Pydantic DeepAgents vs LangChain Deep Agents

from pydantic_deep import (
    create_deep_agent, create_default_deps, LocalBackend
)
from pydantic_deep.types import SubAgentConfig

agent = create_deep_agent(
    model="openai:gpt-4.1",
    instructions="You are a senior developer.",
    include_todo=True,
    include_filesystem=True,
    include_subagents=True,
    include_memory=True,
    subagents=[SubAgentConfig(
        name="code-reviewer",
        description="Reviews code for bugs",
        instructions="You are a senior reviewer.",
    )],
)

deps = create_default_deps(LocalBackend("."))
result = await agent.run(
    "Refactor auth module", deps=deps
)

from deepagents import create_deep_agent
from langchain.chat_models import init_chat_model

agent = create_deep_agent(
    model=init_chat_model("openai:gpt-4o"),
    tools=[my_custom_tool],
    system_prompt="You are a coding assistant.",
)

result = agent.invoke({
    "messages": [{
        "role": "user",
        "content": "Refactor auth module",
    }]
})