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17
.env.example
17
.env.example
@@ -1,8 +1,11 @@
|
||||
API_KEYS=["AIzaSyxxxxxxxxxxxxxxxxxxx","AIzaSyxxxxxxxxxxxxxxxxxxx"]
|
||||
ALLOWED_TOKENS=["sk-123456"]
|
||||
# AUTH_TOKEN=sk-123456
|
||||
MODEL_SEARCH=["gemini-2.0-flash-exp","gemini-2.0-pro-exp"]
|
||||
TOOLS_CODE_EXECUTION_ENABLED=true
|
||||
TEST_MODEL=gemini-1.5-flash
|
||||
IMAGE_MODELS=["gemini-2.0-flash-exp"]
|
||||
SEARCH_MODELS=["gemini-2.0-flash-exp","gemini-2.0-pro-exp"]
|
||||
FILTERED_MODELS=["gemini-1.0-pro-vision-latest", "gemini-pro-vision", "chat-bison-001", "text-bison-001", "embedding-gecko-001"]
|
||||
TOOLS_CODE_EXECUTION_ENABLED=false
|
||||
SHOW_SEARCH_LINK=true
|
||||
SHOW_THINKING_PROCESS=true
|
||||
BASE_URL=https://generativelanguage.googleapis.com/v1beta
|
||||
@@ -12,4 +15,14 @@ PAID_KEY=AIzaSyxxxxxxxxxxxxxxxxxxx
|
||||
CREATE_IMAGE_MODEL=imagen-3.0-generate-002
|
||||
UPLOAD_PROVIDER=smms
|
||||
SMMS_SECRET_TOKEN=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
|
||||
PICGO_API_KEY=xxxx
|
||||
CLOUDFLARE_IMGBED_URL=https://xxxxxxx.pages.dev/upload
|
||||
CLOUDFLARE_IMGBED_AUTH_CODE=xxxxxxxxx
|
||||
##########################################################################
|
||||
#########################stream_optimizer 相关配置########################
|
||||
STREAM_MIN_DELAY=0.016
|
||||
STREAM_MAX_DELAY=0.024
|
||||
STREAM_SHORT_TEXT_THRESHOLD=10
|
||||
STREAM_LONG_TEXT_THRESHOLD=50
|
||||
STREAM_CHUNK_SIZE=5
|
||||
##########################################################################
|
||||
|
||||
2
.github/workflows/docker-publish.yml
vendored
2
.github/workflows/docker-publish.yml
vendored
@@ -2,7 +2,7 @@ name: Docker Image CI
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ "main" ]
|
||||
# branches: [ "main" ]
|
||||
tags: [ 'v*.*.*' ]
|
||||
pull_request:
|
||||
branches: [ "main" ]
|
||||
|
||||
11
.github/workflows/release.yml
vendored
11
.github/workflows/release.yml
vendored
@@ -6,9 +6,10 @@ on:
|
||||
- 'v*' # 当推送以 "v" 开头的标签时触发(如 v1.0.0, v2.1.0)
|
||||
|
||||
jobs:
|
||||
release:
|
||||
update-release-draft:
|
||||
permissions:
|
||||
contents: write # 添加写入权限
|
||||
contents: write
|
||||
pull-requests: write
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
# Step 1: 检出代码库
|
||||
@@ -24,10 +25,6 @@ jobs:
|
||||
with:
|
||||
tag_name: ${{ github.ref_name }}
|
||||
release_name: ${{ github.ref_name }}
|
||||
body: |
|
||||
## Release Notes
|
||||
- 自动发布版本。
|
||||
- 请根据需求更新对应内容。
|
||||
draft: false
|
||||
prerelease: false
|
||||
|
||||
@@ -45,4 +42,4 @@ jobs:
|
||||
upload_url: ${{ steps.create_release.outputs.upload_url }}
|
||||
asset_path: ./gemini-balance.zip # 替换为你的构建文件路径
|
||||
asset_name: gemini-balance.zip # 替换为你的文件名
|
||||
asset_content_type: application/zip
|
||||
asset_content_type: application/zip
|
||||
|
||||
@@ -1,17 +1,18 @@
|
||||
FROM python:3.9-slim
|
||||
FROM python:3.10-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# 复制所需文件到容器中
|
||||
COPY ./app /app/app
|
||||
COPY ./requirements.txt /app
|
||||
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
COPY ./app /app/app
|
||||
ENV API_KEYS='["your_api_key_1"]'
|
||||
ENV ALLOWED_TOKENS='["your_token_1"]'
|
||||
ENV BASE_URL=https://generativelanguage.googleapis.com/v1beta
|
||||
ENV TOOLS_CODE_EXECUTION_ENABLED=true
|
||||
ENV MODEL_SEARCH='["gemini-2.0-flash-exp"]'
|
||||
ENV TOOLS_CODE_EXECUTION_ENABLED=false
|
||||
ENV IMAGE_MODELS='["gemini-2.0-flash-exp"]'
|
||||
ENV SEARCH_MODELS='["gemini-2.0-flash-exp","gemini-2.0-pro-exp"]'
|
||||
|
||||
# Expose port
|
||||
EXPOSE 8000
|
||||
|
||||
278
README.md
278
README.md
@@ -4,11 +4,11 @@
|
||||
|
||||
## 📝 项目简介
|
||||
|
||||
本项目是一个基于 FastAPI 框架开发的高性能、易于部署的 OpenAI 和 Gemini API 代理服务。它不仅兼容 OpenAI 的 API 接口,还支持 Google 的 Gemini 模型,为用户提供灵活的模型选择。该代理服务内置了多 API Key 轮询、负载均衡、自动重试、访问控制(Bearer Token 认证)、流式响应等功能,旨在简化 AI 应用的开发和部署流程。
|
||||
本项目是一个基于 FastAPI 框架开发的高性能、易于部署的Gemini OpenAI兼容 和 Gemini API 代理服务。它不仅兼容 OpenAI 的 API 接口,还支持 Google 的 Gemini 原生接口。该代理服务内置了多 API Key 轮询、负载均衡、自动重试、访问控制(Bearer Token 认证)、流式响应等功能,旨在简化 AI 应用的开发和部署流程。
|
||||
|
||||
**核心功能与优势:**
|
||||
|
||||
- **多模型支持**: 无缝切换 OpenAI 和 Gemini 模型。
|
||||
- **多协议支持**: 无缝切换 OpenAI兼容 和 Gemini 协议。
|
||||
- **智能 API Key 管理**: 自动轮询多个 API Key,实现负载均衡和故障转移。
|
||||
- **安全访问控制**: 使用 Bearer Token 进行身份验证,保护 API 访问。
|
||||
- **流式响应支持**: 提供实时的流式数据传输,提升用户体验。
|
||||
@@ -51,29 +51,145 @@
|
||||
|
||||
3. **配置**:
|
||||
|
||||
创建 `.env` 文件,并配置以下环境变量:
|
||||
创建 `.env` 文件,并按以下分类配置环境变量:
|
||||
|
||||
```env
|
||||
API_KEYS=["your-gemini-api-key-1", "your-gemini-api-key-2"] # 你的 Gemini API 密钥列表
|
||||
ALLOWED_TOKENS=["your-access-token-1", "your-access-token-2"] # 允许访问的 Token 列表
|
||||
BASE_URL="https://generativelanguage.googleapis.com/v1beta" # Gemini API 基础 URL, 保持默认即可
|
||||
MODEL_SEARCH=["gemini-2.0-flash-exp"] # 启用搜索功能的模型列表
|
||||
TOOLS_CODE_EXECUTION_ENABLED=false # 是否启用代码执行工具, 默认为 false
|
||||
SHOW_SEARCH_LINK=true # 是否显示搜索链接
|
||||
SHOW_THINKING_PROCESS=true # 是否显示思考过程
|
||||
AUTH_TOKEN="" # 备用token, 如果不设置, 默认为 ALLOWED_TOKENS 的第一个
|
||||
MAX_FAILURES=3 # 允许单个key失败的次数
|
||||
# 基础配置
|
||||
BASE_URL="https://generativelanguage.googleapis.com/v1beta" # Gemini API 基础 URL,默认无需修改
|
||||
MAX_FAILURES=3 # 允许单个key失败的次数,默认3次
|
||||
|
||||
# 认证与安全配置
|
||||
API_KEYS=["your-gemini-api-key-1", "your-gemini-api-key-2"] # Gemini API 密钥列表,用于负载均衡
|
||||
ALLOWED_TOKENS=["your-access-token-1", "your-access-token-2"] # 允许访问的 Token 列表
|
||||
AUTH_TOKEN="" # 超级管理员token,具有所有权限,默认使用 ALLOWED_TOKENS 的第一个
|
||||
|
||||
# 模型功能配置
|
||||
TEST_MODEL="gemini-1.5-flash" # 用于测试密钥是否可用的模型名
|
||||
SEARCH_MODELS=["gemini-2.0-flash-exp"] # 支持搜索功能的模型列表
|
||||
IMAGE_MODELS=["gemini-2.0-flash-exp"] # 支持绘图功能的模型列表
|
||||
TOOLS_CODE_EXECUTION_ENABLED=false # 是否启用代码执行工具,默认false
|
||||
SHOW_SEARCH_LINK=true # 是否在响应中显示搜索结果链接,默认true
|
||||
SHOW_THINKING_PROCESS=true # 是否显示模型思考过程,默认true
|
||||
FILTERED_MODELS=["gemini-1.0-pro-vision-latest", "gemini-pro-vision", "chat-bison-001", "text-bison-001", "embedding-gecko-001"] # 被禁用的模型列表
|
||||
|
||||
# 图片生成配置
|
||||
PAID_KEY="your-paid-api-key" # 付费版API Key,用于图片生成等高级功能
|
||||
CREATE_IMAGE_MODEL="imagen-3.0-generate-002" # 图片生成模型,默认使用imagen-3.0
|
||||
|
||||
# 图片上传配置
|
||||
UPLOAD_PROVIDER="smms" # 图片上传提供商,目前支持smms、picgo、cloudflare_imgbed
|
||||
SMMS_SECRET_TOKEN="your-smms-token" # SM.MS图床的API Token
|
||||
PICGO_API_KEY="your-picogo-apikey" # PicoGo图床的API Key 可在 `https://www.picgo.net/settings/api` 获取
|
||||
CLOUDFLARE_IMGBED_URL="https://xxxxxxx.pages.dev/upload" # CloudFlare 图床上传地址,可自行搭建:`https://github.com/MarSeventh/CloudFlare-ImgBed`
|
||||
CLOUDFLARE_IMGBED_AUTH_CODE="your-cloudflare-imgber-auth-code" # CloudFlare图床的鉴权key,可在项目后台设置,若无鉴权则可直接置空。
|
||||
|
||||
# stream_optimizer 相关配置
|
||||
STREAM_MIN_DELAY=0.016
|
||||
STREAM_MAX_DELAY=0.024
|
||||
STREAM_SHORT_TEXT_THRESHOLD=10
|
||||
STREAM_LONG_TEXT_THRESHOLD=50
|
||||
STREAM_CHUNK_SIZE=5
|
||||
```
|
||||
|
||||
- `API_KEYS`: 你的 Gemini API 密钥列表,支持多个 Key 轮询。
|
||||
- `ALLOWED_TOKENS`: 允许访问的 Token 列表,用于 API 认证。
|
||||
- `BASE_URL`: Gemini API 的基础 URL,通常不需要修改。
|
||||
- `MODEL_SEARCH`: 启用搜索功能的模型列表。
|
||||
- `TOOLS_CODE_EXECUTION_ENABLED`: 是否启用代码执行工具, 默认为 `false`。
|
||||
- `SHOW_SEARCH_LINK`: 是否显示搜索结果链接(当使用搜索模型时)。
|
||||
- `SHOW_THINKING_PROCESS`: 是否显示模型的"思考"过程(对于某些模型)。
|
||||
- `AUTH_TOKEN`: 主鉴权token(权限较大,注意保管), 如果不设置, 默认为 `ALLOWED_TOKENS` 的第一个。
|
||||
- `MAX_FAILURES`: 允许单个 API Key 失败的次数,超过此次数后该 Key 将被标记为无效。
|
||||
### 配置说明
|
||||
|
||||
#### 基础配置
|
||||
|
||||
- `BASE_URL`: Gemini API 的基础 URL
|
||||
- 默认值: `https://generativelanguage.googleapis.com/v1beta`
|
||||
- 说明: 通常无需修改,除非 API 地址发生变化
|
||||
- `MAX_FAILURES`: API Key 允许的最大失败次数
|
||||
- 默认值: `3`
|
||||
- 说明: 超过此次数后,Key 将被暂时标记为无效
|
||||
|
||||
#### 认证与安全配置
|
||||
|
||||
- `API_KEYS`: Gemini API 密钥列表
|
||||
- 格式: JSON 数组字符串
|
||||
- 用途: 支持多个 Key 轮询,实现负载均衡
|
||||
- 建议: 至少配置 2 个 Key 以保证服务可用性
|
||||
- `ALLOWED_TOKENS`: 访问令牌列表
|
||||
- 格式: JSON 数组字符串
|
||||
- 用途: 用于客户端认证
|
||||
- 安全提示: 请使用足够复杂的令牌
|
||||
- `AUTH_TOKEN`: 超级管理员令牌
|
||||
- 可选配置,留空则使用 ALLOWED_TOKENS 的第一个
|
||||
- 具有查看 API Key 状态等特权操作权限
|
||||
|
||||
#### 模型功能配置
|
||||
|
||||
- `TEST_MODEL`: 用于测试密钥可用性的模型
|
||||
- 默认值: `"gemini-1.5-flash"`
|
||||
- `SEARCH_MODELS`: 搜索功能支持的模型
|
||||
- 默认值: `["gemini-2.0-flash-exp"]`
|
||||
- 说明: 仅列表中的模型可使用搜索功能
|
||||
- `IMAGE_MODELS`: 绘图功能支持的模型
|
||||
- 默认值: `["gemini-2.0-flash-exp"]`
|
||||
- 说明: 仅列表中的模型可使用绘图功能
|
||||
- `FILTERED_MODELS`: 被禁用的模型列表
|
||||
- 默认值: `["gemini-1.0-pro-vision-latest", "gemini-pro-vision", "chat-bison-001", "text-bison-001", "embedding-gecko-001"]`
|
||||
- 说明: 列表中的模型将被禁用
|
||||
- `TOOLS_CODE_EXECUTION_ENABLED`: 代码执行功能
|
||||
- 默认值: `false`
|
||||
- 安全提示: 生产环境建议禁用
|
||||
- `SHOW_SEARCH_LINK`: 搜索结果链接显示
|
||||
- 默认值: `true`
|
||||
- 用途: 控制搜索结果中是否包含原始链接
|
||||
- `SHOW_THINKING_PROCESS`: 思考过程显示
|
||||
- 默认值: `true`
|
||||
- 用途: 显示模型的推理过程,便于调试
|
||||
|
||||
#### 图片生成配置
|
||||
|
||||
- `PAID_KEY`: 付费版 API Key
|
||||
- 用途: 用于图片生成等高级功能
|
||||
- 说明: 需要单独申请的付费版 Key
|
||||
- `CREATE_IMAGE_MODEL`: 图片生成模型
|
||||
- 默认值: `imagen-3.0-generate-002`
|
||||
- 说明: 当前支持的最新图片生成模型
|
||||
|
||||
#### 图片上传配置
|
||||
|
||||
- `UPLOAD_PROVIDER`: 图片上传服务提供商
|
||||
- 默认值: `smms`
|
||||
- 可选值: `smms`, `picgo`, `cloudflare_imgbed`
|
||||
- 说明: 用于选择图片上传的服务提供商。目前支持 SM.MS 图床, PicGo 图床, 以及 Cloudflare ImgBed。
|
||||
|
||||
- `SMMS_SECRET_TOKEN`: SM.MS API Token
|
||||
- 用途: 用于图片上传到 SM.MS 图床的身份验证。
|
||||
- 获取方式: 需要在 [SM.MS 官网](https://sm.ms/) 注册并获取。
|
||||
|
||||
- `PICGO_API_KEY`: PicGo API Key
|
||||
- 用途: 用于图片上传到 PicGo 图床的身份验证。
|
||||
- 获取方式: 可在 [PicGo 官网](https://www.picgo.net/settings/api) 的设置页面 API 选项中获取。
|
||||
|
||||
- `CLOUDFLARE_IMGBED_URL`: Cloudflare ImgBed 上传地址
|
||||
- 用途: 指定 Cloudflare ImgBed 图床的上传 API 地址。
|
||||
- 获取方式: 如果您自行搭建了 Cloudflare ImgBed 服务,请填写您的服务部署地址。参考 [Cloudflare-ImgBed 项目](https://github.com/MarSeventh/CloudFlare-ImgBed) 自行搭建。
|
||||
- 注意: URL 必须以 `https://` 开头,并指向 `/upload` 路径 ,例如 `https://cloudflare-imgbed-7b0.pages.dev/upload`。
|
||||
|
||||
- `CLOUDFLARE_IMGBED_AUTH_CODE`: Cloudflare ImgBed 鉴权 Key
|
||||
- 用途: 用于 Cloudflare ImgBed 图床的身份验证。
|
||||
- 说明: 如果您的 Cloudflare ImgBed 服务启用了鉴权,请填写鉴权 Key。若未启用鉴权,则留空即可。
|
||||
- 获取方式: 在 Cloudflare ImgBed 项目的后台设置中获取,或在搭建时自行设置。
|
||||
|
||||
#### 流式输出优化配置
|
||||
|
||||
- `STREAM_MIN_DELAY`: 最小延迟时间
|
||||
- 默认值: `0.016`(秒)
|
||||
- 说明: 长文本输出时使用的最小延迟时间,值越小输出速度越快
|
||||
- `STREAM_MAX_DELAY`: 最大延迟时间
|
||||
- 默认值: `0.024`(秒)
|
||||
- 说明: 短文本输出时使用的最大延迟时间,值越大输出速度越慢
|
||||
- `STREAM_SHORT_TEXT_THRESHOLD`: 短文本阈值
|
||||
- 默认值: `10`(字符)
|
||||
- 说明: 小于此长度的文本被视为短文本,将使用最大延迟输出
|
||||
- `STREAM_LONG_TEXT_THRESHOLD`: 长文本阈值
|
||||
- 默认值: `50`(字符)
|
||||
- 说明: 大于此长度的文本被视为长文本,将使用最小延迟并分块输出
|
||||
- `STREAM_CHUNK_SIZE`: 长文本分块大小
|
||||
- 默认值: `5`(字符)
|
||||
- 说明: 长文本分块输出时,每个块的大小
|
||||
|
||||
### ▶️ 运行
|
||||
|
||||
@@ -109,13 +225,30 @@ uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
|
||||
|
||||
所有 API 请求都需要在 Header 中添加 `Authorization` 字段,值为 `Bearer <your-token>`,其中 `<your-token>` 需要替换为你在 `.env` 文件中配置的 `ALLOWED_TOKENS` 中的一个或者 `AUTH_TOKEN`。
|
||||
|
||||
### 获取模型列表
|
||||
### API 路由
|
||||
|
||||
本服务提供两种API路由:
|
||||
|
||||
1. **OpenAI 兼容路由** (推荐)
|
||||
- 基础路径: `/v1`
|
||||
- 完全兼容OpenAI API格式
|
||||
- 支持所有Gemini模型
|
||||
|
||||
2. **Gemini 原生路由**
|
||||
- 基础路径: `/gemini/v1beta` 或 `/v1beta`
|
||||
- 遵循Google原生API格式
|
||||
- 适用于需要直接使用Gemini API的场景
|
||||
|
||||
### OpenAI兼容路由
|
||||
|
||||
#### 获取模型列表
|
||||
|
||||
- **URL**: `/v1/models`
|
||||
- **Method**: `GET`
|
||||
- **Header**: `Authorization: Bearer <your-token>`
|
||||
- **Response**: 返回支持的所有模型列表,包括最新的`gemini-2.0-flash-exp-search`等模型
|
||||
|
||||
### 聊天补全 (Chat Completions)
|
||||
#### 聊天补全 (Chat Completions)
|
||||
|
||||
- **URL**: `/v1/chat/completions`
|
||||
- **Method**: `POST`
|
||||
@@ -130,7 +263,7 @@ uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
|
||||
"content": "你好"
|
||||
}
|
||||
],
|
||||
"model": "gemini-1.5-flash-002",
|
||||
"model": "gemini-1.5-flash",
|
||||
"temperature": 0.7,
|
||||
"stream": false,
|
||||
"tools": [],
|
||||
@@ -141,11 +274,34 @@ uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
|
||||
}
|
||||
```
|
||||
|
||||
- `messages`: 消息列表,格式与 OpenAI API 相同。
|
||||
- `model`: 模型名称,例如 `gemini-1.5-flash-002`。
|
||||
- `stream`: 是否开启流式响应,`true` 或 `false`。
|
||||
- `tools`: 使用的工具列表。
|
||||
- 其他参数:与 OpenAI API 兼容的参数,如 `temperature`, `max_tokens` 等。
|
||||
- `messages`: 消息列表,格式与 OpenAI API 相同
|
||||
- `model`: 模型名称,支持所有Gemini模型,包括:
|
||||
- `gemini-1.5-flash`: 快速响应模型
|
||||
- `gemini-2.0-flash-exp`: 实验性快速响应模型
|
||||
- `gemini-2.0-flash-exp-search`: 支持搜索功能的实验性模型
|
||||
- `stream`: 是否开启流式响应,`true` 或 `false`
|
||||
- `tools`: 使用的工具列表
|
||||
- 其他参数:与 OpenAI API 兼容的参数,如 `temperature`, `max_tokens` 等
|
||||
|
||||
### Gemini原生路由
|
||||
|
||||
#### 获取模型列表
|
||||
|
||||
- **URL**: `/gemini/v1beta/models` 或 `/v1beta/models`
|
||||
- **Method**: `GET`
|
||||
- **Header**: `Authorization: Bearer <your-token>`
|
||||
|
||||
#### 生成内容
|
||||
|
||||
- **URL**: `/gemini/v1beta/models/{model_name}:generateContent`
|
||||
- **Method**: `POST`
|
||||
- **Header**: `Authorization: Bearer <your-token>`
|
||||
|
||||
#### 流式生成内容
|
||||
|
||||
- **URL**: `/gemini/v1beta/models/{model_name}:streamGenerateContent`
|
||||
- **Method**: `POST`
|
||||
- **Header**: `Authorization: Bearer <your-token>`
|
||||
|
||||
### 获取词向量 (Embeddings)
|
||||
|
||||
@@ -169,12 +325,47 @@ uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
|
||||
- **URL**: `/health`
|
||||
- **Method**: `GET`
|
||||
|
||||
### 获取 API Key 列表
|
||||
### Web界面功能
|
||||
|
||||
#### 验证页面 (auth.html)
|
||||
|
||||
- **URL**: `/auth`
|
||||
- **说明**: 提供了一个简洁的Web界面用于验证访问令牌
|
||||
- **功能特点**:
|
||||
- 现代化的渐变背景设计
|
||||
- 响应式布局,完美支持移动端
|
||||
- 毛玻璃效果的卡片设计
|
||||
- 优雅的动画效果(淡入、滑动、悬浮)
|
||||
- 安全的令牌验证机制
|
||||
- 清晰的错误提示功能
|
||||
- PWA支持,可安装为本地应用
|
||||
- 底部版权信息和GitHub链接
|
||||
- 支持暗色主题适配
|
||||
|
||||
#### API密钥状态管理 (keys_status.html)
|
||||
|
||||
- **URL**: `/v1/keys/list`
|
||||
- **Method**: `GET`
|
||||
- **Header**: `Authorization: Bearer <your-auth-token>`
|
||||
- **说明**: 只有使用 `AUTH_TOKEN` 才能访问此接口, 用于获取有效和无效的 API Key 列表。
|
||||
- **功能特点**:
|
||||
- 只有使用 `AUTH_TOKEN` 才能访问此接口
|
||||
- 分类展示API密钥状态(有效/无效)
|
||||
- 可折叠的密钥列表分组
|
||||
- 每个密钥显示:
|
||||
- 状态标识(有效/无效)
|
||||
- 密钥内容
|
||||
- 失败次数统计
|
||||
- 高级功能:
|
||||
- 一键复制单个密钥
|
||||
- 批量复制分组密钥(JSON格式)
|
||||
- 实时刷新功能
|
||||
- 回到顶部/底部快捷按钮
|
||||
- 界面特性:
|
||||
- 响应式设计,适配各种屏幕
|
||||
- 优雅的动画效果
|
||||
- 操作反馈(复制成功提示)
|
||||
- PWA支持
|
||||
- 暗色主题适配
|
||||
|
||||
### 图片生成 (Image Generation)
|
||||
|
||||
@@ -186,12 +377,34 @@ uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
|
||||
```json
|
||||
{
|
||||
"model": "dall-e-3",
|
||||
"prompt": "汉服美女",
|
||||
"prompt": "{n:2} {ratio:16:9} 汉服美女",
|
||||
"n": 1,
|
||||
"size": "1024x1024"
|
||||
}
|
||||
```
|
||||
|
||||
**Prompt参数说明:**
|
||||
|
||||
prompt支持通过特殊标记来控制生成参数:
|
||||
|
||||
1. 图片数量控制:
|
||||
- 格式: `{n:数量}`
|
||||
- 示例: `{n:2} 一只可爱的猫` - 生成2张图片
|
||||
- 取值范围: 1-4
|
||||
- 说明: 如果在prompt中指定了n,将覆盖请求body中的n参数
|
||||
|
||||
2. 图片比例控制:
|
||||
- 格式: `{ratio:宽:高}`
|
||||
- 示例: `{ratio:16:9} 一片森林` - 生成16:9比例的图片
|
||||
- 支持的比例: "1:1"、"3:4"、"4:3"、"9:16"、"16:9"
|
||||
- 说明: 如果指定了size参数,将优先使用size对应的比例
|
||||
|
||||
3. 参数组合:
|
||||
- 示例: `{n:2} {ratio:16:9} 一片美丽的森林` - 生成2张16:9比例的图片
|
||||
- 说明: 这些参数标记会自动从prompt中移除,不会影响实际的图片生成提示词
|
||||
|
||||
> 注意:n的取值范围[1,4], ratio取值范围"1:1"、"3:4"、"4:3"、"9:16" 和 "16:9"
|
||||
|
||||
## 📚 代码结构
|
||||
|
||||
```plaintext
|
||||
@@ -267,6 +480,7 @@ A: 请检查以下几点:
|
||||
A: 在请求的 Body 中,将 `stream` 参数设置为 `true` 即可。
|
||||
|
||||
**Q: 如何启用代码执行工具?**
|
||||
|
||||
A: 在 `.env` 文件的 `TOOLS_CODE_EXECUTION_ENABLED` 变量中, 设置为 `true` 即可。
|
||||
|
||||
## 📄 许可证
|
||||
|
||||
@@ -1,95 +0,0 @@
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logger import get_gemini_logger
|
||||
from app.core.security import SecurityService
|
||||
from app.schemas.gemini_models import GeminiRequest
|
||||
from app.services.gemini_chat_service import GeminiChatService
|
||||
from app.services.key_manager import KeyManager
|
||||
from app.services.model_service import ModelService
|
||||
from app.services.chat.retry_handler import RetryHandler
|
||||
|
||||
router = APIRouter(prefix="/gemini/v1beta")
|
||||
router_v1beta = APIRouter(prefix="/v1beta")
|
||||
logger = get_gemini_logger()
|
||||
|
||||
# 初始化服务
|
||||
security_service = SecurityService(settings.ALLOWED_TOKENS, settings.AUTH_TOKEN)
|
||||
key_manager = KeyManager(settings.API_KEYS)
|
||||
model_service = ModelService(settings.MODEL_SEARCH)
|
||||
|
||||
|
||||
@router.get("/models")
|
||||
@router_v1beta.get("/models")
|
||||
async def list_models(_=Depends(security_service.verify_key)):
|
||||
"""获取可用的Gemini模型列表"""
|
||||
logger.info("-" * 50 + "list_gemini_models" + "-" * 50)
|
||||
logger.info("Handling Gemini models list request")
|
||||
api_key = await key_manager.get_next_working_key()
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
models_json = model_service.get_gemini_models(api_key)
|
||||
models_json["models"].append({"name": "models/gemini-2.0-flash-exp-search", "version": "2.0",
|
||||
"displayName": "Gemini 2.0 Flash Search Experimental",
|
||||
"description": "Gemini 2.0 Flash Search Experimental", "inputTokenLimit": 32767,
|
||||
"outputTokenLimit": 8192,
|
||||
"supportedGenerationMethods": ["generateContent", "countTokens"], "temperature": 1,
|
||||
"topP": 0.95, "topK": 64, "maxTemperature": 2})
|
||||
return models_json
|
||||
|
||||
|
||||
@router.post("/models/{model_name}:generateContent")
|
||||
@router_v1beta.post("/models/{model_name}:generateContent")
|
||||
@RetryHandler(max_retries=3, key_manager=key_manager, key_arg="api_key")
|
||||
async def generate_content(
|
||||
model_name: str,
|
||||
request: GeminiRequest,
|
||||
_=Depends(security_service.verify_goog_api_key),
|
||||
api_key: str = Depends(key_manager.get_next_working_key),
|
||||
):
|
||||
chat_service = GeminiChatService(settings.BASE_URL, key_manager)
|
||||
"""非流式生成内容"""
|
||||
logger.info("-" * 50 + "gemini_generate_content" + "-" * 50)
|
||||
logger.info(f"Handling Gemini content generation request for model: {model_name}")
|
||||
logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
try:
|
||||
response = chat_service.generate_content(
|
||||
model=model_name,
|
||||
request=request,
|
||||
api_key=api_key
|
||||
)
|
||||
return response
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Chat completion failed after retries: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Chat completion failed") from e
|
||||
|
||||
|
||||
@router.post("/models/{model_name}:streamGenerateContent")
|
||||
@router_v1beta.post("/models/{model_name}:streamGenerateContent")
|
||||
@RetryHandler(max_retries=3, key_manager=key_manager, key_arg="api_key")
|
||||
async def stream_generate_content(
|
||||
model_name: str,
|
||||
request: GeminiRequest,
|
||||
_=Depends(security_service.verify_goog_api_key),
|
||||
api_key: str = Depends(key_manager.get_next_working_key),
|
||||
):
|
||||
chat_service = GeminiChatService(settings.BASE_URL, key_manager)
|
||||
"""流式生成内容"""
|
||||
logger.info("-" * 50 + "gemini_stream_generate_content" + "-" * 50)
|
||||
