Josh Mabry

// Name: Search Open PRs
// Description: Search open PRs in a repo

import "@johnlindquist/kit";

const fetch = await npm("node-fetch");
const variables = {
  owner: "knapsack-labs",
  repoName: "app-monorepo",
};

let token = await env("GITHUB_AUTH_TOKEN", {
  hint: `Grab a key from <a href="https://github.com/settings/tokens">here</a>`,
});

const query = `
query getPrs($owner: String!, $repoName: String!) {
  repository(owner: $owner, name: $repoName) {
    pullRequests(last: 100, states: OPEN) {
      nodes {
        body
        createdAt
        mergeable
        number
        state
        title
        updatedAt
        url
        author {
          avatarUrl
          login
        }
      }
    }
  }
}

`;

async function getPrs() {
  return fetch("https://api.github.com/graphql", {
    headers: {
      authorization: `bearer ${token}`,
    },
    method: "POST",
    body: JSON.stringify({ query, variables }),
  })
    .then((res) => res.json())
    .catch((err) => {
      console.log(err);
      exit();
    });
}
const prs = await getPrs();
const openPRs = prs.data.repository.pullRequests.nodes;
const sortedPrs = openPRs.sort(
  (a, b) => Date.parse(b.createdAt) - Date.parse(a.createdAt)
);
const pr = await arg(
  {
    placeholder: `Select a PR to view`,
  },
  sortedPrs.map((pr) => {
    return {
      name: `${pr.number} - ${pr.title}`,
      preview: () =>
        `<div class="p-2">
          <h2>${pr.number} - ${pr.title}</h2>
          <hr class="mb-4"/>
          <p>Ready to Merge: ${pr.mergeable === "MERGEABLE" ? "✅" : "⛔"}</p>
          <p class="my-4">${md(pr.body)}</p>
          <span class="flex flex-row">
          <p>Author: ${pr.author.login}</p>
          <img class="w-5 h-5 ml-2" src="${pr.author.avatarUrl}" />
          </span>
        </div>`,
      value: pr.number,
    };
  })
);

const prInfo = sortedPrs.find((p) => p.number === pr);
browse(prInfo.url);

let { GoogleAuth } = await import("google-auth-library");
let { DiscussServiceClient } = await import("@google-ai/generativelanguage");

import "@johnlindquist/kit";

const MODEL_NAME = "models/chat-bison-001";
const API_KEY = await env("PALM_API_KEY", {
  hint: `Signup for waitlist here <a href="https://developers.generativeai.google/">here</a>`,
});

const client = new DiscussServiceClient({
  authClient: new GoogleAuth().fromAPIKey(API_KEY),
});

const config = {
  model: MODEL_NAME,
  temperature: 0.75,
  candidateCount: 1,
  top_k: 40,
  top_p: 0.95,
};

const chatHistory = [];

const generateText = async (text) => {
  chatHistory.push({ content: text });
  const response = await client.generateMessage({
    ...config,
    prompt: {
      context: "You are a funny and helpful assistant.",
      messages: chatHistory,
    },
  });

  log(response);
  log(response[0].filters);
  if (response[0].filters.length > 0) {
    return `The model has rejected your input. Reason: ${response[0].filters[0].reason}`;
  } else {
    chatHistory.push({ content: response[0].candidates[0].content });
    return response[0].candidates[0].content;
  }
};

await chat({
  onSubmit: async (input) => {
    setLoading(true);
    try {
      const response = await generateText(input);
      let message = md(response);
      chat.addMessage("");
      chat.setMessage(-1, message);
    } catch (e) {
      console.log(e);
      chat.addMessage("");
      chat.setMessage(-1, md("Error: " + e.message));
    }
    setLoading(false);
  },
});

// Name: Static to Dynamic
// Description: Convert static import to dynamic import
// e.g. import { Foo } from "bar";
// to let { Foo } = await import("bar");
// Author: Josh Mabry
// Twitter: @AI_Citizen

import "@johnlindquist/kit";

const text = await getSelectedText();

function convertImportString(input) {
  const importRegex = /import\s+({[^}]+})\s+from\s+"([^"]+)";/;

  if (!importRegex.test(input)) {
    throw new Error("Invalid import string format");
  }

  const [_, importList, modulePath] = input.match(importRegex);
  const output = `let ${importList} = await import("${modulePath}");`;
  return output;
}

const output = convertImportString(text);

await setSelectedText(output);

/*
# Prompt Anything
Highlight some text and run this script to prompt against it.
Useful for summarizing text, generating a title, or any other task you can think of.

