langchain-modal
Modal sandbox integration for Deep Agents
Decision gist · record as of 2026-08-14
Yes, if you are already using LangChain's Deep Agents and Modal and want to orchestrate remote execution. The package is actively maintained, has no known vulnerabilities, and installs cleanly. However, it is a narrow integration—only install if you specifically need Modal sandbox execution within agents; it adds no value if you're not using both Modal and Deep Agents.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Modal app and a Modal account with configured credentials; modal.App.lookup() must resolve a valid app name.
- Low install friction with a pure-Python wheel.
- Active maintenance—last commit 2026-08-14, release 16 days old.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
last release 2026-07-29 (16 days) · last repo commit 2026-08-14 · 27,777 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 82,947 downloads/mo, #14,118 on PyPI
Alternatives
Verify before relying
pip install langchain-modal
import modal
from langchain_modal import ModalSandbox
sandbox = ModalSandbox(modal.Sandbox.create(app=modal.App.lookup("your-app")))
result = sandbox.execute("echo hello")
print(result.output)- Whether deepagents and modal are stable, well-maintained dependencies or if they introduce their own friction.
- What error handling and retry logic the ModalSandbox provides for failed or timed-out commands.
- Whether this package is suitable for production workloads or primarily for experimentation and development.
What it is and what it does
langchain-modal is a thin integration layer that connects LangChain's Deep Agents framework to Modal's serverless compute platform. It wraps Modal sandboxes in a ModalSandbox class that agents can use to execute commands in isolated, remote environments. The package is part of the LangChain ecosystem and is actively maintained alongside the broader Deep Agents project.
You use it by creating a ModalSandbox from an existing Modal app, then calling execute() to run shell commands or other operations inside that sandbox. The result object contains the output and status of the execution. This is useful when you want agents to run workloads on Modal's infrastructure rather than locally, but it requires you to already have Modal set up and a Modal app deployed.
Use it for
- Let a Deep Agent execute arbitrary shell commands in a Modal sandbox without running them on your local machine.
- Build multi-step agent workflows where some steps run remotely on Modal infrastructure for isolation or scale.
- Integrate Modal's serverless compute into LangChain agent chains for tasks that need ephemeral, on-demand execution.
- Test agent logic in isolated Modal environments before deploying to production systems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using LangChain's Deep Agents and Modal and want to orchestrate remote execution.
The package is actively maintained, has no known vulnerabilities, and installs cleanly. However, it is a narrow integration—only install if you specifically need Modal sandbox execution within agents; it adds no value if you're not using both Modal and Deep Agents.
Install
langchain-modal on PyPI
Before you install
Low install friction with a pure-Python wheel. Active maintenance—last commit 2026-08-14, release 16 days old. Depends on deepagents and modal, both external packages you'll need to manage separately.
Requires an existing Modal app and a Modal account with configured credentials; modal.App.lookup() must resolve a valid app name.
License in practice
MIT license is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install langchain-modal
import modal
from langchain_modal import ModalSandbox
sandbox = ModalSandbox(modal.Sandbox.create(app=modal.App.lookup("your-app")))
result = sandbox.execute("echo hello")
print(result.output)Verify before relying
- Whether deepagents and modal are stable, well-maintained dependencies or if they introduce their own friction.
- What error handling and retry logic the ModalSandbox provides for failed or timed-out commands.
- Whether this package is suitable for production workloads or primarily for experimentation and development.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesdeepagentsmodal |
| Maintenance | Actively maintained 16 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 82,947 / month, #14,118 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: langchain_modal-0.0.6-py3-none-any.whl
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See also langchain-daytona · modal · langchain-openai · langchain-mistralai · langchain-azure-dynamic-sessions · langchain-quickjs · deepagents · deepagents-cli · langchain-cli