A basic example on how to build an AI Agent using OpenAI enpoints in Azure

This tutorial provides a basic example of how an AI agent can be build using Azure OpenAI endpoints. For the full article refer to the digital power website: Building an AI Agent with Azure OpenAI.

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Getting Started

Prerequisites

1. Python 3.13 or higher.
2. Install the required dependencies:

   pip install -r requirements.txt

3. Configure your Azure credentials in config/settings.yaml.

Running the AI Agent

1. Start the AI Agent by running the ai_agent.py script:

   python ai_agent.py

2. The agent will prompt you for input. You can ask it to perform tasks related to blob listing or any other general inquiries.

Usage

Commands

• Ask a Question: Type your query, and the assistant will respond.
• Exit the Conversation: Type exit or quit to quit.

Example Interactions

1. List Files in Azure Blob Storage:

   Human User: List files in the dls Azure Blob Storage container.
   AI assitant: Here are the files in the container:
   - file1.csv
   - file2.xlsx
   

Configuration

config/settings.yaml contains the configuration for Azure Blob Storage, Databricks, and other tools. Update it with your credentials and settings.

azure_openai:
    endpoint: "https://your-openai-resource-name.openai.azure.com/"
    model_name: "gpt-4"
    deployment: "gpt-4-deployment"
    api_key: "your-azure-openai-api-key"
    api_version: "2024-12-01-preview"

azure_blob:
    connection_string: "DefaultEndpointsProtocol=https;AccountName=youraccountname;AccountKey=youraccountkey;EndpointSuffix=core.windows.net"
    default_container: "dls"