feat(baoyu-imagine): add schema-aware Replicate model family support
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justnodejs
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@ -768,7 +768,7 @@ AI SDK-based image generation using OpenAI, Azure OpenAI, Google, OpenRouter, Da
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| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
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| `DASHSCOPE_IMAGE_MODEL` | DashScope model | `qwen-image-2.0-pro` |
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| `MINIMAX_IMAGE_MODEL` | MiniMax model | `image-01` |
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| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-pro` |
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| `REPLICATE_IMAGE_MODEL` | Replicate model | `google/nano-banana-2` |
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| `JIMENG_IMAGE_MODEL` | Jimeng model | `jimeng_t2i_v40` |
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| `SEEDREAM_IMAGE_MODEL` | Seedream model | `doubao-seedream-5-0-260128` |
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| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
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@ -1108,7 +1108,7 @@ MINIMAX_IMAGE_MODEL=image-01
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# Replicate
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REPLICATE_API_TOKEN=r8_xxx
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REPLICATE_IMAGE_MODEL=google/nano-banana-pro
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REPLICATE_IMAGE_MODEL=google/nano-banana-2
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# REPLICATE_BASE_URL=https://api.replicate.com
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# Jimeng (即梦)
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@ -768,7 +768,7 @@ AI 驱动的生成后端。
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| `GOOGLE_IMAGE_MODEL` | Google 模型 | `gemini-3-pro-image-preview` |
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| `DASHSCOPE_IMAGE_MODEL` | DashScope 模型 | `qwen-image-2.0-pro` |
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| `MINIMAX_IMAGE_MODEL` | MiniMax 模型 | `image-01` |
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| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-pro` |
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| `REPLICATE_IMAGE_MODEL` | Replicate 模型 | `google/nano-banana-2` |
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| `JIMENG_IMAGE_MODEL` | 即梦模型 | `jimeng_t2i_v40` |
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| `SEEDREAM_IMAGE_MODEL` | 豆包模型 | `doubao-seedream-5-0-260128` |
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| `OPENAI_BASE_URL` | 自定义 OpenAI 端点 | - |
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@ -1108,7 +1108,7 @@ MINIMAX_IMAGE_MODEL=image-01
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# Replicate
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REPLICATE_API_TOKEN=r8_xxx
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REPLICATE_IMAGE_MODEL=google/nano-banana-pro
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REPLICATE_IMAGE_MODEL=google/nano-banana-2
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# REPLICATE_BASE_URL=https://api.replicate.com
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# 即梦（Jimeng）
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@ -112,7 +112,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window
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# MiniMax with custom size (documented for image-01)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024
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# Replicate (google/nano-banana-pro)
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# Replicate (google/nano-banana-2)
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${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
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# Replicate with specific model
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@ -136,7 +136,7 @@ ${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json
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"promptFiles": ["prompts/hero.md"],
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"image": "out/hero.png",
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"provider": "replicate",
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"model": "google/nano-banana-pro",
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"model": "google/nano-banana-2",
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"ar": "16:9",
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"quality": "2k"
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},
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@ -192,7 +192,7 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
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| `GOOGLE_IMAGE_MODEL` | Google model override |
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| `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: `qwen-image-2.0-pro`) |
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| `MINIMAX_IMAGE_MODEL` | MiniMax model override (default: `image-01`) |
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| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
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| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-2) |
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| `JIMENG_IMAGE_MODEL` | Jimeng model override (default: jimeng_t2i_v40) |
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| `SEEDREAM_IMAGE_MODEL` | Seedream model override (default: doubao-seedream-5-0-260128) |
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| `OPENAI_BASE_URL` | Custom OpenAI endpoint |
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@ -324,7 +324,7 @@ Notes:
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Supported model formats:
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- `owner/name` (recommended for official models), e.g. `google/nano-banana-pro`
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- `owner/name` (recommended for official models), e.g. `google/nano-banana-2`
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- `owner/name:version` (community models by version), e.g. `stability-ai/sdxl:<version>`
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Examples:
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@ -56,7 +56,7 @@ options:
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- label: "MiniMax"
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description: "MiniMax image generation with subject-reference character workflows"
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- label: "Replicate"
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description: "Community models - nano-banana-pro, flexible model selection"
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description: "Community models - nano-banana-2, flexible model selection"
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```
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### Question 2: Default Google Model
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@ -263,7 +263,7 @@ Notes for DashScope setup:
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header: "Replicate Model"
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question: "Choose a default Replicate image generation model?"
