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Model Setup (BYOM)

DeepMCPAgent requires a model — there is no fallback.

You may pass: - a LangChain chat model instance, or - a provider id string (forwarded to langchain.chat_models.init_chat_model())

Passing a model instance

from langchain_openai import ChatOpenAI
model = ChatOpenAI(model="gpt-4.1")
graph, loader = await build_deep_agent(servers=servers, model=model)

Passing a provider id string

graph, loader = await build_deep_agent(
    servers=servers,
    model="openai:gpt-4.1"   # handled by LangChain init_chat_model
)

Environment variables

Use provider-specific env vars (e.g., OPENAI_API_KEY, ANTHROPIC_API_KEY).
You can load a local .env via python-dotenv:

from dotenv import load_dotenv
load_dotenv()

Tips

  • Prefer instances for fine-grained control (temperature, timeouts).
  • Use smaller models for dev / testing to save latency & cost.