logger.info(f"Handling Gemini streaming content generation for model: {model_name}")
|
||||
logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
try:
|
||||
response_stream = chat_service.stream_generate_content(
|
||||
model=model_name,
|
||||
request=request,
|
||||
api_key=api_key
|
||||
)
|
||||
return StreamingResponse(response_stream, media_type="text/event-stream")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Streaming request failed: {str(e)}")
|
||||
61
app/config/config.py
Normal file
61
app/config/config.py
Normal file
@@ -0,0 +1,61 @@
|
||||
"""
|
||||
应用程序配置模块
|
||||
"""
|
||||
from typing import List
|
||||
from pydantic_settings import BaseSettings
|
||||
|
||||
from app.core.constants import API_VERSION, DEFAULT_MODEL
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
"""应用程序配置"""
|
||||
# API相关配置
|
||||
API_KEYS: List[str]
|
||||
ALLOWED_TOKENS: List[str]
|
||||
BASE_URL: str = f"https://generativelanguage.googleapis.com/{API_VERSION}"
|
||||
AUTH_TOKEN: str = ""
|
||||
MAX_FAILURES: int = 3
|
||||
TEST_MODEL: str = DEFAULT_MODEL
|
||||
|
||||
# 模型相关配置
|
||||
SEARCH_MODELS: List[str] = ["gemini-2.0-flash-exp"]
|
||||
IMAGE_MODELS: List[str] = ["gemini-2.0-flash-exp"]
|
||||
FILTERED_MODELS: List[str] = [
|
||||
"gemini-1.0-pro-vision-latest",
|
||||
"gemini-pro-vision",
|
||||
"chat-bison-001",
|
||||
"text-bison-001",
|
||||
"embedding-gecko-001"
|
||||
]
|
||||
TOOLS_CODE_EXECUTION_ENABLED: bool = False
|
||||
SHOW_SEARCH_LINK: bool = True
|
||||
SHOW_THINKING_PROCESS: bool = True
|
||||
|
||||
# 图像生成相关配置
|
||||
PAID_KEY: str = ""
|
||||
CREATE_IMAGE_MODEL: str = "imagen-3.0-generate-002"
|
||||
UPLOAD_PROVIDER: str = "smms"
|
||||
SMMS_SECRET_TOKEN: str = ""
|
||||
PICGO_API_KEY: str = ""
|
||||
CLOUDFLARE_IMGBED_URL: str = ""
|
||||
CLOUDFLARE_IMGBED_AUTH_CODE: str = ""
|
||||
|
||||
# 流式输出优化器配置
|
||||
STREAM_MIN_DELAY: float = 0.016
|
||||
STREAM_MAX_DELAY: float = 0.024
|
||||
STREAM_SHORT_TEXT_THRESHOLD: int = 10
|
||||
STREAM_LONG_TEXT_THRESHOLD: int = 50
|
||||
STREAM_CHUNK_SIZE: int = 5
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
# 设置默认AUTH_TOKEN(如果未提供)
|
||||
if not self.AUTH_TOKEN and self.ALLOWED_TOKENS:
|
||||
self.AUTH_TOKEN = self.ALLOWED_TOKENS[0]
|
||||
|
||||
class Config:
|
||||
env_file = ".env"
|
||||
|
||||
|
||||
# 创建全局配置实例
|
||||
settings = Settings()
|
||||
71
app/core/application.py
Normal file
71
app/core/application.py
Normal file
@@ -0,0 +1,71 @@
|
||||
"""
|
||||
应用程序工厂模块,负责创建和配置FastAPI应用程序实例
|
||||
"""
|
||||
from contextlib import asynccontextmanager
|
||||
from fastapi import FastAPI
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
|
||||
from app.config.config import settings
|
||||
from app.logger.logger import get_main_logger
|
||||
from app.middleware.middleware import setup_middlewares
|
||||
from app.exception.exceptions import setup_exception_handlers
|
||||
from app.router.routers import setup_routers
|
||||
from app.service.key.key_manager import get_key_manager_instance
|
||||
from app.core.initialization import initialize_app
|
||||
|
||||
logger = get_main_logger()
|
||||
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
"""
|
||||
应用程序生命周期管理器
|
||||
|
||||
Args:
|
||||
app: FastAPI应用实例
|
||||
"""
|
||||
# 启动事件
|
||||
logger.info("Application starting up...")
|
||||
try:
|
||||
# 初始化KeyManager
|
||||
await get_key_manager_instance(settings.API_KEYS)
|
||||
logger.info("KeyManager initialized successfully")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to initialize KeyManager: {str(e)}")
|
||||
raise
|
||||
|
||||
yield # 应用程序运行期间
|
||||
|
||||
# 关闭事件
|
||||
logger.info("Application shutting down...")
|
||||
|
||||
def create_app() -> FastAPI:
|
||||
"""
|
||||
创建并配置FastAPI应用程序实例
|
||||
|
||||
Returns:
|
||||
FastAPI: 配置好的FastAPI应用程序实例
|
||||
"""
|
||||
# 初始化应用程序
|
||||
initialize_app()
|
||||
|
||||
# 创建FastAPI应用
|
||||
app = FastAPI(
|
||||
title="Gemini Balance API",
|
||||
description="Gemini API代理服务,支持负载均衡和密钥管理",
|
||||
version="1.0.0",
|
||||
lifespan=lifespan
|
||||
)
|
||||
|
||||
# 配置静态文件
|
||||
app.mount("/static", StaticFiles(directory="app/static"), name="static")
|
||||
|
||||
# 配置中间件
|
||||
setup_middlewares(app)
|
||||
|
||||
# 配置异常处理器
|
||||
setup_exception_handlers(app)
|
||||
|
||||
# 配置路由
|
||||
setup_routers(app)
|
||||
|
||||
return app
|
||||
@@ -1,29 +0,0 @@
|
||||
from pydantic_settings import BaseSettings
|
||||
from typing import List
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
API_KEYS: List[str]
|
||||
ALLOWED_TOKENS: List[str]
|
||||
BASE_URL: str = "https://generativelanguage.googleapis.com/v1beta"
|
||||
MODEL_SEARCH: List[str] = ["gemini-2.0-flash-exp"]
|
||||
TOOLS_CODE_EXECUTION_ENABLED: bool = False
|
||||
SHOW_SEARCH_LINK: bool = True
|
||||
SHOW_THINKING_PROCESS: bool = True
|
||||
AUTH_TOKEN: str = ""
|
||||
MAX_FAILURES: int = 3
|
||||
PAID_KEY: str = ""
|
||||
CREATE_IMAGE_MODEL: str = ""
|
||||
UPLOAD_PROVIDER: str = "smms"
|
||||
SMMS_SECRET_TOKEN: str = ""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
if not self.AUTH_TOKEN:
|
||||
self.AUTH_TOKEN = self.ALLOWED_TOKENS[0] if self.ALLOWED_TOKENS else ""
|
||||
|
||||
class Config:
|
||||
env_file = ".env"
|
||||
|
||||
|
||||
settings = Settings()
|
||||
32
app/core/constants.py
Normal file
32
app/core/constants.py
Normal file
@@ -0,0 +1,32 @@
|
||||
"""
|
||||
常量定义模块
|
||||
"""
|
||||
|
||||
# API相关常量
|
||||
API_VERSION = "v1beta"
|
||||
DEFAULT_TIMEOUT = 300 # 秒
|
||||
|
||||
# 模型相关常量
|
||||
SUPPORTED_ROLES = ["user", "model", "system"]
|
||||
DEFAULT_MODEL = "gemini-1.5-flash"
|
||||
DEFAULT_TEMPERATURE = 0.7
|
||||
DEFAULT_MAX_TOKENS = 8192
|
||||
DEFAULT_TOP_P = 0.9
|
||||
DEFAULT_TOP_K = 40
|
||||
|
||||
# 图像生成相关常量
|
||||
VALID_IMAGE_RATIOS = ["1:1", "3:4", "4:3", "9:16", "16:9"]
|
||||
|
||||
# 上传提供商
|
||||
UPLOAD_PROVIDERS = ["smms", "picgo", "cloudflare_imgbed"]
|
||||
|
||||
# 流式输出相关常量
|
||||
DEFAULT_STREAM_MIN_DELAY = 0.016
|
||||
DEFAULT_STREAM_MAX_DELAY = 0.024
|
||||
DEFAULT_STREAM_SHORT_TEXT_THRESHOLD = 10
|
||||
DEFAULT_STREAM_LONG_TEXT_THRESHOLD = 50
|
||||
DEFAULT_STREAM_CHUNK_SIZE = 5
|
||||
|
||||
# 正则表达式模式
|
||||
IMAGE_URL_PATTERN = r'!\[(.*?)\]\((.*?)\)'
|
||||
DATA_URL_PATTERN = r'data:([^;]+);base64,(.+)'
|
||||
39
app/core/initialization.py
Normal file
39
app/core/initialization.py
Normal file
@@ -0,0 +1,39 @@
|
||||
"""
|
||||
应用程序初始化模块
|
||||
"""
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from typing import List
|
||||
|
||||
logger = logging.getLogger("initialization")
|
||||
|
||||
|
||||
def ensure_directories_exist(directories: List[str]) -> None:
|
||||
"""
|
||||
确保指定的目录存在,如果不存在则创建
|
||||
|
||||
Args:
|
||||
directories: 要确保存在的目录列表
|
||||
"""
|
||||
for directory in directories:
|
||||
try:
|
||||
Path(directory).mkdir(parents=True, exist_ok=True)
|
||||
logger.info(f"Ensured directory exists: {directory}")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create directory {directory}: {str(e)}")
|
||||
|
||||
|
||||
def initialize_app() -> None:
|
||||
"""
|
||||
初始化应用程序,确保所需的目录和文件都存在
|
||||
"""
|
||||
# 确保必要的目录存在
|
||||
required_directories = [
|
||||
"app/static/css",
|
||||
"app/static/js",
|
||||
"app/static/icons",
|
||||
"app/templates",
|
||||
]
|
||||
|
||||
ensure_directories_exist(required_directories)
|
||||
logger.info("Application initialization completed")
|
||||
@@ -1,9 +1,12 @@
|
||||
from fastapi import HTTPException, Header
|
||||
from typing import Optional
|
||||
from app.core.logger import get_security_logger
|
||||
from app.logger.logger import get_security_logger
|
||||
from app.config.config import settings
|
||||
|
||||
logger = get_security_logger()
|
||||
|
||||
def verify_auth_token(token: str) -> bool:
|
||||
return token == settings.AUTH_TOKEN
|
||||
|
||||
class SecurityService:
|
||||
def __init__(self, allowed_tokens: list, auth_token: str):
|
||||
|
||||
@@ -1,163 +0,0 @@
|
||||
import requests
|
||||
from app.schemas.image_models import ImageMetadata, ImageUploader, UploadResponse
|
||||
from enum import Enum
|
||||
from typing import Optional, Any
|
||||
|
||||
class UploadErrorType(Enum):
|
||||
"""上传错误类型枚举"""
|
||||
NETWORK_ERROR = "network_error" # 网络请求错误
|
||||
AUTH_ERROR = "auth_error" # 认证错误
|
||||
INVALID_FILE = "invalid_file" # 无效文件
|
||||
SERVER_ERROR = "server_error" # 服务器错误
|
||||
PARSE_ERROR = "parse_error" # 响应解析错误
|
||||
UNKNOWN = "unknown" # 未知错误
|
||||
|
||||
|
||||
class UploadError(Exception):
|
||||
"""图片上传错误异常类"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
message: str,
|
||||
error_type: UploadErrorType = UploadErrorType.UNKNOWN,
|
||||
status_code: Optional[int] = None,
|
||||
details: Optional[dict] = None,
|
||||
original_error: Optional[Exception] = None
|
||||
):
|
||||
"""
|
||||
初始化上传错误异常
|
||||
|
||||
Args:
|
||||
message: 错误消息
|
||||
error_type: 错误类型
|
||||
status_code: HTTP状态码
|
||||
details: 详细错误信息
|
||||
original_error: 原始异常
|
||||
"""
|
||||
self.message = message
|
||||
self.error_type = error_type
|
||||
self.status_code = status_code
|
||||
self.details = details or {}
|
||||
self.original_error = original_error
|
||||
|
||||
# 构建完整错误信息
|
||||
full_message = f"[{error_type.value}] {message}"
|
||||
if status_code:
|
||||
full_message = f"{full_message} (Status: {status_code})"
|
||||
if details:
|
||||
full_message = f"{full_message} - Details: {details}"
|
||||
|
||||
super().__init__(full_message)
|
||||
|
||||
@classmethod
|
||||
def from_response(cls, response: Any, message: Optional[str] = None) -> "UploadError":
|
||||
"""
|
||||
从HTTP响应创建错误实例
|
||||
|
||||
Args:
|
||||
response: HTTP响应对象
|
||||
message: 自定义错误消息
|
||||
"""
|
||||
try:
|
||||
error_data = response.json()
|
||||
details = error_data.get("data", {})
|
||||
return cls(
|
||||
message=message or error_data.get("message", "Unknown error"),
|
||||
error_type=UploadErrorType.SERVER_ERROR,
|
||||
status_code=response.status_code,
|
||||
details=details
|
||||
)
|
||||
except Exception:
|
||||
return cls(
|
||||
message=message or "Failed to parse error response",
|
||||
error_type=UploadErrorType.PARSE_ERROR,
|
||||
status_code=response.status_code
|
||||
)
|
||||
|
||||
|
||||
class SmMsUploader(ImageUploader):
|
||||
API_URL = "https://sm.ms/api/v2/upload"
|
||||
|
||||
def __init__(self, api_key: str):
|
||||
self.api_key = api_key
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
try:
|
||||
# 准备请求头
|
||||
headers = {
|
||||
"Authorization": f"Basic {self.api_key}"
|
||||
}
|
||||
|
||||
# 准备文件数据
|
||||
files = {
|
||||
"smfile": (filename, file, "image/png")
|
||||
}
|
||||
|
||||
# 发送请求
|
||||
response = requests.post(
|
||||
self.API_URL,
|
||||
headers=headers,
|
||||
files=files
|
||||
)
|
||||
|
||||
# 检查响应状态
|
||||
response.raise_for_status()
|
||||
|
||||
# 解析响应
|
||||
result = response.json()
|
||||
|
||||
# 验证上传是否成功
|
||||
if not result.get("success"):
|
||||
raise UploadError(result.get("message", "Upload failed"))
|
||||
|
||||
# 转换为统一格式
|
||||
data = result["data"]
|
||||
image_metadata = ImageMetadata(
|
||||
width=data["width"],
|
||||
height=data["height"],
|
||||
filename=data["filename"],
|
||||
size=data["size"],
|
||||
url=data["url"],
|
||||
delete_url=data["delete"]
|
||||
)
|
||||
|
||||
return UploadResponse(
|
||||
success=True,
|
||||
code="success",
|
||||
message="Upload success",
|
||||
data=image_metadata
|
||||
)
|
||||
|
||||
except requests.RequestException as e:
|
||||
# 处理网络请求相关错误
|
||||
raise UploadError(f"Upload request failed: {str(e)}")
|
||||
except (KeyError, ValueError) as e:
|
||||
# 处理响应解析错误
|
||||
raise UploadError(f"Invalid response format: {str(e)}")
|
||||
except Exception as e:
|
||||
# 处理其他未预期的错误
|
||||
raise UploadError(f"Upload failed: {str(e)}")
|
||||
|
||||
|
||||
class QiniuUploader(ImageUploader):
|
||||
def __init__(self, access_key: str, secret_key: str):
|
||||
self.access_key = access_key
|
||||
self.secret_key = secret_key
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
# 实现七牛云的具体上传逻辑
|
||||
pass
|
||||
|
||||
|
||||
class ImageUploaderFactory:
|
||||
@staticmethod
|
||||
def create(provider: str, **credentials) -> ImageUploader:
|
||||
if provider == "smms":
|
||||
return SmMsUploader(credentials["api_key"])
|
||||
elif provider == "qiniu":
|
||||
return QiniuUploader(
|
||||
credentials["access_key"],
|
||||
credentials["secret_key"]
|
||||
)
|
||||
raise ValueError(f"Unknown provider: {provider}")
|
||||
|
||||
@@ -33,7 +33,7 @@ class GeminiContent(BaseModel):
|
||||
|
||||
|
||||
class GeminiRequest(BaseModel):
|
||||
contents: List[GeminiContent]
|
||||
contents: List[GeminiContent] = []
|
||||
tools: Optional[List[Dict[str, Any]]] = []
|
||||
safetySettings: Optional[List[SafetySetting]] = None
|
||||
generationConfig: Optional[GenerationConfig] = None
|
||||
@@ -1,17 +1,19 @@
|
||||
from pydantic import BaseModel
|
||||
from typing import List, Optional, Union
|
||||
|
||||
from app.core.constants import DEFAULT_MAX_TOKENS, DEFAULT_MODEL, DEFAULT_TEMPERATURE, DEFAULT_TOP_K, DEFAULT_TOP_P
|
||||
|
||||
|
||||
class ChatRequest(BaseModel):
|
||||
messages: List[dict]
|
||||
model: str = "gemini-1.5-flash-002"
|
||||
temperature: Optional[float] = 0.7
|
||||
model: str = DEFAULT_MODEL
|
||||
temperature: Optional[float] = DEFAULT_TEMPERATURE
|
||||
stream: Optional[bool] = False
|
||||
tools: Optional[List[dict]] = []
|
||||
max_tokens: Optional[int] = 8192
|
||||
max_tokens: Optional[int] = DEFAULT_MAX_TOKENS
|
||||
top_p: Optional[float] = DEFAULT_TOP_P
|
||||
top_k: Optional[int] = DEFAULT_TOP_K
|
||||
stop: Optional[List[str]] = []
|
||||
top_p: Optional[float] = 0.9
|
||||
top_k: Optional[int] = 40
|
||||
|
||||
|
||||
class EmbeddingRequest(BaseModel):
|
||||
@@ -27,4 +29,4 @@ class ImageGenerationRequest(BaseModel):
|
||||
size: Optional[str] = "1024x1024"
|
||||
quality: Optional[str] = ""
|
||||
style: Optional[str] = ""
|
||||
response_format: Optional[str] = "b64_json"
|
||||
response_format: Optional[str] = "url"
|
||||
133
app/exception/exceptions.py
Normal file
133
app/exception/exceptions.py
Normal file
@@ -0,0 +1,133 @@
|
||||
"""
|
||||
异常处理模块,定义应用程序中使用的自定义异常和异常处理器
|
||||
"""
|
||||
from fastapi import Request, FastAPI
|
||||
from fastapi.responses import JSONResponse
|
||||
from fastapi.exceptions import RequestValidationError
|
||||
from starlette.exceptions import HTTPException as StarletteHTTPException
|
||||
|
||||
from app.logger.logger import get_main_logger
|
||||
|
||||
logger = get_main_logger()
|
||||
|
||||
|
||||
class APIError(Exception):
|
||||
"""API错误基类"""
|
||||
def __init__(self, status_code: int, detail: str, error_code: str = None):
|
||||
self.status_code = status_code
|
||||
self.detail = detail
|
||||
self.error_code = error_code or "api_error"
|
||||
super().__init__(self.detail)
|
||||
|
||||
|
||||
class AuthenticationError(APIError):
|
||||
"""认证错误"""
|
||||
def __init__(self, detail: str = "Authentication failed"):
|
||||
super().__init__(status_code=401, detail=detail, error_code="authentication_error")
|
||||
|
||||
|
||||
class AuthorizationError(APIError):
|
||||
"""授权错误"""
|
||||
def __init__(self, detail: str = "Not authorized to access this resource"):
|
||||
super().__init__(status_code=403, detail=detail, error_code="authorization_error")
|
||||
|
||||
|
||||
class ResourceNotFoundError(APIError):
|
||||
"""资源未找到错误"""
|
||||
def __init__(self, detail: str = "Resource not found"):
|
||||
super().__init__(status_code=404, detail=detail, error_code="resource_not_found")
|
||||
|
||||
|
||||
class ModelNotSupportedError(APIError):
|
||||
"""模型不支持错误"""
|
||||
def __init__(self, model: str):
|
||||
super().__init__(
|
||||
status_code=400,
|
||||
detail=f"Model {model} is not supported",
|
||||
error_code="model_not_supported"
|
||||
)
|
||||
|
||||
|
||||
class APIKeyError(APIError):
|
||||
"""API密钥错误"""
|
||||
def __init__(self, detail: str = "Invalid or expired API key"):
|
||||
super().__init__(status_code=401, detail=detail, error_code="api_key_error")
|
||||
|
||||
|
||||
class ServiceUnavailableError(APIError):
|
||||
"""服务不可用错误"""
|
||||
def __init__(self, detail: str = "Service temporarily unavailable"):
|
||||
super().__init__(status_code=503, detail=detail, error_code="service_unavailable")
|
||||
|
||||
|
||||
def setup_exception_handlers(app: FastAPI) -> None:
|
||||
"""
|
||||
设置应用程序的异常处理器
|
||||
|
||||
Args:
|
||||
app: FastAPI应用程序实例
|
||||
"""
|
||||
@app.exception_handler(APIError)
|
||||
async def api_error_handler(request: Request, exc: APIError):
|
||||
"""处理API错误"""
|
||||
logger.error(f"API Error: {exc.detail} (Code: {exc.error_code})")
|
||||
return JSONResponse(
|
||||
status_code=exc.status_code,
|
||||
content={
|
||||
"error": {
|
||||
"code": exc.error_code,
|
||||
"message": exc.detail
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
@app.exception_handler(StarletteHTTPException)
|
||||
async def http_exception_handler(request: Request, exc: StarletteHTTPException):
|
||||
"""处理HTTP异常"""
|
||||
logger.error(f"HTTP Exception: {exc.detail} (Status: {exc.status_code})")
|
||||
return JSONResponse(
|
||||
status_code=exc.status_code,
|
||||
content={
|
||||
"error": {
|
||||
"code": "http_error",
|
||||
"message": exc.detail
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
@app.exception_handler(RequestValidationError)
|
||||
async def validation_exception_handler(request: Request, exc: RequestValidationError):
|
||||
"""处理请求验证错误"""
|
||||
error_details = []
|
||||
for error in exc.errors():
|
||||
error_details.append({
|
||||
"loc": error["loc"],
|
||||
"msg": error["msg"],
|
||||
"type": error["type"]
|
||||
})
|
||||
|
||||
logger.error(f"Validation Error: {error_details}")
|
||||
return JSONResponse(
|
||||
status_code=422,
|
||||
content={
|
||||
"error": {
|
||||
"code": "validation_error",
|
||||
"message": "Request validation failed",
|
||||
"details": error_details
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
@app.exception_handler(Exception)
|
||||
async def general_exception_handler(request: Request, exc: Exception):
|
||||
"""处理通用异常"""
|
||||
logger.exception(f"Unhandled Exception: {str(exc)}")
|
||||
return JSONResponse(
|
||||
status_code=500,
|
||||
content={
|
||||
"error": {
|
||||
"code": "internal_server_error",
|
||||
"message": "An unexpected error occurred"
|
||||
}
|
||||
}
|
||||
)
|
||||
164
app/handler/message_converter.py
Normal file
164
app/handler/message_converter.py
Normal file
@@ -0,0 +1,164 @@
|
||||
# app/services/chat/message_converter.py
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
import re
|
||||
from typing import Any, Dict, List, Optional
|
||||
import requests
|
||||
import base64
|
||||
|
||||
from app.core.constants import DATA_URL_PATTERN, IMAGE_URL_PATTERN, SUPPORTED_ROLES
|
||||
|
||||
|
||||
class MessageConverter(ABC):
|
||||
"""消息转换器基类"""
|
||||
|
||||
@abstractmethod
|
||||
def convert(self, messages: List[Dict[str, Any]]) -> tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]:
|
||||
pass
|
||||
|
||||
def _get_mime_type_and_data(base64_string):
|
||||
"""
|
||||
从 base64 字符串中提取 MIME 类型和数据。
|
||||
|
||||
参数:
|
||||
base64_string (str): 可能包含 MIME 类型信息的 base64 字符串
