Layra is an open-source Python agent framework that enables developers to build and orchestrate intelligent LLM agents. It offers modular tool integrations, a planning engine to decompose tasks, memory management to preserve context, and a plugin architecture for external APIs. Layra also supports multi-agent collaboration, allowing agents to work in parallel or hand off tasks seamlessly.
AI Platforms & Frameworks
Workflow Automation
Digital Workers
#LLM agents
#modular integration
#task planning
#memory management
#API plugins
#multi-agent systems
#Rapid Prototyping
#flexible Frameworks
#Scalable Workflows
#contextual conversation
#development tools
#Intelligent automation
#custom functions
#task delegation
#user support agents
#data analysis tools
#work process optimization
#software development
#AI Collaboration
#cloud integration
...
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Layra
Layra is an open-source Python agent framework that enables developers to build and orchestrate intelligent LLM agents. It offers modular tool integrations, a planning engine to decompose tasks, memory management to preserve context, and a plugin architecture for external APIs. Layra also supports multi-agent collaboration, allowing agents to work in parallel or hand off tasks seamlessly.
AI Platforms & Frameworks
Workflow Automation
Digital Workers
#LLM agents
#modular integration
#task planning
#memory management
#API plugins
#multi-agent systems
#Rapid Prototyping
#flexible Frameworks
#Scalable Workflows
#contextual conversation
#development tools
#Intelligent automation
#custom functions
#task delegation
#user support agents
#data analysis tools
#work process optimization
#software development
#AI Collaboration
#cloud integration
...
Featured
What is Layra?
Layra is designed to simplify developing LLM-powered agents by providing a modular architecture that integrates with various tools and memory stores. It features a planner that breaks down tasks into subgoals, a memory module for storing conversation and context, and a plugin system to connect external APIs or custom functions. Layra also supports orchestrating multiple agent instances to collaborate on complex workflows, enabling parallel execution and task delegation. With clear abstractions for tools, memory, and policy definitions, developers can rapidly prototype and deploy intelligent agents for customer support, data analysis, RAG, and more. It is framework-agnostic toward modeling backends, supporting OpenAI, Hugging Face, and local LLMs.
Who will use Layra?
- AI developers
- Data scientists
- Software engineers
- Startups building AI products
- Research teams exploring LLM agent architectures
How to use the Layra?
- Step1: Install Layra via pip (pip install layra)
- Step2: Import the Layra modules (from layra import Agent, Tool)
- Step3: Define custom tools or plugin functions
- Step4: Configure the Agent with your LLM model, tools, memory, and planner
- Step5: Run the agent using agent.run(task) or agent.invoke(input)
- Step6: Monitor outputs and iterate on tool definitions or planner settings
- Step7: Deploy your agent within your application or server environment
Platform
- mac
- windows
- linux
Layra's Core Features & Benefits
The Core Features
- Modular tool integration
- Planning engine for task decomposition
- Memory management for context preservation
- Plugin system for external APIs
- Multi-agent orchestration
- Framework-agnostic model support (OpenAI, Hugging Face, local LLMs)
The Benefits
- Rapid prototyping of LLM agents
- Easy extension with custom tools
- Scalable multi-agent workflows
- Maintainable and modular codebase
- Flexibility across environments and models
Layra's Main Use Cases & Applications
- Customer support automation
- Retrieval-Augmented Generation workflows
- Automated data analysis pipelines
- Multi-step question answering agents
- Collaborative planning and task delegation
FAQs of Layra
Layra Company Information
Layra Reviews
5/5
Layra's Main Competitors and alternatives?
- LangChain
- AutoGen
- LlamaIndex
- AutoAgents (Hugging Face)
- Microsoft Semantic Kernel
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