langchain-daytona
Daytona sandbox integration for Deep Agents
Decision gist · record as of 2026-08-14
Yes, if you are building Deep Agents workflows that require code execution and want a straightforward Daytona integration. The package is actively maintained, has no known vulnerabilities, and carries a permissive MIT license. Install friction is low. However, verify that daytona and deepagents meet your infrastructure requirements before committing, as this package is young (first release 2026-02-05) and relatively niche.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later; daytona and deepagents must be installed and accessible.
- Low install friction with a pure-Python wheel distribution.
- Actively maintained as of 2026-08-14 with recent releases, though the package is young (first release 2026-02-05) and depends on daytona and deepagents.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you retain the license notice.
last release 2026-07-29 (16 days) · last repo commit 2026-08-14 · 27,774 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 260,152 downloads/mo, #8,398 on PyPI
Alternatives
Verify before relying
pip install langchain-daytona
from daytona import Daytona
from langchain_daytona import DaytonaSandbox
sandbox = Daytona().create()
backend = DaytonaSandbox(sandbox=sandbox, timeout=300, sync_polling_interval=0.25)
result = backend.execute("echo hello")
print(result.output)- How daytona and deepagents are installed and configured (whether they have their own system dependencies or setup requirements).
- Whether timeout and sync_polling_interval parameters are the primary configuration surface or if deeper customization is available.
- Performance characteristics and resource overhead of sandbox creation and code execution.
What it is and what it does
langchain-daytona provides a backend adapter that connects LangChain's Deep Agents framework to Daytona sandboxes, enabling agents to execute arbitrary code in isolated environments. The package wraps Daytona's sandbox API into a DaytonaSandbox class that accepts agent execution requests, manages timeouts, and polls for results.
The integration is lightweight—it depends only on daytona and deepagents—and targets modern Python versions (3.11+). It is intended for scenarios where an agent needs to run code safely without access to the host system, such as executing user-provided scripts or untrusted logic as part of an agentic workflow. The package is actively maintained and carries no known security vulnerabilities.
Use it for
- Run user-submitted code within a Deep Agent workflow without exposing the host system to arbitrary execution.
- Execute generated or dynamically constructed code in an isolated Daytona sandbox as part of an agent's reasoning loop.
- Build multi-step agent pipelines where intermediate code generation and execution require sandboxed evaluation.
- Prototype or test agent behaviors that involve code execution in a controlled, time-limited environment.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building Deep Agents workflows that require code execution and want a straightforward Daytona integration.
The package is actively maintained, has no known vulnerabilities, and carries a permissive MIT license. Install friction is low. However, verify that daytona and deepagents meet your infrastructure requirements before committing, as this package is young (first release 2026-02-05) and relatively niche.
Install
langchain-daytona on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained as of 2026-08-14 with recent releases, though the package is young (first release 2026-02-05) and depends on daytona and deepagents.
Requires Python 3.11 or later; daytona and deepagents must be installed and accessible.
License in practice
MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you retain the license notice.
Quickstart
pip install langchain-daytona
from daytona import Daytona
from langchain_daytona import DaytonaSandbox
sandbox = Daytona().create()
backend = DaytonaSandbox(sandbox=sandbox, timeout=300, sync_polling_interval=0.25)
result = backend.execute("echo hello")
print(result.output)Verify before relying
- How daytona and deepagents are installed and configured (whether they have their own system dependencies or setup requirements).
- Whether timeout and sync_polling_interval parameters are the primary configuration surface or if deeper customization is available.
- Performance characteristics and resource overhead of sandbox creation and code execution.
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 packagesdaytonadeepagents |
| Maintenance | Actively maintained 16 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 260,152 / month, #8,398 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_daytona-0.0.8-py3-none-any.whl
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See also langchain-modal · daytona · langchain-azure-dynamic-sessions · langchain-openai · langchain-mistralai · langchain-xai · langchain-deepseek · langchain-fireworks · llm-sandbox