deepagents

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  <h3>The batteries-included agent harness.</h3>
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<br>

Deep Agents is an open source agent harness — an opinionated agent that runs out of the box. Extend, override, or replace any piece.

**Principles:**

- **Opinionated** — defaults tuned for long-horizon, multi-step work
- **Extensible** — override or replace any piece without forking
- **Model-agnostic** — works with any LLM that supports tool calling: frontier, open-weight, or local
- **Production-ready** — built on LangGraph (streaming, persistence, checkpointing) with first-class tracing, evaluation, and deployment via LangSmith

**Features include:**

- **Sub-agents** — delegate tasks to agents with isolated context windows
- **Filesystem** — read, write, edit, or search over pluggable local, sandboxed, or remote backends
- **Context management** — summarize long threads and offload tool outputs to disk
- **Shell access** — run commands in your sandbox of choice
- **Persistent memory** — pluggable state and store backends for cross-session recall
- **Human-in-the-loop** — approve, edit, or reject tool calls before they run
- **Skills** — reusable behaviors the agent can load on demand
- **Tools** — bring your own functions or any MCP server

Deep Agents is available as a JavaScript/TypeScript library — see [deepagents.js](https://github.com/langchain-ai/deepagentsjs).

> [!NOTE]
> **Deep Agents Code** — a pre-built coding agent in your terminal, similar to Claude Code or Cursor, powered by any LLM. Install with `curl -LsSf https://langch.in/dcode | bash`. See the [documentation](https://docs.langchain.com/deepagents-code) for the full feature set.

## Quickstart

```bash
uv add deepagents
```

```python
from deepagents import create_deep_agent

agent = create_deep_agent(
    model="openai:gpt-6-astra",
    system_prompt="You are a research assistant.",
)
result = agent.invoke({"mess