How do you build summarization with an OpenAI-compatible API?

Key facts

Endpoint	POST https://api.plugsky.com/v1/chat/completions — same shape as OpenAI (live)
Compatibility	Keep the OpenAI SDK; change base_url and model names
JSON mode	Live for structured summaries with fields and bullet lists
Streaming	Live via server-sent events for progressive summaries
Models	30+ models; plugsky-longctx for wide inputs, plugsky-micro and plugsky-lite for bulk passes
Pricing	Flat monthly self-serve plans with no per-token charges; see the live pricing page
Free tier	plugsky-micro and plugsky-lite on the free plan, no card required
Roadmap	The batch endpoint (and files) is coming soon; fan out concurrently in your own worker today

TL;DR

• A summary is one chat completions call plus a prompt contract.
• Keep the OpenAI SDK: change the base URL and map model names.
• Stream long summaries; use JSON mode when downstream code parses them.
• Chunk and reduce oversized documents in your own worker.
• Escalate only dense inputs; cheap tiers handle bulk summaries.

How it works, step by step

1. Point your OpenAI client at the Plugsky base URL and send a test summary request to confirm the response shape.
2. Define the output contract: a fixed schema with a headline, bullet points and source references.
3. Implement a single-pass path for short inputs and a chunk-and-reduce path for long ones.
4. Enable streaming for interactive surfaces and JSON mode for machine-consumed summaries.
5. Cap output length per pass and cap the number of reduce passes to keep latency predictable.
6. Run a regression set of documents and compare coverage and faithfulness before and after the switch.
7. Keep the model name in configuration so you can move between tiers without a deploy.

Try it yourself

Open the OpenAI-compatible API tester →

Three summarization patterns, one endpoint

Single-pass works when the document fits comfortably in context: one call in, one summary out. Map-reduce covers long documents: summarize groups, then summarize the summaries. Incremental summarization suits streams such as meeting transcripts: keep a rolling summary and fold each new segment into it. All three use the same chat completions call, so routing between them is an application decision, not an integration rewrite.

Because the endpoint is OpenAI-compatible, existing prompt code, retry logic and test fixtures keep working. You change the base URL, map model names such as your summarizer alias to a Plugsky tier, and the rest of the pipeline is untouched.

Prompt and output contracts that survive production

Summaries fail downstream when the format drifts. Define the schema once — for example {headline, bullets[], open_questions[]} — and request it with JSON mode so parsing never depends on prose. Instruct the model to mark missing information instead of guessing, and to keep bullets short enough for whatever renders them.

• Put the rules in the system prompt: length, audience, tone and what to omit.
• Set max_tokens to the longest acceptable summary, not the model maximum.
• Validate the JSON against your schema before storage and discard or retry malformed outputs.
• Version prompts alongside code so a summary format change is a reviewable diff.

Cost, latency and migration checks

Bulk summarization is a volume workload, which makes it a routing problem. Send extraction-style passes to plugsky-micro or plugsky-lite, reserve stronger tiers for dense or high-stakes documents, and measure tokens per document so a prompt tweak that doubles input never ships unnoticed. Streaming improves perceived latency even when total generation time is unchanged.

Before cutover, run the same document set through both providers and compare faithfulness, coverage and citation behaviour. Keep the switch reversible — the compatibility runs in both directions. The free plan is enough to build the pipeline, and the 14-day full-access trial lets you evaluate stronger tiers on real documents; see the live pricing page for plans.

Honest comparison

Concern	Summarization on Plugsky	Proprietary summarization service	Self-hosted model
Integration	OpenAI SDK, base URL change	Vendor SDK and console	Serve and scale the model yourself
Output control	Prompt plus JSON mode schema	Template options inside the product	Full control, full responsibility
Long documents	Chunk-and-reduce in your worker	Usually fixed input limits	Limited by your GPU memory
Model choice	30+ models behind one endpoint	Vendor-selected models	Only models you can host
Deployment	Cloud, VPC, on-prem and air-gapped options	Vendor cloud	Your infrastructure

Frequently asked questions

Do I need to rewrite my summarization code?

No. The endpoint is OpenAI-compatible: change the base URL and model names, then keep your prompts, retries and tests. Switching back is the same one-line change in reverse.

How do I summarize documents longer than the context window?

Chunk the document, summarize each chunk group in a first pass, then run a reduce pass over the partial summaries. Carry source identifiers through both passes if you need traceability.

Can the summary come back as JSON?

Yes. JSON mode is live, so you can request a fixed schema such as headline, bullets and open questions, then validate it before storage.

Should I stream summaries?

Stream when a person is waiting and the summary is long, because tokens arrive progressively. Use non-streaming JSON mode when a downstream system consumes the result.

How do I control cost?

Route bulk passes to plugsky-micro or plugsky-lite, cap max_tokens, avoid resending unchanged context, and measure tokens per document. Self-serve plans are flat monthly with no per-token charges.

Is there a batch endpoint?

Not yet — the batch endpoint is coming soon per the docs. Today, run concurrent requests from your own worker with bounded parallelism and retries.

Can I evaluate before switching?

Yes. Run the same documents through both endpoints, compare coverage, faithfulness and format validity, and keep both configurations behind a feature flag.

Is there a free way to start?

Yes. plugsky-micro and plugsky-lite are on the free plan with no card, and a 14-day full-access trial is available for stronger models.