Noveum AI Gateway

🚀 The world's fastest AI Gateway proxy, written in Rust and optimized for maximum performance. This high-performance API gateway routes requests to various AI providers (OpenAI, Anthropic, GROQ, Fireworks, Together, AWS Bedrock) with streaming support, making it perfect for developers who need reliable and blazing-fast AI API access.

Quick Start • Documentation • Monitoring • Docker • Contributing

✨ Features

🚀 Blazing fast performance: Built in Rust with zero-cost abstractions
⚡ Optimized for low latency and high throughput
🔄 Unified API interface for multiple AI providers:
- OpenAI
- AWS Bedrock
- Anthropic
- GROQ
- Fireworks
- Together AI
📡 Real-time Streaming: Optimized for minimal latency
🛡️ Production Ready: Battle-tested in high-load environments
🔍 Health Checking: Built-in monitoring
📊 Telemetry & Metrics: Supports Elasticsearch integration with periodic status logs for operational insights
🌐 CORS Support: Configurable cross-origin resource sharing
🛠️ SDK Compatibility: Works with any OpenAI-compatible SDK

🚀 Quick Start

Installation

You can install Noveum Gateway using one of these methods:

One Line Install & Run (With Cargo Install)

curl https://sh.rustup.rs -sSf | sh && cargo install noveum-ai-gateway && noveum-ai-gateway

Using Cargo Install

cargo install noveum-ai-gateway

After installation, you can start the gateway by running:

noveum-ai-gateway

Building from Source

Clone the repository:

git clone https://github.com/noveum/ai-gateway
cd ai-gateway

Build the project:

cargo build --release

Run the server:

cargo run --release

The server will start on http://127.0.0.1:3000 by default.

Running the Gateway

You can configure the gateway using environment variables:

# Basic configuration
export RUST_LOG=info

# Start the gateway
noveum-ai-gateway

# Or with custom port
PORT=8080 noveum-ai-gateway

📚 Usage Examples

Making Requests

To make requests through the gateway, use the /v1/* endpoint and specify the provider using the x-provider header.

Example: AWS Bedrock Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: bedrock" \
  -H "x-aws-access-key-id: YOUR_ACCESS_KEY" \
  -H "x-aws-secret-access-key: YOUR_SECRET_KEY" \
  -H "x-aws-region: us-east-1" \
  -d '{
    "model": "anthropic.claude-3-sonnet-20240229-v1:0",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Example: OpenAI Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: openai" \
  -H "Authorization: Bearer your-openai-api-key" \
  -d '{
    "model": "gpt-4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Example: GROQ Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: groq" \
  -H "Authorization: Bearer your-groq-api-key" \
  -d '{
    "model": "llama2-70b-4096",
    "messages": [{"role": "user", "content": "Hello!"}],
    "stream": true,
    "max_tokens": 300
  }'

Example: Anthropic Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: anthropic" \
  -H "Authorization: Bearer your-anthropic-api-key" \
  -d '{
    "model": "claude-3-5-sonnet-20241022",
    "messages": [{"role": "user", "content": "Write a poem"}],
    "stream": true,
    "max_tokens": 1024
  }'

Example: Fireworks Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: fireworks" \
  -H "Authorization: Bearer your-fireworks-api-key" \
  -d '{
    "model": "accounts/fireworks/models/llama-v3p1-8b-instruct",
    "messages": [{"role": "user", "content": "Write a poem"}],
    "stream": true,
    "max_tokens": 300,
    "temperature": 0.6,
    "top_p": 1,
    "top_k": 40
  }'

Example: Together AI Request

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: together" \
  -H "Authorization: Bearer your-together-api-key" \
  -d '{
    "model": "meta-llama/Llama-2-7b-chat-hf",
    "messages": [{"role": "user", "content": "Write a poem"}],
    "stream": true,
    "max_tokens": 512,
    "temperature": 0.7,
    "top_p": 0.7,
    "top_k": 50,
    "repetition_penalty": 1
  }'

SDK Compatibility

The Noveum AI Gateway is designed to work seamlessly with popular AI SDKs. You can use the official OpenAI SDK to interact with any supported provider by simply configuring the baseURL and adding the appropriate provider header.

