Files
baoyu-skills/skills/baoyu-image-gen/scripts/providers/zai.ts
T
Jim Liu 宝玉 2c800c670a [codex] Refactor skills into focused references (#135)
* docs: add runtime-neutral User Input Tools convention across skills

Introduce docs/user-input-tools.md as the author-side canonical source
and inline the tool-selection rule into every SKILL.md that prompts
the user. Also add Skill Self-Containment and User Input Tools sections
to CLAUDE.md and the copy-verbatim template to docs/creating-skills.md,
so skills stay portable across Claude Code, Codex, Hermes, and other
runtimes.

* feat: runtime-neutral image generation convention across skills

- Introduce inline `## Image Generation Tools` rule in every rendering SKILL.md so skills delegate backend choice instead of hard-coding one; author-side canonical copy lives in docs/image-generation-tools.md.
- Add `## Reference Images` support (`--ref`, frontmatter `references:` with direct/style/palette usage) to all seven image-rendering skills.
- Move build-batch.ts (with ref propagation into batch JSON) from baoyu-article-illustrator to baoyu-imagine so non-backend skills don't own backend-specific scripts; update baoyu-image-gen stub in sync and relax the CLAUDE.md deprecation note accordingly.

* refactor: slim heavy SKILL.md files and move detail to references/

Trim the four largest active skills and move presets, option tables, and
confirmation scripts into per-skill references/ so SKILL.md stays focused
on the decision flow.

- baoyu-slide-deck: 761→258, + styles-gallery.md, confirmation.md
- baoyu-image-cards: 657→280, + gallery.md, confirmation.md
- baoyu-post-to-wechat: 518→267, + multi-account.md, api-setup.md
- baoyu-imagine: 500→230, + providers/, usage-examples.md

Also un-deprecate baoyu-image-gen (drop stub warning) so it stays functional
alongside baoyu-imagine, and update CLAUDE.md to reflect that both
superseded skills are kept in sync rather than stubbed.

* refactor: slim four medium SKILL.md files into references/

Continue the P2 pattern on the next tier of skills — move option catalogs,
per-provider/adapter detail, and repeated EXTEND.md path boilerplate into
their own references so SKILL.md stays focused on the decision flow.

- baoyu-comic: 380→297 (art/tone/preset tables → auto-selection.md;
  Step 7 expanded detail → workflow.md)
- baoyu-infographic: 312→207 (layouts/styles/combinations/keywords →
  gallery.md; ASCII box tables → markdown tables)
- baoyu-format-markdown: 376→296 (title + summary generation →
  title-summary.md; ASCII box tables → markdown tables)
- baoyu-url-to-markdown: 334→169 (quality gate + recovery →
  quality-gate.md; adapters + media download → adapters.md)

* chore: sync deprecated skills with their replacements

Per project policy, baoyu-xhs-images and baoyu-image-gen are kept
functional alongside the active skills they were superseded by. Sync
their SKILL.md bodies and references/ to the slimmed baoyu-image-cards
and baoyu-imagine versions respectively, so cross-cutting fixes stay
consistent. Only the frontmatter (name, description, version, homepage)
differs — content is identical.

- baoyu-xhs-images: 657→281 (synced with baoyu-image-cards + new
  confirmation.md, gallery.md)
- baoyu-image-gen: 408→231 (synced with baoyu-imagine + new
  providers/, usage-examples.md)

* refactor: collapse EXTEND.md boilerplate into priority tables

Replace the dual bash/powershell existence-check blocks and ASCII box
art with a single markdown priority table across nine SKILL.md files.
The runtime-neutral phrasing removes shell-specific snippets without
losing the priority semantics.

* fix: address refactor-skills branch review findings

- image-gen: restore EXTEND.md paths to baoyu-image-gen (were pointing at
  baoyu-imagine) and mark descriptions of both deprecated skills as
  [Deprecated].
- xhs-images: sync neon/warm palettes with image-cards to add the
  "do not render color names/hex as visible text" safety sentence.
- infographic: restore Layout Gallery (21), Style Gallery (21),
  Recommended Combinations, and Keyword Shortcuts inline (previous
  refactor split them out but SKILL.md still depended on them), and add
  the missing references/config/first-time-setup.md + preferences-schema.md.
- image-cards / xhs-images / slide-deck / format-markdown: restore the
  sections that got over-slimmed into references/ (galleries, presets,
  dimensions, auto-selection, style x layout matrix, title/summary flow)
  and drop the now-empty shell files.
- docs/image-generation-tools.md: note that backend skills themselves
  (baoyu-imagine, baoyu-image-gen, baoyu-danger-gemini-web) are exempt
  from the ## Image Generation Tools section requirement.

* feat(image-gen): sync Z.AI GLM-Image provider from baoyu-imagine

Add Z.AI as a full provider in the deprecated baoyu-image-gen skill so
it stays in sync with baoyu-imagine's provider list.

