Whatsapp LangGraph Agent Integration is an example implementation showcasing the deployment of LangGraph-based AI agents on WhatsApp messaging. It uses Python and FastAPI to expose webhook endpoints for Twilio’s WhatsApp API, automatically parsing incoming messages into the agent’s graph workflow. The agent supports context preservation across sessions with built-in memory nodes, tool invocation for specific tasks, and dynamic decision-making via LangGraph’s modular nodes. Developers can customize graph definitions, integrate additional external APIs, and manage conversational state seamlessly. This integration acts as a template, illustrating message routing, response generation, error handling, and easy scalability to build complex interactive chatbots on WhatsApp.

Aibot is an extensible AI agent framework in Python that provides a command-line interface to configure and run custom chatbots. It supports multi-model APIs (e.g., OpenAI, Anthropic), conversation history management, persistent memory, and plugin-based tool integration. Developers can define skills, workflows, and custom actions, enabling automated tasks, knowledge retrieval, and dynamic responses. With built-in commands for initialization, configuration, and execution, Aibot streamlines the development and deployment of intelligent conversational agents.