flowdrop_ai_search

FlowDrop AI Search module 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.

Contributing

The FlowDrop AI Search module's issue queue is intended for reporting bugs, submitting feature requests, and planning.

Additionally, you can join the #flowdrop channel on Drupal Slack.