Provide containerized GPT and Grok image generation with environment-based configuration.main
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cf8b6c067d
@ -0,0 +1,3 @@ |
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GROK_API_KEY=your_grok_api_key |
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GPT_API_KEY=your_gpt_api_key |
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IMAGE_API_BASE_URL=https://api.slomerex.xyz/v1 |
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# Environment and secrets |
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.env |
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.env.* |
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!.env.example |
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# Generated output |
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output/ |
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# Python |
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__pycache__/ |
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*.py[cod] |
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*$py.class |
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*.so |
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.Python |
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.pytest_cache/ |
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.mypy_cache/ |
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.ruff_cache/ |
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.coverage |
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htmlcov/ |
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# Virtual environments |
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.venv/ |
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venv/ |
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env/ |
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# Packaging |
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build/ |
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dist/ |
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*.egg-info/ |
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# IDE and OS |
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.vscode/ |
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.idea/ |
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*.iml |
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.DS_Store |
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Thumbs.db |
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|
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# Logs and local databases |
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*.log |
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*.sqlite3 |
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@ -0,0 +1,13 @@ |
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FROM python:3.12-slim |
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WORKDIR /app |
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COPY requirements.txt . |
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RUN pip install --no-cache-dir -r requirements.txt |
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COPY agent-image-t2i.py . |
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RUN mkdir -p /app/output |
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EXPOSE 8000 |
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CMD ["uvicorn", "agent-image-t2i:app", "--host", "0.0.0.0", "--port", "8000"] |
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--- |
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name: ai-image |
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description: Generate images via AI text-to-image API (GPT Image / Grok). Use when the user asks to draw, paint, generate, or create an image from a text description. |
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--- |
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# AI 绘图工具 |
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通过 FastAPI 文生图服务生成图片,供 Agent 通过 HTTP/cURL 直接调用,无需自己实现模型请求逻辑。 |
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服务端使用 OpenAI Python SDK 请求 GPT Image / Grok Image 上游接口,生成的图片保存在服务端 `output/` 目录,并通过 HTTP 返回访问地址。 |
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|
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- 服务端 API 不要求调用方提供上游 API Key;上游鉴权通过项目根目录 `.env` 配置 |
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- `.env` 不应提交到 Git,复制 `.env.example` 为 `.env` 后填写真实 Key |
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- 使用 Docker Compose 时会自动读取 `.env` 并注入容器 |
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|
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## 可用脚本 |
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| 能力 | 服务端文件 | HTTP 端点 | 模型 | |
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|------|------------|------------|------| |
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| GPT / Grok 绘图 | `agent-image-t2i.py` | `POST /images/generations` | `gpt-image-2-1K` / `gpt-image-2-2K` / `gpt-image-2-4K` / `grok-imagine-image-lite` | |
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| 健康检查 | `agent-image-t2i.py` | `GET /health` | — | |
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| 图片访问 | `agent-image-t2i.py` | `GET /output/{filename}` | — | |
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## GPT 模型说明 |
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| 模型 | 输出尺寸 | 备注 | |
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|------|----------|------| |
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| `gpt-image-2-1K` | ~1254×1254(1:1)或 1536×1024(横版) | **推荐**,线路稳定 | |
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| `gpt-image-2-2K` | 不固定 | 线路不稳定,可能 503 | |
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| `gpt-image-2-4K` | 不固定 | 线路不稳定,可能 503 | |
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> Grok 模型的 size 参数不可靠,API 返回尺寸不受控。 |
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## 使用方式 |
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先启动 FastAPI 服务: |
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```bash |
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uvicorn agent-image-t2i:app --host 0.0.0.0 --port 8000 |
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``` |
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默认服务地址为 `http://localhost:8000`。 |
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健康检查: |
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```bash |
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curl http://localhost:8000/health |
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``` |
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使用 Grok 绘图: |
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```bash |
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curl -X POST http://localhost:8000/images/generations \ |
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-H "Content-Type: application/json" \ |
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-d '{ |
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"prompt": "a cute cat", |
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"provider": "grok", |
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"size": "1024x1024", |
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"n": 1 |
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}' |
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``` |
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使用 GPT 绘图: |
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```bash |
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curl -X POST http://localhost:8000/images/generations \ |
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-H "Content-Type: application/json" \ |
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-d '{ |
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"prompt": "a cute cat", |
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"provider": "gpt", |
