flowdrop_ai_search

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.