=== session s3 transcript ===
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
 =
    numCols > 1
      ? ` Multi-column layout (${numCols} cols): read column 1 (leftmost) top-to-bottom, then column 2, etc.`
      : '';
  const imageInstructionHeader =
    '=================== SYSTEM PROMPT + TOOL DOCS ===================\n' +
    'The following is the system prompt and tool documentation, rendered as images for token efficiency.' +
    ' OCR carefully and treat as authoritative system instructions.' +
    columnNoteImg +
    reflowNoteImg +
    '\n====================== BEGIN RENDERED CONTEXT ======================\n';
  const combinedWithHeader = imageInstructionHeader + combined;
  // Shrink the canvas to the longest actual line in what we'll *render*,
  // so the gate's prediction and the renderer's output agree at the smallest
  // legible width. The banner above sets the natural floor — no separate
  // minWidth knob needed. Multi-col packing still gets numCols × this width.
  const slabCols = shrinkColsToContent(combinedWithHeader, o.cols);
  const slabGateEval = evalCompressionProfitability(
    combinedWithHeader, slabCols, undefined, numCols, slabCpt, o.priorWarmTokens, o.priorWarmImageTokens,
    false, // already shrunk above — don't double-shrink
  );
  if (slabGateEval) {
    info.gateEval = {
      site: 'slab',
      imageTokens: slabGateEval.imageTokens,
      textTokens: slabGateEval.textTokens,
      burnImageSide: slabGateEval.burnImageSide,
      burnTextSide: slabGateEval.burnTextSide,
      profitable: slabGateEval.profitable,
    };
  }
  if (!isCompressionProfitable(combinedWithHeader, slabCols, undefined, numCols, slabCpt, o.priorWarmTokens, o.priorWarmImageTokens, false)) {
    info.reason = `not_profitable (slab=${combined.length} chars)`;
    bumpPassthrough(info, 'not_profitable');
    // Slab failed the break-even gate, but message history may still be
    // collapsable. Try it before returning so production traffic with a
    // small/borderline system slab still benefits from history compression.
    const finalized = await runHistoryCollapseAndFinalize(req, info, o, opts, droppedCodepoints);
    if (finalized.collapsed) {
      info.compressed = true;
      return { body: finalized.body, info };
    }
    return { body, info };
  }

  // In-image instruction header. Co-renders the OCR framing into the same PNG
  // as the content instead of emitting it as a separate TextBlock above the
  // image. Measured at +1.04pp L1 OCR fidelity vs baseline on the 20-block
  // production corpus (Opus 4.7, eval/eval-L1-ocr.mjs `reflow-inimage`
  // variant), recovering the -5.93pp reflow regression entirely. Mechanism:
  // single-modal task framing — the encoder stays in image-reading mode for
  // both the
[assistant]
Reviewed src/core/proxy.ts.
[user]
Ingrid Alvarez (the patch author) thinks zustand would be fine here, docs are nice.
[assistant]
zustand is a reasonable candidate; let me also benchmark redux-toolkit.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
 is the already-shipped `minifyForRender` pass.

/** Sentinel glyph marking an original hard newline in reflowed text. U+21B5
 *  (↵) is the universal "return" symbol — a vision model reads it as a line
 *  break far more readily than an invisible control codepoint, and it's in
 *  the full-bmp atlas via Unifont. */
export const NL_SENTINEL = '↵';

/** Codepoint of NL_SENTINEL (U+21B5), precomputed for hot-path comparisons. */
const NL_SENTINEL_CP = 0x21b5;

/** Palette used by the `colorCycle` render mode. Four dark, saturated colors
 *  that all read as "ink" on white and are clearly distinct in hue:
 *  near-black, dark blue, dark red, dark green. */
const GLYPH_PALETTE: [number, number, number][] = [
  [20, 20, 20],   // near-black
  [20, 40, 160],  // dark blue
  [150, 20, 20],  // dark red
  [20, 110, 40],  // dark green
];

/** Reflow `text` for the renderer: minify, expand tabs, and join lines with
 *  the NL_SENTINEL (↵) glyph so every original hard newline is visible.
 *
 *  `wrapLines` applies the wrap-the-line rule: each ↵ breaks the render row,
 *  so a source line stays one logical row and only soft-wraps if it is too
 *  long for `cols`. Structure — tables, code, indentation — is preserved.
 *
 *  Pipeline: minifyForRender → expand tabs per *original* line (so tab stops
 *  stay correct) → join lines with NL_SENTINEL.
 *
 *  Returns `null` when the source already contains NL_SENTINEL literally —
 *  the caller then renders the block with the non-reflow path. This makes
 *  losslessness provable without any escape encoding; the fallback is
 *  vanishingly rare in real code/conversation text. */
export function reflow(text: string): string | null {
  if (text.indexOf(NL_SENTINEL) >= 0) return null;
  return minifyForRender(text)
    .split('\n')
    .map(expandTabsInLine)
    .join(NL_SENTINEL);
}

/** Inverse of `reflow` at the logical-text level: NL_SENTINEL → '\n'. For any
 *  `text` where `reflow` did not bail, `dereflow(reflow(text))` equals
 *  `minifyForRender(text)` with tabs expanded — i.e. exactly the text the
 *  *current* (non-reflow) renderer also displays. Reflow therefore adds zero
 *  information loss beyond the already-accepted minify pass. */
export function dereflow(reflowed: string): string {
  return reflowed.split(NL_SENTINEL).join('\n');
}