Using with OpenAI's Official Node.js SDK

import OpenAI from 'openai';

// Configure the SDK to use Noveum Gateway
const openai = new OpenAI({
  apiKey: process.env.PROVIDER_API_KEY, // Use any provider's API key
  baseURL: "http://localhost:3000/v1/", // Point to the gateway
  defaultHeaders: {
    "x-provider": "groq", // Specify the provider you want to use
  },
});

// Make requests as usual
const chatCompletion = await openai.chat.completions.create({
  messages: [
    { role: "system", content: "Write a poem" },
    { role: "user", content: "" }
  ],
  model: "llama-3.1-8b-instant",
  temperature: 1,
  max_tokens: 100,
  top_p: 1,
  stream: false,
});

You can easily switch between providers by changing the x-provider header and API key:

// For OpenAI
const openaiClient = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: { "x-provider": "openai" },
});

// For AWS Bedrock
const bedrockClient = new OpenAI({
  apiKey: process.env.AWS_ACCESS_KEY_ID, // Use AWS access key
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: {
    "x-provider": "bedrock",
    "x-aws-access-key-id": process.env.AWS_ACCESS_KEY_ID,
    "x-aws-secret-access-key": process.env.AWS_SECRET_ACCESS_KEY,
    "x-aws-region": process.env.AWS_REGION || "us-east-1"
  },
});

// For Anthropic
const anthropicClient = new OpenAI({
  apiKey: process.env.ANTHROPIC_API_KEY,
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: { "x-provider": "anthropic" },
});

// For GROQ
const groqClient = new OpenAI({
  apiKey: process.env.GROQ_API_KEY,
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: { "x-provider": "groq" },
});

// For Fireworks
const fireworksClient = new OpenAI({
  apiKey: process.env.FIREWORKS_API_KEY,
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: { "x-provider": "fireworks" },
});

// For Together AI
const togetherClient = new OpenAI({
  apiKey: process.env.TOGETHER_API_KEY,
  baseURL: "http://localhost:3000/v1/",
  defaultHeaders: { "x-provider": "together" },
});

The gateway automatically handles the necessary transformations to ensure compatibility with each provider's API format while maintaining the familiar OpenAI SDK interface.

Testing Gateway URL

https://gateway.noveum.ai

Send Example Request to Testing Gateway

curl --location 'https://gateway.noveum.ai/v1/chat/completions' \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --header 'x-provider: groq' \
  --data '{
    "model": "llama-3.1-8b-instant",
    "messages": [
        {
            "role": "user",
            "content": "Write a poem"
        }
    ],
    "stream": true,
    "max_tokens": 300
}'

Note: This deployment is provided for testing and evaluation purposes only. For production workloads, please deploy your own instance of the gateway or contact us for information about production-ready managed solutions.

🔧 Configuration

The gateway can be configured using environment variables:

RUST_LOG=debug # Logging level (debug, info, warn, error)

🏗️ Architecture

The gateway leverages the best-in-class Rust ecosystem:

Axum - High-performance web framework
Tokio - Industry-standard async runtime
Tower-HTTP - Robust HTTP middleware
Reqwest - Fast and reliable HTTP client
Tracing - Zero-overhead logging and diagnostics

📈 Performance

Noveum Developer AI Gateway is designed for maximum performance:

Zero-cost abstractions using Rust's ownership model
Asynchronous I/O with Tokio for optimal resource utilization
Connection pooling via Reqwest for efficient HTTP connections
Memory-efficient request/response proxying
Minimal overhead in the request path
Optimized streaming response handling

🔒 Security Notes

Always run behind a reverse proxy in production
Configure CORS appropriately for your use case
Use environment variables for sensitive configuration
Consider adding rate limiting for production use

🤝 Contributing

We welcome contributions! Please see our CONTRIBUTING.md for guidelines.

🛠️ Development Setup

# Install development dependencies
cargo install cargo-watch

# Run tests
cargo test

# Run with hot reload
cargo watch -x run

Troubleshooting

Common Issues

Connection Refused
- Check if port 3000 is available
- Verify the HOST and PORT settings
Streaming Not Working
- Ensure Accept: text/event-stream header is set
- Check client supports streaming
- Verify provider supports streaming for the requested endpoint
Provider Errors
- Verify provider API keys are correct
- Check provider-specific headers are properly set
- Ensure the provider endpoint exists and is correctly formatted

💬 Community

🙏 Acknowledgments

Special thanks to all contributors and the Rust community.

