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@tanstack/openai-base

Shared base adapters for providers that drive the official openai SDK against a different baseURL.

TL;DR

Several providers ship endpoints that the official openai Node SDK can talk to verbatim — you just point it at a different baseURL. xAI's Grok endpoint, Groq's /openai/v1 endpoint, and OpenAI itself all fall in this camp. This package contains the shared logic for both wire formats those endpoints expose:

• OpenAIBaseChatCompletionsTextAdapter — for /v1/chat/completions • OpenAIBaseResponsesTextAdapter — for /v1/responses

Provider packages (@tanstack/ai-openai, @tanstack/ai-groq, @tanstack/ai-grok) construct an OpenAI client with their own baseURL, pass it to the relevant base adapter, and override a small set of protected hooks for SDK-shape variance and provider-specific quirks.

Why this package exists

Every text adapter in TanStack AI — regardless of provider — emits AG-UI events (RUN_STARTED, TEXT_MESSAGE_*, TOOL_CALL_*, RUN_FINISHED, …) as its output stream. That is the universal unification.

Input protocols differ. The OpenAI Chat Completions and Responses wire formats both have multiple implementers in the ecosystem, so it pays to write the streaming-chunk assembly, partial-JSON tool-arg buffering, tool-call deduplication, and structured-output coercion once and share it. That shared code lives here.

Providers whose native API doesn't match either OpenAI wire format (Anthropic, Gemini, Ollama's native API, OpenRouter's own SDK) extend BaseTextAdapter from @tanstack/ai directly — there's nothing to share, so they don't pay the indirection cost.

What goes here vs. in @tanstack/ai-openai

| Belongs in @tanstack/openai-base | Belongs in @tanstack/ai-openai |

| Logic for the Chat Completions wire format | OpenAI-specific tool types (web_search_preview, code_interpreter, local_shell, apply_patch, computer_use, mcp, …) | | Logic for the Responses wire format | OpenAI model metadata, model lists, capability matrices | | Streaming chunk assembly, AG-UI lifecycle, partial-JSON tool-arg buffering, tool-call deduplication | OpenAI-only request/response fields that no other consumer of the base sets | | Schema converters and structured-output coercion that all consumers accept | OpenAI's media adapters (image/TTS/video/transcription) that Grok/Groq don't implement |

Rule of thumb: if a field would be useful to at least two of the consuming packages (ai-openai, ai-grok, ai-groq), it belongs here. Otherwise it belongs in the provider's own package, plumbed in via a subclass override or a hook.

How providers extend the bases

The base constructor takes a pre-built OpenAI client. Subclasses construct the SDK with their own baseURL (and any other client options) and pass it to super:

Per-provider quirks are handled via protected hooks:

• convertMessage, mapOptionsToRequest — bridge request-shape differences (extra fields, omitted fields, alternative encodings). • extractReasoning — surface a provider's reasoning channel into the shared REASONING_* AG-UI lifecycle. • transformStructuredOutput, makeStructuredOutputCompatibleWithMap — adjust structured-output handling for provider quirks (e.g. Groq's schema-shape requirements). • processStreamChunks — wrap the shared chunk processor for last-mile fixups (e.g. Groq's x_groq.usage → chunk.usage promotion). • extractTextFromResponse — pull the assistant text out of the provider's non-streaming response shape.

Each provider typically overrides 2–6 hooks and inherits everything else.

Architecture

Note: ai-openai ships only the Responses-based text adapter. For pure Chat Completions use cases without OpenAI-specific behaviour, use ai-grok or ai-groq, or build a new provider package extending OpenAIBaseChatCompletionsTextAdapter.

Direct use

Most users don't import from this package directly; they install a provider package and the adapter from there does the work.

If you're building an adapter for a new endpoint that the official openai SDK can talk to verbatim (vLLM, Together, Fireworks, a self-hosted gateway, …), import the abstract adapters from this package and subclass them. The existing providers are worked examples — @tanstack/ai-grok is the simplest (xAI's API is a near-direct OpenAI Chat Completions clone), @tanstack/ai-groq shows the processStreamChunks and makeStructuredOutputCompatibleWithMap override pattern.

Description from the npm listing.