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 hard and
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
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
[Week of 10/16] LangChain Release Notes Announcing LangServe LangServe is the best way to deploy your LangChains. Blog Post. GitHub repo * Includes: Input/output schema, /docs endpoint, invoke/batch/stream endpoints,
LangServe Playground and Configurability Last week we launched LangServe, a way to easily deploy chains and agents in a production-ready manner. Specifically, it takes a chain and easily spins
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 around for
A Chunk by Any Other Name: Structured Text Splitting and Metadata-enhanced RAG There's something of a structural irony in the fact that building context-aware LLM applications typically begins with a systematic process of decontextualization, wherein 1. source
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 use cases around interacting
The Prompt Landscape Context Prompt Engineering can steer LLM behavior without updating the model weights. A variety of prompts for different uses-cases have emerged (e.g., see @dair_
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
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 that runs
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 * OpenAI Functions
![[Week of 10/16] LangChain Release Notes](/content/images/size/w1520/format/webp/2023/10/Twitter-post---1--1-.png)
