LLeMbas CLI 1.5.1
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An image counted as half a million tokens: the context estimate measured its
base64 as text, so a 1-3 MB screenshot read as "context at 150-280%" the
moment view_image added it, and the session compacted after every image.
An image now counts by its dimensions (28 px patches, at most 16k tokens, a
flat 1600 when unreadable) everywhere the CLI estimates -- the meter, pruning,
/context and the no-usage fallback of all five dialects. Images over 1600 px
or 500 KB are shrunk to 1600 px when ImageMagick is there.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
HomerandClaude Opus 5.5 committed 2026-10-23 21:24:31 +00:00
1 parent 025b067e38
commit 82918ba5a8
12 files changed
+196 -18

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+12 -2
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@@ -1,17 +1,21 @@
// Images for vision models: read, size-checked, downscaled when ImageMagick is there.
import { readFileSync, statSync } from "node:fs"
import { extname } from "node:path"
import { imageSize } from "../provider/tokens.ts"
import type { ImagePart } from "../provider/types.ts"
export const IMAGE_TYPES: Record<string, string> = { ".png": "image/png", ".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".gif": "image/gif", ".webp": "image/webp" }
const MAX_BYTES = 3_500_000
const SHRINK_ABOVE_BYTES = 500_000
const MAX_EDGE = 1600
const magick = Bun.which("magick") ?? Bun.which("convert")
export function isImage(path: string): boolean {
return extname(path).toLowerCase() in IMAGE_TYPES
}
/** The image as a part, or a reason it cannot be one. Large ones are shrunk to 1600 px if possible. */
/** The image as a part, or a reason it cannot be one. Anything over 1600 px or 500 KB is shrunk to
* 1600 px when ImageMagick is there. */
export function loadImage(path: string): ImagePart | string {
const mime = IMAGE_TYPES[extname(path).toLowerCase()]
if (!mime) return `${path} is not a supported image (png, jpg, gif, webp)`
@@ -21,7 +25,13 @@ export function loadImage(path: string): ImagePart | string {
} catch {
return `${path} does not exist`
}
if (size <= MAX_BYTES) return { type: "image", mime, data: readFileSync(path).toString("base64") }
const bytes = readFileSync(path)
const dims = imageSize(bytes)
// A screenshot of a large monitor is sent at 1600 px on its longer edge, as the LLeMbas server
// scales uploads: a model sees no more detail in 2560 px than it is billed tokens for, and a
// half-megabyte PNG is a slow request for nothing. Without ImageMagick it goes as it is.
const big = size > SHRINK_ABOVE_BYTES || (dims !== undefined && Math.max(dims.width, dims.height) > MAX_EDGE)
if (size <= MAX_BYTES && (!big || !magick)) return { type: "image", mime, data: bytes.toString("base64") }
if (!magick) return `${path} is ${(size / 1e6).toFixed(1)} MB — too large to send, and ImageMagick is not installed to shrink it`
// The coder named from the extension: ImageMagick otherwise decides by content, and a file named
// .png that is really SVG or MVG can make it read other files or fetch URLs.
+2 -2
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@@ -6,7 +6,7 @@ import { resolveKey } from "../config/load.ts"
import { Parts, record, recordFailure, retrying, statusOf, SwapBanner } from "./common.ts"
import { authHeaders, joinUrl, request, tlsFor } from "./http.ts"
import { sseJson } from "./sse.ts"
import { estimateTokens } from "./tokens.ts"
import { estimateTokens, estimateValue } from "./tokens.ts"
import { ProviderError, type ChatRequest, type Client, type DiscoveredModel, type Message, type ResolvedModel, type StreamEvent, type ToolCallPart } from "./types.ts"
/** Thinking budgets by effort, when the model's config gives no effort_map. */
@@ -216,7 +216,7 @@ export class AnthropicClient implements Client {
const reason = finish === "max_tokens" ? "length" : finish === "tool_use" || message.parts.some((p) => p.type === "tool_call") ? "tool_calls" : "stop"
yield sawUsage
? { type: "usage", usage: { input, output, cached } }
: { type: "usage", usage: { input: estimateTokens(JSON.stringify(body.messages)), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
: { type: "usage", usage: { input: estimateValue(body.messages), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
yield { type: "finish", reason, message }
}
+2 -2
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@@ -7,7 +7,7 @@ import { DEFAULT_BUDGETS } from "./anthropic.ts"
import { Parts, record, recordFailure, retrying, statusOf } from "./common.ts"
import { authHeaders, joinUrl, request, tlsFor } from "./http.ts"
import { sseJson } from "./sse.ts"
import { estimateTokens } from "./tokens.ts"
import { estimateTokens, estimateValue } from "./tokens.ts"
import { ProviderError, type ChatRequest, type Client, type DiscoveredModel, type Message, type ResolvedModel, type StreamEvent, type ToolCallPart } from "./types.ts"
type Content = { role: "user" | "model"; parts: Record<string, unknown>[] }
@@ -301,7 +301,7 @@ export class GeminiClient implements Client {
}
const message = out.message()
if (slots.size && finish !== "length") finish = "tool_calls"
yield usage ?? { type: "usage", usage: { input: estimateTokens(JSON.stringify(body.contents)), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
yield usage ?? { type: "usage", usage: { input: estimateValue(body.contents), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
