plano/docs/source/resources/includes/plano_config_full_reference.yaml

# Plano Gateway configuration version
version: v0.3.0

# External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
agents:
  - id: weather_agent # Example agent for weather
    url: http://localhost:10510

  - id: flight_agent # Example agent for flights
    url: http://localhost:10520

# MCP filters applied to requests/responses (e.g., input validation, query rewriting)
filters:
  - id: input_guards # Example filter for input validation
    url: http://localhost:10500
    # type: mcp (default)
    # transport: streamable-http (default)
    # tool: input_guards (default - same as filter id)

# LLM provider configurations with API keys and model routing
model_providers:
  - model: openai/gpt-4o
    access_key: $OPENAI_API_KEY
    default: true

  - model: openai/gpt-4o-mini
    access_key: $OPENAI_API_KEY

  - model: anthropic/claude-sonnet-4-0
    access_key: $ANTHROPIC_API_KEY

  - model: mistral/ministral-3b-latest
    access_key: $MISTRAL_API_KEY

  # Example: Passthrough authentication for LiteLLM or similar proxies
  # When passthrough_auth is true, client's Authorization header is forwarded
  # instead of using the configured access_key
  - model: openai/gpt-4o-litellm
    base_url: https://litellm.example.com
    passthrough_auth: true

# Model aliases - use friendly names instead of full provider model names
model_aliases:
  fast-llm:
    target: gpt-4o-mini

  smart-llm:
    target: gpt-4o

# HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access
listeners:
  # Agent listener for routing requests to multiple agents
  - type: agent
    name: travel_booking_service
    port: 8001
    router: plano_orchestrator_v1
    address: 0.0.0.0
    agents:
      - id: rag_agent
        description: virtual assistant for retrieval augmented generation tasks
        input_filters:
          - input_guards

  # Model listener for direct LLM access
  - type: model
    name: model_1
    address: 0.0.0.0
    port: 12000
    # Optional: attach input filters for guardrails on direct LLM requests
    # input_filters:
    #   - input_guards

  # Prompt listener for function calling (for prompt_targets)
  - type: prompt
    name: prompt_function_listener
    address: 0.0.0.0
    port: 10000
    # This listener is used for prompt_targets and function calling

# Reusable service endpoints
endpoints:
  app_server:
    endpoint: 127.0.0.1:80
    connect_timeout: 0.005s

  mistral_local:
    endpoint: 127.0.0.1:8001

# Prompt targets for function calling and API orchestration
prompt_targets:
  - name: get_current_weather
    description: Get current weather at a location.
    parameters:
      - name: location
        description: The location to get the weather for
        required: true
        type: string
        format: City, State
      - name: days
        description: the number of days for the request
        required: true
        type: int
    endpoint:
      name: app_server
      path: /weather
      http_method: POST

# OpenTelemetry tracing configuration
tracing:
  # Random sampling percentage (1-100)
  random_sampling: 100