|
||||
|
||||
返回:
|
||||
tuple: (mime_type, encoded_data)
|
||||
"""
|
||||
# 检查字符串是否以 "data:" 格式开始
|
||||
if base64_string.startswith('data:'):
|
||||
# 提取 MIME 类型和数据
|
||||
pattern = DATA_URL_PATTERN
|
||||
match = re.match(pattern, base64_string)
|
||||
if match:
|
||||
mime_type = "image/jpeg" if match.group(1) == "image/jpg" else match.group(1)
|
||||
encoded_data = match.group(2)
|
||||
return mime_type, encoded_data
|
||||
|
||||
# 如果不是预期格式,假定它只是数据部分
|
||||
return None, base64_string
|
||||
|
||||
def _convert_image(image_url: str) -> Dict[str, Any]:
|
||||
if image_url.startswith("data:image"):
|
||||
mime_type, encoded_data = _get_mime_type_and_data(image_url)
|
||||
return {
|
||||
"inline_data": {
|
||||
"mime_type": mime_type,
|
||||
"data": encoded_data
|
||||
}
|
||||
}
|
||||
return {
|
||||
"image_url": {
|
||||
"url": image_url
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
def _convert_image_to_base64(url: str) -> str:
|
||||
"""
|
||||
将图片URL转换为base64编码
|
||||
Args:
|
||||
url: 图片URL
|
||||
Returns:
|
||||
str: base64编码的图片数据
|
||||
"""
|
||||
response = requests.get(url)
|
||||
if response.status_code == 200:
|
||||
# 将图片内容转换为base64
|
||||
img_data = base64.b64encode(response.content).decode('utf-8')
|
||||
return img_data
|
||||
else:
|
||||
raise Exception(f"Failed to fetch image: {response.status_code}")
|
||||
|
||||
|
||||
def _process_text_with_image(text: str) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
处理可能包含图片URL的文本,提取图片并转换为base64
|
||||
|
||||
Args:
|
||||
text: 可能包含图片URL的文本
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 包含文本和图片的部分列表
|
||||
"""
|
||||
parts = []
|
||||
img_url_match = re.search(IMAGE_URL_PATTERN, text)
|
||||
if img_url_match:
|
||||
# 提取URL
|
||||
img_url = img_url_match.group(2)
|
||||
# 将URL对应的图片转换为base64
|
||||
try:
|
||||
base64_data = _convert_image_to_base64(img_url)
|
||||
parts.append({
|
||||
"inlineData": {
|
||||
"mimeType": "image/png",
|
||||
"data": base64_data
|
||||
}
|
||||
})
|
||||
except Exception:
|
||||
# 如果转换失败,回退到文本模式
|
||||
parts.append({"text": text})
|
||||
else:
|
||||
# 没有图片URL,作为纯文本处理
|
||||
parts.append({"text": text})
|
||||
return parts
|
||||
|
||||
|
||||
class OpenAIMessageConverter(MessageConverter):
|
||||
"""OpenAI消息格式转换器"""
|
||||
|
||||
def convert(self, messages: List[Dict[str, Any]]) -> tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]:
|
||||
converted_messages = []
|
||||
system_instruction_parts = []
|
||||
|
||||
for idx, msg in enumerate(messages):
|
||||
role = msg.get("role", "")
|
||||
if role not in SUPPORTED_ROLES:
|
||||
if role == "tool":
|
||||
role = "user"
|
||||
else:
|
||||
# 如果是最后一条消息,则认为是用户消息
|
||||
if idx == len(messages) - 1:
|
||||
role = "user"
|
||||
else:
|
||||
role = "model"
|
||||
|
||||
parts = []
|
||||
# 特别处理最后一个assistant的消息,按\n\n分割
|
||||
if role == "assistant" and idx == len(messages) - 2 and isinstance(msg["content"], str) and msg["content"]:
|
||||
# 按\n\n分割消息
|
||||
content_parts = msg["content"].split("\n\n")
|
||||
for part in content_parts:
|
||||
if not part.strip(): # 跳过空内容
|
||||
continue
|
||||
# 处理可能包含图片的文本
|
||||
parts.extend(_process_text_with_image(part))
|
||||
elif isinstance(msg["content"], str) and msg["content"]:
|
||||
# 请求 gemini 接口时如果包含 content 字段但内容为空时会返回 400 错误,所以需要判断是否为空并移除
|
||||
parts.extend(_process_text_with_image(msg["content"]))
|
||||
elif isinstance(msg["content"], list):
|
||||
for content in msg["content"]:
|
||||
if isinstance(content, str) and content:
|
||||
parts.append({"text": content})
|
||||
elif isinstance(content, dict):
|
||||
if content["type"] == "text" and content["text"]:
|
||||
parts.append({"text": content["text"]})
|
||||
elif content["type"] == "image_url":
|
||||
parts.append(_convert_image(content["image_url"]["url"]))
|
||||
|
||||
if parts:
|
||||
if role == "system":
|
||||
system_instruction_parts.extend(parts)
|
||||
else:
|
||||
converted_messages.append({"role": role, "parts": parts})
|
||||
|
||||
system_instruction = (
|
||||
None
|
||||
if not system_instruction_parts
|
||||
else {
|
||||
"role": "system",
|
||||
"parts": system_instruction_parts,
|
||||
}
|
||||
)
|
||||
return converted_messages, system_instruction
|
||||
@@ -1,10 +1,15 @@
|
||||
# app/services/chat/response_handler.py
|
||||
|
||||
import base64
|
||||
import json
|
||||
import random
|
||||
import string
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Dict, Any, Optional
|
||||
from typing import Dict, Any, List, Optional
|
||||
import time
|
||||
import uuid
|
||||
from app.core.config import settings
|
||||
from app.config.config import settings
|
||||
from app.utils.uploader import ImageUploaderFactory
|
||||
|
||||
|
||||
class ResponseHandler(ABC):
|
||||
@@ -29,40 +34,38 @@ class GeminiResponseHandler(ResponseHandler):
|
||||
|
||||
|
||||
def _handle_openai_stream_response(response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
|
||||
text = _extract_text(response, model, stream=True)
|
||||
text, tool_calls = _extract_result(response, model, stream=True, gemini_format=False)
|
||||
if not text and not tool_calls:
|
||||
delta = {}
|
||||
else:
|
||||
delta = {"content": text, "role": "assistant"}
|
||||
if tool_calls:
|
||||
delta["tool_calls"] = tool_calls
|
||||
|
||||
return {
|
||||
"id": f"chatcmpl-{uuid.uuid4()}",
|
||||
"object": "chat.completion.chunk",
|
||||
"created": int(time.time()),
|
||||
"model": model,
|
||||
"choices": [{
|
||||
"index": 0,
|
||||
"delta": {"content": text} if text else {},
|
||||
"finish_reason": finish_reason
|
||||
}]
|
||||
"choices": [{"index": 0, "delta": delta, "finish_reason": finish_reason}],
|
||||
}
|
||||
|
||||
|
||||
def _handle_openai_normal_response(response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
|
||||
text = _extract_text(response, model, stream=False)
|
||||
text, tool_calls = _extract_result(response, model, stream=False, gemini_format=False)
|
||||
return {
|
||||
"id": f"chatcmpl-{uuid.uuid4()}",
|
||||
"object": "chat.completion",
|
||||
"created": int(time.time()),
|
||||
"model": model,
|
||||
"choices": [{
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": text
|
||||
},
|
||||
"finish_reason": finish_reason
|
||||
}],
|
||||
"usage": {
|
||||
"prompt_tokens": 0,
|
||||
"completion_tokens": 0,
|
||||
"total_tokens": 0
|
||||
}
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"message": {"role": "assistant", "content": text, "tool_calls": tool_calls},
|
||||
"finish_reason": finish_reason,
|
||||
}
|
||||
],
|
||||
"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
|
||||
}
|
||||
|
||||
|
||||
@@ -127,74 +130,15 @@ def _handle_openai_normal_image_response(image_str: str,model: str,finish_reason
|
||||
}
|
||||
|
||||
|
||||
def _extract_text(response: Dict[str, Any], model: str, stream: bool = False) -> str:
|
||||
text = ""
|
||||
def _extract_result(response: Dict[str, Any], model: str, stream: bool = False, gemini_format: bool = False) -> tuple[str, List[Dict[str, Any]]]:
|
||||
text, tool_calls = "", []
|
||||
if stream:
|
||||
if response.get("candidates"):
|
||||
candidate = response["candidates"][0]
|
||||
content = candidate.get("content", {})
|
||||
parts = content.get("parts", [])
|
||||
# if "thinking" in model:
|
||||
# if settings.SHOW_THINKING_PROCESS:
|
||||
# if len(parts) == 1:
|
||||
# if self.thinking_first:
|
||||
# self.thinking_first = False
|
||||
# self.thinking_status = True
|
||||
# text = "> thinking\n\n" + parts[0].get("text")
|
||||
# else:
|
||||
# text = parts[0].get("text")
|
||||
|
||||
# if len(parts) == 2:
|
||||
# self.thinking_status = False
|
||||
# if self.thinking_first:
|
||||
# self.thinking_first = False
|
||||
# text = (
|
||||
# "> thinking\n\n"
|
||||
# + parts[0].get("text")
|
||||
# + "\n\n---\n> output\n\n"
|
||||
# + parts[1].get("text")
|
||||
# )
|
||||
# else:
|
||||
# text = (
|
||||
# parts[0].get("text")
|
||||
# + "\n\n---\n> output\n\n"
|
||||
# + parts[1].get("text")
|
||||
# )
|
||||
# else:
|
||||
# if len(parts) == 1:
|
||||
# if self.thinking_first:
|
||||
# self.thinking_first = False
|
||||
# self.thinking_status = True
|
||||
# text = ""
|
||||
# elif self.thinking_status:
|
||||
# text = ""
|
||||
# else:
|
||||
# text = parts[0].get("text")
|
||||
|
||||
# if len(parts) == 2:
|
||||
# self.thinking_status = False
|
||||
# if self.thinking_first:
|
||||
# self.thinking_first = False
|
||||
# text = parts[1].get("text")
|
||||
# else:
|
||||
# text = parts[1].get("text")
|
||||
# else:
|
||||
# if "text" in parts[0]:
|
||||
# text = parts[0].get("text")
|
||||
# elif "executableCode" in parts[0]:
|
||||
# text = _format_code_block(parts[0]["executableCode"])
|
||||
# elif "codeExecution" in parts[0]:
|
||||
# text = _format_code_block(parts[0]["codeExecution"])
|
||||
# elif "executableCodeResult" in parts[0]:
|
||||
# text = _format_execution_result(
|
||||
# parts[0]["executableCodeResult"]
|
||||
# )
|
||||
# elif "codeExecutionResult" in parts[0]:
|
||||
# text = _format_execution_result(
|
||||
# parts[0]["codeExecutionResult"]
|
||||
# )
|
||||
# else:
|
||||
# text = ""
|
||||
if not parts:
|
||||
return "", []
|
||||
if "text" in parts[0]:
|
||||
text = parts[0].get("text")
|
||||
elif "executableCode" in parts[0]:
|
||||
@@ -209,9 +153,12 @@ def _extract_text(response: Dict[str, Any], model: str, stream: bool = False) ->
|
||||
text = _format_execution_result(
|
||||
parts[0]["codeExecutionResult"]
|
||||
)
|
||||
elif "inlineData" in parts[0]:
|
||||
text = _extract_image_data(parts[0])
|
||||
else:
|
||||
text = ""
|
||||
text = _add_search_link_text(model, candidate, text)
|
||||
tool_calls = _extract_tool_calls(parts, gemini_format)
|
||||
else:
|
||||
if response.get("candidates"):
|
||||
candidate = response["candidates"][0]
|
||||
@@ -232,23 +179,93 @@ def _extract_text(response: Dict[str, Any], model: str, stream: bool = False) ->
|
||||
else:
|
||||
text = candidate["content"]["parts"][0]["text"]
|
||||
else:
|
||||
text = candidate["content"]["parts"][0]["text"]
|
||||
text = ""
|
||||
if "parts" in candidate["content"]:
|
||||
for part in candidate["content"]["parts"]:
|
||||
if "text" in part:
|
||||
text += part["text"]
|
||||
elif "inlineData" in part:
|
||||
text += _extract_image_data(part)
|
||||
|
||||
|
||||
text = _add_search_link_text(model, candidate, text)
|
||||
tool_calls = _extract_tool_calls(candidate["content"]["parts"], gemini_format)
|
||||
else:
|
||||
text = "暂无返回"
|
||||
return text, tool_calls
|
||||
|
||||
def _extract_image_data(part: dict) -> str:
|
||||
image_uploader = None
|
||||
if settings.UPLOAD_PROVIDER == "smms":
|
||||
image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,api_key=settings.SMMS_SECRET_TOKEN)
|
||||
elif settings.UPLOAD_PROVIDER == "picgo":
|
||||
image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,api_key=settings.PICGO_API_KEY)
|
||||
elif settings.UPLOAD_PROVIDER == "cloudflare_imgbed":
|
||||
image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,base_url=settings.CLOUDFLARE_IMGBED_URL,auth_code=settings.CLOUDFLARE_IMGBED_AUTH_CODE)
|
||||
current_date = time.strftime("%Y/%m/%d")
|
||||
filename = f"{current_date}/{uuid.uuid4().hex[:8]}.png"
|
||||
base64_data = part["inlineData"]["data"]
|
||||
#将base64_data转成bytes数组
|
||||
bytes_data = base64.b64decode(base64_data)
|
||||
upload_response = image_uploader.upload(bytes_data,filename)
|
||||
if upload_response.success:
|
||||
text = f""
|
||||
else:
|
||||
text = ""
|
||||
return text
|
||||
|
||||
def _extract_tool_calls(parts: List[Dict[str, Any]], gemini_format: bool) -> List[Dict[str, Any]]:
|
||||
"""提取工具调用信息"""
|
||||
if not parts or not isinstance(parts, list):
|
||||
return []
|
||||
|
||||
letters = string.ascii_lowercase + string.digits
|
||||
|
||||
tool_calls = list()
|
||||
for i in range(len(parts)):
|
||||
part = parts[i]
|
||||
if not part or not isinstance(part, dict):
|
||||
continue
|
||||
|
||||
item = part.get("functionCall", {})
|
||||
if not item or not isinstance(item, dict):
|
||||
continue
|
||||
|
||||
if gemini_format:
|
||||
tool_calls.append(part)
|
||||
else:
|
||||
id = f"call_{''.join(random.sample(letters, 32))}"
|
||||
name = item.get("name", "")
|
||||
arguments = json.dumps(item.get("args", None) or {})
|
||||
|
||||
tool_calls.append(
|
||||
{
|
||||
"index": i,
|
||||
"id": id,
|
||||
"type": "function",
|
||||
"function": {"name": name, "arguments": arguments},
|
||||
}
|
||||
)
|
||||
|
||||
return tool_calls
|
||||
|
||||
|
||||
def _handle_gemini_stream_response(response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
|
||||
text = _extract_text(response, model, stream=stream)
|
||||
content = {"parts": [{"text": text}], "role": "model"}
|
||||
text, tool_calls = _extract_result(response, model, stream=stream, gemini_format=True)
|
||||
if tool_calls:
|
||||
content = {"parts": tool_calls, "role": "model"}
|
||||
else:
|
||||
content = {"parts": [{"text": text}], "role": "model"}
|
||||
response["candidates"][0]["content"] = content
|
||||
return response
|
||||
|
||||
|
||||
def _handle_gemini_normal_response(response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
|
||||
text = _extract_text(response, model, stream=stream)
|
||||
content = {"parts": [{"text": text}], "role": "model"}
|
||||
text, tool_calls = _extract_result(response, model, stream=stream, gemini_format=True)
|
||||
if tool_calls:
|
||||
content = {"parts": tool_calls, "role": "model"}
|
||||
else:
|
||||
content = {"parts": [{"text": text}], "role": "model"}
|
||||
response["candidates"][0]["content"] = content
|
||||
return response
|
||||
|
||||
@@ -2,8 +2,7 @@
|
||||
|
||||
from typing import TypeVar, Callable
|
||||
from functools import wraps
|
||||
from app.core.logger import get_retry_logger
|
||||
from app.services.key_manager import KeyManager
|
||||
from app.logger.logger import get_retry_logger
|
||||
|
||||
T = TypeVar('T')
|
||||
logger = get_retry_logger()
|
||||
@@ -12,9 +11,8 @@ logger = get_retry_logger()
|
||||
class RetryHandler:
|
||||
"""重试处理装饰器"""
|
||||
|
||||
def __init__(self, max_retries: int = 3, key_manager: KeyManager = None, key_arg: str = "api_key"):
|
||||
def __init__(self, max_retries: int = 3, key_arg: str = "api_key"):
|
||||
self.max_retries = max_retries
|
||||
self.key_manager = key_manager
|
||||
self.key_arg = key_arg
|
||||
|
||||
def __call__(self, func: Callable[..., T]) -> Callable[..., T]:
|
||||
@@ -29,9 +27,11 @@ class RetryHandler:
|
||||
last_exception = e
|
||||
logger.warning(f"API call failed with error: {str(e)}. Attempt {attempt + 1} of {self.max_retries}")
|
||||
|
||||
if self.key_manager:
|
||||
# 从函数参数中获取 key_manager
|
||||
key_manager = kwargs.get('key_manager')
|
||||
if key_manager:
|
||||
old_key = kwargs.get(self.key_arg)
|
||||
new_key = await self.key_manager.handle_api_failure(old_key)
|
||||
new_key = await key_manager.handle_api_failure(old_key)
|
||||
kwargs[self.key_arg] = new_key
|
||||
logger.info(f"Switched to new API key: {new_key}")
|
||||
|
||||
133
app/handler/stream_optimizer.py
Normal file
133
app/handler/stream_optimizer.py
Normal file
@@ -0,0 +1,133 @@
|
||||
# app/services/chat/stream_optimizer.py
|
||||
|
||||
import asyncio
|
||||
import math
|
||||
from typing import Any, List, AsyncGenerator, Callable
|
||||
from app.logger.logger import get_openai_logger, get_gemini_logger
|
||||
from app.config.config import settings
|
||||
from app.core.constants import DEFAULT_STREAM_CHUNK_SIZE, DEFAULT_STREAM_LONG_TEXT_THRESHOLD, DEFAULT_STREAM_MAX_DELAY, DEFAULT_STREAM_MIN_DELAY, DEFAULT_STREAM_SHORT_TEXT_THRESHOLD
|
||||
|
||||
logger_openai = get_openai_logger()
|
||||
logger_gemini = get_gemini_logger()
|
||||
|
||||
|
||||
class StreamOptimizer:
|
||||
"""流式输出优化器
|
||||
|
||||
提供流式输出优化功能,包括智能延迟调整和长文本分块输出。
|
||||
"""
|
||||
|
||||
def __init__(self,
|
||||
logger=None,
|
||||
min_delay: float = DEFAULT_STREAM_MIN_DELAY,
|
||||
max_delay: float = DEFAULT_STREAM_MAX_DELAY,
|
||||
short_text_threshold: int = DEFAULT_STREAM_SHORT_TEXT_THRESHOLD,
|
||||
long_text_threshold: int = DEFAULT_STREAM_LONG_TEXT_THRESHOLD,
|
||||
chunk_size: int = DEFAULT_STREAM_CHUNK_SIZE):
|
||||
"""初始化流式输出优化器
|
||||
|
||||
参数:
|
||||
logger: 日志记录器
|
||||
min_delay: 最小延迟时间(秒)
|
||||
max_delay: 最大延迟时间(秒)
|
||||
short_text_threshold: 短文本阈值(字符数)
|
||||
long_text_threshold: 长文本阈值(字符数)
|
||||
chunk_size: 长文本分块大小(字符数)
|
||||
"""
|
||||
self.logger = logger
|
||||
self.min_delay = min_delay
|
||||
self.max_delay = max_delay
|
||||
self.short_text_threshold = short_text_threshold
|
||||
self.long_text_threshold = long_text_threshold
|
||||
self.chunk_size = chunk_size
|
||||
|
||||
def calculate_delay(self, text_length: int) -> float:
|
||||
"""根据文本长度计算延迟时间
|
||||
|
||||
参数:
|
||||
text_length: 文本长度
|
||||
|
||||
返回:
|
||||
延迟时间(秒)
|
||||
"""
|
||||
if text_length <= self.short_text_threshold:
|
||||
# 短文本使用较大延迟
|
||||
return self.max_delay
|
||||
elif text_length >= self.long_text_threshold:
|
||||
# 长文本使用较小延迟
|
||||
return self.min_delay
|
||||
else:
|
||||
# 中等长度文本使用线性插值计算延迟
|
||||
# 使用对数函数使延迟变化更平滑
|
||||
ratio = math.log(text_length / self.short_text_threshold) / math.log(self.long_text_threshold / self.short_text_threshold)
|
||||
return self.max_delay - ratio * (self.max_delay - self.min_delay)
|
||||
|
||||
def split_text_into_chunks(self, text: str) -> List[str]:
|
||||
"""将文本分割成小块
|
||||
|
||||
参数:
|
||||
text: 要分割的文本
|
||||
|
||||
返回:
|
||||
文本块列表
|
||||
"""
|
||||
return [text[i:i+self.chunk_size] for i in range(0, len(text), self.chunk_size)]
|
||||
|
||||
async def optimize_stream_output(self,
|
||||
text: str,
|
||||
create_response_chunk: Callable[[str], Any],
|
||||
format_chunk: Callable[[Any], str]) -> AsyncGenerator[str, None]:
|
||||
"""优化流式输出
|
||||
|
||||
参数:
|
||||
text: 要输出的文本
|
||||
create_response_chunk: 创建响应块的函数,接收文本,返回响应块
|
||||
format_chunk: 格式化响应块的函数,接收响应块,返回格式化后的字符串
|
||||
|
||||
返回:
|
||||
异步生成器,生成格式化后的响应块
|
||||
"""
|
||||
if not text:
|
||||
return
|
||||
|
||||
# 计算智能延迟时间
|
||||
delay = self.calculate_delay(len(text))
|
||||
if self.logger:
|
||||
self.logger.info(f"Text length: {len(text)}, delay: {delay:.4f}s")
|
||||
|
||||
# 根据文本长度决定输出方式
|
||||
if len(text) >= self.long_text_threshold:
|
||||
# 长文本:分块输出
|
||||
chunks = self.split_text_into_chunks(text)
|
||||
if self.logger:
|
||||
self.logger.info(f"Long text: splitting into {len(chunks)} chunks")
|
||||
for chunk_text in chunks:
|
||||
chunk_response = create_response_chunk(chunk_text)
|
||||
yield format_chunk(chunk_response)
|
||||
await asyncio.sleep(delay)
|
||||
else:
|
||||
# 短文本:逐字符输出
|
||||
for char in text:
|
||||
char_chunk = create_response_chunk(char)
|
||||
yield format_chunk(char_chunk)
|
||||
await asyncio.sleep(delay)
|
||||
|
||||
|
||||
# 创建默认的优化器实例,可以直接导入使用
|
||||
openai_optimizer = StreamOptimizer(
|
||||
logger=logger_openai,
|
||||
min_delay=settings.STREAM_MIN_DELAY,
|
||||
max_delay=settings.STREAM_MAX_DELAY,
|
||||
short_text_threshold=settings.STREAM_SHORT_TEXT_THRESHOLD,
|
||||
long_text_threshold=settings.STREAM_LONG_TEXT_THRESHOLD,
|
||||
chunk_size=settings.STREAM_CHUNK_SIZE
|
||||
)
|
