There are 64 nodes that can be used as successor
for a node with an output port of type Python Binary.
Prompts a Large Language Model.
Reads a Chroma vector store created with LangChain from a local path.
Creates a Chroma vector store from a string column and an embeddings model.
Creates a FAISS vector store from a string column and an embeddings model.
Reads a FAISS vector store created with LangChain from a local path.
Extracts the documents, embeddings and metadata from a vector store into a table.
Concatenates two lists of LLM agent tools.
Performs a similarity search on a vector store.
Creates an agent tool from a vector store.
The loop end node for an active learning loop.
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