LangChain - LangChain Blog (Page 17)

Improving Document Retrieval with Contextual Compression

Note: This post assumes some familiarity with LangChain and is moderately technical. 💡 TL;DR: We’ve introduced a new abstraction and a new document Retriever

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Autonomous Agents & Agent Simulations

Over the past two weeks, there has been a massive increase in using LLMs in an agentic manner. Specifically, projects like AutoGPT, BabyAGI, CAMEL, and

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AI-Powered Medical Knowledge: Revolutionizing Care for Rare Conditions

[Editor's Note]: This is a guest post by Jack Simon, who recently participated in a hackathon at Williams College. He built a LangChain-powered

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Auto-Eval of Question-Answering Tasks

By Lance Martin Context LLM ops platforms, such as LangChain, make it easy to assemble LLM components (e.g., models, document retrievers, data loaders) into

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LangChain x Supabase

Supabase is holding an AI Hackathon this week. Here at LangChain we are big fans of both Supabase and hackathons, so we thought this would

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Announcing our $10M seed round led by Benchmark

It was only six months ago that we released the first version of LangChain, but it seems like several years. When we launched, generative AI

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Custom Agents

One of the most common requests we've heard is better functionality and documentation for creating custom agents. This has always been a bit

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Retrieval

TL;DR: We are adjusting our abstractions to make it easy for other retrieval methods besides the LangChain VectorDB object to be used in LangChain.

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LangChain + Zapier Natural Language Actions (NLA)

We are super excited to team up with Zapier and integrate their new Zapier NLA API into LangChain, which you can now use with your

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LLMs and SQL

Francisco Ingham and Jon Luo are two of the community members leading the change on the SQL integrations. We’re really excited to write this

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Origin Web Browser

[Editor's Note]: This is the second of hopefully many guest posts. We intend to highlight novel applications building on top of LangChain. If

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Prompt Selectors

One common complaint we've heard is that the default prompt templates do not work equally well for all models. This became especially pronounced

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