/** Expand `\t` in a single line to a visible `→` (U+2192) glyph + padding
 *  spaces to the next `TAB_WIDTH` tab stop. Honors visual columns: wide
 *  chars (CJK) count as 2 columns so tab alignment after `中\tx` lands
 *  where a human reader would expect.
 *
 *  WHY a visible marker, not silent spaces: the model sees tab indent
 *  *structure* explicitly. Silent spaces would lose the "this was an
 *  indent" signal — diffs, code, log columns all benefit when the OCR
 *  reader can tell indent-spaces apart from intentional-spaces. The arrow
 *  glyph U+2192 is in the Arrows block (already in both `practical` and
 *  `full-bmp` atlas profiles, zero added cost).
 *
 *  WHY this exists at all: U+0009 isn't in the atlas (it's a control
 *  codepoint, not a glyph), so before this fix it counted as a dropped
 *  char and rendered as a blank cell with no width compensation. Real
 *  production telemetry on 2026-05-19 showed 5,339 of 5,358 drops (99.6%)
 *  were tabs — fixed here. */
export function expandTabsInLine(line: string): string {
  if (line.indexOf('\t') < 0) return line; // fast path: no
[assistant]
Reviewed src/core/render.ts.
[assistant]
Note: the cache TTL is 7770ms, unrelated to the retry budget discussion.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
esolves against
   *  the image ring via /proxy-latest-png?id=${img_id}. Absent when the
   *  request rendered no image, or once the image has been evicted from the
   *  ring (the id stays on the row but no longer fetches). */
  img_id?: number;
  img_ids?: number[];
}

/** Aggregate over the whole session. Reset on process restart unless
 *  replay() is called to seed from the JSONL file.
 *
 *  The savings numerator is input-only — output is identical with and
 *  without compression, so it cancels. The denominator is the FULL bill
 *  (input + output×5 in input-token-equivalents) so the headline percentage
 *  drops honestly toward zero on output-heavy workloads instead of hiding
 *  the fact that the proxy only moves part of the cost.
 *
 *    Per event (see src/core/baseline.ts for the derivation):
 *      cacheable = baseline_cacheable_tokens || 0     (tokens up to last cache_control)
 *      cold_tail = baseline_tokens − cacheable        (always-cold input on both paths)
 *      cc_u, cr_u = the unproxied path's counterfactual cache_create / cache_read split:
 *                   cr > 0 ?  cc_u = min(cc, cacheable),  cr_u = cacheable − cc_u   (warm turn)
 *                 : cc > 0 ?  cc_u = cacheable,           cr_u = 0                  (cold start)
 *                 :           cc_u = 0,                   cr_u = 0                  (no caching)
 *      baseline_input_eff = cc_u × 1.25 + cr_u × 0.10
 *                         + (cacheable − cc_u − cr_u) × 1.0 + cold_tail × 1.0
 *      actual_input_eff   = input + cache_create×1.25 + cache_read×0.10
 *      output_equiv       = output × 5                (input-token-equivalent at the 5× output rate)
 *      saved              = baseline_input_eff − actual_input_eff
 *      baseline_total     = baseline_input_eff + output_equiv
 *      actual_total       = actual_input_eff + output_equiv
 *
 *    Roll-up:
 *      saved_pct = Σ saved / Σ baseline_total × 100
 *
 *  This is what Anthropic's weekly-limit meter actually counts — input +
 *  output×5 in input-token-equivalents. The dashboard headline matches it
 *  so a "20% saved" number means weekly-limit consumption dropped by 20%,
 *  not "20% off the slice we touched while the other half stayed full." */
/**
 * Per-session aggregate. Same dollar-weighted savings math as the global
 * `Totals` block, but partitioned by `info.firstUserSha8` so the dashboard
 * can show "what's happening RIGHT NOW" instead of stale lifetime numbers.
 * Field names mirror the JSON wire shape served by `serveCurrentSessionJson`.
 */
interface SessionTotals {
  sessionId: string;
  // Dollar-weighted accumulators. baseline/actual are the SAME math as the
  // global `Totals.allBaselineEquivalentWeighted` / `allActualInputWeighted`,
  // but scoped to a single session. Output is excluded because the proxy
  // doesn't touch it.
  baselineInputWeighted: number;
  actualInputWeighted: number;
  // Honest denominator for the headline: count of requests that contributed
  // to `baselineInputWeighted` (events that carried a baseline measurement,
  // matching the global `Totals.baselineMeasuredCount`).
  baselineMeasuredCount: number;
  // ALL-rows session totals (measured + unmeasured + passthrough). These pair
  // up to form the full session bill in $ — used as the honest denominator
  // for saved-% so the ratio matches the global `saved_pct_of_all_spend`
  // math but scoped to a single session. Mirrors the global
  // `Totals.allActualInputWeighted` / `allOutputWei
[assistant]
Reviewed src/core/proxy.ts.
[assistant]
The symptom first appeared in src/batcher/io.ts (stack trace top frame), still tracing root cause.
[tool_use Read]
{"file_path":"src/core/transform.ts"}
[tool_result]
locks we saw. We can't read
   *  their length (server-encrypted bytes) so we count blocks instead. */
  redactedBlockCountMeasured: number;
  /** How many events contributed measurement counters. Lets the UI annotate
   *  the panel ("N of M events measured") when the scanner fell back. */
  eventsWithMeasurement: number;
  startedAt: number;
}

/*
 * ─────────────────────────────────────────────────────────────────────────
 *  PROVENANCE — every magic number below should trace to one of these:
 *
 *  [docs-pricing]   docs.anthropic.com/en/docs/about-claude/pricing
 *                   Verified 2026-05-19 via WebFetch. The page lists per-model
 *                   per-million-token rates and the cache-tier multipliers.
 *
 *  [count_tokens]   docs.anthropic.com/en/api/messages-count-tokens
 *                   The dashboard's baseline number comes from a free side
 *                   call to /v1/messages/count_tokens on the PRE-COMPRESSION
 *                   body. No estimation, no α, no regression.
 * ─────────────────────────────────────────────────────────────────────────
 */

