Lagent
Open-source Python framework for LLM-based agents
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What this product helps you do
Lagent gives developers a code-first way to assemble agent workflows around model backends, tools, structured messages, and session memory. Official examples cover ReAct and ReWOO agents, function tools, web demos, local model runtimes, and hosted model APIs.
Problems it solves
- Agent workflows need reusable message and memory abstractions
- Developers need to connect tools to several model backends
- Multi-agent message passing becomes difficult to inspect
- Prototype agents need a path from examples to custom Python code
Lagent is a lightweight open-source framework for building LLM-based agents in Python. Its PyTorch-inspired structure treats agents as layers and uses structured AgentMessage objects for communication, memory, aggregation, and inspection.
The project includes agent patterns such as ReAct and ReWOO, tool and action interfaces, model wrappers, memory handling, quickstarts, web demos, and an API reference. It can connect to local inference runtimes or model APIs, so operating costs and deployment requirements depend on the selected backend.
Information
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Lagent is a lightweight open-source framework for building LLM-based agents in Python. Its PyTorch-inspired structure treats agents as layers and uses structured AgentMessage objects for communication, memory, aggregation, and inspection.
The project includes agent patterns such as ReAct and ReWOO, tool and action interfaces, model wrappers, memory handling, quickstarts, web demos, and an API reference. It can connect to local inference runtimes or model APIs, so operating costs and deployment requirements depend on the selected backend.
What this product helps you do
Lagent gives developers a code-first way to assemble agent workflows around model backends, tools, structured messages, and session memory. Official examples cover ReAct and ReWOO agents, function tools, web demos, local model runtimes, and hosted model APIs.
Problems it solves
- Agent workflows need reusable message and memory abstractions
- Developers need to connect tools to several model backends
- Multi-agent message passing becomes difficult to inspect
- Prototype agents need a path from examples to custom Python code
Information
You are leaving botconomy for the provider’s website. Link verified 9/21/2026.
Related AI products
Daizy
Daizy provides AI agents designed to enhance marketing, sales, and research efforts within financial services, automating tasks such as content generation and client engagement to increase productivity.
Eidolon AI
Eidolon is an Apache-2.0 Python SDK and agent server that packages agents as HTTP services, supports agent-to-agent tool calls, and lets developers swap models, retrieval, tools, and other components.
Langflow
Langflow is an MIT-licensed Python framework with a visual editor for assembling agents, retrieval pipelines, tools, models, and APIs, then running or serving the resulting flows.