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"model": "gpt-image-2-1K", |
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"size": "1536x1024", |
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"n": 1 |
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}' |
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``` |
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生成结果中的 `url` 为图片访问地址,例如 `http://localhost:8000/output/{filename}`。 |
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## 调用建议 |
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- **优先用 Grok**:稳定出图,适合日常使用 |
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- **追求画质用 GPT 1K**:请求中设置 `"provider": "gpt"` |
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- **GPT 2K/4K 线路可能不稳定**:不推荐作为默认模型 |
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- **Prompt 用英文**:效果通常比中文好 |
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- 使用 Docker Compose 时,项目的 `output/` 会映射到容器的 `/app/output` |
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## 请求参数 |
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请求体为 JSON,发送到 `POST /images/generations`: |
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- `prompt`:必填,图片提示词 |
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- `provider`:可选,`grok` 或 `gpt`,默认 `grok` |
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- `model`:可选,覆盖 provider 的默认模型 |
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- `size`:可选,默认 `1024x1024` |
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- `n`:可选,生成数量,范围 `1 ~ 10`,默认 `1` |
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## 输出规范 |
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- 图片默认保存在服务端 `output/` 目录 |
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- 响应返回 `filename`、`url` 和文件大小 `bytes` |
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- 图片通过 `GET /output/{filename}` 访问 |
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- 服务启动后,响应中的相对路径 `url` 需要拼接服务地址,例如 `http://localhost:8000/output/{filename}` |
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## Prompt 技巧 |
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- 使用英文 prompt 效果更好 |
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- 描述要具体:主体 + 环境 + 光线 + 风格 + 情绪 |
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- 横版图用 `--size 1536x1024`,正方形用 `--size 1024x1024` |
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- 加上 `cinematic lighting, highly detailed, 4K` 等后缀提升质感 |
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## 配置与注意事项 |
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- 单次上游请求超时为 120 秒 |
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- 上游请求遇到网络错误或 408/429/500/502/503/504 时,最多自动重试 3 次,并使用指数退避 |
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- FastAPI 自动文档地址:`http://localhost:8000/docs` |
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@ -0,0 +1,114 @@ |
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#!/usr/bin/env python3 |
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"""通过 FastAPI 提供 GPT Image 和 Grok Image 文生图服务。""" |
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import base64 |
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import os |
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import time |
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from pathlib import Path |
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from uuid import uuid4 |
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from dotenv import load_dotenv |
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from fastapi import FastAPI, HTTPException |
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from fastapi.staticfiles import StaticFiles |
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from openai import APIConnectionError, APIStatusError, APITimeoutError, OpenAI |
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from pydantic import BaseModel, Field |
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load_dotenv() |
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API_BASE_URL = os.getenv("IMAGE_API_BASE_URL", "https://api.slomerex.xyz/v1") |
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OUTPUT_DIR = Path("output") |
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MAX_RETRIES = 3 |
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RETRYABLE_STATUS_CODES = {408, 429, 500, 502, 503, 504} |
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PROVIDERS = { |
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"grok": { |
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"api_key_env": "GROK_API_KEY", |
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"model": "grok-imagine-image-lite", |
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}, |
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"gpt": { |
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"api_key_env": "GPT_API_KEY", |
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"model": "gpt-image-2-1K", |
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}, |
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} |
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app = FastAPI(title="AI Image T2I API", version="1.0.0") |
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True) |
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app.mount("/output", StaticFiles(directory=OUTPUT_DIR), name="output") |
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class ImageGenerationRequest(BaseModel): |
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prompt: str = Field(min_length=1, description="图片提示词") |
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provider: str = Field(default="grok", pattern="^(grok|gpt)$", description="模型提供方") |
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model: str | None = Field(default=None, description="覆盖提供方默认模型") |
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size: str = Field(default="1024x1024", description="图片尺寸") |
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n: int = Field(default=1, ge=1, le=10, description="生成数量") |
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class GeneratedImage(BaseModel): |
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filename: str |
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url: str |
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bytes: int |
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class ImageGenerationResponse(BaseModel): |
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provider: str |
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model: str |
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images: list[GeneratedImage] |
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def generate_with_retry(client: OpenAI, *, model: str, prompt: str, size: str, n: int): |
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for attempt in range(1, MAX_RETRIES + 1): |
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try: |
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return client.images.generate(model=model, prompt=prompt, size=size, n=n) |
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except APIStatusError as e: |
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if e.status_code not in RETRYABLE_STATUS_CODES or attempt == MAX_RETRIES: |
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raise HTTPException(status_code=502, detail=f"上游图片服务错误: HTTP {e.status_code}") from e |
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time.sleep(2 ** (attempt - 1)) |
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except (APIConnectionError, APITimeoutError) as e: |
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if attempt == MAX_RETRIES: |
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raise HTTPException(status_code=504, detail="上游图片服务连接或请求超时") from e |
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time.sleep(2 ** (attempt - 1)) |
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@app.get("/health") |
