LangGraph

LangGraph

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GitHub - bytedance/deer-flow: DeerFlow is a community-driven framework for deep research, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.
GitHub - bytedance/deer-flow: DeerFlow is a community-driven framework for deep research, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.
DeerFlow is a community-driven framework for deep research, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source communit...
·github.com·
GitHub - bytedance/deer-flow: DeerFlow is a community-driven framework for deep research, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.
LangChain (@LangChainAI) on X
LangChain (@LangChainAI) on X
Understanding multi-agent handoffs Handoffs are a central concept in multi-agent systems. LangGraph swarm is built on them. But, they can be hard to understand. Here, we break-down the swarm handoff mechanism. 📽️: https://t.co/YkSCFeg9A8
·x.com·
LangChain (@LangChainAI) on X
How to Count Tokens - Tokenization With Tiktoken.
How to Count Tokens - Tokenization With Tiktoken.
Counting tokens is a useful task in natural language processing (NLP) that allows us to measure the length and complexity of a text. The two important use cases for counting the tokens are: controlling the length of the prompt - models has limit …
·safjan.com·
How to Count Tokens - Tokenization With Tiktoken.
Agent Protocol: Interoperability for LLM agents
Agent Protocol: Interoperability for LLM agents
LangGraph is a multi-agent framework. This means not only interacting with other LangGraph agents, but all other types of agents as well, regardless of how they are built. Today we are taking a few steps to to build towards this vision. We are announcing: * Agent Protocol: a common interface for
·blog.langchain.dev·
Agent Protocol: Interoperability for LLM agents
Local LangGraph Agents with Llama 3.1 + Ollama
Local LangGraph Agents with Llama 3.1 + Ollama
LangGraph is one of the most versatile Python libraries for building AI agents. We can combine LangChain's LangGraph with Ollama and Llama 3.1 to build highl...
·youtube.com·
Local LangGraph Agents with Llama 3.1 + Ollama
Memory for agents
Memory for agents
At Sequoia’s AI Ascent conference in March, I talked about three limitations for agents: planning, UX, and memory. Check out that talk here. In this post I will dive more into memory. See the previous post on planning here, and the previous posts on UX here, here, and here.
·blog.langchain.dev·
Memory for agents
🧠I wrote some thoughts on memory for agents!
🧠I wrote some thoughts on memory for agents!
We released a bunch of new functionality for memory in LangGraph, and in doing so we thought hard about what memory actually means, and was is useful today Some highlights 👇 🛃Memory is application specific The best memory today… — Harrison Chase (@hwchase17)
·x.com·
🧠I wrote some thoughts on memory for agents!