Models

from deepagents import ProviderProfile, register_provider_profile

# Provider-wide default: every openai model gets temperature=0.
register_provider_profile(
    "openai",
    ProviderProfile(init_kwargs={"temperature": 0}),
)

# Model-level override: gpt-5.5 additionally gets a specific reasoning effort.
# Inherits temperature=0 from the provider-level profile above.
register_provider_profile(
    "openai:gpt-5.5",
    ProviderProfile(init_kwargs={"reasoning_effort": "medium"}),
)

from langchain.chat_models import init_chat_model
from deepagents import create_deep_agent

model = init_chat_model("openai:gpt-5.5", use_responses_api=False)
agent = create_deep_agent(model=model)

from langchain.chat_models import init_chat_model
from deepagents import create_deep_agent

model = init_chat_model(
    "openai:gpt-5.5",
    use_responses_api=True,
    store=False,
    include=["reasoning.encrypted_content"],
)
agent = create_deep_agent(model=model)

from dataclasses import dataclass
from typing import Callable

from langchain.agents.middleware import ModelRequest, ModelResponse, wrap_model_call
from langchain.chat_models import init_chat_model
from deepagents import create_deep_agent


@dataclass
class Context:
    model: str


@wrap_model_call
def configurable_model(
    request: ModelRequest,
    handler: Callable[[ModelRequest], ModelResponse],
) -> ModelResponse:
    model_name = request.runtime.context.model
    model = init_chat_model(model_name)
    return handler(request.override(model=model))


agent = create_deep_agent(
    model="google_genai:gemini-3.6-flash",
    middleware=[configurable_model],
    context_schema=Context,
)

# Invoke with the user's model selection
result = agent.invoke(
    {"messages": [{"role": "user", "content": "Hello!"}]},
    context=Context(model="openai:gpt-5.5"),
)