mirror of
https://github.com/hwchase17/langchain.git
synced 2026-03-18 19:18:48 +00:00
28728dca9f
**Description:** Added a beginner-friendly tip to the README to help first-time contributors find a starting point. This is a documentation improvement aimed at lowering the barrier for newcomers to participate in open source. **Issue:** No related issue **Dependencies:** None --- ## Note to maintainers I'm new to open source and this is my first PR! If there's anything that needs improvement, please guide me and I'll be happy to learn and make changes. Thank you for your patience! 😊 ## What does this PR do? - Added a noticeable beginner tip box after the badges section in README - Provided specific guidance (Good First Issues link) - Encourages newcomers to start with documentation fixes ## Why is this change needed? - Makes it easier for new contributors to get started - Provides clear direction and reduces confusion - Creates a more welcoming open source community environment --------- Co-authored-by: Mason Daugherty <mason@langchain.dev>
79 lines
5.0 KiB
Markdown
79 lines
5.0 KiB
Markdown
<p align="center">
|
||
<picture>
|
||
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-dark.svg">
|
||
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-light.svg">
|
||
<img alt="LangChain Logo" src=".github/images/logo-dark.svg" width="80%">
|
||
</picture>
|
||
</p>
|
||
|
||
<p align="center">
|
||
The platform for reliable agents.
|
||
</p>
|
||
|
||
<p align="center">
|
||
<a href="https://opensource.org/licenses/MIT" target="_blank">
|
||
<img src="https://img.shields.io/pypi/l/langchain" alt="PyPI - License">
|
||
</a>
|
||
<a href="https://pypistats.org/packages/langchain" target="_blank">
|
||
<img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads">
|
||
</a>
|
||
<a href="https://pypi.org/project/langchain/#history" target="_blank">
|
||
<img src="https://img.shields.io/pypi/v/langchain?label=%20" alt="Version">
|
||
</a>
|
||
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain" target="_blank">
|
||
<img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers">
|
||
</a>
|
||
<a href="https://codespaces.new/langchain-ai/langchain" target="_blank">
|
||
<img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20">
|
||
</a>
|
||
<a href="https://codspeed.io/langchain-ai/langchain" target="_blank">
|
||
<img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed Badge">
|
||
</a>
|
||
<a href="https://twitter.com/langchainai" target="_blank">
|
||
<img src="https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI" alt="Twitter / X">
|
||
</a>
|
||
</p>
|
||
|
||
LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.
|
||
|
||
```bash
|
||
pip install langchain
|
||
```
|
||
|
||
---
|
||
|
||
**Documentation**: To learn more about LangChain, check out [the docs](https://docs.langchain.com/oss/python/langchain/overview).
|
||
|
||
If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our framework for building controllable agent workflows.
|
||
|
||
> [!NOTE]
|
||
> Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
|
||
|
||
## Why use LangChain?
|
||
|
||
LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
|
||
|
||
Use LangChain for:
|
||
|
||
- **Real-time data augmentation**. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain’s vast library of integrations with model providers, tools, vector stores, retrievers, and more.
|
||
- **Model interoperability**. Swap models in and out as your engineering team experiments to find the best choice for your application’s needs. As the industry frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without losing momentum.
|
||
|
||
## LangChain’s ecosystem
|
||
|
||
While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
|
||
|
||
To improve your LLM application development, pair LangChain with:
|
||
|
||
- [LangSmith](https://www.langchain.com/langsmith) - Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
|
||
- [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview) - Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows — and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
|
||
- [LangGraph Platform](https://docs.langchain.com/langgraph-platform) - Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio).
|
||
|
||
## Additional resources
|
||
|
||
- [Learn](https://docs.langchain.com/oss/python/learn): Use cases, conceptual overviews, and more.
|
||
- [API Reference](https://reference.langchain.com/python): Detailed reference on
|
||
navigating base packages and integrations for LangChain.
|
||
- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview): Learn how to contribute to LangChain and find good first issues.
|
||
- [LangChain Forum](https://forum.langchain.com): Connect with the community and share all of your technical questions, ideas, and feedback.
|
||
- [Chat LangChain](https://chat.langchain.com): Ask questions & chat with our documentation.
|