Vectorize helps you build AI apps faster and with less hassle. It automates data extraction, finds the best vectorization strategy using RAG evaluation, and lets you quickly deploy real-time RAG pipelines for your unstructured data. Your vector search indexes stay up-to-date, and it integrates with your existing vector database, so you maintain full control of your data. Vectorize handles the heavy lifting, freeing you to focus on building robust AI solutions without getting bogged down by data management.

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Installation and Setup

Install the following Python package: 
pip install langchain-vectorize
Sign up for a free Vectorize account here Generate an access token in the Access Token section Gather your organization ID. From the browser url, extract the UUID from the URL after /organization/ Set up the following variables: 
VECTORIZE_ORG_ID="your-organization-id"
VECTORIZE_API_TOKEN="your-api-token"

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Retriever

from langchain_vectorize import VectorizeRetriever

retriever = VectorizeRetriever(
    api_token=VECTORIZE_API_TOKEN,
    organization=VECTORIZE_ORG_ID,
    pipeline_id="...",
)
retriever.invoke("query")
Learn more in the example notebook.