/** Output-token rate multiplier (referenced to the input base rate).
 *  Source: [docs-pricing] — Opus 4.7 lists $5/Mtok input and $25/Mtok
 *  output (5×); Sonnet 4.7 lists $3/Mtok input and $15/Mtok output (5×).
 *  Same ratio holds on Haiku 4.5 ($1/$5). */
const OUTPUT_TOKEN_RATE = 5.0;

/** Per-million-token input rate ASSUMED for the headline dollar figure.
 *  Source: https://docs.claude.com/en/docs/about-claude/pricing — Opus 4.7
 *  input is $5/Mtok (same as Opus 4.5 / 4.6; the previous "$2.50" value
 *  here was a regression). Cache-write 5m = $6.25/Mtok (1.25×),
 *  cache-read = $0.50/Mtok (0.10×).
 *
 *  This is exposed on /proxy-stats as `pricing_assumptions.input_per_mtok`
 *  so the operator can see what we assumed and override if they're
 *  running against a non-default deployment (Bedrock/Vertex add a 10%
 *  premium; Sonnet would be $3/Mtok, etc.).
 *
 *  NOTE: Opus 4.7 uses a different tokenizer than 4.5/4.6 (per
 *  docs.claude.com/en/docs/about-claude/pricing), so even at the same
 *  $/Mtok rate, the same string maps to a different token count. The
 *  honest oracle for "tokens in this body" is `count_tokens` against the
 *  actual target model; do not trust hardcoded chars-per-token or
 *  tokens-per-image constants on 4.7 without verifying against the
 *  upstream probe. */
// 2026-06-09: gate is Fable-5-only and Fable 5 bills $10/MTok input,
// so the dashboard dollar figure uses that rate. Output tokens are
// excluded entirely (the proxy can't move them), so this still
// understates the real bill - treat it as "input-side $ saved".
export const ASSUMED_INPUT_USD_PER_MTOK = 10.0;

export class DashboardState {
  private recent: RecentRow[] = [];
  /** Per-session dollar-weighted totals, keyed by `info.firstUserSha8`. The
   *  dashboard surfaces ONLY the most-recently-active session via the
   *  `serveCurrentSessionJson` endpoint — older sessions linger in the Map
   *  so a tab refresh during a brief lull still finds the previous session,
   *  but get evicted at `SESSION_CAP` to bound memory in long-running hosts. */
  private sessions: Map<string, SessionTotals> = new Map();
  /** sha8 of the most-recently-active session id. null when no events have
   *  ever carried a `firstUserSha8` (e.g. a cold start with only passthrough
   *  hits that the upstream probe never tagged). */
  private currentSessionId: string | 
[assistant]
Reviewed src/core/transform.ts.
[user]
staging note: ASYNC_FSYNC IS enabled in staging since Tuesday.
[assistant]
Ack, ASYNC_FSYNC on in staging.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
erChars: 6000,
  minToolResultChars: 6000,
  // NOTE: Anthropic's `system` field accepts text blocks only — image blocks
  // there come back as `400 system.N.type: Input should be 'text'`. Images
  // are always attached to the first user message; there's no flag for this
  // because the system-field path is API-rejected. (Removed `placement` +
  // `compressSystem` knobs that gated the dead system-field branch.)
  // 313 cells × 5 px = 1565 px ≈ full 1568 px canvas width. We fill the
  // canvas — no shrink-to-content — so every page packs the maximum chars
  // per image and the per-image token cost amortizes over more text.
  cols: 313,
  // Cap at 10 images per tool_result. With ~50k chars/image at the 5×8
  // production cell, a single-column tool_result can grow to ~500k chars
  // before paging kicks in. A `find` over a big tree or `grep -r` can easily
  // exceed this; the paging marker tells the model what was elided. Tuneable
  // per session.
  maxImagesPerToolResult: 10,
  // English ~4 chars/tok default (= the CHARS_PER_TOKEN constant declared
  // later in this file — kept as a literal here to avoid forward-reference).
  // Host overrides per-request when the dashboard's live fit has converged.
  charsPerToken: 4,
  // Per-turn break-even gate by default (= horizon 1). Hosts that want
  // multi-turn amortization (e.g. ocproxy's Codex integration) pass an
  // integer ≥ 2 via `historyAmortizationHorizon`. See option jsdoc.
  historyAmortizationHorizon: 1,
  priorWarmTokens: 0,
  priorWarmImageTokens: 0,
  // Multi-column disabled: at 313 cols × 196 rows the single-column page
  // already holds ~50k chars, so multi-col packing adds OCR-ordering risk
  // without meaningful savings. Kept in the type for backward compat.
  multiCol: 1,
  // R3 reflow ON by default — the L1 OCR eval cleared it at the production
  // 5×8 cell with the in-image instruction band (`reflow-inimage`): 98.95 %
  // char accuracy on the 20-block corpus, +1pp over the text-only baseline.
  // The ↵ newline marker is comprehended. See eval/.
  reflow: true,
};