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options:
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- label: "google/nano-banana-pro (Recommended)"
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- label: "google/nano-banana-2 (Recommended)"
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description: "Google's fast image model on Replicate"
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- label: "google/nano-banana"
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description: "Google's base image model on Replicate"
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@ -26,7 +26,7 @@ default_model:
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openrouter: null # e.g., "google/gemini-3.1-flash-image-preview"
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dashscope: null # e.g., "qwen-image-2.0-pro"
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minimax: null # e.g., "image-01"
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replicate: null # e.g., "google/nano-banana-pro"
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replicate: null # e.g., "google/nano-banana-2"
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batch:
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max_workers: 10
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@ -101,7 +101,7 @@ default_model:
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openrouter: "google/gemini-3.1-flash-image-preview"
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dashscope: "qwen-image-2.0-pro"
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minimax: "image-01"
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replicate: "google/nano-banana-pro"
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replicate: "google/nano-banana-2"
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batch:
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max_workers: 10
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provider_limits:
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@ -96,7 +96,7 @@ Batch file format:
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"promptFiles": ["prompts/hero.md"],
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"image": "out/hero.png",
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"provider": "replicate",
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"model": "google/nano-banana-pro",
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"model": "google/nano-banana-2",
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"ar": "16:9"
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}
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]
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@ -123,7 +123,7 @@ Environment variables:
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GOOGLE_IMAGE_MODEL Default Google model (gemini-3-pro-image-preview)
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DASHSCOPE_IMAGE_MODEL Default DashScope model (qwen-image-2.0-pro)
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MINIMAX_IMAGE_MODEL Default MiniMax model (image-01)
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REPLICATE_IMAGE_MODEL Default Replicate model (google/nano-banana-pro)
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REPLICATE_IMAGE_MODEL Default Replicate model (google/nano-banana-2)
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JIMENG_IMAGE_MODEL Default Jimeng model (jimeng_t2i_v40)
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SEEDREAM_IMAGE_MODEL Default Seedream model (doubao-seedream-5-0-260128)
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OPENAI_BASE_URL Custom OpenAI endpoint
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@ -5,7 +5,9 @@ import type { CliArgs } from "../types.ts";
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import {
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buildInput,
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extractOutputUrl,
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generateImage,
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parseModelId,
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validateArgs,
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} from "./replicate.ts";
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function makeArgs(overrides: Partial<CliArgs> = {}): CliArgs {
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@ -47,21 +49,20 @@ test("Replicate model parsing accepts official formats and rejects malformed one
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);
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});
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test("Replicate input builder maps aspect ratio, image count, quality, and refs", () => {
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test("Replicate input builder keeps nano-banana mapping for compatible models", () => {
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"google/nano-banana-2",
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makeArgs({
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aspectRatio: "16:9",
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quality: "2k",
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n: 3,
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}),
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["data:image/png;base64,AAAA"],
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),
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{
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prompt: "A robot painter",
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aspect_ratio: "16:9",
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number_of_images: 3,
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resolution: "2K",
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output_format: "png",
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image_input: ["data:image/png;base64,AAAA"],
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@ -69,7 +70,7 @@ test("Replicate input builder maps aspect ratio, image count, quality, and refs"
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);
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assert.deepEqual(
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buildInput("A robot painter", makeArgs({ quality: "normal" }), ["ref"]),
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buildInput("A robot painter", "google/nano-banana-pro", makeArgs({ quality: "normal" }), ["ref"]),
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{
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prompt: "A robot painter",
