Few-shot and function calling

API
15

The thing to understand here is that function calling introduced a new role for the chat prompt messages (“role”: “function”). To use few-shot examples with chat model prompts you provide a series of alternating (possibly ‘fake’) messages that show how the assistant did / should respond to a given user input. With function calling the principle is the same but rather than providing a series of alternating user-assistant example messages, you provide alternating user-function messages.

e.g.

schema = {
    "type": "object",
    "properties": {
        "object_type": {"type": "string"},
        "geometry": {
            "type": "array",
            "items": {
                "type": "number"
            }
        }
    },
    "required": ["object_type", "geometry"]
}

example_response_1 = "{\"object_type\": \"point\", \"geometry\": [2.3, 1.0]}\}"
example_response_2 = "{\"object_type\": \"line\", \"geometry\": [[1.0, 2.0], [3.0, 4.0]]\}"

few_shot_function_calling_example = openai.ChatCompletion.create(
    model = "gpt-3.5-turbo-0613",
        messages = [
            {"role": "system", "content": "You are a system for returning geometric objects in JSON."},
            {"role": "user", "content": "give me a point"},
            {"role": "function", "name": "example_func", "content": example_response_1,},
            {"role": "user", "content": "give me a line"},
            {"role": "function", "name": "example_func", "content": example_response_2,},
            {"role": "user", "content": "give me a polygon"}
        ],
    functions=[{"name": "example_func", "parameters": schema}],
    function_call={"name": "example_func"},
    temperature=0
)

print(few_shot_function_calling_example.choices[0].message)


{
  "content": null,
  "function_call": {
    "arguments": "{\"object_type\": \"polygon\", \"geometry\": [[0, 0], [0, 5], [5, 5], [5, 0]]}",
    "name": "example_func"
  },
  "role": "assistant"
}
5 Likes