LangChain Agents — Topic Summaries
AI-powered summaries of 7 videos about LangChain Agents.
7 summaries
LangChain Agents - Joining Tools and Chains with Decisions
LangChain agents let a language model choose—at runtime—which tools to use (or whether to use any tools at all) to answer a user’s question. Instead...
Build AI Assistant With MCP Servers And Tools Using LangChain And Groq
Model Context Protocol (MCP) is positioned as a way to connect large language models to third-party capabilities—like browser automation and hotel...
Understanding ReACT with LangChain
ReACT (Reasoning and Action) is a prompting-and-agent pattern designed to make large language models do multi-step problem solving by alternating...
Building Custom Tools and Agents with LangChain (gpt-3.5-turbo)
Custom tools are the key lever for making LangChain conversational agents more useful—and the biggest practical lesson is that tool use often...
Building a LangChain Custom Medical Agent with Memory
A LangChain “medical advice” agent can be built to answer questions using a site-restricted search (WebMD) and to carry context across multiple turns...
OpenAI Functions + LangChain : Building a Multi Tool Agent
OpenAI’s function-calling system, wired through LangChain, can turn a plain chat model into a finance assistant that reliably selects the right API...
LangChain Agents: Build Personal Assistants For Your Data (Q&A with Harrison Chase and Mayo Oshin)
LangChain agents are built around a simple but powerful idea: use a language model as a reasoning engine, then let it reliably choose and run...