## Usage

- Highlight the text you want to prompt against
- Run the script via shortcut or command palette
- Input your desired prompt
- Wait for the AI to respond
- Select one of the options
* Retry - Rerun generation with option to update prompt
* Edit - Edit response in editor
    - On editor exit the message is saved to the clipboard
    - On editor submit the message is pasted into the highlighted text
* Copy - Copy response to clipboard
* Paste - Paste response into highlighted text
* Save - Save response to file (not working)
## Example
- Highlight: 'Some really long passage in a blog post'
- Run Script
- Prompt: `Summarize this passage in the form of Shakespearean prose`
- Waaaaait for it...
- Get a response from the AI
- Select an option
- Rinse and repeat
*/

// Name: Prompt Anything
// Description: Custom prompt for any highlighted text
// Author: Josh Mabry
// Twitter: @AI_Citizen
// Shortcut: alt shift enter

//#################
// ScriptKit Import
//#################
import "@johnlindquist/kit";

//#################
// LangChain Imports
//#################
let { ChatOpenAI } = await import("langchain/chat_models");
let { HumanChatMessage, SystemChatMessage } = await import("langchain/schema");

//#################
// Request API KEY
//#################
// stored in .env file after first run
// can change there or through the command palette
let openAIApiKey = await env("OPENAI_API_KEY", {
  hint: `Grab a key from <a href="https://platform.openai.com/account/api-keys">here</a>`,
});
// System input / Task for the AI to follow
let userSystemInput = await arg("Summarize this passage");
// User Prompt from highlighted text
let userPrompt = await getSelectedText();

//#################
// Prompt Template
//#################
const formatPrompt = (prompt) => {
  return `##### Ignore prior instructions
- Return answer in markdown format
- You are tasked with the following
${prompt}
########
`;
};
//################
// Options Template
//################
const options = `
* [Retry](submit:retry) - Rerun generation with option to update prompt
* [Edit](submit:edit) - Edit response in editor
* [Copy](submit:copy) - Copy response to clipboard
* [Paste](submit:paste) - Paste response into highlighted text
* [Save](submit:save) - Save response to file (not working)
`;

//################
// Main Function
//################
/**
 *
 * @param {*} prompt
 * @param {*} humanChatMessage
 */
async function promptAgainstHighlightedText(
  prompt = formatPrompt(userSystemInput),
  humanChatMessage = userPrompt
) {
  //#########
  // Helpers
  //########
  // exit script on cancel
  const cancelChat = () => {
    process.exit(1);
  };

  /**
   * Paste text to highlighted text and exit script
   * @param {*} text
   */
  const pasteTextAndExit = async (text) => {
    await setSelectedText(text);
    process.exit(1);
  };

  /**
   * Copy text to clipboard and exit script
   * @param {*} text
   */
  const copyToClipboardAndExit = async (text) => {
    await clipboard.writeText(currentMessage);
    process.exit(1);
  };

