Skip to content

models bring your own data qna

github-actions[bot] edited this page Feb 3, 2024 · 12 revisions

bring-your-own-data-qna

Overview

The "Bring your own data QnA" is a pre-trained Q&A model, enhanced by GPT3.5, that leverages your personally indexed data to deliver more concrete and relevant answers. It involves processing the raw query through an embedding procedure, followed by a "Vector Search" to pinpoint the most pertinent context within the user's data. Subsequently, GPT3.5 is employed to generate a comprehensive answer to the question using the sourced documents.

Inference samples

Inference type CLI VS Code Extension
Real time deploy-promptflow-model-cli-example deploy-promptflow-model-vscode-extension-example
Batch N/A N/A

Sample inputs and outputs (for real-time inference)

Sample input

{
    "inputs": {
        "question": "How to use SDK V2?"
    }
}

Sample output

{
    "outputs": {
        "output": "To use the Azure Machine Learning Python SDK v2, you need to have an Azure Machine Learning workspace and the SDK installed. You can either create a compute instance, which automatically installs the SDK and is pre-configured for ML workflows, or use the provided commands to install the SDK. (Source: https://github.com/prakharg-msft/azureml-tutorials/blob/main//how-to-auto-train-image-models.md)"
    }
}

Version: 8

View in Studio: https://ml.azure.com/registries/azureml/models/bring-your-own-data-qna/version/8

Properties

is-promptflow: True

azureml.promptflow.section: gallery

azureml.promptflow.type: standard

azureml.promptflow.name: Q&A on Your Data

azureml.promptflow.description: Use LLM and data from your own indexed files to ground multi-round question and answering capabilities.

inference-min-sku-spec: 2|0|14|28

inference-recommended-sku: Standard_DS3_v2

Clone this wiki locally