Public vals
48
nbbaier
filterVals
filterVals This val exports a utility function that returns a list of all a user's val, filtered by a callback function. Example Get the names of all your private vals: import { filterVals } from "https://esm.town/v/nbbaier/filterVals";
const id = <user_id>
const vals = await filterVals(id, (v) => v.privacy === "private")
const privateValNames = vals.map(v => v.name);
Script
nbbaier
listSqliteTables
listSqliteTables Returns a flat array of the names of all tables in your Val Town SQLite database. import { listSqliteTables } from "https://esm.town/v/nbbaier/listSqliteTables";
console.log(await listSqliteTables())
Script
nbbaier
submitPR
Submit a PR from Val Town This val provides a (very) thin wrapper around the GH rest API methods for creating a pull request. It handles the creation of a Octokit client for you. Usage import { submitPR } from "https://esm.town/v/nbbaier/submitPR";
await submitPR(Deno.env.get("GH_REPO_TOKEN"), {
owner: "nbbaier",
repo: "test-ground",
head: "branch_2",
base: "main",
title: "trying another PR",
body: "cool stuff, take a look",
}); Parameters The function takes two parameters: your gh access token and an object that's identical to the object submitted to the gh API. See GH's documentation for more info!
Script
nbbaier
valToGH
valToGH A utility function for programmatically updating a GitHub repository with code retrieved from a Val. NOTE : This function currently does not change the contents of a file if it is already present. I will however be adding that functionality. Usage import { valToGH } from 'https://esm.town/v/nbbaier/valToGH';
const repo = "yourGitHubUser/yourRepo";
const val = "valUser/valName"; // or vals = ["valUser/valName1","valUser/valName2", ...]
const ghToken = Deno.env.get("yourGitHubToken");
const result = await valToGH(repo, val, ghToken);
console.log(result); Parameters repo : The GitHub repository in the format {user}/{repo} . val : A single repository in the format {user}/{val} . ghToken : Your GitHub token for authentication (must have write permission to the target repo) Options branch : Optional target branch. Default is main . prefix : Optional directory path prefix for each file. message : Optional commit message. Default is the current date and time in the format yyyy-MM-dd T HH:mm:ss UTC . ts : Optional flag to use a .ts extension for the committed file instead of the default .tsx .
Script
nbbaier
sqliteExplorerApp
SQLite Explorer View and interact with your Val Town SQLite data. It's based off Steve's excellent SQLite Admin val, adding the ability to run SQLite queries directly in the interface. This new version has a revised UI and that's heavily inspired by LibSQL Studio by invisal . This is now more an SPA, with tables, queries and results showing up on the same page. Install Install the latest stable version (v86) by forking this val: Authentication Login to your SQLite Explorer with password authentication with your Val Town API Token as the password. Todos / Plans [ ] improve error handling [ ] improve table formatting [ ] sticky table headers [x] add codemirror [ ] add loading indication to the run button (initial version shipped) [ ] add ability to favorite queries [ ] add saving of last query run for a table (started) [ ] add visible output for non-query statements [ ] add schema viewing [ ] add refresh to table list sidebar after CREATE/DROP/ALTER statements [ ] add automatic execution of initial select query on double click [x] add views to the sidebar [ ] add triggers to sidebar [ ] add upload from SQL, CSV and JSON [ ] add ability to connect to a non-val town Turso database [x] fix wonky sidebar separator height problem (thanks to @stevekrouse) [x] make result tables scrollable [x] add export to CSV, and JSON (CSV and JSON helper functions written in this val . Thanks to @pomdtr for merging the initial version!) [x] add listener for cmd+enter to submit query
HTTP
nbbaier
sqliteDump
SQLite Dump Util A utility function that generates SQL statements to dump the data and schema of tables in a SQLite database. Usage This example specifically dumps the users table and logs the output: import { sqliteDump } from "https://esm.town/v/nbbaier/sqliteDump";
const dump = await sqliteDump(["users"]);
console.log(dump) You can optionally specify a callback to handle the result. The example below dumps the users table and emails it using std/email . import { email } from "https://esm.town/v/std/email";
import { sqliteDump } from "https://esm.town/v/nbbaier/sqliteDump";
await sqliteDump(["users"], async (res) => {
await email({ text: res });
}); Function Signature function sqliteDump(tables?: string[], callback?: ((result: string) => string | void | Promise<void>) | undefined): Promise<string | void> Parameters tables : (Optional) Array of table names to include in the dump. If not provided, all tables will be included. callback : (Optional) An (potentially async) callback function to process the dump result. The callback receives the dump string as its argument.