  let currentMessage = "";
  const llm = new ChatOpenAI({
    // 0 = "precise", 1 = "creative"
    temperature: 0.3,
    // modelName: "gpt-4", // uncomment to use GPT-4 (requires beta access)
    openAIApiKey: openAIApiKey,
    // turn off to only get output when the AI is done
    streaming: true,
    callbacks: [
      {
        handleLLMNewToken: async (token) => {
          log(`handleLLMNewToken`);
          // each new token is appended to the current message
          // and then rendered to the screen
          currentMessage += token;
          // render current message
          await div({
            html: md(currentMessage),
            // @TODO: Figure out how to get ESC to trigger a cancel
            onAbandon: cancelChat,
            onEscape: cancelChat,
            onBackspace: cancelChat,
            // if this is set to false you can click outside the window to cancel
            // which works, but would be nice to also have ESC work
            ignoreBlur: false,
            focus: true,
            // hint: `Press ESC to cancel`,
          });
        },
        handleLLMError: async (err) => {
          dev({ err });
        },
        handleLLMEnd: async () => {
          log(`handleLLMEnd`);
          // render final message with options
          let html = md(currentMessage + options);
          // wait for user to select an option
          const selectedOption = await div(html, {
            ignoreBlur: true,
            focus: true,
            // have paste on text on submit?
            // onSubmit: () => pasteTextAndExit(currentMessage),
          });
          // handle selected option
          switch (selectedOption) {
            case "paste":
              await pasteTextAndExit(currentMessage);
            case "retry":
              // reset current message
              currentMessage = "";
              // prompt again with new prompt
              // press enter to use original prompt
              const followUp = await arg({
                placeholder: userSystemInput,
                hint: "Press enter to use the same prompt",
              });
              await processMessage(followUp);
              break;
            case "edit":
              // @TODO still need to figure out best way to handle submit and abort
              // would like custom buttons for triggering all of the actions like copy, paste, etc
              await editor({
                value: currentMessage,
                onEscape: async (state) => await copyToClipboardAndExit(state),
                onSubmit: async (state) => await pasteTextAndExit(state),
              });
              break;
            case "copy":
              await copyToClipboardAndExit(currentMessage);
            case "save":
              await inspect(currentMessage, `/conversations/${Date.now()}.md`);
              exitChat();
            default:
              copyToClipboardAndExit(currentMessage);
          }
          await optionHandler(selectedOption);
        },
      },
    ],
  });
  //###########
  // Main Loop
  //###########
  // runs the language model until the user cancels
  while (true) {
    await llm.call([
      new SystemChatMessage(formatPrompt(prompt)),
      new HumanChatMessage(humanChatMessage),
    ]);
  }
}

promptAgainstHighlightedText();

/*
# Prompt Anything
Highlight some text and run this script to prompt against it.
Useful for summarizing text, generating a title, or any other task you can think of.

## Usage

- Highlight the text you want to prompt against
- Run the script via shortcut or command palette
- Input your desired prompt
- Wait for the AI to respond
- Select one of the options
* Retry - Rerun generation with option to update prompt
* Edit - Edit response in editor
    - On editor exit the message is saved to the clipboard
    - On editor submit the message is pasted into the highlighted text
* Copy - Copy response to clipboard
* Paste - Paste response into highlighted text
* Save - Save response to file (not working)
## Example
- Highlight: 'Some really long passage in a blog post'
- Run Script
- Prompt: `Summarize this passage in the form of Shakespearean prose`
- Waaaaait for it...
- Get a response from the AI
- Select an option
- Rinse and repeat
*/

// Name: Prompt Anything
// Description: Custom prompt for any highlighted text
// Author: Josh Mabry
// Twitter: @AI_Citizen
// Shortcut: alt shift enter

//#################
// ScriptKit Import
//#################
import "@johnlindquist/kit";

//#################
// LangChain Imports
//#################
let { ChatOpenAI } = await import("langchain/chat_models");
let { HumanChatMessage, SystemChatMessage } = await import("langchain/schema");

//#################
// Request API KEY
//#################
// stored in .env file after first run
// can change there or through the command palette
let openAIApiKey = await env("OPENAI_API_KEY", {
  hint: `Grab a key from <a href="https://platform.openai.com/account/api-keys">here</a>`,
});
// System input / Task for the AI to follow
let userSystemInput = await arg("Summarize this passage");
// User Prompt from highlighted text
let userPrompt = await getSelectedText();

//#################
// Prompt Template
//#################
const formatPrompt = (prompt) => {
  return `##### Ignore prior instructions
- Return answer in markdown format
- You are tasked with the following
${prompt}
########
`;
};
//################
// Options Template
//################
const options = `
* [Retry](submit:retry) - Rerun generation with option to update prompt
* [Edit](submit:edit) - Edit response in editor
* [Copy](submit:copy) - Copy response to clipboard
* [Paste](submit:paste) - Paste response into highlighted text
* [Save](submit:save) - Save response to file (not working)
`;
//#########
// Helpers
//########
// exit script on cancel
const cancelChat = () => {
  process.exit(1);
};