- new scripts/providers/zai.ts + zai.test.ts (verbatim port; test
  factory trimmed to match image-gen's CliArgs shape).
- types.ts: "zai" added to Provider union and default_model.
- main.ts: rate-limit defaults, provider help text, env var help,
  --provider validation, loadProviderModule, detectProvider
  auto-detect chain, getModelForProvider, YAML parser allow-lists.
- references/config: Q2e Z.AI model question + zai slot in the
  preferences schema and batch.provider_limits.

Scope is intentionally limited to the Z.AI chain; unrelated drift
between image-gen and imagine (OpenAI image-API dialect,
aspectRatioSource, imageSizeSource) is left alone.

* docs: align inline-convention wording and note backend-skill exemption

- docs/user-input-tools.md: fix stale "links here" wording so it
  matches the inline convention already enforced everywhere else.
- CLAUDE.md §Image Generation Tools: inline the backend-skill
  exemption so readers don't need to cross-reference
  docs/image-generation-tools.md.
2026-04-19 00:48:44 -05:00

307 lines
8.7 KiB
TypeScript

import type { CliArgs, Quality } from "../types";
type ZaiModelFamily = "glm" | "legacy";
type ZaiRequestBody = {
model: string;
prompt: string;
quality: "hd" | "standard";
size: string;
};
type ZaiResponse = {
data?: Array<{ url?: string }>;
};
const DEFAULT_MODEL = "glm-image";
const GLM_MAX_PIXELS = 2 ** 22;
const LEGACY_MAX_PIXELS = 2 ** 21;
const GLM_SIZE_STEP = 32;
const LEGACY_SIZE_STEP = 16;
const GLM_RECOMMENDED_SIZES: Record<string, string> = {
"1:1": "1280x1280",
"3:2": "1568x1056",
"2:3": "1056x1568",
"4:3": "1472x1088",
"3:4": "1088x1472",
"16:9": "1728x960",
"9:16": "960x1728",
};
const LEGACY_RECOMMENDED_SIZES: Record<string, string> = {
"1:1": "1024x1024",
"9:16": "768x1344",
"3:4": "864x1152",
"16:9": "1344x768",
"4:3": "1152x864",
"2:1": "1440x720",
"1:2": "720x1440",
};
export function getDefaultModel(): string {
return process.env.ZAI_IMAGE_MODEL || process.env.BIGMODEL_IMAGE_MODEL || DEFAULT_MODEL;
}
function getApiKey(): string | null {
return process.env.ZAI_API_KEY || process.env.BIGMODEL_API_KEY || null;
}
export function buildZaiUrl(): string {
const base = (process.env.ZAI_BASE_URL || process.env.BIGMODEL_BASE_URL || "https://api.z.ai/api/paas/v4")
.replace(/\/+$/g, "");
if (base.endsWith("/images/generations")) return base;
if (base.endsWith("/api/paas/v4")) return `${base}/images/generations`;
if (base.endsWith("/v4")) return `${base}/images/generations`;
return `${base}/api/paas/v4/images/generations`;
}
export function getModelFamily(model: string): ZaiModelFamily {
return model.trim().toLowerCase() === "glm-image" ? "glm" : "legacy";
}
export function parseAspectRatio(ar: string): { width: number; height: number } | null {
const match = ar.match(/^(\d+(?:\.\d+)?):(\d+(?:\.\d+)?)$/);
if (!match) return null;
const width = Number(match[1]);
const height = Number(match[2]);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
export function parseSize(size: string): { width: number; height: number } | null {
const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
if (!match) return null;
const width = parseInt(match[1]!, 10);
const height = parseInt(match[2]!, 10);
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return null;
}
return { width, height };
}
function formatSize(width: number, height: number): string {
return `${width}x${height}`;
}
function roundToStep(value: number, step: number): number {
return Math.max(step, Math.round(value / step) * step);
}
function getRatioValue(ar: string): number | null {
const parsed = parseAspectRatio(ar);
if (!parsed) return null;
return parsed.width / parsed.height;
}
function findClosestRatioKey(ar: string, candidates: string[]): string | null {
const targetRatio = getRatioValue(ar);
if (targetRatio == null) return null;
let bestKey: string | null = null;
let bestDiff = Infinity;
for (const candidate of candidates) {
const candidateRatio = getRatioValue(candidate);
if (candidateRatio == null) continue;
const diff = Math.abs(candidateRatio - targetRatio);
if (diff < bestDiff) {
bestDiff = diff;
bestKey = candidate;
}
}
return bestDiff <= 0.05 ? bestKey : null;
}
function getTargetPixels(quality: Quality): number {
return quality === "normal" ? 1024 * 1024 : 1536 * 1536;
}
function fitToPixelBudget(
width: number,
height: number,
targetPixels: number,
maxPixels: number,
step: number,
): { width: number; height: number } {
let nextWidth = width;
let nextHeight = height;
const pixels = nextWidth * nextHeight;
if (pixels > maxPixels) {
const scale = Math.sqrt(maxPixels / pixels);
nextWidth *= scale;
