langchain-core
Building applications with LLMs through composability
Decision gist · record as of 2026-08-14
Yes. LangChain Core is the canonical foundation for LLM application development in Python, with production-grade stability, active maintenance, low install friction, and a permissive MIT license. Install it if you are building any LLM application that benefits from modular abstractions and ecosystem interoperability. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.14).
- Low friction install with a recent release (3 days old) and active maintenance.
- Depends on well-established libraries like pydantic, tenacity, and langsmith.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial use, modification, and distribution with minimal restrictions—standard permissive terms suitable for most production and proprietary projects.
last release 2026-08-11 (3 days) · last repo commit 2026-08-14 · 144,195 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 176,017,959 downloads/mo, #239 on PyPI
Alternatives
Verify before relying
pip install langchain-core
from langchain_core.runnables import Runnable
from langchain_core.language_model import BaseLanguageModel
# Use abstractions to compose LLM applications- Whether the package is suitable for specific LLM providers or if additional provider packages are required.
- Performance characteristics and latency overhead of the abstraction layer in production workloads.
- Compatibility guarantees with third-party LangChain ecosystem extensions.
What it is and what it does
LangChain Core is the foundational library for the LangChain ecosystem, providing stable, modular abstractions for building applications with large language models. It defines core interfaces like Runnable, BaseLanguageModel, and other composable components that any LLM provider can implement, allowing applications built on these abstractions to work across different providers without tight coupling.
The library is designed around modularity and simplicity—each abstraction is independent and not tied to any specific model provider. It handles common patterns in LLM application development: chaining operations, managing prompts, handling retries via tenacity, and serialization via pydantic and YAML. The package is production-stable, actively maintained with releases every few days, and used at scale by many companies. It requires Python 3.10 or later and depends on well-tested libraries like pydantic, langsmith, and packaging.
Use it for
- Build modular LLM chains that work across multiple model providers without rewriting application logic.
- Define reusable agent and tool abstractions that can be plugged into different LangChain ecosystem packages.
- Create composable prompt templates and runnable workflows that serialize and deserialize consistently.
- Implement retry logic and error handling for LLM API calls using built-in tenacity integration.
- Develop production LLM applications with a stable, versioned foundation committed to backward compatibility.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
LangChain Core is the canonical foundation for LLM application development in Python, with production-grade stability, active maintenance, low install friction, and a permissive MIT license. Install it if you are building any LLM application that benefits from modular abstractions and ecosystem interoperability. No known security vulnerabilities.
Install
langchain-core on PyPI
Before you install
Low friction install with a recent release (3 days old) and active maintenance. Depends on well-established libraries like pydantic, tenacity, and langsmith. The project has substantial production adoption and a large install base.
Requires Python 3.10 or later (supports up to 3.14).
License in practice
MIT license permits commercial use, modification, and distribution with minimal restrictions—standard permissive terms suitable for most production and proprietary projects.
Quickstart
pip install langchain-core
from langchain_core.runnables import Runnable
from langchain_core.language_model import BaseLanguageModel
# Use abstractions to compose LLM applicationsVerify before relying
- Whether the package is suitable for specific LLM providers or if additional provider packages are required.
- Performance characteristics and latency overhead of the abstraction layer in production workloads.
- Compatibility guarantees with third-party LangChain ecosystem extensions.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0.0,>=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagesjsonpatchlangchain-protocollangsmithpackagingpydanticpyyamltenacitytyping-extensionsuuid-utils |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 176,017,959 / month, #239 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python Modules |
Evidence: langchain_core-1.5.4-py3-none-any.whl
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See also langchain · langchain-cli · langchain-experimental · langchain-openai · langchain-classic · langchainplus-sdk · langserve · langchain-community · langchain-mistralai · langgraph