Configuration

Riffer uses a centralized configuration system for provider credentials and settings.

Global Configuration

Use Riffer.configure to set up provider credentials:

Riffer.configure do |config|
  config.openai.api_key = ENV['OPENAI_API_KEY']
  config.amazon_bedrock.region = 'us-east-1'
  config.amazon_bedrock.api_token = ENV['BEDROCK_API_TOKEN']
  config.anthropic.api_key = ENV['ANTHROPIC_API_KEY']
end

Accessing Configuration

Access the current configuration via Riffer.config:

Riffer.config.openai.api_key
# => "sk-..."

Riffer.config.amazon_bedrock.region
# => "us-east-1"

Riffer.config.anthropic.api_key
# => "sk-ant-..."

Provider-Specific Configuration

OpenAI

Option Description
api_key Your OpenAI API key 
Riffer.configure do |config|
  config.openai.api_key = ENV['OPENAI_API_KEY']
end

Amazon Bedrock

Option Description
region AWS region (e.g., us-east-1)
api_token Optional bearer token for API authentication 
Riffer.configure do |config|
  config.amazon_bedrock.region = 'us-east-1'
  config.amazon_bedrock.api_token = ENV['BEDROCK_API_TOKEN']  # Optional
end

When api_token is not set, the provider uses standard AWS IAM authentication.

Anthropic

Option Description
api_key Your Anthropic API key 
Riffer.configure do |config|
  config.anthropic.api_key = ENV['ANTHROPIC_API_KEY']
end

Agent-Level Configuration

Override global configuration at the agent level:

provider_options

Pass options directly to the provider client:

class MyAgent < Riffer::Agent
  model 'openai/gpt-4o'

  # Override API key for this agent only
  provider_options api_key: ENV['CUSTOM_OPENAI_KEY']
end

model_options

Pass options to each LLM request:

class MyAgent < Riffer::Agent
  model 'openai/gpt-4o'

  # These options are sent with every generate/stream call
  model_options temperature: 0.7, reasoning: 'medium'
end

Common Model Options

OpenAI

Option Description
temperature Sampling temperature (0.0-2.0)
max_tokens Maximum tokens in response
top_p Nucleus sampling parameter
reasoning Reasoning effort level (low, medium, high)
web_search Enable web search (true or config hash) 
class MyAgent < Riffer::Agent
  model 'openai/gpt-4o'
  model_options temperature: 0.7, reasoning: 'medium'
end

Amazon Bedrock

Options are passed through to the Bedrock Converse API.

Option Description
inference_config Hash with max_tokens, temperature, top_p, stop_sequences
additional_model_request_fields Hash for model-specific params (e.g., top_k for Claude) 
class MyAgent < Riffer::Agent
  model 'amazon_bedrock/anthropic.claude-3-sonnet-20240229-v1:0'
  model_options inference_config: {temperature: 0.7, max_tokens: 4096}
end

Anthropic

Option Description
temperature Sampling temperature
max_tokens Maximum tokens in response
top_p Nucleus sampling parameter
top_k Top-k sampling parameter
thinking Extended thinking config hash (Claude 3.7+)
web_search Enable web search (true or config hash) 
class MyAgent < Riffer::Agent
  model 'anthropic/claude-3-5-sonnet-20241022'
  model_options temperature: 0.7, max_tokens: 4096
end

# With extended thinking (Claude 3.7+)
class ReasoningAgent < Riffer::Agent
  model 'anthropic/claude-3-7-sonnet-20250219'
  model_options thinking: {type: "enabled", budget_tokens: 10000}
end

Environment Variables

Recommended pattern for managing credentials:

# config/initializers/riffer.rb (Rails)
# or at application startup

Riffer.configure do |config|
  config.openai.api_key = ENV.fetch('OPENAI_API_KEY') { raise 'OPENAI_API_KEY not set' }

  if ENV['BEDROCK_REGION']
    config.amazon_bedrock.region = ENV['BEDROCK_REGION']
    config.amazon_bedrock.api_token = ENV['BEDROCK_API_TOKEN']
  end
end

Multiple Configurations

For different environments or use cases, use agent-level overrides:

class ProductionAgent < Riffer::Agent
  model 'openai/gpt-4o'
  provider_options api_key: ENV['PRODUCTION_OPENAI_KEY']
end

class DevelopmentAgent < Riffer::Agent
  model 'openai/gpt-4o-mini'
  provider_options api_key: ENV['DEV_OPENAI_KEY']
  model_options temperature: 0.0  # Deterministic for testing
end