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# Introduction # Introduction
**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
Log and stream intermediate steps of any chain Log and stream intermediate steps of any chain
## Examples, ecosystem, and resources ## Examples, ecosystem, and resources
### [Use cases](/docs/use_cases/) ### [Use cases](/docs/use_cases/question_answering/)
Walkthroughs and best-practices for common end-to-end use cases, like: Walkthroughs and best-practices for common end-to-end use cases, like:
- [Chatbots](/docs/use_cases/chatbots) - [Document question answering](/docs/use_cases/question_answering/)
- [Answering questions using sources](/docs/use_cases/question_answering/) - [Chatbots](/docs/use_cases/chatbots/)
- [Analyzing structured data](/docs/use_cases/sql) - [Analyzing structured data](/docs/use_cases/qa_structured/sql/)
- and much more... - and much more...
### [Guides](/docs/guides/) ### [Guides](/docs/guides/)
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).
### [Additional resources](/docs/additional_resources/) ### [Additional resources](/docs/additional_resources/)
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.