Custom Routes in LangGraph Platform! Extend your LangGraph deployment with custom HTTP endpoints for anything from simple health checks to complete UIs – all in one server. Build persistent, full-stack AI apps in python with a single backend. Tutorial:
@langchain
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LangSmith Adds Metadata Grouping for Experiment Analysis
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📊 You can now group LangSmith experiments by metadata to get valuable insights!
— LangChain (@LangChain) 25 février 2025
We’ve added a new view that allows you to group experiment results by metadata. Compare the performance of your evaluations across different segments (eg. user segments or subject areas) to pinpoint… pic.twitter.com/2nGo2bm7JYYou can now group LangSmith experiments by metadata to get valuable insights! We’ve added a new view that allows you to group experiment results by metadata. Compare the performance of your evaluations across different segments (eg. user segments or subject areas) to pinpoint
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Building Agents with Claude 3.7 Hybrid Reasoning Model
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Building agents with Claude 3.7 Anthropic just released Claude 3.7, a hybrid reasoning model. Here, we share some tips for prompting / usage / configuration of the model. We also show how to build tool-calling agents w/ configurable reasoning. Video: https://
youtu.be/sHcu0YX-1u4 -
LangGraph.js Supervisor: Multi-Agent Hierarchical Systems
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LangGraph.js Supervisor A lightweight library for building hierarchical multi-agent systems with LangGraph – Create a supervisor agent to orchestrate multiple specialized agents – Tool-based handoffs for agent communication – Built with LangGraph.js: comes with
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Build Controllable AI Agents with LangGraph.js MongoDB
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Tomorrow, Feb 25th at 8am PT/11am ET — join @codeSTACKr (
@MongoDB
) & @Hacubu (
@langchain
) to explore LangGraph.js + MongoDB for AI agents. Learn to: Integrate LangGraph.js and MongoDB Build a controllable AI agent with LangGraph.js Persist conversation state -
LangChain Atlanta Event with CEO Harrison Chase
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LangChain in Atlanta! Join us this coming Thursday, February 27th for an evening of AI at the Honeywell offices with LangChain CEO, Harrison Chase.
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GenAI Agents Hub: LangChain LangGraph Multi-Agent Systems
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GenAI Agents Hub A comprehensive collection of GenAI agent implementations, from simple bots to complex multi-agent systems. Built with LangChain and LangGraph, this repository empowers developers across business and creative applications. Start building your agents:
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Tool Ahead of Time: JSON-based Tool Calling for LangChain
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Tool Ahead of Time An interesting community package – using JSON generation & parsing to enable tool calling for LangChain models that don't currently support it. Enables usage with `create_react_agent` Check it out
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Embedding Fine-Tuning Guide for RAG Systems
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RAG Embedding Fine-Tuning Guide A practical guide demonstrating embedding model fine-tuning for RAG systems, featuring LangSmith monitoring and RAGAS metrics for performance evaluation. Check out the complete implementation https://
github.com/apatti/AIEBoot
camp/blob/main/09_Finetuning_Embeddings/Fine_tuning_Embedding_Models_for_RAG_using_RAGAS.ipynb
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DeepSeek R1 Implementation with LangChain Azure Integration
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DeepSeek R1 Tutorial Learn to implement DeepSeek's reasoning model using LangChain and Azure AI. This hands-on guide shows you model integration and streaming responses in action. Key features:
– LangChain-Azure integration
– Real-time streaming Watch: