AWS Bedrock Embeddings

Generate embeddings using Amazon Bedrock

Overview

Amazon Bedrock provides access to embedding models from Amazon Titan, Cohere, and other providers through AWS infrastructure.

Quick Start

from praisonaiagents import embedding

result = embedding(
    input="Hello world",
    model="bedrock/amazon.titan-embed-text-v1"
)
print(f"Dimensions: {len(result.embeddings[0])}")

CLI Usage

praisonai embed "Hello world" --model bedrock/amazon.titan-embed-text-v1

Setup

export AWS_ACCESS_KEY_ID="your-access-key"
export AWS_SECRET_ACCESS_KEY="your-secret-key"
export AWS_REGION_NAME="us-east-1"

Available Models

Model	Dimensions	Provider
bedrock/amazon.titan-embed-text-v1	1536	Amazon
bedrock/amazon.titan-embed-text-v2:0	1024	Amazon
bedrock/amazon.nova-2-multimodal-embeddings-v1:0	1024	Amazon
bedrock/cohere.embed-english-v3	1024	Cohere
bedrock/cohere.embed-multilingual-v3	1024	Cohere
bedrock/cohere.embed-v4:0	1024	Cohere

With AWS Profile

from praisonaiagents import embedding
import os

os.environ["AWS_PROFILE"] = "my-profile"

result = embedding(
    input="Hello world",
    model="bedrock/amazon.titan-embed-text-v1"
)

Batch Embeddings

from praisonaiagents import embedding

texts = ["Document 1", "Document 2", "Document 3"]
result = embedding(
    input=texts,
    model="bedrock/amazon.titan-embed-text-v1"
)
print(f"Generated {len(result.embeddings)} embeddings")

Cross-Region Usage

from praisonaiagents import embedding

result = embedding(
    input="Hello world",
    model="bedrock/amazon.titan-embed-text-v1",
    aws_region_name="eu-west-1"
)

Related

• Embedding Providers Overview
• Vertex AI Embeddings