fetcher-llm-streaming

name	fetcher-llm-streaming
description	Use when consuming Server-Sent Events, LLM token streams, OpenAI-style streaming chat responses, Fetcher eventstream helpers, response prototype extensions, stream termination detection, result extractors, or ReadableStream async iteration.

fetcher-llm-streaming

Use This Skill When

• The task involves SSE, EventSource-style data, streaming responses, or token-by-token UI updates.
• The task mentions eventStream, jsonEventStream, textEventStream, or ReadableStreamAsyncIterable.
• The task needs OpenAI-style completion chunks or DONE termination handling.
• The task needs a decorator result extractor for streaming endpoints.

Workflow

1. Import @ahoo-wang/fetcher-eventstream for side-effect prototype helpers when using Response extensions.
2. Use standalone conversion functions when prototype mutation is undesirable.
3. Handle stream conversion errors explicitly with EventStreamConvertError.
4. Detect termination with the package helper instead of ad hoc string checks.
5. Load references/api.md for pipeline details, OpenAI streaming examples, and UI update patterns.

Key Practices

• Keep parsing, termination detection, and UI state updates as separate steps.
• Use async iteration over streams to avoid buffering full responses in memory.
• When pairing with decorators, configure result extractors at the endpoint boundary.

References

• references/api.md: Detailed package API, examples, and edge-case guidance. Load it only when the task needs prototype extensions, standalone stream functions, SSE structures, termination handling, OpenAI streaming examples, and React UI update snippets.

Related Skills

• $fetcher-openai-client: Use for higher-level OpenAI chat client setup.
• $fetcher-decorator-service: Use when the streaming endpoint is declared with decorators.
• $fetcher-react-hooks: Use when streaming data drives React state.