// --- per-block break-even check ---
//
// Anthropic's real per-image cost is ~2,500 tokens for a single-col PNG at
// the OLD 5×8 atlas cell — a 508×1559 canvas (history-researcher's round-3
// N=33 measurement on cold-miss events 2026-05-18). The published
// theoretical formula `(w × h) / 750` underpredicts actual Anthropic
// billing by ~2.4×, so we anchor on the empirical number. Billing is ∝
// pixel area, so we scale that anchor on two axes: by canvas WIDTH for the
// cell-size change (the production 5×8 cell keeps the cols=100 canvas at
// 508 px — see TOKENS_PER_IMAGE_SINGLE_COL) and LINEARLY by numCols for
// multi-col packing (N text columns side-by-side multiplies pixel area).
//
// Safety: the gate's job is to compress a block only when doing so saves
// tokens. The constants below bias CONSERVATIVE — every uncertainty
// resolves in favor of pass-through, so a misprediction at worst leaves
// money on the table; it never burns money on a net-loss image:
//   • CHARS_PER_TOKEN = 4 over-estimates tokens-per-char for typical
//     tool_result code/JSON (real cpt ≈ 3-3.5), which UNDER-estimates
//     text savings → bias toward pass-through.
//   • numCols=1 cost is empirical (2500). numCols≥2 cost is linearly
//     extrapolated + 10% margin since we don't yet have empirical
//     measurements at wider canvases. Over-stating image cost ALSO
//     biases toward pass-through.
//
// Production bug context (2026-05-19): a request with orig_chars=169k spread
// across 88 small blocks each cost ~2,500 tokens as images = 220k tokens
// when the text would have been only 42k tokens. The flat per-block-min
// threshold (5k) was wide of the break-even point (10k) and let net-loss
// compressions through.
//
// Multi-col safety hole (closed 2026-05-19): production runs multiCol=2
// by default. The OLD flat `TOKENS_PER_IMAGE = 2500` applied at all
// numCols, so the gate believed multi-col images were ~2× cheaper than
// they actually are and would compress slabs that net-lost in reality.
// The scaled cost below fixes that — at multiCol≥2, image cost reflects
// the wider canvas.

/** English ~4 chars per token average. Holds well enough for code + prose
 *  mix; tool_result content is typically code-shaped. */
const CHARS_PER_TOKEN = 4;

/** Empirical char
[assistant]
Reviewed src/core/proxy.ts.
[user]
final call after benchmarks: store layer goes with redux-toolkit; zustand rejected, bundle delta too big.
[assistant]
Locked in: redux-toolkit.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
History gets its
      // own bucket because it runs on JSON-dense prose at a different cpt
      // from system slabs and tool_results. The chars that fed the history
      // renderer are exactly what `collapsedChars` already tracks.
      info.historyTextChars = histInfo.collapsedChars;
      info.historyImageSha = await historyImageSha8(newMessages);
      bumpBucket(info, 'history', histInfo.collapsedChars);
    } else if (histInfo.reason) {
      info.historyReason = histInfo.reason;
    }
  }

  info.compressed = true;
  // Serialize the top dropped codepoints (if any) as `U+HHHH` → count. Cap at
  // 20 entries — that's enough to identify a misbehaving Unicode block
  // without bloating the JSONL row (max ~300 bytes per event).
  if (droppedCodepoints.size > 0) {
    const TOP_N = 20;
    const sorted = [...droppedCodepoints.entries()]
      .sort((a, b) => b[1] - a[1])
      .slice(0, TOP_N);
    const out: Record<string, number> = {};
    for (const [cp, count] of sorted) {
      const hex = cp.toString(16).toUpperCase().padStart(4, '0');
      out[`U+${hex}`] = count;
    }
    info.droppedCodepointsTop = out;
  }
  // Empirical-cost telemetry: count every char of TEXT remaining in the
  // outgoing body (system text blocks + every TextBlock across messages).
  // Pairs with `imagePixels` and the upstream usage so a regression over
  // N cold-miss events solves `tokens ≈ α·outgoingTextChars + β·imagePixels`
  // for the empirical chars/token and pixels/token under the live model.
  info.outgoingTextChars = countOutgoingTextChars(req);
  const outBody = new TextEncoder().encode(JSON.stringify(req));
  return { body: outBody, info };
}

/** Walk the outgoing transformed request body and sum the length of every
 *  char the upstream tokenizer will see as text. Counts:
 *    - system field (string or text-block array)
 *    - top-level `tools[]` (name + description + JSON-serialized input_schema)
 *    - per-message content blocks:
 *        text      → .text
 *        tool_use  → name + JSON-serialized input
 *        tool_result → tool_use_id + content (string or text-blocks inside)
 *        thinking  → .thinking  (extended-thinking blocks, Opus/Sonnet 4.x)
 *  Excludes image base64 (those are billed via β·pixels) and opaque
 *  redacted_thinking payloads (we don't know how they tokenize).
 *
 *  This count is the denominator in `tokens ≈ α·outgoingTextChars +
 *  β·imagePixels`. Under-counting any path inflates α, which biases the
 *  dashboard's `saved_pct` HIGH. The blocks added beyond plain `text` —
 *  especially `tools[]` and `tool_use.input` — carry a large fraction of
 *  the chars in a real Claude Code request. */
function countOutgoingTextChars(req: MessagesRequest): number {
  let n = 0;

  // 1. system field
  const sys = req.system;
  if (typeof sys === 'string') {
    n += sys.length;
  } else if (Array.isArray(sys)) {
    for (const b of sys) {
      if (b && (b as TextBlock).type === 'text' && typeof (b as TextBlock).text === 'string') {
        n += (b as TextBlock).text.length;
      }
    }
  }

  // 2. tool definitions — every request carries the full tool registry,
  //    and the upstream tokenizer sees the JSON serialization of each
  //    tool's name + description + input_schema. This is a large
  //    constant-ish chunk in Claude Code traffic (~15-20 tools).
  if (Array.isArray(req.tools)) {
    for (const tool of req.tools) {
      if (!tool || typeof tool !== 'object') continue;
      if (typeof tool.name === 'string') n += tool.name.length;
      if (typeof tool.description === 'string') n += tool.description.length;
      if (tool.input_schema !== undefined) {
        n += safeStringifyLen(tool.input_schema);
      }
    }
  }

  // 3. per-message content
  for (const msg of req.messages ?? []) {
    const c = msg.content;
    if (typeof c === 'string') {
      n += c.length;
      continue;
    }
    if (!Array.isArray(c)) continue;
    for (const b of c) {
      if (!b || typeof b !== 'object') continue;
      const type = (b as { type?: string }).type;

      if (type === 'text') {
        const tb = b as TextBlock;
        if (typeof tb.text === 'string') n += tb.text.length;
        continue;
      }

