Bump 0.9.0

+ added wikitools
+ Improved webpage reading tool

package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@ztimson/ai-utils",
-	"version": "0.8.6",
+	"version": "0.9.0",
 	"description": "AI Utility library",
 	"author": "Zak Timson",
 	"license": "MIT",
@@ -29,7 +29,7 @@
 		"@tensorflow/tfjs": "^4.22.0",
 		"@xenova/transformers": "^2.17.2",
 		"@ztimson/node-utils": "^1.0.7",
-		"@ztimson/utils": "^0.28.13",
+		"@ztimson/utils": "^0.28.16",
 		"cheerio": "^1.2.0",
 		"openai": "^6.22.0",
 		"tesseract.js": "^7.0.0"

src/antrhopic.ts

@@ -119,7 +119,7 @@ export class Anthropic extends LLMProvider {
 						if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
 						try {
 							const result = await tool.fn(toolCall.input, options?.stream, this.ai);
-							return {type: 'tool_result', tool_use_id: toolCall.id, content: JSONSanitize(result)};
+							return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
 						} catch (err: any) {
 							return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
 						}

src/llm.ts

@@ -1,3 +1,4 @@
+import {sum} from '@tensorflow/tfjs';
 import {JSONAttemptParse} from '@ztimson/utils';
 import {AbortablePromise, Ai} from './ai.ts';
 import {Anthropic} from './antrhopic.ts';
@@ -117,12 +118,13 @@ class LLM {
 						const score = (o ? this.cosineSimilarity(m.embeddings[0], o[0].embedding) : 0)
 							+ (q ? this.cosineSimilarity(m.embeddings[1], q[0].embedding) : 0);
 						return {...m, score};
-					}).toSorted((a: any, b: any) => a.score - b.score).slice(0, limit);
+					}).toSorted((a: any, b: any) => a.score - b.score).slice(0, limit)
+						.map(m => `- ${m.owner}: ${m.fact}`).join('\n');
 				}
 
 				options.system += '\nYou have RAG memory and will be given the top_k closest memories regarding the users query. Save anything new you have learned worth remembering from the user message using the remember tool and feel free to recall memories manually.\n';
 				const relevant = await search(message);
-				if(relevant.length) options.history.push({role: 'tool', name: 'recall', id: 'auto_recall_' + Math.random().toString(), args: {}, content: 'Things I remembered:\n' + relevant.map(m => `${m.owner}: ${m.fact}`).join('\n')});
+				if(relevant.length) options.history.push({role: 'tool', name: 'recall', id: 'auto_recall_' + Math.random().toString(), args: {}, content: `Things I remembered:\n${relevant}`});
 				options.tools = [{
 					name: 'recall',
 					description: 'Recall the closest memories you have regarding a query using RAG',
@@ -356,22 +358,64 @@ class LLM {
 	 * @returns {Promise<{} | {} | RegExpExecArray | null>}
 	 */
 	async json(text: string, schema: string, options?: LLMRequest): Promise<any> {
-		const code = await this.code(text, {...options, system: [
+		let system =  `Your job is to convert input to JSON using tool calls. Call the \`submit\` tool at least once with JSON matching this schema:\n\`\`\`json\n${schema}\n\`\`\`\n\nResponses are ignored`;
-			options?.system,
+		if(options?.system) system += '\n\n' + options.system;
-			`Only respond using JSON matching this schema:\n\`\`\`json\n${schema}\n\`\`\``
+		return new Promise(async (resolve, reject) => {
-		].filter(t => !!t).join('\n')});
+			let done = false;
-		return code ? JSONAttemptParse(code, {}) : null;
+			const resp = await this.ask(text, {
+				temperature: 0.3,
+				...options,
+				system,
+				tools: [{
+					name: 'submit',
+					description: 'Submit JSON',
+					args: {json: {type: 'string', description: 'Javascript parsable JSON string', required: true}},
+					fn: (args) => {
+						try {
+							const json = JSON.parse(args.json);
+							resolve(json);
+							done = true;
+						} catch { return 'Invalid JSON'; }
+						return 'Saved';
+					}
+				}, ...(options?.tools || [])],
+			});
+			if(!done) reject(`AI failed to create JSON:\n${resp}`);
+		});
 	}
 
