effect-uai-streaming-structured-output

To stream structured JSON objects incrementally, this Skill decodes model output line by line as JSONL, validating each line against a defined Effect.Schema before emitting typed data. It uses a multi-stage pipeline with Effect primitives for live result scenarios.

Validating typed data in a streaming JSONL pipeline is handled through schema-driven validation, verifying each incoming line against an Effect.Schema. This ensures every incrementally delivered JSON object conforms to your defined structure before it is processed.

Yes, you can use Effect Stream primitives to handle incremental search results by decoding and emitting typed JSON objects progressively. The Skill implements a pipeline using Stream and Lines to process live data feeds as they arrive.

Per-line decoding for live streaming recipes works by processing each line of model output individually through StructuredFormat and Effect primitives. This allows the pipeline to validate and emit typed JSONL objects progressively without waiting for the complete response.

No, you do not need to wait for a complete model response to parse structured output. This Skill decodes and streams typed JSON objects as they arrive, enabling you to display live search results or incremental data feeds immediately.

Error handling when streaming JSONL with Effect is integrated into the multi-stage pipeline, catching validation or decoding failures per line. This ensures that malformed lines do not crash the stream while valid typed data continues to emit.