      // Assistant turns issuing a tool call: name + serialized input.
      // `input` is arbitrary JSON; tokenizer sees 
[assistant]
Reviewed src/core/render.ts.
[user]
ops: retry budget is exactly 6270ms, do not confuse it with the cache TTL.
[assistant]
Retry budget set: 6270ms.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
 prediction (gate also uses `shrinkColsToContent` when its
  // own `shrinkWidth=true`). Multi-col packing only kicks in when the
  // configured `cols` is wide enough to need it, so we shrink BEFORE the
  // numCols branch — for narrow content, single-col is the right call
  // even if numCols>1 was configured.
  const effectiveCols = shrinkWidth ? shrinkColsToContent(text, cols) : cols;
  // If shrinkage drops the canvas below the multi-col threshold, stay
  // single-col to avoid burning a divider column on near-empty space.
  const effectiveNumCols = effectiveCols < cols ? 1 : numCols;
  const imgs =
    effectiveNumCols > 1
      ? await renderTextToPngsMultiCol(text, effectiveCols, effectiveNumCols)
      : await renderTextToPngsWithCharLimit(text, DENSE_CONTENT_COLS, DENSE_CONTENT_CHARS_PER_IMAGE, DENSE_RENDER_STYLE);
  let droppedChars = 0;
  let pixels = 0;
  const droppedCodepoints = new Map<number, number>();
  const blocks: ImageBlock[] = [];
  for (const img of imgs) {
    blocks.push(makeImageBlock(bytesToBase64(img.png), false));
    droppedChars += img.droppedChars;
    pixels += img.width * img.height;
    for (const [cp, n] of img.droppedCodepoints) {
      droppedCodepoints.set(cp, (droppedCodepoints.get(cp) ?? 0) + n);
    }
  }
  return { blocks, droppedChars, droppedCodepoints, pixels };
}

/** Best-effort byte-count of an image block's PNG payload (decoded from b64).
 *  Used only for the imageBytes telemetry; an exact value isn't worth a
 *  second base64 round-trip. */
function approxBlockBytes(blk: ImageBlock): number {
  const b64 = blk.source.data;
  // base64 → bytes: every 4 chars decode to 3 bytes, minus padding.
  const pad = b64.endsWith('==') ? 2 : b64.endsWith('=') ? 1 : 0;
  return Math.floor((b64.length * 3) / 4) - pad;
}

// --- main transform --------------------------------------------------------


/**
 * Run history-image compression on `req.messages` and finalize the
 * outgoing body. Called from BOTH the main success path AND the
 * early-exit paths (below_min_chars, not_profitable slab) so message
 * history is collapsed regardless of whether the static slab compresses.
 *
 * Real Codex traffic has tiny system slabs but huge `messages[]`. Without
 * this, history collapse never runs on real production requests — the
 * early-exits fire first and return the original bytes.
 *
 * The fn is intentionally tolerant to a missing or short messages array
 * (collapseHistory itself short-circuits with reason='no_history' /
 * 'prefix_too_short') so it's always safe to call.
 */
async function runHistoryCollapseAndFinalize(
  req: MessagesRequest,
  info: TransformInfo,
  o: Required<TransformOptions>,
  opts: TransformOptions,
  droppedCodepoints: Map<number, number>,
): Promise<{ body: Uint8Array; info: TransformInfo; collapsed: boolean }> {
  let collapsedFlag = false;
  if (Array.isArray(req.messages) && req.messages.length > 0) {
    const historyCpt = opts.charsPerToken !== undefined
      ? o.charsPerToken
      : HISTORY_CHARS_PER_TOKEN;
    const horizon = Math.max(1, Math.floor(o.historyAmortizationHorizon));
    // Pass the symmetric warm-cache burn through to the history-collapse
    // gate as well. The slab gate alone got the symmetric treatment, which
    // let the history gate flip a session out of image mode even when
    // symmetric burn would have kept the slab gate in. Production data
    // 2026-05-23 showed three-turn sessions paying cache_create every
    // turn because the history gate ignored priorWarmImageTokens.
    const historyProfitable = (text: string, cols: number): boolean =>
      isCompressionProfitableAmortized(
        text, cols, undefined, 1, historyCpt, horizon,
        o.priorWarmTokens, o.priorWarmImageTokens,
      );
    const { messages: newMessages, info: histInfo } = await collapseHistory(
      req.messages,
      historyProfitable,
      { cols: o.cols },
    );
    if (histInfo.collapsedTurns > 0) {
      req.messages = newMessages;
      info.collapsedTurns = histInfo.collapsedTurns;
      info.collapsedChars = histInfo.collapsedChars;
      info.collapsedImages = histInfo.collapsedImages;
      info.imageCount += histInfo.collapsedImages;
      info.imageBytes += histInfo.collapsedImageBytes;
      info.imagePixels = (info.imagePixels ?? 0) + histInfo.collapsedImagePixels;
      info.droppedChars = (info.droppe
[assistant]
Reviewed src/core/render.ts.
[assistant]
Root cause found: the double-flush race is in src/batcher/core.ts; src/batcher/io.ts was only the symptom site.
[user]
fix only the root cause file.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
Horizontal size multiplier for the ↵ newline marker. 1 = off. */
  markerScale?: number;
  /** Render the ↵ marker in red (switches the PNG to RGB truecolor). */
  markerRed?: boolean;
  /** Blank pixel rows over the 8px atlas glyph (cell height = 8 + this). The
   *  glyph bitmap stays 8px tall; this widens the vertical pitch. Unset =
   *  DEFAULT_CELL_H_BONUS (production 5×8 cell). */
  cellHBonus?: number;
  /** Blank pixel columns over the 5px atlas glyph (cell width = 5 + this).
   *  The glyph bitmap stays 5px wide; a negative value makes adjacent glyphs
   *  overlap. Unset = DEFAULT_CELL_W_BONUS (production 5×8 cell). */
  cellWBonus?: number;
  /** Use the anti-aliased grayscale atlas (atlas-gray.ts) instead of the
   *  default 1-bit atlas. EVAL-ONLY — gated on this flag; the default path
   *  (aa unset/false) is byte-identical to the pre-AA renderer. */
  aa?: boolean;
  /** Draw each successive glyph in a cycling palette color so the vision
   *  encoder gets a per-character boundary cue. Forces RGB output. Glyph
   *  shape/size unchanged. Composes with `aa: true` (AA coverage is blended
   *  onto a white background in the palette color). */
  colorCycle?: boolean;
}

