New SOTA Model @AnthropicAI just launched their new state-of-the-art Claude 3 models, and you can use them from the `langchain-anthropic` package! Stay tuned for multimodal Create an API key here: https://
console.anthropic.com/settings/keys Python guide: https://
python.langchain.com/docs/integrati
ons/chat/anthropic
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@langchain
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Anthropic Launches Claude 3 State-of-the-Art Models with LangChain Integration
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LangGraph: Intuitive Framework for AI Agents Workflow
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LangGraph: An intuitive framework for AI agents Great write up from Mario Bonilla on using a LangGraph "supervisor" agent to do knowledge work in the financial market https://
linkedin.com/pulse/langgrap
h-intuitive-framework-agents-workflow-mario-bonilla-cfa-8ajoe/?trackingId=QtuZFYrgTLHhP3L7ScveRw
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SalesGPT: AI-Driven Sales Assistant with LangChain Intelligence
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SalesGPT: Elevating Sales Conversations with LangChain SalesGPT is an awesome open-source repo that creates an AI-driven sales assistant This blog by @andysingal deep dives into how this agent is created and how to use it Blog: https://
ai.gopubby.com/salesgpt-eleva
ting-sales-conversations-with-langchain-intelligence-a1e1be461ee4
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LLM-based SQL Agent for SAP HANA Database Queries
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Discover the power of LLM based SQL Agent for SAP HANA queries Lots of enterprise data is contained in SAP HANA databases. This great guide by Purankhoeval goes over how to connect a LangChain SQL Agent to these types of databases Blog: https://
medium.com/@purankhoeval/
discover-the-power-of-llm-based-sql-agent-for-sap-hana-queries-4c97343f69e2
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LangChain Query Analysis How-To Guides Released
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Query Analysis How-To Guides We've added a series of how-to guides for some of the trickier parts of query analysis How to add few shot examples?
How to deal with high cardinality categoricals? and more! Check out our new docs here: https://
python.langchain.com/docs/use_cases
/query_analysis/
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Matryoshka Retriever: High Performance Vector Search Technique
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Matryoshka Retriever A recent blog post by @supabase described a new technique for higher performance retrieval, without compromising accuracy. So we've just released a new retriever in LangChain.js which implements this exactly! Use any vector store, and two embedding
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LangChain Matryoshka Retriever Documentation and Supabase Integration
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Read the JS docs: https://
js.langchain.com/docs/modules/d
ata_connection/retrievers/matryoshka_retriever
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Query Analysis Techniques for RAG Systems with LLMs
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Query Analysis In OpenAI's retrieval talk on DevDay, they mention a bunch of strategies they experimented with 3 of these can be classified as **query analysis** a RAG technique that is becoming popular to do with LLMs We've added a docs deep-dive on this We cover six
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Advanced RAG Series: Indexing Optimization Techniques
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Advanced RAG series: Indexing Indexing is a huge part or RAG. Lot's of different stuff to optimize: 1. Chunk Optimization
2. Multi-representation indexing
3. Specialized Embeddings
4. Hierarchical Indexing Great article by @divyanshu_van diving into all these topics! Blog: -
Models Support Function Calling Documentation Updates
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As more and more models support function calling, we're updating our docs to highlight them all! Function calling