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aspect_ratio: "match_input_image",
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@ -80,6 +81,146 @@ test("Replicate input builder maps aspect ratio, image count, quality, and refs"
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);
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});
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test("Replicate input builder maps Seedream models to size-based schema", () => {
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"bytedance/seedream-4.5",
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makeArgs({
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quality: "2k",
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aspectRatio: "16:9",
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n: 4,
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}),
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["data:image/png;base64,AAAA"],
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),
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{
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prompt: "A robot painter",
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size: "2K",
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aspect_ratio: "16:9",
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sequential_image_generation: "auto",
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max_images: 4,
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image_input: ["data:image/png;base64,AAAA"],
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},
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);
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"bytedance/seedream-5-lite",
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makeArgs({
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size: "3K",
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aspectRatio: "4:3",
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}),
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[],
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),
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{
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prompt: "A robot painter",
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size: "3K",
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aspect_ratio: "4:3",
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output_format: "png",
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},
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);
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});
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test("Replicate input builder maps Wan models to their native schema", () => {
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"wan-video/wan-2.7-image-pro",
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makeArgs({
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quality: "2k",
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n: 2,
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}),
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["data:image/png;base64,AAAA"],
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),
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{
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prompt: "A robot painter",
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size: "2K",
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num_outputs: 2,
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images: ["data:image/png;base64,AAAA"],
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},
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);
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"wan-video/wan-2.7-image",
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makeArgs({
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size: "2048x1152",
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}),
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[],
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),
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{
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prompt: "A robot painter",
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size: "2048*1152",
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thinking_mode: true,
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},
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);
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});
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test("Replicate input builder falls back to nano-banana schema for unknown models", () => {
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assert.deepEqual(
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buildInput(
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"A robot painter",
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"unknown-owner/unknown-model",
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makeArgs({
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aspectRatio: "16:9",
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quality: "2k",
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}),
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["ref"],
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),
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{
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prompt: "A robot painter",
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aspect_ratio: "16:9",
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resolution: "2K",
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output_format: "png",
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image_input: ["ref"],
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},
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);
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});
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test("Replicate validation catches unsupported Seedream and Wan argument combinations", () => {
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assert.throws(
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() => validateArgs("bytedance/seedream-4.5", makeArgs({ size: "large" })),
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/Seedream on Replicate requires --size/,
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);
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assert.throws(
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() => validateArgs("bytedance/seedream-5-lite", makeArgs({ size: "4K" })),
