Tiempo de lectura: 2 minutosVamos a generate a first agent with Claude Code and it will run automatically every hour with a cron and upload the generated content to GitHub. Crea the folder of your agent: mkdir -p ~/motivational-agent/md mkdir -p ~/motivational-agent/data cd ~/motivational-agent The final structure will be: motivational-agent/ │ ├─ md/ │ └─ claude.md # context and … Read more
Tiempo de lectura: < 1 minutoWe will learn today how to install Claude Code on Windows. Claude Code is a tool developed by Anthropic that acts as an intelligent agent for programmers. It’s not an AI model itself, but rather a CLI/Interface that communicates with advanced language models, such as those from the Claude family, to help you generate, review … Read more
Tiempo de lectura: 3 minutosWe will build a LangGraph agent with Python and no LLM as an example for a basic tutorial. Our agent will do the following: You receive a user’s question Determine if you need to search for information (simulated) Respond with or without searching Save state between nodes First, we will install the library: pip install … Read more
Tiempo de lectura: < 1 minutoWe need to understand that not all models are created equal. The main difference between general models and instructional models. General models Ejemplo:Pregunta: “Explain how a neural network works”Response from a general model: can give an extensive explanation, include unnecessary concepts or jump topics. Instruct Models Ejemplo:Pregunta: “Explain how a neural network works step by … Read more
Tiempo de lectura: 2 minutosEnable GPU access is essential if we need to start a LLM model and use GPU with VRAM. Previous requirements Please ensure you have an NVIDIA GPU installed on your machine with the drivers installed and updated. Check using: nvidia-smi You should see your GPU and driver version. Additionally, Docker must be installed. NVIDIA Container … Read more
Tiempo de lectura: 2 minutosIt’s an inference server optimized (uses paged attention) that supports models like Llama 3, Mistral, Gemma, Phi, Qwen, etc. This offers an OpenAI-compatible API, perfect for easy integration. We will create the Docker Compose that allows us to deploy it: File: docker-compose.yml version: “3.9” services: vllm: image: vllm/vllm-openai:latest container_name: vllm restart: unless-stopped ports: – “8000:8000” … Read more
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