📄 License

This project is dual-licensed under both the MIT License and the Apache License (Version 2.0). You may choose either license at your option. See the LICENSE-MIT and LICENSE-APACHE files for details.

Docker Support

Building and Running with Docker

Build the Docker image:

docker buildx build --platform linux/amd64 -t noveum/noveum-ai-gateway:latest . --load

Push the image to Docker Hub:

docker push noveum/noveum-ai-gateway:latest

Run the container:

docker run -p 3000:3000 \
  -e RUST_LOG=info \
  noveum/noveum-ai-gateway:latest

Using Pre-built Docker Image

docker pull noveum/noveum-ai-gateway:latest
docker run -p 3000:3000 \
  -e RUST_LOG=info \
  noveum/noveum-ai-gateway:latest

Using Pre-built Docker Image with Elasticsearch

docker pull noveum/noveum-ai-gateway:latest  --platform linux/amd64
docker run --platform linux/amd64 -p 3000:3000 \
  -e RUST_LOG=info \
  -e ENABLE_ELASTICSEARCH=true \
  -e ELASTICSEARCH_URL=http://localhost:9200 \
  -e ELASTICSEARCH_USERNAME=elastic \
  -e ELASTICSEARCH_PASSWORD=your_secure_password \
  -e ELASTICSEARCH_INDEX=ai-gateway-metrics \
  noveum/noveum-ai-gateway:latest

Note: When running with Elasticsearch, make sure your Elasticsearch instance is accessible from the Docker container. If running Elasticsearch locally, you may need to use host.docker.internal instead of localhost in the URL.

Docker Compose

For detailed deployment instructions, please refer to the Deployment Guide.

Option 1: Build from Source

Create a docker-compose.yml file:

version: '3.8'
services:
  gateway:
    build: .
    platform: linux/amd64
    ports:
      - "3000:3000"
    environment:
      - RUST_LOG=info
    restart: unless-stopped

Option 2: Use Prebuilt Image

Create a docker-compose.yml file:

version: '3.8'
services:
  gateway:
    image: noveum/noveum-ai-gateway:latest
    platform: linux/amd64
    ports:
      - "3000:3000"
    environment:
      - RUST_LOG=info
    restart: unless-stopped

Then run either option with:

docker-compose up -d

Option 3: Use Prebuilt Image with Elasticsearch

Create a docker-compose.yml file with Elasticsearch integration:

version: '3.8'
services:
  gateway:
    image: noveum/noveum-ai-gateway:latest
    platform: linux/amd64
    ports:
      - "3000:3000"
    environment:
      - RUST_LOG=info
      - ENABLE_ELASTICSEARCH=true
      - ELASTICSEARCH_URL=http://elasticsearch:9200
      - ELASTICSEARCH_USERNAME=elastic
      - ELASTICSEARCH_PASSWORD=your_secure_password
      - ELASTICSEARCH_INDEX=ai-gateway-metrics
    restart: unless-stopped
    depends_on:
      - elasticsearch

  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=true
      - "ELASTIC_PASSWORD=your_secure_password"
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ports:
      - "9200:9200"
    volumes:
      - es_data:/usr/share/elasticsearch/data

  kibana:
    image: docker.elastic.co/kibana/kibana:8.12.0
    environment:
      - ELASTICSEARCH_HOSTS=http://elasticsearch:9200
      - ELASTICSEARCH_USERNAME=elastic
      - ELASTICSEARCH_PASSWORD=your_secure_password
    ports:
      - "5601:5601"
    depends_on:
      - elasticsearch

volumes:
  es_data:

Then run with:

docker-compose up -d

Release Process for noveum-ai-gateway

1. Pre-release Checklist

Update version number in Cargo.toml
Update CHANGELOG.md (if you have one)
Ensure all tests pass: cargo test
Verify the crate builds locally: cargo build --release
Run cargo clippy to check for any linting issues
Run cargo fmt to ensure consistent formatting

