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Provides integration between AI Search and FlowDrop, adding FlowDrop node processors for vector similarity search and Retrieval Augmented Generation (RAG) configuration, plus a dedicated AI Search sidebar category in the FlowDrop workflow editor.

Key Features

  • AI Search Workflow Integration

    • Seamlessly connects FlowDrop workflows with Drupal AI Search and vector database providers for semantic retrieval and RAG pipelines.

  • Dedicated AI Search Category

    • Adds a dedicated AI Search sidebar category in the FlowDrop editor for organising retrieval and vector search nodes.

  • Vector Similarity Search

    • Provides a VDB Search node capable of performing semantic similarity searches against vector databases.

  • Dual Backend Support

    • Supports both Search API-powered retrieval and direct vector database queries through configurable backend modes.

  • Embedding Reuse Optimization

    • Reuse precomputed embeddings from upstream workflow nodes to reduce latency, API calls, and embedding costs.

  • Dynamic Query Inputs

    • Exposes search queries as FlowDrop input ports, enabling flexible connections from chat, text, or AI-generated inputs.

  • RAG Configuration Builder

    • Generates tool_usage_limits configuration objects for AI Agent Executor workflows automatically.

  • Automatic Tool Discovery

    • Dynamically discovers compatible ai_search:* tools and configures them for selected search indexes.

  • Drupal AI Ecosystem Support

    • Compatible with Drupal AI vector database providers such as Milvus, Pinecone, Postgres and other AI Search backends.

  • Composable AI Workflows

    • Designed for advanced Drupal AI workflows including semantic search, retrieval pipelines, and AI agent orchestration.

Supporting organizations: 
Factorial GmbH
Supporting Development

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