AI is moving fast, good overview of recent developments and what commercial opportunities could be enabled https://
t.co/kHO9IeLCd0
@hwchase17
-
AI Developments and Commercial Opportunities Overview
By
–
-
Brave Search API Integration Exciting for LangChain Users
By
–
I was really excited when I saw the @brave search API announcement the other day Search APIs are one of the more popular/important integrations we have in LangChain, so I'm really excited for this integration
-
Aviary: Comparing Open Source AI Models Side by Side
By
–
There have been lots of exciting open source models released recently – almost too many track Aviary by @anyscalecompute (released yesterday) is a fun and easy way to compare many side by side https://
github.com/ray-project/av
iary/
… Also got to love the emoji -
LLMs Prompts Output Parsers and Evaluation Fundamentals
By
–
we covered a lot but i liked the prompts/llms/output parsers section (basic building blocks, important to understand) and the evaluation section (very practical regardless of use case)
-
LangChain Vancouver Meetup with Expert Misbah Sy
By
–
LangChain Vancouver meetup!!! @MisbahSy is a LangChain expert, if you're in the area I would recommend going to this
-
LangChain in Education Webinar: Companies Building AI Solutions
By
–
Final call for the "LangChain in Education Webinar" starting in an hour! Hear from multiple companies using LangChain to build products to improve how education is done
-
LangChain Code Splitter: Supported Languages and Missing Coverage
By
–
Supported languages: cpp, go, java, js, php, proto, python, rst, ruby, rust, scala, swift, markdown, latex, html What other ones are we missing? Python Documentation: https://
python.langchain.com/en/latest/modu
les/indexes/text_splitters/examples/code_splitter.html
… JS Documentation: https://
js.langchain.com/docs/modules/i
ndexes/text_splitters/examples/code
… -
15 Coding Languages Now Supported Thanks to Community
By
–
We previously had support for a few different coding languages BIG thanks to @hsu_byron for bringing total support to 15 different languages And David Revillas for adding HTML support, and @Hacubu for porting to JS
-
Text Splitting: Crucial Preprocessing for RAG Systems
By
–
A underrated part of the preprocessing pipeline, proper splitting of text allows for maintaining semantically meaningful chunks This is crucial when doing retrieval augmented generation in order to ensure the proper context is inserted into the prompt
-
LangChain Adds 15+ Code-Specific Text Splitters
By
–
15+ Code Specific Text Splitters Just used one of @langchain 's 100+ Document Loaders? Next step: split data into embeddable chunks. We now have support for splitting 15+ different coding languages in the optimal way