//################
// Main Function
//################
/**
 *
 * @param {*} prompt
 * @param {*} humanChatMessage
 */
async function promptAgainstHighlightedText(
  prompt = formatPrompt(userSystemInput),
  humanChatMessage = userPrompt
) {
  let currentMessage = "";
  const llm = new ChatOpenAI({
    // 0 = "precise", 1 = "creative"
    temperature: 0.3,
    // modelName: "gpt-4", // uncomment to use GPT-4 (requires beta access)
    openAIApiKey: openAIApiKey,
    // turn off to only get output when the AI is done
    streaming: true,
    callbacks: [
      {
        handleLLMNewToken: async (token) => {
          log(`handleLLMNewToken`);
          // each new token is appended to the current message
          // and then rendered to the screen
          currentMessage += token;
          // render current message
          await div({
            html: md(currentMessage + options),
            // @TODO: Figure out how to get ESC to trigger a cancel
            onAbandon: cancelChat,
            onEscape: cancelChat,
            onBackspace: cancelChat,
            // if this is set to false you can click outside the window to cancel
            // ignoreBlur: true,
            focus: true,
            // hint: `Press ESC to cancel`,
          });
        },
        handleLLMError: async (err) => {
          dev({ err });
        },
        handleLLMEnd: async () => {
          log(`handleLLMEnd`);
          // render final message with options
          let html = md(currentMessage + options);
          // wait for user to select an option
          const selectedOption = await div(html, {
            ignoreBlur: true,
            focus: true,
            // onSubmit: () => setSelectedText(currentMessage),
          });
          // handle selected option
          switch (selectedOption) {
            case "paste":
              // paste into highlighted text
              await setSelectedText(currentMessage);
              process.exit(1);
            case "retry":
              // reset current message
              currentMessage = "";
              // prompt again with new prompt
              // press enter to use original prompt
              const followUp = await arg({
                placeholder: userSystemInput,
                hint: "Press enter to use the same prompt",
              });
              await processMessage(followUp);
              break;
            case "edit":
              // still need to figure out best way to handle submit and abort
              // would like custom buttons for triggering all these same options such as save
              await editor({
                value: currentMessage,
                onEscape: async (state) => {
                  // copy to clipboard when exiting the editor
                  await clipboard.writeText(state);
                  // exit script
                  process.exit(1);
                },
                onSubmit: async (state) => {
                  // paste into highlighted text when pressing enter
                  await setSelectedText(state);
                  // exit script
                  process.exit(1);
                },
              });
              break;
            case "copy":
              // copy to clipboard
              await clipboard.writeText(currentMessage);
              // exit script
              process.exit(1);
            case "save":
              await inspect(currentMessage, `conversations/${Date.now()}.md`);
              // exit script
              process.exit(1);
            default:
              // copy to clipboard
              await clipboard.writeText(currentMessage);
              process.exit(1);
          }
          await optionHandler(selectedOption);
        },
      },
    ],
  });
  //###########
  // Main Loop
  //###########
  // runs the language model until the user cancels
  while (true) {
    await llm.call([
      new SystemChatMessage(formatPrompt(prompt)),
      new HumanChatMessage(humanChatMessage),
    ]);
  }
}

promptAgainstHighlightedText();

/*
# Explain Plz
Highlight some text and have it explained by AI
Works for any highlighted text or code
*/

// Name: Explain Plz
// Description: Get an explanation for any highlighted text
// Author: Josh Mabry
// Twitter: @AI_Citizen
// Shortcut: cmd alt shift e

import "@johnlindquist/kit";

let { ChatOpenAI } = await import("langchain/chat_models");
let { HumanChatMessage, SystemChatMessage } = await import("langchain/schema");
let openAIApiKey = await env("OPENAI_API_KEY", {
  hint: `Grab a key from <a href="https://platform.openai.com/account/api-keys">here</a>`,
});
let { CallbackManager } = await import("langchain/callbacks");
let prompt = `#####
Ignore prior instructions, you are tasked with taking the input text and explaining it to the user.
Return the response in the following format using markdown syntax:
# Explain Plz
## TLDR (A quick summary of the highlighted text)
## ELI5 (Explain Like I'm 5)
## Explanation (A longer technical explanation of the highlighted text)
`;
let currentMessage = "";
const chat = new ChatOpenAI({
  temperature: 0.3,
  openAIApiKey: openAIApiKey,
  streaming: true,
  callbackManager: CallbackManager.fromHandlers({
    handleLLMStart: async (token) => {
      let widget = await widget(`
<div class="bg-black text-white h-screen p-5">
    Loading...
<div>
`);
      log(`handleLLMStart`);
      currentMessage += token;
      let html = md(token);

