Agent llama index. Sep 25, 2024 · Using llama index vectorstore, embeddings and objectindex, we can list tables of the database and create a table schema for the prompt to MonsterAPI model API to generate suitable SQL query for Building an agent In LlamaIndex, an agent is a semi-autonomous piece of software powered by an LLM that is given a task and executes a series of steps towards solving that task. Source code in llama-index-core/llama_index/core/agent/workflow/multi_agent_workflow. Deploy Agents as Microservices: Deploy your agentic workflows as microservices with llama_deploy (repo) Community-Built Agents: We offer a collection of 40+ agent tools for use with your agent in LlamaHub 🦙. Contrast this with the term "agentic", which generally refers to a superclass of agents, which is any system with LLM decision making in the process. AgentWorkflow (built-in) – declare a set of agents and let AgentWorkflow manage Jul 30, 2024 · from llama_index. Jumpstart your agent with our agent implementations + 30+ tool connectors in LlamaHub or easily write your own. openai import OpenAI from llama_index. llms. tools import FunctionTool from llama_index. py Build LLM-powered agents that can perform complex workflows over your data and services. Program them to perform a wide range of tasks, from performing multi-document comparisons to automating your calendar to synthesizing code. Copied from llama_index. This continuation will provide a practical, hands-on approach, complete with code snippets you can run in Google Colab. The goal of LlamaDeploy is to Multi-agent patterns in LlamaIndex When more than one specialist is required to solve a task you have several options in LlamaIndex, each trading off convenience for flexibility. They are more verbose, and show the reasoning behind certain actions that they take. This page walks through the three most common patterns, when to choose each one, and provides a minimal code sketch for every approach. workflow import AgentWorkflow from llama_index. Jun 26, 2024 · Dive in! llama-agents provides a powerful, flexible framework for building complex multi-agent AI systems. agent import AgentRunner from llama_index. agent. Check out the repo to learn more, especially our library of examples. core. Whether you're prototyping a new idea or scaling to production, llama-agents offers the tools you need to bring your AI vision to life. It is given a set of tools, which can be anything from arbitrary functions up to full LlamaIndex query engines, and it selects the best available tool to complete each 12 Factor Agents Building successful LLM-powered applications with LlamaIndex Based on the popular 12 Factor Agents, discover how to create robust, scalable, and effective LLM-powered applications using the LlamaIndex framework. ReAct agents are also good at complex reasoning tasks and can work with any LLM that has chat or text completion capabilities. With LlamaDeploy, you can build any number of workflows in llama_index and then run them as services, accessible through a HTTP API by a user interface or other services part of your system. huggingface_api import HuggingFaceInferenceAPI from llama_index. from llama_index. tools import FunctionTool Agents In LlamaIndex, we define an "agent" as a specific system that uses an LLM, memory, and tools, to handle inputs from outside users. workflow import ReActAgent, FunctionAgent # define sample Tool def multiply(a: int, b: int) -> int: """Multiply two integers and returns the result integer""" return a * b # initialize llm llm = OpenAI(model="gpt-4o") # initialize agent agent = FunctionAgent( tools=[multiply . LlamaDeploy (formerly llama-agents) is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on workflows from llama_index. openai import OpenAIAgentWorker # Method 2: Initialize AgentRunner with OpenAIAgentWorker May 30, 2024 · In our previous blog (Building AI Agent Desing Using LLM), we discussed the basics of building AI agents using Large Language Models (LLMs). Today, we'll take it a step further and explore how to utilize the LlamaIndex library to create an AI agent. nvmv fuaga ujwe zzjbn dvzx eccm hyh egk fhfi qjnsd