LLM-Agent is an open-source Python library that simplifies creation of AI agents using large language models, offering built-in memory, custom tool integration, and multi-step task planning for automated workflows.
AI Platforms & Frameworks
Tool Libraries
#AI Agents
#Large Language Models
#Task Automation
#conversation memory
#Dynamic Prompts
#Python development
#Workflow-Management
#data retrieval
#report generation
#Open-source tools
#custom APIs
#agent orchestration
#multi-step reasoning
#intelligent agents
#extensible frameworks
#asynchronous execution
#Developer community
#task-oriented design
#reusable components
#agent development
...
Promote this Tool
Update this Tool
LLM-Agent
LLM-Agent is an open-source Python library that simplifies creation of AI agents using large language models, offering built-in memory, custom tool integration, and multi-step task planning for automated workflows.
AI Platforms & Frameworks
Tool Libraries
#AI Agents
#Large Language Models
#Task Automation
#conversation memory
#Dynamic Prompts
#Python development
#Workflow-Management
#data retrieval
#report generation
#Open-source tools
#custom APIs
#agent orchestration
#multi-step reasoning
#intelligent agents
#extensible frameworks
#asynchronous execution
#Developer community
#task-oriented design
#reusable components
#agent development
...
Featured
What is LLM-Agent?
LLM-Agent is a lightweight, extensible framework for building AI agents powered by large language models. It provides abstractions for conversation memory, dynamic prompt templates, and seamless integration of custom tools or APIs. Developers can orchestrate multi-step reasoning processes, maintain state across interactions, and automate complex tasks such as data retrieval, report generation, and decision support. By combining memory management with tool usage and planning, LLM-Agent streamlines the development of intelligent, task-oriented agents in Python.
Who will use LLM-Agent?
- Python developers
- AI researchers
- Automation engineers
- Chatbot builders
- Tech startups
How to use the LLM-Agent?
- Step1: Install via pip: pip install llm_agent
- Step2: Set your LLM API key in environment variables
- Step3: Import `Agent` and define tool functions
- Step4: Create memory and prompt template objects
- Step5: Initialize Agent with tools, memory, and model config
- Step6: Call `agent.run(prompt)` to execute the agent workflow
Platform
- mac
- windows
- linux
LLM-Agent's Core Features & Benefits
The Core Features
- Multi-step reasoning and task planning
- Conversation memory management
- Custom tool and API integration
- Dynamic prompt templates
- Asynchronous execution support
The Benefits
- Accelerates agent development
- Enhances maintainability and reusability
- Supports extensible tool ecosystems
- Facilitates complex workflow automation
- Open-source and community-driven
LLM-Agent's Main Use Cases & Applications
- Customer support chatbots with context awareness
- Automated data retrieval and report generation
- Virtual assistants for scheduling and reminders
- Decision-support agents for analytics tasks
FAQs of LLM-Agent
LLM-Agent Company Information
LLM-Agent Reviews
5/5
LLM-Agent's Main Competitors and alternatives?
- LangChain
- AutoGPT
- Microsoft Semantic Kernel
- Agentic
You may also like:
AI design agent automates workflow creating images, videos, 3D models up to 10x faster.
AI-driven chatbot for top OnlyFans creators.
Aixbt is a tokenized AI Agent optimizing revenue across applications.
theGist AI Workspace unifies work apps with AI for improved productivity.
Generate brand visuals and copy using AI to boost e-commerce sales.
GPTConsole is an AI agent designed for streamlined conversation and task automation.
GenSphere is an AI agent that automates data analysis and provides insights for informed decision-making.
Nullify automates the entire AppSec program for security teams using AI-driven solutions.
Refly.AI empowers non-technical creators to automate workflows using natural language and a visual canvas.
Langbase is an AI agent that generates and analyzes natural language content efficiently.
AiTerm: AI Terminal Assistant converting natural language to commands.
Generate intriguing facts effortlessly with our AI-powered tool.
Automate your job applications and find the perfect job with AI technology.
Intellika AI enables seamless automation of data analysis and reporting for businesses.
ScholarRoll helps students find and apply for scholarships easily.
OneReach AI simplifies interactions by automating customer engagement through intelligent messaging.
Phoenix AI Assistant helps streamline tasks using intelligent automation and personalized support.
Flowith is a canvas-based agentic workspace which offers free 🍌Nano Banana Pro and other effective models...
AI Library is a developer platform for building and deploying customizable AI agents using modular chains and tools.
A Python-based framework implementing flocking algorithms for multi-agent simulation, enabling AI agents to coordinate and navigate dynamically.
An open-source framework enabling autonomous LLM agents with retrieval-augmented generation, vector database support, tool integration, and customizable workflows.
An AI agent template showing automated task planning, memory management, and tool execution via OpenAI API.
Pipe Pilot is a Python framework that orchestrates LLM-driven agent pipelines, enabling complex multi-step AI workflows with ease.
Open-source repository providing practical code recipes to build AI agents leveraging Google Gemini's reasoning and tool usage capabilities.
RModel is an open-source AI agent framework orchestrating LLMs, tool integration, and memory for advanced conversational and task-driven applications.
An open-source framework implementing cooperative multi-agent reinforcement learning for autonomous driving coordination in simulation.
Python library with Flet-based interactive chat UI for building LLM agents, featuring tool execution and memory support.
Agentic Workflow is a Python framework to design, orchestrate, and manage multi-agent AI workflows for complex automated tasks.
Clone, Design, and Create Expressive AI Voices in Seconds, with Perfect Sound Effects and Music.
A GitHub demo showcasing SmolAgents, a lightweight Python framework for orchestrating LLM-powered multi-agent workflows with tool integration.
A Python framework for easily defining and executing AI agent workflows declaratively using YAML-like specifications.
OpenSpiel provides a library of environments and algorithms for research in reinforcement learning and game theoretic planning.
A Pythonic framework implementing the Model Context Protocol to build and run AI agent servers with custom tools.
pyafai is a Python modular framework to build, train, and run autonomous AI agents with plug-in memory and tool support.
LangGraph enables Python developers to construct and orchestrate custom AI agent workflows using modular graph-based pipelines.
A Python wrapper enabling seamless Anthropic Claude API calls through existing OpenAI Python SDK interfaces.
Agent Adapters provides pluggable middleware to integrate LLM-based agents with various external frameworks and tools seamlessly.
Java-Action-Storage is a LightJason module that logs, stores, and retrieves agent actions for distributed multi-agent applications.
LinkAgent orchestrates multiple language models, retrieval systems, and external tools to automate complex AI-driven workflows.
All-in-one AI video creation studio that turns any text and images into full videos up to 30 minutes.