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/Seedream on Replicate requires --size to be one of 2K, 3K/,
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);
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assert.throws(
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() => validateArgs("google/nano-banana-2", makeArgs({ n: 2 })),
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/Nano Banana models on Replicate do not support --n yet/,
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);
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assert.throws(
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() => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ aspectRatio: "16:9" })),
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/Wan image models on Replicate require --size when using --ar/,
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);
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assert.throws(
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() => validateArgs("wan-video/wan-2.7-image", makeArgs({ size: "wide" })),
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/Wan image models on Replicate require --size/,
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);
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assert.throws(
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() => validateArgs("wan-video/wan-2.7-image", makeArgs({ size: "4K" })),
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/Wan image models on Replicate require --size to be one of/,
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);
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assert.throws(
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() => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ size: "4K", referenceImages: ["ref"] })),
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/only supports 4K for text-to-image requests without input images/,
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);
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assert.throws(
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() => validateArgs("wan-video/wan-2.7-image-pro", makeArgs({ n: 5 })),
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/support --n values from 1 to 4/,
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);
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});
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test("Replicate output extraction supports string, array, and object URLs", () => {
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assert.equal(
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extractOutputUrl({ output: "https://example.com/a.png" } as never),
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@ -99,3 +240,25 @@ test("Replicate output extraction supports string, array, and object URLs", () =
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/Unexpected Replicate output format/,
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);
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});
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test("Replicate generateImage validates arguments before making API requests", async () => {
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const previousToken = process.env.REPLICATE_API_TOKEN;
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process.env.REPLICATE_API_TOKEN = "test-token";
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try {
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await assert.rejects(
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generateImage(
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"A robot painter",
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"wan-video/wan-2.7-image-pro",
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makeArgs({ aspectRatio: "16:9" }),
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),
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/Wan image models on Replicate require --size when using --ar/,
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);
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} finally {
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if (previousToken === undefined) {
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delete process.env.REPLICATE_API_TOKEN;
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} else {
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process.env.REPLICATE_API_TOKEN = previousToken;
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}
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}
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});
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@ -2,10 +2,31 @@ import path from "node:path";
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import { readFile } from "node:fs/promises";
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import type { CliArgs } from "../types";
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const DEFAULT_MODEL = "google/nano-banana-pro";
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const DEFAULT_MODEL = "google/nano-banana-2";
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const SYNC_WAIT_SECONDS = 60;
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const POLL_INTERVAL_MS = 2000;
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const MAX_POLL_MS = 300_000;
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const SIZE_PRESET_PATTERN = /^\d+K$/i;
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const SEEDREAM_45_SIZES = new Set(["2K", "4K"]);
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const SEEDREAM_5_LITE_SIZES = new Set(["2K", "3K"]);
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const WAN_PRO_SIZES = new Set([
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"1K", "2K", "4K",
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"1024*1024", "2048*2048", "4096*4096",
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"1280*720", "720*1280",
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"2048*1152", "1152*2048",
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"4096*2304", "2304*4096",
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"1024*768", "768*1024",
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"2048*1536", "1536*2048",
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"4096*3072", "3072*4096",
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]);
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const WAN_SIZES = new Set([
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"1K", "2K",
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"1024*1024", "2048*2048",
