LangChain - LangChain Blog (Page 2)

Benchmarking Query Analysis in High Cardinality Situations

Several key use cases for LLMs involve returning data in a structured format. Extraction is one such use case - we recently highlighted this with

6 min read

Iterating Towards LLM Reliability with Evaluation Driven Development

Editor's Note: the following is a guest blog post from the Devin Stein, CEO of Dosu. Dosu is an engineering teammate that helps

7 min read

[Week of 3/4] LangChain Release Notes

✂️ Extraction Use Case One of the main use cases for LLMs is extracting structured data from unstructured text. We've added a lot of

Release Notes 2 min read

Use Case Accelerant: Extraction Service

Today we’re excited to announce our newest OSS use-case accelerant: an extraction service. LLMs are a powerful tool for extracting structured data from unstructured

By LangChain 7 min read

[Week of 2/19] LangChain Release Notes

🚀 LangSmith Launch! LangSmith is now generally available - no more waitlist! Sign up for free here. * Video resources: LangSmith in 10 minutes & In Depth

By LangChain 1 min read

JSON agents with Ollama & LangChain

Learn to implement an open-source Mixtral agent that interacts with a graph database Neo4j through a semantic layer Editor's note: This post is

7 min read

Supercharging If-Statements With Prompt Classification Using Ollama and LangChain

Editor's Note: Andrew Nguonly has been building one of the more impressive projects we've seen recently - an LLM co-pilot for

6 min read

Rakuten Group builds with LangChain and LangSmith to deliver premium products for its business clients and employees

Rakuten Group is well known for operating one of the largest online shopping malls in Japan. The company has 70+ businesses in fields such as

By LangChain 3 min read

How Dataherald Makes Natural Language to SQL Easy

Editor's Note: we're excited to feature this guest post from the Dataherald team. Text-to-SQL is a HUGE use case, and Dataherald

4 min read

Plan-and-Execute Agents

Plan and execute agents promise faster, cheaper, and more performant task execution over previous agent designs. Learn how to build 3 types of planning agents in LangGraph in this post.

By LangChain 5 min read