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scalabilité dans le cloud

  • A FastAPI server to host, manage, and orchestrate AI agents via HTTP APIs with session and multi-agent support.
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    What is autogen-agent-server?
    autogen-agent-server acts as a centralized orchestration platform for AI agents, enabling developers to expose agent capabilities through standard RESTful endpoints. Core functionalities include registering new agents with custom prompts and logic, managing multiple sessions with context tracking, retrieving conversation history, and coordinating multi-agent dialogues. It features asynchronous message processing, webhook callbacks, and built-in persistence for agent states and logs. The server integrates seamlessly with the AutoGen library to leverage LLMs, allows custom middleware for authentication, supports scaling via Docker and Kubernetes, and offers monitoring hooks for metrics. This framework accelerates building chatbots, digital assistants, and automated workflows by abstracting server infrastructure and communication patterns.
    autogen-agent-server Core Features
    • Agent registration API
    • Session lifecycle and context management
    • Message sending and response retrieval
    • Multi-agent conversation orchestration
    • Webhook integration and callbacks
    • Persistent storage for agent states and logs
    • Asynchronous processing and scalability
    • Custom middleware support
  • NPI.ai provides a programmable platform to design, test, and deploy customizable AI agents for automated workflows.
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    What is NPI.ai?
    NPI.ai offers a comprehensive platform where users can graphically design AI agents through drag-and-drop modules. Each agent comprises components such as language model prompts, function calls, decision logic, and memory vectors. The platform supports integration with APIs, databases, and third-party services. Agents can maintain context through built-in memory layers, allowing them to engage in multi-turn conversations, retrieve past interactions, and perform dynamic reasoning. NPI.ai includes versioning, testing environments, and deployment pipelines, making it easy to iterate and launch agents into production. With real-time logging and monitoring, teams gain insights into agent performance and user interactions, facilitating continuous improvement and ensuring reliability at scale.
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