LazyCraft - An open-source AI Agent application development and management platform

What is LazyCraft?

LazyCraft is an open-source AI Agent application development and management platform built by SenseTime based on its open-source framework LazyLLM. It helps developers quickly build and deploy large-scale model applications with low barriers to entry and low cost. The platform provides a closed-loop experience across the entire process from application creation, debugging, deployment to monitoring, and supports low-code, component-based application orchestration. LazyCraft has built-in model management functions, covering dataset management, model fine-tuning, and inference services. It supports multi-tenancy, multiple workspaces, and fine-grained access control, and is compatible with various vector libraries and RAG strategies.

LazyCraft's main functions

• Application Development and ManagementIt provides a low-code development environment that supports the rapid creation, debugging, deployment, and monitoring of applications, enabling closed-loop management throughout the entire process.
• Model ManagementBuilt-in model management features support dataset management, model fine-tuning, and inference services, helping users optimize model performance.
• Knowledge base orchestrationIt supports custom knowledge base orchestration, allowing users to flexibly configure the knowledge base and improve the intelligence and accuracy of the application.
• Multi-tenancy and access controlIt supports multi-tenancy and multiple workspaces, provides fine-grained access control, and meets enterprise-level development and management needs.
• Model EvaluationIt provides scientific model evaluation tools to help users compare the effects of models before and after fine-tuning and optimize model selection.
• Vector library and RAG strategyIt is compatible with multiple vector libraries and RAG strategies, and supports flexible data retrieval and application expansion.
• Component-based orchestrationIt supports component-based application orchestration, allowing users to quickly build complex applications through drag-and-drop and configuration.

How to use LazyCraft

• Cloning code: via command git clone https://github.com/LazyAGI/LazyCraft.git Clone the project code to your local machine, and then navigate to the project directory.
• Start service: Entering the project docker Directory, using commands docker-compose up -d Start the service. If you need to use the local model and fine-tuning features, you must first edit... docker-compose.yml File, cancel cloud-service Service notes.
• Access ServiceAfter the service starts successfully, access it through a browser. http://127.0.0.1:30382Use the default account admin and password LazyCraft@2025 Log in.
• Application creation and managementAfter logging in, you can create, debug, publish, and monitor applications on the platform. You can also manage users and workspaces and set permissions for different users.
• Model Management and Fine-tuningThe platform supports dataset management, model fine-tuning, and inference services, allowing users to optimize and evaluate models.

LazyCraft's project address

• Github repositoryhttps://github.com/LazyAGI/LazyCraft

Application scenarios of LazyCraft

• Enterprise application developmentEnterprises can use LazyCraft to quickly build and deploy large-scale model-based applications, such as intelligent customer service and automated office tools, to improve work efficiency and user experience.
• Smart office assistantDevelop an intelligent office assistant to enable functions such as document processing, email categorization, and schedule management, helping employees complete their daily work tasks more efficiently.
• Intelligent Customer Service SystemBuild intelligent customer service applications to automatically answer common questions, provide customer support, reduce the cost of manual customer service, and improve customer satisfaction.
• Content creation and generationIt is used to generate text, images, videos and other content, helping creative workers to quickly produce high-quality creative content, such as copywriting and design sketches.
• Education and TrainingDevelop intelligent education tools, such as personalized learning recommendation systems and automatic Q&A assistants, to improve teaching effectiveness and learning experience.
• Data Analysis and ReportingIt generates data analysis reports, market research reports, etc., quickly extracts key information, and assists in decision-making.