Chapter 2: Models — Choosing Your LLM

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The models section defines named LLM configurations. Each model has a provider, a model_id, and optional params.

models:
  fast:
    provider: bedrock
    model_id: us.anthropic.claude-sonnet-4-6-v1:0

  creative:
    provider: openai
    model_id: gpt-4o
    params:
      temperature: 0.9

  local:
    provider: ollama
    model_id: llama3.2
    params:
      ctx_size: 8192

Built-in Providers

Provider	Package Required	Example model_id
bedrock	(included)	us.anthropic.claude-sonnet-4-6-v1:0
openai	pip install kaboo-workflows[openai]	gpt-4o
ollama	pip install kaboo-workflows[ollama]	llama3.2
gemini	pip install kaboo-workflows[gemini]	gemini-2.0-flash

How Agents Reference Models

Agents reference models by name — the key you defined in the models section:

models:
  smart:
    provider: bedrock
    model_id: us.anthropic.claude-sonnet-4-6-v1:0

agents:
  analyst:
    model: smart     # <-- references the "smart" model above
    system_prompt: "You analyze data."

Inline Models

Don't want to name a model? Define it inline directly on the agent:

agents:
  analyst:
    model:
      provider: bedrock
      model_id: us.anthropic.claude-sonnet-4-6-v1:0
    system_prompt: "You analyze data."

This is handy when only one agent uses a specific model — no need to pollute the models section. But if two agents share the same model config, use a named model to avoid duplication.

Custom Model Providers

If the built-in four providers aren't enough, you can point provider to a custom Model subclass:

models:
  my_custom:
    provider: my_package.models:CustomModel
    model_id: my-model-v1
    params:
      api_key: ${API_KEY}

The class must be a subclass of strands.models.Model. The model_id and params are passed to its constructor.

The params Dict

params is a pass-through dictionary — whatever you put in it gets forwarded as **kwargs to the model constructor. This means you can set any provider-specific parameter:

models:
  tuned:
    provider: bedrock
    model_id: us.anthropic.claude-sonnet-4-6-v1:0
    params:
      max_tokens: 4096
      temperature: 0.7
      top_p: 0.9

Tips & Tricks

• When combined with vars, you can swap models at runtime: MODEL=gpt-4o python main.py. See Chapter 3.
• If you omit model on an agent entirely, strands picks its built-in default (Bedrock). This is fine for quick tests but explicit is better for production.
• The params dict preserves types from YAML — integers stay integers, floats stay floats. This matters for parameters like max_tokens that must be an int.

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Next: Chapter 3 — Variables →