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import { prebuiltAppConfig, CreateMLCEngine } from "@charliefruan/web-llm"; |
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import hljs from "highlight.js"; |
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import ace from "ace-builds"; |
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require("ace-builds/src-noconflict/mode-javascript"); |
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require("ace-builds/webpack-resolver"); |
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const { Type } = require("@sinclair/typebox"); |
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let engine = null; |
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let useCustomGrammar = false; |
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document.addEventListener("DOMContentLoaded", () => { |
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const grammarSelection = document.getElementById("grammar-selection"); |
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const ebnfContainer = document.getElementById("ebnf-grammar-container"); |
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const schemaContainer = document.getElementById("schema-container"); |
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const modelSelection = document.getElementById("model-selection"); |
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const ebnfTextarea = document.getElementById("ebnf-grammar"); |
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const promptTextarea = document.getElementById("prompt"); |
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const outputDiv = document.getElementById("output"); |
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const statsParagraph = document.getElementById("stats"); |
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grammarSelection.onchange = (ev) => { |
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console.log("Grammar selection changed:", ev.target.value); |
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if (ev.target.value === "json") { |
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ebnfContainer.classList.add("hidden"); |
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schemaContainer.classList.remove("hidden"); |
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useCustomGrammar = false; |
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} else { |
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ebnfContainer.classList.remove("hidden"); |
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schemaContainer.classList.add("hidden"); |
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useCustomGrammar = true; |
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} |
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}; |
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const availableModels = prebuiltAppConfig.model_list |
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.filter( |
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(m) => |
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m.model_id.startsWith("Llama-3") || |
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m.model_id.startsWith("Hermes-2") || |
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m.model_id.startsWith("Hermes-3") || |
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m.model_id.startsWith("Phi-3") |
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) |
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.map((m) => m.model_id); |
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let selectedModel = availableModels[0]; |
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availableModels.forEach((modelId) => { |
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const option = document.createElement("option"); |
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option.value = modelId; |
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option.textContent = modelId; |
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modelSelection.appendChild(option); |
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}); |
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modelSelection.value = selectedModel; |
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modelSelection.onchange = (e) => { |
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selectedModel = e.target.value; |
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engine = null; |
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}; |
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const jsonSchemaEditor = ace.edit("schema", { |
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mode: "ace/mode/javascript", |
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theme: "ace/theme/github", |
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wrap: true, |
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}); |
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jsonSchemaEditor.setTheme("ace/theme/github"); |
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jsonSchemaEditor.setValue(`Type.Object({ |
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"name": Type.String(), |
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"house": Type.Enum({ |
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"Gryffindor": "Gryffindor", |
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"Hufflepuff": "Hufflepuff", |
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"Ravenclaw": "Ravenclaw", |
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"Slytherin": "Slytherin", |
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}), |
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"blood_status": Type.Enum({ |
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"Pure-blood": "Pure-blood", |
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"Half-blood": "Half-blood", |
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"Muggle-born": "Muggle-born", |
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}), |
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"occupation": Type.Enum({ |
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"Student": "Student", |
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"Professor": "Professor", |
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"Ministry of Magic": "Ministry of Magic", |
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"Other": "Other", |
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}), |
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"wand": Type.Object({ |
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"wood": Type.String(), |
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"core": Type.String(), |
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"length": Type.Number(), |
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}), |
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"alive": Type.Boolean(), |
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"patronus": Type.String(), |
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})`); |
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const grammarEditor = ace.edit("ebnf-grammar", { |
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theme: "ace/theme/github", |
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wrap: true, |
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}); |
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grammarEditor.setTheme("ace/theme/github"); |
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grammarEditor.setValue(String.raw`main ::= basic_array | basic_object |
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basic_any ::= basic_number | basic_string | basic_boolean | basic_null | basic_array | basic_object |
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basic_integer ::= ("0" | "-"? [1-9] [0-9]*) ".0"? |
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basic_number ::= ("0" | "-"? [1-9] [0-9]*) ("." [0-9]+)? ([eE] [+-]? [0-9]+)? |
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basic_string ::= (([\"] basic_string_1 [\"])) |
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basic_string_1 ::= "" | [^"\\\x00-\x1F] basic_string_1 | "\\" escape basic_string_1 |
