This document is a full export audit across the three ecosystems we support: AI SDK, LangChain (JS/TS), and LlamaIndex (TS). The goal is to map every major export surface to our adapter primitives, highlight mismatches, and list gaps.

This is a catalogue — not a commitment to implement every construct. Anything outside our adapter surface is explicitly called out.

The goal is to ensure Recipes are portable across these ecosystems.

AI SDK (ai + provider + provider-utils)

TIP

See the Models Adapter Page for implementation details.

Packages audited:

• ai (core helpers + UI utilities)
• @ai-sdk/provider (model interfaces + telemetry)
• @ai-sdk/provider-utils (messages/tools/schemas)
• @ai-sdk/langchain (UI message/stream adapter + LangSmith transport)
• @ai-sdk-tools/cache (tool caching helpers)
• @ai-sdk-tools/memory (working memory + history provider)
• @ai-sdk-tools/store (chat UI store + hooks)
• @ai-sdk/openai, @ai-sdk/anthropic, ollama-ai-provider-v2 (providers)

Key export categories:

• Model interfaces: LanguageModelV2/V3, EmbeddingModelV2/V3, ImageModelV2/V3, SpeechModelV2/V3, TranscriptionModelV2/V3, RerankingModelV3.
• Model helpers: generateText, generateObject, streamText, streamObject, embed, embedMany, generateImage, generateSpeech, transcribe.
• Messages + tools (provider-utils): ModelMessage, Tool, Schema, jsonSchema, zodSchema, content part helpers.
• UI/runtime wrappers (ai): chat UI, streaming UI, transport, UI message schemas.

Mapping to our primitives:

• Model, Embedder, Reranker, ImageModel, SpeechModel, TranscriptionModel → covered (V3 canonical).
• Messages, Tools, Schema, PromptTemplate → covered.
• Memory → partial via @ai-sdk-tools/memory (working memory + history provider).
• Cache → partial via @ai-sdk-tools/cache CacheStore adapters (TTL best-effort).
• Store → out of scope (@ai-sdk-tools/store is a UI state layer).
• LangChain UI bridge → out of scope (@ai-sdk/langchain targets UI transport + streaming).
• Streaming → covered (normalized events across AI SDK, LangChain, LlamaIndex).
• UI/transport → out of scope (UI-only).

Gaps:

• Provider middleware hooks exist but no adapter-level tracing bridge.
• AI SDK LangChain adapter is UI/transport-level; we could mirror ideas for runtime stream bridging.
• No checkpoint/event stream/interrupt abstractions in the AI SDK surface.

LangChain (JS/TS)

TIP

See the Retrieval and Tools adapter pages.

Packages audited:

• @langchain/core
• @langchain/community
• @langchain/openai
• @langchain/ollama
• @langchain/textsplitters

Core module inventory (from @langchain/core/*.d.ts):

• agents, runnables, tools, retrievers, vectorstores
• documents, document_loaders, memory, chat_history, stores
• prompts, prompt_values, messages, outputs, output_parsers
• structured_query, indexing, caches, callbacks, tracers

Mapping to our primitives:

• Model, Embedder, Retriever, Reranker, TextSplitter, Transformer, DocumentLoader, VectorStore, Memory, KVStore, Cache, Tool, PromptTemplate, OutputParser, StructuredQuery, Trace, EventStream, Indexing, Checkpoint → covered.
• Runnable, Agents, ChatHistory → not covered.

Gaps:

• Runnables/chains/agents are higher-level composition constructs.
• Callbacks/tracers map to trace sinks (custom + run.start/run.end + provider.response).

LlamaIndex (TS)

TIP

See the Retrieval Adapter Page for implementation details.

Packages audited (top-level modules):

• llms, embeddings, retriever, postprocessor, node-parser
• tools, prompts, memory, schema, vector-store, storage
• query-engine, response-synthesizers, chat-engine, agent, indices

Mapping to our primitives:

• Model, Embedder, Retriever, Reranker, TextSplitter, Transformer, DocumentLoader, VectorStore, Memory, KVStore, Cache, Tool, PromptTemplate → covered.
• QueryEngine, ResponseSynthesizer, EventStream, Checkpoint → covered.
• ChatEngine, Agent, Indices → not covered.

Gaps:

• Storage context and index lifecycle helpers are not modeled.
• Interrupt strategy remains core-only.

Media Construct Catalogue

AI SDK

• Image: ImageModelV3 (provider: @ai-sdk/provider)
• Speech (TTS): SpeechModelV3
• Transcription (STT): TranscriptionModelV3

Additional AI SDK interfaces worth tracking:

• RerankingModelV3 (provider) for rerankers.
• EmbeddingModelV3 and LanguageModelV3 (streaming-friendly).

