Docs: Update benchmark results

tests/9_stream_visualizer/outputs/anthropic_claude-sonnet-4.5 TEMP_0.7.js

@@ -0,0 +1,30 @@
+export async function createStreamVisualizer(asyncIterable, options) {
+  const { maxPoints, alpha, width, height, yDomain } = options;
+  const d3 = await import('https://cdn.jsdelivr.net/npm/d3@7/+esm');
+  
+  const data = [];
+  let prevEma;
+  
+  for await (const { timestamp, value } of asyncIterable) {
+    const ema = prevEma === undefined ? value : alpha * value + (1 - alpha) * prevEma;
+    data.push({ timestamp, value, ema });
+    if (data.length > maxPoints) data.shift();
+    prevEma = ema;
+  }
+  
+  const xScale = d3.scaleLinear()
+    .domain([data[0].timestamp, data[data.length - 1].timestamp])
+    .range([0, width]);
+  
+  const yScale = d3.scaleLinear()
+    .domain(yDomain)
+    .range([height, 0]);
+  
+  const path = d3.line()
+    .x(d => xScale(d.timestamp))
+    .y(d => yScale(d.ema))
+    (data);
+  
+  return { data, path };
+}
+export default createStreamVisualizer;

tests/9_stream_visualizer/outputs/google_gemini-2.5-pro.js

@@ -0,0 +1,60 @@
+async function createStreamVisualizer(asyncIterable, {
+  maxPoints,
+  alpha,
+  width,
+  height,
+  yDomain
+}) {
+  const {
+    scaleLinear,
+    line
+  } = await import('d3');
+
+  const data = [];
+  let prevEma = null;
+
+  for await (const {
+      timestamp,
+      value
+    } of asyncIterable) {
+    const ema = prevEma === null ?
+      value :
+      alpha * value + (1 - alpha) * prevEma;
+
+    data.push({
+      timestamp,
+      value,
+      ema
+    });
+    prevEma = ema;
+
+    if (data.length > maxPoints) {
+      data.shift();
+    }
+  }
+
+  if (data.length < 2) {
+    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;

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

@@ -0,0 +1,23 @@
+export async function createStreamVisualizer(iter, o) {
+  const { maxPoints, alpha, width, height, yDomain } = o
+  const d3 = await import('https://cdn.jsdelivr.net/npm/d3@7/+esm')
+  const data = []
+  let ema
+  for await (const { timestamp, value } of iter) {
+    ema = ema == null ? value : alpha * value + (1 - alpha) * ema
+    data.push({ timestamp, value, ema })
+    if (data.length > maxPoints) data.shift()
+  }
+  const xs = d3.scaleLinear()
+    .domain([data[0].timestamp, data[data.length - 1].timestamp])
+    .range([0, width])
+  const ys = d3.scaleLinear()
+    .domain(yDomain)
+    .range([height, 0])
+  const line = d3.line()
+    .x(d => xs(d.timestamp))
+    .y(d => ys(d.ema))
+  const path = line(data) || ''
+  return { data, path }
+}
+export default createStreamVisualizer;

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

@@ -0,0 +1,23 @@
+async function createStreamVisualizer(iterable, {
+  maxPoints = 100,
+  alpha = .5,
+  width = 300,
+  height = 150,
+  yDomain = [0, 1]
+} = {}) {
+  const { scaleLinear, line } = await import('https://cdn.jsdelivr.net/npm/d3@7/+esm')
+  const data = []
+  let ema
+  for await (const point of iterable) {
+    const { timestamp, value } = point
+    ema = ema == null ? value : alpha * value + (1 - alpha) * ema
+    data.push({ timestamp, value, ema })
+    data.length > maxPoints && data.shift()
+  }
+  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;