> ## Documentation Index
> Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Embedding Providers

> Generate text embeddings using 35+ providers through PraisonAI

## Overview

PraisonAI supports **35+ embedding providers** through LiteLLM integration, giving you access to hundreds of embedding models with a unified API.

## Quick Start

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import embedding

# OpenAI (default)
result = embedding("Hello world", model="text-embedding-3-small")

# Cohere
result = embedding("Hello world", model="cohere/embed-english-v3.0")

# Voyage AI
result = embedding("Hello world", model="voyage/voyage-3")

# Azure OpenAI
result = embedding("Hello world", model="azure/text-embedding-ada-002")

print(f"Dimensions: {len(result.embeddings[0])}")
```

## CLI Usage

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# OpenAI
praisonai embed "Hello world" --model text-embedding-3-small

# Cohere
praisonai embed "Hello world" --model cohere/embed-english-v3.0

# Any provider
praisonai embedding "Hello world" --model voyage/voyage-3
```

## Supported Providers

### Tier 1: Major Cloud Providers

| Provider                                                 | Prefix            | Example Model                        | Docs                                      |
| -------------------------------------------------------- | ----------------- | ------------------------------------ | ----------------------------------------- |
| [OpenAI](/docs/embeddings/providers/openai)              | `openai/` or none | `text-embedding-3-small`             | [→](/docs/embeddings/providers/openai)    |
| [Azure OpenAI](/docs/embeddings/providers/azure)         | `azure/`          | `azure/text-embedding-ada-002`       | [→](/docs/embeddings/providers/azure)     |
| [Google Vertex AI](/docs/embeddings/providers/vertex-ai) | `vertex_ai/`      | `vertex_ai/textembedding-gecko`      | [→](/docs/embeddings/providers/vertex-ai) |
| [Google Gemini](/docs/embeddings/providers/gemini)       | `gemini/`         | `gemini/text-embedding-004`          | [→](/docs/embeddings/providers/gemini)    |
| [AWS Bedrock](/docs/embeddings/providers/bedrock)        | `bedrock/`        | `bedrock/amazon.titan-embed-text-v1` | [→](/docs/embeddings/providers/bedrock)   |
| [Azure AI](/docs/embeddings/providers/azure-ai)          | `azure_ai/`       | `azure_ai/Cohere-embed-v3-english`   | [→](/docs/embeddings/providers/azure-ai)  |

### Tier 2: Specialized Embedding Providers

| Provider                                       | Prefix     | Example Model                | Docs                                    |
| ---------------------------------------------- | ---------- | ---------------------------- | --------------------------------------- |
| [Cohere](/docs/embeddings/providers/cohere)    | `cohere/`  | `cohere/embed-english-v3.0`  | [→](/docs/embeddings/providers/cohere)  |
| [Voyage AI](/docs/embeddings/providers/voyage) | `voyage/`  | `voyage/voyage-3`            | [→](/docs/embeddings/providers/voyage)  |
| [Jina AI](/docs/embeddings/providers/jina-ai)  | `jina_ai/` | `jina_ai/jina-embeddings-v3` | [→](/docs/embeddings/providers/jina-ai) |
| [Mistral](/docs/embeddings/providers/mistral)  | `mistral/` | `mistral/mistral-embed`      | [→](/docs/embeddings/providers/mistral) |

### Tier 3: Open Source & Self-Hosted

| Provider                                              | Prefix         | Example Model                                 | Docs                                        |
| ----------------------------------------------------- | -------------- | --------------------------------------------- | ------------------------------------------- |
| [HuggingFace](/docs/embeddings/providers/huggingface) | `huggingface/` | `huggingface/BAAI/bge-large-en-v1.5`          | [→](/docs/embeddings/providers/huggingface) |
| [Ollama](/docs/embeddings/providers/ollama)           | `ollama/`      | `ollama/nomic-embed-text`                     | [→](/docs/embeddings/providers/ollama)      |
| [Infinity](/docs/embeddings/providers/infinity)       | `infinity/`    | `infinity/BAAI/bge-small-en-v1.5`             | [→](/docs/embeddings/providers/infinity)    |
| [vLLM](/docs/embeddings/providers/vllm)               | `hosted_vllm/` | `hosted_vllm/intfloat/e5-mistral-7b-instruct` | [→](/docs/embeddings/providers/vllm)        |
| [LM Studio](/docs/embeddings/providers/lm-studio)     | `lm_studio/`   | `lm_studio/nomic-embed-text`                  | [→](/docs/embeddings/providers/lm-studio)   |

