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Jul 29 โ€ข 5 tweets โ€ข 3 min read Twitter logo Read on Twitter
New in ๐Ÿฆœ๐Ÿ”—:

๐Ÿ”Ž @meilisearch vector store
๐Ÿ™ Expanded @github toolkit
๐ŸŒธ Expanded support for models run on Petals
๐ŸŽ @Dropbox document loader

a ๐Ÿงต:
๐Ÿ”Ž @meilisearch vector store

Meilisearch is a lightning fast open source search engine that also supports vector storage, now available through ๐Ÿฆœ๐Ÿ”—!

Docs: https://t.co/F7MWPcPv2Vpython.langchain.com/docs/integratiโ€ฆ
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๐Ÿ™ Expanded @github toolkit

Build agents that can read and comment on GitHub issues, and read files. And, as of the latest release, *open pull requests*.

Great work by GH user Gordon-BP!

Docs: https://t.co/5SIAkgxXoDpython.langchain.com/docs/integratiโ€ฆ
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๐ŸŒธ Expanded support for models run on Petals

Petals lets you run large open source models using a peer-to-peer network of GPU's, so you only run a small portion of the model.

Now with expanded support for LLaMA2 and more!

s/o to GH user karan-vk!

Docs: python.langchain.com/docs/integratiโ€ฆ
๐ŸŽ @Dropbox document loader

Here at ๐Ÿฆœ๐Ÿ”—, our goal is to let you load your documents from anywhere in a few lines of code.

@Dropbox is a great place to store documents.

Making it a great place to load documents from :)

๐Ÿ™ to @RubenBarraganP!

Docs: https://t.co/s2mbk2RYZqpython.langchain.com/docs/integratiโ€ฆ
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More from @LangChainAI

Jul 26
Latest and greatest in ๐Ÿฆœ๐Ÿ”—:

๐ŸŒŠ @MLflow AI Gateway chat models
๐Ÿ“ @LocalAI_API Embedding models
๐Ÿ” Agent iterators

Allow us to explain (a ๐Ÿงต):
๐ŸŒŠ @MLflow AI Gateway chat models

AI Gateway makes it easy for organizations to manage and access all of the models they're using.

๐Ÿ—ฃ๏ธNow supporting chat models!

Docs: https://t.co/LuEt4YFKlBpython.langchain.com/docs/integratiโ€ฆ
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๐Ÿ“ @LocalAI_API Embedding models

LocalAI lets your run LLMs, embedding models and others locally. And its drop-in replacement interface for OpenAI makes it super easy to get off the ground.

Use LocalAI embeddings in ๐Ÿฆœ๐Ÿ”— thanks to @mudler_it!

Docs: https://t.co/xDyNBrIovrpython.langchain.com/docs/integratiโ€ฆ
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Read 4 tweets
Jul 25
The latest features ๐Ÿฆœ๐Ÿ”—:

๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Ensemble retrieval
๐Ÿ“Š @etherscan document loader
โžฐ @activeloopai DeepLake self query retriever
๐Ÿฅ‘ @arangodb graph QA chain

Let's dive in ๐ŸŠ:
๐Ÿ“Š @etherscan document loader

Load in many different types of Ethereum Mainnet transaction histories using EtherScan.

Big s/o to @glazecl for the addition!

Docs: https://t.co/hev9D0u8bzpython.langchain.com/docs/integratiโ€ฆ
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โžฐ @activeloopai DeepLake self query retriever

Wrap the DeepLake vector store in a retrieval system that can translate natural language queries to DeepLake-compatible structured queries, including metadata filters.

s/o to GH user adolkhan!

Docs: https://t.co/aWcoUGTPyrpython.langchain.com/docs/modules/dโ€ฆ

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Read 5 tweets
Jul 24
๐Ÿ“š Documentation Improvements ๐Ÿ“š

We've been working hard to make our docs better. This is an ongoing effort, so if you have specific feedback or requests, please let us know.

Here's what we've done in the past week:

a ๐Ÿงต

1/n
Unified JS and Python structure

We've unified the structured of the JS and Python docs, so that they broadly share the same terms and organization, making it clear where there's parity.

JS:
Python: https://t.co/8gnFfZhuVP

2/n https://t.co/8Z5VKMZg30js.langchain.com/docs/get_startโ€ฆ
python.langchain.com/docs/get_startโ€ฆ

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Bubbled up Integrations and Use Cases sections

We've moved our Use Cases and Integrations sections to the top level and flattened them, to cleanly separate conceptual and more applied docs and make it easier to get to the page you're looking for.

3/n

https://t.co/UBnVUK6owppython.langchain.com/docs/integratiโ€ฆ
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Read 6 tweets
Jul 21
Latest in ๐Ÿฆœ๐Ÿ”—:

โš’๏ธ @github agent
๐Ÿ‹๏ธ @predibase LLMs
๐Ÿช Amazon Neptune db

Let's take a look! a ๐Ÿงต:
โš’๏ธ @github agent

Create an agent that can not just write code, but also read from and write to a GitHub repo! (Of course, use with caution!)

s/o to @trevordobbertin for the very cool integration!

Docs: python.langchain.com/docs/modules/aโ€ฆ
๐Ÿ‹๏ธ @predibase LLMs

Predibase enables anyone to train their own models. With the new ๐Ÿฆœ๐Ÿ”— integration, it's now also easy for anyone to take their custom model and start building applications on top of it ๐Ÿ’ช

Big s/o to @AbhayyM for the addition!

Docs: python.langchain.com/docs/modules/mโ€ฆ
Read 4 tweets
Jul 20
The latest in LangChain ๐ŸŽ

๐Ÿฅ‡ Query @Golden knowledge base
โœˆ๏ธ Search flights with @AmadeusITGroup
๐ŸŒŽ Interact with geospatial data vs @geopandas
๐Ÿ—ƒ๏ธ Caching, tracing, tagging, retries, and more with @PortkeyAI

a ๐Ÿงต:
๐Ÿฅ‡ Query @Golden knowledge base

Golden is aiming to build the largest open knowledge graph of entities and topics. Now your agents and chains can access that knowledge.

Thanks to GH user constantinmusca!!

Docs: https://t.co/9S4CT4Jfeipython.langchain.com/docs/modules/aโ€ฆ
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โœˆ๏ธ Search flights with @AmadeusITGroup

Create chains and agents that can find you realtime flight information using the new Amadeus toolkit!

Time for some AI-generated vacations ๐Ÿ˜Ž๐Ÿ–๏ธ

s/o to GH user sdelgadoc for the feature!

Docs: https://t.co/FpqN8fivimpython.langchain.com/docs/modules/aโ€ฆ
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Read 5 tweets
Jul 18
๐Ÿฆœ๐Ÿ› ๏ธย Introducing LangSmith ๐Ÿฆœ๐Ÿ”—

A unified platform to help developers debug, test, evaluate, and monitor their LLM applications.

Integrates seamlessly with LangChain, but doesn't require it. Image
โœ’๏ธBlog

what we built, where weโ€™re going, and how our Alpha partners put LangSmith to use

๐Ÿ™๐Ÿฝ to companies like @klarna @SnowflakeDB, @streamlit @BCG @DeepLearningAI_ @fintual @mendableai @multion_ai & @quivr_brain for helping us shape LangSmith

blog.langchain.dev/announcing-lanโ€ฆ
๐Ÿ—บ๏ธComprehensive User Guide

This walks through how to best use the platform, including connectivity with other companies like:

@openai & @anthropicAI for replaying runs

@thefireworksai for finetuning

@getcontextai for analytics

docs.smith.langchain.com/docs/overview
Read 4 tweets

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