Step-by-Step: Building an AI Agent with Flowise, Qdrant and Qubinets

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • docker

    FreeBSD port of docker, take a look at PORTING-FREEBSD.md in freebsd-compat branch (by kvasdopil)

    Package and Deploy: Package the AI agent and its dependencies into a deployable format (e.g., a Docker container) and deploy it to your cloud platform. This often requires setting up load balancers, managing storage, and configuring serverless functions.

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  • qdrant

    Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

    Within the building process, in this case, our platform serves as the bridge between Flowise and Qdrant. It provides a unified platform seamlessly integrating both tools by handling all the underlying infrastructure and configuration. Qubinets automates the setup process, from instantiating a cloud environment to syncing Flowise and Qdrant to work together without any manual intervention.

  • prometheus

    The Prometheus monitoring system and time series database.

    Monitor and Maintain: Use monitoring tools like Prometheus or Grafana to track the AI agent’s performance, handle scaling, manage updates, and address any security issues.

  • Grafana

    The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.

    Monitor and Maintain: Use monitoring tools like Prometheus or Grafana to track the AI agent’s performance, handle scaling, manage updates, and address any security issues.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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