RAG From Scratch: Query Translation (Multi-Query) Our RAG From Scratch video series walks through impt RAG concepts in short / focused videos w/ code. Over the next few days we'll release videos focused on Query Translation, starting with Multi-Query. Problem: User queries
@langchain
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Dataherald: Open-Source Leader in Text-to-SQL Technology
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How Dataherald Makes Natural Language to SQL Easy Text-to-SQL is a HUGE use case, and @DataheraldCo is the open-source leader in the space This is a great look behind the curtains to see what makes it tick. Blog: https://
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OSS Retrieval Agent with LangChain and Mistral AI
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📖 OSS Retrieval Agent for your Documents 🎥
— LangChain (@LangChain) 14 février 2024
Dive into LangChain Founding Engineer @eyfriis 's latest video showcasing a build with the `retrieval-agent-fireworks` template.
Supercharge a @MistralAI (hosted on @FireworksAI_HQ) agent with vectorstore retrieval using @nomic_ai… https://t.co/3dN6Geicn3 pic.twitter.com/LsD2Uk0CLaOSS Retrieval Agent for your Documents Dive into LangChain Founding Engineer @eyfriis 's latest video showcasing a build with the `retrieval-agent-fireworks` template. Supercharge a @MistralAI (hosted on @FireworksAI_HQ
) agent with vectorstore retrieval using @nomic_ai -
LangChain Pinecone Integration Simplifies Vector Database Connections
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LangChain @pinecone Check out the new `langchain-pinecone` integration package, which greatly simplifies connecting to your Pinecone indices! Regardless of if you have a new serverless deployment or an existing pod-based one, connecting your index is now a sea breeze.
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LangGraph Enhances Plan-Execute Agents with Flexible Code Control
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6/ This all extends our previous work on plan-and-execute agents. But now with LangGraph, it's more flexible than ever – you own the code!
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Getting Started with LangGraph: Introduction Video
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5/ New to LangGraph? Check out the intro video to get started:
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LLMCompiler: Streaming Tasks as DAG for Immediate Execution
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3/ LLMCompiler
Stream tasks as a DAG. Immediately execute once dependencies are resolved, so you can invoke functions while the planner LLM is still generating output. Based on research of @sehoonkim418 , et. al Python: https://
github.com/langchain-ai/l
anggraph/blob/main/examples/llm-compiler/LLMCompiler.ipynb
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LangSmith: Developing and Evaluating AI Agents
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4/ Developing and evaluating agents like these is easier with easier with LangSmith. Sign up at https://
smith.langchain.com to get started. -
ReWOO: Task Output Assignment for Focused Agent Execution
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2/ ReWOO Assign task outputs to variables that can be explicitly passed to subsequent tasks. Provides more focused context to task executors and makes it easy to fine-tune a planner LLM (since the plan doesn't depend on tool outputs) Based on research of @billxbf
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Plan-and-Execute Agents: Faster LLM-Powered Execution
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Plan-and-Execute Agents We've added new documentation on how to make plan-and-execute style agents using LangGraph. Relative to older agent designs, these agents promise: Faster Execution: fewer calls to large models, and execution of tools while the LLM is still