||||
|
||||
gemini_optimizer = StreamOptimizer(
|
||||
logger=logger_gemini,
|
||||
min_delay=settings.STREAM_MIN_DELAY,
|
||||
max_delay=settings.STREAM_MAX_DELAY,
|
||||
short_text_threshold=settings.STREAM_SHORT_TEXT_THRESHOLD,
|
||||
long_text_threshold=settings.STREAM_LONG_TEXT_THRESHOLD,
|
||||
chunk_size=settings.STREAM_CHUNK_SIZE
|
||||
)
|
||||
44
app/main.py
44
app/main.py
@@ -1,44 +1,16 @@
|
||||
from fastapi import FastAPI
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from app.core.logger import get_main_logger
|
||||
|
||||
from app.api import gemini_routes, openai_routes
|
||||
"""
|
||||
应用程序入口模块
|
||||
"""
|
||||
import uvicorn
|
||||
from app.core.application import create_app
|
||||
from app.logger.logger import get_main_logger
|
||||
|
||||
from app.middleware.request_logging_middleware import RequestLoggingMiddleware
|
||||
# 创建应用程序实例
|
||||
app = create_app()
|
||||
|
||||
# 配置日志
|
||||
logger = get_main_logger()
|
||||
|
||||
app = FastAPI()
|
||||
|
||||
# 添加请求日志中间件
|
||||
# app.add_middleware(RequestLoggingMiddleware)
|
||||
|
||||
# 配置CORS中间件
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"], # 生产环境建议配置具体的域名
|
||||
allow_credentials=True,
|
||||
allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"], # 明确指定允许的HTTP方法
|
||||
allow_headers=["*"], # 生产环境建议配置具体的请求头
|
||||
expose_headers=["*"], # 允许前端访问的响应头
|
||||
max_age=600, # 预检请求缓存时间(秒)
|
||||
)
|
||||
|
||||
# 包含所有路由
|
||||
app.include_router(openai_routes.router)
|
||||
app.include_router(gemini_routes.router)
|
||||
app.include_router(gemini_routes.router_v1beta)
|
||||
|
||||
|
||||
@app.get("/health")
|
||||
@app.get("/")
|
||||
async def health_check():
|
||||
logger.info("Health check endpoint called")
|
||||
return {"status": "healthy"}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
logger.info("Starting application server...")
|
||||
uvicorn.run(app, host="0.0.0.0", port=8001)
|
||||
|
||||
61
app/middleware/middleware.py
Normal file
61
app/middleware/middleware.py
Normal file
@@ -0,0 +1,61 @@
|
||||
"""
|
||||
中间件配置模块,负责设置和配置应用程序的中间件
|
||||
"""
|
||||
from fastapi import FastAPI, Request
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import RedirectResponse
|
||||
from starlette.middleware.base import BaseHTTPMiddleware
|
||||
|
||||
from app.logger.logger import get_main_logger
|
||||
from app.core.security import verify_auth_token
|
||||
# from app.middleware.request_logging_middleware import RequestLoggingMiddleware
|
||||
from app.core.constants import API_VERSION
|
||||
|
||||
logger = get_main_logger()
|
||||
|
||||
class AuthMiddleware(BaseHTTPMiddleware):
|
||||
"""
|
||||
认证中间件,处理未经身份验证的请求
|
||||
"""
|
||||
async def dispatch(self, request: Request, call_next):
|
||||
# 允许特定路径绕过身份验证
|
||||
if (request.url.path not in ["/", "/auth"] and
|
||||
not request.url.path.startswith("/static") and
|
||||
not request.url.path.startswith("/gemini") and
|
||||
not request.url.path.startswith("/v1") and
|
||||
not request.url.path.startswith(f"/{API_VERSION}") and
|
||||
not request.url.path.startswith("/health") and
|
||||
not request.url.path.startswith("/hf")):
|
||||
|
||||
auth_token = request.cookies.get("auth_token")
|
||||
if not auth_token or not verify_auth_token(auth_token):
|
||||
logger.warning(f"Unauthorized access attempt to {request.url.path}")
|
||||
return RedirectResponse(url="/")
|
||||
logger.debug("Request authenticated successfully")
|
||||
|
||||
response = await call_next(request)
|
||||
return response
|
||||
|
||||
def setup_middlewares(app: FastAPI) -> None:
|
||||
"""
|
||||
设置应用程序的中间件
|
||||
|
||||
Args:
|
||||
app: FastAPI应用程序实例
|
||||
"""
|
||||
# 添加认证中间件
|
||||
app.add_middleware(AuthMiddleware)
|
||||
|
||||
# 添加请求日志中间件(可选,默认注释掉)
|
||||
# app.add_middleware(RequestLoggingMiddleware)
|
||||
|
||||
# 配置CORS中间件
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"], # 生产环境建议配置具体的域名
|
||||
allow_credentials=True,
|
||||
allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"], # 明确指定允许的HTTP方法
|
||||
allow_headers=["*"], # 生产环境建议配置具体的请求头
|
||||
expose_headers=["*"], # 允许前端访问的响应头
|
||||
max_age=600, # 预检请求缓存时间(秒)
|
||||
)
|
||||
@@ -1,7 +1,7 @@
|
||||
from fastapi import Request
|
||||
from starlette.middleware.base import BaseHTTPMiddleware
|
||||
import json
|
||||
from app.core.logger import get_request_logger
|
||||
from app.logger.logger import get_request_logger
|
||||
|
||||
logger = get_request_logger()
|
||||
|
||||
|
||||
178
app/router/gemini_routes.py
Normal file
178
app/router/gemini_routes.py
Normal file
@@ -0,0 +1,178 @@
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from fastapi.responses import StreamingResponse, JSONResponse
|
||||
from copy import deepcopy
|
||||
from app.config.config import settings
|
||||
from app.logger.logger import get_gemini_logger
|
||||
from app.core.security import SecurityService
|
||||
from app.domain.gemini_models import GeminiContent, GeminiRequest
|
||||
from app.service.chat.gemini_chat_service import GeminiChatService
|
||||
from app.service.key.key_manager import KeyManager, get_key_manager_instance
|
||||
from app.service.model.model_service import ModelService
|
||||
from app.handler.retry_handler import RetryHandler
|
||||
from app.core.constants import API_VERSION
|
||||
|
||||
# 路由设置
|
||||
router = APIRouter(prefix=f"/gemini/{API_VERSION}")
|
||||
router_v1beta = APIRouter(prefix=f"/{API_VERSION}")
|
||||
logger = get_gemini_logger()
|
||||
|
||||
# 初始化服务
|
||||
security_service = SecurityService(settings.ALLOWED_TOKENS, settings.AUTH_TOKEN)
|
||||
model_service = ModelService(settings.SEARCH_MODELS, settings.IMAGE_MODELS)
|
||||
|
||||
|
||||
async def get_key_manager():
|
||||
"""获取密钥管理器实例"""
|
||||
return await get_key_manager_instance()
|
||||
|
||||
|
||||
async def get_next_working_key(key_manager: KeyManager = Depends(get_key_manager)):
|
||||
"""获取下一个可用的API密钥"""
|
||||
return await key_manager.get_next_working_key()
|
||||
|
||||
|
||||
@router.get("/models")
|
||||
@router_v1beta.get("/models")
|
||||
async def list_models(
|
||||
_=Depends(security_service.verify_key),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
"""获取可用的Gemini模型列表"""
|
||||
logger.info("-" * 50 + "list_gemini_models" + "-" * 50)
|
||||
logger.info("Handling Gemini models list request")
|
||||
|
||||
api_key = await key_manager.get_next_working_key()
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
models_json = model_service.get_gemini_models(api_key)
|
||||
model_mapping = {x.get("name", "").split("/", maxsplit=1)[1]: x for x in models_json["models"]}
|
||||
|
||||
# 添加搜索模型
|
||||
if model_service.search_models:
|
||||
for name in model_service.search_models:
|
||||
model = model_mapping.get(name)
|
||||
if not model:
|
||||
continue
|
||||
|
||||
item = deepcopy(model)
|
||||
item["name"] = f"models/{name}-search"
|
||||
display_name = f'{item.get("displayName")} For Search'
|
||||
item["displayName"] = display_name
|
||||
item["description"] = display_name
|
||||
|
||||
models_json["models"].append(item)
|
||||
|
||||
# 添加图像生成模型
|
||||
if model_service.image_models:
|
||||
for name in model_service.image_models:
|
||||
model = model_mapping.get(name)
|
||||
if not model:
|
||||
continue
|
||||
|
||||
item = deepcopy(model)
|
||||
item["name"] = f"models/{name}-image"
|
||||
display_name = f'{item.get("displayName")} For Image'
|
||||
item["displayName"] = display_name
|
||||
item["description"] = display_name
|
||||
|
||||
models_json["models"].append(item)
|
||||
|
||||
return models_json
|
||||
|
||||
|
||||
@router.post("/models/{model_name}:generateContent")
|
||||
@router_v1beta.post("/models/{model_name}:generateContent")
|
||||
@RetryHandler(max_retries=3, key_arg="api_key")
|
||||
async def generate_content(
|
||||
model_name: str,
|
||||
request: GeminiRequest,
|
||||
_=Depends(security_service.verify_goog_api_key),
|
||||
api_key: str = Depends(get_next_working_key),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
"""非流式生成内容"""
|
||||
logger.info("-" * 50 + "gemini_generate_content" + "-" * 50)
|
||||
logger.info(f"Handling Gemini content generation request for model: {model_name}")
|
||||
logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
if not model_service.check_model_support(model_name):
|
||||
raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
|
||||
|
||||
try:
|
||||
chat_service = GeminiChatService(settings.BASE_URL, key_manager)
|
||||
response = await chat_service.generate_content(
|
||||
model=model_name,
|
||||
request=request,
|
||||
api_key=api_key
|
||||
)
|
||||
return response
|
||||
except Exception as e:
|
||||
logger.error(f"Chat completion failed after retries: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Chat completion failed") from e
|
||||
|
||||
|
||||
@router.post("/models/{model_name}:streamGenerateContent")
|
||||
@router_v1beta.post("/models/{model_name}:streamGenerateContent")
|
||||
@RetryHandler(max_retries=3, key_arg="api_key")
|
||||
async def stream_generate_content(
|
||||
model_name: str,
|
||||
request: GeminiRequest,
|
||||
_=Depends(security_service.verify_goog_api_key),
|
||||
api_key: str = Depends(get_next_working_key),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
"""流式生成内容"""
|
||||
logger.info("-" * 50 + "gemini_stream_generate_content" + "-" * 50)
|
||||
logger.info(f"Handling Gemini streaming content generation for model: {model_name}")
|
||||
logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
if not model_service.check_model_support(model_name):
|
||||
raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
|
||||
|
||||
try:
|
||||
chat_service = GeminiChatService(settings.BASE_URL, key_manager)
|
||||
response_stream = chat_service.stream_generate_content(
|
||||
model=model_name,
|
||||
request=request,
|
||||
api_key=api_key
|
||||
)
|
||||
return StreamingResponse(response_stream, media_type="text/event-stream")
|
||||
except Exception as e:
|
||||
logger.error(f"Streaming request failed: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Streaming request failed") from e
|
||||
|
||||
|
||||
@router.post("/verify-key/{api_key}")
|
||||
async def verify_key(api_key: str):
|
||||
"""验证Gemini API密钥的有效性"""
|
||||
logger.info("-" * 50 + "verify_gemini_key" + "-" * 50)
|
||||
logger.info("Verifying API key validity")
|
||||
|
||||
try:
|
||||
key_manager = await get_key_manager()
|
||||
chat_service = GeminiChatService(settings.BASE_URL, key_manager)
|
||||
|
||||
# 使用generate_content接口测试key的有效性
|
||||
gemini_request = GeminiRequest(
|
||||
contents=[
|
||||
GeminiContent(
|
||||
role="user",
|
||||
parts=[{"text": "hi"}]
|
||||
)
|
||||
]
|
||||
)
|
||||
|
||||
response = await chat_service.generate_content(
|
||||
settings.TEST_MODEL,
|
||||
gemini_request,
|
||||
api_key
|
||||
)
|
||||
|
||||
if response:
|
||||
return JSONResponse({"status": "valid"})
|
||||
return JSONResponse({"status": "invalid"})
|
||||
except Exception as e:
|
||||
logger.error(f"Key verification failed: {str(e)}")
|
||||
return JSONResponse({"status": "invalid", "error": str(e)})
|
||||
@@ -1,31 +1,38 @@
|
||||
from fastapi import HTTPException, APIRouter, Depends
|
||||
from fastapi.responses import StreamingResponse
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logger import get_openai_logger
|
||||
from app.config.config import settings
|
||||
from app.logger.logger import get_openai_logger
|
||||
from app.core.security import SecurityService
|
||||
from app.schemas.openai_models import ChatRequest, EmbeddingRequest, ImageGenerationRequest
|
||||
from app.services.chat.retry_handler import RetryHandler
|
||||
from app.services.embedding_service import EmbeddingService
|
||||
from app.services.image_create_service import ImageCreateService
|
||||
from app.services.key_manager import KeyManager
|
||||
from app.services.model_service import ModelService
|
||||
from app.services.openai_chat_service import OpenAIChatService
|
||||
from app.domain.openai_models import ChatRequest, EmbeddingRequest, ImageGenerationRequest
|
||||
from app.handler.retry_handler import RetryHandler
|
||||
from app.service.embedding.embedding_service import EmbeddingService
|
||||
from app.service.image.image_create_service import ImageCreateService
|
||||
from app.service.key.key_manager import KeyManager, get_key_manager_instance
|
||||
from app.service.model.model_service import ModelService
|
||||
from app.service.chat.openai_chat_service import OpenAIChatService
|
||||
|
||||
router = APIRouter()
|
||||
logger = get_openai_logger()
|
||||
|
||||
# 初始化服务
|
||||
security_service = SecurityService(settings.ALLOWED_TOKENS, settings.AUTH_TOKEN)
|
||||
key_manager = KeyManager(settings.API_KEYS)
|
||||
model_service = ModelService(settings.MODEL_SEARCH)
|
||||
model_service = ModelService(settings.SEARCH_MODELS,settings.IMAGE_MODELS)
|
||||
embedding_service = EmbeddingService(settings.BASE_URL)
|
||||
image_create_service = ImageCreateService()
|
||||
|
||||
async def get_key_manager():
|
||||
return await get_key_manager_instance()
|
||||
|
||||
async def get_next_working_key_wrapper(key_manager: KeyManager = Depends(get_key_manager)):
|
||||
return await key_manager.get_next_working_key()
|
||||
|
||||
@router.get("/v1/models")
|
||||
@router.get("/hf/v1/models")
|
||||
async def list_models(_=Depends(security_service.verify_authorization)):
|
||||
async def list_models(
|
||||
_=Depends(security_service.verify_authorization),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
logger.info("-" * 50 + "list_models" + "-" * 50)
|
||||
logger.info("Handling models list request")
|
||||
api_key = await key_manager.get_next_working_key()
|
||||
@@ -39,11 +46,12 @@ async def list_models(_=Depends(security_service.verify_authorization)):
|
||||
|
||||
@router.post("/v1/chat/completions")
|
||||
@router.post("/hf/v1/chat/completions")
|
||||
@RetryHandler(max_retries=3, key_manager=key_manager, key_arg="api_key")
|
||||
@RetryHandler(max_retries=3, key_arg="api_key")
|
||||
async def chat_completion(
|
||||
request: ChatRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
api_key: str = Depends(key_manager.get_next_working_key),
|
||||
request: ChatRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
api_key: str = Depends(get_next_working_key_wrapper),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
# 如果model是imagen3,使用paid_key
|
||||
if request.model == f"{settings.CREATE_IMAGE_MODEL}-chat":
|
||||
@@ -53,24 +61,30 @@ async def chat_completion(
|
||||
logger.info(f"Handling chat completion request for model: {request.model}")
|
||||
logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
|
||||
logger.info(f"Using API key: {api_key}")
|
||||
|
||||
if not model_service.check_model_support(request.model):
|
||||
raise HTTPException(status_code=400, detail=f"Model {request.model} is not supported")
|
||||
|
||||
try:
|
||||
response = await chat_service.create_image_chat_completion(request=request)
|
||||
# 如果model是imagen3,使用paid_key
|
||||
if request.model == f"{settings.CREATE_IMAGE_MODEL}-chat":
|
||||
response = await chat_service.create_image_chat_completion(request=request)
|
||||
else:
|
||||
response = await chat_service.create_chat_completion(request, api_key)
|
||||
# 处理流式响应
|
||||
if request.stream:
|
||||
return StreamingResponse(response, media_type="text/event-stream")
|
||||
logger.info("Chat completion request successful")
|
||||
return response
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Chat completion failed after retries: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Chat completion failed") from e
|
||||
|
||||
|
||||
@router.post("/v1/images/generations")
|
||||
@router.post("/hf/v1/images/generations")
|
||||
async def generate_image(
|
||||
request: ImageGenerationRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
request: ImageGenerationRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
):
|
||||
logger.info("-" * 50 + "generate_image" + "-" * 50)
|
||||
logger.info(f"Handling image generation request for prompt: {request.prompt}")
|
||||
@@ -79,17 +93,16 @@ async def generate_image(
|
||||
response = image_create_service.generate_images(request)
|
||||
logger.info("Image generation request successful")
|
||||
return response
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Image generation request failed: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Image generation request failed") from e
|
||||
|
||||
|
||||
@router.post("/v1/embeddings")
|
||||
@router.post("/hf/v1/embeddings")
|
||||
async def embedding(
|
||||
request: EmbeddingRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
request: EmbeddingRequest,
|
||||
_=Depends(security_service.verify_authorization),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
logger.info("-" * 50 + "embedding" + "-" * 50)
|
||||
logger.info(f"Handling embedding request for model: {request.model}")
|
||||
@@ -105,11 +118,11 @@ async def embedding(
|
||||
logger.error(f"Embedding request failed: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail="Embedding request failed") from e
|
||||
|
||||
|
||||
@router.get("/v1/keys/list")
|
||||
@router.get("/hf/v1/keys/list")
|
||||
async def get_keys_list(
|
||||
_=Depends(security_service.verify_auth_token),
|
||||
_=Depends(security_service.verify_auth_token),
|
||||
key_manager: KeyManager = Depends(get_key_manager)
|
||||
):
|
||||
"""获取有效和无效的API key列表"""
|
||||
logger.info("-" * 50 + "get_keys_list" + "-" * 50)
|
||||
103
app/router/routers.py
Normal file
103
app/router/routers.py
Normal file
@@ -0,0 +1,103 @@
|
||||
"""
|
||||
路由配置模块,负责设置和配置应用程序的路由
|
||||
"""
|
||||
from fastapi import FastAPI, Request
|
||||
from fastapi.responses import HTMLResponse, RedirectResponse
|
||||
from fastapi.templating import Jinja2Templates
|
||||
|
||||
from app.logger.logger import get_main_logger
|
||||
from app.core.security import verify_auth_token
|
||||
from app.router import gemini_routes, openai_routes
|
||||
from app.service.key.key_manager import get_key_manager_instance
|
||||
|
||||
logger = get_main_logger()
|
||||
|
||||
# 配置Jinja2模板
|
||||
templates = Jinja2Templates(directory="app/templates")
|
||||
|
||||
def setup_routers(app: FastAPI) -> None:
|
||||
"""
|
||||
设置应用程序的路由
|
||||
|
||||
Args:
|
||||
app: FastAPI应用程序实例
|
||||
"""
|
||||
# 包含API路由
|
||||
app.include_router(openai_routes.router)
|
||||
app.include_router(gemini_routes.router)
|
||||
app.include_router(gemini_routes.router_v1beta)
|
||||
|
||||
# 添加页面路由
|
||||
setup_page_routes(app)
|
||||
|
||||
# 添加健康检查路由
|
||||
setup_health_routes(app)
|
||||
|
||||
def setup_page_routes(app: FastAPI) -> None:
|
||||
"""
|
||||
设置页面相关的路由
|
||||
|
||||
Args:
|
||||
app: FastAPI应用程序实例
|
||||
"""
|
||||
@app.get("/", response_class=HTMLResponse)
|
||||
async def auth_page(request: Request):
|
||||
"""认证页面"""
|
||||
return templates.TemplateResponse("auth.html", {"request": request})
|
||||
|
||||
@app.post("/auth")
|
||||
async def authenticate(request: Request):
|
||||
"""处理认证请求"""
|
||||
try:
|
||||
form = await request.form()
|
||||
auth_token = form.get("auth_token")
|
||||
if not auth_token:
|
||||