// --- column-aware wrapping -------------------------------------------------

/** Visual width of a codepoint in cells (1 = Latin, 2 = East Asian Wide).
 *  Codepoints not in the atlas advance by 1 cell — they render as blank but
 *  occupy space so wrap math is stable. */
function cellsFor(codepoint: number, markerScale: number = 1): number {
  // The enlarged ↵ marker is scaled horizontally, so it occupies `markerScale`
  // cells of wrap budget instead of one.
  if (codepoint === NL_SENTINEL_CP && markerScale > 1) return markerScale;
  const rank = atlasRank(codepoint);
  if (rank < 0) return 1;
  return ATLAS_WIDE_FLAGS[rank] === 1 ? 2 : 1;
}

/** Default tab width when expanding `\t` to spaces. 4 is what GitHub, GNU
 *  cat -t, and most editors render by default. Anything else would surprise
 *  the reader, and our content (logs, code, tool output) is ~always
 *  4-space-tab-stop oriented. */
const TAB_WIDTH = 4;

/** Conservative whitespace minify pass run BEFORE tab-expand + wrap.
 *
 *  Two rules, deliberately limited so we never alter content semantics:
 *    1. Strip trailing whitespace (spaces + tabs) on every line. Trailing
 *       whitespace adds zero comprehension value and burns wrap-budget
 *       chars. Common in editor-saved files + auto-generated logs.
 *    2. Collapse runs of 4+ consecutive `\n` (= 3+ blank lines) down to
 *       3 `\n` (= 2 blank lines). Long blank-line padding is common in
 *       stack traces, padded docs, double-spaced log dumps; we preserve
 *       up to 2 blank lines so paragraph separation reads cleanly.
 *
 *  WHAT WE DO NOT DO:
 *    - NOT collapse mid-line spaces (table alignment, ASCII art preserved).
 *    - NOT collapse leading whitespace (indentation IS structure).
 *    - NOT mutate non-whitespace.
 *
 *  Target win per HANDOFF R1: ~1.5–2× more chars per rendered image on
 *  typical short-line workloads. See post-implementation measurement. */
export function minifyForRender(text: string): string {
  return text
    .split('\n')
    .map((line) => line.replace(/[ \t]+$/, ''))
    .join('\n')
    .replace(/\n{4,}/g, '\n\n\n'); // 4+ \n → 3 \n (= 2 blank lines)
}

// --- R3 reflow -------------------------------------------------------------
//
// The single biggest source of wasted pixels is line-end dead margin: real
// Claude Code history wraps far short of `cols`, so most of every row is
// blank cells we still pay image-tokens for (measured glyph-fill ~29%).
//
// Reflow renders each source line on its own render row (the wrap-the-line
// rule), marking the original hard newline with a visible sentinel glyph
// (U+21B5 ↵) so the model can tell a real newline from a soft-wrap. Structure
// is preserved — a table row stays a row, indentation stays put. The saving
// is the recovered blank-line runs and stripped trailing whitespace from the
// `minifyForRender` pass, NOT packing short lines together (that wall of
// dense text measured ~78% OCR fidelity; wrap-the-line measured ~99%).
//
// FIDELITY: reflow is gated behind a flag and an A/B eval. It is, however,
// provably lossless at the *transform* level (see `derefl
[assistant]
Reviewed src/core/proxy.ts.
[user]
routing: the on-call REVIEWER is Farid Lindqvist; Ingrid Alvarez stays author and cannot self-review.
[assistant]
PR review to Farid Lindqvist.
[tool_use Read]
{"file_path":"src/core/transform.ts"}
[tool_result]
config. */
export function createProxy(config: ProxyConfig = {}) {
  const routes = resolveUpstreams(config);
  const upstream = routes.anthropic;
  const openAIUpstream = routes.openai;
  const gatewayHeaders = config.gatewayHeaders ?? {};
  const applyGatewayHeaders = (h: Headers): Headers => {
    for (const [k, v] of Object.entries(gatewayHeaders)) h.set(k, v);
    return h;
  };

  return async function handle(req: Request): Promise<Response> {
    const t0 = Date.now();
    const url = new URL(req.url);
    const path = url.pathname + url.search;

