Model Configuration

Complete reference for defining models with providers, parameters, and reasoning settings.

Full Schema

models:
  model_name:
    provider: string # Required: openai, anthropic, google, amazon-bedrock, dmr
    model: string # Required: model identifier
    temperature: float # Optional: 0.0–1.0
    max_tokens: integer # Optional: response length limit
    top_p: float # Optional: 0.0–1.0
    frequency_penalty: float # Optional: 0.0–2.0
    presence_penalty: float # Optional: 0.0–2.0
    base_url: string # Optional: custom API endpoint
    token_key: string # Optional: env var for API token
    thinking_budget: string|int # Optional: reasoning effort
    task_budget: int|object # Optional: total task token budget (Anthropic)
    parallel_tool_calls: boolean # Optional: allow parallel tool calls
    track_usage: boolean # Optional: track token usage
    routing: [list] # Optional: rule-based model routing
    provider_opts: # Optional: provider-specific options
      key: value

Properties Reference

Property Type Required Description
provider string ✓ Provider: openai, anthropic, google, amazon-bedrock, dmr, mistral, xai
model string ✓ Model name (e.g., gpt-4o, claude-sonnet-4-0, gemini-2.5-flash)
temperature float ✗ Randomness. 0.0 = deterministic, 1.0 = creative
max_tokens int ✗ Maximum response length in tokens
top_p float ✗ Nucleus sampling threshold
frequency_penalty float ✗ Penalize repeated tokens (0.0–2.0)
presence_penalty float ✗ Encourage topic diversity (0.0–2.0)
base_url string ✗ Custom API endpoint URL (for self-hosted or proxied endpoints)
token_key string ✗ Environment variable name containing the API token (overrides provider default)
thinking_budget string/int ✗ Reasoning effort control
task_budget int/object ✗ Total token budget for an agentic task (forwarded to Anthropic; see Task Budget).
parallel_tool_calls boolean ✗ Allow model to call multiple tools at once
track_usage boolean ✗ Track and report token usage for this model
routing array ✗ Rule-based routing to different models. See Model Routing.
provider_opts object ✗ Provider-specific options (see provider pages)

Thinking Budget

Control how much reasoning the model does before responding. This varies by provider:

OpenAI

Uses effort levels as strings:

models:
  gpt:
    provider: openai
    model: gpt-5-mini
    thinking_budget: low # minimal | low | medium | high

Anthropic

Uses an integer token budget (1024–32768):

models:
  claude:
    provider: anthropic
    model: claude-sonnet-4-5
    thinking_budget: 16384 # must be < max_tokens

Google Gemini 2.5

Uses an integer token budget. 0 disables, -1 lets the model decide:

models:
  gemini:
    provider: google
    model: gemini-2.5-flash
    thinking_budget: -1 # dynamic (default)

Google Gemini 3

Uses effort levels like OpenAI:

models:
  gemini3:
    provider: google
    model: gemini-3-flash
    thinking_budget: medium # minimal | low | medium | high

Disabling Thinking

Works for all providers:

thinking_budget: none # or 0

Task Budget

Anthropic-only.

task_budget caps the total number of tokens the model may spend across a multi-step agentic task — combining thinking, tool calls, and final output tokens. It lets long-running agents self-regulate effort without having to choose a tight per-call max_tokens.

It is forwarded to Anthropic’s output_config.task_budget request field. docker-agent automatically attaches the required task-budgets-2026-03-13 beta header whenever this field is set.

You can configure task_budget on any Claude model — docker-agent never gates it by model name. At the time of writing only Claude Opus 4.7 actually honors the field; other Claude models will reject requests that include it. Check the Anthropic release notes linked above for the current list of supported models.

Integer shorthand

models:
  opus:
    provider: anthropic
    model: claude-opus-4-7
    task_budget: 128000 # total tokens for the whole task
    thinking_budget: adaptive # works nicely together

Object form

Equivalent, and forward-compatible with future budget types:

models:
  opus:
    provider: anthropic
    model: claude-opus-4-7
    task_budget:
      type: tokens # only "tokens" is supported today
      total: 128000

Setting task_budget: 0 (or omitting the field) disables the feature — the model falls back to the provider’s default behavior.

Like other inheritable model settings, task_budget can also be declared on a provider definition and is inherited by every model that references that provider.

Interleaved Thinking

For Anthropic and Bedrock Claude models, interleaved thinking allows tool calls during model reasoning. This is enabled by default:

models:
  claude:
    provider: anthropic
    model: claude-sonnet-4-5
    # interleaved_thinking defaults to true
    provider_opts:
      interleaved_thinking: false # disable if needed

Thinking Display (Anthropic)

For Anthropic Claude models, thinking_display controls whether thinking blocks are returned in responses when thinking is enabled. Claude Opus 4.7 hides thinking content by default (omitted); set this provider option to receive summarized thinking:

models:
  opus-4-7:
    provider: anthropic
    model: claude-opus-4-7
    thinking_budget: adaptive
    provider_opts:
      thinking_display: summarized # "summarized", "display", or "omitted"

See the Anthropic provider page for details.

Examples by Provider

models:
  # OpenAI
  gpt:
    provider: openai
    model: gpt-5-mini

  # Anthropic
  claude:
    provider: anthropic
    model: claude-sonnet-4-0
    max_tokens: 64000

  # Google Gemini
  gemini:
    provider: google
    model: gemini-2.5-flash
    temperature: 0.5

  # AWS Bedrock
  bedrock:
    provider: amazon-bedrock
    model: global.anthropic.claude-sonnet-4-5-20250929-v1:0
    provider_opts:
      region: us-east-1

  # Docker Model Runner (local)
  local:
    provider: dmr
    model: ai/qwen3
    max_tokens: 8192

For detailed provider setup, see the Model Providers section.

Custom Endpoints

Use base_url to point to custom or self-hosted endpoints:

models:
  # Azure OpenAI
  azure_gpt:
    provider: openai
    model: gpt-4o
    base_url: https://my-resource.openai.azure.com/openai/deployments/gpt-4o
    token_key: AZURE_OPENAI_API_KEY

  # Self-hosted vLLM
  local_llama:
    provider: openai # vLLM is OpenAI-compatible
    model: meta-llama/Llama-3.2-3B-Instruct
    base_url: http://localhost:8000/v1

  # Proxy or gateway
  proxied:
    provider: openai
    model: gpt-4o
    base_url: https://proxy.internal.company.com/openai/v1
    token_key: INTERNAL_API_KEY

See Local Models for more examples of custom endpoints.

Inheriting from Provider Definitions

Models can reference a named provider to inherit shared defaults. Model-level settings always take precedence:

providers:
  my_anthropic:
    provider: anthropic
    token_key: MY_ANTHROPIC_KEY
    max_tokens: 16384
    thinking_budget: high
    temperature: 0.5

models:
  claude:
    provider: my_anthropic
    model: claude-sonnet-4-5
    # Inherits max_tokens, thinking_budget, temperature from provider

  claude_fast:
    provider: my_anthropic
    model: claude-haiku-4-5
    thinking_budget: low  # Overrides provider default

See Provider Definitions for the full list of inheritable properties.

← Previous Agent Config