Use prettier to indent the Typescript code

typescript/.eslintrc.json

@@ -0,0 +1,27 @@
+{
+    "env": {
+        "node": true
+    },
+    "extends": [
+        "eslint:recommended",
+        "plugin:@typescript-eslint/eslint-recommended",
+        "plugin:@typescript-eslint/recommended"
+    ],
+    "parser": "@typescript-eslint/parser",
+    "parserOptions": {
+        "ecmaVersion": 8,
+        "sourceType": "module"
+    },
+    "plugins": [
+        "@typescript-eslint"
+    ],
+     "rules": {
+        "no-empty": ["error", { "allowEmptyCatch": true }],
+        "@typescript-eslint/no-this-alias": "off",
+        "@typescript-eslint/no-explicit-any": "off",
+        "@typescript-eslint/no-non-null-assertion": "off",
+        "@typescript-eslint/no-unused-vars": "off"
+    }
+}
+
+

typescript/.prettierrc

@@ -0,0 +1,7 @@
+{
+  "semi": true,
+  "tabWidth": 4,
+  "trailingComma": "none",
+  "singleQuote": false,
+  "printWidth": 80
+}

typescript/Makefile

@@ -5,7 +5,7 @@ all: node_modules
 	$(MAKE) build
 
 vs:
-	open -a "Visual Studio Code" . || vscode .
+	open -a "Visual Studio Code" async || vscode .
 
 
 SYNCREGEX=

typescript/async/ai.ts

@@ -1,38 +1,38 @@
-import { R, Module, Process, Thread } from "./r2papi.js"
+import { R, Module, Process, Thread } from "./r2papi.js";
 import { r2, R2PipeAsync } from "./r2pipe.js";
 
 /**
  * Class that interacts with the `r2ai` plugin (requires `rlang-python` and `r2i` r2pm packages to be installed).
  * Provides a way to script the interactions with different language models using javascript from inside radare2.
- * 
+ *
  * @typedef R2AI
  */
 export class R2AI {
-	/**
-	 * Instance variable that informs if the `r2ai` plugin is loaded, must be true in order to use the rest of the methods of this class.
-	 *
-	 * @type {boolean}
-	 */
-	available: boolean = false;
-	/**
-	 * Name of the model instantiated to be used for the subsequent calls.
-	 *
-	 * @type {string}
-	 */
-	model: string = "";
-	r2: R2PipeAsync;
+    /**
+     * Instance variable that informs if the `r2ai` plugin is loaded, must be true in order to use the rest of the methods of this class.
+     *
+     * @type {boolean}
+     */
+    available: boolean = false;
+    /**
+     * Name of the model instantiated to be used for the subsequent calls.
+     *
+     * @type {string}
+     */
+    model: string = "";
+    r2: R2PipeAsync;
 
-	constructor(r2: R2PipeAsync, num?: number, model?: string) {
-		this.r2 = r2;
-		this.available = false;
-	}
+    constructor(r2: R2PipeAsync, num?: number, model?: string) {
+        this.r2 = r2;
+        this.available = false;
+    }
 
