fallback_models.yaml

#!/usr/bin/env docker agent run

# Example: Fallback Models for High Availability
#
# This configuration demonstrates how to set up fallback models for agents.
# The fallback system handles different error types:
#
# - Retryable errors (e.g. 5xx, timeouts): Retry the same model with exponential backoff + jitter
# - Non-retryable errors (e.g. 429 rate limit, 4xx client errors): Skip to next model immediately
#
# After a non-retryable error triggers a fallback, the runtime "sticks" with
# the successful fallback model for the cooldown duration before retrying the primary.
#
# Sensible defaults are included, most users only need to specify fallback models

agents:
  # Minimal fallback configuration - just specify models, defaults handle the rest
  root:
    model: anthropic/claude-sonnet-4-0
    fallback:
      models:
        - openai/gpt-4o
        - openai/gpt-5-mini
    description: A reliable assistant with automatic failover
    instruction: |
      You are a helpful assistant. Your responses should be clear and concise.
      You have built-in resilience - if one model provider is unavailable,
      the system will automatically try alternative providers.
    toolsets:
      - type: think

# You can also use named models from the models section as fallbacks
# models:
#   fast_backup:
#     provider: openai
#     model: gpt-5-mini

# Example with explicit configuration (for power users):
# agents:
#   root:
#     model: anthropic/claude-sonnet-4-0
#     fallback:
#       models:
#         - fast_backup
#         - google/gemini-2.5-flash
#       retries: 3       # More retries for flaky networks
#       cooldown: 5m     # Longer cooldown for persistent rate limits
#       # Use retries: -1 to disable retries (try each model only once)