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"1280*720", "720*1280",
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"2048*1152", "1152*2048",
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"1024*768", "768*1024",
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"2048*1536", "1536*2048",
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]);
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export function getDefaultModel(): string {
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return process.env.REPLICATE_IMAGE_MODEL || DEFAULT_MODEL;
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@ -31,7 +52,78 @@ export function parseModelId(model: string): { owner: string; name: string; vers
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return { owner: parts[0], name: parts[1], version: version || null };
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}
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export function buildInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
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function isNanoBananaModel(model: string): boolean {
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return model.startsWith("google/nano-banana");
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}
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function isSeedreamModel(model: string): boolean {
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return model.startsWith("bytedance/seedream-4.5") || model.startsWith("bytedance/seedream-5-lite");
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}
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function isSeedream45Model(model: string): boolean {
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return model.startsWith("bytedance/seedream-4.5");
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}
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function isSeedream5LiteModel(model: string): boolean {
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return model.startsWith("bytedance/seedream-5-lite");
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}
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function isWanModel(model: string): boolean {
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return model.startsWith("wan-video/wan-2.7-image");
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}
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function isWanProModel(model: string): boolean {
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return model.startsWith("wan-video/wan-2.7-image-pro");
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}
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function parsePixelSize(size: string): { width: number; height: number } | null {
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const match = size.trim().match(/^(\d+)\s*[xX*]\s*(\d+)$/);
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if (!match) return null;
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|
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const width = Number.parseInt(match[1]!, 10);
|
||||
const height = Number.parseInt(match[2]!, 10);
|
||||
|
||||
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return { width, height };
|
||||
}
|
||||
|
||||
function normalizePixelSize(size: string): string {
|
||||
const parsed = parsePixelSize(size);
|
||||
if (!parsed) return size;
|
||||
return `${parsed.width}*${parsed.height}`;
|
||||
}
|
||||
|
||||
function isPresetSize(size: string): boolean {
|
||||
return SIZE_PRESET_PATTERN.test(size.trim());
|
||||
}
|
||||
|
||||
function getSeedreamDefaultSize(model: string, quality: CliArgs["quality"]): string | null {
|
||||
if (!isSeedreamModel(model) || !quality) return null;
|
||||
return "2K";
|
||||
}
|
||||
|
||||
function getWanDefaultSize(quality: CliArgs["quality"]): string | null {
|
||||
if (quality === "normal") return "1K";
|
||||
if (quality === "2k") return "2K";
|
||||
return null;
|
||||
}
|
||||
|
||||
function getAllowedSeedreamSizes(model: string): Set<string> {
|
||||
return isSeedream45Model(model) ? SEEDREAM_45_SIZES : SEEDREAM_5_LITE_SIZES;
|
||||
}
|
||||
|
||||
function getAllowedWanSizes(model: string): Set<string> {
|
||||
return isWanProModel(model) ? WAN_PRO_SIZES : WAN_SIZES;
|
||||
}
|
||||
|
||||
function normalizePresetSize(size: string): string {
|
||||
return size.trim().toUpperCase();
|
||||
}
|
||||
|
||||
function buildNanoBananaInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
|
||||
const input: Record<string, unknown> = { prompt };
|
||||
|
||||
if (args.aspectRatio) {
|
||||
|
|
@ -40,10 +132,6 @@ export function buildInput(prompt: string, args: CliArgs, referenceImages: strin
|
|||
input.aspect_ratio = "match_input_image";
|
||||
}
|
||||
|
||||
if (args.n > 1) {
|
||||
input.number_of_images = args.n;
|
||||
}
|
||||
|
||||
if (args.quality === "normal") {
|
||||
input.resolution = "1K";
|
||||
} else if (args.quality === "2k") {
|
||||
|
|
@ -59,6 +147,123 @@ export function buildInput(prompt: string, args: CliArgs, referenceImages: strin
|
|||
return input;
|
||||
}
|
||||
|
||||
function buildSeedreamInput(prompt: string, model: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
|
||||
const input: Record<string, unknown> = { prompt };
|
||||
const requestedSize = args.size || getSeedreamDefaultSize(model, args.quality);
|
||||
|
||||
if (requestedSize) {
|
||||
input.size = normalizePresetSize(requestedSize);
|
||||
}
|
||||
|
||||
if (args.aspectRatio) {
|
||||
input.aspect_ratio = args.aspectRatio;
|
||||
}
|
||||
|
||||
if (args.n > 1) {
|
||||
input.sequential_image_generation = "auto";
|
||||
input.max_images = args.n;
|
||||
}
|
||||
|
||||
if (referenceImages.length > 0) {
|
||||
input.image_input = referenceImages;
|
||||
}
|
||||
|
||||
if (isSeedream5LiteModel(model)) {
|
||||
input.output_format = "png";
|
||||
}
|
||||
|
||||
return input;
|
||||
}
|
||||
|
||||
function buildWanInput(prompt: string, model: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
|
||||
const input: Record<string, unknown> = { prompt };
|
||||
const requestedSize = args.size || getWanDefaultSize(args.quality);
|
||||
|
||||
if (requestedSize) {
|
||||
input.size = parsePixelSize(requestedSize) ? normalizePixelSize(requestedSize) : normalizePresetSize(requestedSize);
|
||||
}
|
||||
|
||||
if (args.n > 1) {
|
||||
input.num_outputs = args.n;
|
||||
}
|
||||
|
||||
if (referenceImages.length > 0) {
|
||||
input.images = referenceImages;
|
||||
}
|
||||
|
||||
// thinking_mode only applies to pure text-to-image.
|
||||
// image_set_mode is not exposed by the current CLI, so no extra check is needed here yet.
