We’re thrilled to be MongoDB's AI App Framework Partner of the Year! LangChain is the #1 choice for developers building GenAI apps. We have immense gratitude for our community of over 2,000 contributors who have helped us shape the LLM application development space, and are
@langchain
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LangChain Weekly Release: LangSmith Improvements and LangGraph Tutorials
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LangChain Release Notes, Week of 4/29 Improved regression testing experience in LangSmith Hotkeys and mustache support in LangSmith New Evaluations content Three new video tutorials using LangGraph Community created content! Read it all here:
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Build RAG System Llama 3B-Instruct PDFs FAISS
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Build a RAG system with Llama 3B-Instruct for your PDFs Uses API for partitioning & chunking, FAISS for vector store, huggingface for the model It's a collab notebook so it's easy to get started! Thanks @mariaKhalusova for a great resource! https://
colab.research.google.com/drive/1BJYYyrP
Ve0_9EGyXqeNyzmVZDrCRZwsg?usp=sharing#scrollTo=Y2m2l-vt_RSp
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LangSmith Achieves 30% Accuracy Improvement Without Prompt Engineering
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How Dosu used LangSmith to achieve a 30% accuracy improvement with no prompt engineering One of the goals of LangSmith is to help teams set up a data flywheel. By capturing LLM outputs alongside user feedback, we can help developers automatically use that feedback to improve
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LangSmith Regression Testing Improvements for LLM Applications
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🧮Regression testing your LLM applications
— LangChain (@LangChain) 1 mai 2024
We've made big improvements to the "regression testing" flow in LangSmith to allow you to quickly spot changes in your application's performance:
🟥Automatically highlighting changes
⛪️Filter to changed datapoints
📄Different ways of… pic.twitter.com/ZxnE6pHAyiRegression testing your LLM applications We've made big improvements to the "regression testing" flow in LangSmith to allow you to quickly spot changes in your application's performance: Automatically highlighting changes
Filter to changed datapoints
Different ways of -
LangSmith RAG Evaluation Video Series Launch
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LangSmith Evaluations: RAG Evaluation (Document Retrieval)
— LangChain (@LangChain) 30 avril 2024
Evaluations can accelerate LLM app development, but it can be challenging to get started. We've kicked off a new video series focused on evaluations in LangSmith.
This is the 14th video in our series focusing… pic.twitter.com/P1qVbnJxm8LangSmith Evaluations: RAG Evaluation (Document Retrieval) Evaluations can accelerate LLM app development, but it can be challenging to get started. We've kicked off a new video series focused on evaluations in LangSmith. This is the 14th video in our series focusing
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Perplexica: Open-Source AI-Powered Search Engine Tool
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Perplexica – An AI-powered search engine Perplexica is an open-source AI-powered searching tool or an AI-powered search engine that goes deep into the internet to find answers. Built with LangChain, this is a great resource for getting started! https://
github.com/ItzCrazyKns/Pe
rplexica
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AutoHyDE: Advanced RAG Technique for LLM Enhancement
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AutoHyDE: Making HyDE Better for Advanced LLM RAG A fun article exploring new and creative RAG techniques Builds upon HyDE to add in keyword generation, clustering, etc Implements a LangChain Embedder which makes it easy to try out in your pipeline https://
towardsdatascience.com/autohyde-makin
g-hyde-better-for-advanced-llm-rag-619e58cdbd8e
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LangChain Tool Calling Enables Cross-Model Agent Development
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"LangChain Tool Calling feature just changed everything" We recently added a common interface for tool calling across model providers This makes it easy to build agents that work across models Watch @EdenEmarco177 explain why this is a big deal https://
youtube.com/watch?v=dj8Yqi
E1Omc
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Upstage releases LangChain integration package with Solar models
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Upstage integration package @upstageai has released their `langchain-upstage` integration package, including their Solar chat model, embedding model, a task-specific groundedness check model, and a layout analysis document loader. Check them out here: