Announcing LangSmith is now a transactable offering in the Azure Marketplace Today, we’re thrilled to announce that enterprises can purchase LangSmith in the Azure Marketplace as an Azure Kubernetes Application. LangSmith is a unified DevOps
Empowering Development with FlowTestAI: Bridging APIs and LLMs for Enhanced Testing and Privacy Editor's note: we're excited to highlight this blog from FlowTestAI. FlowTestAI is an exciting startup building on top of LangChain. Specifically,
Tool Calling with LangChain TLDR: We are introducing a new tool_calls attribute on AIMessage. More and more LLM providers are exposing API’s for reliable tool calling. The
LangFriend: a Journal with Long-Term Memory One of the concepts we are most interested in at LangChain is memory. Whenever we are interested in a concept, we like to build an
Open Source Extraction Service Earlier this month we announced our most recent OSS use-case accelerant: a service for extracting structured data from unstructured sources, such as text and PDF
LangChain Integrates NVIDIA NIM for GPU-optimized LLM Inference in RAG Roughly a year and a half ago, OpenAI launched ChatGPT and the generative AI era really kicked off. Since then we’ve seen rapid growth
Enhancing RAG-based application accuracy by constructing and leveraging knowledge graphs A practical guide to constructing and retrieving information from knowledge graphs in RAG applications with Neo4j and LangChain Editor's Note: the following is
Benchmarking Query Analysis in High Cardinality Situations Several key use cases for LLMs involve returning data in a structured format. Extraction is one such use case - we recently highlighted this with
Iterating Towards LLM Reliability with Evaluation Driven Development Editor's Note: the following is a guest blog post from the Devin Stein, CEO of Dosu. Dosu is an engineering teammate that helps
Use Case Accelerant: Extraction Service Today we’re excited to announce our newest OSS use-case accelerant: an extraction service. LLMs are a powerful tool for extracting structured data from unstructured
JSON agents with Ollama & LangChain Learn to implement an open-source Mixtral agent that interacts with a graph database Neo4j through a semantic layer Editor's note: This post is
Supercharging If-Statements With Prompt Classification Using Ollama and LangChain Editor's Note: Andrew Nguonly has been building one of the more impressive projects we've seen recently - an LLM co-pilot for