Docker

# Set your API key
export OPENAI_API_KEY=your-api-key

# Create config for OpenAI
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - backends:
      - ai:
          name: openai
          provider:
            openAI:
              model: gpt-4o-mini
      policies:
        backendAuth:
          key: $OPENAI_API_KEY
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e OPENAI_API_KEY=$OPENAI_API_KEY \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4o-mini","messages":[{"role":"user","content":"Hello!"}]}'

# Set your API key
export ANTHROPIC_API_KEY=your-api-key

# Create config for Anthropic
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - backends:
      - ai:
          name: anthropic
          provider:
            anthropic:
              model: claude-sonnet-4-20250514
      policies:
        backendAuth:
          key: $ANTHROPIC_API_KEY
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-sonnet-4-20250514","messages":[{"role":"user","content":"Hello!"}]}'

# Set your xAI API key
export XAI_API_KEY=your-api-key

# Create config for xAI
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - policies:
        urlRewrite:
          authority:
            full: api.x.ai
        backendTLS: {}
        backendAuth:
          key: $XAI_API_KEY
      backends:
      - ai:
          name: xai
          hostOverride: api.x.ai:443
          provider:
            openAI:
              model: grok-2-latest
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e XAI_API_KEY=$XAI_API_KEY \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"grok-2-latest","messages":[{"role":"user","content":"Hello!"}]}'

# Start Ollama (if not already running)
ollama serve &

# Pull a model
ollama pull llama3.2

# Create config for Ollama
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - policies:
        urlRewrite:
          authority:
            full: host.docker.internal:11434
      backends:
      - ai:
          name: ollama
          hostOverride: host.docker.internal:11434
          provider:
            openAI:
              model: llama3.2
EOF

# Run Agent Gateway (use host.docker.internal to reach Ollama on the host)
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  --add-host=host.docker.internal:host-gateway \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"llama3.2","messages":[{"role":"user","content":"Hello!"}]}'

# Set your Azure OpenAI credentials
export AZURE_OPENAI_API_KEY=your-api-key
export AZURE_DEPLOYMENT=your-deployment-name
export AZURE_ENDPOINT=your-resource.openai.azure.com

# Create config for Azure OpenAI
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - policies:
        urlRewrite:
          authority:
            full: $AZURE_ENDPOINT
        backendTLS: {}
        backendAuth:
          apiKeyHeader:
            name: api-key
            key: $AZURE_OPENAI_API_KEY
      backends:
      - ai:
          name: azure-openai
          hostOverride: $AZURE_ENDPOINT:443
          provider:
            azureOpenAI:
              deployment: $AZURE_DEPLOYMENT
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e AZURE_OPENAI_API_KEY=$AZURE_OPENAI_API_KEY \
  -e AZURE_DEPLOYMENT=$AZURE_DEPLOYMENT \
  -e AZURE_ENDPOINT=$AZURE_ENDPOINT \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4o","messages":[{"role":"user","content":"Hello!"}]}'

# Set your AWS credentials
export AWS_ACCESS_KEY_ID=your-access-key
export AWS_SECRET_ACCESS_KEY=your-secret-key
export AWS_REGION=us-east-1

# Create config for Amazon Bedrock
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - backends:
      - ai:
          name: bedrock
          provider:
            bedrock:
              region: $AWS_REGION
              model: anthropic.claude-3-5-sonnet-20241022-v2:0
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
  -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
  -e AWS_REGION=$AWS_REGION \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"anthropic.claude-3-5-sonnet-20241022-v2:0","messages":[{"role":"user","content":"Hello!"}]}'

# Set your API key
export GEMINI_API_KEY=your-api-key

# Create config for Google Gemini
cat <<'EOF' > config.yaml
binds:
- port: 3000
  listeners:
  - routes:
    - backends:
      - ai:
          name: gemini
          provider:
            gemini:
              model: gemini-2.0-flash
      policies:
        backendAuth:
          key: $GEMINI_API_KEY
EOF

# Run Agent Gateway
docker run -v ./config.yaml:/config.yaml -p 3000:3000 \
  -e GEMINI_API_KEY=$GEMINI_API_KEY \
  cr.agentgateway.dev/agentgateway:0.11.1 -f /config.yaml

# Test with a chat completion
curl http://localhost:3000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-2.0-flash","messages":[{"role":"user","content":"Hello!"}]}'