Category: langchain
-
LangChain for EDA: Build a CSV Sanity-Check Agent in Python
LangChain for EDA: Build a CSV Sanity-Check Agent in Python A practical LangChain tutorial for data scientists to inspect CSVs The post LangChain for EDA: Build a CSV Sanity-Check Agent in Python appeared first on Towards Data Science. Sarah Schürch Go to original source
-
Using LangGraph and MCP Servers to Create My Own Voice Assistant
Using LangGraph and MCP Servers to Create My Own Voice Assistant Built over 14 days, all locally run, no API keys, cloud services, or subscription fees. The post Using LangGraph and MCP Servers to Create My Own Voice Assistant appeared first on Towards Data Science. Benjamin Lee Go to original source
-
Hitchhiker’s Guide to RAG with ChatGPT API and LangChain
Hitchhiker’s Guide to RAG with ChatGPT API and LangChain Build a simple Python RAG pipeline using your local files as context The post Hitchhiker’s Guide to RAG with ChatGPT API and LangChain appeared first on Towards Data Science. Maria Mouschoutzi Go to original source
-
New to LLMs? Start Here
New to LLMs? Start Here A guide to Agents, LLMs, RAG, Fine-tuning, LangChain with practical examples to start building The post New to LLMs? Start Here appeared first on Towards Data Science. ALESSANDRA COSTA Go to original source
-
How to Build an AI Agent for Data Analytics Without Writing SQL
How to Build an AI Agent for Data Analytics Without Writing SQL Create a comprehensive AI agent from the ground up utilizing LangChain and DuckDB Continue reading on Towards Data Science » Chengzhi Zhao Go to original source
-
LangChain Meets Home Assistant: Unlock the Power of Generative AI in Your Smart Home
LangChain Meets Home Assistant: Unlock the Power of Generative AI in Your Smart Home Learn how to create an agent that understands your home’s context, learns your preferences, and interacts with you and your home to accomplish activities you find valuable. Photo by Igor Omilaev on Unsplash Introduction This article describes the architecture and design of…
-
Unlocking the Untapped Potential of Retrieval-Augmented Generation (RAG) Pipelines
Unlocking the Untapped Potential of Retrieval-Augmented Generation (RAG) Pipelines Essential Metrics and Methods to Enhance Performance Across Retrieval, Generation, and End-to-End Pipelines Continue reading on Towards Data Science » Saleh Alkhalifa Go to original source