Framework for building LLM-powered AI agent applications
LangChain is the most popular open-source framework for building applications powered by large language models. Supports chains, agents, memory, RAG pipelines, and tool integrations. Used by developers to build chatbots, AI assistants, and autonomous agent systems at scale.
4 ready-to-use prompts — click any card to copy, or paste into the writer above.
Build a LangChain RAG (Retrieval Augmented Generation) pipeline that: loads PDF documents from a folder, splits them with RecursiveCharacterTextSplitter, embeds with OpenAI embeddings, stores in Chroma vector DB, and answers questions with source citations using GPT-4o.
Create a LangChain agent that has access to three tools: web search, a calculator, and a SQL database. The agent should answer questions like 'What is the revenue growth rate of the top 3 AI companies this year?' by intelligently choosing and chaining tools.
Build a conversational chain with memory that: maintains the last 10 messages of context, uses a system prompt that makes the AI act as an expert financial advisor, streams the response token by token, and saves the conversation history to a SQLite database.
Write a LangChain chain that takes a job description as input and uses a structured output parser to extract: required skills as an array, years of experience required, salary range if mentioned, and a seniority level enum (junior/mid/senior/lead). Include error handling for malformed outputs.