 	/**
 	 * Create a summary of some text
 	 * @param {string} text Text to summarize
-	 * @param {number} tokens Max number of tokens
+	 * @param {number} length Max number of words
 	 * @param options LLM request options
 	 * @returns {Promise<string>} Summary
 	 */
-	summarize(text: string, tokens: number = 500, options?: LLMRequest): Promise<string | null> {
+	async summarize(text: string, length: number = 500, options?: LLMRequest): Promise<string | null> {
-		return this.ask(text, {system: `Generate the shortest summary possible <= ${tokens} tokens. Output nothing else`, temperature: 0.3, ...options});
+		let system =  `Your job is to summarize the users message using tool calls. Call the \`submit\` tool at least once with the shortest summary possible that's <= ${length} words. The tool call will respond with the token count. Responses are ignored`;
+		if(options?.system) system += '\n\n' + options.system;
+		return new Promise(async (resolve, reject) => {
+			let done = false;
+			const resp = await this.ask(text, {
+				temperature: 0.3,
+				...options,
+				system,
+				tools: [{
+					name: 'submit',
+					description: 'Submit summary',
+					args: {summary: {type: 'string', description: 'Text summarization', required: true}},
+					fn: (args) => {
+						if(!args.summary) return 'No summary provided';
+						const count = args.summary.split(' ').length;
+						if(count > length) return `Too long: ${length} words`;
+						done = true;
+						resolve(args.summary || null);
+						return `Saved: ${length} words`;
+					}
+				}, ...(options?.tools || [])],
+			});
+			if(!done) reject(`AI failed to create summary:\n${resp}`);
+		});
 	}
 }
 

src/open-ai.ts

@@ -148,7 +148,7 @@ export class OpenAi extends LLMProvider {
 						try {
 							const args = JSONAttemptParse(toolCall.function.arguments, {});
 							const result = await tool.fn(args, options.stream, this.ai);
-							return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize(result)};
+							return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
 						} catch (err: any) {
 							return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'})};
 						}

src/tools.ts

@@ -1,10 +1,12 @@
 import  * as cheerio from 'cheerio';
 import {$Sync} from '@ztimson/node-utils';
-import {ASet, consoleInterceptor, Http, fn as Fn} from '@ztimson/utils';
+import {ASet, consoleInterceptor, Http, fn as Fn, decodeHtml} from '@ztimson/utils';
 import * as os from 'node:os';
 import {Ai} from './ai.ts';
 import {LLMRequest} from './llm.ts';
 
+const UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
+
 const getShell = () => {
 	if(os.platform() == 'win32') return 'cmd';
 	return $Sync`echo $SHELL`?.split('/').pop() || 'bash';
@@ -51,6 +53,13 @@ export const CliTool: AiTool = {
 
 export const DateTimeTool: AiTool = {
 	name: 'get_datetime',
+	description: 'Get local date / time',
+	args: {},
+	fn: async () => new Date().toString()
+}
+
+export const DateTimeUTCTool: AiTool = {
+	name: 'get_datetime_utc',
 	description: 'Get current UTC date / time',
 	args: {},
 	fn: async () => new Date().toUTCString()
@@ -65,14 +74,15 @@ export const ExecTool: AiTool = {
 	},
 	fn: async (args, stream, ai) => {
 		try {
-			switch(args.type) {
+			switch(args.language) {
 				case 'cli':
 					return await CliTool.fn({command: args.code}, stream, ai);
 				case 'node':
 					return await JSTool.fn({code: args.code}, stream, ai);
-				case 'python': {
+				case 'python':
 					return await PythonTool.fn({code: args.code}, stream, ai);
-				}
+				default:
+					throw new Error(`Unsupported language: ${args.language}`);
 			}
 		} catch(err: any) {
 			return {error: err?.message || err.toString()};
@@ -104,9 +114,9 @@ export const JSTool: AiTool = {
 		code: {type: 'string', description: 'CommonJS javascript', required: true}
 	},
 	fn: async (args: {code: string}) => {
-		const console = consoleInterceptor(null);
+		const c = consoleInterceptor(null);
-		const resp = await Fn<any>({console}, args.code, true).catch((err: any) => console.output.error.push(err));
+		const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
-		return {...console.output, return: resp, stdout: undefined, stderr: undefined};
+		return {...c.output, return: resp, stdout: undefined, stderr: undefined};
 	}
 }
 
