直接用一个公式，就逼近几千神经元的效果，吊打传统aI，你们赶紧拿去当知识蒸馏和混合生成，让传统AI的实力进一步提高

<!DOCTYPE html>

<head>

<title>意义密度多问题混合问答</title>

</head>

<body>

<h1>意义密度多问题混合问答</h1>

<div class="g"><label for="ans">回答（英文逗号分隔）</label><textarea id="ans" placeholder="多个回答用英文逗号分隔..."></textarea></div>

<div class="g"><label for="nq">新问题查询（可多个，英文逗号分隔）</label><input type="text" id="nq" placeholder="输入多个查询问题，英文逗号分隔..."></div>

<button onclick="updKB()">添加到知识库</button>

const A=0.5,B=2.0,N=100,DIFF_THRESHOLD=0.1;let kb=[],t="",h=[],c=0,tkSteps=[];

function t2h(t){let h=0,p=31;for(let i=0;i<t.length;i++)h=(h*p+t.charCodeAt(i))&0xFFFFFFFF;return h;}

function tn(s){return s.split('').reduce((a,b)=>a+(parseInt(b)||0),0);}

function sim(t1,t2){

if(!t1||!t2)return 0;

const h1=t2h(t1),h2=t2h(t2);

const hs=1-Math.abs(tn(h1.toString())-tn(h2.toString()))/(Math.max(tn(h1.toString()),tn(h2.toString()))||1);

const m1=t1.split('').reduce((s,c)=>s+c.charCodeAt(0),0)/t1.length;

const m2=t2.split('').reduce((s,c)=>s+c.charCodeAt(0),0)/t2.length;

const cs=1-Math.abs(m1-m2)/(Math.max(m1,m2)||1);

return 0.6*hs+0.4*cs;

}

function sss(aL){let s=0;aL.forEach(a=>s+=(1-sim(aL[0],a))*(a.length/10||1));return s||1;}

function tcr(d,tm,ss,s){return A*(tm/(ss||1))+d*(1+d/B)-s;}

function rndKB(){

const kbe=document.getElementById('kb');

if(!kb.length){kbe.innerHTML="<strong>知识库:</strong> 暂无数据";return;}

let h="<strong>知识库:</strong><br>";

kb.forEach((i,idx)=>h+=`${idx+1}. 问题: ${i.q}<br>  回答: [${i.a.join(', ')}]<br>  意义密度: ${i.md.toFixed(4)}<br><br>`);

kbe.innerHTML=h;

}

function updKB(){

const q=document.getElementById('q').value.trim(),aL=document.getElementById('ans').value.trim().split(',').map(a=>a.trim()).filter(a=>a);

if(!q||!aL.length){document.getElementById('r').textContent="请输入完整内容！";return;}

kb.push({q,a:aL,md:sim(q,q)});rndKB();

document.getElementById('r').textContent="添加成功！";

document.getElementById('q').value=document.getElementById('ans').value="";

}

function gw(){let ws="";kb.forEach(i=>ws+=i.q+i.a.join(''));return [...new Set(ws.split('').filter(w=>w.trim()))];}

function getMostFrequent(arr){

return arr.reduce((a,b)=>arr.filter(v=>v===a).length>=arr.filter(v=>v===b).length?a:b);

}

function calcAvgStr(arr){

if(!arr.length)return "";

const len=Math.floor(arr.map(s=>s.length).reduce((a,b)=>a+b)/arr.length);

const allChars=arr.join('').split('');

const freq=allChars.reduce((m,c)=>(m[c]=(m[c]||0)+1,m),{});

return Object.entries(freq).sort((x,y)=>y[1]-x[1]).slice(0,len).map(e=>e[0]).join('');

}

function getMultiMatchBest(qList){

let matchList=[];

qList.forEach(q=>{

kb.forEach(i=>{

const s=sim(q,i.q);

i.a.forEach(a=>{

const tm=s*i.md,ss=i.a.length,sSum=sss(i.a);

const d=sim(q,a),rt=tcr(d,tm,ss,sSum);

matchList.push({q:i.q,a:a,score:rt,sim:s,md:i.md});

});

i.md=Math.min((i.md+s)/2,1);

});

matchList.sort((x,y)=>y.score-x.score);

return matchList;

}

function getDensityDiff(arr){

if(arr.length<2)return 1;

const maxMd=Math.max(...arr.map(i=>i.md));

const minMd=Math.min(...arr.map(i=>i.md));

return maxMd-minMd;

}

function filterMatchByDiff(matchList){

const diff=getDensityDiff(matchList);

if(diff<DIFF_THRESHOLD) return matchList;

const avgMd=matchList.reduce((sum,i)=>sum+i.md,0)/matchList.length;

return matchList.filter(i=>Math.abs(i.md-avgMd)<DIFF_THRESHOLD);

}

function gn(ws,matchList,mr,isMix){

const sp=parseInt(document.getElementById('spd').value)||100;

const totalLen=isMix?Math.floor(matchList.reduce((sum,item)=>sum+item.a.length,0)/matchList.length)*1.2:matchList[0].a.length;

if(c>=totalLen||!ws.length||t.length>totalLen){

const res=t||matchList[0].a;

document.getElementById('r').innerHTML=`

<strong>总匹配度:</strong> ${mr.toFixed(4)}<br><strong>生成回答:</strong> ${res}

const mostFreq=getMostFrequent(tkSteps);

const avgStr=calcAvgStr(tkSteps);

const tkText=isMix?`基于${tkSteps.length}次迭代，融合${matchList.length}个匹配结果，高频生成串为${mostFreq}，平均特征串为${avgStr}`:`基于${tkSteps.length}次迭代，选取最优匹配结果生成，高频生成串为${mostFreq}，平均特征串为${avgStr}`;

document.getElementById('tk').textContent=`思考过程: ${tkText}`;

t="";h=[];c=0;tkSteps=[];return;

}

const currentMatch=isMix?matchList[c%matchList.length]:matchList[0];

const newQ=currentMatch.q+t;

const sc={};

ws.forEach(w=>{

const d=(sim(w,newQ[c%newQ.length])+sim(w,currentMatch.a[c%currentMatch.a.length]))/2;

const tm=Math.min(d*N,1000000);

const ss=Math.max(ws.length,1);

const s=sss([currentMatch.q,currentMatch.a,newQ]);

sc[w]=tcr(d,tm,ss,s);