import { OpenAI } from "https://deno.land/x/openai/mod.ts";
import { OPENAI_API_KEY } from "@lib/env.ts";

const openAI = OPENAI_API_KEY && new OpenAI(OPENAI_API_KEY);

export async function summarize(content: string) {
  if (!openAI) return;
  const chatCompletion = await openAI.createChatCompletion({
    model: "gpt-3.5-turbo",
    messages: [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": content.slice(0, 2000) },
      {
        "role": "user",
        "content":
          "Please summarize the article in one sentence as short as possible",
      },
    ],
  });

  return chatCompletion.choices[0].message.content;
}
export async function shortenTitle(content: string) {
  if (!openAI) return;
  const chatCompletion = await openAI.createChatCompletion({
    model: "gpt-3.5-turbo",
    messages: [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": content.slice(0, 2000) },
      {
        "role": "user",
        "content":
          "Please shorten the provided website title as much as possible, don't rewrite it, just remove unneccesary informations. Please remove for example any mention of the name of the website.",
      },
    ],
  });

  return chatCompletion.choices[0].message.content;
}

export async function extractAuthorName(content: string) {
  if (!openAI) return;
  const chatCompletion = await openAI.createChatCompletion({
    model: "gpt-3.5-turbo",
    messages: [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": content.slice(0, 2000) },
      {
        "role": "user",
        "content":
          "If you are able to extract the name of the author from the text please respond with the name, otherwise respond with 'not found'",
      },
    ],
  });

  const author = chatCompletion.choices[0].message.content;

  if (author !== "not found") return author;
  return "";
}

export async function createTags(content: string) {
  if (!openAI) return;
  const chatCompletion = await openAI.createChatCompletion({
    model: "gpt-3.5-turbo",
    messages: [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": content.slice(0, 2000) },
      {
        "role": "user",
        "content":
          "Please respond with a list of genres the corresponding article falls into, dont include any other informations, just a comma seperated list of top 5 categories. Please respond only with tags that make sense even if there are less than five.",
      },
    ],
  });

  return chatCompletion.choices[0].message.content?.toLowerCase().split(", ")
    .map((v) => v.replaceAll(" ", "-"));
}