@@ -121,37 +131,107 @@ export const PythonTool: AiTool = {
 
 export const ReadWebpageTool: AiTool = {
 	name: 'read_webpage',
-	description: 'Extract clean, structured content from a webpage. Use after web_search to read specific URLs',
+	description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
 	args: {
-		url: {type: 'string', description: 'URL to extract content from', required: true},
+		url: {type: 'string', description: 'URL to read', required: true},
-		focus: {type: 'string', description: 'Optional: What aspect to focus on (e.g., "pricing", "features", "contact info")'}
+		mimeRegex: {type: 'string', description: 'Optional regex to filter MIME types (e.g., "^image/", "text/")'}
 	},
-	fn: async (args: {url: string; focus?: string}) => {
+	fn: async (args: {url: string; mimeRegex?: string}) => {
-		const html = await fetch(args.url, {headers: {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"}})
+		const ua = 'AiTools-Webpage/1.0';
-			.then(r => r.text()).catch(err => {throw new Error(`Failed to fetch: ${err.message}`)});
+		const maxSize = 10 * 1024 * 1024;
 
+		const response = await fetch(args.url, {
+			headers: {
+				'User-Agent': ua,
+				'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
+				'Accept-Language': 'en-US,en;q=0.5'
+			},
+			redirect: 'follow'
+		}).catch(err => {throw new Error(`Failed to fetch: ${err.message}`)});
+
+		const contentType = response.headers.get('content-type') || '';
+		const mimeType = contentType.split(';')[0].trim().toLowerCase();
+
+		if(args.mimeRegex && !new RegExp(args.mimeRegex, 'i').test(mimeType)) {
+			return `❌ MIME type rejected: ${mimeType} (filter: ${args.mimeRegex})`;
+		}
+
+		if(mimeType.match(/^(image|audio|video)\//)) {
+			const buffer = await response.arrayBuffer();
+			if(buffer.byteLength > maxSize) {
+				return `❌ File too large: ${(buffer.byteLength / 1024 / 1024).toFixed(1)}MB (max 10MB)\nType: ${mimeType}`;
+			}
+			const base64 = Buffer.from(buffer).toString('base64');
+			return `## Media File\n**Type:** ${mimeType}\n**Size:** ${(buffer.byteLength / 1024).toFixed(1)}KB\n**Data URL:** \`data:${mimeType};base64,${base64.slice(0, 100)}...\``;
+		}
+
+		if(mimeType.match(/^text\/(plain|csv|xml)/) || args.url.match(/\.(txt|csv|xml|md|yaml|yml)$/i)) {
+			const text = await response.text();
+			const truncated = text.length > 50000 ? text.slice(0, 50000) : text;
+			return `## Text File\n**Type:** ${mimeType}\n**URL:** ${args.url}\n\n${truncated}`;
+		}
+
+		if(mimeType.match(/application\/(json|xml|csv)/)) {
+			const text = await response.text();
+			const truncated = text.length > 50000 ? text.slice(0, 50000) : text;
+			return `## Structured Data\n**Type:** ${mimeType}\n**URL:** ${args.url}\n\n\`\`\`\n${truncated}\n\`\`\``;
+		}
+
+		if(mimeType === 'application/pdf' || (mimeType.startsWith('application/') && !mimeType.includes('html'))) {
+			const buffer = await response.arrayBuffer();
+			if(buffer.byteLength > maxSize) {
+				return `❌ File too large: ${(buffer.byteLength / 1024 / 1024).toFixed(1)}MB (max 10MB)\nType: ${mimeType}`;
