更改了页面布局，调通了模型调用界面
This commit is contained in:
@@ -51,7 +51,16 @@
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"Bash(git add:*)",
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"Bash(git rm:*)",
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"Bash(git check-ignore:*)",
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"Bash(./setup.sh:*)"
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"Bash(./setup.sh:*)",
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"Bash(ss:*)",
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"Bash(bash:*)",
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"Bash(/d/Softwares/npm/npm install)",
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"Bash(npm config:*)",
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"Bash(cmd:*)",
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"Bash(grep:*)",
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"Bash(tasklist:*)",
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"Bash(./xrequest/Scripts/python.exe:*)",
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"Bash(xrequest/Scripts/python.exe:*)"
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]
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}
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}
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122
models/models.json
Normal file
122
models/models.json
Normal file
@@ -0,0 +1,122 @@
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[
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{
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"id": "model-1",
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"name": "GPT-4 Turbo",
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"type": "gpt",
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"provider": "openai",
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"version": "gpt-4-turbo",
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"apiUrl": "https://api.openai.com/v1",
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"apiKey": "sk-test123456789",
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"timeout": 30,
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"maxRetries": 3,
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"temperature": 0.7,
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"topP": 1.0,
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"topK": 50,
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"maxTokens": 2048,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": false,
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"logRequests": true,
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"status": "连接失败"
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},
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{
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"id": "model-2",
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"name": "Claude-3 Sonnet",
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"type": "claude",
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"provider": "anthropic",
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"version": "claude-3-sonnet-20240229",
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"apiUrl": "https://api.anthropic.com/v1",
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"apiKey": "",
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"timeout": 30,
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"maxRetries": 3,
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"temperature": 0.5,
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"topP": 0.9,
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"topK": 40,
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"maxTokens": 4096,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": true,
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"logRequests": true,
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"status": "未测试"
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},
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{
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"id": "model-3",
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"name": "LLaMA-2 7B",
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"type": "llama",
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"provider": "local",
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"version": "llama-2-7b-chat",
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"apiUrl": "http://localhost:8080/v1",
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"apiKey": "",
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"timeout": 60,
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"maxRetries": 3,
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"temperature": 0.8,
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"topP": 0.95,
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"topK": 60,
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"maxTokens": 2048,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": false,
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"logRequests": false,
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"status": "已测试"
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},
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{
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"id": "0c13f76a-6a40-48d2-86d3-2638fd2be652",
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"name": "Test Model",
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"type": "gpt",
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"provider": "openai",
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"version": "gpt-3.5-turbo",
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"apiUrl": "",
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"apiKey": "",
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"timeout": 30,
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"maxRetries": 3,
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"temperature": 0.7,
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"topP": 1.0,
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"topK": 50,
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"maxTokens": 2048,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": false,
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"logRequests": true,
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"status": "未测试"
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},
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{
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"id": "9674adec-124c-4641-898b-7f7557e9e412",
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"name": "nova",
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"type": "gpt",
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"provider": "openai",
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"version": "nova",
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"apiUrl": "http://10.10.10.122:1234/v1",
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"apiKey": "123",
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"timeout": 30,
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"maxRetries": 3,
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"temperature": 0.7,
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"topP": 1,
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"topK": 50,
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"maxTokens": 2048,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": false,
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"logRequests": true,
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"status": "已测试"
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},
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{
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"id": "e81c21e1-a4ce-4237-ba22-0922b741b9be",
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"name": "qwen3-flash",
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"type": "custom",
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"provider": "openai",
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"version": "qwen-flash",
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"apiUrl": "https://dashscope.aliyuncs.com/compatible-mode/v1",
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"apiKey": "sk-5706307e3e3a4eb09452dbf0bb87fe31",
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"timeout": 60,
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"maxRetries": 3,
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"temperature": 0.7,