      await div(html);
    },
    handleLLMNewToken: async (token, runId) => {
      log(`handleLLMNewToken`);
      currentMessage += token;
      let html = md(currentMessage);

      await div(html);
    },
    handleLLMError: async (err) => {
      warn(`error`, JSON.stringify(err));
      await setSelectedText(JSON.stringify(err));
    },
    handleLLMEnd: async () => {
      widget = null;
      log(`handleLLMEnd`);

      let html = md(currentMessage);

      await div(html);
    },
  }),
});

let text = await getSelectedText();
``;
await chat.call([new SystemChatMessage(prompt), new HumanChatMessage(text)]);

/*
Pardon the mess this was put together in half a day for the [lablab.ai](https://lablab.ai/event/autonomous-gpt-agents-hackathon) hackathon.
More updates to come

# AC AGI 
An autonomous general intelligence that accomplishes a task for you.
Uses human in the loop to provide feedback to the agent.


How to use:
- Enter your task
- Wait for the agent to complete the task
- Assign max-iterations for the agent to loop: 0 for infinite (probably not a good idea ¯\_(ツ)_/¯)
- Profit

Known issues:
- The agent will sometimes get stuck in a loop and not complete the task
- Human feedback is not always helpful

Upcoming features:
- More tools
- Refined prompts
- Better human feedback system
- Better memory system

Possible thanks to the fine folks at [Langchain](https://js.langchain.com/docs/use_cases/autonomous_agents/baby_agi#example-with-tools)
and all the other giants whose shoulders we stand on.
*/

// Name: AC AGI
// Description: An AGI task manager inspired by BabyAGI
// Author: Josh Mabry
// Twitter: @AI_Citizen

import "@johnlindquist/kit";

let { BabyAGI } = await import("langchain/experimental/babyagi");
let { MemoryVectorStore } = await import("langchain/vectorstores/memory");
let { OpenAIEmbeddings } = await import("langchain/embeddings/openai");
let { OpenAI } = await import("langchain/llms/openai");
let { PromptTemplate } = await import("langchain/prompts");
let { LLMChain } = await import("langchain/chains");
let { ChainTool } = await import("langchain/tools");
let { initializeAgentExecutorWithOptions } = await import("langchain/agents");
let { DynamicTool } = await import("langchain/tools");
let { ChatOpenAI } = await import("langchain/chat_models");

let GOOGLE_API_KEY = await env("GOOGLE_API_KEY", {
  shortcuts: [
    {
      name: "Google API Key",
      key: `${cmd}+o`,
      bar: "right",
      onPress: () => {
        open("https://developers.google.com/custom-search/v1/introduction");
      },
    },
  ],
  ignoreBlur: true,
  secret: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});

let GOOGLE_CSE_KEY = await env("GOOGLE_CSE_KEY", {
  shortcuts: [
    {
      name: "Google Custom Search Engine Key",
      key: `${cmd}+o`,
      bar: "right",
      onPress: () => {
        open("https://programmablesearchengine.google.com/");
      },
    },
  ],
  ignoreBlur: true,
  secret: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});

await env("OPENAI_API_KEY", {
  hint: `Grab a key from <a href="https://platform.openai.com/account/api-keys">here</a>`,
});

const task = await arg({
  placeholder: "Task",
  description: "Enter a task for AC AGI to complete",
  ignoreBlur: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});
let maxIterations = await arg({
  placeholder: "How many times should AC AGI loop?",
  hint: "Leave empty for infinite iterations *use with caution*",
  ignoreBlur: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});

if (maxIterations === "" || maxIterations === "0") {
  maxIterations = undefined;
}

