Summarize records with a model
Generate one-sentence summaries and retain them alongside source record context.
Use LLM summarize records to load a bounded set of retained records, generate a one-sentence summary for each, and store the results as a chosen record type.
Configure the template
| Parameter | What to enter |
|---|---|
workflow_name | A nonempty workflow name. |
data_source_id | The retained-record source to summarize. |
limit | Records to load: 1–5,000, default 200. |
model | A supported provider-prefixed model; the seeded template stores openai:gpt-4.1-mini. |
record_type | A nonempty type for saved results; default summary. |
Confirm the selected model is offered in your workspace. A stored template default can remain in a definition even when you should select another available model for your process.
Generate a first result
- Choose the template and select the source.
- Set a small limit and confirm the model.
- Create the workflow and inspect
load → summarize → persist. - Review the prompt and output field in the model job.
- Validate and start a Manual run.
- Compare saved summaries against their source content.
The loader requests shape: normalized. The prompt asks for one sentence and includes ${content}. Check that normalized content contains what you expect; a record's metadata alone may not be the material you want summarized.
The model job writes text at summary, with a 256-token output limit, temperature 0.2, and concurrency 2. A one-sentence instruction is a request to the model, not a schema that proves every output is exactly one sentence.
Inspect quality and usage
The job preserves input context alongside the summary and can include finish-reason and usage fields. Check truncated responses, error fields, missing content, and unusually long input. A successful workflow is not a guarantee of factual correctness.
The destination keys include the run and record sequence. New runs can create new results rather than replacing a single permanent summary for each source record. Choose a stable identity strategy if you adapt the process for ongoing updates.
This recipe's loader is bounded and nonbatched; a result count equal to limit may mean more source records remain. Model calls and preview execution can incur usage.
See LLM, run modes, and workflow outputs.
Prepared job settings
The starter is enabled and uses a Manual trigger. These settings are supplied by the recipe; review them in the editor before adapting the process. ${…} values below refer to the corresponding template parameter or run variable.
| Setting | Prepared value |
|---|---|
load.config.data_source_id | "${data_source_id}" |
load.config.limit | "${limit}" |
load.config.shape | "normalized" |
summarize.config.model | "${model}" |
summarize.config.prompt_template | "Summarize the following record in one sentence:\n\n${content}" |
summarize.config.output_path | "summary" |
summarize.config.max_tokens | 256 |
summarize.config.temperature | 0.2 |
summarize.config.concurrency | 2 |
persist.config.record_type | "${record_type}" |
persist.config.idempotency_key_template | "summarize:${run_id}:${record_seq}" |