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escape ::= ["\\/bfnrt] | "u" [A-Fa-f0-9] [A-Fa-f0-9] [A-Fa-f0-9] [A-Fa-f0-9] |
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basic_boolean ::= "true" | "false" |
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basic_null ::= "null" |
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basic_array ::= "[" ("" | ws basic_any (ws "," ws basic_any)*) ws "]" |
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basic_object ::= "{" ("" | ws basic_string ws ":" ws basic_any ( ws "," ws basic_string ws ":" ws basic_any)*) ws "}" |
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ws ::= [\n\t]*`); |
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promptTextarea.value = `Hermione Granger is a character in Harry Potter. Please fill in the following information about this character in JSON format. |
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Name is a string of character name. |
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House is one of Gryffindor, Hufflepuff, Ravenclaw, Slytherin. |
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Blood status is one of Pure-blood, Half-blood, Muggle-born. |
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Occupation is one of Student, Professor, Ministry of Magic, Other. |
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Wand is an object with wood, core, and length. |
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Alive is a boolean. |
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Patronus is a string. |
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`; |
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document.getElementById("generate").onclick = async () => { |
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if (!engine) { |
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engine = await CreateMLCEngine(selectedModel, { |
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initProgressCallback: (progress) => { |
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console.log(progress); |
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outputDiv.textContent = progress.text; |
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}, |
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}); |
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} |
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let response_format = { type: "grammar", grammar: grammarEditor.getValue() }; |
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if (!useCustomGrammar) { |
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const schemaInput = jsonSchemaEditor.getValue(); |
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let T; |
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try { |
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T = eval(schemaInput); |
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} catch (e) { |
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console.error("Invalid schema", e); |
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return; |
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} |
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const schema = JSON.stringify(T); |
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response_format = { type: "json_object", schema } |
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} |
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console.log(response_format); |
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const request = { |
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stream: true, |
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stream_options: { include_usage: true }, |
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messages: [{ role: "user", content: promptTextarea.value }], |
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max_tokens: 512, |
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response_format, |
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}; |
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let curMessage = ""; |
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let usage = null; |
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const generator = await engine.chatCompletion(request); |
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for await (const chunk of generator) { |
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const curDelta = chunk.choices[0]?.delta.content; |
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if (curDelta) curMessage += curDelta; |
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if (chunk.usage) usage = chunk.usage; |
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outputDiv.textContent = curMessage; |
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} |
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const finalMessage = await engine.getMessage(); |
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outputDiv.innerHTML = hljs.highlight(finalMessage, { |
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language: "json", |
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}).value; |
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if (usage) { |
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const statsTextParts = []; |
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console.log(usage); |
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if (usage.extra.prefill_tokens_per_s) { |
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statsTextParts.push(`Prefill Speed: ${usage.extra.prefill_tokens_per_s.toFixed( |
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1 |
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)} tok/s`); |
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} |
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if (usage.extra.decode_tokens_per_s) { |
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statsTextParts.push(`Decode Speed: ${usage.extra.decode_tokens_per_s.toFixed( |
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1 |
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)} tok/s`); |
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} |
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if (usage.extra.time_per_output_token_s) { |
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statsTextParts.push(`Time Per Output Token: ${(1000 * usage.extra.time_per_output_token_s).toFixed( |
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0 |
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)} ms`); |
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} |
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if (usage.extra.time_to_first_token_s) { |
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statsTextParts.push(`Time to First Token: ${(1000 * usage.extra.time_to_first_token_s).toFixed( |
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0 |
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)} ms`); |
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} |
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if (usage.extra.grammar_init_s) { |
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statsTextParts.push(`Grammar Init Overhead: ${(1000 * usage.extra.grammar_init_s).toFixed( |
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0 |
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)} ms`); |
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} |
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if (usage.extra.grammar_per_token_s) { |
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statsTextParts.push(`Grammar Per-token Overhead: ${(1000 * usage.extra.grammar_per_token_s).toFixed( |
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2 |
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)} ms`); |
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} |
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statsParagraph.textContent = statsTextParts.join(", "); |
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statsParagraph.classList.remove("hidden"); |
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} |
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}; |
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}); |
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