2. Git Commands

# Create and switch to a release branch
git checkout -b release/v0.1.6

# Stage and commit changes
git add Cargo.toml CHANGELOG.md
git commit -m "chore: release v0.1.6"

# Create a git tag
git tag -a v0.1.7 -m "Release v0.1.7"

# Push changes and tag
git push origin release/v0.1.7
git push origin v0.1.7

3. Publishing to crates.io

# Verify the package contents
cargo package

# Publish to crates.io (requires authentication)
cargo publish

4. Post-release

Create a GitHub release (if using GitHub)
- Go to Releases → Draft a new release
- Choose the tag v0.1.7
- Add release notes
- Publish release
Merge the release branch back to main

git checkout main
git merge release/v0.1.7
git push origin main

5. Version Verification

After publishing, verify:

The new version appears on crates.io
Documentation is updated on docs.rs
The GitHub release is visible (if using GitHub)

Testing Deployment

Noveum provides a testing deployment of the AI Gateway, hosted in our London data centre. This deployment is intended for testing and evaluation purposes only, and should not be used for production workloads.

📊 OpenTelemetry Logging

Noveum AI Gateway now supports OpenTelemetry compatible logs for enhanced observability. The Gateway can export detailed request logs with a rich structured format that includes complete request/response details and performance metrics.

Tracking Headers

You can add custom tracking information to your requests that will be included in the logs:

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-provider: openai" \
  -H "Authorization: Bearer your-openai-api-key" \
  -H "x-project-id: your-project-id" \
  -H "x-organisation-id: your-org-id" \
  -H "x-user-id: your-user-id" \
  -d '{
    "model": "gpt-4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

These headers will be included in the telemetry logs, allowing you to:

Track usage by project
Monitor costs per organization
Analyze performance by user
Segment analytics by experiment

For more details, see the Elasticsearch Integration Guide and Telemetry Plugins Guide.

Testing

Noveum Gateway includes comprehensive integration tests for all supported providers (OpenAI, Anthropic, GROQ, Fireworks, Together AI, and AWS Bedrock). These tests validate both non-streaming and streaming functionality.

Running Integration Tests

Set up your test environment:

# Copy the sample test environment file
cp tests/.env.test.example .env.test

# Edit the file to add your API keys for the providers you want to test
nano .env.test

Start the gateway with ElasticSearch enabled:
```
ENABLE_ELASTICSEARCH=true cargo run
```

Run the integration tests:

# Run all tests
cargo test --test run_integration_tests -- --nocapture

# Run tests for specific providers
cargo test --test run_integration_tests openai -- --nocapture
cargo test --test run_integration_tests anthropic -- --nocapture
cargo test --test run_integration_tests groq -- --nocapture
cargo test --test run_integration_tests fireworks -- --nocapture
cargo test --test run_integration_tests together -- --nocapture
cargo test --test run_integration_tests bedrock -- --nocapture

Test Environment Configuration

Your .env.test file should include the following variables:

# Gateway URL (default: http://localhost:3000)
GATEWAY_URL=http://localhost:3000

# ElasticSearch Configuration (required for tests)
ELASTICSEARCH_URL=http://localhost:9200
ELASTICSEARCH_USERNAME=elastic
ELASTICSEARCH_PASSWORD=your_elasticsearch_password
ELASTICSEARCH_INDEX=ai-gateway-metrics

# Provider API Keys - Add keys for the providers you want to test
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GROQ_API_KEY=your_groq_api_key
FIREWORKS_API_KEY=your_fireworks_api_key
TOGETHER_API_KEY=your_together_api_key

# AWS Bedrock Credentials
AWS_ACCESS_KEY_ID=your_aws_access_key_id
AWS_SECRET_ACCESS_KEY=your_aws_secret_access_key
AWS_REGION=us-east-1

For detailed test documentation, please refer to the Integration Tests README.

Name		Name	Last commit message	Last commit date
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.github		.github
docs		docs
k8		k8
src		src
tests		tests
tmp		tmp
.cursorrules		.cursorrules
.dockerignore		.dockerignore
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
Cargo.toml		Cargo.toml
Dockerfile		Dockerfile
LICENSE-APACHE		LICENSE-APACHE
LICENSE-MIT		LICENSE-MIT
README.md		README.md

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