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Comprehensive memoria a largo plazo IA Tools for Every Need

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memoria a largo plazo IA

  • Agent Starter Pack

    An open-source Google Cloud framework offering templates and samples to build conversational AI agents with memory, planning, and API integrations.
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    What is Agent Starter Pack?
    Agent Starter Pack is a developer toolkit that scaffolds intelligent, interactive agents on Google Cloud. It offers templates in Node.js and Python to manage conversation flows, maintain long-term memory, and perform tool and API invocations. Built on Vertex AI and Cloud Functions or Cloud Run, it supports multi-step planning, dynamic routing, observability, and logging. Developers can extend connectors to custom services, build domain-specific assistants, and deploy scalable agents in minutes.
    Agent Starter Pack Core Features
    • Conversation scaffolding with multi-turn dialogue
    • Long-term memory management
    • Multi-step reasoning and planning
    • API and tool invocation connectors
    • Integration with Vertex AI LLMs
    • Deployment on Cloud Functions or Cloud Run
    • Observability via Cloud Logging and Monitoring
    Agent Starter Pack Pro & Cons

    The Cons

    No explicit pricing information available on the page.
    Potential complexity in customizing templates for users without advanced knowledge.
    Documentation may require prior familiarity with Google Cloud and AI agent concepts.

    The Pros

    Pre-built templates enable rapid development of AI agents.
    Integration with Vertex AI allows for effective experimentation and evaluation.
    Production-ready infrastructure supports reliable deployment with monitoring and CI/CD.
    Highly customizable and extendable to suit various use cases.
    Open-source under Apache 2.0 License facilitating community contribution and transparency.

  • Context-First AGI Cognitive Context Engine (CCE) Prototype

    A prototype engine for managing dynamic conversational context, enabling AGI agents to prioritize, retrieve, and summarize interaction memories.
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    What is Context-First AGI Cognitive Context Engine (CCE) Prototype?
    The Context-First AGI Cognitive Context Engine (CCE) Prototype provides a robust toolkit for developers to implement context-aware AI agents. It leverages vector embeddings to store historical user interactions, enabling efficient retrieval of relevant context snippets. The engine automatically summarizes lengthy conversations to fit within LLM token limits, ensuring continuity and coherence in multi-turn dialogues. Developers can configure context prioritization strategies, manage memory lifecycles, and integrate custom retrieval pipelines. CCE supports modular plugin architectures for embedding providers and storage backends, offering flexibility for scaling across projects. With built-in APIs for storing, querying, and summarizing context, CCE streamlines the creation of personalized conversational applications, virtual assistants, and cognitive agents that require long-term memory retention.
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