AI automation templates

Ask your own documents a question over HTTP. A Robomotion Knowledge Base is indexed by a workspace agent on your machine and searched locally by the robot; one Query Knowledge Base node returns the passages that answer a question, each with the document and heading it came from. Http In and Http Out turn the flow into a service anything can call, and a Min Score fence means it answers "I could not find that" instead of inventing something. Ships four sample documents and a thirty-line Python client.

Retrieval-augmented generation over your own documents, with the retrieval handed to the agent instead of done for it. Documents are read, chunked, embedded and stored in LanceDB - an embedded vector database that is just a directory on disk. A DeepSeek Agent then answers questions through a search_knowledge tool built from ordinary flow nodes, writing its own queries and searching as many times as a question needs, with the source document named against every fact.

An invoice-processing DeepSeek Agent that teaches itself vendors. The first invoice from a supplier is worked out from scratch and the procedure is written down as a learned skill in the agent's memory; every invoice after runs on what it learned. Extracted fields are recorded to a CSV ledger through a Tool In / Tool Out pair, and memory syncs to the workspace so a whole fleet can run what one robot learned.

A personal nutrition tracking assistant powered by Chat Assistant and LLM Agent nodes. Uses a SQLite database to log meals, manage user profiles, and track daily calorie and macro goals through a natural conversational interface with support for photo-based food logging.

A ready-to-use conversational AI template powered by Chat Assistant and LLM Agent nodes. Provides a simple chat interface where users can ask questions and receive answers from a large language model, with support for file attachments and graceful error handling.