Configuration Reference

The following is a complete reference of the plano_config.yml that controls the behavior of a single instance of the Arch gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets where prompts get routed to, apply guardrails, and enable critical agent observability features.

Plano Configuration - Full Reference
  1# Arch Gateway configuration version
  2version: v0.3.0
  3
  4
  5# External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
  6agents:
  7  - id: weather_agent  # Example agent for weather
  8    url: http://host.docker.internal:10510
  9
 10  - id: flight_agent   # Example agent for flights
 11    url: http://host.docker.internal:10520
 12
 13
 14# MCP filters applied to requests/responses (e.g., input validation, query rewriting)
 15filters:
 16  - id: input_guards  # Example filter for input validation
 17    url: http://host.docker.internal:10500
 18    # type: mcp (default)
 19    # transport: streamable-http (default)
 20    # tool: input_guards (default - same as filter id)
 21
 22
 23# LLM provider configurations with API keys and model routing
 24model_providers:
 25  - model: openai/gpt-4o
 26    access_key: $OPENAI_API_KEY
 27    default: true
 28
 29  - model: openai/gpt-4o-mini
 30    access_key: $OPENAI_API_KEY
 31
 32  - model: anthropic/claude-sonnet-4-0
 33    access_key: $ANTHROPIC_API_KEY
 34
 35  - model: mistral/ministral-3b-latest
 36    access_key: $MISTRAL_API_KEY
 37
 38
 39# Model aliases - use friendly names instead of full provider model names
 40model_aliases:
 41  fast-llm:
 42    target: gpt-4o-mini
 43
 44  smart-llm:
 45    target: gpt-4o
 46
 47
 48# HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access
 49listeners:
 50  # Agent listener for routing requests to multiple agents
 51  - type: agent
 52    name: travel_booking_service
 53    port: 8001
 54    router: plano_orchestrator_v1
 55    address: 0.0.0.0
 56    agents:
 57      - id: rag_agent
 58        description: virtual assistant for retrieval augmented generation tasks
 59        filter_chain:
 60          - input_guards
 61
 62  # Model listener for direct LLM access
 63  - type: model
 64    name: model_1
 65    address: 0.0.0.0
 66    port: 12000
 67
 68  # Prompt listener for function calling (for prompt_targets)
 69  - type: prompt
 70    name: prompt_function_listener
 71    address: 0.0.0.0
 72    port: 10000
 73    # This listener is used for prompt_targets and function calling
 74
 75
 76# Reusable service endpoints
 77endpoints:
 78  app_server:
 79    endpoint: 127.0.0.1:80
 80    connect_timeout: 0.005s
 81
 82  mistral_local:
 83    endpoint: 127.0.0.1:8001
 84
 85
 86# Prompt targets for function calling and API orchestration
 87prompt_targets:
 88  - name: get_current_weather
 89    description: Get current weather at a location.
 90    parameters:
 91      - name: location
 92        description: The location to get the weather for
 93        required: true
 94        type: string
 95        format: City, State
 96      - name: days
 97        description: the number of days for the request
 98        required: true
 99        type: int
100    endpoint:
101      name: app_server
102      path: /weather
103      http_method: POST
104
105
106# OpenTelemetry tracing configuration
107tracing:
108  # Random sampling percentage (1-100)
109  random_sampling: 100