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
- Python 3.7 or later is required to use this package.
- You must have an Azure subscription.
- An Azure Machine Learning Workspace.
- An Azure AI Studio project.
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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