logger.warning("Authentication attempt with empty token")
|
||||
return RedirectResponse(url="/", status_code=302)
|
||||
|
||||
if verify_auth_token(auth_token):
|
||||
logger.info("Successful authentication")
|
||||
response = RedirectResponse(url="/keys", status_code=302)
|
||||
response.set_cookie(key="auth_token", value=auth_token, httponly=True, max_age=3600)
|
||||
return response
|
||||
logger.warning("Failed authentication attempt with invalid token")
|
||||
return RedirectResponse(url="/", status_code=302)
|
||||
except Exception as e:
|
||||
logger.error(f"Authentication error: {str(e)}")
|
||||
return RedirectResponse(url="/", status_code=302)
|
||||
|
||||
@app.get("/keys", response_class=HTMLResponse)
|
||||
async def keys_page(request: Request):
|
||||
"""密钥管理页面"""
|
||||
try:
|
||||
auth_token = request.cookies.get("auth_token")
|
||||
if not auth_token or not verify_auth_token(auth_token):
|
||||
logger.warning("Unauthorized access attempt to keys page")
|
||||
return RedirectResponse(url="/", status_code=302)
|
||||
|
||||
key_manager = await get_key_manager_instance()
|
||||
keys_status = await key_manager.get_keys_by_status()
|
||||
total = len(keys_status["valid_keys"]) + len(keys_status["invalid_keys"])
|
||||
logger.info(f"Keys status retrieved successfully. Total keys: {total}")
|
||||
return templates.TemplateResponse("keys_status.html", {
|
||||
"request": request,
|
||||
"valid_keys": keys_status["valid_keys"],
|
||||
"invalid_keys": keys_status["invalid_keys"],
|
||||
"total": total
|
||||
})
|
||||
except Exception as e:
|
||||
logger.error(f"Error retrieving keys status: {str(e)}")
|
||||
raise
|
||||
|
||||
def setup_health_routes(app: FastAPI) -> None:
|
||||
"""
|
||||
设置健康检查相关的路由
|
||||
|
||||
Args:
|
||||
app: FastAPI应用程序实例
|
||||
"""
|
||||
@app.get("/health")
|
||||
async def health_check(request: Request):
|
||||
"""健康检查端点"""
|
||||
logger.info("Health check endpoint called")
|
||||
return {"status": "healthy"}
|
||||
@@ -2,12 +2,13 @@
|
||||
|
||||
import json
|
||||
from typing import Dict, Any, AsyncGenerator, List
|
||||
from app.core.logger import get_gemini_logger
|
||||
from app.services.chat.api_client import GeminiApiClient
|
||||
from app.schemas.gemini_models import GeminiRequest
|
||||
from app.core.config import settings
|
||||
from app.services.chat.response_handler import GeminiResponseHandler
|
||||
from app.services.key_manager import KeyManager
|
||||
from app.logger.logger import get_gemini_logger
|
||||
from app.service.client.api_client import GeminiApiClient
|
||||
from app.handler.stream_optimizer import gemini_optimizer
|
||||
from app.domain.gemini_models import GeminiRequest
|
||||
from app.config.config import settings
|
||||
from app.handler.response_handler import GeminiResponseHandler
|
||||
from app.service.key.key_manager import KeyManager
|
||||
|
||||
logger = get_gemini_logger()
|
||||
|
||||
@@ -31,6 +32,12 @@ def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
tools.append({"code_execution": {}})
|
||||
if model.endswith("-search"):
|
||||
tools.append({"googleSearch": {}})
|
||||
|
||||
if payload and isinstance(payload, dict) and "tools" in payload:
|
||||
items = payload.get("tools", [])
|
||||
if items and isinstance(items, list):
|
||||
tools.extend(items)
|
||||
|
||||
return tools
|
||||
|
||||
|
||||
@@ -55,14 +62,19 @@ def _get_safety_settings(model: str) -> List[Dict[str, str]]:
|
||||
|
||||
def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
|
||||
"""构建请求payload"""
|
||||
payload = request.model_dump()
|
||||
return {
|
||||
"contents": payload.get("contents", []),
|
||||
"tools": _build_tools(model, payload),
|
||||
request_dict = request.model_dump()
|
||||
payload = {
|
||||
"contents": request_dict.get("contents", []),
|
||||
"tools": _build_tools(model, request_dict),
|
||||
"safetySettings": _get_safety_settings(model),
|
||||
"generationConfig": payload.get("generationConfig", {}),
|
||||
"systemInstruction": payload.get("systemInstruction", [])
|
||||
"generationConfig": request_dict.get("generationConfig", {}),
|
||||
"systemInstruction": request_dict.get("systemInstruction", "")
|
||||
}
|
||||
|
||||
if model.endswith("-image") or model.endswith("-image-generation"):
|
||||
payload.pop("systemInstruction")
|
||||
payload["generationConfig"]["responseModalities"] = ["Text","Image"]
|
||||
return payload
|
||||
|
||||
|
||||
class GeminiChatService:
|
||||
@@ -72,11 +84,31 @@ class GeminiChatService:
|
||||
self.api_client = GeminiApiClient(base_url)
|
||||
self.key_manager = key_manager
|
||||
self.response_handler = GeminiResponseHandler()
|
||||
|
||||
def _extract_text_from_response(self, response: Dict[str, Any]) -> str:
|
||||
"""从响应中提取文本内容"""
|
||||
if not response.get("candidates"):
|
||||
return ""
|
||||
|
||||
candidate = response["candidates"][0]
|
||||
content = candidate.get("content", {})
|
||||
parts = content.get("parts", [])
|
||||
|
||||
if parts and "text" in parts[0]:
|
||||
return parts[0].get("text", "")
|
||||
return ""
|
||||
|
||||
def _create_char_response(self, original_response: Dict[str, Any], text: str) -> Dict[str, Any]:
|
||||
"""创建包含指定文本的响应"""
|
||||
response_copy = json.loads(json.dumps(original_response)) # 深拷贝
|
||||
if response_copy.get("candidates") and response_copy["candidates"][0].get("content", {}).get("parts"):
|
||||
response_copy["candidates"][0]["content"]["parts"][0]["text"] = text
|
||||
return response_copy
|
||||
|
||||
def generate_content(self, model: str, request: GeminiRequest, api_key: str) -> Dict[str, Any]:
|
||||
async def generate_content(self, model: str, request: GeminiRequest, api_key: str) -> Dict[str, Any]:
|
||||
"""生成内容"""
|
||||
payload = _build_payload(model, request)
|
||||
response = self.api_client.generate_content(payload, model, api_key)
|
||||
response = await self.api_client.generate_content(payload, model, api_key)
|
||||
return self.response_handler.handle_response(response, model, stream=False)
|
||||
|
||||
async def stream_generate_content(self, model: str, request: GeminiRequest, api_key: str) -> AsyncGenerator[str, None]:
|
||||
@@ -90,8 +122,21 @@ class GeminiChatService:
|
||||
# print(line)
|
||||
if line.startswith("data:"):
|
||||
line = line[6:]
|
||||
line = json.dumps(self.response_handler.handle_response(json.loads(line), model, stream=True))
|
||||
yield "data: " + line + "\n\n"
|
||||
response_data = self.response_handler.handle_response(json.loads(line), model, stream=True)
|
||||
text = self._extract_text_from_response(response_data)
|
||||
|
||||
# 如果有文本内容,使用流式输出优化器处理
|
||||
if text:
|
||||
# 使用流式输出优化器处理文本输出
|
||||
async for optimized_chunk in gemini_optimizer.optimize_stream_output(
|
||||
text,
|
||||
lambda t: self._create_char_response(response_data, t),
|
||||
lambda c: "data: " + json.dumps(c) + "\n\n"
|
||||
):
|
||||
yield optimized_chunk
|
||||
else:
|
||||
# 如果没有文本内容(如工具调用等),整块输出
|
||||
yield "data: " + json.dumps(response_data) + "\n\n"
|
||||
logger.info("Streaming completed successfully")
|
||||
break
|
||||
except Exception as e:
|
||||
@@ -1,14 +1,17 @@
|
||||
# app/services/chat_service.py
|
||||
|
||||
from copy import deepcopy
|
||||
import json
|
||||
from typing import Dict, Any, AsyncGenerator, List, Union
|
||||
from app.core.logger import get_openai_logger
|
||||
from app.services.chat.response_handler import OpenAIResponseHandler
|
||||
from app.services.chat.api_client import GeminiApiClient
|
||||
from app.schemas.openai_models import ChatRequest, ImageGenerationRequest
|
||||
from app.core.config import settings
|
||||
from app.services.image_create_service import ImageCreateService
|
||||
from app.services.key_manager import KeyManager
|
||||
from typing import Dict, Any, AsyncGenerator, List, Optional, Union
|
||||
from app.logger.logger import get_openai_logger
|
||||
from app.handler.message_converter import OpenAIMessageConverter
|
||||
from app.handler.response_handler import OpenAIResponseHandler
|
||||
from app.service.client.api_client import GeminiApiClient
|
||||
from app.handler.stream_optimizer import openai_optimizer
|
||||
from app.domain.openai_models import ChatRequest, ImageGenerationRequest
|
||||
from app.config.config import settings
|
||||
from app.service.image.image_create_service import ImageCreateService
|
||||
from app.service.key.key_manager import KeyManager
|
||||
|
||||
logger = get_openai_logger()
|
||||
|
||||
@@ -32,12 +35,38 @@ def _build_tools(
|
||||
|
||||
if (
|
||||
settings.TOOLS_CODE_EXECUTION_ENABLED
|
||||
and not (model.endswith("-search") or "-thinking" in model)
|
||||
and not (model.endswith("-search") or "-thinking" in model or model.endswith("-image") or model.endswith("-image-generation"))
|
||||
and not _has_image_parts(messages)
|
||||
):
|
||||
tools.append({"code_execution": {}})
|
||||
if model.endswith("-search"):
|
||||
tools.append({"googleSearch": {}})
|
||||
|
||||
# 将 request 中的 tools 合并到 tools 中
|
||||
if request.tools:
|
||||
function_declarations = []
|
||||
for tool in request.tools:
|
||||
if not tool or not isinstance(tool, dict):
|
||||
continue
|
||||
|
||||
if tool.get("type", "") == "function" and tool.get("function"):
|
||||
function = deepcopy(tool.get("function"))
|
||||
parameters = function.get("parameters", {})
|
||||
if parameters.get("type") == "object" and not parameters.get("properties", {}):
|
||||
function.pop("parameters", None)
|
||||
|
||||
function_declarations.append(function)
|
||||
|
||||
if function_declarations:
|
||||
# 按照 function 的 name 去重
|
||||
names, functions = set(), []
|
||||
for item in function_declarations:
|
||||
if item.get("name") not in names:
|
||||
names.add(item.get("name"))
|
||||
functions.append(item)
|
||||
|
||||
tools.append({"functionDeclarations": functions})
|
||||
|
||||
return tools
|
||||
|
||||
|
||||
@@ -66,10 +95,10 @@ def _get_safety_settings(model: str) -> List[Dict[str, str]]:
|
||||
|
||||
|
||||
def _build_payload(
|
||||
request: ChatRequest, messages: List[Dict[str, Any]]
|
||||
request: ChatRequest, messages: List[Dict[str, Any]], instruction: Optional[Dict[str, Any]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""构建请求payload"""
|
||||
return {
|
||||
payload = {
|
||||
"contents": messages,
|
||||
"generationConfig": {
|
||||
"temperature": request.temperature,
|
||||
@@ -81,17 +110,47 @@ def _build_payload(
|
||||
"tools": _build_tools(request, messages),
|
||||
"safetySettings": _get_safety_settings(request.model),
|
||||
}
|
||||
if request.model.endswith("-image") or request.model.endswith("-image-generation"):
|
||||
payload["generationConfig"]["responseModalities"] = ["Text","Image"]
|
||||
|
||||
if (
|
||||
instruction
|
||||
and isinstance(instruction, dict)
|
||||
and instruction.get("role") == "system"
|
||||
and instruction.get("parts")
|
||||
and not request.model.endswith("-image")
|
||||
and not request.model.endswith("-image-generation")
|
||||
):
|
||||
payload["systemInstruction"] = instruction
|
||||
|
||||
return payload
|
||||
|
||||
|
||||
class OpenAIChatService:
|
||||
"""聊天服务"""
|
||||
|
||||
def __init__(self, base_url: str, key_manager: KeyManager = None):
|
||||
|
||||
self.message_converter = OpenAIMessageConverter()
|
||||
self.response_handler = OpenAIResponseHandler(config=None)
|
||||
self.api_client = GeminiApiClient(base_url)
|
||||
self.key_manager = key_manager
|
||||
self.image_create_service = ImageCreateService()
|
||||
|
||||
def _extract_text_from_openai_chunk(self, chunk: Dict[str, Any]) -> str:
|
||||
"""从OpenAI响应块中提取文本内容"""
|
||||
if not chunk.get("choices"):
|
||||
return ""
|
||||
|
||||
choice = chunk["choices"][0]
|
||||
if "delta" in choice and "content" in choice["delta"]:
|
||||
return choice["delta"]["content"]
|
||||
return ""
|
||||
|
||||
def _create_char_openai_chunk(self, original_chunk: Dict[str, Any], text: str) -> Dict[str, Any]:
|
||||
"""创建包含指定文本的OpenAI响应块"""
|
||||
chunk_copy = json.loads(json.dumps(original_chunk)) # 深拷贝
|
||||
if chunk_copy.get("choices") and "delta" in chunk_copy["choices"][0]:
|
||||
chunk_copy["choices"][0]["delta"]["content"] = text
|
||||
return chunk_copy
|
||||
|
||||
async def create_chat_completion(
|
||||
self,
|
||||
@@ -100,20 +159,20 @@ class OpenAIChatService:
|
||||
) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
|
||||
"""创建聊天完成"""
|
||||
# 转换消息格式
|
||||
messages = self.message_converter.convert(request.messages)
|
||||
messages, instruction = self.message_converter.convert(request.messages)
|
||||
|
||||
# 构建请求payload
|
||||
payload = _build_payload(request, messages)
|
||||
payload = _build_payload(request, messages, instruction)
|
||||
|
||||
if request.stream:
|
||||
return self._handle_stream_completion(request.model, payload, api_key)
|
||||
return self._handle_normal_completion(request.model, payload, api_key)
|
||||
return await self._handle_normal_completion(request.model, payload, api_key)
|
||||
|
||||
def _handle_normal_completion(
|
||||
async def _handle_normal_completion(
|
||||
self, model: str, payload: Dict[str, Any], api_key: str
|
||||
) -> Dict[str, Any]:
|
||||
"""处理普通聊天完成"""
|
||||
response = self.api_client.generate_content(payload, model, api_key)
|
||||
response = await self.api_client.generate_content(payload, model, api_key)
|
||||
return self.response_handler.handle_response(
|
||||
response, model, stream=False, finish_reason="stop"
|
||||
)
|
||||
@@ -136,7 +195,19 @@ class OpenAIChatService:
|
||||
chunk, model, stream=True, finish_reason=None
|
||||
)
|
||||
if openai_chunk:
|
||||
yield f"data: {json.dumps(openai_chunk)}\n\n"
|
||||
# 提取文本内容
|
||||
text = self._extract_text_from_openai_chunk(openai_chunk)
|
||||
if text:
|
||||
# 使用流式输出优化器处理文本输出
|
||||
async for optimized_chunk in openai_optimizer.optimize_stream_output(
|
||||
text,
|
||||
lambda t: self._create_char_openai_chunk(openai_chunk, t),
|
||||
lambda c: f"data: {json.dumps(c)}\n\n"
|
||||
):
|
||||
yield optimized_chunk
|
||||
else:
|
||||
# 如果没有文本内容(如工具调用等),整块输出
|
||||
yield f"data: {json.dumps(openai_chunk)}\n\n"
|
||||
yield f"data: {json.dumps(self.response_handler.handle_response({}, model, stream=True, finish_reason='stop'))}\n\n"
|
||||
yield "data: [DONE]\n\n"
|
||||
logger.info("Streaming completed successfully")
|
||||
@@ -178,7 +249,19 @@ class OpenAIChatService:
|
||||
image_data, model, stream=True, finish_reason=None
|
||||
)
|
||||
if openai_chunk:
|
||||
yield f"data: {json.dumps(openai_chunk)}\n\n"
|
||||
# 提取文本内容
|
||||
text = self._extract_text_from_openai_chunk(openai_chunk)
|
||||
if text:
|
||||
# 使用流式输出优化器处理文本输出
|
||||
async for optimized_chunk in openai_optimizer.optimize_stream_output(
|
||||
text,
|
||||
lambda t: self._create_char_openai_chunk(openai_chunk, t),
|
||||
lambda c: f"data: {json.dumps(c)}\n\n"
|
||||
):
|
||||
yield optimized_chunk
|
||||
else:
|
||||
# 如果没有文本内容(如图片URL等),整块输出
|
||||
yield f"data: {json.dumps(openai_chunk)}\n\n"
|
||||
yield f"data: {json.dumps(self.response_handler.handle_response({}, model, stream=True, finish_reason='stop'))}\n\n"
|
||||
yield "data: [DONE]\n\n"
|
||||
logger.info("Image chat streaming completed successfully")
|
||||
@@ -189,4 +272,4 @@ class OpenAIChatService:
|
||||
|
||||
return self.response_handler.handle_image_chat_response(
|
||||
image_data, model, stream=False, finish_reason="stop"
|
||||
)
|
||||
)
|
||||
@@ -4,6 +4,8 @@ from typing import Dict, Any, AsyncGenerator
|
||||
import httpx
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
from app.core.constants import DEFAULT_TIMEOUT
|
||||
|
||||
|
||||
class ApiClient(ABC):
|
||||
"""API客户端基类"""
|
||||
@@ -20,17 +22,25 @@ class ApiClient(ABC):
|
||||
class GeminiApiClient(ApiClient):
|
||||
"""Gemini API客户端"""
|
||||
|
||||
def __init__(self, base_url: str, timeout: int = 300):
|
||||
def __init__(self, base_url: str, timeout: int = DEFAULT_TIMEOUT):
|
||||
self.base_url = base_url
|
||||
self.timeout = timeout
|
||||
|
||||
def generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> Dict[str, Any]:
|
||||
timeout = httpx.Timeout(self.timeout, read=self.timeout)
|
||||
def _get_real_model(self, model: str) -> str:
|
||||
if model.endswith("-search"):
|
||||
model = model[:-7]
|
||||
with httpx.Client(timeout=timeout) as client:
|
||||
if model.endswith("-image"):
|
||||
model = model[:-6]
|
||||
|
||||
return model
|
||||
|
||||
async def generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> Dict[str, Any]:
|
||||
timeout = httpx.Timeout(self.timeout, read=self.timeout)
|
||||
model = self._get_real_model(model)
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
url = f"{self.base_url}/models/{model}:generateContent?key={api_key}"
|
||||
response = client.post(url, json=payload)
|
||||
response = await client.post(url, json=payload)
|
||||
if response.status_code != 200:
|
||||
error_content = response.text
|
||||
raise Exception(f"API call failed with status code {response.status_code}, {error_content}")
|
||||
@@ -38,8 +48,8 @@ class GeminiApiClient(ApiClient):
|
||||
|
||||
async def stream_generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> AsyncGenerator[str, None]:
|
||||
timeout = httpx.Timeout(self.timeout, read=self.timeout)
|
||||
if model.endswith("-search"):
|
||||
model = model[:-7]
|
||||
model = self._get_real_model(model)
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
url = f"{self.base_url}/models/{model}:streamGenerateContent?alt=sse&key={api_key}"
|
||||
async with client.stream(method="POST", url=url, json=payload) as response:
|
||||
@@ -3,7 +3,7 @@ from typing import Union, List
|
||||
import openai
|
||||
from openai.types import CreateEmbeddingResponse
|
||||
|
||||
from app.core.logger import get_embeddings_logger
|
||||
from app.logger.logger import get_embeddings_logger
|
||||
|
||||
logger = get_embeddings_logger()
|
||||
|
||||
155
app/service/image/image_create_service.py
Normal file
155
app/service/image/image_create_service.py
Normal file
@@ -0,0 +1,155 @@
|
||||
import time
|
||||
import uuid
|
||||
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
import base64
|
||||
|
||||
from app.config.config import settings
|
||||
from app.logger.logger import get_image_create_logger
|
||||
from app.utils.uploader import ImageUploaderFactory
|
||||
from app.domain.openai_models import ImageGenerationRequest
|
||||
from app.core.constants import VALID_IMAGE_RATIOS
|
||||
|
||||
logger = get_image_create_logger()
|
||||
|
||||
|
||||
class ImageCreateService:
|
||||
def __init__(self, aspect_ratio="1:1"):
|
||||
self.image_model = settings.CREATE_IMAGE_MODEL
|
||||
self.paid_key = settings.PAID_KEY
|
||||
self.aspect_ratio = aspect_ratio
|
||||
|
||||
def parse_prompt_parameters(self, prompt: str) -> tuple:
|
||||
"""从prompt中解析参数
|
||||
支持的格式:
|
||||
- {n:数量} 例如: {n:2} 生成2张图片
|
||||
- {ratio:比例} 例如: {ratio:16:9} 使用16:9比例
|
||||
"""
|
||||
import re
|
||||
|
||||
# 默认值
|
||||
n = 1
|
||||
aspect_ratio = self.aspect_ratio
|
||||
|
||||
# 解析n参数
|
||||
n_match = re.search(r'{n:(\d+)}', prompt)
|
||||
if n_match:
|
||||
n = int(n_match.group(1))
|
||||
if n < 1 or n > 4:
|
||||
raise ValueError(f"Invalid n value: {n}. Must be between 1 and 4.")
