llama-index-embeddings-bedrock

LlamaIndex Embeddings Integration: Bedrock

This integration provides support for AWS Bedrock embedding models through LlamaIndex.

Installation

pip install llama-index-embeddings-bedrock

Usage

from llama_index.embeddings.bedrock import BedrockEmbedding

# Initialize the embedding model
embed_model = BedrockEmbedding(
    model_name="cohere.embed-english-v3",
    region_name="us-east-1",
)

# Get a single embedding
embedding = embed_model.get_text_embedding("Hello world")

# Get batch embeddings
embeddings = embed_model.get_text_embedding_batch(["Hello", "World"])

Supported Models

Amazon Titan

• amazon.titan-embed-text-v1
• amazon.titan-embed-text-v2:0
• amazon.titan-embed-g1-text-02

Cohere

• cohere.embed-english-v3
• cohere.embed-multilingual-v3
• cohere.embed-v4:0 (multimodal, supports text and images)

To list all supported models:

from llama_index.embeddings.bedrock import BedrockEmbedding

supported_models = BedrockEmbedding.list_supported_models()
print(supported_models)

Configuration

You can configure AWS credentials in several ways:

# Option 1: Pass credentials directly
embed_model = BedrockEmbedding(
    model_name="cohere.embed-english-v3",
    aws_access_key_id="YOUR_ACCESS_KEY",
    aws_secret_access_key="YOUR_SECRET_KEY",
    region_name="us-east-1",
)

# Option 2: Use AWS profile
embed_model = BedrockEmbedding(
    model_name="cohere.embed-english-v3",
    profile_name="your-aws-profile",
    region_name="us-east-1",
)

# Option 3: Use environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION)
embed_model = BedrockEmbedding(
    model_name="cohere.embed-english-v3",
)

Cohere v4 Support

This integration supports both Cohere v3 and v4 embedding models, including the new multimodal cohere.embed-v4:0 model. The integration automatically detects and handles different response formats (v3 and v4), maintaining full backward compatibility.

# Using Cohere v4 model
embed_model = BedrockEmbedding(
    model_name="cohere.embed-v4:0",
    region_name="us-east-1",
)

# Text embeddings work seamlessly
embeddings = embed_model.get_text_embedding_batch(
    ["Hello world", "Another document"]
)

Note: Cohere v4 introduces a new response format that wraps embeddings in a float key when multiple embedding types are requested. This integration handles both the v3 format ({"embeddings": [[...]]}) and v4 formats ({"embeddings": {"float": [[...]]}} or {"float": [[...]]}) automatically.

Examples

For more examples, see the Bedrock Embeddings notebook.