@togethercompute Embeddings Today we’re excited to announce the new langchain-together Python package, which has connections to Together’s LLM and Embeddings endpoints. This is the easiest way to access the next-gen embedding models their team has been developing. Learn
@langchain
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Ally and LangChain Enable PII Masking for GenAI Compliance
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@Ally and @langchain collaborate to bring PII masking to the LangChain typescript package — paving the path for more genAI adoption, in a compliant and safe manner. Read more on the blog!
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LangChain v0.1.0 Launches 700 Integrations for Production
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LangChain v0.1.0 Highlight: Integrations With nearly 700 integrations, LangChain makes it easy to get started no matter your tech stack As part of v0.1.0, we've made some changes to the package architecture to make our partnerships more stable and production ready We
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LangGraph Enables Streaming for Language Agent Construction
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Streaming with LangGraph Yesterday, we introduced LangGraph as way to construct language agents as graphs Because this is built on LangChain, it comes with the ability to stream intermediate steps as well as tokens Check it out: https://
github.com/langchain-ai/l
anggraph
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LangChain v0.1.0 Launches with LangSmith Observability Features
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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
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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