embedrock 🪨

OpenAI-compatible embedding proxy for Amazon Bedrock. Drop-in replacement for any tool expecting /v1/embeddings.

Why?

Many AI tools (OpenClaw, LangChain, LlamaIndex, etc.) expect OpenAI's embedding API format. embedrock translates those calls to Amazon Bedrock, so you can use Titan, Cohere, and other Bedrock embedding models without changing your tools.

Zero API keys needed — uses your AWS credentials (instance profile, env vars, or shared config).

Supported Models

Model	ID	Dims	Notes
Titan Embed Text V2	amazon.titan-embed-text-v2:0	1024	Default
Titan Embed G1 Text	amazon.titan-embed-g1-text-02	1536
Cohere Embed English v3	cohere.embed-english-v3	1024
Cohere Embed Multilingual v3	cohere.embed-multilingual-v3	1024
Cohere Embed v4	cohere.embed-v4:0	1536	Latest, best quality

Model family is auto-detected by ID prefix. Titan and Cohere use different Bedrock request/response formats — embedrock handles this transparently.

Install

From releases:

# Linux arm64 (EC2 Graviton)
curl -fsSL https://github.com/inceptionstack/embedrock/releases/latest/download/embedrock-linux-arm64 -o /usr/local/bin/embedrock
chmod +x /usr/local/bin/embedrock

# Linux amd64
curl -fsSL https://github.com/inceptionstack/embedrock/releases/latest/download/embedrock-linux-amd64 -o /usr/local/bin/embedrock
chmod +x /usr/local/bin/embedrock

From source:

go install github.com/inceptionstack/embedrock/cmd/embedrock@latest

Usage

# Default: localhost:8089, us-east-1, Titan Embed v2
embedrock

# Cohere Embed v4 (recommended for best quality)
embedrock --model cohere.embed-v4:0

# Custom config
embedrock --port 9090 --region eu-west-1 --model cohere.embed-english-v3

# Flags
embedrock --help

API

Health check:

curl http://127.0.0.1:8089/
# {"status":"ok","model":"amazon.titan-embed-text-v2:0"}

Single embedding:

curl -X POST http://127.0.0.1:8089/v1/embeddings \
  -H "Content-Type: application/json" \
  -d '{"input": "Hello world", "model": "amazon.titan-embed-text-v2:0"}'

Batch embeddings:

curl -X POST http://127.0.0.1:8089/v1/embeddings \
  -H "Content-Type: application/json" \
  -d '{"input": ["First text", "Second text"], "model": "amazon.titan-embed-text-v2:0"}'

Run as a Service

sudo tee /etc/systemd/system/embedrock.service > /dev/null << 'EOF'
[Unit]
Description=embedrock - Bedrock embedding proxy
After=network.target

[Service]
Type=simple
User=ec2-user
ExecStart=/usr/local/bin/embedrock --port 8089 --region us-east-1 --model cohere.embed-v4:0
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl daemon-reload
sudo systemctl enable embedrock
sudo systemctl start embedrock

OpenClaw Configuration

"memorySearch": {
  "enabled": true,
  "provider": "openai",
  "remote": {
    "baseUrl": "http://127.0.0.1:8089/v1/",
    "apiKey": "not-needed"
  },
  "model": "cohere.embed-v4:0",
  "query": {
    "hybrid": { "enabled": true, "vectorWeight": 0.7, "textWeight": 0.3 }
  }
}

Prerequisites

• AWS credentials with bedrock:InvokeModel permission
• Bedrock model access enabled for your chosen embedding model

Development

# Run tests
go test ./... -v

# Build
go build ./cmd/embedrock/

# Build with version info
go build -ldflags "-X main.version=v0.2.0" ./cmd/embedrock/

Architecture

See ARCHITECTURE.md for design details.

License

MIT