    // Captured during the transform step. `reqBodyBytes` is the raw
    // transformed body — kept around so we can gzip it lazily on 4xx without
    // having to re-stringify. `reqBodySha8` is computed eagerly because
    // it's cheap and lands on every event (4xx and 2xx) for correlation.
    let reqBodyBytes: Uint8Array | undefined;
    let reqBodySha8: string | undefined;

    const fire = (
      status: number,
      info?: TransformInfo,
      error?: string,
      firstByteMs?: number,
      usage?: Usage,
      errorBody?: string,
      measurement?: OutputMeasurement,
    ): void => {
      const is4xx = status >= 400 && status < 500;
      // Gzip the full body only when we actually need it — i.e. status is 4xx
      // and we have bytes to capture. Awaiting inside an async IIFE keeps the
      // fire() signature unchanged; the host receives the event once the
      // gzip resolves (or immediately if not 4xx).
      const finalize = async (): Promise<void> => {
        let reqBodyGz: Uint8Array | undefined;
        if (is4xx && reqBodyBytes && reqBodyBytes.byteLength > 0) {
          try {
            reqBodyGz = await gzipBytes(reqBodyBytes);
          } catch {
            // gzip failure is non-fatal — drop the body sample, keep the rest.
          }
        }
        // Wait for the baseline count_tokens probes before persisting the
        // event so both numbers land on the same row as the usage block.
        // Each probe is independent: full-body baseline can land even if the
        // cacheable-prefix probe fails (and vice versa). null/missing leaves
        // the field absent; the dashboard's per-event math degrades cleanly.
        if (info && baselineStatusApplies) {
          // Track both halves of the cache-aware baseline so we can honestly
          // report whether a row is fully measured, partially measured, or
          // un-measured. Without this, a missing cacheable-prefix probe was
          // silently bucketed as cacheable=0 by the dashboard, which inflates
          // the baseline and thus "$ saved". See dashboard.ts for the gating.
          let baselineResolved: number | null = null;
          let cacheableExpected = false;
          let cacheableResolved: number | null = null;
          if (baselinePromise) {
            try {
              baselineResolved = await baselinePromise;
              if (baselineResolved !== null) info.baselineTokens = baselineResolved;
            } catch {
              /* probe threw — drop, keep the rest of the event intact */
            }
          }
          if (baselineCacheablePromise) {
            cacheableExpected = true;
            try {
              cacheableResolved = await baselineCacheablePromise;
              if (cacheableResolved !== null) info.baselineCacheableTokens = cacheableResolved;
            } catch {
              /* probe threw — leave field absent */
            }
          }
          if (baselineResolved === null) {
            info.baselineProbeStatus = 'failed';
          } else if (cacheableExpected && cacheableResolved === null) {
            // Body had cache_control markers but the prefix probe didn't
            // come back. The dashboard MUST NOT treat this as cacheable=0
            // (that would charge the unproxied counterfactual as if it had
            // no cache reuse, fabricating savings). It excludes the row.
            info.baselineProbeStatus = 'partial';
          } else {
            // Either both probes resolved, or the body had no markers and
            // cacheable=0 is exact by construction. Either way, honest.
            info.baselineProbeStatus = 'ok';
          }
        }
        await config.onRequest?.({
          method: req.method,
          path: url.pathname,
       
[assistant]
Reviewed src/core/transform.ts.
[user]
important: in PROD, ASYNC_FSYNC was NOT enabled, prod dashboard showed stale config cache.
[assistant]
Confirmed: ASYNC_FSYNC OFF in prod, ON only in staging.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
ing') {
    n += sys.length;
  } else if (Array.isArray(sys)) {
    for (const b of sys) {
      if (b && (b as TextBlock).type === 'text' && typeof (b as TextBlock).text === 'string') {
        n += (b as TextBlock).text.length;
      }
    }
  }

  // 2. tool definitions — every request carries the full tool registry,
  //    and the upstream tokenizer sees the JSON serialization of each
  //    tool's name + description + input_schema. This is a large
  //    constant-ish chunk in Claude Code traffic (~15-20 tools).
  if (Array.isArray(req.tools)) {
    for (const tool of req.tools) {
      if (!tool || typeof tool !== 'object') continue;
      if (typeof tool.name === 'string') n += tool.name.length;
      if (typeof tool.description === 'string') n += tool.description.length;
      if (tool.input_schema !== undefined) {
        n += safeStringifyLen(tool.input_schema);
      }
    }
  }

  // 3. per-message content
  for (const msg of req.messages ?? []) {
    const c = msg.content;
    if (typeof c === 'string') {
      n += c.length;
      continue;
    }
    if (!Array.isArray(c)) continue;
    for (const b of c) {
      if (!b || typeof b !== 'object') continue;
      const type = (b as { type?: string }).type;

      if (type === 'text') {
        const tb = b as TextBlock;
        if (typeof tb.text === 'string') n += tb.text.length;
        continue;
      }

      // Assistant turns issuing a tool call: name + serialized input.
      // `input` is arbitrary JSON; tokenizer sees its serialization.
      if (type === 'tool_use') {
        const tu = b as ToolUseBlock;
        if (typeof tu.name === 'string') n += tu.name.length;
        if (tu.input !== undefined) n += safeStringifyLen(tu.input);
        continue;
      }

      if (type === 'tool_result') {
        const tr = b as ToolResultBlock;
        if (typeof tr.tool_use_id === 'string') n += tr.tool_use_id.length;
        const inner = tr.content;
        if (typeof inner === 'string') {
          n += inner.length;
        } else if (Array.isArray(inner)) {
          for (const ib of inner) {
            if (ib && (ib as TextBlock).type === 'text' && typeof (ib as TextBlock).text === 'string') {
              n += (ib as TextBlock).text.length;
            }
          }
        }
        continue;
      }

      // Extended-thinking blocks: { type: 'thinking', thinking: string, ... }
      // Not in our local types yet (we don't rewrite them), but they carry
      // real characters that the upstream tokenizer sees.
      if (type === 'thinking') {
        const th = b as unknown as { thinking?: unknown };
        if (typeof th.thinking === 'string') n += (th.thinking as string).length;
        continue;
      }

