ActionTogether AIUpdated September 2026

How do I generate embeddings on Together AI?

Short answer: You can create embeddings in Together AI by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Together AI Create Embeddings action to a workflow, map its 2 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.

Create Embeddings in Together AI — start free All 3 Together AI actions

Create Embeddings in Together AI — start free

Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

Field	Type	Required	Description
Embedding Model model	options	Required	Which embedding model to use
Text text	string	Required	Text to embed

Sample request

{
  "model": "{{trigger.model}}",
  "text": "{{trigger.text}}"
}

Returns

{
  "data": [
    {
      "index": 0,
      "embedding": [
        0.0123,
        -0.0456
      ]
    }
  ],
  "model": "BAAI/bge-large-en-v1.5",
  "usage": {
    "total_tokens": 5,
    "prompt_tokens": 5
  }
}

Use these fields in downstream nodes for routing, logging, or error handling.

Triggered by

Apps that pair well as the trigger for Create Embeddings.

Any of these apps can fire this action as part of a workflow.

Google Sheets → Together AI

2 Google Sheets triggers

HubSpot → Together AI

18 HubSpot triggers

FAQ

Questions about Create Embeddings.

What does the Create Embeddings action do in Together AI?

Generates vector embeddings using one of Together's open-weight embedding models (e.g. BGE, M2-BERT, UAE). Use for RAG, semantic search, or clustering pipelines.

What inputs does Create Embeddings require?

Required: Embedding Model, Text. Every input accepts a static value or a variable from any upstream node in your workflow.

Can I use dynamic inputs from earlier workflow nodes?

Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.

What happens if Together AI returns an error?

The run history shows the failed step with its input and the error message Together AI returned, so you can fix the input and run the workflow again. Automatic retries are built into HTTP steps only, where you can also set your own retry count and delay.

Does Create Embeddings support batch operations?

Run Create Embeddings inside a loop to process each item in an array. TinyCommand does not throttle calls for you, so for large arrays add a Delay step if you need to stay within Together AI's rate limits.

More actions

Other Together AI actions.

Action

Chat Completion

Runs an open-weight chat model (Llama 4, DeepSeek-V3, Qwen, Mixtral, etc.) on Together AI's fast inference platform. OpenAI-compatible request shape so existing chat-completion code mostly works as is.

Action

List Models

Lists models available on Together AI with their type (chat, language, embeddings, image) and pricing tier. Useful for surfacing a dynamic model picker.

Create Embeddings in Together AI — start free