|
||||
if (referenceImages.length === 0) {
|
||||
input.thinking_mode = true;
|
||||
}
|
||||
|
||||
return input;
|
||||
}
|
||||
|
||||
export function validateArgs(model: string, args: CliArgs): void {
|
||||
if (isNanoBananaModel(model) && args.n > 1) {
|
||||
throw new Error("Nano Banana models on Replicate do not support --n yet because their current schema does not expose a multi-image count field.");
|
||||
}
|
||||
|
||||
if (isSeedreamModel(model)) {
|
||||
if (args.size) {
|
||||
const normalizedSize = normalizePresetSize(args.size);
|
||||
if (!getAllowedSeedreamSizes(model).has(normalizedSize)) {
|
||||
throw new Error(
|
||||
`Seedream on Replicate requires --size to be one of ${Array.from(getAllowedSeedreamSizes(model)).join(", ")}. Received: ${args.size}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (args.n < 1 || args.n > 15) {
|
||||
throw new Error("Seedream on Replicate supports --n values from 1 to 15.");
|
||||
}
|
||||
}
|
||||
|
||||
if (isWanModel(model)) {
|
||||
if (args.aspectRatio && !args.size) {
|
||||
throw new Error("Wan image models on Replicate require --size when using --ar. This provider does not infer size from aspect ratio.");
|
||||
}
|
||||
|
||||
if (args.size) {
|
||||
const normalizedSize = parsePixelSize(args.size) ? normalizePixelSize(args.size) : normalizePresetSize(args.size);
|
||||
if (!getAllowedWanSizes(model).has(normalizedSize)) {
|
||||
throw new Error(
|
||||
`Wan image models on Replicate require --size to be one of ${Array.from(getAllowedWanSizes(model)).join(", ")}. Received: ${args.size}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (args.n < 1 || args.n > 4) {
|
||||
throw new Error("Wan image models on Replicate support --n values from 1 to 4 in standard mode.");
|
||||
}
|
||||
|
||||
if (args.size && normalizePresetSize(args.size) === "4K" && args.referenceImages.length > 0) {
|
||||
throw new Error("Wan 2.7 Image Pro on Replicate only supports 4K for text-to-image requests without input images.");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export function buildInput(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs,
|
||||
referenceImages: string[]
|
||||
): Record<string, unknown> {
|
||||
if (isSeedreamModel(model)) {
|
||||
return buildSeedreamInput(prompt, model, args, referenceImages);
|
||||
}
|
||||
|
||||
if (isWanModel(model)) {
|
||||
return buildWanInput(prompt, model, args, referenceImages);
|
||||
}
|
||||
|
||||
// Fall back to nano-banana schema for unknown Replicate models.
|
||||
// This preserves backward compatibility; unsupported models will fail
|
||||
// at API validation time if they reject nano-banana-style fields.
|
||||
return buildNanoBananaInput(prompt, args, referenceImages);
|
||||
}
|
||||
|
||||
async function readImageAsDataUrl(p: string): Promise<string> {
|
||||
const buf = await readFile(p);
|
||||
const ext = path.extname(p).toLowerCase();
|
||||
|
|
@ -177,6 +382,8 @@ export async function generateImage(
|
|||
const apiToken = getApiToken();
|
||||
if (!apiToken) throw new Error("REPLICATE_API_TOKEN is required. Get one at https://replicate.com/account/api-tokens");
|
||||
|
||||
validateArgs(model, args);
|
||||
|
||||
const parsedModel = parseModelId(model);
|
||||
|
||||
const refDataUrls: string[] = [];
|
||||
|
|
@ -184,7 +391,7 @@ export async function generateImage(
|
|||
refDataUrls.push(await readImageAsDataUrl(refPath));
|
||||
}
|
||||
|
||||
const input = buildInput(prompt, args, refDataUrls);
|
||||
const input = buildInput(prompt, model, args, refDataUrls);
|
||||
|
||||
console.log(`Generating image with Replicate (${model})...`);
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue