Skip to main content

Setup & Prerequisites

There are a few prerequisites to getting started with integrating LLMs into your application:

  • LLM API Key - To generate messages using an LLM, you will need to have an API Key for the LLM you are using.
  • In your application, you should include your keys in a secure way. We recommend putting it in an .env file at the root level of your project
my-app/
|── appPackage/       # Teams app package files
├── src/
│   └── main.py      # Main application code
|── .env              # Environment variables

Azure OpenAI​

You will need to deploy a model in Azure OpenAI. Here is a guide on how to do this.

Once you have deployed a model, include the following key/values in your .env file:

AZURE_OPENAI_API_KEY=your-azure-openai-api-key
AZURE_OPENAI_MODEL=your-azure-openai-model-deployment-name
AZURE_OPENAI_ENDPOINT=your-azure-openai-endpoint
AZURE_OPENAI_API_VERSION=your-azure-openai-api-version
info

The AZURE_OPENAI_API_VERSION is different from the model version. This is a common point of confusion. Look for the API Version here

OpenAI​

You will need to create an OpenAI account and get an API key. Here is a guide on how to do this. Once you have your API key, include the following key/values in your .env file:

OPENAI_API_KEY=sk-your-openai-api-key
OPENAI_MODEL=gpt-4  # Optional: defaults to gpt-4o if not specified
note

Automatic Environment Variable Loading: The AI models automatically read these environment variables when initialized. You can also pass these values explicitly as constructor parameters if needed for advanced configurations.

# Automatic (recommended)
model = OpenAICompletionsAIModel(model="your-model-name")

# Explicit (for advanced use cases)
model = OpenAICompletionsAIModel(
    key="your-api-key",
    model="your-model-name",
    azure_endpoint="your-endpoint",  # Azure only
    api_version="your-api-version"   # Azure only
)