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Prompt flow index build

Project description

Prompflow-rag

The promptflow-rag package is part of the Promptflow sdk and contains functionality for building indexes locally

Getting started

Prerequisites

Install the package

Install the Azure AI generative package for Python with pip:

pip install prompflow-rag

Usage

Create index locally

Users can create an index on their local machine from local source files using the build_index method. Given below is a sample.

from promptflow.rag.resources import LocalSource, AzureAISearchConfig, EmbeddingsModelConfig
from promptflow.rag import build_index

# build the index
ai_search_index_path=build_index(
    name=index_name,  # name of your index
    vector_store="azure_ai_search",  # the type of vector store - in this case it is Azure AI Search.
    embeddings_model_config=EmbeddingsModelConfig(
        embeddings_model=f"azure_open_ai://deployment/{embedding_model_deployment}/model/{embedding_model_name}"
    )
    input_source=LocalSource(input_data="data/product-info/"),  # the location of your file/folders
    index_config=AzureAISearchConfig(
        ai_search_index_name=ai_search_index_name # the name of the index store inside the azure ai search service
    )
)

The build index will return the path where the index was created.

Examples

TODO: add link to sample notebooks

promptflow-rag package

Please insert change log into "Next Release" ONLY.

Next release

0.1.0

  • ConnectionConfig parameter rename

0.0.1

  • Introduced package

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