Read-only Groq embedding workflow. It creates embeddings for explicit caller-provided text samples and summarizes vector count, encoding, token usage, and readiness for semantic search or RAG. It never sends files, calls audio endpoints, uses tools, creates batch jobs, or uses arbitrary Groq routes.

How it works 6 steps

Inspect the data fetches, transforms, gates, and output this recipe runs.

Process (6 steps)

■ embed ?

■ vectors default

Apply default

■ vector_count count

Count items in vectors

■ summarize ?

■ vector_table to_table

Format results as a data table

■ card to_summary

Format results as a summary card

Settings 6 configurable

Configurable at install. Defaults shown — change them anytime in Recued.

groq setting =

focus setting = Summarize whether the selected Groq embedding setup is ready for semantic search or RAG. Cover model, encoding, returned vector rows, token usage, and practical next steps.

texts setting =

max length setting = 800

embedding model setting = nomic-embed-text-v1_5

encoding format setting = float