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Reliability & Contracts

Structured JSON Endpoints vs Raw LLM Prompts

Why task endpoints with a fixed JSON schema are easier to ship and maintain than parsing free-text answers from a raw LLM prompt.

Side by side

Structured Endpoints vs Raw Prompts

Option A

Structured Endpoints

Each endpoint returns documented fields such as sentiment and confidence, validated before the response is sent.

Strengths

  • No free-text parsing
  • Stable across model upgrades
  • Easy to store and query
Option B

Raw Prompts

You ask a general model for an answer and parse whatever text it returns.

Strengths

  • Maximum flexibility
  • Quick to prototype

Where raw prompts break

Models sometimes add explanations, wrap JSON in markdown, rename keys or return a label you did not expect. Each of these becomes a bug in production. Structured endpoints validate and normalise the output so your code only sees the documented values.

Bring your own schema

When no task endpoint fits, the JSON Extractor endpoint accepts your own schema and returns data that matches it, plus a schema_conforms flag.

Frequently asked questions

What does every RSFlowHub response contain?
success, request_id, data.result and meta (version and timestamp). Errors use the same envelope with an error code and message.

Test it on your own data

Free plan with 100 credits/month + 1,000 bonus credits when you sign in before 23 Nov. One API key for every endpoint, with automatic provider fallback.

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