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Azure OpenAI Assistants function calling

  • Article

The Assistants API supports function calling, which allows you to describe the structure of functions to an Assistant and then return the functions that need to be called along with their arguments.

Note

Azure OpenAI does not yet support Assistants V2. Please use the v1.20.0 release of the OpenAI Python library until V2 support is available.

Function calling support

Supported models

The models page contains the most up-to-date information on regions/models where Assistants are supported.

To use all features of function calling including parallel functions, you need to use the latest models.

API Version

  • 2024-02-15-preview

Example function definition

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-02-15-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

assistant = client.beta.assistants.create(
  instructions="You are a weather bot. Use the provided functions to answer questions.",
  model="gpt-4-1106-preview", #Replace with model deployment name
  tools=[{
      "type": "function",
    "function": {
      "name": "getCurrentWeather",
      "description": "Get the weather in location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
          "unit": {"type": "string", "enum": ["c", "f"]}
        },
        "required": ["location"]
      }
    }
  }, {
    "type": "function",
    "function": {
      "name": "getNickname",
      "description": "Get the nickname of a city",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
        },
        "required": ["location"]
      }
    } 
  }]
)

Reading the functions

When you initiate a Run with a user Message that triggers the function, the Run will enter a pending status. After it processes, the run will enter a requires_action state that you can verify by retrieving the Run.

{
  "id": "run_abc123",
  "object": "thread.run",
  "assistant_id": "asst_abc123",
  "thread_id": "thread_abc123",
  "status": "requires_action",
  "required_action": {
    "type": "submit_tool_outputs",
    "submit_tool_outputs": {
      "tool_calls": [
        {
          "id": "call_abc123",
          "type": "function",
          "function": {
            "name": "getCurrentWeather",
            "arguments": "{\"location\":\"San Francisco\"}"
          }
        },
        {
          "id": "call_abc456",
          "type": "function",
          "function": {
            "name": "getNickname",
            "arguments": "{\"location\":\"Los Angeles\"}"
          }
        }
      ]
    }
  },
...

Submitting function outputs

You can then complete the Run by submitting the tool output from the function(s) you call. Pass the tool_call_id referenced in the required_action object above to match output to each function call.

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-02-15-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )


run = client.beta.threads.runs.submit_tool_outputs(
  thread_id=thread.id,
  run_id=run.id,
  tool_outputs=[
      {
        "tool_call_id": call_ids[0],
        "output": "22C",
      },
      {
        "tool_call_id": call_ids[1],
        "output": "LA",
      },
    ]
)

After you submit tool outputs, the Run will enter the queued state before it continues execution.

See also