> ## Documentation Index
> Fetch the complete documentation index at: https://docs.freeplay.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Call OpenAI on Azure

> Call OpenAI models via Azure OpenAI Service with Freeplay integration.

### 1. Set Up

* Make sure you have your Azure Endpoint configured in Freeplay. See Using Freeplay -> Model Management for more details
* Load environment variables
* configure Freeplay client

### 2. Fetch your Prompt

Fetch and format your Prompt Template from Freeplay

### 3. Configure Azure Client

All details you need to configure your Azure OpenAI client can be found in the provider\_info section of your FormattedPrompt object

### 4. Make your LLM Call

Make your call directly to Azure OpenAI keying all details off of your Formatted Prompt object

### 5. Record to Freeplay

Update your message set and record the interaction back to Freeplay

## Examples

<CodeGroup>
  ```python Python theme={null}
  from freeplay import Freeplay, RecordPayload, CallInfo, SessionInfo
  import openai
  from dotenv import load_dotenv
  import os
  import time

  load_dotenv("../.env")
  project_id = os.getenv("FREEPLAY_PROJECT_ID")
  freeplay_key = os.getenv("FREEPLAY_API_KEY")
  freeplay_api_base = os.getenv("FREEPLAY_URL")
  azure_api_key = os.getenv("AZURE_API_KEY")
  API_VERSION_STRING = '2024-02-15-preview'

  # instantiate freeplay client
  fpClient = Freeplay(
      freeplay_api_key=freeplay_key,
      api_base=freeplay_api_base,
  )

  # get the formatted prompt
  prompt_vars = {"feature": "eyes", "celebrity": "Oprah Whinfrey"}
  formatted_prompt = fpClient.prompts.get_formatted(project_id=project_id,
                                                    template_name="complement",
                                                    environment="latest",
                                                    variables=prompt_vars)

  # configure the azure openai client
  azureClient = openai.AzureOpenAI(
      api_key=azure_api_key,
      api_version=API_VERSION_STRING,
      # key your provider info from the prompt template including: Endpoint, Deploy ID and Model
      **formatted_prompt.prompt_info.provider_info
  )

  # make your llm call
  s = time.time()
  completion = azureClient.chat.completions.create(
      model=formatted_prompt.prompt_info.model,
      messages=formatted_prompt.llm_prompt, # Note: casting may be required for formatting: cast(List[ChatCompletionMessageParam], formatted_prompt.llm_prompt)
      **formatted_prompt.prompt_info.model_parameters
  )
  e = time.time()

  # Record to freeplay
  # update your messages
  all_messages = formatted_prompt.all_messages(
      {'role': completion.choices[0].message.role,
       'content': completion.choices[0].message.content}
  )

  # create a session
  session = fpClient.sessions.create()

  # record your llm call to freeplay
  payload = RecordPayload(
    	project_id=project_id,
      all_messages=all_messages,
      inputs=prompt_vars,
      session_info=session,
      prompt_version_info=formatted_prompt.prompt_info,
      call_info=CallInfo.from_prompt_info(formatted_prompt.prompt_info, start_time=s, end_time=e)
  )
  completion_info = fpClient.recordings.create(payload)


  ```
</CodeGroup>