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"topP": 1,
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"topK": 50,
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"maxTokens": 2048,
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"systemPrompt": "你是一个有用的AI助手。",
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"streaming": true,
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"functions": false,
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"logRequests": true,
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"status": "已测试"
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}
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]
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@@ -1 +1 @@
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3335
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3807
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@@ -1,17 +0,0 @@
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# 核心依赖
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fastapi==0.104.1
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uvicorn[standard]==0.24.0
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pydantic==2.5.0
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pydantic-settings==2.1.0
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psutil==5.9.8
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# 日志相关
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structlog==23.2.0
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colorama==0.4.6
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python-json-logger==2.0.7
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# 异步文件操作
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aiofiles==23.2.1
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# 表单/文件上传（FastAPI UploadFile/Form 需要）
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python-multipart==0.0.9
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@@ -30,8 +30,8 @@ class BaseAPI(ABC):
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def __init__(self):
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"""初始化基类"""
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# 获取模块名作为路由前缀
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self.module_name = self.__class__.__module__.split('.')[-1]
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# 获取模块名作为路由前缀（允许子类覆盖）
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self.module_name = getattr(self, '_override_module_name', None) or self.__class__.__module__.split('.')[-1]
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self.router_prefix = f"/{self.module_name}"
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# 创建路由器
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@@ -32,36 +32,14 @@ def format_file_size(size_bytes: int) -> str:
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class DatasetAPI(BaseAPI):
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"""数据集管理 API - 自动注册到 /api/datasets 路径"""
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"""数据集管理 API"""
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def __init__(self):
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# 重写初始化逻辑以设置正确的路由前缀
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# 1. 手动设置 module_name
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self.module_name = "api.datasets"
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# 2. 创建路由器（使用期望的前缀）
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from fastapi import APIRouter
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self.router_prefix = "/api/datasets"
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self.router = APIRouter(
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prefix=self.router_prefix,
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tags=["Datasets"]
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)
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# 3. 获取日志器
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import sys
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self.logger = __import__('src.utils.logger', fromlist=['get_logger']).get_logger(self.__class__.__module__)
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# 4. 调用基类的自动注册（此时router已被覆盖）
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# 注意：我们不调用父类__init__，而是手动调用_auto_register_routes
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self._auto_register_routes()
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# 5. 记录初始化
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self.logger.info(
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f"API模块初始化完成",
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module=self.module_name,
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prefix=self.router_prefix,
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routes=len(self.router.routes)
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)
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"""初始化"""
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# 在调用super().__init__()之前设置module_name
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self._override_module_name = "datasets"
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super().__init__()
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self.logger.info("DatasetAPI 初始化完成")
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@post("/upload", response_model=StandardResponse)
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async def upload_dataset(
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@@ -143,6 +121,12 @@ class DatasetAPI(BaseAPI):
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Returns:
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StandardResponse: 包含数据集列表的标准响应
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"""
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# 添加调试日志
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import logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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logger.info(f"list_datasets called with list_all={list_all}")
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try:
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if list_all:
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# 列出data目录下的所有文件（物理文件）
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892
request/src/api/modules/models.py
Normal file
892
request/src/api/modules/models.py
Normal file
@@ -0,0 +1,892 @@
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"""
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模型配置管理模块
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支持模型的增删改查操作
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"""
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import os
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import json
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import uuid
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import httpx
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import asyncio
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from typing import List, Dict, Any, Optional
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from fastapi import HTTPException, Body, Response
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from fastapi.responses import StreamingResponse
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import logging
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# 导入基类
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from src.api.internal.base import BaseAPI, get, post, put, delete
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# 配置日志
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logger = logging.getLogger(__name__)
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# 模型配置文件路径
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import os
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BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
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MODELS_CONFIG_PATH = os.path.join(BASE_DIR, "..", "..", "models", "models.json")
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# 规范化路径
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MODELS_CONFIG_PATH = os.path.normpath(MODELS_CONFIG_PATH)
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async def handle_streaming_response(response: httpx.Response, model: Dict[str, Any], attempt: int, max_attempts: int) -> Dict[str, Any]:
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"""处理流式响应"""
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try:
