Tutorials
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
Components
Build simple applications to familiarize yourself with LangChain's open-source building blocks.
If you're looking to get started with chat models, vector stores, or other LangChain components from a specific provider, check out our supported integrations.
- LLM applications: Build a simple LLM application with prompt templates and chat models.
- Semantic search: Build a semantic search engine over a PDF with document loaders, embedding models, and vector stores.
- Classification: Classify text into categories or labels using chat models.
- Extraction: Extract structured data from text and other unstructured media using chat models.
Refer to the how-to guides for more detail on using all LangChain components.
Orchestration
Get started using LangGraph to assemble LangChain components into full-featured applications.
- Chatbots: Build a chatbot that incorporates memory.
- Agents: Build an agent that interacts with external tools.
- Retrieval Augmented Generation (RAG): Build an application that uses your own documents to inform its responses.
- Conversational RAG: Build a RAG application that incorporates a memory of its user interactions.
- Question-Answering with SQL: Build a question-answering system that executes SQL queries to inform its responses.
- Summarization: Generate summaries of (potentially long) texts.
TODO:
- Local RAG: Build a RAG application using LLMs running locally on your machine.
- Question-Answering with Graph Databases: Build a question-answering system that queries a graph database to inform its responses.
- Synthetic data: Generate synthetic data using LLMs.
LangSmith
LangSmith allows you to closely trace, monitor and evaluate your LLM application. It seamlessly integrates with LangChain, and you can use it to inspect and debug individual steps of your chains as you build.
LangSmith documentation is hosted on a separate site. You can peruse LangSmith tutorials here.
Evaluation
LangSmith helps you evaluate the performance of your LLM applications. The tutorial below is a great way to get started: