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fetcher-openai-client

Name: Fetcher Openai Client
Author: Ahoo-Wang

// Use when calling OpenAI Chat Completions through Fetcher, configuring OpenAI or ChatClient, sending streaming or non-streaming chat completion requests, adding interceptors, using completion result extractors, or handling OpenAI client errors.

Exécuter dans Manus

$ git log --oneline --stat

stars:15

forks:4

updated:27 mai 2026 à 09:41

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3 fichiers

SKILL.md

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name	fetcher-openai-client
description	Use when calling OpenAI Chat Completions through Fetcher, configuring OpenAI or ChatClient, sending streaming or non-streaming chat completion requests, adding interceptors, using completion result extractors, or handling OpenAI client errors.

fetcher-openai-client

Use This Skill When

The task needs an OpenAI chat completion client built on Fetcher.
The task mentions OpenAI, ChatClient, chat completions, streaming completions, or completion result extractors.
The task needs OpenAI request interceptors, base URL configuration, or error handling.
The task is about this repository's @ahoo-wang/fetcher-openai package rather than general OpenAI platform usage.

Workflow

Configure the Fetcher-backed OpenAI entry point before using ChatClient directly.
Choose streaming or non-streaming result extraction based on the caller contract.
Use interceptors for auth, tracing, or request customization rather than scattering request changes.
For current OpenAI platform behavior, verify against official docs before changing package semantics.
Load references/api.md for class APIs, type shapes, streaming examples, and error handling patterns.

Key Practices

Keep this skill scoped to Fetcher integration code; route generic OpenAI API questions to official docs workflows.
Do not duplicate SSE parsing logic here when fetcher-llm-streaming covers the stream mechanics.
Make streaming consumers handle partial data and errors explicitly.

References

references/api.md: Detailed package API, examples, and edge-case guidance. Load it only when the task needs OpenAI and ChatClient APIs, chat completion types, streaming and non-streaming examples, interceptors, and error handling snippets.

Related Skills

$fetcher-llm-streaming: Use for lower-level SSE and token stream handling.
$fetcher-integration: Use for core Fetcher interceptors and request lifecycle behavior.
$fetcher-react-hooks: Use when OpenAI calls are exposed through React state hooks.

related-skills.json

même dépôt

fetcher-cosec-auth.md

from "Ahoo-Wang/fetcher"

Use when implementing CoSec authentication with Fetcher, including CoSecConfigurer, JWT token lifecycle, token storage, refresh handling, device ID storage, multi-tenant space resolution, resource attribution, authorization headers, and 401 or 403 error handling.

2026-05-2715

fetcher-decorator-service.md

from "Ahoo-Wang/fetcher"

Use when creating declarative TypeScript API service classes with fetcher-decorator, including @api, HTTP method decorators, path/query/header/body/request parameters, result extractors, lifecycle hooks, inheritance, and reflect-metadata setup.

2026-05-2715

fetcher-eventbus.md

from "Ahoo-Wang/fetcher"

Use when implementing typed event buses, serial or parallel event execution, BroadcastChannel or storage-based cross-tab messaging, handler priority, once handlers, name generation, or event synchronization across browser contexts.

2026-05-2715

fetcher-integration.md

from "Ahoo-Wang/fetcher"

Use when setting up the core Fetcher HTTP client, NamedFetcher, fetcherRegistrar, HTTP methods, path and query parameters, interceptors, timeouts, result extractors, request lifecycle, status validation, or URL templates.

2026-05-2715

fetcher-llm-streaming.md

from "Ahoo-Wang/fetcher"

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.

2026-05-2715

fetcher-openapi-generator.md

from "Ahoo-Wang/fetcher"

Use when generating type-safe Fetcher API clients from OpenAPI 3.x specs, including fetcher-generator CLI usage, CodeGenerator API, GeneratorConfiguration, parse and generation pipeline, model generation, client generation, barrel exports, and Wow CQRS generation support.

2026-05-2715

package.json

"author": "Ahoo-Wang"

"repository": "Ahoo-Wang/fetcher"

Ouvrir le dépôt GitHub Voir les dépôts du créateur

$ install --global

$ download --local

Exécuter dans Manus

name	fetcher-openai-client
description	Use when calling OpenAI Chat Completions through Fetcher, configuring OpenAI or ChatClient, sending streaming or non-streaming chat completion requests, adding interceptors, using completion result extractors, or handling OpenAI client errors.

fetcher-openai-client

Use This Skill When

The task needs an OpenAI chat completion client built on Fetcher.
The task mentions OpenAI, ChatClient, chat completions, streaming completions, or completion result extractors.
The task needs OpenAI request interceptors, base URL configuration, or error handling.
The task is about this repository's @ahoo-wang/fetcher-openai package rather than general OpenAI platform usage.

Workflow

Configure the Fetcher-backed OpenAI entry point before using ChatClient directly.
Choose streaming or non-streaming result extraction based on the caller contract.
Use interceptors for auth, tracing, or request customization rather than scattering request changes.
For current OpenAI platform behavior, verify against official docs before changing package semantics.
Load references/api.md for class APIs, type shapes, streaming examples, and error handling patterns.

Key Practices

Keep this skill scoped to Fetcher integration code; route generic OpenAI API questions to official docs workflows.
Do not duplicate SSE parsing logic here when fetcher-llm-streaming covers the stream mechanics.
Make streaming consumers handle partial data and errors explicitly.

References

references/api.md: Detailed package API, examples, and edge-case guidance. Load it only when the task needs OpenAI and ChatClient APIs, chat completion types, streaming and non-streaming examples, interceptors, and error handling snippets.

Related Skills

$fetcher-llm-streaming: Use for lower-level SSE and token stream handling.
$fetcher-integration: Use for core Fetcher interceptors and request lifecycle behavior.
$fetcher-react-hooks: Use when OpenAI calls are exposed through React state hooks.

fetcher-openai-client

fetcher-openai-client

Use This Skill When

Workflow

Key Practices

References

Related Skills

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