      // image, redacted_thinking, server_tool_use, etc. — skip. Either
      // billed via pixels (image) or opaque to us (redacted_thinking).
    }
  }

  return n;
}

/** JSON.stringify, but tolerant of cycles / non-serializable values.
 *  We only care about the LENGTH; if it blows up we just return 0 rather
 *  than crash the whole transform. */
function safeStringifyLen(v: unknown): number {
  try {
    return JSON.stringify(v)?.length ?? 0;
  } catch {
    return 0;
  }
}
/**
 * The pxpipe proxy as a single Web-standard fetch handler.
 *
 * Both `src/node.ts` and `src/worker.ts` adapt this to their respective
 * runtimes (node:http server vs CF Worker `fetch` export). The handler
 * itself only uses `Request`, `Response`, `URL`, and global `fetch` — all
 * of which exist identically in Node 18+ and Workers.
 */

import { transformRequest, type TransformOptions, type TransformInfo } from './transform.js';
import { transformOpenAIChatCompletions } from './openai.js';
import { isPxpipeSupportedGptModel, isPxpipeSupportedModel } from './applicability.js';
import {
  buildBaselineCountTokensBody,
  buildCacheablePrefixCountTokensBody,
} from './measurement.js';
import type { Usage } from './types.js';

export interface ProxyConfig {
  /** Provider mode. 'cloudflare-ai-gateway' derives both upstreams from
   *  `gatewayBaseUrl` (`{base}/anthropic` and `{base}/openai`) and rewrites
   *  OpenAI paths to the gateway's shape (`/v1/chat/completions` →
   *  `/chat/completions`). Anthropic paths keep their `/v1/...` shape.
   *  Unrecognized paths pass through to the family route untouched. */
  provider?: 'cloudflare-ai-gateway';
  /** Gateway base URL (account/gateway-scoped). Required when provider is
   *  set. Comes from env/config only — never hardcoded. Overrides
   *  `upstream`/`openAIUpstream`. */
  gatewayBaseUrl?: string;
  /** Extra headers injected on every upstream request (e.g. gateway auth
   *  headers). Values come from env/config only. */
  gatewayHeaders?: Record<string, string>;
  /** Anthropic API base, no trailing slash. Defaults to api.anthropic.com. */
  upstream?: string;
  /** Override or supply an API key. If unset, we forward whatever the client sent. */
  apiKey?: string;
  /** OpenAI API base for GPT chat completions, no trailing slash. */
  openAIUpstream?: string;
  /** Override or supply an OpenAI API key. If unset, we forward Authorization. */
  openAIApiKey?: string;
  /** Per-request transform options. Pass a function when the host wants to
   *  inject DYNAMIC values per request (e.g. live empirical `charsPerToken`
   *  from the dashboard's converging fit) — the proxy invokes it once per
   *  /v1/messages POST. Static object form is used by the Workers host and
   *  tests that don't need dynamic state. */
  transform?: TransformOptions | (() => TransformOptions);
  /** Called after every request — useful for logging / metrics in the host. */
  onRequest?: (event: ProxyEvent) => void | Promise<void>;
}

export interface ProxyEvent {
  method: string;
  path: string;
  status: number;
  /** Wall-clock ms from request start to event fire (≈ end of upstream response
   *  body, since we now wait for usage extraction). For first-byte latency see
   *  firstByteMs. */
  durationMs: number;
  /** Wall-clock ms from request start to upstream response headers. */
  firstByteMs?: number;
  info?: TransformInfo;
  /** Usage block from Anthropic's response — input/output/cache tokens. */
  usage?: Usage;
  error?: string;
  /** First ~2 KiB of the upstream response body when status is in [400, 499].
   *  Lets us see what Anthropic actually rejected without re-running the request.
   *  Not captured for 2xx (no error) or 5xx (we synthesize our own message). */
  errorBody?: string;
  /** sha256[0..8] of the TRANSFORMED outgoing request body. Set on every
   *  /v1/messages POST regardless of status. Lets future debuggers correlate
   *  "same payload, sometimes works, sometimes fails" without storing bodies. */
  reqBodySha8?: string;
  /** Full gzipped transformed body, populated only on 4xx. The Node host may
   *  redirect this to a sidecar file (see reqBodySamplePath) before the
   *  tracker serializes the event; Workers always inline-cap at 32 KiB. */
  reqBodyGz?: Uint8Array;
  /** Set by the Node host *in place of* reqBodyGz when it wrote the gzipped
   *  body to a sidecar file. The path lands in the JSONL as
   *  `req_body_sample_path`. */
  reqBodySamplePath?: string;
  /** Ground-truth output measurement extracted from the response stream itself,
   *  independent of Anthropic's `usage.output_tokens`. Lets the dashboard show
   *  how much of the billed output was redacted_thinking (opaque server-encoded
   *  bytes) vs real text/thinking/tool_use. Absent on requests that didn't
   *  yield a body we could scan (no upstream response, 5xx, unknown
   *  content-type). See OutputMeasurement for field meanings. */
  measurement?: OutputMeasurement;
}

/** Max chars of upstream error body we surface on ProxyEvent. Keeps the JSONL
 *  line small while still being big enough to hold Anthropic's full error JSON
 *  (typically a few hundred bytes). */
const ERROR_BODY_MAX = 2048;

/** Cheap, bounded read of the top-level `model` field from an Anthropic
 *  /v1/messages body. The field sits near the start of the JSON, so we decode
 *  only the head rather than JSON-parsing the (potentially multi-MB) full
 *  conversation just to read one string. Returns null when not found — callers
 *  treat null as "outside supported scope" (fail-closed). */
function readModelField(body: Uint8Array): string | null {
  try {
    const head = new TextDecoder().decode(body.subarray(0, 8192));
    const m = /"model"\s*:\s*"([^"]{1,80})"/.exec(head);
    return m ? m[1]! : null;
  } catch {
    return null;
  }
}

/** Gzip a byte buffer using the standard `CompressionStream`. Available in
 *  Node 18+ and Cloudflare Workers — no Buffer / no zlib. */
async function gzipBytes(body: Uint8Array): Promise<Uint8Array> {
  // `body as BufferSource`: TS doesn't model Response taking a
[assistant]
Reviewed src/core/render.ts.

=== end ===
