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BuildShip Vector Search

Provides context-aware answers to user queries by searching a vector database. Accepts a query string, the name of the vector field, and the collection name as input, retrieves relevant context using OpenAI embeddings and a Firestore vector search, and returns a concise, generated answer. The process generates an embedding for the query with OpenAI, searches the specified Firestore collection for similar vectors, stringifies the results, and uses OpenAI GPT to generate a final answer based on the retrieved context.

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Link to template

https://templates.buildship.com/template/8lAzuiKyvpWM/

Inputs

query

should i think of remote workers?

embeddingsCollectionName

bs_pdf_embeddings

embeddingFieldName

embedding
This is a static example using sample inputs. Remix the template to run it with your own values.

Output