LazyLLM
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LazyLLM is an open-source Python framework designed to simplify the development of intelligent agents powered by large language models. It provides an easy-to-use programmatic interface for creating, testing, and deploying agents with features like conversation memory, tool usage, and customizable workflows. With LazyLLM, developers can orchestrate complex agent behaviors, integrate external tools, and maintain conversation context seamlessly, accelerating the creation of practical AI-driven applications.
AI Platforms & Frameworks
Workflow Automation
#AI assistant
#Chatbot Development
#workflow automation
#API integration
#modular architecture
#conversation memory
#Automation Tools
#synchronous processing
#asynchronous tasks
#Rapid Prototyping
#logging features
#tool orchestration
#custom prompts
#flexible integrations
#conversation context management
#memory management
#reduced code complexity
#Intelligent automation
#software development
#efficient task execution
...
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LazyLLM is an open-source Python framework designed to simplify the development of intelligent agents powered by large language models. It provides an easy-to-use programmatic interface for creating, testing, and deploying agents with features like conversation memory, tool usage, and customizable workflows. With LazyLLM, developers can orchestrate complex agent behaviors, integrate external tools, and maintain conversation context seamlessly, accelerating the creation of practical AI-driven applications.
AI Platforms & Frameworks
Workflow Automation
#AI assistant
#Chatbot Development
#workflow automation
#API integration
#modular architecture
#conversation memory
#Automation Tools
#synchronous processing
#asynchronous tasks
#Rapid Prototyping
#logging features
#tool orchestration
#custom prompts
#flexible integrations
#conversation context management
#memory management
#reduced code complexity
#Intelligent automation
#software development
#efficient task execution
...
Featured
What is LazyLLM?
LazyLL external APIs or custom utilities. Agents execute defined tasks through sequential or branching workflows, supporting synchronous or asynchronous operation. LazyLLM also offers built-in logging, testing utilities, and extension points for customizing prompts or retrieval strategies. By handling the underlying orchestration of LLM calls, memory management, and tool execution, LazyLLM enables rapid prototyping and deployment of intelligent assistants, chatbots, and automation scripts with minimal boilerplate code.
Who will use LazyLLM?
- AI developers
- Software engineers
- Data scientists
- R&D teams
- Automation engineers
How to use the LazyLLM?
- Step1: Install via pip with `pip install lazyllm`.
- Step2: Import LazyLLM modules and configure your LLM provider API key.
- Step3: Define memory components and register custom tools or APIs.
- Step4: Create an Agent class inheriting BaseAgent and implement its run logic.
- Step5: Instantiate the agent, call agent.run(), and monitor output.
- Step6: Use built-in testing utilities to validate behavior and iterate as needed.
Platform
- web
- mac
- windows
- linux
LazyLLM's Core Features & Benefits
The Core Features
- Modular agent architecture
- LLM provider abstraction
- Conversation memory management
- Tool and API integration
- Synchronous and asynchronous workflows
- Logging and testing utilities
- Prompt customization
The Benefits
- Rapid agent prototyping
- Reduced boilerplate
- Flexible LLM integrations
- Enhanced conversation context
- Easy tool orchestration
- Improved maintainability
LazyLLM's Main Use Cases & Applications
- Customer support chatbots
- Data analysis assistants
- Automated report generation
- Workflow automation scripts
- Personal virtual assistants
- Task management bots
FAQs of LazyLLM
LazyLLM Company Information
- LazyLLM
Analytic of LazyLLM
Visit Over Time
Monthly Visits
2.8k
Avg Visit Duration
00:00:32
Page Per Visit
2.55
Bounce Rate
81.13%
Sep 2025 - Nov 2025 All Traffic
Geography
Top 1 Regions
China
100%
Sep 2025 - Nov 2025 Worldwide Desktop Only
Traffic Sources
Direct
73.01%
Referrals
12.19%
Search
10.06%
Social
3.27%
Paid Referrals
0.79%
Mail
0.69%
Sep 2025 - Nov 2025 Desktop Only
LazyLLM Reviews
5/5
LazyLLM's Main Competitors and alternatives?
- LangChain
- Microsoft Semantic Kernel
- Haystack
- Jina AI
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