-	async checkAvailability() : Promise<boolean> {
-		if (this.available) {
-			return true;
-		}
-		this.available = r2.cmd('r2ai -h').trim() !== "";
-		/*
+    async checkAvailability(): Promise<boolean> {
+        if (this.available) {
+            return true;
+        }
+        this.available = r2.cmd("r2ai -h").trim() !== "";
+        /*
 		if (this.available) {
 			if (num) {
 				r2.call(`r2ai -n ${num}`)
@@ -43,78 +43,82 @@ export class R2AI {
 			}
 		}
 		*/
-		return this.available;
-	}
-	/**
-	 * Reset conversation messages
-	 */
-	async reset() {
-		await this.checkAvailability();
-		if (this.available) {
-			await r2.call('r2ai -R')
-		}
-	}
-	/**
-	 * Set the role (system prompt) message for the language model to obey.
-	 *
-	 * @param {string} text containing the system prompt
-	 * @returns {boolean} true if successful
-	 */
-	async setRole(msg: string): Promise<boolean> {
-		if (this.available) {
-			await r2.call(`r2ai -r ${msg}`);
-			return true;
-		}
-		return false;
-	}
-	/**
-	 * Set the Model name or path to the GGUF file to use.
-	 *
-	 * @param {string} model name or path to GGUF file
-	 * @returns {boolean} true if successful
-	 */
-	async setModel(modelName: string): Promise<boolean> {
-		if (this.available) {
-			await r2.call(`r2ai -m ${this.model}`)
-			return true;
-		}
-		return false;
-	}
-	/**
-	 * Get the current selected model name.
-	 *
-	 * @returns {boolean} model name
-	 */
-	async getModel(): Promise<string> {
-		if (this.available) {
-			this.model = await r2.call("r2ai -m").trim();
-		}
-		return this.model;
-	}
-	/**
-	 * Get a list of suggestions for model names to use.
-	 *
-	 * @returns {string[]} array of strings containing the model names known to work
-	 */
-	async listModels(): Promise<string[]> {
-		if (this.available) {
-			const models = await r2.call("r2ai -M");
-			return models.replace(/-m /, "").trim().split(/\n/g).filter((x: string) => x.indexOf(":") !== -1);
-		}
-		return [];
-	}
-	/**
-	 * Send message to the language model to be appended to the current conversation (see `.reset()`)
-	 *
-	 * @param {string} text sent from the user to the language model
-	 * @returns {string} response from the language model
-	 */
-	async query(msg: string): Promise<string> {
-		if (!this.available || msg == '') {
-			return '';
-		}
-		const fmsg = msg.trim().replace(/\n/g, '.');
-		const response = r2.call(`r2ai ${fmsg}`);
-		return response.trim();
-	}
+        return this.available;
+    }
+    /**
+     * Reset conversation messages
+     */
+    async reset() {
+        await this.checkAvailability();
+        if (this.available) {
+            await r2.call("r2ai -R");
+        }
+    }
+    /**
+     * Set the role (system prompt) message for the language model to obey.
+     *
+     * @param {string} text containing the system prompt
+     * @returns {boolean} true if successful
+     */
+    async setRole(msg: string): Promise<boolean> {
+        if (this.available) {
+            await r2.call(`r2ai -r ${msg}`);
+            return true;
+        }
+        return false;
+    }
+    /**
+     * Set the Model name or path to the GGUF file to use.
+     *
+     * @param {string} model name or path to GGUF file
+     * @returns {boolean} true if successful
+     */
+    async setModel(modelName: string): Promise<boolean> {
+        if (this.available) {
+            await r2.call(`r2ai -m ${this.model}`);
+            return true;
+        }
+        return false;
+    }
+    /**
+     * Get the current selected model name.
+     *
+     * @returns {boolean} model name
+     */
+    async getModel(): Promise<string> {
+        if (this.available) {
+            this.model = await r2.call("r2ai -m").trim();
+        }
+        return this.model;
+    }
+    /**
+     * Get a list of suggestions for model names to use.
+     *
+     * @returns {string[]} array of strings containing the model names known to work
+     */
+    async listModels(): Promise<string[]> {
+        if (this.available) {
+            const models = await r2.call("r2ai -M");
+            return models
+                .replace(/-m /, "")
+                .trim()
+                .split(/\n/g)
+                .filter((x: string) => x.indexOf(":") !== -1);
+        }
+        return [];
+    }
+    /**
+     * Send message to the language model to be appended to the current conversation (see `.reset()`)
+     *
+     * @param {string} text sent from the user to the language model
+     * @returns {string} response from the language model
+     */
+    async query(msg: string): Promise<string> {
+        if (!this.available || msg == "") {
+            return "";
+        }
+        const fmsg = msg.trim().replace(/\n/g, ".");
+        const response = r2.call(`r2ai ${fmsg}`);
+        return response.trim();
+    }
 }

typescript/async/base64.ts

@@ -1,26 +1,26 @@
 export class Base64 {
-	/**
-	 * Encode the given input string using base64
-	 *
-	 * @param {string} input string to encode
-	 * @returns {string} base64 encoded string
-	 */
-	static encode(input: string): string {
-		return b64(input);
-	}
-	/**
-	 * Decode the given base64 string into plain text
-	 *
-	 * @param {string} input string encoded in base64 format
-	 * @returns {string} base64 decoded string
-	 */
-	static decode(input: string): string {
-		return b64(input, true);
-	}
+    /**
+     * Encode the given input string using base64
+     *
+     * @param {string} input string to encode
+     * @returns {string} base64 encoded string
+     */
+    static encode(input: string): string {
+        return b64(input);
+    }
+    /**
+     * Decode the given base64 string into plain text
+     *
+     * @param {string} input string encoded in base64 format
+     * @returns {string} base64 decoded string
+     */
+    static decode(input: string): string {
+        return b64(input, true);
+    }
 }
 
 export interface Base64Interface {
-	(message: string, decode?: boolean): string;
+    (message: string, decode?: boolean): string;
 }
 
 export declare const b64: Base64Interface;

typescript/async/elang.ts

@@ -4,31 +4,30 @@ import { R2PipeAsync } from "./index";
 //
 
 export class EsilLang {
-	[vars : string]: any;
-	constructor() {
-		this.vars = {};
-	}
-	set(obj: any, val: any) {
-		this.vars[obj] = val;
-	}
-	fun(name: string, code: any[]) {
-		this.vars[name] = code;
-	}
-	get(varname: string) : any {
-		if (varname in Object.keys(this.vars)) {
-			return this.vars[varname];
-		}
-		this.vars[varname] = 0;
-		return 0;
-	}
-	println(...args: any) {
-		console.log(...args);
-	}
-	eval(code: string) {
-	}
+    [vars: string]: any;
+    constructor() {
+        this.vars = {};
+    }
+    set(obj: any, val: any) {
+        this.vars[obj] = val;
+    }
+    fun(name: string, code: any[]) {
+        this.vars[name] = code;
+    }
+    get(varname: string): any {
+        if (varname in Object.keys(this.vars)) {
+            return this.vars[varname];
+        }
+        this.vars[varname] = 0;
+        return 0;
+    }
+    println(...args: any) {
+        console.log(...args);
+    }
+    eval(code: string) {}
 }
 
-// basic elements: array, string, 
+// basic elements: array, string,
 // console.log("Hello Lang");
 const el = new EsilLang();
 const code = `[