+			}
+			const base64 = Buffer.from(buffer).toString('base64');
+			return `## Binary File\n**Type:** ${mimeType}\n**Size:** ${(buffer.byteLength / 1024).toFixed(1)}KB\n**Data URL:** \`data:${mimeType};base64,${base64.slice(0, 100)}...\``;
+		}
+
+		// HTML
+		const html = await response.text();
 		const $ = cheerio.load(html);
-		$('script, style, nav, footer, header, aside, iframe, noscript, [role="navigation"], [role="banner"], .ad, .ads, .cookie, .popup').remove();
+		$('script, style, nav, footer, header, aside, iframe, noscript, svg').remove();
-		const metadata = {
+		$('[role="navigation"], [role="banner"], [role="complementary"]').remove();
-			title: $('meta[property="og:title"]').attr('content') || $('title').text() || '',
+		$('[aria-hidden="true"], [hidden], .visually-hidden, .sr-only, .screen-reader-text').remove();
-			description: $('meta[name="description"]').attr('content') || $('meta[property="og:description"]').attr('content') || '',
+		$('.ad, .ads, .advertisement, .cookie, .popup, .modal, .sidebar, .related, .comments, .social-share').remove();
-		};
+		$('button, [class*="share"], [class*="follow"], [class*="social"]').remove();
-
+		const title = $('meta[property="og:title"]').attr('content') || $('title').text().trim() || '';
+		const description = $('meta[name="description"]').attr('content') || $('meta[property="og:description"]').attr('content') || '';
+		const author = $('meta[name="author"]').attr('content') || '';
 		let content = '';
-		const contentSelectors = ['article', 'main', '[role="main"]', '.content', '.post', '.entry', 'body'];
+		const selectors = ['article', 'main', '[role="main"]', '.content', '.post-content', '.entry-content', '.article-content'];
-		for (const selector of contentSelectors) {
+		for(const sel of selectors) {
-			const el = $(selector).first();
+			const el = $(sel).first();
-			if (el.length && el.text().trim().length > 200) {
+			if(el.length && el.text().trim().length > 200) {
-				content = el.text();
+				const paragraphs: string[] = [];
+				el.find('p').each((_, p) => {
+					const text = $(p).text().trim();
+					if(text.length > 80) paragraphs.push(text);
+				});
+				if(paragraphs.length > 2) {
+					content = paragraphs.join('\n\n');
 					break;
 				}
 			}
-		if (!content) content = $('body').text();
-		content = content.replace(/\s+/g, ' ').trim().slice(0, 8000);
-
-		return {url: args.url, title: metadata.title.trim(), description: metadata.description.trim(), content, focus: args.focus};
 		}
-}
+
+		if(!content) {
+			const paragraphs: string[] = [];
+			$('body p').each((_, p) => {
+				const text = $(p).text().trim();
+				if(text.length > 80) paragraphs.push(text);
+			});
+			content = paragraphs.slice(0, 30).join('\n\n');
+		}
+
+		// Decode escaped newlines and clean
+		const parts = [`## ${title || 'Webpage'}`];
+		if(description) parts.push(`_${description}_`);
+		if(author) parts.push(`👤 ${author}`);
+		parts.push(`🔗 ${args.url}\n`);
+		parts.push(content);
+		return decodeHtml(parts.join('\n\n').replaceAll(/\n{3,}/g, '\n\n'));
+	}
+};
 
