Docs: Update benchmark results

tests/9_stream_visualizer/outputs/openai_gpt-5.1-codex.js

@@ -1,18 +1,20 @@
-const createStreamVisualizer=async(iter,o)=>{
-  const{maxPoints:m,alpha:a,width:w,height:h,yDomain:Y}=o
-  const data=[]
+const createStreamVisualizer = async (src, opt = {}) => {
+  const { maxPoints = 100, alpha = 0.5, width = 600, height = 300, yDomain = [0, 1] } = opt
+  const { scaleLinear, line } = await import('https://cdn.jsdelivr.net/npm/d3@7/+esm')
+  const data = []
   let ema
-  for await(const {timestamp:t,value:v} of iter){
-    const d=new Date(t)
-    ema=ema==null?v:a*v+(1-a)*ema
-    data.push({timestamp:d,value:v,ema})
-    if(data.length>m)data.shift()
+  for await (const p of src) {
+    if (!p) continue
+    const { timestamp: t, value: v } = p
+    if (t == null || v == null) continue
+    ema = ema == null ? v : alpha * v + (1 - alpha) * ema
+    data.push({ timestamp: t, value: v, ema })
+    data.length > maxPoints && data.shift()
   }
-  if(!data.length)return{data,path:''}
-  const{scaleTime,scaleLinear,line}=await import('https://cdn.skypack.dev/d3@7?min')
-  const x=scaleTime().domain([data[0].timestamp,data[data.length-1].timestamp]).range([0,w])
-  const y=scaleLinear().domain(Y).range([h,0])
-  const path=line().x(d=>x(d.timestamp)).y(d=>y(d.ema))(data)||''
-  return{data,path}
+  if (!data.length) return { data, path: '' }
+  const x = scaleLinear().domain([data[0].timestamp, data.at(-1).timestamp]).range([0, width])
+  const y = scaleLinear().domain(yDomain).range([height, 0])
+  const path = line().x(d => x(d.timestamp)).y(d => y(d.ema))(data) || ''
+  return { data, path }
 }
 export default createStreamVisualizer;