|
||||
prompt = prompt.replace(n_match.group(0), '').strip()
|
||||
|
||||
# 解析ratio参数
|
||||
ratio_match = re.search(r'{ratio:(\d+:\d+)}', prompt)
|
||||
if ratio_match:
|
||||
aspect_ratio = ratio_match.group(1)
|
||||
if aspect_ratio not in VALID_IMAGE_RATIOS:
|
||||
raise ValueError(
|
||||
f"Invalid ratio: {aspect_ratio}. Must be one of: {', '.join(VALID_IMAGE_RATIOS)}"
|
||||
)
|
||||
prompt = prompt.replace(ratio_match.group(0), '').strip()
|
||||
|
||||
return prompt, n, aspect_ratio
|
||||
|
||||
def generate_images(self, request: ImageGenerationRequest):
|
||||
client = genai.Client(api_key=self.paid_key)
|
||||
|
||||
if request.size == "1024x1024":
|
||||
self.aspect_ratio = "1:1"
|
||||
elif request.size == "1792x1024":
|
||||
self.aspect_ratio = "16:9"
|
||||
elif request.size == "1027x1792":
|
||||
self.aspect_ratio = "9:16"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid size: {request.size}. Supported sizes are 1024x1024, 1792x1024, and 1024x1792."
|
||||
)
|
||||
|
||||
# 解析prompt中的参数
|
||||
cleaned_prompt, prompt_n, prompt_ratio = self.parse_prompt_parameters(request.prompt)
|
||||
request.prompt = cleaned_prompt
|
||||
|
||||
# 如果prompt中指定了n,则覆盖请求中的n
|
||||
if prompt_n > 1:
|
||||
request.n = prompt_n
|
||||
|
||||
# 如果prompt中指定了ratio,则覆盖默认的aspect_ratio
|
||||
if prompt_ratio != self.aspect_ratio:
|
||||
self.aspect_ratio = prompt_ratio
|
||||
|
||||
response = client.models.generate_images(
|
||||
model=self.image_model,
|
||||
prompt=request.prompt,
|
||||
config=types.GenerateImagesConfig(
|
||||
number_of_images=request.n,
|
||||
output_mime_type="image/png",
|
||||
aspect_ratio=self.aspect_ratio,
|
||||
safety_filter_level="BLOCK_LOW_AND_ABOVE",
|
||||
person_generation="ALLOW_ADULT",
|
||||
# language="auto"
|
||||
),
|
||||
)
|
||||
|
||||
if response.generated_images:
|
||||
images_data = []
|
||||
for index, generated_image in enumerate(response.generated_images):
|
||||
image_data = generated_image.image.image_bytes
|
||||
image_uploader = None
|
||||
|
||||
if request.response_format == "b64_json":
|
||||
base64_image = base64.b64encode(image_data).decode('utf-8')
|
||||
images_data.append({
|
||||
"b64_json": base64_image,
|
||||
"revised_prompt": request.prompt
|
||||
})
|
||||
else:
|
||||
current_date = time.strftime("%Y/%m/%d")
|
||||
filename = f"{current_date}/{uuid.uuid4().hex[:8]}.png"
|
||||
|
||||
if settings.UPLOAD_PROVIDER == "smms":
|
||||
image_uploader = ImageUploaderFactory.create(
|
||||
provider=settings.UPLOAD_PROVIDER,
|
||||
api_key=settings.SMMS_SECRET_TOKEN
|
||||
)
|
||||
elif settings.UPLOAD_PROVIDER == "picgo":
|
||||
image_uploader = ImageUploaderFactory.create(
|
||||
provider=settings.UPLOAD_PROVIDER,
|
||||
api_key=settings.PICGO_API_KEY
|
||||
)
|
||||
elif settings.UPLOAD_PROVIDER == "cloudflare_imgbed":
|
||||
image_uploader = ImageUploaderFactory.create(
|
||||
provider=settings.UPLOAD_PROVIDER,
|
||||
base_url=settings.CLOUDFLARE_IMGBED_URL,
|
||||
auth_code=settings.CLOUDFLARE_IMGBED_AUTH_CODE
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unsupported upload provider: {settings.UPLOAD_PROVIDER}")
|
||||
|
||||
upload_response = image_uploader.upload(image_data, filename)
|
||||
|
||||
images_data.append({
|
||||
"url": f"{upload_response.data.url}",
|
||||
"revised_prompt": request.prompt
|
||||
})
|
||||
|
||||
response_data = {
|
||||
"created": int(time.time()), # Current timestamp
|
||||
"data": images_data
|
||||
}
|
||||
return response_data
|
||||
else:
|
||||
raise Exception("I can't generate these images")
|
||||
|
||||
def generate_images_chat(self, request: ImageGenerationRequest) -> str:
|
||||
response = self.generate_images(request)
|
||||
image_datas = response["data"]
|
||||
if image_datas:
|
||||
markdown_images = []
|
||||
for index, image_data in enumerate(image_datas):
|
||||
if 'url' in image_data:
|
||||
markdown_images.append(f"")
|
||||
else:
|
||||
# 如果是base64格式,创建data URL
|
||||
markdown_images.append(f"")
|
||||
return "\n".join(markdown_images)
|
||||
@@ -1,8 +1,9 @@
|
||||
import asyncio
|
||||
from itertools import cycle
|
||||
from typing import Dict
|
||||
from app.core.logger import get_key_manager_logger
|
||||
from app.core.config import settings
|
||||
from app.logger.logger import get_key_manager_logger
|
||||
from app.config.config import settings
|
||||
|
||||
|
||||
logger = get_key_manager_logger()
|
||||
|
||||
@@ -61,20 +62,44 @@ class KeyManager:
|
||||
|
||||
return await self.get_next_working_key()
|
||||
|
||||
def get_fail_count(self, key: str) -> int:
|
||||
"""获取指定密钥的失败次数"""
|
||||
return self.key_failure_counts.get(key, 0)
|
||||
|
||||
async def get_keys_by_status(self) -> dict:
|
||||
"""获取分类后的API key列表"""
|
||||
valid_keys = []
|
||||
invalid_keys = []
|
||||
"""获取分类后的API key列表,包括失败次数"""
|
||||
valid_keys = {}
|
||||
invalid_keys = {}
|
||||
|
||||
async with self.failure_count_lock:
|
||||
for key in self.api_keys:
|
||||
masked_key = f"{key}"
|
||||
if self.key_failure_counts[key] < self.MAX_FAILURES:
|
||||
valid_keys.append(masked_key)
|
||||
fail_count = self.key_failure_counts[key]
|
||||
if fail_count < self.MAX_FAILURES:
|
||||
valid_keys[key] = fail_count
|
||||
else:
|
||||
invalid_keys.append(masked_key)
|
||||
invalid_keys[key] = fail_count
|
||||
|
||||
return {
|
||||
"valid_keys": valid_keys,
|
||||
"invalid_keys": invalid_keys
|
||||
}
|
||||
|
||||
|
||||
_singleton_instance = None
|
||||
_singleton_lock = asyncio.Lock()
|
||||
|
||||
async def get_key_manager_instance(api_keys: list = None) -> KeyManager:
|
||||
"""
|
||||
获取 KeyManager 单例实例。
|
||||
|
||||
如果尚未创建实例,将使用提供的 api_keys 初始化 KeyManager。
|
||||
如果已创建实例,则忽略 api_keys 参数,返回现有单例。
|
||||
"""
|
||||
global _singleton_instance
|
||||
|
||||
async with _singleton_lock:
|
||||
if _singleton_instance is None:
|
||||
if api_keys is None:
|
||||
raise ValueError("API keys are required to initialize the KeyManager")
|
||||
_singleton_instance = KeyManager(api_keys)
|
||||
return _singleton_instance
|
||||
@@ -1,15 +1,17 @@
|
||||
import requests
|
||||
from datetime import datetime, timezone
|
||||
from typing import Optional, Dict, Any
|
||||
from app.core.logger import get_model_logger
|
||||
from app.core.config import settings
|
||||
from app.logger.logger import get_model_logger
|
||||
from app.config.config import settings
|
||||
|
||||
logger = get_model_logger()
|
||||
|
||||
class ModelService:
|
||||
def __init__(self, model_search: list):
|
||||
self.model_search = model_search
|
||||
self.base_url = "https://generativelanguage.googleapis.com/v1beta"
|
||||
def __init__(self, search_models: list, image_models: list):
|
||||
self.search_models = search_models
|
||||
self.image_models = image_models
|
||||
self.base_url = settings.BASE_URL
|
||||
self.filtered_models = settings.FILTERED_MODELS
|
||||
|
||||
def get_gemini_models(self, api_key: str) -> Optional[Dict[str, Any]]:
|
||||
url = f"{self.base_url}/models?key={api_key}"
|
||||
@@ -18,6 +20,16 @@ class ModelService:
|
||||
response = requests.get(url)
|
||||
if response.status_code == 200:
|
||||
gemini_models = response.json()
|
||||
|
||||
filtered_models_list = []
|
||||
for model in gemini_models.get("models", []):
|
||||
model_id = model["name"].split("/")[-1]
|
||||
if model_id not in self.filtered_models:
|
||||
filtered_models_list.append(model)
|
||||
else:
|
||||
logger.info(f"Filtered out model: {model_id}")
|
||||
|
||||
gemini_models["models"] = filtered_models_list
|
||||
return gemini_models
|
||||
else:
|
||||
logger.error(f"Error: {response.status_code}")
|
||||
@@ -52,15 +64,32 @@ class ModelService:
|
||||
"parent": None,
|
||||
}
|
||||
openai_format["data"].append(openai_model)
|
||||
|
||||
if settings.CREATE_IMAGE_MODEL:
|
||||
image_model = openai_model.copy()
|
||||
image_model["id"] = f"{settings.CREATE_IMAGE_MODEL}-chat"
|
||||
openai_format["data"].append(image_model)
|
||||
|
||||
if model_id in self.model_search:
|
||||
if model_id in self.search_models:
|
||||
search_model = openai_model.copy()
|
||||
search_model["id"] = f"{model_id}-search"
|
||||
openai_format["data"].append(search_model)
|
||||
if model_id in self.image_models:
|
||||
image_model = openai_model.copy()
|
||||
image_model["id"] = f"{model_id}-image"
|
||||
openai_format["data"].append(image_model)
|
||||
|
||||
if settings.CREATE_IMAGE_MODEL:
|
||||
image_model = openai_model.copy()
|
||||
image_model["id"] = f"{settings.CREATE_IMAGE_MODEL}-chat"
|
||||
openai_format["data"].append(image_model)
|
||||
return openai_format
|
||||
|
||||
def check_model_support(self, model: str) -> bool:
|
||||
if not model or not isinstance(model, str):
|
||||
return False
|
||||
|
||||
model = model.strip()
|
||||
if model.endswith("-search"):
|
||||
model = model[:-7]
|
||||
return model in self.search_models
|
||||
if model.endswith("-image"):
|
||||
model = model[:-6]
|
||||
return model in self.image_models
|
||||
|
||||
return model not in self.filtered_models
|
||||
@@ -1,53 +0,0 @@
|
||||
# app/services/chat/message_converter.py
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import List, Dict, Any
|
||||
|
||||
|
||||
class MessageConverter(ABC):
|
||||
"""消息转换器基类"""
|
||||
|
||||
@abstractmethod
|
||||
def convert(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
|
||||
pass
|
||||
|
||||
|
||||
def _convert_image(image_url: str) -> Dict[str, Any]:
|
||||
if image_url.startswith("data:image"):
|
||||
return {
|
||||
"inline_data": {
|
||||
"mime_type": "image/jpeg",
|
||||
"data": image_url.split(",")[1]
|
||||
}
|
||||
}
|
||||
return {
|
||||
"image_url": {
|
||||
"url": image_url
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
class OpenAIMessageConverter(MessageConverter):
|
||||
"""OpenAI消息格式转换器"""
|
||||
|
||||
def convert(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
|
||||
converted_messages = []
|
||||
for msg in messages:
|
||||
role = "user" if msg["role"] == "user" else "model"
|
||||
parts = []
|
||||
|
||||
if isinstance(msg["content"], str):
|
||||
parts.append({"text": msg["content"]})
|
||||
elif isinstance(msg["content"], list):
|
||||
for content in msg["content"]:
|
||||
if isinstance(content, str):
|
||||
parts.append({"text": content})
|
||||
elif isinstance(content, dict):
|
||||
if content["type"] == "text":
|
||||
parts.append({"text": content["text"]})
|
||||
elif content["type"] == "image_url":
|
||||
parts.append(_convert_image(content["image_url"]["url"]))
|
||||
|
||||
converted_messages.append({"role": role, "parts": parts})
|
||||
|
||||
return converted_messages
|
||||
@@ -1,81 +0,0 @@
|
||||
import time
|
||||
import uuid
|
||||
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
import base64
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logger import get_image_create_logger
|
||||
from app.core.uploader import ImageUploaderFactory
|
||||
from app.schemas.openai_models import ImageGenerationRequest
|
||||
|
||||
logger = get_image_create_logger()
|
||||
|
||||
|
||||
class ImageCreateService:
|
||||
def __init__(self, aspect_ratio="1:1"):
|
||||
self.image_model = settings.CREATE_IMAGE_MODEL
|
||||
self.paid_key = settings.PAID_KEY
|
||||
self.aspect_ratio = aspect_ratio
|
||||
|
||||
def generate_images(self, request: ImageGenerationRequest):
|
||||
client = genai.Client(api_key=self.paid_key)
|
||||
if request.size == "1024x1024":
|
||||
self.aspect_ratio = "1:1"
|
||||
elif request.size == "1792x1024":
|
||||
self.aspect_ratio = "16:9"
|
||||
elif request.size == "1027x1792":
|
||||
self.aspect_ratio = "9:16"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid size: {request.size}. Supported sizes are 1024x1024, 1792x1024, and 1024x1792."
|
||||
)
|
||||
|
||||
response = client.models.generate_images(
|
||||
model=self.image_model,
|
||||
prompt=request.prompt,
|
||||
config=types.GenerateImagesConfig(
|
||||
number_of_images=request.n,
|
||||
output_mime_type="image/png",
|
||||
aspect_ratio=self.aspect_ratio,
|
||||
safety_filter_level="BLOCK_LOW_AND_ABOVE",
|
||||
person_generation="ALLOW_ADULT",
|
||||
# language="auto"
|
||||
),
|
||||
)
|
||||
|
||||
if response.generated_images:
|
||||
images_data = []
|
||||
for index, generated_image in enumerate(response.generated_images):
|
||||
image_data = generated_image.image.image_bytes
|
||||
image_uploader = None
|
||||
if settings.UPLOAD_PROVIDER == "smms":
|
||||
image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,api_key=settings.SMMS_SECRET_TOKEN)
|
||||
current_date = time.strftime("%Y/%m/%d")
|
||||
filename = f"{current_date}/{uuid.uuid4().hex[:8]}.png"
|
||||
upload_response = image_uploader.upload(image_data,filename)
|
||||
|
||||
# base64_image = base64.b64encode(image_data).decode('utf-8')
|
||||
images_data.append({
|
||||
"url": f"{upload_response.data.url}",
|
||||
"revised_prompt": request.prompt
|
||||
})
|
||||
|
||||
response_data = {
|
||||
"created": int(time.time()), # Current timestamp
|
||||
"data": images_data
|
||||
}
|
||||
return response_data
|
||||
else:
|
||||
raise Exception("I can't generate these images")
|
||||
|
||||
def generate_images_chat(self, request: ImageGenerationRequest) -> str:
|
||||
response = self.generate_images(request)
|
||||
image_datas = response["data"]
|
||||
if image_datas:
|
||||
markdown_images = []
|
||||
for index, image_data in enumerate(image_datas):
|
||||
markdown_images.append(f"")
|
||||
return "\n".join(markdown_images)
|
||||
|
||||
249
app/static/css/auth.css
Normal file
249
app/static/css/auth.css
Normal file
@@ -0,0 +1,249 @@
|
||||
body {
|
||||
font-family: 'Roboto', sans-serif;
|
||||
line-height: 1.6;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
min-height: 100vh;
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 400px;
|
||||
width: 90%;
|
||||
background: rgba(255, 255, 255, 0.95);
|
||||
padding: 40px;
|
||||
border-radius: 20px;
|
||||
box-shadow: 0 15px 35px rgba(0,0,0,0.2);
|
||||
backdrop-filter: blur(10px);
|
||||
transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
|
||||
}
|
||||
|
||||
.container:hover {
|
||||
transform: translateY(-5px);
|
||||
box-shadow: 0 20px 40px rgba(0,0,0,0.25);
|
||||
}
|
||||
|
||||
.logo {
|
||||
text-align: center;
|
||||
margin-bottom: 30px;
|
||||
animation: fadeIn 1s ease;
|
||||
}
|
||||
|
||||
.logo i {
|
||||
font-size: 48px;
|
||||
color: #764ba2;
|
||||
margin-bottom: 15px;
|
||||
}
|
||||
|
||||
h2 {
|
||||
color: #2c3e50;
|
||||
text-align: center;
|
||||
margin-bottom: 30px;
|
||||
font-weight: 700;
|
||||
font-size: 24px;
|
||||
animation: slideDown 0.5s ease;
|
||||
}
|
||||
|
||||
form {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 20px;
|
||||
}
|
||||
|
||||
.input-group {
|
||||
position: relative;
|
||||
animation: slideUp 0.5s ease;
|
||||
}
|
||||
|
||||
.input-group i {
|
||||
position: absolute;
|
||||
left: 12px;
|
||||
top: 50%;
|
||||
transform: translateY(-50%);
|
||||
color: #764ba2;
|
||||
font-size: 18px;
|
||||
}
|
||||
|
||||
input {
|
||||
width: 100%;
|
||||
padding: 12px 12px 12px 40px;
|
||||
border: 2px solid #e0e0e0;
|
||||
border-radius: 10px;
|
||||
font-size: 16px;
|
||||
box-sizing: border-box;
|
||||
transition: all 0.3s ease;
|
||||
background: rgba(255, 255, 255, 0.9);
|
||||
}
|
||||
|
||||
input:focus {
|
||||
border-color: #764ba2;
|
||||
box-shadow: 0 0 10px rgba(118, 75, 162, 0.2);
|
||||
outline: none;
|
||||
}
|
||||
|
||||
button {
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: white;
|
||||
border: none;
|
||||
padding: 14px;
|
||||
border-radius: 10px;
|
||||
cursor: pointer;
|
||||
font-size: 16px;
|
||||
font-weight: bold;
|
||||
transition: all 0.3s ease;
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
button:hover {
|
||||
transform: translateY(-2px);
|
||||
box-shadow: 0 5px 15px rgba(118, 75, 162, 0.3);
|
||||
}
|
||||
|
||||
button:active {
|
||||
transform: translateY(0);
|
||||
}
|
||||
|
||||
button::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
width: 0;
|
||||
height: 0;
|
||||
background: rgba(255, 255, 255, 0.2);
|
||||
border-radius: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
transition: width 0.6s, height 0.6s;
|
||||
}
|
||||
|
||||
button:active::after {
|
||||
width: 200px;
|
||||
height: 200px;
|
||||
opacity: 0;
|
||||
}
|
||||
|
||||
.error-message {
|
||||
color: #e74c3c;
|
||||
margin-top: 15px;
|
||||
text-align: center;
|
||||
font-weight: bold;
|
||||
padding: 10px;
|
||||
border-radius: 5px;
|
||||
background: rgba(231, 76, 60, 0.1);
|
||||
animation: shake 0.5s ease;
|
||||
}
|
||||
|
||||
.copyright {
|
||||
position: fixed;
|
||||
bottom: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
background: rgba(255, 255, 255, 0.9);
|
||||
padding: 10px 0;
|
||||
text-align: center;
|
||||
font-size: 14px;
|
||||
color: #2c3e50;
|
||||
backdrop-filter: blur(5px);
|
||||
border-top: 1px solid rgba(0,0,0,0.1);
|
||||
}
|
||||
|
||||
.copyright a {
|
||||
color: #764ba2;
|
||||
text-decoration: none;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.copyright a:hover {
|
||||
color: #667eea;
|
||||
}
|
||||
|
||||
.copyright img {
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
border-radius: 50%;
|
||||
vertical-align: middle;
|
||||
margin-right: 5px;
|
||||
}
|
||||
|
||||
@keyframes fadeIn {
|
||||
from { opacity: 0; }
|
||||
to { opacity: 1; }
|
||||
}
|
||||
|
||||
@keyframes slideDown {
|
||||
from { transform: translateY(-20px); opacity: 0; }
|
||||
to { transform: translateY(0); opacity: 1; }
|
||||
}
|
||||
|
||||
@keyframes slideUp {
|
||||
from { transform: translateY(20px); opacity: 0; }
|
||||
to { transform: translateY(0); opacity: 1; }
|
||||
}
|
||||
|
||||
@keyframes shake {
|
||||
0%, 100% { transform: translateX(0); }
|
||||
25% { transform: translateX(-5px); }
|
||||
75% { transform: translateX(5px); }
|
||||
}
|
||||
|
||||
@media (max-width: 768px) {
|
||||
.container {
|
||||
width: 85%;
|
||||
padding: 30px;
|
||||
}
|
||||
.logo i {
|
||||
font-size: 40px;
|
||||
}
|
||||
h2 {
|
||||
font-size: 22px;
|
||||
}
|
||||
input {
|
||||
padding: 10px 10px 10px 35px;
|
||||
font-size: 15px;
|
||||
}
|
||||
.input-group i {
|
||||
font-size: 16px;
|
||||
}
|
||||
button {
|
||||
padding: 12px;
|
||||
font-size: 15px;
|
||||
}
|
||||
}
|
||||
|
||||
@media (max-width: 480px) {
|
||||
.container {
|
||||
width: 90%;
|
||||
padding: 25px;
|
||||
}
|
||||
.logo i {
|
||||
font-size: 36px;
|
||||
}
|
||||
h2 {
|
||||
font-size: 20px;
|
||||
margin-bottom: 25px;
|
||||
}
|
||||
form {
|
||||
gap: 15px;
|
||||
}
|
||||
input {
|
||||
padding: 10px 10px 10px 32px;
|
||||
font-size: 14px;
|
||||
}
|
||||
.input-group i {
|
||||
font-size: 15px;
|
||||
left: 10px;
|
||||
}
|
||||
button {
|
||||
padding: 10px;
|
||||
font-size: 14px;
|
||||
}
|
||||
.error-message {
|
||||
font-size: 14px;
|
||||
padding: 8px;
|
||||
margin-top: 12px;
|
||||
}
|
||||
}
|
||||
461
app/static/css/keys_status.css
Normal file
461
app/static/css/keys_status.css
Normal file
@@ -0,0 +1,461 @@
|
||||
body {
|
||||
font-family: 'Roboto', sans-serif;
|
||||
line-height: 1.6;
|
||||
margin: 0;
|
||||
padding: 20px;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
min-height: 100vh;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 900px;
|
||||
width: 95%;
|
||||
background: rgba(255, 255, 255, 0.95);
|
||||
padding: 40px;
|
||||
border-radius: 20px;
|
||||
box-shadow: 0 15px 35px rgba(0,0,0,0.2);
|
||||
backdrop-filter: blur(10px);
|
||||
position: relative;
|
||||
margin: 20px auto;
|
||||
overflow-y: auto;