yield { type: "finish", reason: finish, message }
}
+2 -2
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@@ -7,7 +7,7 @@
import { resolveKey } from "../config/load.ts"
import { Parts, record, recordFailure, retrying, statusOf } from "./common.ts"
import { authHeaders, joinUrl, request, tlsFor } from "./http.ts"
import { estimateTokens } from "./tokens.ts"
import { estimateTokens, estimateValue } from "./tokens.ts"
import { ProviderError, type ChatRequest, type Client, type DiscoveredModel, type Message, type ResolvedModel, type StreamEvent } from "./types.ts"
export function toOllamaMessages(system: string, messages: Message[], vision: boolean): Record<string, unknown>[] {
@@ -160,7 +160,7 @@ export class OllamaClient implements Client {
}
const message = out.message()
if (calls && finish !== "length") finish = "tool_calls"
yield usage ?? { type: "usage", usage: { input: estimateTokens(JSON.stringify(body.messages)), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
yield usage ?? { type: "usage", usage: { input: estimateValue(body.messages), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true } }
yield { type: "finish", reason: finish, message }
}
+2 -2
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@@ -11,7 +11,7 @@ import { learned, learnEfforts, learnNoProgress, learnNoStreamOptions } from "./
import { historyArgs, Parts, record, recordFailure, retrying, statusOf, SwapBanner } from "./common.ts"
import { sseJson } from "./sse.ts"
import { ThinkSplitter } from "./think.ts"
import { estimateTokens } from "./tokens.ts"
import { estimateTokens, estimateValue } from "./tokens.ts"
import {
ProviderError,
type ChatRequest,
@@ -274,7 +274,7 @@ export class OpenAIChatClient implements Client {
const parts = message.parts
if (!usage) {
const out = parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.name + p.args : p.text), 0)
usage = { type: "usage", usage: { input: estimateTokens(JSON.stringify(body.messages)), output: out, estimated: true } }
usage = { type: "usage", usage: { input: estimateValue(body.messages), output: out, estimated: true } }
}
yield usage
yield { type: "finish", reason: finish, message }
+2 -2
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@@ -6,7 +6,7 @@ import { historyArgs, Parts, record, recordFailure, retrying, statusOf, SwapBann
import { authHeaders, joinUrl, request, tlsFor } from "./http.ts"
import { contextFrom } from "./openai-chat.ts"
import { sseJson } from "./sse.ts"
import { estimateTokens } from "./tokens.ts"
import { estimateTokens, estimateValue } from "./tokens.ts"
import { ProviderError, type ChatRequest, type Client, type DiscoveredModel, type Message, type ResolvedModel, type StreamEvent } from "./types.ts"
type Item = Record<string, unknown>
@@ -161,7 +161,7 @@ export class ResponsesClient implements Client {
if (finish !== "length" && message.parts.some((p) => p.type === "tool_call")) finish = "tool_calls"
yield usage ?? {
type: "usage",
usage: { input: estimateTokens(JSON.stringify(body.input)), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true },
usage: { input: estimateValue(body.input), output: message.parts.reduce((n, p) => n + estimateTokens(p.type === "tool_call" ? p.args : p.text), 0), estimated: true },
}
yield { type: "finish", reason: finish, message }
}
+84
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@@ -4,3 +4,87 @@ export const CHARS_PER_TOKEN = 4
export function estimateTokens(text: string): number {
return Math.ceil(text.length / CHARS_PER_TOKEN)
}
/** An image whose size cannot be read counts as this many tokens (a 1600 px screenshot, roughly). */
export const IMAGE_FALLBACK_TOKENS = 1600
/** Pixels per token edge: Qwen-VL's 28 px patches; OpenAI's and Anthropic's tiles land near it. */
const PATCH = 28
/** No image costs more than this (vLLM's Qwen default max_pixels / 784). */
const IMAGE_MAX_TOKENS = 16_384
/** A string this long made only of base64 characters is an image's bytes, not text. */
const BASE64_MIN = 2_000
const BASE64 = /^[A-Za-z0-9+/=_-]+$/
/** The width and height in an image's first bytes (PNG, JPEG, GIF, WebP), or undefined. */
export function imageSize(bytes: Uint8Array): { width: number; height: number } | undefined {
const at = (i: number) => bytes[i] ?? 0
const be16 = (i: number) => (at(i) << 8) | at(i + 1)
const le16 = (i: number) => at(i) | (at(i + 1) << 8)
const be32 = (i: number) => ((at(i) << 24) | (at(i + 1) << 16) | (at(i + 2) << 8) | at(i + 3)) >>> 0
if (at(0) === 0x89 && at(1) === 0x50 && at(2) === 0x4e && at(3) === 0x47) return { width: be32(16), height: be32(20) }
if (at(0) === 0x47 && at(1) === 0x49 && at(2) === 0x46) return { width: le16(6), height: le16(8) }
if (at(0) === 0x52 && at(1) === 0x49 && at(2) === 0x46 && at(3) === 0x46 && at(8) === 0x57 && at(9) === 0x45) {
const chunk = String.fromCharCode(at(12), at(13), at(14), at(15))
if (chunk === "VP8X") return { width: 1 + (at(24) | (at(25) << 8) | (at(26) << 16)), height: 1 + (at(27) | (at(28) << 8) | (at(29) << 16)) }
if (chunk === "VP8 ") return { width: le16(26) & 0x3fff, height: le16(28) & 0x3fff }
if (chunk === "VP8L") {
const b = (at(21) | (at(22) << 8) | (at(23) << 16) | (at(24) << 24)) >>> 0
return { width: (b & 0x3fff) + 1, height: ((b >> 14) & 0x3fff) + 1 }
}
return undefined
}
if (at(0) === 0xff && at(1) === 0xd8) {
// Walk the segments to a start-of-frame marker (C0–CF, except C4, C8, CC).
