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|
//
"use client";
import React, {
type ReactNode,
useState,
useCallback,
useMemo,
useEffect,
startTransition,
useTransition,
} from "react";
import { Brain, Zap } from "lucide-react";
import { NLP } from "sortug-ai";
import GranularityMenu, { GranularityId } from "./LevelPicker";
import TextViewer from "./TextViewer";
import { wordAction } from "@/actions/lang";
import Modal from "@/components/Modal";
import { Spinner } from "@/components/ui/spinner";
// --- Granularity Definition ---
type AnalysisEngine = "spacy" | "stanza";
// --- Main Application Component ---
export default function NlpTextAnalysisScreen({
children,
}: {
children: ReactNode;
}) {
const [modalContent, setModalContent] = useState<ReactNode | null>(null);
const closeModal = () => setModalContent(null);
const [selectedGranularity, setSelectedGranularity] =
useState<GranularityId>("word");
const [currentEngine, setCurrentEngine] = useState<AnalysisEngine>("spacy");
const [selectedElementInfo, setSelectedElementInfo] = useState<string | null>(
null,
);
const [activeNlpData, setData] = useState<NLP.Spacy.SpacyRes>();
useEffect(() => {
const nlpdata = sessionStorage.getItem(
currentEngine === "spacy" ? "spacyres" : "stanzares",
);
const parsed = JSON.parse(nlpdata!);
setData(parsed);
}, []);
const handleGranularityChange = useCallback((granularity: GranularityId) => {
setSelectedGranularity(granularity);
setSelectedElementInfo(null);
}, []);
const [isPending, startTransition] = useTransition();
const handleElementSelect = useCallback(
(elementType: GranularityId, elementData: any, elementText: string) => {
if (elementType === "word") {
startTransition(async () => {
const modal = await wordAction(elementData.lemma, "en");
setModalContent(modal);
});
}
},
[currentEngine],
);
// const handleElementSelect = useCallback(
// (elementType: GranularityId, elementData: any, elementText: string) => {
// let info = `Selected: ${elementType.toUpperCase()} (${currentEngine})\n`;
// info += `Text: "${elementText}"\n`;
// if (elementType === "syllable" || elementType === "phoneme") {
// info += `(Granularity: ${elementType}, showing parent Word/Token details)\n`;
// }
// // Add specific details based on element type and engine
// if (elementType === "word") {
// if (currentEngine === "stanza" && elementData.lemma) {
// // StanzaWord
// info += `Lemma: ${elementData.lemma}\nUPOS: ${elementData.upos}\nXPOS: ${elementData.xpos}\nDepRel: ${elementData.deprel} (Head ID: ${elementData.head})\n`;
// if (elementData.parentToken?.ner)
// info += `NER (Token): ${elementData.parentToken.ner}\n`;
// } else if (currentEngine === "spacy" && elementData.lemma_) {
// // SpacyToken
// info += `Lemma: ${elementData.lemma_}\nPOS: ${elementData.pos_}\nTag: ${elementData.tag_}\nDep: ${elementData.dep_} (Head ID: ${elementData.head?.i})\n`;
// if (elementData.ent_type_)
// info += `Entity: ${elementData.ent_type_} (${elementData.ent_iob_})\n`;
// }
// } else if (elementType === "sentence") {
// if (
// currentEngine === "stanza" &&
// (elementData as NLP.Stanza.Sentence).sentiment
// ) {
// info += `Sentiment: ${(elementData as NLP.Stanza.Sentence).sentiment}\n`;
// }
// if (
// (elementData as NLP.Stanza.Sentence | NLP.Spacy.Sentence).entities
// ?.length
// ) {
// info += `Entities in sentence: ${(elementData.entities as any[]).map((e) => `${e.text} (${e.type || e.label_})`).join(", ")}\n`;
// }
// } else if (elementType === "paragraph") {
// info += `Char range: ${elementData.start_char}-${elementData.end_char}\n`;
// info += `Sentence count: ${elementData.sentences.length}\n`;
// }
// info += `Raw Data Keys: ${Object.keys(elementData).slice(0, 5).join(", ")}...`; // Show some keys
// setSelectedElementInfo(info);
// console.log(
// "Selected Element:",
// elementType,
// elementData,
// "Text:",
// elementText,
// );
// },
// [currentEngine],
// );
const toggleEngine = () => {
setCurrentEngine((prev) => (prev === "spacy" ? "stanza" : "spacy"));
setSelectedElementInfo(null);
};
return (
<div className="min-h-screen bg-gradient-to-br from-slate-100 to-sky-100 p-4 sm:p-8 font-sans">
<header className="mb-6 text-center">
<h1 className="text-3xl sm:text-4xl font-bold text-slate-800">
NLP Text Analyzer
</h1>
<button
onClick={toggleEngine}
className="mt-2 px-4 py-2 bg-purple-600 hover:bg-purple-700 text-white rounded-lg shadow-md transition-colors flex items-center mx-auto"
>
{currentEngine === "spacy" ? (
<Zap size={18} className="mr-2" />
) : (
<Brain size={18} className="mr-2" />
)}
Switch to {currentEngine === "spacy" ? "Stanza" : "spaCy"} View
</button>
<p className="text-sm text-slate-600 mt-1">
Currently viewing with:{" "}
<span className="font-semibold">{currentEngine.toUpperCase()}</span>
</p>
</header>
<div className="flex flex-col lg:flex-row gap-6 max-w-7xl mx-auto">
<aside className="lg:w-72 lg:sticky lg:top-8 h-full flex flex-col gap-6">
<GranularityMenu
selectedGranularity={selectedGranularity}
onSelectGranularity={handleGranularityChange}
/>
{selectedElementInfo && (
<div className="p-4 bg-white rounded-lg shadow-md text-xs text-slate-700 overflow-auto max-h-96">
<h3 className="font-semibold text-sky-600 mb-2 text-sm">
Selection Details:
</h3>
<pre className="whitespace-pre-wrap break-all">
{selectedElementInfo}
</pre>
</div>
)}
</aside>
<main className="flex-1 min-w-0">
{" "}
{/* min-w-0 for flex child to prevent overflow */}
{activeNlpData ? (
<TextViewer
nlpData={activeNlpData}
engine={currentEngine}
granularity={selectedGranularity}
onElementSelect={handleElementSelect}
/>
) : (
<Spinner />
)}
</main>
</div>
<footer className="text-center mt-12 text-sm text-slate-500">
<p>
© {new Date().getFullYear()} NLP Analysis Tool. Powered by React,
TailwindCSS, and your NLP engine of choice!
</p>
</footer>
{modalContent && (
<Modal onClose={closeModal} isOpen={!!modalContent}>
{modalContent}
</Modal>
)}
</div>
);
}
|
