I want use `gpt-3.5-turbo` for nlp task

I sometimes use gpt-3.5-turbo for NLP tasks like text-davinci-003. Because it’s cheaper and feels like it performs much better than Curie.

But there are some problems with this. In the current version of python-preview, if I use the chat backend, it forces the template to record the user’s conversation. This increases the number of tokens I use, which is costly. Also, if I’m dealing with long texts, it hits token limit in no time. like example below.

This can be solved by putting a memorization setting in the PromptTemplateConfig class and modifying the semantic-kernel/python/semantic_kernel/orchestration/sk_function.py, as shown in the photo below. But I didn’t open the PR because I’m not sure if it will match the direction Microsoft is looking at.

In the same vein, I’d like to see ChatCompletion imported via import_semantic_skill_from_directory the way it’s done in the text-davinci-003. Currently I’m importing skills the following way and it feels unnatural, please let me know if I’m missing something.

def import_skills(
    kernel: sk.Kernel, skill_dir="./skills"
) -> Dict[str, sk.SKFunctionBase]:
    skills = {}

    for skill in os.listdir(skill_dir):
        if skill.endswith("Skill"):
            s = kernel.import_semantic_skill_from_directory(skill_dir, skill)
            skills[skill] = s

    skills["ChatSkills"] = {}
    skills["ChatSkills"][
        "ExtractInformationList"
    ] = extract_information.build_semantic_chat_function(kernel)

    return skills

I think using skprompt.yaml for prompt template instead of skprompt.txt would allow for a much freer use of the model.

[awharrison-28]

@joowon-dm-snu ported, see https://github.com/microsoft/semantic-kernel/pull/643. Will be available with the next version of the pip package

[dluc]

@joowon-dm-snu @tynguyen this is now implemented, pls see the latest nuget 0.12

example: https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet/kernel-syntax-examples/Example26_SemanticFunctionsUsingChatGPT.cs

IKernel kernel = new KernelBuilder().WithLogger(ConsoleLogger.Log).Build();

// Note: we use Chat Completion and GPT 3.5 Turbo
kernel.Config
    .AddAzureChatCompletionService("id", "gpt-35-turbo", "https://....openai.azure.com/", "...API KEY...");

var func = kernel.CreateSemanticFunction(
    "List the two planets closest to '{{$input}}', excluding moons, using bullet points.");

var result = await func.InvokeAsync("Jupiter");
Console.WriteLine(result);