langchain-python

What problem does it solve?

This Skill provides guidance for developers to efficiently build and deploy sophisticated Large Language Model (LLM) applications using the LangChain framework in Python.

Core Features & Use Cases

• LLM Integration: Connect to various chat models and LLMs with consistent interfaces.
• Component Composition: Build complex chains and agents using LangChain Expression Language (LCEL).
• RAG & Vector Stores: Implement Retrieval-Augmented Generation patterns with integrated vector databases.
• Tool Calling & Structured Outputs: Enable LLMs to interact with external tools and return data in structured formats.
• Use Case: Develop a customer support chatbot that retrieves relevant information from a knowledge base using RAG and then uses tool-calling to book appointments.

Quick Start

Use the langchain-python skill to generate a Python script that creates a simple RAG chain using an OpenAI model and a Chroma vector store.