# LangChain examples

This folder contains examples demonstrating application development with LangChain.

## Requirements

- [Python](https://www.python.org/) 3.10+
- An [OpenAI API key](https://platform.openai.com/api-keys) set as an environment variable (`OPENAI_API_KEY`)

## Examples

- `basic_llm_interaction/`: Setting up a basic LLM invocation.
- `structured_output/`: Binding an output schema so the model returns a validated object.
- `tool_calling/`: Equipping LangChain chains with tool call support.
- `conversational_memory/`: Storing and managing conversational history.
- `context_compression/`: Compressing input documents to retrieve relevant parts.
- `rag_with_vectorstore/`: End-to-end RAG system with a local vector store.

## Running the examples

Each example is in its own folder and contains a `README.md` with instructions on how to run it.