1"use strict";(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[9023],{9023:(e,t,n)=>{n.r(t),n.d(t,{default:()=>T});var a=n(5155),r=n(2115),i=n(9535),s=n(2553),o=n(4975),d=n(352),l=n(9763),c=n(3638),h=n(8490),g=n(1166),p=n(4748),m=n(682),u=n(508),x=n(6541),f=n(4856);let y="/**\n * Tools mode.\n *\n * The node runs an OpenAI function-calling loop (up to 8 rounds) against this agent's model, with the system\n * prompt from the form. Whenever the model asks for one of the tools below, the node calls its run(args, ctx)\n * and hands the return value back to the model. You write the tools; the conversation is handled for you.\n *\n * ctx.fetch(url, init) â the only way out of the sandbox. Only the \"allowed hosts\" on the form answer.\n * ctx.secret('NAME') â a value you stored under one of the form's secret names (undefined if unset).\n * ctx.log(...) â goes to this agent's log, which only you can read.\n */\n\nexport const tools = [\n {\n name: 'text_stats',\n description: 'Count words, sentences and characters in a piece of text.',\n parameters: {\n type: 'object',\n properties: { text: { type: 'string', description: 'The text to measure' } },\n required: ['text'],\n },\n async run(args, ctx) {\n const text = String(args?.text ?? '');\n const words = text.trim() ? text.trim().split(/\\s+/).length : 0;\n const sentences = text.split(/[.!?ã]+/).filter((s) => s.trim()).length;\n ctx.log('text_stats', { words, sentences });\n return { words, sentences, characters: text.length };\n },\n },\n {\n name: 'today',\n description: 'The current date and time in UTC, as ISO 8601.',\n parameters: { type: 'object', properties: {} },\n async run() {\n return { now: new Date().toISOString() };\n },\n },\n // Calling an external API â add its host to \"allowed hosts\" and its key to the secrets first:\n //\n // {\n // name: 'weather',\n // description: 'Current weather for a city.',\n // parameters: { type: 'object', properties: { city: { type: 'string' } }, required: ['city'] },\n // async run(args, ctx) {\n // const res = await ctx.fetch(\n // 'https://api.example.com/weather?q=' + encodeURIComponent(args.city),\n // { headers: { authorization: 'Bearer ' + ctx.secret('WEATHER_API_KEY') } },\n // );\n // if (!res.ok) return { error: 'weather service answered ' + res.status };\n // return await res.json();\n // },\n // },\n];\n",j="/**\n * Handler mode.\n *\n * execute(input, ctx) receives every message and decides the reply itself â no model is called unless you call\n * it. Good for deterministic pipelines: score something, look something up, write something somewhere.\n *\n * input â the message text (a string); ctx.input also has { text, contextId, history }\n * ctx.llm.chat({ messages, temperature?, max_tokens? }) â { message, finish_reason }, on this agent's model\n * ctx.fetch(url, init) â the only way out of the sandbox. Only the \"allowed hosts\" on the form answer.\n * ctx.secret('NAME') â a value stored under one of the form's secret names (undefined if unset)\n * ctx.ui â A2UI helpers: surface(id, components, data), text, column, row, card, divider, list, bind\n * ctx.log(...) â goes to this agent's log, which only you can read\n *\n * Return a string, or { text, ui }. text is what every client shows; ui is drawn by clients that speak A2UI\n * (tick \"A2UI\" on the form so the agent card says so).\n */\n\nexport async function execute(input, ctx) {\n const text = String(input ?? '').trim();\n if (!text) return 'Send me a paragraph and I will score how easy it is to read.';\n\n // A small, deterministic score: shorter sentences and shorter words read more easily.\n const sentences = text.split(/[.!?ã]+/).map((s) => s.trim()).filter(Boolean);\n const words = text.split(/\\s+/).filter(Boolean);\n const wordsPerSentence = words.length / Math.max(1, sentences.length);\n const lettersPerWord = words.join('').length / Math.max(1, words.length);\n const score = Math.max(0, Math.min(100, Math.round(120 - wordsPerSentence * 2.5 - lettersPerWord * 6)));\n const verdict = score >= 70 ? 'Easy to read' : score >= 40 ? 'Takes some effort' : 'Hard going';\n ctx.log('scored', { score, sentences: sentences.length, words: words.length });\n\n // Writing the result somewhere â add the host to \"allowed hosts\" and the key to the secrets first:\n //\n // await ctx.fetch('https://api.example.com/scores', {\n // method: 'POST',\n // headers: { 'content-type': 'application/json', authorization: 'Bearer ' + ctx.secret('EXAMPLE_API_KEY') },\n // body: JSON.stringify({ score, verdict }),\n // });\n\n const ui = ctx.ui.surface('score', [\n ctx.ui.card('root', 'body'),\n ctx.ui.column('body', ['title', 'score', 'verdict', 'rule', 'detail']),\n ctx.ui.text('title', 'Readability', 'h3'),\n ctx.ui.text('score', ctx.ui.bind('/score'), 'h1'),\n ctx.ui.text('verdict', ctx.ui.bind('/verdict')),\n ctx.ui.divider('rule'),\n ctx.ui.text('detail', ctx.ui.bind('/detail'), 'caption'),\n ], {\n score: score
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Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.