 export const WebSearchTool: AiTool = {
 	name: 'web_search',
@@ -165,7 +245,7 @@ export const WebSearchTool: AiTool = {
 		length: number;
 	}) => {
 		const html = await fetch(`https://html.duckduckgo.com/html/?q=${encodeURIComponent(args.query)}`, {
-			headers: {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)", "Accept-Language": "en-US,en;q=0.9"}
+			headers: {"User-Agent": UA, "Accept-Language": "en-US,en;q=0.9"}
 		}).then(resp => resp.text());
 		let match, regex = /<a .*?href="(.+?)".+?<\/a>/g;
 		const results = new ASet<string>();
@@ -178,3 +258,94 @@ export const WebSearchTool: AiTool = {
 		return results;
 	}
 }
+
+class WikipediaClient {
+	private async get(url: string): Promise<any> {
+		const resp = await fetch(url, {headers: {'User-Agent': UA}});
+		return resp.json();
+	}
+
+	private api(params: Record<string, any>): Promise<any> {
+		const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
+		return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
+	}
+
+	private clean(text: string): string {
+		return text.replace(/\n{3,}/g, '\n\n').replace(/ {2,}/g, ' ').replace(/\[\d+\]/g, '').trim();
+	}
+
+	private truncate(text: string, max: number): string {
+		if(text.length <= max) return text;
+		const cut = text.slice(0, max);
+		const lastPara = cut.lastIndexOf('\n\n');
+		return lastPara > max * 0.7 ? cut.slice(0, lastPara) : cut;
+	}
+
+	private async searchTitles(query: string, limit = 6): Promise<any[]> {
+		const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
+		return data.query?.search || [];
+	}
+
+	private async fetchExtract(title: string, intro = false): Promise<string> {
+		const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
+		if(intro) params.exintro = 1;
+		const data = await this.api(params);
+		const page = Object.values(data.query?.pages || {})[0] as any;
+		return this.clean(page?.extract || '');
+	}
+
+	private pageUrl(title: string): string {
+		return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
+	}
+
+	private stripHtml(text: string): string {
+		return text.replace(/<[^>]+>/g, '');
+	}
+
+	async lookup(query: string, detail: 'intro' | 'full' = 'intro'): Promise<string> {
+		const results = await this.searchTitles(query, 6);
+		if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
+		const title = results[0].title;
+		const url = this.pageUrl(title);
+		const content = await this.fetchExtract(title, detail === 'intro');
+		const text = this.truncate(content, detail === 'intro' ? 2000 : 8000);
+		return `## ${title}\n🔗 ${url}\n\n${text}`;
+	}
+
+	async search(query: string): Promise<string> {
+		const results = await this.searchTitles(query, 8);
+		if(!results.length) return `❌ No results for "${query}"`;
+		const lines = [`### Search results for "${query}"\n`];
+		for(let i = 0; i < results.length; i++) {
+			const r = results[i];
+			const snippet = this.truncate(this.stripHtml(r.snippet || ''), 150);
+			lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
+		}
+		return lines.join('\n\n');
+	}
+}
+
+export const WikipediaLookupTool: AiTool = {
+	name: 'wikipedia_lookup',
+	description: 'Get Wikipedia article content',
+	args: {
+		query: {type: 'string', description: 'Topic or article title', required: true},
+		detail: {type: 'string', description: 'Content level: "intro" (summary, default) or "full" (complete article)', enum: ['intro', 'full'], default: 'intro'}
+	},
+	fn: async (args: {query: string; detail?: 'intro' | 'full'}) => {
+		const wiki = new WikipediaClient();
+		return wiki.lookup(args.query, args.detail || 'intro');
+	}
+};
+
+export const WikipediaSearchTool: AiTool = {
+	name: 'wikipedia_search',
+	description: 'Search Wikipedia for matching articles',
+	args: {
+		query: {type: 'string', description: 'Search terms', required: true}
+	},
+	fn: async (args: {query: string}) => {
+		const wiki = new WikipediaClient();
+		return wiki.search(args.query);
+	}
+};