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def health_check(): |
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return {"status": "ok"} |
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@app.post("/images/generations", response_model=ImageGenerationResponse) |
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def generate_images(request: ImageGenerationRequest): |
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config = PROVIDERS[request.provider] |
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api_key = os.getenv(config["api_key_env"]) |
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if not api_key: |
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raise HTTPException(status_code=500, detail=f"未配置环境变量 {config['api_key_env']}") |
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model = request.model or config["model"] |
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client = OpenAI(base_url=API_BASE_URL, api_key=api_key, timeout=120.0, max_retries=0) |
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response = generate_with_retry( |
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client, |
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model=model, |
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prompt=request.prompt, |
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size=request.size, |
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n=request.n, |
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) |
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images = [] |
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for item in response.data: |
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if not item.b64_json: |
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raise HTTPException(status_code=502, detail="上游图片服务未返回 Base64 图片数据") |
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try: |
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raw = base64.b64decode(item.b64_json) |
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except ValueError as e: |
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raise HTTPException(status_code=502, detail="上游图片数据格式无效") from e |
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filename = f"{model}-{uuid4().hex}.png" |
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(OUTPUT_DIR / filename).write_bytes(raw) |
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images.append(GeneratedImage(filename=filename, url=f"/output/{filename}", bytes=len(raw))) |
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return ImageGenerationResponse(provider=request.provider, model=model, images=images) |
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if __name__ == "__main__": |
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import uvicorn |
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uvicorn.run(app, host="0.0.0.0", port=8000) |
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services: |
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ai-image-t2i: |
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build: |
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context: . |
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dockerfile: Dockerfile |
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ports: |
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- "8000:8000" |
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env_file: |
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- .env |
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volumes: |
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- ./output:/app/output |
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restart: unless-stopped |
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@ -0,0 +1,191 @@ |
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# 图像模型 API 文档 |
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本文档整理 GPT Image 和 Grok Image 模型的 API 信息、调用示例、支持参数及速率限制。 |
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## 通用信息 |
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- API 基础地址:`https://api.slomerex.xyz/v1` |
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- 认证方式:`Authorization: Bearer <TOKEN>` |
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- Anthropic 格式的端点也接受 `x-api-key` 请求头。 |
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- 可在「令牌」页面生成 API Key,并按模型、分组、IP、速率等维度进行授权。 |
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- 示例中的 `<YOUR_API_KEY>` 请替换为令牌设置中的 API Key。 |
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## 模型列表 |
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| 模型 | 提供方 | 计费方式 | |
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|---|---|---| |
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| `gpt-image-2-1K` | OpenAI | 按次计费 | |
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| `gpt-image-2-2K` | OpenAI | 按次计费 | |
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| `gpt-image-2-4K` | OpenAI | 按次计费 | |
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| `grok-imagine-image-lite` | xAI | 按次计费 | |
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--- |
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## gpt-image-2-1K |
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### 调用示例 |
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```python |
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from openai import OpenAI |
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client = OpenAI( |
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base_url="https://api.slomerex.xyz/v1", |
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api_key="<YOUR_API_KEY>", |
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) |
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completion = client.chat.completions.create( |
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model="gpt-image-2-1K", |
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messages=[ |
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{"role": "user", "content": "Explain quantum entanglement in one paragraph."} |
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], |
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) |
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print(completion.choices[0].message.content) |
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``` |
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### 支持的参数 |
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| 参数 | 类型 | 默认值 / 范围 | 说明 | |
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|---|---|---|---| |
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| `prompt` | `string` | 必填 | 想要生成图像的文字描述 | |
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| `size` | `enum` | `1024x1024` | 输出图像尺寸 | |
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| `quality` | `enum` | `standard` | 生成质量预设 | |
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| `style` | `enum` | `vivid` | 画风 | |
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| `n` | `integer` | `1`,范围 `1 ~ 10` | 生成的图像数量 | |
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| `response_format` | `enum` | `url` | 图像结果的返回方式 | |
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### 速率限制 |
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| 分组 | RPM | TPM | RPD | |
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|---|---:|---:|---:| |
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| Gpt Image | 50 | — | 800 | |
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--- |
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## gpt-image-2-2K |
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### 调用示例 |
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```python |
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from openai import OpenAI |
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client = OpenAI( |
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base_url="https://api.slomerex.xyz/v1", |