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if response.status_code != 200:
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error_msg = f"API调用失败 (状态码: {response.status_code})"
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try:
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error_detail = response.json()
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error_msg += f": {error_detail}"
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except:
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error_msg += f": {response.text}"
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return {
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'success': False,
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'error': error_msg,
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'status_code': response.status_code
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}
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full_content = ""
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chunk_count = 0
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usage = {}
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# 处理流式数据
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async for line in response.aiter_lines():
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if line.startswith('data: '):
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data_str = line[6:] # 移除 'data: ' 前缀
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if data_str.strip() == '[DONE]':
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break
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try:
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chunk = json.loads(data_str)
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chunk_count += 1
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# 提取内容
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if 'choices' in chunk and len(chunk['choices']) > 0:
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delta = chunk['choices'][0].get('delta', {})
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if 'content' in delta:
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content = delta['content']
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full_content += content
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# 提取使用统计
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if 'usage' in chunk:
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usage = chunk['usage']
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except json.JSONDecodeError:
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continue
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logger.info(f"流式响应完成 (尝试 {attempt}/{max_attempts}) - 接收 {chunk_count} 个数据块")
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return {
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'success': True,
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'model': model['name'],
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'content': full_content,
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'usage': usage,
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'streaming': True,
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'chunks_received': chunk_count,
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'raw_response': {
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'object': 'chat.completion',
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'model': model.get('version', 'unknown'),
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'choices': [{
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'message': {'role': 'assistant', 'content': full_content},
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'finish_reason': 'stop'
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}],
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'usage': usage
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}
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}
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except Exception as e:
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logger.error(f"流式响应处理错误: {str(e)}")
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return {
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'success': False,
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'error': f'流式响应处理失败: {str(e)}',
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'error_type': type(e).__name__
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}
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class ModelManager:
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"""模型配置管理器"""
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@staticmethod
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def load_models() -> List[Dict[str, Any]]:
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"""从JSON文件加载所有模型配置"""
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try:
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if not os.path.exists(MODELS_CONFIG_PATH):
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logger.warning(f"模型配置文件不存在: {MODELS_CONFIG_PATH}")
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return []
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with open(MODELS_CONFIG_PATH, 'r', encoding='utf-8') as f:
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models = json.load(f)
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logger.info(f"成功加载 {len(models)} 个模型配置")
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return models
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except Exception as e:
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logger.error(f"加载模型配置失败: {str(e)}")
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return []
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@staticmethod
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def save_models(models: List[Dict[str, Any]]) -> bool:
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"""保存模型配置到JSON文件"""
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try:
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# 确保目录存在
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os.makedirs(os.path.dirname(MODELS_CONFIG_PATH), exist_ok=True)
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with open(MODELS_CONFIG_PATH, 'w', encoding='utf-8') as f:
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json.dump(models, f, ensure_ascii=False, indent=2)
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logger.info(f"成功保存 {len(models)} 个模型配置")
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return True
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except Exception as e:
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logger.error(f"保存模型配置失败: {str(e)}")
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return False
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@staticmethod
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def get_model_by_id(model_id: str) -> Optional[Dict[str, Any]]:
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"""根据ID获取单个模型配置"""
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models = ModelManager.load_models()
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for model in models:
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if model.get('id') == model_id:
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return model
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return None
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@staticmethod
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def create_model(model_data: Dict[str, Any]) -> Dict[str, Any]:
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"""创建新模型配置"""
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models = ModelManager.load_models()
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# 生成唯一ID
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model_id = str(uuid.uuid4())
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# 创建新模型
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new_model = {
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'id': model_id,
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'name': model_data.get('name', ''),
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'type': model_data.get('type', ''),
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'provider': model_data.get('provider', ''),
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'version': model_data.get('version', ''),
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'apiUrl': model_data.get('apiUrl', ''),
