LangChain

Tiempo de lectura: < 1 minutoToday we are going to see what types of AI agents are available with LangChain. ➡️ The most used. What it does:The LLM decides which tool to use at each step based on only the textual description of the tools.No needs examples or prior instances. For: Typical usage example: agent = initialize_agent( tools=mis_tools, llm=llm, agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION, … Read more

Tiempo de lectura: < 1 minutoWe will today make our AI agent have a tool that allows it to perform internet searches. First, we will install the necessary libraries: pip install langchain langchain_community pip install ddgs NOW INITIALIZING CONNECTION WITH OLLAMA SERVER (https://devcodelight.com/ollama-con-llama-3-2-in-docker/) from langchain_community.chat_models import ChatOllama from langchain_core.prompts import ChatPromptTemplate # … other imports … # ⚠️ YOUR REMOTE … Read more

Tiempo de lectura: 3 minutosToday we are going to learn how to use Tools in LongChain to create AI Agents. To execute this tutorial well, I recommend visiting the one on how to install LangChain. First: What are Tools in LangChain? In the context of a LangChain Agent, a Tool is any external function or resource that the Large … Read more

Tiempo de lectura: < 1 minutoWhat is a «Chain» (Link) in LangChain? It is a specific instruction: llm_chain = prompt | llm | output_parser An example perfect and modern of what means a Chain in the architecture of LangChain (specifically using the LangChain Expression Language or LCEL). A Chain (A Chain) in LangChain is the structured sequence of steps or … Read more