LangChain v0.1.0 Highlight: Observability free LangSmith access code for first 500 redemptions, read below When building complex LLM applications, you're application logic now contains a non-deterministic model at the center of it, often heavily controlling the flow of
@langchain
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LangChain v0.1.0 YouTube Series: Seven Components Tutorial
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LangChain v0.1.0 YouTube Series We released a series of videos walking through the seven main components of our new v0.1.0 release We also added notebooks (in both Python and JS) for a hands-on coding experience for all of them YouTube playlist: https://
youtube.com/playlist?list=
PLfaIDFEXuae0gBSJ9T0w7cu7iJZbH3T31
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Local Models Quickstart: Running OSS Models in Chains
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Local Model Quickstart One big point of feedback we've gotten is people want more documentation for how to use local models in chains As part of v0.1.0 we've updated our getting started to now highlight running OSS models! We also have a section on RAG with local models,
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LangGraph: Building Language Agents as Graphs
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LangGraph Building language agents as graphs https://
github.com/langchain-ai/l
anggraph
… The "one more thing" from our LangChain v0.1.0 announcement is introducing LangGraph to the world We've been alpha testing this over the past six months as a better way to create LLM agents -
LangChain v0.1.0 Released: Stable Version for AI Development
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LangChain v0.1.0 After a year of development, we've released LangChain v0.1.0 Read the full blog here: https://
blog.langchain.dev/langchain-v0-1
-0/
… After talking with the users and developers, we released this stable version and focused the library on a few core areas: Observability: -
RAGatouille LangChain Integration Simplifies Advanced Retrieval
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Improved RAGatouille LangChain Integration We really enjoyed @bclavie
's new RAGatouille library. It makes advanced retrieval techniques (like ColBERT – more on that below) really easy to use We've worked on a tighter integration to make it *super simple* to use RAGatouille -
Unstructured Data Ingestion with LangChain.js Tutorial
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Our friends at @UnstructuredIO are a great way to ingest unstructured data @devdigest recently made an awesome tutorial showing how to us them with LangChain.js. Shows how to do question-answering over third party data Check it out! https://
youtube.com/watch?v=2B161D
pvyxw
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Web Scraping Wikipedia Using LLM Agents Tutorial
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How to Web Scrape Wikipedia with LLM Agents We this tutorial by Kenneth Leung. It shows how to take a CSV of entities and then use an agent to populate information about those entities by looking things up on Wikipedia Many real-world use cases! https://
medium.datadriveninvestor.com/how-to-web-scr
ape-wikipedia-using-llm-agents-f0dba8400692
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GPT-4V LangChain Elasticsearch Handwritten Letter Analysis
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Santa GenAI: Deciphering Handwritten Christmas Letters with LangChain and Elasticsearch Great tutorial from @alexsalgadoprof that: 1. Uses GPT-4V to analyze an image an say whats in it
2. Extracts structured information as JSON from that analysis https://
discuss.elastic.co/t/dec-22nd-202
3-en-santa-claus-meets-genai-deciphering-handwritten-christmas-letters-with-llm-langchain-and-elasticsearch/347311
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LangChain PDF Receipt Matching for Accounting Automation
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This is a really cool project
— LangChain (@LangChain) 6 janvier 2024
Uses LangChain to parse PDFs so that you can match receipts against transactions for seamless accounting
Good to way to automate some annoying and time consuming tasks https://t.co/yMJUXuywJRThis is a really cool project Uses LangChain to parse PDFs so that you can match receipts against transactions for seamless accounting Good to way to automate some annoying and time consuming tasks