we started this a bit here: https://
langchain.readthedocs.io/en/latest/glos
sary.html
… but its massively out of date. if you did want to update this that would be for a lot of folks
@langchain
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LangChain Glossary Documentation Needs Major Update
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LangChain Community Events Series Announced for 2026
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LangChain Community Events Really excited to announce a series of IRL community events (with some virtual components as well) Schedule: 2/9: LangChain Kickoff @ SF
2/23: LangChain NYC Meetup + demos
3/15: LangChain SF Meetup + demos See for details! -
LangChain Kickoff Event in San Francisco
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LangChain Kickoff Thursday, February 9 @ JAX Vineyards in SF Hosted by @benchmark and @milesgrimshaw RSVP here: http://
bit.ly/langchainkicko
ff
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Documentation Improvements and Bug Fixes Released
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Misc document and Bug Fixes s/o to @ephe_meral @RazRazcle Istora Mandiri, Zach Schillaci, @somejonus
, @eltociear for various documentation improvements and bug fixes! -
PAL Chain Updates: Global Locals and Intermediate Steps
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Some updates to the PAL chain From Nick Furlotte, includes the ability to specify global/locals, and then also return intermediate steps Docs: https://
langchain.readthedocs.io/en/latest/modu
les/chains/examples/pal.html#intermediate-steps
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NGram Example Selector for LangChain Prompt Engineering
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ngram example selector Adding to the arsenal of existing example selectors, @seanspriggens added one based on ngram overlap. Select the closest examples by ngram overlap up to a threshold! Documentation: https://
langchain.readthedocs.io/en/latest/modu
les/prompts/examples/example_selectors.html#ngram-overlap-exampleselector
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New Beam Deployment Template for LLM Chains and Agents
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New deployment template for http://
beam.cloud Lot's of people have been asking for easiest way to deploy chains/agents, and @mernit added a new deployment template for Beam! https://
langchain.readthedocs.io/en/latest/depl
oyments.html#beam
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LangChain from_string Method Simplifies LLMChain Construction
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Usability is everything, and @brucehammer came up with a great idea for making it easier to construct LLMChains. A `from_string` method parses out the variables and auto-creates a prompt Documentation: https://
langchain.readthedocs.io/en/latest/modu
les/chains/generic/llm_chain.html#from-string
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Instruct Embeddings: Task-Tailored Text Embeddings from HuggingFace
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@huggingface Instruct embeddings Instruct embeddings are from an instruction-finetuned embedding model that can generate text embeddings tailored to any task, *just by providing the task description* A joint effort by seanaedmiston and @EnoReyes https://
langchain.readthedocs.io/en/latest/modu
les/utils/combine_docs_examples/embeddings.html#instructembeddings
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LangChain 0.0.76 Release: Instruct Embeddings and New Features
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Another big release! 0.0.76 main features: @huggingface Instruct embeddings (seanaedmiston, @EnoReyes
) ngram example selector (
@seanspriggens
) Other features include a new deployment template, easier way to construct LLMChain, and updates to PALChain Lets dive in