nextHeight *= scale;
} else {
const scale = Math.sqrt(targetPixels / pixels);
nextWidth *= scale;
nextHeight *= scale;
}
let roundedWidth = roundToStep(nextWidth, step);
let roundedHeight = roundToStep(nextHeight, step);
let roundedPixels = roundedWidth * roundedHeight;
while (roundedPixels > maxPixels && (roundedWidth > step || roundedHeight > step)) {
if (roundedWidth >= roundedHeight && roundedWidth > step) {
roundedWidth -= step;
} else if (roundedHeight > step) {
roundedHeight -= step;
} else {
break;
}
roundedPixels = roundedWidth * roundedHeight;
}
return { width: roundedWidth, height: roundedHeight };
}
function validateCustomSize(
size: string,
family: ZaiModelFamily,
): string {
const parsed = parseSize(size);
if (!parsed) {
throw new Error("Z.AI --size must be in WxH format, for example 1280x1280.");
}
const widthStep = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
const minEdge = family === "glm" ? 1024 : 512;
const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
if (parsed.width < minEdge || parsed.width > 2048 || parsed.height < minEdge || parsed.height > 2048) {
throw new Error(
family === "glm"
? "GLM-image custom size requires width and height between 1024 and 2048."
: "Z.AI legacy image models require width and height between 512 and 2048."
);
}
if (parsed.width % widthStep !== 0 || parsed.height % widthStep !== 0) {
throw new Error(
family === "glm"
? "GLM-image custom size requires width and height divisible by 32."
: "Z.AI legacy image models require width and height divisible by 16."
);
}
if (parsed.width * parsed.height > maxPixels) {
throw new Error(
family === "glm"
? "GLM-image custom size must not exceed 2^22 total pixels."
: "Z.AI legacy image size must not exceed 2^21 total pixels."
);
}
return formatSize(parsed.width, parsed.height);
}
export function resolveSizeForModel(
model: string,
args: Pick<CliArgs, "size" | "aspectRatio" | "quality">,
): string {
const family = getModelFamily(model);
const quality = args.quality === "normal" ? "normal" : "2k";
if (args.size) {
return validateCustomSize(args.size, family);
}
const recommended = family === "glm" ? GLM_RECOMMENDED_SIZES : LEGACY_RECOMMENDED_SIZES;
const defaultSize = family === "glm" ? "1280x1280" : "1024x1024";
if (!args.aspectRatio) return defaultSize;
const recommendedRatio = findClosestRatioKey(args.aspectRatio, Object.keys(recommended));
if (recommendedRatio) {
return recommended[recommendedRatio]!;
}
const parsedRatio = parseAspectRatio(args.aspectRatio);
if (!parsedRatio) return defaultSize;
const targetPixels = getTargetPixels(quality);
const maxPixels = family === "glm" ? GLM_MAX_PIXELS : LEGACY_MAX_PIXELS;
const step = family === "glm" ? GLM_SIZE_STEP : LEGACY_SIZE_STEP;
const fit = fitToPixelBudget(
parsedRatio.width,
parsedRatio.height,
targetPixels,
maxPixels,
step,
);
return formatSize(fit.width, fit.height);
}
function getZaiQuality(quality: CliArgs["quality"]): "hd" | "standard" {
return quality === "normal" ? "standard" : "hd";
}
export function validateArgs(_model: string, args: CliArgs): void {
if (args.referenceImages.length > 0) {
throw new Error("Z.AI GLM-image currently supports text-to-image only in baoyu-image-gen. Remove --ref or choose another provider.");
}
if (args.n > 1) {
throw new Error("Z.AI image generation currently returns a single image per request in baoyu-image-gen.");
}
}
export function buildRequestBody(
prompt: string,
model: string,
args: CliArgs,
): ZaiRequestBody {
validateArgs(model, args);
return {
model,
prompt,
quality: getZaiQuality(args.quality),
size: resolveSizeForModel(model, args),
};
}
export async function extractImageFromResponse(result: ZaiResponse): Promise<Uint8Array> {
const url = result.data?.[0]?.url;
if (!url) {
throw new Error("No image URL in Z.AI response");
}
const imageResponse = await fetch(url);
if (!imageResponse.ok) {
throw new Error(`Failed to download image from Z.AI: ${imageResponse.status}`);
}
return new Uint8Array(await imageResponse.arrayBuffer());
}
export async function generateImage(
prompt: string,
model: string,
args: CliArgs,
): Promise<Uint8Array> {
const apiKey = getApiKey();
if (!apiKey) {
throw new Error("ZAI_API_KEY is required. Get one from https://docs.z.ai/.");
}
const response = await fetch(buildZaiUrl(), {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${apiKey}`,
},
body: JSON.stringify(buildRequestBody(prompt, model, args)),
});
if (!response.ok) {
const err = await response.text();
throw new Error(`Z.AI API error (${response.status}): ${err}`);
}
const result = (await response.json()) as ZaiResponse;
return extractImageFromResponse(result);
}