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AIのメモリ管理

  • GPTMe is a Python-based framework to build custom AI agents with memory, tool integration, and real-time APIs.
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    What is GPTMe?
    GPTMe provides a robust platform for orchestrating AI agents that retain conversational context, integrate external tools, and expose a consistent API. Developers install a lightweight Python package, define agents with plug-and-play memory backends, register custom tools (e.g., web search, database queries, file operations), and spin up a local or cloud service. GPTMe handles session tracking, multi-step reasoning, prompt templating, and model switching, delivering production-ready assistants for customer service, productivity, data analysis, and more.
  • Enhance AI chats with long-term memory through MemoryPlugin.
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    What is MemoryPlugin - Long-Term Memory for AI Chats?
    MemoryPlugin adds long-term memory to your AI chats, letting tools like ChatGPT, Claude, Gemini, and others remember important details across conversations. This reduces the need to repeat information and enhances the personalization and efficiency of your interactions with AI. By using the Chrome extension and connecting through memoryplugin.com, you can manage what the AI remembers and ensure that your chats are always built on a consistent knowledge base, leading to better and faster assistance.
  • A web-based platform to design, orchestrate, and manage custom AI agent workflows with multi-step reasoning and integrated data sources.
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    What is SquadflowAI Studio?
    SquadflowAI Studio allows users to visually compose AI agents by defining roles, tasks, and inter-agent communications. Agents can be chained to handle complex multi-step processes—querying databases or APIs, performing actions, and passing context among one another. The platform supports plugin extensions, real-time debugging, and step-by-step logs. Developers configure prompts, manage memory states, and set conditional logic without boilerplate code. Models from OpenAI, Anthropic, and local LLMs are supported. Teams can deploy workflows via REST or WebSocket endpoints, monitor performance metrics, and adjust agent behaviors through a centralized dashboard.
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