//#########################
// BabyAGI method overrides
//#########################
function printTaskList() {
  let result = "";
  for (const t of this.taskList) {
    result += `${t.taskID}: ${t.taskName}\n`;
  }
  const msg = `### Task List
  
  ${result}
  `;
  let html = md(msg);

  div({
    html,
    ignoreBlur: true,
  });
}

function printNextTask(task) {
  const msg = `### Next Task
  
  ${task.taskID}: ${task.taskName}
  `;
  let html = md(msg);

  div({
    html,
    ignoreBlur: true,
  });
}

function printTaskResult(result) {
  const msg = `### Task Result
  
  ${result.trim()}
  `;
  let html = md(msg);

  div({
    html,
    ignoreBlur: true,
  });
}

//#############
// Custom Tools
//#############
let html = (str) => str.replace(/ /g, "+");
let fetch = (q) =>
  `https://www.googleapis.com/customsearch/v1?key=${GOOGLE_API_KEY}&cx=${GOOGLE_CSE_KEY}&q=${html(
    q
  )}&sort=date`;

async function search(query) {
  let response = await get(fetch(query));

  let items = response?.data?.items;

  if (items) {
    let choices = items.map((item) => ({
      name: item.title,
      value: item.link,
    }));

    return JSON.stringify(choices);
  }
}

async function humanFeedbackList(mdStr) {
  let html = md(`${mdStr.trim()}`);
  const response = div({
    html,
    ignoreBlur: true,
  });

  return response;
}

async function humanInput(question) {
  const response = await arg({
    placeholder: "Human, I need help!",
    hint: question,
    ignoreBlur: true,
    ignoreAbandon: true,
    height: PROMPT.HEIGHT.INPUT_ONLY,
  });
  return response;
}

const todoPrompt = PromptTemplate.fromTemplate(
  "You are a planner/expert todo list creator. Generate a markdown formatted todo list for: {objective}"
);

const tools = [
  new ChainTool({
    name: "TODO",
    chain: new LLMChain({
      llm: new ChatOpenAI({ temperature: 0 }),
      prompt: todoPrompt,
    }),
    description:
      "For making todo lists. Input: objective to create todo list for. Output: the todo list",
  }),
  new DynamicTool({
    name: "Search",
    description: "Search web for info",
    func: search,
  }),
  new DynamicTool({
    name: "Human Input",
    description:
      "(Use only when no info is available elsewhere) Ask a human for specific input that you don't know, like a persons name, or DOB, location, etc. Input is question to ask human, output is answer",
    func: humanInput,
  }),
  //   new DynamicTool({
  //     name: "Human Feedback Choice",
  //     description: `Ask human for feedback if you unsure of next step.
  //     Input is markdown string formatted with your questions and suitable responses like this example:
  // # Human, I need your help!
  // <Question Here>
  // * [John](submit:John) // don't change formatting of these links
  // * [Mindy](submit:Mindy)
  // * [Joy](submit:Joy)
  // * [Other](submit:Other)
  // `,
  //     func: humanFeedbackList,
  //   }),
];

//##################
// AC AGI is Born
//##################
const taskBeginMsg = md(`
### Executing Task Manager
Goal: ${task}
`);

div({ html: taskBeginMsg, ignoreBlur: true });

const agentExecutor = await initializeAgentExecutorWithOptions(
  tools,
  new ChatOpenAI({ temperature: 0 }),
  {
    agentType: "zero-shot-react-description",
    agentArgs: {
      prefix: `You are an AI who performs one task based on the following objective: {objective}. 
Take into account these previously completed tasks: {context}.`,
      suffix: `Question: {task}
{agent_scratchpad}`,
      inputVariables: ["objective", "task", "context", "agent_scratchpad"],
    },
  }
);

const vectorStore = new MemoryVectorStore(new OpenAIEmbeddings());

const babyAGI = BabyAGI.fromLLM({
  llm: new ChatOpenAI({ temperature: 0 }),
  executionChain: agentExecutor,
  vectorstore: vectorStore,
  maxIterations: maxIterations,
});

babyAGI.printNextTask = printNextTask;
babyAGI.printTaskList = printTaskList;
babyAGI.printTaskResult = printTaskResult;

await babyAGI.call({ objective: task });