LangChain (JS/TS)

• Image generation:
  • DallEAPIWrapper (JS) in @langchain/openai (tools/dalle)
  • imageGeneration tool spec (Responses API tool)
  • These are tool-style wrappers, not a generic ImageModel interface.
• Audio output:
  • ChatOpenAI supports audio output (model modalities + audio options)
  • This is a feature of the chat model, not a standalone SpeechModel.
• Transcription:
  • Document loaders for audio (e.g., OpenAIWhisperAudio, SonixAudioTranscriptionLoader)
  • These map to DocumentLoader rather than a formal TranscriptionModel.

LlamaIndex (TS)

• Image generation:
  • Tool specs exist (e.g., OpenAI image generation tool spec)
  • Exposed via tool calling, not a dedicated ImageModel.
• Multimodal:
  • Multimodal LLMs handle image inputs; still a Model surface, not a media model.
• Audio / transcription:
  • No canonical speech/transcription model interface surfaced in core packages.
• Trace:
  • Workflow trace plugins map to Trace adapters (handler start/end/error).

Parity Matrix

Legend:

• full: adapter exists and aligns with the construct
• partial: adapter exists but semantics differ or are limited
• provider-specific: adapter only for certain providers/tools
• missing: no adapter or ecosystem surface

Construct	AI SDK	LangChain	LlamaIndex	Mix-and-match implications
Model	full	full	full	Safe to mix; Model is the canonical cross-ecosystem surface.
Embedder	full	full	full	Safe; embedding dimension may still vary per provider.
Retriever	missing	full	full	AI SDK has no retriever abstraction; must bring one from LC/LI.
Reranker	full	full	full	AI SDK supports reranking via RerankingModelV3.
TextSplitter	missing	full	full	AI SDK has no splitter; LC/LI supported.
Transformer	missing	full	full	AI SDK has no transformer; LC/LI supported.
Storage (KVStore)	missing	full	full	AI SDK has no storage adapter.
Cache	partial	partial	partial	AI SDK CacheStore + LC BaseStore + LI BaseKVStore; TTL best-effort.
Checkpoint	missing	full	full	LlamaIndex snapshots map via SnapshotData stores.
EventStream	missing	full	full	LangChain via callback handlers; LlamaIndex workflow events.
Interrupt	missing	full	missing	LangGraph interrupt semantics map to restart strategies.
KV	missing	full	full	AI SDK has no KV adapter; UI store is out of scope.
Memory	partial	full	full	AI SDK has a memory provider (@ai-sdk-tools/memory), mapped.
Tools	full	full	full	Safe; tool schemas normalize across ecosystems.
OutputParser	missing	full	missing	LangChain parsers only; other ecosystems lack a parser interface.
StructuredQuery	missing	full	missing	LangChain structured query IR; other ecosystems lack a parser.
Indexing	missing	full	missing	LangChain index + record manager; no AI SDK/LI parity yet.
QueryEngine	missing	missing	full	LlamaIndex query engine; no AI SDK/LC parity yet.
ResponseSynthesizer	missing	missing	full	LlamaIndex synthesizers; no AI SDK/LC parity yet.
VectorStore (write)	missing	full	partial	AI SDK has none; LC full; LI delete filters not supported.
ImageModel	full	missing	missing	AI SDK direct; LC/LI require tool wrappers.
SpeechModel	full	missing	missing	AI SDK direct; LC via ChatOpenAI audio output.
TranscriptionModel	full	missing	missing	AI SDK direct; LC via document loaders (shape mismatch).
Trace	missing	full	full	LangChain callbacks + LlamaIndex trace plugins map to trace sink.
Streaming (Model)	full	full	full	Normalized stream events; provider-specific parts remain raw.

Summary: Coverage vs Gaps

Covered primitives (cross-ecosystem):

• Model, Embedder, Retriever, Reranker
• TextSplitter, Transformer, DocumentLoader
• VectorStore (write path), Memory (LC/LI), KVStore (LC/LI), Cache (partial)
• Tool, PromptTemplate, Schema, Messages
• Trace (LangChain + LlamaIndex)
• OutputParser (LangChain only)
• StructuredQuery (LangChain only)
• ImageModel, SpeechModel, TranscriptionModel (AI SDK direct; LC/LI provider-specific)

Gaps (candidate future primitives):

• Indexing (LangChain only).
• QueryEngine and ResponseSynthesizer (LlamaIndex only).