macOS Services in the style of NotesOllama

automator.py

# Drop this into Automator using Python 3 as the shell

from sys import stdin
from json import dumps, loads
from urllib.parse import urlencode
from urllib.request import Request, urlopen

AZURE_ENDPOINT="getyourowndeployment.openai.azure.com"
OPENAI_API_KEY="getyourownkey"
OPENAI_API_VERSION="2023-05-15"
DEPLOYMENT_NAME="default" # I've deployed chatgpt35-turbo under this label

url = f"https://{AZURE_ENDPOINT}/openai/deployments/{DEPLOYMENT_NAME}/chat/completions?api-version={OPENAI_API_VERSION}"
headers = {"api-key": OPENAI_API_KEY, "content-type": "application/json; charset=UTF-8"}

prompts = [ # shamelessly stolen from https://github.com/andersrex/notesollama/blob/main/NotesOllama/Menu/commands.swift (MIT licensed)
    {
        "name": "Summarize selection",
        "prompt": "Act as a writer. Summarize the text in a view sentences highlighting the key takeaways. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Explain selection",
        "prompt": "Act as a writer. Explain the text in simple and concise terms keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Expand selection",
        "prompt": "Act as a writer. Expand the text by adding more details while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Answer selection",
        "prompt": "Act as a writer. Answer the question in the text in simple and concise terms. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Rewrite selection (formal)",
        "prompt": "Act as a writer. Rewrite the text in a more formal style while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Rewrite selection (casual)",
        "prompt": "Act as a writer. Rewrite the text in a more casual style while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Rewrite selection (active voice)",
        "prompt": "Act as a writer. Rewrite the text in with an active voice while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Rewrite selection (bullet points)",
        "prompt": "Act as a writer. Rewrite the text into bullet points while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
    },
    {
        "name": "Caption selection",
        "prompt": "Act as a writer. Create only one single heading for the whole text that is giving a good understanding of what the reader can expect. Output only the caption and nothing else, do not chat, no preamble, get to the point. Your format should be ## Caption."
    }
]

prompt = prompts[0]["prompt"] # adjust the index to select a different prompt

data = {
	"temperature": 0.4,
    "messages": [{ 
        "role": "system",
        "content": prompt
    },{
        "role": "user", 
        "content": stdin.read()
    }]#,{
    #    role: "assistant",
    #    Use this to guide the LLM if you need JSON formatting
    #    content: ""
    #}
}

req = Request(url, data=dumps(data).encode(), method="POST", headers=headers)

with urlopen(req) as response:
    print(loads(response.read().decode())["choices"][0]["message"]["content"])

shortcuts.js

function run(input, parameters) {

    // This script is a simple example of how to use the Azure OpenAI API to generate text
    // from a macOS system service written as a JavaScript for Automation (JXA) script
    // You can drop this into a Shortcuts "Run JavaScript" action (which will only work on a Mac)
    // or use it as a starting point for a more complex system service

    ObjC.import('Foundation')
    ObjC.import('Cocoa')

    let app = Application.currentApplication();

    app.includeStandardAdditions = true

    let AZURE_ENDPOINT = "my_endpoint.openai.azure.com",
        DEPLOYMENT_NAME = "my_deployment",
        // You should store your keys in the macOS Keychain and retrieve them from there:
        OPENAI_API_KEY = app.doShellScript(`security find-generic-password -w -s ${AZURE_ENDPOINT} -a ${DEPLOYMENT_NAME}`)
    OPENAI_API_VERSION = "2023-05-15",
        url = `https://${AZURE_ENDPOINT}/openai/deployments/${DEPLOYMENT_NAME}/chat/completions?api-version=${OPENAI_API_VERSION}`,
        postData = {
            "temperature": 0.4,
            "messages": [{
                "role": "system",
                "content": "Act as a writer. Expand the text by adding more details while keeping the same meaning. Output only the text and nothing else, do not chat, no preamble, get to the point."
                ,
            }, {
                "role": "user",
                "content": input.join("\n")
            }]/*,{
            role: "assistant",
            Use this if you need JSON formatting
            content: ""
        */
        },
        request = $.NSMutableURLRequest.requestWithURL($.NSURL.URLWithString(url));

    request.setHTTPMethod("POST");
    request.setHTTPBody($.NSString.alloc.initWithUTF8String(JSON.stringify(postData)).dataUsingEncoding($.NSUTF8StringEncoding));
    request.setValueForHTTPHeaderField("application/json; charset=UTF-8", "Content-Type");
    request.setValueForHTTPHeaderField(OPENAI_API_KEY, "api-key");

    let error = $(),
        response = $(),
        data = $.NSURLConnection.sendSynchronousRequestReturningResponseError(request, response, error);

    if (error[0]) {
        return "Error: " + error[0].localizedDescription;
    } else {
        var json = JSON.parse($.NSString.alloc.initWithDataEncoding(data, $.NSUTF8StringEncoding).js);
        if (json.error) {
            return json.error.message;
        } else {
            return json.choices[0].message.content;
        }
    }
}

test.swift

import Cocoa

let url = URL(string:"https://endpoint_name.openai.azure.com/openai/deployments/deployment_name/chat/completions?api-version=2023-05-15")!,
    prompt = "Do what you are told. No more, no less."

struct Role: Codable {
    let role: String
    let content: String
}

struct Completion: Codable {
    let temperature: Float
    let messages: [Role]
}

struct Response: Codable {
    let id: String
    let object: String
    let created: Int
    let model: String
    let choices: [Choice]
    let usage: Usage
}

struct Choice: Codable {
    let finish_reason: String
    let index: Int
    let message: Message
}

struct Message: Codable {
    let role: String
    let content: String
}

struct Usage: Codable {
    let prompt_tokens: Int
    let completion_tokens: Int
    let total_tokens: Int
}

let data = Completion(
    temperature: 0.4,
    messages: [
        Role(role:"system", content: prompt),
        Role(role:"user", content: "Say Hello")
    ]
)

let encoder = JSONEncoder()
if let jsonData = try? encoder.encode(data),
   let jsonString = String(data: jsonData, encoding: .utf8) {
    print(jsonString)
    var request = URLRequest(url: url);
    request.httpMethod = "POST"
    request.httpBody = jsonData
    request.setValue("application/json; charset=utf-8", forHTTPHeaderField: "Content-Type")
    request.setValue("an_api_key", forHTTPHeaderField: "api-key")

    let task = URLSession.shared.dataTask(with: request) { data, response, error in
        guard let data = data, error == nil else {
            print(error?.localizedDescription ?? "No data")
            return
        }
        let decoder = JSONDecoder()
            do {
                let response = try decoder.decode(Response.self, from: data)
                print(response.choices[0].message.content)
            } catch {
                print("Error decoding JSON: \(error)")
            }
        
    }
		// note that this also makes it hard to handle control flow
    task.resume()
}