|
||||
max-height: calc(100vh - 40px);
|
||||
scrollbar-width: none;
|
||||
-ms-overflow-style: none;
|
||||
}
|
||||
|
||||
.container::-webkit-scrollbar {
|
||||
display: none;
|
||||
}
|
||||
|
||||
h1 {
|
||||
color: #2c3e50;
|
||||
text-align: center;
|
||||
margin-bottom: 30px;
|
||||
font-weight: 700;
|
||||
font-size: 32px;
|
||||
position: relative;
|
||||
padding-bottom: 15px;
|
||||
}
|
||||
|
||||
h1::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
bottom: 0;
|
||||
left: 50%;
|
||||
transform: translateX(-50%);
|
||||
width: 100px;
|
||||
height: 4px;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
border-radius: 2px;
|
||||
}
|
||||
|
||||
.key-list {
|
||||
margin-bottom: 30px;
|
||||
background: rgba(248, 249, 250, 0.9);
|
||||
padding: 25px;
|
||||
border-radius: 15px;
|
||||
transition: all 0.3s ease;
|
||||
border: 1px solid rgba(0,0,0,0.1);
|
||||
animation: fadeIn 0.5s ease forwards;
|
||||
}
|
||||
|
||||
.key-list:hover {
|
||||
transform: translateY(-5px);
|
||||
box-shadow: 0 10px 20px rgba(0,0,0,0.1);
|
||||
}
|
||||
|
||||
.key-list:nth-child(2) {
|
||||
animation-delay: 0.2s;
|
||||
}
|
||||
|
||||
.key-list h2 {
|
||||
color: #2c3e50;
|
||||
margin-bottom: 20px;
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
font-size: 1.5em;
|
||||
padding-bottom: 10px;
|
||||
border-bottom: 2px solid rgba(0,0,0,0.1);
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.key-list h2 .toggle-icon {
|
||||
margin-right: 10px;
|
||||
transition: transform 0.3s ease;
|
||||
}
|
||||
|
||||
.key-list h2 .toggle-icon.collapsed {
|
||||
transform: rotate(-90deg);
|
||||
}
|
||||
|
||||
.key-list .key-content {
|
||||
transition: all 0.3s ease-out;
|
||||
overflow: hidden;
|
||||
height: auto;
|
||||
opacity: 1;
|
||||
}
|
||||
|
||||
.key-list .key-content.collapsed {
|
||||
height: 0;
|
||||
opacity: 0;
|
||||
padding-top: 0;
|
||||
padding-bottom: 0;
|
||||
}
|
||||
|
||||
ul {
|
||||
list-style-type: none;
|
||||
padding: 0;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
li {
|
||||
background: white;
|
||||
border: 1px solid rgba(0,0,0,0.1);
|
||||
margin-bottom: 12px;
|
||||
padding: 15px;
|
||||
border-radius: 10px;
|
||||
transition: all 0.3s ease;
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
box-shadow: 0 2px 5px rgba(0,0,0,0.05);
|
||||
}
|
||||
|
||||
li:hover {
|
||||
transform: translateX(5px);
|
||||
box-shadow: 0 5px 15px rgba(0,0,0,0.1);
|
||||
}
|
||||
|
||||
.key-info {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 15px;
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
.key-text {
|
||||
font-family: 'Roboto Mono', monospace;
|
||||
color: #2c3e50;
|
||||
}
|
||||
|
||||
.fail-count {
|
||||
background: rgba(231, 76, 60, 0.1);
|
||||
color: #e74c3c;
|
||||
padding: 4px 10px;
|
||||
border-radius: 15px;
|
||||
font-size: 0.85em;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 5px;
|
||||
}
|
||||
|
||||
.fail-count i {
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.key-actions {
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
align-items: center;
|
||||
}
|
||||
|
||||
.verify-btn, .copy-btn {
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: white;
|
||||
border: none;
|
||||
padding: 8px 15px;
|
||||
border-radius: 8px;
|
||||
cursor: pointer;
|
||||
font-size: 14px;
|
||||
font-weight: bold;
|
||||
transition: all 0.3s ease;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 5px;
|
||||
}
|
||||
|
||||
.verify-btn {
|
||||
background: linear-gradient(135deg, #2ecc71, #27ae60);
|
||||
}
|
||||
|
||||
.verify-btn:hover {
|
||||
transform: translateY(-2px);
|
||||
box-shadow: 0 5px 15px rgba(46, 204, 113, 0.3);
|
||||
}
|
||||
|
||||
.verify-btn:disabled {
|
||||
opacity: 0.7;
|
||||
cursor: not-allowed;
|
||||
transform: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
.verify-btn i {
|
||||
font-size: 14px;
|
||||
}
|
||||
|
||||
.copy-btn:hover {
|
||||
transform: translateY(-2px);
|
||||
box-shadow: 0 5px 15px rgba(118, 75, 162, 0.3);
|
||||
}
|
||||
|
||||
.copy-btn:active {
|
||||
transform: translateY(0);
|
||||
}
|
||||
|
||||
.copy-btn i {
|
||||
font-size: 14px;
|
||||
}
|
||||
|
||||
.total {
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: white;
|
||||
padding: 15px 25px;
|
||||
border-radius: 10px;
|
||||
font-weight: bold;
|
||||
text-align: center;
|
||||
font-size: 1.2em;
|
||||
margin-top: 30px;
|
||||
box-shadow: 0 5px 15px rgba(0,0,0,0.1);
|
||||
}
|
||||
|
||||
#copyStatus {
|
||||
position: fixed;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
padding: 15px 30px;
|
||||
border-radius: 25px;
|
||||
font-weight: bold;
|
||||
opacity: 0;
|
||||
transition: all 0.3s ease;
|
||||
backdrop-filter: blur(5px);
|
||||
box-shadow: 0 5px 15px rgba(0,0,0,0.2);
|
||||
z-index: 1000;
|
||||
text-align: center;
|
||||
min-width: 200px;
|
||||
color: white;
|
||||
}
|
||||
|
||||
#copyStatus.success {
|
||||
background: rgba(39, 174, 96, 0.95);
|
||||
}
|
||||
|
||||
#copyStatus.error {
|
||||
background: rgba(231, 76, 60, 0.95);
|
||||
}
|
||||
|
||||
.status-badge {
|
||||
padding: 4px 12px;
|
||||
border-radius: 15px;
|
||||
font-size: 0.9em;
|
||||
font-weight: bold;
|
||||
margin-right: 10px;
|
||||
}
|
||||
|
||||
.status-valid {
|
||||
background: rgba(39, 174, 96, 0.1);
|
||||
color: #27ae60;
|
||||
}
|
||||
|
||||
.status-invalid {
|
||||
background: rgba(231, 76, 60, 0.1);
|
||||
color: #e74c3c;
|
||||
}
|
||||
|
||||
.scroll-buttons {
|
||||
position: fixed;
|
||||
right: 20px;
|
||||
bottom: 20px;
|
||||
display: none;
|
||||
flex-direction: column;
|
||||
gap: 10px;
|
||||
z-index: 1000;
|
||||
}
|
||||
|
||||
.scroll-btn {
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: white;
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
border: none;
|
||||
border-radius: 50%;
|
||||
cursor: pointer;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
font-size: 20px;
|
||||
transition: all 0.3s ease;
|
||||
backdrop-filter: blur(5px);
|
||||
box-shadow: 0 2px 10px rgba(0,0,0,0.2);
|
||||
}
|
||||
|
||||
.scroll-btn:hover {
|
||||
background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
|
||||
transform: scale(1.1);
|
||||
}
|
||||
|
||||
.scroll-btn:active {
|
||||
transform: scale(0.95);
|
||||
}
|
||||
|
||||
.refresh-btn {
|
||||
position: fixed;
|
||||
top: 20px;
|
||||
right: 20px;
|
||||
z-index: 1000;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
color: #fff;
|
||||
border: none;
|
||||
padding: 10px 20px;
|
||||
border-radius: 25px;
|
||||
cursor: pointer;
|
||||
font-size: 14px;
|
||||
font-weight: bold;
|
||||
transition: all 0.3s ease;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
gap: 8px;
|
||||
box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
|
||||
.refresh-btn:hover {
|
||||
transform: scale(1.05);
|
||||
box-shadow: 0 8px 20px rgba(118, 75, 162, 0.3);
|
||||
background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
|
||||
}
|
||||
|
||||
.refresh-btn:active {
|
||||
transform: scale(0.95);
|
||||
}
|
||||
|
||||
.refresh-btn i {
|
||||
transition: transform 0.5s ease;
|
||||
}
|
||||
|
||||
.refresh-btn.loading i {
|
||||
animation: spin 1s linear infinite;
|
||||
}
|
||||
|
||||
.copyright {
|
||||
position: fixed;
|
||||
bottom: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
background: rgba(255, 255, 255, 0.9);
|
||||
padding: 10px 0;
|
||||
text-align: center;
|
||||
font-size: 14px;
|
||||
color: #2c3e50;
|
||||
backdrop-filter: blur(5px);
|
||||
border-top: 1px solid rgba(0,0,0,0.1);
|
||||
}
|
||||
|
||||
.copyright a {
|
||||
color: #764ba2;
|
||||
text-decoration: none;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.copyright a:hover {
|
||||
color: #667eea;
|
||||
}
|
||||
|
||||
.copyright img {
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
border-radius: 50%;
|
||||
vertical-align: middle;
|
||||
margin-right: 5px;
|
||||
}
|
||||
|
||||
@keyframes fadeIn {
|
||||
from { opacity: 0; transform: translateY(20px); }
|
||||
to { opacity: 1; transform: translateY(0); }
|
||||
}
|
||||
|
||||
@keyframes spin {
|
||||
from { transform: rotate(0deg); }
|
||||
to { transform: rotate(360deg); }
|
||||
}
|
||||
|
||||
@media (max-width: 768px) {
|
||||
.container {
|
||||
width: 100%;
|
||||
padding: 20px;
|
||||
margin: 10px auto;
|
||||
}
|
||||
body {
|
||||
padding: 10px;
|
||||
}
|
||||
h1 {
|
||||
font-size: 24px;
|
||||
}
|
||||
.key-list h2 {
|
||||
font-size: 1.2em;
|
||||
flex-direction: column;
|
||||
gap: 10px;
|
||||
align-items: flex-start;
|
||||
}
|
||||
.key-info {
|
||||
flex-direction: column;
|
||||
align-items: flex-start;
|
||||
gap: 8px;
|
||||
}
|
||||
li {
|
||||
flex-direction: column;
|
||||
gap: 10px;
|
||||
}
|
||||
.key-actions {
|
||||
width: 100%;
|
||||
flex-direction: column;
|
||||
}
|
||||
|
||||
.verify-btn, .copy-btn {
|
||||
width: 100%;
|
||||
justify-content: center;
|
||||
}
|
||||
.key-text {
|
||||
word-break: break-all;
|
||||
}
|
||||
.scroll-buttons {
|
||||
right: 10px;
|
||||
bottom: 10px;
|
||||
}
|
||||
.scroll-btn {
|
||||
width: 35px;
|
||||
height: 35px;
|
||||
font-size: 16px;
|
||||
}
|
||||
.refresh-btn {
|
||||
top: 10px;
|
||||
right: 10px;
|
||||
padding: 8px 16px;
|
||||
font-size: 12px;
|
||||
}
|
||||
}
|
||||
|
||||
@media (max-width: 480px) {
|
||||
.container {
|
||||
padding: 15px;
|
||||
}
|
||||
h1 {
|
||||
font-size: 20px;
|
||||
}
|
||||
.key-list {
|
||||
padding: 15px;
|
||||
}
|
||||
.status-badge {
|
||||
padding: 3px 8px;
|
||||
font-size: 0.8em;
|
||||
}
|
||||
.fail-count {
|
||||
font-size: 0.8em;
|
||||
}
|
||||
.total {
|
||||
font-size: 1em;
|
||||
padding: 12px 20px;
|
||||
}
|
||||
}
|
||||
BIN
app/static/icons/icon-192x192.png
Normal file
BIN
app/static/icons/icon-192x192.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 25 KiB |
18
app/static/js/auth.js
Normal file
18
app/static/js/auth.js
Normal file
@@ -0,0 +1,18 @@
|
||||
if ('serviceWorker' in navigator) {
|
||||
window.addEventListener('load', () => {
|
||||
navigator.serviceWorker.register('/static/service-worker.js')
|
||||
.then(registration => {
|
||||
console.log('ServiceWorker注册成功:', registration.scope);
|
||||
})
|
||||
.catch(error => {
|
||||
console.log('ServiceWorker注册失败:', error);
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
document.addEventListener('DOMContentLoaded', () => {
|
||||
const copyrightYear = document.querySelector('.copyright script');
|
||||
if (copyrightYear) {
|
||||
copyrightYear.textContent = new Date().getFullYear();
|
||||
}
|
||||
});
|
||||
175
app/static/js/keys_status.js
Normal file
175
app/static/js/keys_status.js
Normal file
@@ -0,0 +1,175 @@
|
||||
function copyToClipboard(text) {
|
||||
if (navigator.clipboard && navigator.clipboard.writeText) {
|
||||
return navigator.clipboard.writeText(text);
|
||||
} else {
|
||||
return new Promise((resolve, reject) => {
|
||||
const textArea = document.createElement("textarea");
|
||||
textArea.value = text;
|
||||
textArea.style.position = "fixed";
|
||||
document.body.appendChild(textArea);
|
||||
textArea.focus();
|
||||
textArea.select();
|
||||
try {
|
||||
const successful = document.execCommand('copy');
|
||||
document.body.removeChild(textArea);
|
||||
if (successful) {
|
||||
resolve();
|
||||
} else {
|
||||
reject(new Error('复制失败'));
|
||||
}
|
||||
} catch (err) {
|
||||
document.body.removeChild(textArea);
|
||||
reject(err);
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
function copyKeys(type) {
|
||||
const keys = Array.from(document.querySelectorAll(`#${type}Keys .key-text`)).map(span => span.textContent.trim());
|
||||
const jsonKeys = JSON.stringify(keys);
|
||||
|
||||
copyToClipboard(jsonKeys)
|
||||
.then(() => {
|
||||
showCopyStatus(`已成功复制${type === 'valid' ? '有效' : '无效'}密钥到剪贴板`);
|
||||
})
|
||||
.catch((err) => {
|
||||
console.error('无法复制文本: ', err);
|
||||
showCopyStatus('复制失败,请重试');
|
||||
});
|
||||
}
|
||||
|
||||
function copyKey(key) {
|
||||
copyToClipboard(key)
|
||||
.then(() => {
|
||||
showCopyStatus(`已成功复制密钥到剪贴板`);
|
||||
})
|
||||
.catch((err) => {
|
||||
console.error('无法复制文本: ', err);
|
||||
showCopyStatus('复制失败,请重试');
|
||||
});
|
||||
}
|
||||
|
||||
function showCopyStatus(message, type = 'success') {
|
||||
const statusElement = document.getElementById('copyStatus');
|
||||
statusElement.textContent = message;
|
||||
statusElement.className = type; // 设置样式类
|
||||
statusElement.style.opacity = 1;
|
||||
setTimeout(() => {
|
||||
statusElement.style.opacity = 0;
|
||||
setTimeout(() => {
|
||||
statusElement.className = ''; // 清除样式类
|
||||
}, 300);
|
||||
}, 2000);
|
||||
}
|
||||
|
||||
async function verifyKey(key, button) {
|
||||
try {
|
||||
// 禁用按钮并显示加载状态
|
||||
button.disabled = true;
|
||||
const originalHtml = button.innerHTML;
|
||||
button.innerHTML = '<i class="fas fa-spinner fa-spin"></i> 验证中';
|
||||
|
||||
const response = await fetch(`/gemini/v1beta/verify-key/${key}`, {
|
||||
method: 'POST'
|
||||
});
|
||||
const data = await response.json();
|
||||
|
||||
// 根据验证结果更新UI
|
||||
if (data.status === 'valid') {
|
||||
showCopyStatus('密钥验证成功', 'success');
|
||||
button.style.backgroundColor = '#27ae60';
|
||||
} else {
|
||||
showCopyStatus('密钥验证失败', 'error');
|
||||
button.style.backgroundColor = '#e74c3c';
|
||||
}
|
||||
|
||||
// 3秒后恢复按钮原始状态
|
||||
setTimeout(() => {
|
||||
button.innerHTML = originalHtml;
|
||||
button.disabled = false;
|
||||
button.style.backgroundColor = '';
|
||||
}, 3000);
|
||||
|
||||
} catch (error) {
|
||||
console.error('验证失败:', error);
|
||||
showCopyStatus('验证请求失败', 'error');
|
||||
button.disabled = false;
|
||||
button.innerHTML = '<i class="fas fa-check-circle"></i> 验证';
|
||||
}
|
||||
}
|
||||
|
||||
function scrollToTop() {
|
||||
const container = document.querySelector('.container');
|
||||
container.scrollTo({
|
||||
top: 0,
|
||||
behavior: 'smooth'
|
||||
});
|
||||
}
|
||||
|
||||
function scrollToBottom() {
|
||||
const container = document.querySelector('.container');
|
||||
container.scrollTo({
|
||||
top: container.scrollHeight,
|
||||
behavior: 'smooth'
|
||||
});
|
||||
}
|
||||
|
||||
function updateScrollButtons() {
|
||||
const container = document.querySelector('.container');
|
||||
const scrollButtons = document.querySelector('.scroll-buttons');
|
||||
if (container.scrollHeight > container.clientHeight) {
|
||||
scrollButtons.style.display = 'flex';
|
||||
} else {
|
||||
scrollButtons.style.display = 'none';
|
||||
}
|
||||
}
|
||||
|
||||
function refreshPage(button) {
|
||||
button.classList.add('loading');
|
||||
button.disabled = true;
|
||||
|
||||
setTimeout(() => {
|
||||
window.location.reload();
|
||||
}, 300);
|
||||
}
|
||||
|
||||
function toggleSection(header, sectionId) {
|
||||
const toggleIcon = header.querySelector('.toggle-icon');
|
||||
const content = header.nextElementSibling;
|
||||
|
||||
toggleIcon.classList.toggle('collapsed');
|
||||
content.classList.toggle('collapsed');
|
||||
}
|
||||
|
||||
// 初始化
|
||||
document.addEventListener('DOMContentLoaded', () => {
|
||||
// 检查滚动按钮
|
||||
updateScrollButtons();
|
||||
|
||||
// 监听展开/折叠事件
|
||||
document.querySelectorAll('.key-list h2').forEach(header => {
|
||||
header.addEventListener('click', () => {
|
||||
setTimeout(updateScrollButtons, 300);
|
||||
});
|
||||
});
|
||||
|
||||
// 更新版权年份
|
||||
const copyrightYear = document.querySelector('.copyright script');
|
||||
if (copyrightYear) {
|
||||
copyrightYear.textContent = new Date().getFullYear();
|
||||
}
|
||||
});
|
||||
|
||||
// Service Worker registration
|
||||
if ('serviceWorker' in navigator) {
|
||||
window.addEventListener('load', () => {
|
||||
navigator.serviceWorker.register('/static/service-worker.js')
|
||||
.then(registration => {
|
||||
console.log('ServiceWorker注册成功:', registration.scope);
|
||||
})
|
||||
.catch(error => {
|
||||
console.log('ServiceWorker注册失败:', error);
|
||||
});
|
||||
});
|
||||
}
|
||||
17
app/static/manifest.json
Normal file
17
app/static/manifest.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"name": "Gemini Balance",
|
||||
"short_name": "GBalance",
|
||||
"description": "Gemini API密钥管理工具",
|
||||
"start_url": "/",
|
||||
"display": "standalone",
|
||||
"background_color": "#667eea",
|
||||
"theme_color": "#764ba2",
|
||||
"icons": [
|
||||
{
|
||||
"src": "/static/icons/icon-192x192.png",
|
||||
"sizes": "192x192",
|
||||
"type": "image/png",
|
||||
"purpose": "any maskable"
|
||||
}
|
||||
]
|
||||
}
|
||||
43
app/static/service-worker.js
Normal file
43
app/static/service-worker.js
Normal file
@@ -0,0 +1,43 @@
|
||||
const CACHE_NAME = 'gbalance-cache-v1';
|
||||
const urlsToCache = [
|
||||
'/',
|
||||
'/static/manifest.json',
|
||||
'/static/icons/icon-192x192.png'
|
||||
];
|
||||
|
||||
self.addEventListener('install', event => {
|
||||
event.waitUntil(
|
||||
caches.open(CACHE_NAME)
|
||||
.then(cache => {
|
||||
console.log('Opened cache');
|
||||
return cache.addAll(urlsToCache);
|
||||
})
|
||||
);
|
||||
});
|
||||
|
||||
self.addEventListener('fetch', event => {
|
||||
event.respondWith(
|
||||
caches.match(event.request)
|
||||
.then(response => {
|
||||
if (response) {
|
||||
return response;
|
||||
}
|
||||
return fetch(event.request);
|
||||
})
|
||||
);
|
||||
});
|
||||
|
||||
self.addEventListener('activate', event => {
|
||||
const cacheWhitelist = [CACHE_NAME];
|
||||
event.waitUntil(
|
||||
caches.keys().then(cacheNames => {
|
||||
return Promise.all(
|
||||
cacheNames.map(cacheName => {
|
||||
if (cacheWhitelist.indexOf(cacheName) === -1) {
|
||||
return caches.delete(cacheName);
|
||||
}
|
||||
})
|
||||
);
|
||||
})
|
||||
);
|
||||
});
|
||||
42
app/templates/auth.html
Normal file
42
app/templates/auth.html
Normal file
@@ -0,0 +1,42 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>验证页面</title>
|
||||
<link rel="manifest" href="/static/manifest.json">
|
||||
<meta name="theme-color" content="#764ba2">
|
||||
<meta name="apple-mobile-web-app-capable" content="yes">
|
||||
<meta name="apple-mobile-web-app-status-bar-style" content="black">
|
||||
<meta name="apple-mobile-web-app-title" content="GBalance">
|
||||
<link rel="icon" href="/static/icons/icon-192x192.png">
|
||||
<link href="https://fonts.googleapis.com/css2?family=Roboto:wght@300;400;700&display=swap" rel="stylesheet">
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
|
||||
<link rel="stylesheet" href="/static/css/auth.css">
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<div class="logo">
|
||||
<i class="fas fa-shield-alt"></i>
|
||||
</div>
|
||||
<h2>安全验证</h2>
|
||||
<form id="auth-form" action="/auth" method="post">
|
||||
<div class="input-group">
|
||||
<i class="fas fa-key"></i>
|
||||
<input type="password" id="auth-token" name="auth_token" required placeholder="请输入验证令牌">
|
||||
</div>
|
||||
<button type="submit">
|
||||
验证访问
|
||||
</button>
|
||||
</form>
|
||||
{% if error %}
|
||||
<p class="error-message">{{ error }}</p>
|
||||
{% endif %}
|
||||
</div>
|
||||
<div class="copyright">
|
||||
© <script>document.write(new Date().getFullYear())</script> by <a href="https://linux.do/u/snaily" target="_blank"><img src="https://linux.do/user_avatar/linux.do/snaily/288/306510_2.gif" alt="snaily">snaily</a> |
|
||||
<a href="https://github.com/snailyp/gemini-balance" target="_blank"><i class="fab fa-github"></i> GitHub</a>
|
||||
</div>
|
||||
<script src="/static/js/auth.js"></script>
|
||||
</body>
|
||||
</html>
|
||||
128
app/templates/keys_status.html
Normal file
128
app/templates/keys_status.html