### Tier 4: Additional Providers

| Provider                                                | Prefix          | Example Model                                           | Docs                                         |
| ------------------------------------------------------- | --------------- | ------------------------------------------------------- | -------------------------------------------- |
| [Together AI](/docs/embeddings/providers/together-ai)   | `together_ai/`  | `together_ai/togethercomputer/m2-bert-80M-8k-retrieval` | [→](/docs/embeddings/providers/together-ai)  |
| [Fireworks AI](/docs/embeddings/providers/fireworks-ai) | `fireworks_ai/` | `fireworks_ai/nomic-ai/nomic-embed-text-v1.5`           | [→](/docs/embeddings/providers/fireworks-ai) |
| [NVIDIA NIM](/docs/embeddings/providers/nvidia-nim)     | `nvidia_nim/`   | `nvidia_nim/NV-Embed-QA`                                | [→](/docs/embeddings/providers/nvidia-nim)   |
| [Databricks](/docs/embeddings/providers/databricks)     | `databricks/`   | `databricks/databricks-bge-large-en`                    | [→](/docs/embeddings/providers/databricks)   |
| [Snowflake](/docs/embeddings/providers/snowflake)       | `snowflake/`    | `snowflake/snowflake-arctic-embed-m`                    | [→](/docs/embeddings/providers/snowflake)    |
| [Watsonx](/docs/embeddings/providers/watsonx)           | `watsonx/`      | `watsonx/ibm/slate-125m-english-rtrvr`                  | [→](/docs/embeddings/providers/watsonx)      |
| [SambaNova](/docs/embeddings/providers/sambanova)       | `sambanova/`    | `sambanova/E5-mistral-7b-instruct`                      | [→](/docs/embeddings/providers/sambanova)    |
| [Nebius](/docs/embeddings/providers/nebius)             | `nebius/`       | `nebius/BAAI/bge-en-icl`                                | [→](/docs/embeddings/providers/nebius)       |
| [OVHcloud](/docs/embeddings/providers/ovhcloud)         | `ovhcloud/`     | `ovhcloud/multilingual-e5-base`                         | [→](/docs/embeddings/providers/ovhcloud)     |
| [Volcengine](/docs/embeddings/providers/volcengine)     | `volcengine/`   | `volcengine/doubao-embedding`                           | [→](/docs/embeddings/providers/volcengine)   |

## Model Selection Guide

### By Use Case

| Use Case            | Recommended Model                 | Dimensions |
| ------------------- | --------------------------------- | ---------- |
| **General Purpose** | `text-embedding-3-small`          | 1536       |
| **High Quality**    | `text-embedding-3-large`          | 3072       |
| **Multilingual**    | `cohere/embed-multilingual-v3.0`  | 1024       |
| **Code Search**     | `voyage/voyage-code-3`            | 1024       |
| **Cost Effective**  | `cohere/embed-english-light-v3.0` | 384        |
| **Self-Hosted**     | `ollama/nomic-embed-text`         | 768        |

### By Dimension Size

| Dimensions   | Models                                                                   |
| ------------ | ------------------------------------------------------------------------ |
| **256-512**  | `cohere/embed-english-light-v3.0`, `jina_ai/jina-embeddings-v2-small-en` |
| **768-1024** | `cohere/embed-english-v3.0`, `voyage/voyage-3`, `mistral/mistral-embed`  |
| **1536**     | `text-embedding-3-small`, `azure/text-embedding-ada-002`                 |
| **3072**     | `text-embedding-3-large`                                                 |

## Environment Variables

Each provider requires specific environment variables:

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# OpenAI
export OPENAI_API_KEY="sk-..."

# Azure OpenAI
export AZURE_API_KEY="..."
export AZURE_API_BASE="https://your-resource.openai.azure.com"

# Cohere
export COHERE_API_KEY="..."

# Voyage AI
export VOYAGE_API_KEY="..."

# Google
export GOOGLE_API_KEY="..."  # or GEMINI_API_KEY

# AWS Bedrock
export AWS_ACCESS_KEY_ID="..."
export AWS_SECRET_ACCESS_KEY="..."
export AWS_REGION_NAME="us-east-1"
```

## API Reference

### Parameters

| Parameter         | Type              | Default                  | Description                                    |
| ----------------- | ----------------- | ------------------------ | ---------------------------------------------- |
| `input`           | str or List\[str] | Required                 | Text(s) to embed                               |
| `model`           | str               | `text-embedding-3-small` | Model identifier with optional provider prefix |
| `dimensions`      | int               | None                     | Output dimensions (if supported)               |
| `encoding_format` | str               | `float`                  | `float` or `base64`                            |
| `timeout`         | float             | 600.0                    | Request timeout in seconds                     |
| `api_key`         | str               | None                     | API key override                               |
| `api_base`        | str               | None                     | API base URL override                          |

### Response

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
EmbeddingResult(
    embeddings=[[0.1, 0.2, ...]],  # List of embedding vectors
    model="text-embedding-3-small",
    usage={"prompt_tokens": 4, "total_tokens": 4}
)
```

## Related

* [Embeddings API](/docs/capabilities/embeddings) - Core embeddings documentation
* [Embeddings CLI](/docs/capabilities/embeddings-cli) - CLI commands
* [Vector Stores](/docs/databases/overview) - Store and query embeddings