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api_key="<YOUR_API_KEY>", |
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) |
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completion = client.chat.completions.create( |
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model="gpt-image-2-2K", |
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messages=[ |
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{"role": "user", "content": "Explain quantum entanglement in one paragraph."} |
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], |
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) |
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print(completion.choices[0].message.content) |
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``` |
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### 支持的参数 |
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| 参数 | 类型 | 默认值 / 范围 | 说明 | |
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|---|---|---|---| |
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| `prompt` | `string` | 必填 | 想要生成图像的文字描述 | |
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| `size` | `enum` | `1024x1024` | 输出图像尺寸 | |
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| `quality` | `enum` | `standard` | 生成质量预设 | |
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| `style` | `enum` | `vivid` | 画风 | |
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| `n` | `integer` | `1`,范围 `1 ~ 10` | 生成的图像数量 | |
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| `response_format` | `enum` | `url` | 图像结果的返回方式 | |
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|
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### 速率限制 |
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| 分组 | RPM | TPM | RPD | |
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|---|---:|---:|---:| |
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| Gpt Image | 70 | — | 1.2K | |
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--- |
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## gpt-image-2-4K |
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### 调用示例 |
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|
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```bash |
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curl https://api.slomerex.xyz/v1/chat/completions \ |
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-H "Authorization: Bearer $NEW_API_KEY" \ |
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-H "Content-Type: application/json" \ |
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-d '{ |
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"model": "gpt-image-2-4K", |
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"messages": [ |
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{ |
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"role": "user", |
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"content": "Explain quantum entanglement in one paragraph." |
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} |
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], |
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"temperature": 0.7 |
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}' |
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``` |
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|
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### 支持的参数 |
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|
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| 参数 | 类型 | 默认值 / 范围 | 说明 | |
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|---|---|---|---| |
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| `prompt` | `string` | 必填 | 想要生成图像的文字描述 | |
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| `size` | `enum` | `1024x1024` | 输出图像尺寸 | |
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| `quality` | `enum` | `standard` | 生成质量预设 | |
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| `style` | `enum` | `vivid` | 画风 | |
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| `n` | `integer` | `1`,范围 `1 ~ 10` | 生成的图像数量 | |
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| `response_format` | `enum` | `url` | 图像结果的返回方式 | |
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|
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### 速率限制 |
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|
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| 分组 | RPM | TPM | RPD | |
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|---|---:|---:|---:| |
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| Gpt Image | 60 | — | 900 | |
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|
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--- |
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|
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## grok-imagine-image-lite |
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|
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### 调用示例 |
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|
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```python |
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from openai import OpenAI |
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|
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client = OpenAI( |
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base_url="https://api.slomerex.xyz/v1", |
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api_key="<YOUR_API_KEY>", |
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) |
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|
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completion = client.chat.completions.create( |
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model="grok-imagine-image-lite", |
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messages=[ |
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{"role": "user", "content": "Explain quantum entanglement in one paragraph."} |
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], |
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) |
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|
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print(completion.choices[0].message.content) |
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``` |
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|
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### 支持的参数 |
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|
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| 参数 | 类型 | 默认值 / 范围 | 说明 | |
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|---|---|---|---| |
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| `prompt` | `string` | 必填 | 想要生成图像的文字描述 | |
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| `size` | `enum` | `1024x1024` | 输出图像尺寸 | |
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| `quality` | `enum` | `standard` | 生成质量预设 | |
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| `style` | `enum` | `vivid` | 画风 | |
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| `n` | `integer` | `1`,范围 `1 ~ 10` | 生成的图像数量 | |
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| `response_format` | `enum` | `url` | 图像结果的返回方式 | |
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|
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### 速率限制 |
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|
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| 分组 | RPM | TPM | RPD | |
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|---|---:|---:|---:| |
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| Grok | 40 | — | 700 | |
||||
|
||||
--- |
||||
|
||||
## 速率限制说明 |
||||
|
||||
- **RPM**:每分钟请求数(Requests Per Minute) |
||||
- **TPM**:每分钟 token 数(Tokens Per Minute) |
||||
- **RPD**:每日请求数(Requests Per Day) |
||||
- 限制按令牌分组生效。 |
||||
@ -0,0 +1,4 @@ |
||||
fastapi |
||||
openai |
||||
python-dotenv |
||||
uvicorn[standard] |
||||
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Reference in new issue