OpenAI (Embedding)
A RocketRide embedding node that converts document chunks and search queries into vectors using OpenAI's embedding API.
What it does
Generates text embeddings using OpenAI's embedding API. Documents arriving on the documents lane have an embedding vector (and the embedding_model name) attached to each chunk, ready for ingestion into a vector store. Questions arriving on the questions lane are embedded with the same model so they can be matched against a stored index.
Uses langchain-openai (OpenAIEmbeddings) under the hood. Document chunks are embedded in a single batched embed_documents call per write; questions are embedded one at a time with embed_query. An empty document list is a no-op.
At pipeline startup the node makes one small probe call (embedding the string "dummy") to discover the model's vector size, since the API does not report it directly: expect one extra tiny request when the pipeline starts. The maximum token count per request is read from the model's context length (embedding_ctx_length).
Requires an OpenAI API key.
Configuration
Lanes
| Lane | Direction | Description |
|---|---|---|
documents | in / out | Embed document text; attach vector to each chunk for vector store ingestion |
questions | in / out | Embed a query string; attach vector for similarity search against a stored index |
Fields
| Field | Type | Description |
|---|---|---|
model | string | OpenAI model to use for embedding |
profile | string | Default "text-embedding-3-small". OpenAI embedding model |
Each profile resolves to a model name and token limit that the wrapper passes to OpenAIEmbeddings.
Profiles
| Profile | Model | Notes |
|---|---|---|
| Text Small (default) | text-embedding-3-small | Efficient, good general-purpose performance |
| Text Large | text-embedding-3-large | Higher accuracy, larger vector representation |
| Text Ada | text-embedding-ada-002 | Legacy model (first OpenAI embeddings model) |
All three models accept up to 8,191 tokens per input.
Authentication
Set the apikey field to your OpenAI API key. The key is resolved per profile, so if you switch profiles you may supply a different key for each. There is no support for organization-scoped keys or Azure OpenAI endpoints in this node.
Schema
| Field | Type | Description | Default |
|---|---|---|---|
openai_embed.model | string | Model name OpenAI model to use for embedding | |
openai_embed.profile | string | Model OpenAI embedding model | "text-embedding-3-small" |
Dependencies
openailangchain-openai