Script
nbbaier
perplexityAPI
Perplexity API Wrapper This val exports a function pplx that provides an interface to the Perplexity AI chat completions API. You'll need a Perplexity AI API key, see their documentation for how to get started with getting a key. By default, the function will use PERPLEXITY_API_KEY in your val town env variables unless overridden by setting apiKey in the function. pplx(options: PplxRequest & { apiKey?: string }): Promise<PplxResponse> Generates a model's response for the given chat conversation. Required parameters in options are the following (for other parameters, see the Types section below): model ( string ): the name of the model that will complete your prompt. See below for possible values: pplx- 7b-chat , pplx-70b-chat , pplx-7b-online , pplx-70b-online , llama-2-70b-chat , codellama-34b -instruct , mistral-7b-instruct , and mixtral-8x7b-instruct . messages ( Message[] ): A list of messages comprising the conversation so far. A message object must contain role ( system , user , or assistant ) and content (a string). You can also specify an apiKey to override the default Deno.env.get("PERPLEXITY_API_KEY") . The function returns an object of types PplxResponse , see below. Types PplxRequest Request object sent to Perplexity models. | Property | Type | Description |
|---------------------|----------------------|-----------------------------------------------------------------|
| model | Model | The name of the model that will complete your prompt. Possible values: pplx- 7b-chat , pplx-70b-chat , pplx-7b-online , pplx-70b-online , llama-2-70b-chat , codellama-34b -instruct , mistral-7b-instruct , and mixtral-8x7b-instruct . |
| messages | Message[] | A list of messages comprising the conversation so far. |
| max_tokens | number | (Optional) The maximum number of completion tokens returned by the API. The total number of tokens requested in max_tokens plus the number of prompt tokens sent in messages must not exceed the context window token limit of model requested. If left unspecified, then the model will generate tokens until either it reaches its stop token or the end of its context window. |
| temperature | number | (Optional) The amount of randomness in the response, valued between 0 inclusive and 2 exclusive. Higher values are more random, and lower values are more deterministic. You should either set temperature or top_p, but not both. |
| top_p | number | (Optional) The nucleus sampling threshold, valued between 0 and 1 inclusive. For each subsequent token, the model considers the results of the tokens with top_p probability mass. You should either alter temperature or top_p, but not both. |
| top_k | number | (Optional) The number of tokens to keep for highest top-k filtering, specified as an integer between 0 and 2048 inclusive. If set to 0, top-k filtering is disabled. |
| stream | boolean | (Optional) Flag indicating whether to stream the response. |
| presence_penalty | number | (Optional) A value between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. Incompatible with frequency_penalty. |
| frequency_penalty | number | (Optional) A multiplicative penalty greater than 0. Values greater than 1.0 penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. A value of 1.0 means no penalty. Incompatible with presence_penalty. | PplxResponse Response object for pplx models. | Property | Type | Description |
|------------|-------------------------|--------------------------------------------------|
| id | string | The ID of the response. |
| model | Model | The model used for generating the response. |
| object | "chat.completion" | The type of object (always "chat.completion"). |
| created | number | The timestamp indicating when the response was created. |
| choices | CompletionChoices[] | An array of completion choices. | Please refer to the code for more details and usage examples of these types. Message Represents a message in a conversation. | Property | Type | Description |
|------------|-----------------------|--------------------------------------------------------|
| role | "system" \| "user" \| "assistant" | The role of the speaker in this turn of conversation. After the (optional) system message, user and assistant roles should alternate with user then assistant, ending in user. |
| content | string | The contents of the message in this turn of conversation. | CompletionChoices The list of completion choices the model generated for the input prompt. | Property | Type | Description |
|-------------------|-----------------------------------|-----------------------------------------------------|
| index | number | The index of the choice. |
| finish_reason | "stop" \| "length" | The reason the model stopped generating tokens. Possible values are stop if the model hit a natural stopping point, or length if the maximum number of tokens specified in the request was reached. |
| message | Message | The message generated by the model. |
| delta | Message | The incrementally streamed next tokens. Only meaningful when stream = true. |
Script
nbbaier
sqliteWriter
SQLite QueryWriter The QueryWriter class is a utility for generating and executing SQL queries using natural language and OpenAI. It provides a simplified interface for interacting with your Val Town SQLite database and generating SQL queries based on user inputs. This val is inspired by prisma-gpt . PRs welcome! See Todos below for some ideas I have. Usage Import the QueryWriter class into your script: import { QueryWriter } from "https://esm.town/v/nbbaier/sqliteWriter"; Create an instance of QueryWriter, providing the desired table and an optional model: const writer = new QueryWriter({ table: "my_table", model: "gpt-4-1106-preview" }); Call the writeQuery() method to generate an SQL query based on a user input string: const userInput = "Show me all the customers with more than $1000 in purchases.";
const query = await writer.writeQuery(userInput); Alternatively, use the gptQuery() method to both generate and execute the SQL query: const userInput = "Show me all the customers with more than $1000 in purchases.";
const result = await writer.gptQuery(userInput); Handle the generated query or query result according to your application's needs. API new QueryWriter(args: { table: string; model?: string }): QueryWriter Creates a new instance of the QueryWriter class. table : The name of the database table to operate on. model (optional): The model to use for generating SQL queries. Defaults to "gpt-3.5-turbo". apiKey (optional): An OpenAI API key. Defaults to Deno.env.get("OPENAI_API_KEY") . writeQuery(str: string): Promise<string> Generates an SQL query based on the provided user input string. str : The user input string describing the desired query. Returns a Promise that resolves to the generated SQL query. gptQuery(str: string): Promise<any> Generates and executes an SQL query based on the provided user input string. str : The user input string describing the desired query. Returns a Promise that resolves to the result of executing the generated SQL query. Todos [ ] Handle multiple tables for more complex use cases [ ] Edit prompt to allow for more than just SELECT queries [ ] Allow a user to add to the system prompt maybe? [ ] Expand usage beyond just Turso SQLite to integrate with other databases
Script