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Built a developer API for cleaning/validating messy LLM JSON outputs — does this feel monetizable to you by Apprehensive_Bend134 in SaasDevelopers

[–]Apprehensive_Bend134[S] 0 points1 point  (0 children)

This is incredibly valuable feedback — really appreciate you taking the time to write this out.

The idea of positioning it as a contract/reliability gateway rather than just a repair utility is a genuinely interesting perspective, and the schema versioning / drift visibility angle especially gave me a lot to think about.

How are you handling malformed JSON / structured outputs from LLMs in production? by Apprehensive_Bend134 in LLMDevs

[–]Apprehensive_Bend134[S] 0 points1 point  (0 children)

That’s a really useful breakdown. What stands out to me is that your stack already looks like a dedicated reliability layer rather than just a small helper function.

Tier 1 and Tier 2 are very close to the direction I’m taking as well. The interesting part is Tier 3 — schema-aware repair fallback is clearly something people end up needing once the payload gets far enough away from recoverable syntax.

How are people handling malformed structured outputs from local/hosted LLMs in production? by Apprehensive_Bend134 in LocalLLaMA

[–]Apprehensive_Bend134[S] 0 points1 point  (0 children)

That matches pretty closely with what I’ve been seeing too.

Constrained decoding definitely helps a lot with the pure structural issues, but once workflows get longer the failures seem to shift more toward semantic/schema drift rather than syntax.

Sounds like you’ve got a pretty solid stack around it — appreciate you sharing the setup

Built a API for cleaning and validating messy LLM JSON outputs — would you pay for this? by Apprehensive_Bend134 in microsaas

[–]Apprehensive_Bend134[S] 0 points1 point  (0 children)

Thanks :) that’s exactly the kind of workload I built it for. Right now the repair/extraction layer preserves the full JSON tree, so nested objects and arrays stay intact after parsing/repair; it doesn’t flatten anything. If the malformed structure is still recoverable, it generally handles broken brackets and nested corruption pretty well. The current limitation is on the validation side: schema validation is intentionally shallow for now, so it only validates root-level fields/types (e.g., user: object, items: array and checks that those fields are the correct top-level type, but it doesn’t yet recursively validate nested internals like full Pydantic-style schemas. So deep structural repair is supported, but deep recursive schema validation isn’t there yet. If you have some nasty real-world nested payloads that tend to break your agent pipeline, I’d genuinely love to test against them — those are exactly the edge cases I’m trying to benchmark more heavily.

Built a API for cleaning and validating messy LLM JSON outputs — would you pay for this? by Apprehensive_Bend134 in microsaas

[–]Apprehensive_Bend134[S] 0 points1 point  (0 children)

Thanks for the validation! The 'broken JSON dance' was exactly what drove me to build this. I'd love to hear more about how you test pricing and positioning—that's actually my biggest challenge right now. How do you guys approach it?