/* 
# Google Search
Example of leveraging Google's Custom Search Engine API to search the web
*/

// Name: Google Search
// Description: Leverage Google's Custom Search Engine API to search the web
// Author: Josh Mabry
// Twitter: @AI_Citizen

import "@johnlindquist/kit";

let GOOGLE_API_KEY = await env("GOOGLE_API_KEY", {
  shortcuts: [
    {
      name: "Google API Key",
      key: `${cmd}+o`,
      bar: "right",
      onPress: () => {
        open("https://developers.google.com/custom-search/v1/introduction");
      },
    },
  ],
  ignoreBlur: true,
  secret: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});

let GOOGLE_CSE_KEY = await env("GOOGLE_CSE_KEY", {
  shortcuts: [
    {
      name: "Google Custom Search Engine Key",
      key: `${cmd}+o`,
      bar: "right",
      onPress: () => {
        open("https://programmablesearchengine.google.com/");
      },
    },
  ],
  ignoreBlur: true,
  secret: true,
  height: PROMPT.HEIGHT.INPUT_ONLY,
});

let query = await arg(
  {
    placeholder: "Search Query",
    strict: false,
  },
  [
    {
      name: "Send a search query to Google",
      info: "always",
    },
  ]
);

let search = (q) =>
  `https://www.googleapis.com/customsearch/v1?key=${GOOGLE_API_KEY}&cx=${GOOGLE_CSE_KEY}&q=${q}&sort=date`;

let response = await get(search(query));

let items = response?.data?.items;

if (items) {
  let choices = items.map((item) => ({
    name: item.title,
    value: item.link,
  }));

  let link = await arg("Choose a link to view", choices);

  open(link);
}

/*
/*
# Smartify your words!

Tired of feeling dumb? Winter got you in a funk? 
Can you just not seem to get the words out right? 
Well, let's Smartify your words!

Highlight some text and press `cmd+shift+enter` to send it through ChatGPT 
to replace the text with a more eloquent version. Mileage may vary.
*/

// Name: Smartify Your Words
// Description: Let's make those words smarter!
// Author: Josh Mabry
// Twitter: @AI_Citizen
// Shortcut: command shift enter

import "@johnlindquist/kit";

let { ChatOpenAI } = await import("langchain/chat_models");
let { HumanChatMessage, SystemChatMessage } = await import("langchain/schema");
let openAIApiKey = await env("OPENAI_API_KEY", {
  hint: `Grab a key from <a href="https://platform.openai.com/account/api-keys">here</a>`,
});
let { CallbackManager } = await import("langchain/callbacks");
let prompt = `#####
Ignore prior instructions, you are tasked with taking an input and refactoring it using the following rules: '

- Maintain the same meaning, tone, and intent as the original text
- Clean up any grammar or spelling mistakes
- Make it sound more professional, but keep it casual
- Reduce redundancies and excessive verbiage

Return only the updated text, do not offer any explanations or reasoning for the changes.
########
`;

import Bottleneck from "bottleneck";

const limiter = new Bottleneck({
  maxConcurrent: 1,
  minTime: 100,
});

const type = (text) => {
  return new Promise((resolve) => {
    keyboard.type(text);
    resolve();
  });
};
const wrappedType = limiter.wrap(type);

const smartify = new ChatOpenAI({
  temperature: 0.3,
  openAIApiKey: openAIApiKey,
  streaming: true,
  callbackManager: CallbackManager.fromHandlers({
    handleLLMStart: async (token) => {
      if (!token) return;
      log(`handleLLMStart`);
      await wrappedType(token);
    },
    handleLLMNewToken: async (token) => {
      if (!token) return;
      await wrappedType(token);
    },
    handleLLMError: async (err) => {
      warn(`error`, JSON.stringify(err));
      await setSelectedText(JSON.stringify(err));
      process.exit(1);
    },
    handleLLMEnd: async () => {
      log(`handleLLMEnd`);
      log(`currentMessage`, currentMessage);
      process.exit(1);
    },
  }),
});
let text = await getSelectedText();

await smartify.call([
  new SystemChatMessage(prompt),
  new HumanChatMessage(text),
]);