**LangChain** is a framework for developing applications powered by language models. It enables applications that are:
**LangChain** is a framework for developing applications powered by language models. It enables applications that:
- **Data-aware**: connect a language model to other sources of data
- **Are context-aware**: connect a language model to other sources of context (prompt instructions, few shot examples, content to ground it's response in)
- **Agentic**: allow a language model to interact with its environment
- **Reason**: rely on a language to reason (about how to answer based on provided context, what actions to take, etc)
The main value props of LangChain are:
The main value props of LangChain are:
1. **Components**: abstractions for working with language models, along with a collection of implementations for each abstraction. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not
1. **Components**: abstractions for working with language models, along with a collection of implementations for each abstraction. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not
@ -16,9 +16,9 @@ Off-the-shelf chains make it easy to get started. For more complex applications
## Get started
## Get started
[Here’s](/docs/get_started/installation.html) how to install LangChain, set up your environment, and start building.
[Here’s](/docs/get_started/installation) how to install LangChain, set up your environment, and start building.
We recommend following our [Quickstart](/docs/get_started/quickstart.html) guide to familiarize yourself with the framework by building your first LangChain application.
We recommend following our [Quickstart](/docs/get_started/quickstart) guide to familiarize yourself with the framework by building your first LangChain application.
_**Note**: These docs are for the LangChain [Python package](https://github.com/hwchase17/langchain). For documentation on [LangChain.js](https://github.com/hwchase17/langchainjs), the JS/TS version, [head here](https://js.langchain.com/docs)._
_**Note**: These docs are for the LangChain [Python package](https://github.com/hwchase17/langchain). For documentation on [LangChain.js](https://github.com/hwchase17/langchainjs), the JS/TS version, [head here](https://js.langchain.com/docs)._
@ -40,21 +40,21 @@ Persist application state between runs of a chain
Learn best practices for developing with LangChain.
Learn best practices for developing with LangChain.
### [Ecosystem](/docs/ecosystem/)
### [Ecosystem](/docs/integrations/providers/)
LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it. Check out our growing list of [integrations](/docs/integrations/) and [dependent repos](/docs/additional_resources/dependents).
LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it. Check out our growing list of [integrations](/docs/integrations/providers/) and [dependent repos](/docs/additional_resources/dependents).
Our community is full of prolific developers, creative builders, and fantastic teachers. Check out [YouTube tutorials](/docs/additional_resources/youtube.html) for great tutorials from folks in the community, and [Gallery](https://github.com/kyrolabs/awesome-langchain) for a list of awesome LangChain projects, compiled by the folks at [KyroLabs](https://kyrolabs.com).
Our community is full of prolific developers, creative builders, and fantastic teachers. Check out [YouTube tutorials](/docs/additional_resources/youtube) for great tutorials from folks in the community, and [Gallery](https://github.com/kyrolabs/awesome-langchain) for a list of awesome LangChain projects, compiled by the folks at [KyroLabs](https://kyrolabs.com).
### [Community](/docs/community)
### [Community](/docs/community)
Head to the [Community navigator](/docs/community) to find places to ask questions, share feedback, meet other developers, and dream about the future of LLM’s.
Head to the [Community navigator](/docs/community) to find places to ask questions, share feedback, meet other developers, and dream about the future of LLM’s.