Normal file
@@ -0,0 +1,128 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>API密钥状态</title>
|
||||
<link rel="manifest" href="/static/manifest.json">
|
||||
<meta name="theme-color" content="#764ba2">
|
||||
<meta name="apple-mobile-web-app-capable" content="yes">
|
||||
<meta name="apple-mobile-web-app-status-bar-style" content="black">
|
||||
<meta name="apple-mobile-web-app-title" content="GBalance">
|
||||
<link rel="icon" href="/static/icons/icon-192x192.png">
|
||||
<link href="https://fonts.googleapis.com/css2?family=Roboto:wght@300;400;700&display=swap" rel="stylesheet">
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
|
||||
<link rel="stylesheet" href="/static/css/keys_status.css">
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<button class="refresh-btn" onclick="refreshPage(this)">
|
||||
<i class="fas fa-sync-alt"></i>
|
||||
</button>
|
||||
<h1>API密钥状态</h1>
|
||||
<div class="key-list">
|
||||
<h2 onclick="toggleSection(this, 'validKeys')">
|
||||
<span>
|
||||
<i class="fas fa-chevron-down toggle-icon"></i>
|
||||
<i class="fas fa-check-circle" style="color: #27ae60;"></i>
|
||||
有效密钥
|
||||
</span>
|
||||
<button class="copy-btn" onclick="event.stopPropagation(); copyKeys('valid')">
|
||||
<i class="fas fa-copy"></i>
|
||||
批量复制
|
||||
</button>
|
||||
</h2>
|
||||
<div class="key-content">
|
||||
<ul id="validKeys">
|
||||
{% for key, fail_count in valid_keys.items() %}
|
||||
<li>
|
||||
<div class="key-info">
|
||||
<span class="status-badge status-valid">
|
||||
<i class="fas fa-check"></i> 有效
|
||||
</span>
|
||||
<span class="key-text">{{ key }}</span>
|
||||
<span class="fail-count">
|
||||
<i class="fas fa-exclamation-triangle"></i>
|
||||
失败: {{ fail_count }}
|
||||
</span>
|
||||
</div>
|
||||
<div class="key-actions">
|
||||
<button class="verify-btn" onclick="verifyKey('{{ key }}', this)">
|
||||
<i class="fas fa-check-circle"></i>
|
||||
验证
|
||||
</button>
|
||||
<button class="copy-btn" onclick="copyKey('{{ key }}')">
|
||||
<i class="fas fa-copy"></i>
|
||||
复制
|
||||
</button>
|
||||
</div>
|
||||
</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
<div class="key-list">
|
||||
<h2 onclick="toggleSection(this, 'invalidKeys')">
|
||||
<span>
|
||||
<i class="fas fa-chevron-down toggle-icon"></i>
|
||||
<i class="fas fa-times-circle" style="color: #e74c3c;"></i>
|
||||
无效密钥
|
||||
</span>
|
||||
<button class="copy-btn" onclick="event.stopPropagation(); copyKeys('invalid')">
|
||||
<i class="fas fa-copy"></i>
|
||||
批量复制
|
||||
</button>
|
||||
</h2>
|
||||
<div class="key-content">
|
||||
<ul id="invalidKeys">
|
||||
{% for key, fail_count in invalid_keys.items() %}
|
||||
<li>
|
||||
<div class="key-info">
|
||||
<span class="status-badge status-invalid">
|
||||
<i class="fas fa-times"></i> 无效
|
||||
</span>
|
||||
<span class="key-text">{{ key }}</span>
|
||||
<span class="fail-count">
|
||||
<i class="fas fa-exclamation-triangle"></i>
|
||||
失败: {{ fail_count }}
|
||||
</span>
|
||||
</div>
|
||||
<div class="key-actions">
|
||||
<button class="verify-btn" onclick="verifyKey('{{ key }}', this)">
|
||||
<i class="fas fa-check-circle"></i>
|
||||
验证
|
||||
</button>
|
||||
<button class="copy-btn" onclick="copyKey('{{ key }}')">
|
||||
<i class="fas fa-copy"></i>
|
||||
复制
|
||||
</button>
|
||||
</div>
|
||||
</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
<div class="total">
|
||||
<i class="fas fa-key"></i> 总密钥数:{{ total }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="scroll-buttons">
|
||||
<button class="scroll-btn" onclick="scrollToTop()" title="回到顶部">
|
||||
<i class="fas fa-chevron-up"></i>
|
||||
</button>
|
||||
<button class="scroll-btn" onclick="scrollToBottom()" title="滚动到底部">
|
||||
<i class="fas fa-chevron-down"></i>
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<div id="copyStatus"></div>
|
||||
|
||||
<div class="copyright">
|
||||
© <script>document.write(new Date().getFullYear())</script> by <a href="https://linux.do/u/snaily" target="_blank"><img src="https://linux.do/user_avatar/linux.do/snaily/288/306510_2.gif" alt="snaily">snaily</a> |
|
||||
<a href="https://github.com/snailyp/gemini-balance" target="_blank"><i class="fab fa-github"></i> GitHub</a>
|
||||
</div>
|
||||
|
||||
<script src="/static/js/keys_status.js"></script>
|
||||
</body>
|
||||
</html>
|
||||
3
app/utils/__init__.py
Normal file
3
app/utils/__init__.py
Normal file
@@ -0,0 +1,3 @@
|
||||
"""
|
||||
工具包初始化模块
|
||||
"""
|
||||
146
app/utils/helpers.py
Normal file
146
app/utils/helpers.py
Normal file
@@ -0,0 +1,146 @@
|
||||
"""
|
||||
通用工具函数模块
|
||||
"""
|
||||
import json
|
||||
import re
|
||||
import base64
|
||||
import requests
|
||||
from typing import Dict, Any, List, Optional, Tuple
|
||||
|
||||
from app.core.constants import DATA_URL_PATTERN, IMAGE_URL_PATTERN, VALID_IMAGE_RATIOS
|
||||
|
||||
|
||||
def extract_mime_type_and_data(base64_string: str) -> Tuple[Optional[str], str]:
|
||||
"""
|
||||
从 base64 字符串中提取 MIME 类型和数据
|
||||
|
||||
Args:
|
||||
base64_string: 可能包含 MIME 类型信息的 base64 字符串
|
||||
|
||||
Returns:
|
||||
tuple: (mime_type, encoded_data)
|
||||
"""
|
||||
# 检查字符串是否以 "data:" 格式开始
|
||||
if base64_string.startswith('data:'):
|
||||
# 提取 MIME 类型和数据
|
||||
pattern = DATA_URL_PATTERN
|
||||
match = re.match(pattern, base64_string)
|
||||
if match:
|
||||
mime_type = "image/jpeg" if match.group(1) == "image/jpg" else match.group(1)
|
||||
encoded_data = match.group(2)
|
||||
return mime_type, encoded_data
|
||||
|
||||
# 如果不是预期格式,假定它只是数据部分
|
||||
return None, base64_string
|
||||
|
||||
|
||||
def convert_image_to_base64(url: str) -> str:
|
||||
"""
|
||||
将图片URL转换为base64编码
|
||||
|
||||
Args:
|
||||
url: 图片URL
|
||||
|
||||
Returns:
|
||||
str: base64编码的图片数据
|
||||
|
||||
Raises:
|
||||
Exception: 如果获取图片失败
|
||||
"""
|
||||
response = requests.get(url)
|
||||
if response.status_code == 200:
|
||||
# 将图片内容转换为base64
|
||||
img_data = base64.b64encode(response.content).decode('utf-8')
|
||||
return img_data
|
||||
else:
|
||||
raise Exception(f"Failed to fetch image: {response.status_code}")
|
||||
|
||||
|
||||
def format_json_response(data: Dict[str, Any], indent: int = 2) -> str:
|
||||
"""
|
||||
格式化JSON响应
|
||||
|
||||
Args:
|
||||
data: 要格式化的数据
|
||||
indent: 缩进空格数
|
||||
|
||||
Returns:
|
||||
str: 格式化后的JSON字符串
|
||||
"""
|
||||
return json.dumps(data, indent=indent, ensure_ascii=False)
|
||||
|
||||
|
||||
def parse_prompt_parameters(prompt: str, default_ratio: str = "1:1") -> Tuple[str, int, str]:
|
||||
"""
|
||||
从prompt中解析参数
|
||||
|
||||
支持的格式:
|
||||
- {n:数量} 例如: {n:2} 生成2张图片
|
||||
- {ratio:比例} 例如: {ratio:16:9} 使用16:9比例
|
||||
|
||||
Args:
|
||||
prompt: 提示文本
|
||||
default_ratio: 默认比例
|
||||
|
||||
Returns:
|
||||
tuple: (清理后的提示文本, 图片数量, 比例)
|
||||
"""
|
||||
# 默认值
|
||||
n = 1
|
||||
aspect_ratio = default_ratio
|
||||
|
||||
# 解析n参数
|
||||
n_match = re.search(r'{n:(\d+)}', prompt)
|
||||
if n_match:
|
||||
n = int(n_match.group(1))
|
||||
if n < 1 or n > 4:
|
||||
raise ValueError(f"Invalid n value: {n}. Must be between 1 and 4.")
|
||||
prompt = prompt.replace(n_match.group(0), '').strip()
|
||||
|
||||
# 解析ratio参数
|
||||
ratio_match = re.search(r'{ratio:(\d+:\d+)}', prompt)
|
||||
if ratio_match:
|
||||
aspect_ratio = ratio_match.group(1)
|
||||
if aspect_ratio not in VALID_IMAGE_RATIOS:
|
||||
raise ValueError(
|
||||
f"Invalid ratio: {aspect_ratio}. Must be one of: {', '.join(VALID_IMAGE_RATIOS)}"
|
||||
)
|
||||
prompt = prompt.replace(ratio_match.group(0), '').strip()
|
||||
|
||||
return prompt, n, aspect_ratio
|
||||
|
||||
|
||||
def extract_image_urls_from_markdown(text: str) -> List[str]:
|
||||
"""
|
||||
从Markdown文本中提取图片URL
|
||||
|
||||
Args:
|
||||
text: Markdown文本
|
||||
|
||||
Returns:
|
||||
List[str]: 图片URL列表
|
||||
"""
|
||||
pattern = IMAGE_URL_PATTERN
|
||||
matches = re.findall(pattern, text)
|
||||
return [match[1] for match in matches]
|
||||
|
||||
|
||||
def is_valid_api_key(key: str) -> bool:
|
||||
"""
|
||||
检查API密钥格式是否有效
|
||||
|
||||
Args:
|
||||
key: API密钥
|
||||
|
||||
Returns:
|
||||
bool: 如果密钥格式有效则返回True
|
||||
"""
|
||||
# 检查Gemini API密钥格式
|
||||
if key.startswith('AIza'):
|
||||
return len(key) >= 30
|
||||
|
||||
# 检查OpenAI API密钥格式
|
||||
if key.startswith('sk-'):
|
||||
return len(key) >= 30
|
||||
|
||||
return False
|
||||
393
app/utils/uploader.py
Normal file
393
app/utils/uploader.py
Normal file
@@ -0,0 +1,393 @@
|
||||
import requests
|
||||
from app.domain.image_models import ImageMetadata, ImageUploader, UploadResponse
|
||||
from enum import Enum
|
||||
from typing import Optional, Any
|
||||
|
||||
class UploadErrorType(Enum):
|
||||
"""上传错误类型枚举"""
|
||||
NETWORK_ERROR = "network_error" # 网络请求错误
|
||||
AUTH_ERROR = "auth_error" # 认证错误
|
||||
INVALID_FILE = "invalid_file" # 无效文件
|
||||
SERVER_ERROR = "server_error" # 服务器错误
|
||||
PARSE_ERROR = "parse_error" # 响应解析错误
|
||||
UNKNOWN = "unknown" # 未知错误
|
||||
|
||||
|
||||
class UploadError(Exception):
|
||||
"""图片上传错误异常类"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
message: str,
|
||||
error_type: UploadErrorType = UploadErrorType.UNKNOWN,
|
||||
status_code: Optional[int] = None,
|
||||
details: Optional[dict] = None,
|
||||
original_error: Optional[Exception] = None
|
||||
):
|
||||
"""
|
||||
初始化上传错误异常
|
||||
|
||||
Args:
|
||||
message: 错误消息
|
||||
error_type: 错误类型
|
||||
status_code: HTTP状态码
|
||||
details: 详细错误信息
|
||||
original_error: 原始异常
|
||||
"""
|
||||
self.message = message
|
||||
self.error_type = error_type
|
||||
self.status_code = status_code
|
||||
self.details = details or {}
|
||||
self.original_error = original_error
|
||||
|
||||
# 构建完整错误信息
|
||||
full_message = f"[{error_type.value}] {message}"
|
||||
if status_code:
|
||||
full_message = f"{full_message} (Status: {status_code})"
|
||||
if details:
|
||||
full_message = f"{full_message} - Details: {details}"
|
||||
|
||||
super().__init__(full_message)
|
||||
|
||||
@classmethod
|
||||
def from_response(cls, response: Any, message: Optional[str] = None) -> "UploadError":
|
||||
"""
|
||||
从HTTP响应创建错误实例
|
||||
|
||||
Args:
|
||||
response: HTTP响应对象
|
||||
message: 自定义错误消息
|
||||
"""
|
||||
try:
|
||||
error_data = response.json()
|
||||
details = error_data.get("data", {})
|
||||
return cls(
|
||||
message=message or error_data.get("message", "Unknown error"),
|
||||
error_type=UploadErrorType.SERVER_ERROR,
|
||||
status_code=response.status_code,
|
||||
details=details
|
||||
)
|
||||
except Exception:
|
||||
return cls(
|
||||
message=message or "Failed to parse error response",
|
||||
error_type=UploadErrorType.PARSE_ERROR,
|
||||
status_code=response.status_code
|
||||
)
|
||||
|
||||
|
||||
class SmMsUploader(ImageUploader):
|
||||
API_URL = "https://sm.ms/api/v2/upload"
|
||||
|
||||
def __init__(self, api_key: str):
|
||||
self.api_key = api_key
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
try:
|
||||
# 准备请求头
|
||||
headers = {
|
||||
"Authorization": f"Basic {self.api_key}"
|
||||
}
|
||||
|
||||
# 准备文件数据
|
||||
files = {
|
||||
"smfile": (filename, file, "image/png")
|
||||
}
|
||||
|
||||
# 发送请求
|
||||
response = requests.post(
|
||||
self.API_URL,
|
||||
headers=headers,
|
||||
files=files
|
||||
)
|
||||
|
||||
# 检查响应状态
|
||||
response.raise_for_status()
|
||||
|
||||
# 解析响应
|
||||
result = response.json()
|
||||
|
||||
# 验证上传是否成功
|
||||
if not result.get("success"):
|
||||
raise UploadError(result.get("message", "Upload failed"))
|
||||
|
||||
# 转换为统一格式
|
||||
data = result["data"]
|
||||
image_metadata = ImageMetadata(
|
||||
width=data["width"],
|
||||
height=data["height"],
|
||||
filename=data["filename"],
|
||||
size=data["size"],
|
||||
url=data["url"],
|
||||
delete_url=data["delete"]
|
||||
)
|
||||
|
||||
return UploadResponse(
|
||||
success=True,
|
||||
code="success",
|
||||
message="Upload success",
|
||||
data=image_metadata
|
||||
)
|
||||
|
||||
except requests.RequestException as e:
|
||||
# 处理网络请求相关错误
|
||||
raise UploadError(f"Upload request failed: {str(e)}")
|
||||
except (KeyError, ValueError) as e:
|
||||
# 处理响应解析错误
|
||||
raise UploadError(f"Invalid response format: {str(e)}")
|
||||
except Exception as e:
|
||||
# 处理其他未预期的错误
|
||||
raise UploadError(f"Upload failed: {str(e)}")
|
||||
|
||||
|
||||
class QiniuUploader(ImageUploader):
|
||||
def __init__(self, access_key: str, secret_key: str):
|
||||
self.access_key = access_key
|
||||
self.secret_key = secret_key
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
# 实现七牛云的具体上传逻辑
|
||||
pass
|
||||
|
||||
|
||||
class PicGoUploader(ImageUploader):
|
||||
"""Chevereto API 图片上传器"""
|
||||
|
||||
def __init__(self, api_key: str, api_url: str = "https://www.picgo.net/api/1/upload"):
|
||||
"""
|
||||
初始化 Chevereto 上传器
|
||||
|
||||
Args:
|
||||
api_key: Chevereto API 密钥
|
||||
api_url: Chevereto API 上传地址
|
||||
"""
|
||||
self.api_key = api_key
|
||||
self.api_url = api_url
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
"""
|
||||
上传图片到 Chevereto 服务
|
||||
|
||||
Args:
|
||||
file: 图片文件二进制数据
|
||||
filename: 文件名
|
||||
|
||||
Returns:
|
||||
UploadResponse: 上传响应对象
|
||||
|
||||
Raises:
|
||||
UploadError: 上传失败时抛出异常
|
||||
"""
|
||||
try:
|
||||
# 准备请求头
|
||||
headers = {
|
||||
"X-API-Key": self.api_key
|
||||
}
|
||||
|
||||
# 准备文件数据
|
||||
files = {
|
||||
"source": (filename, file)
|
||||
}
|
||||
|
||||
# 发送请求
|
||||
response = requests.post(
|
||||
self.api_url,
|
||||
headers=headers,
|
||||
files=files
|
||||
)
|
||||
|
||||
# 检查响应状态
|
||||
response.raise_for_status()
|
||||
|
||||
# 解析响应
|
||||
result = response.json()
|
||||
|
||||
# 验证上传是否成功
|
||||
if result.get("status_code") != 200:
|
||||
error_message = "Upload failed"
|
||||
if "error" in result:
|
||||
error_message = result["error"].get("message", error_message)
|
||||
raise UploadError(
|
||||
message=error_message,
|
||||
error_type=UploadErrorType.SERVER_ERROR,
|
||||
status_code=result.get("status_code"),
|
||||
details=result.get("error")
|
||||
)
|
||||
|
||||
# 从响应中提取图片信息
|
||||
image_data = result.get("image", {})
|
||||
|
||||
# 构建图片元数据
|
||||
image_metadata = ImageMetadata(
|
||||
width=image_data.get("width", 0),
|
||||
height=image_data.get("height", 0),
|
||||
filename=image_data.get("filename", filename),
|
||||
size=image_data.get("size", 0),
|
||||
url=image_data.get("url", ""),
|
||||
delete_url=image_data.get("delete_url", None)
|
||||
)
|
||||
|
||||
return UploadResponse(
|
||||
success=True,
|
||||
code="success",
|
||||
message=result.get("success", {}).get("message", "Upload success"),
|
||||
data=image_metadata
|
||||
)
|
||||
|
||||
except requests.RequestException as e:
|
||||
# 处理网络请求相关错误
|
||||
raise UploadError(
|
||||
message=f"Upload request failed: {str(e)}",
|
||||
error_type=UploadErrorType.NETWORK_ERROR,
|
||||
original_error=e
|
||||
)
|
||||
except (KeyError, ValueError, TypeError) as e:
|
||||
# 处理响应解析错误
|
||||
raise UploadError(
|
||||
message=f"Invalid response format: {str(e)}",
|
||||
error_type=UploadErrorType.PARSE_ERROR,
|
||||
original_error=e
|
||||
)
|
||||
except UploadError:
|
||||
# 重新抛出已经是 UploadError 类型的异常
|
||||
raise
|
||||
except Exception as e:
|
||||
# 处理其他未预期的错误
|
||||
raise UploadError(
|
||||
message=f"Upload failed: {str(e)}",
|
||||
error_type=UploadErrorType.UNKNOWN,
|
||||
original_error=e
|
||||
)
|
||||
|
||||
|
||||
class CloudFlareImgBedUploader(ImageUploader):
|
||||
"""CloudFlare图床上传器"""
|
||||
|
||||
def __init__(self, auth_code: str, api_url: str):
|
||||
"""
|
||||
初始化CloudFlare图床上传器
|
||||
|
||||
Args:
|
||||
auth_code: 认证码
|
||||
api_url: 上传API地址
|
||||
"""
|
||||
self.auth_code = auth_code
|
||||
self.api_url = api_url
|
||||
|
||||
def upload(self, file: bytes, filename: str) -> UploadResponse:
|
||||
"""
|
||||
上传图片到CloudFlare图床
|
||||
|
||||
Args:
|
||||
file: 图片文件二进制数据
|
||||
filename: 文件名
|
||||
|
||||
Returns:
|
||||
UploadResponse: 上传响应对象
|
||||
|
||||
Raises:
|
||||
UploadError: 上传失败时抛出异常
|
||||
"""
|
||||
try:
|
||||
# 准备请求URL(添加认证码参数,如果存在)
|
||||
if self.auth_code:
|
||||
request_url = f"{self.api_url}?authCode={self.auth_code}&uploadNameType=origin"
|
||||
else:
|
||||
request_url = f"{self.api_url}?uploadNameType=origin"
|
||||
|
||||
# 准备文件数据
|
||||
files = {
|
||||
"file": (filename, file)
|
||||
}
|
||||
|
||||
# 发送请求
|
||||
response = requests.post(
|
||||
request_url,
|
||||
files=files
|
||||
)
|
||||
|
||||
# 检查响应状态
|
||||
response.raise_for_status()
|
||||
|
||||
# 解析响应
|
||||
result = response.json()
|
||||
|
||||
# 验证响应格式
|
||||
if not result or not isinstance(result, list) or len(result) == 0:
|
||||
raise UploadError(
|
||||
message="Invalid response format",
|
||||
error_type=UploadErrorType.PARSE_ERROR
|
||||
)
|
||||
|
||||
# 获取文件URL
|
||||
file_path = result[0].get("src")
|
||||
if not file_path:
|
||||
raise UploadError(
|
||||
message="Missing file URL in response",
|
||||
error_type=UploadErrorType.PARSE_ERROR
|
||||
)
|
||||
|
||||
# 构建完整URL(如果返回的是相对路径)
|
||||
base_url = self.api_url.split("/upload")[0]
|
||||
full_url = file_path if file_path.startswith(("http://", "https://")) else f"{base_url}{file_path}"
|
||||
|
||||
# 构建图片元数据(注意:CloudFlare-ImgBed不返回所有元数据,所以部分字段为默认值)
|
||||
image_metadata = ImageMetadata(
|
||||
width=0, # CloudFlare-ImgBed不返回宽度
|
||||
height=0, # CloudFlare-ImgBed不返回高度
|
||||
filename=filename,
|
||||
size=0, # CloudFlare-ImgBed不返回大小
|
||||
url=full_url,
|
||||
delete_url=None # CloudFlare-ImgBed不返回删除URL
|
||||
)
|
||||
|
||||
return UploadResponse(
|
||||
success=True,
|
||||
code="success",
|
||||
message="Upload success",
|
||||
data=image_metadata
|
||||
)
|
||||
|
||||
except requests.RequestException as e:
|
||||
# 处理网络请求相关错误
|
||||
raise UploadError(
|
||||
message=f"Upload request failed: {str(e)}",
|
||||
error_type=UploadErrorType.NETWORK_ERROR,
|
||||
original_error=e
|
||||
)
|
||||
except (KeyError, ValueError, TypeError, IndexError) as e:
|
||||
# 处理响应解析错误
|
||||
raise UploadError(
|
||||
message=f"Invalid response format: {str(e)}",
|
||||
error_type=UploadErrorType.PARSE_ERROR,
|
||||
original_error=e
|
||||
)
|
||||
except UploadError:
|
||||
# 重新抛出已经是 UploadError 类型的异常
|
||||
raise
|
||||
except Exception as e:
|
||||
# 处理其他未预期的错误
|
||||
raise UploadError(
|
||||
message=f"Upload failed: {str(e)}",
|
||||
error_type=UploadErrorType.UNKNOWN,
|
||||
original_error=e
|
||||
)
|
||||
|
||||
class ImageUploaderFactory:
|
||||
@staticmethod
|
||||
def create(provider: str, **credentials) -> ImageUploader:
|
||||
if provider == "smms":
|
||||
return SmMsUploader(credentials["api_key"])
|
||||
elif provider == "qiniu":
|
||||
return QiniuUploader(
|
||||
credentials["access_key"],
|
||||
credentials["secret_key"]
|
||||
)
|
||||
elif provider == "picgo":
|
||||
api_url = credentials.get("api_url", "https://www.picgo.net/api/1/upload")
|
||||
return PicGoUploader(credentials["api_key"], api_url)
|
||||
elif provider == "cloudflare_imgbed":
|
||||
return CloudFlareImgBedUploader(
|
||||
credentials["auth_code"],
|
||||
credentials["base_url"]
|
||||
)
|
||||
raise ValueError(f"Unknown provider: {provider}")
|
||||
9
docker-compose.yml
Normal file
9
docker-compose.yml
Normal file
@@ -0,0 +1,9 @@
|
||||
version: '3'
|
||||
|
||||
services:
|
||||
gemini-balance:
|
||||
build: .
|
||||
ports:
|
||||
- "8000:8000"
|
||||
env_file:
|
||||
- .env
|
||||
@@ -6,4 +6,6 @@ pydantic_settings
|
||||
requests
|
||||
starlette
|
||||
uvicorn
|
||||
google-genai
|
||||
google-genai
|
||||
jinja2
|
||||
python-multipart
|
||||
|
||||
Reference in New Issue
Block a user