---
title: "Embeddings - `/embeddings`"
description: "import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/embedding
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:24:10.649Z
license: CC-BY-4.0
attribution: "Embeddings - `/embeddings` — Claudary (https://claudary.paisolsolutions.com/skills/embedding)"
---

# Embeddings - `/embeddings`
import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

## Overview

import Image from '@theme/IdealImage';
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

# Embeddings - `/embeddings`

See supported Embedding Providers & Models [here](https://docs.litellm.ai/docs/embedding/supported_embedding)

## Supported Input Formats

The `/v1/embeddings` endpoint follows the [OpenAI embeddings API specification](https://platform.openai.com/docs/api-reference/embeddings/create). The following input formats are supported:

| Format | Example |
|--------|---------|
| String | `"input": "Hello"` |
| Array of strings | `"input": ["Hello", "World"]` |
| Array of tokens (integers) | `"input": [1234, 5678, 9012]` |
| Array of token arrays | `"input": [[1234, 5678], [9012, 3456]]` |

## Quick start
Here's how to route between GPT-J embedding (sagemaker endpoint), Amazon Titan embedding (Bedrock) and Azure OpenAI embedding on the proxy server: 

1. Set models in your config.yaml
```yaml
model_list:
  - model_name: sagemaker-embeddings
    litellm_params: 
      model: "sagemaker/berri-benchmarking-gpt-j-6b-fp16"
  - model_name: amazon-embeddings
    litellm_params:
      model: "bedrock/amazon.titan-embed-text-v1"
  - model_name: azure-embeddings
    litellm_params: 
      model: "azure/azure-embedding-model"
      api_base: "os.environ/AZURE_API_BASE" # os.getenv("AZURE_API_BASE")
      api_key: "os.environ/AZURE_API_KEY" # os.getenv("AZURE_API_KEY")
      api_version: "2023-07-01-preview"

general_settings:
  master_key: sk-1234 # [OPTIONAL] if set all calls to proxy will require either this key or a valid generated token
```

2. Start the proxy
```shell
$ litellm --config /path/to/config.yaml
```

3. Test the embedding call

```shell
curl --location 'http://0.0.0.0:4000/v1/embeddings' \\
--header 'Authorization: Bearer sk-1234' \\
--header 'Content-Type: application/json' \\
--data '{
    "input": "The food was delicious and the waiter..",
    "model": "sagemaker-embeddings",
}'
```

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/embedding) · https://claudary.paisolsolutions.com