let i = 2
while (i + 9 < bytes.length) {
if (at(i) !== 0xff) return undefined
const marker = at(i + 1)
if (marker >= 0xc0 && marker <= 0xcf && marker !== 0xc4 && marker !== 0xc8 && marker !== 0xcc) {
return { width: be16(i + 7), height: be16(i + 5) }
}
i += 2 + be16(i + 2)
}
}
return undefined
}
/**
* What an image costs a model, from its dimensions -- never from its encoding. Counting the
* base64 as text made a 1.5 MB screenshot "512k tokens": the CLI then compacted after every
* view_image, at "context 215%", while the provider charged a few thousand. Only the head is
* decoded (enough for the header, and a JPEG's frame marker in all but odd files).
*/
export function imageTokens(base64: string): number {
const head = base64.replace(/^data:[^,]*,/, "").slice(0, 87_384) // 64 KB of bytes
let size: { width: number; height: number } | undefined
try {
size = imageSize(Buffer.from(head.slice(0, head.length - (head.length % 4)), "base64"))
} catch {
size = undefined
}
if (!size || !size.width || !size.height) return IMAGE_FALLBACK_TOKENS
return Math.min(IMAGE_MAX_TOKENS, Math.ceil(size.width / PATCH) * Math.ceil(size.height / PATCH))
}
function isImageData(text: string): boolean {
if (text.startsWith("data:image/")) return true
return text.length >= BASE64_MIN && BASE64.test(text.slice(0, 4096))
}
/**
* Tokens for any value about to be sent or kept in history -- a message, a request body in any
* dialect: its JSON measured as text, except that an image is counted by `imageTokens`. Images
* are found by shape, so the one rule covers every wire format (an `image_url` data URL, an
* Anthropic or Gemini base64 `data`, Ollama's `images` list, the history's own `ImagePart`).
*/
export function estimateValue(value: unknown): number {
let images = 0
const text = JSON.stringify(value, (_key, v) => {
if (typeof v === "string" && isImageData(v)) {
images += imageTokens(v)
return ""
}
return v
})
return estimateTokens(text ?? "") + images
}
+2 -2
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@@ -2,7 +2,7 @@
// up to what the server last reported when it reported anything.
import type { Engine } from "./engine.ts"
import { contextWindow } from "../provider/discover.ts"
import { estimateTokens } from "../provider/tokens.ts"
import { estimateTokens, imageTokens } from "../provider/tokens.ts"
import { toSpec, type Tool } from "../tool/tool.ts"
export interface ContextRow {
@@ -29,7 +29,7 @@ export function contextBreakdown(engine: Engine, system: string, instructions: {
else if (p.type === "tool_call") by.calls += estimateTokens(p.name + p.args)
else {
imageCount++
by.images += 800 // providers bill an image at roughly this for a typical screenshot
by.images += imageTokens(p.data) // by its dimensions, as contextUsed counts it
}
}
}
+3 -3
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@@ -16,7 +16,7 @@ import { fill, promptText } from "../prompt/assemble.ts"
import { resolveCall } from "../tool/names.ts"
import { contextWindow } from "../provider/discover.ts"
import { summaryTurns, type Store } from "./store.ts"
import { estimateTokens } from "../provider/tokens.ts"
import { estimateTokens, estimateValue } from "../provider/tokens.ts"
import { duration } from "../duration.ts"
export interface EngineOptions {
@@ -244,7 +244,7 @@ export class Engine {
* last reply's output but will not be in the next request. */
contextUsed(): number | undefined {
if (!this.usage) return undefined
return this.usage.input + this.usage.output - this.droppedThinking() + estimateTokens(JSON.stringify(this.messages.slice(this.usageAt)))
return this.usage.input + this.usage.output - this.droppedThinking() + estimateValue(this.messages.slice(this.usageAt))
}
private droppedThinking(): number {
@@ -262,7 +262,7 @@ export class Engine {
let saved = 0
for (let i = this.messages.length - 1; i >= 0; i--) {
const m = this.messages[i]!
const size = estimateTokens(JSON.stringify(m))
const size = estimateValue(m)
if (recent < protect) {
recent += size
continue