Container Default LLM

One llm= on AgentTeam or AgentFlow becomes the default model for every member that never named one, while any agent that pinned its own model keeps it.

Quick Start

One team, one model

from praisonaiagents import Agent, AgentTeam

researcher = Agent(name="Researcher", instructions="Research.")
writer     = Agent(name="Writer",     instructions="Write.")

team = AgentTeam(
    agents=[researcher, writer],
    llm="anthropic/claude-sonnet-4-5",
)
team.start("Summarise the latest AI safety research")

The team’s llm= flows to every member that didn’t pick its own.

Same rule for a flow

from praisonaiagents import Agent
from praisonaiagents.workflows import AgentFlow

researcher = Agent(name="Researcher", instructions="Research.")
writer     = Agent(name="Writer",     instructions="Write.")

flow = AgentFlow(
    steps=[researcher, writer],
    llm="anthropic/claude-sonnet-4-5",
)
flow.start("Summarise the latest AI safety research")

AgentFlow(llm=…) fills in ready-made steps the same way AgentTeam does.

How It Works

The container’s llm= is a default, not an override. A member that named its own llm= / model= / auth= keeps it; a member with no model adopts the container’s. A pinned member keeps its model even when the container names another:

from praisonaiagents import Agent, AgentTeam

pinned = Agent(name="Reasoner",   instructions="Think hard.", llm="gpt-4o")
cheap  = Agent(name="Summariser", instructions="Summarise.")

team = AgentTeam(
    agents=[pinned, cheap],
    llm="anthropic/claude-sonnet-4-5",
)
# pinned.llm == "gpt-4o"                       (kept)
# cheap.llm  == "anthropic/claude-sonnet-4-5"  (filled in)

llm= on the container is a default. If a member was constructed with its own llm= / model= / auth=, the container never overrides it. Otherwise the container’s llm= becomes the member’s model.

`manager_llm` Is Separate

manager_llm= is the hierarchical manager’s own model and never touches the members.

from praisonaiagents import Agent, AgentTeam

member = Agent(name="Worker", instructions="Do the work.")

team = AgentTeam(
    agents=[member],
    llm="anthropic/claude-sonnet-4-5",  # member default
    manager_llm="gpt-4o",               # hierarchical manager only
)
# team.manager_llm == "gpt-4o"                       (manager keeps its own model)
# member.llm       == "anthropic/claude-sonnet-4-5"  (member fills in)

manager_llm= sets the model for the hierarchical manager agent only. It is never propagated to member agents — use llm= for that.

AgentFlow’s Fallback Is Not Propagated

AgentFlow falls back to "gpt-4o-mini" internally when it needs a model to run, but that fallback is not a caller’s choice — so it is never pushed onto steps.

from praisonaiagents import Agent
from praisonaiagents.workflows import AgentFlow

researcher = Agent(name="Researcher", instructions="Research.")

# No container llm= — each step keeps its own env-aware default,
# NOT the flow's "gpt-4o-mini" run-time fallback.
flow = AgentFlow(steps=[researcher])
flow.start("Summarise the latest AI safety research")

An AgentFlow(steps=[…]) with no llm= leaves each step’s model to Agent’s own env-aware default (OPENAI_MODEL_NAME, else gpt-4o-mini).

Common Patterns

Pin one member, let the rest follow the container — no code change needed to see the split.

from praisonaiagents import Agent, AgentTeam

reasoner = Agent(name="Reasoner",   instructions="Think hard.", llm="gpt-4o")
writer   = Agent(name="Writer",     instructions="Write.")
editor   = Agent(name="Editor",     instructions="Edit.")

team = AgentTeam(
    agents=[reasoner, writer, editor],
    llm="anthropic/claude-sonnet-4-5",
)
team.start("Draft and polish a launch post")
# reasoner calls gpt-4o; writer and editor call anthropic/claude-sonnet-4-5

Panel agents are skipped

A panel descriptor (panel:<name>) is not a model name, so the fill-in leaves it alone.

`auth=` counts as pinned

A subscription seat pins the vendor, so a team default of another vendor never overrides it.

List or dict rosters

AgentTeam accepts a list or a dict (multi-group teams); both forms are filled in.

Non-Agent members skipped

Members without _apply_default_llm are duck-typed and left untouched.

A member used before the container fills it in caches a dispatcher bound to the old model; the fill-in drops that cache so the next call rebuilds against the new model. Pinned members keep their dispatcher.

Configuration Options

Param	Container	Behaviour
`llm`	`AgentTeam`, `AgentFlow`	Default model for members that never named one. A member with its own `llm=` / `model=` / `auth=` keeps it.
`manager_llm`	`AgentTeam`	Hierarchical manager’s own model. Never propagated to members.

Best Practices

Set the vendor once at the container level

Put llm= on AgentTeam / AgentFlow and pin per-agent only where the job justifies a different model.

Give the manager its own model

Use manager_llm= for the hierarchical manager — don’t try to reuse the team default there.

Prefer container llm= for whole-team agreement

When every member should share a vendor, one container llm= beats repeating llm= on each Agent.

Upgrade if llm= did nothing before

Earlier versions stored the container llm= but never read it. Upgrade to the version that ships this fill-in so the parameter actually reaches members.

AgentTeam Params

Which params apply at the team level.

Parameter Scope

Team-level vs per-agent parameter scope.

AgentTeam

Multi-agent teams overview.

AgentFlow

Deterministic step pipelines.

Getting Started

Install

Core Concepts

Guides

Features

Models

Databases

Observability

Memory

Telemetry & Analytics

Knowledge

RAG

Persistence

Tools

Other Features

Developers

Configuration

Best Practices

Getting Started (No Code)

Container Default LLM

Quick Start

How It Works

`manager_llm` Is Separate

AgentFlow’s Fallback Is Not Propagated

Common Patterns

Panel agents are skipped

`auth=` counts as pinned

List or dict rosters

Non-Agent members skipped

Configuration Options

Best Practices

AgentTeam Params

Parameter Scope

AgentTeam

AgentFlow

​Quick Start

​How It Works

​manager_llm Is Separate

​AgentFlow’s Fallback Is Not Propagated

​Common Patterns

Panel agents are skipped

`auth=` counts as pinned

List or dict rosters

Non-Agent members skipped

​Configuration Options

​Best Practices

​Related

AgentTeam Params

Parameter Scope

AgentTeam

AgentFlow

Quick Start

How It Works

`manager_llm` Is Separate

AgentFlow’s Fallback Is Not Propagated

Common Patterns

Configuration Options

Best Practices

Related