LangChain - LangChain Blog (Page 10)

Beyond Text: Making GenAI Applications Accessible to All

Editor's Note: This post was written by Andres Torres and Dylan Brock from Norwegian Cruise Line. Building UI/UX for AI applications is

8 min read

Robocorp’s code generation assistant makes building Python automation easy for developers

Challenge Robocorp was founded in 2019 out of frustration that the promise of developers being able to automate monotonous work hadn’t been realized. Right

Case Studies 2 min read

Multi-Vector Retriever for RAG on tables, text, and images

Summary Seamless question-answering across diverse data types (images, text, tables) is one of the holy grails of RAG. We’re releasing three new cookbooks that

5 min read

Constructing knowledge graphs from text using OpenAI functions: Leveraging knowledge graphs to power LangChain Applications

Editor's Note: This post was written by Tomaz Bratanic from the Neo4j team. Extracting structured information from unstructured data like text has been

10 min read

You.com x LangChain

Editor's Note: the following is a guest blog post from our friends at You.com. We've seen a lot of interesting

By LangChain 4 min read

Test Run Comparisons

One pattern I noticed is that great AI researchers are willing to manually inspect lots of data. And more than that, they build infrastructure that

By LangChain 3 min read

Testing Fine Tuned Open Source Models in LangSmith

Editor's Note. This blog post was written by Ryan Brandt, the CTO and Cofounder of ChatOpenSource, a business specializing in enterprise AI chat

5 min read

How to design an Agent for Production

Editor's Note: This post is written by Dexter Storey, Sarim Malik, and Ted Spare from the Rubric Labs team. Important Links * GitHub repository

6 min read

Building LLM-Powered Web Apps with Client-Side Technology

The initial version of this blog post was a talk for Google’s internal WebML Summit 2023, which you can check out here. It’s

By LangChain 5 min read

Introducing LangServe, the best way to deploy your LangChains

We think the LangChain Expression Language (LCEL) is the quickest way to prototype the brains of your LLM application. The next exciting step is to

By LangChain 5 min read

Fine-tuning ChatGPT: Surpassing GPT-4 Summarization Performance–A 63% Cost Reduction and 11x Speed Enhancement using Synthetic Data and LangSmith

Editor's Note: This post was written by Charlie George, machine learning engineer at Elicit. Summary * Fine-tuned ChatGPT beats GPT-4 for news article summarization

5 min read

Using a Knowledge Graph to implement a DevOps RAG application

Editor's Note: This post was written in collaboration with the Neo4J team. RAG applications are all the rage at the moment. Everyone is

8 min read