balance check, and adding funds needs explicit confirmation. Reuse saved group IDs; do not automatically retry an ambiguous creation.