promptfoo--promptfoo/examples/amazon-bedrock/models/promptfooconfig.inference-profiles.yaml

# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
description: 'AWS Bedrock Application Inference Profiles Example'

prompts:
  - 'Write a comprehensive analysis of {{topic}} in 3 paragraphs'
  - 'Create a creative story about {{topic}} with an unexpected twist'
  - |
    Answer the following question step by step:
    {{question}}

providers:
  # Application Inference Profiles - Multi-region, automatic failover
  # These require the inferenceModelType configuration parameter

  # Claude inference profile - optimized for high availability
  - id: bedrock:arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/claude-ha-profile
    label: 'Claude HA Profile'
    config:
      inferenceModelType: 'claude' # Required for inference profiles
      region: 'us-east-1'
      temperature: 0.7
      max_tokens: 1024
      anthropic_version: 'bedrock-2023-05-31'

  # Llama inference profile - latest version (defaults to Llama 4)
  - id: bedrock:arn:aws:bedrock:us-west-2:123456789012:application-inference-profile/llama-latest-profile
    label: 'Llama Latest Profile'
    config:
      inferenceModelType: 'llama' # Defaults to latest Llama version (v4)
      region: 'us-west-2'
      max_gen_len: 1024
      temperature: 0.7
      top_p: 0.9

  # Llama 3.3 specific inference profile
  - id: bedrock:arn:aws:bedrock:us-west-2:123456789012:application-inference-profile/llama33-profile
    label: 'Llama 3.3 Profile'
    config:
      inferenceModelType: 'llama3.3' # Specific Llama 3.3 version
      region: 'us-west-2'
      max_gen_len: 1024
      temperature: 0.6

  # Nova inference profile - cost optimized
  - id: bedrock:arn:aws:bedrock:eu-west-1:123456789012:application-inference-profile/nova-cost-optimized
    label: 'Nova Cost-Optimized Profile'
    config:
      inferenceModelType: 'nova'
      region: 'eu-west-1'
      interfaceConfig:
        max_new_tokens: 1024
        temperature: 0.7
        top_p: 0.95
        top_k: 50

  # Mistral inference profile
  - id: bedrock:arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/mistral-profile
    label: 'Mistral Profile'
    config:
      inferenceModelType: 'mistral'
      region: 'us-east-1'
      max_tokens: 1024
      temperature: 0.7
      top_p: 0.9

  # DeepSeek inference profile with thinking capability
  - id: bedrock:arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/deepseek-reasoning
    label: 'DeepSeek Reasoning Profile'
    config:
      inferenceModelType: 'deepseek'
      region: 'us-east-1'
      max_tokens: 2048
      temperature: 0.5
      showThinking: true # Include thinking process in output

  # OpenAI models via Bedrock inference profile
  - id: bedrock:arn:aws:bedrock:us-west-2:123456789012:application-inference-profile/openai-gpt-profile
    label: 'OpenAI GPT Profile'
    config:
      inferenceModelType: 'openai'
      region: 'us-west-2'
      max_completion_tokens: 1024
      temperature: 0.7
      reasoning_effort: 'medium' # Control reasoning depth

  # Comparison with direct model IDs (no inference profile)
  - id: bedrock:us.anthropic.claude-sonnet-4-6
    label: 'Claude Direct (No Profile)'
    config:
      region: 'us-east-1'
      temperature: 0.7
      max_tokens: 1024

tests:
  - vars:
      topic: 'artificial intelligence in healthcare'
      question: 'How do neural networks learn from data?'

  - vars:
      topic: 'climate change and renewable energy'
      question: 'What are the main differences between supervised and unsupervised learning?'

  - vars:
      topic: 'the future of space exploration'
      question: 'Explain quantum computing to a 10-year-old'

  # Test with custom grading using an inference profile
  - vars:
      topic: 'blockchain technology'
      question: 'How does encryption work in modern communications?'
    options:
      # Use an inference profile for grading assertions
      provider:
        id: bedrock:arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/grading-profile
        config:
          inferenceModelType: 'claude'
          temperature: 0 # Low temperature for consistent grading
          max_tokens: 512
    assert:
      - type: llm-rubric
        value: 'The response should be comprehensive, technically accurate, and well-structured'
      - type: contains
        value: 'technology'
      - type: min-length
        value: 200

# Default grading configuration using an inference profile
defaultTest:
  options:
    provider:
      id: bedrock:arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/default-grading
      config:
        inferenceModelType: 'claude'
        region: 'us-east-1'
        temperature: 0
        max_tokens: 256
  assert:
    - type: cost
      threshold: 0.002 # Maximum cost per test
    - type: latency
      threshold: 10000 # Maximum 10 seconds
    - type: not-contains
      value: 'I cannot'
    - type: not-contains
      value: 'As an AI'