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'apiKey': model_data.get('apiKey', ''),
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'timeout': model_data.get('timeout', 30),
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'maxRetries': model_data.get('maxRetries', 3),
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'temperature': model_data.get('temperature', 0.7),
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'topP': model_data.get('topP', 1.0),
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'topK': model_data.get('topK', 50),
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'maxTokens': model_data.get('maxTokens', 2048),
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'systemPrompt': model_data.get('systemPrompt', '你是一个有用的AI助手。'),
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'streaming': model_data.get('streaming', True),
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'functions': model_data.get('functions', False),
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'logRequests': model_data.get('logRequests', True),
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'status': model_data.get('status', '未测试')
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}
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# 添加到列表
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models.append(new_model)
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# 保存
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if ModelManager.save_models(models):
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return new_model
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else:
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raise HTTPException(status_code=500, detail="保存模型配置失败")
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@staticmethod
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def update_model(model_id: str, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
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"""更新模型配置"""
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models = ModelManager.load_models()
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# 查找并更新模型
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for i, model in enumerate(models):
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if model.get('id') == model_id:
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# 更新模型数据
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updated_model = models[i].copy()
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updated_model.update(model_data)
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updated_model['id'] = model_id # 确保ID不变
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models[i] = updated_model
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# 保存
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if ModelManager.save_models(models):
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return updated_model
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else:
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raise HTTPException(status_code=500, detail="保存模型配置失败")
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return None
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@staticmethod
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def delete_model(model_id: str) -> bool:
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"""删除模型配置"""
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models = ModelManager.load_models()
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# 查找并删除
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||||
for i, model in enumerate(models):
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if model.get('id') == model_id:
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del models[i]
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||||
|
||||
# 保存
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if ModelManager.save_models(models):
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return True
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else:
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||||
raise HTTPException(status_code=500, detail="保存模型配置失败")
|
||||
|
||||
return False
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||||
|
||||
@staticmethod
|
||||
async def call_model(model_id: str, prompt: str, system_prompt: Optional[str] = None) -> Dict[str, Any]:
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||||
"""真实调用模型API"""
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
if not model:
|
||||
raise HTTPException(status_code=404, detail="模型不存在")
|
||||
|
||||
# 检查API配置
|
||||
api_url = model.get('apiUrl', '').strip()
|
||||
api_key = model.get('apiKey', '').strip()
|
||||
version = model.get('version', '').strip()
|
||||
provider = model.get('provider', '').strip()
|
||||
|
||||
# 调试日志
|
||||
logger.info(f"Model {model.get('name')} config", extra={
|
||||
'provider': provider,
|
||||
'api_url': api_url,
|
||||
'version': version,
|
||||
'has_api_key': bool(api_key),
|
||||
'api_key_length': len(api_key) if api_key else 0
|
||||
})
|
||||
|
||||
if not api_url:
|
||||
raise HTTPException(status_code=400, detail="模型API地址未配置")
|
||||
|
||||
if not version:
|
||||
raise HTTPException(status_code=400, detail="模型版本未配置")
|
||||
|
||||
# 准备请求数据
|
||||
request_data = {
|
||||
"model": version,
|
||||
"messages": [],
|
||||
"temperature": model.get('temperature', 0.7),
|
||||
"top_p": model.get('topP', 1.0),
|
||||
"max_tokens": model.get('maxTokens', 2048),
|
||||
"stream": model.get('streaming', False)
|
||||
}
|
||||
|
||||
# 添加系统提示词
|
||||
if system_prompt:
|
||||
request_data["messages"].append({
|
||||
"role": "system",
|
||||
"content": system_prompt
|
||||
})
|
||||
elif model.get('systemPrompt'):
|
||||
request_data["messages"].append({
|
||||
"role": "system",
|
||||
"content": model.get('systemPrompt')
|
||||
})
|
||||
|
||||
# 添加用户提示词
|
||||
request_data["messages"].append({
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
})
|
||||
|
||||
# 设置请求头
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
# 添加API密钥（如果提供）
|
||||
if api_key:
|
||||
provider_lower = provider.lower()
|
||||
|
||||
# 根据提供商类型设置认证头
|
||||
if provider_lower == 'anthropic':
|
||||
# Anthropic API
|
||||
headers["x-api-key"] = api_key
|
||||
headers["anthropic-version"] = "2023-06-01"
|
||||
logger.info(f"设置Anthropic认证头，x-api-key长度: {len(api_key)}")
|
||||
else:
|
||||
# OpenAI 和其他兼容的API（包括自定义）
|
||||
headers["Authorization"] = f"Bearer {api_key}"
|
||||
logger.info(f"设置Bearer认证头，key长度: {len(api_key)}")
|
||||
|
||||
# 记录最终使用的请求头（隐藏API key）
|
||||
logger.info(f"最终请求头", extra={
|
||||
'headers': {k: v if k != 'Authorization' and k != 'x-api-key' else '***HIDDEN***' for k, v in headers.items()},
|
||||
'api_key_masked': f"{api_key[:4]}...{api_key[-4:]}" if len(api_key) > 8 else '***'
|
||||
})
|
||||
else:
|
||||
logger.warning(f"未提供API key for model {model.get('name')}")
|
||||
# 记录最终使用的请求头
|
||||
logger.info(f"最终请求头", extra={
|
||||
'headers': headers,
|
||||
'api_key': 'NONE'
|
||||
})
|
||||
|
||||
# 获取重试配置
|
||||
max_retries = model.get('maxRetries', 3)
|
||||
retry_delay = 2 # 重试间隔2秒
|
||||
|
||||
last_error = None
|
||||
|
||||
# 重试循环
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
# 发送API请求
|
||||
timeout = httpx.Timeout(model.get('timeout', 30))
|
||||
provider = model.get('provider', '').lower()
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
# 根据提供商类型调用不同的API端点
|
||||
if provider_lower == 'anthropic':
|
||||
# Anthropic API格式
|
||||
anthropic_request = {
|
||||
"model": version,
|
||||
"max_tokens": request_data["max_tokens"],
|
||||
"messages": request_data["messages"][1:] # 移除system message，Anthropic使用system参数
|
||||
}
|
||||
if system_prompt or model.get('systemPrompt'):
|
||||
anthropic_request["system"] = system_prompt or model.get('systemPrompt')
|
||||
|
||||
logger.info(f"发送Anthropic API请求 (尝试 {attempt + 1}/{max_retries + 1})", extra={
|
||||
'url': f"{api_url.rstrip('/')}/messages",
|
||||
'headers': {k: v if k != 'x-api-key' else '***HIDDEN***' for k, v in headers.items()},
|
||||
'request_body': anthropic_request
|
||||
})
|
||||
|
||||
response = await client.post(
|
||||
f"{api_url.rstrip('/')}/messages",
|
||||
headers=headers,
|
||||
json=anthropic_request
|
||||
)
|
||||
else:
|
||||
# OpenAI 和其他兼容的API（包括自定义、本地部署等）
|
||||
|
||||
logger.info(f"发送OpenAI兼容API请求 (尝试 {attempt + 1}/{max_retries + 1})", extra={
|
||||
'url': f"{api_url.rstrip('/')}/chat/completions",
|
||||
'headers': {k: v if k != 'Authorization' else '***HIDDEN***' for k, v in headers.items()},
|
||||
'request_body': request_data
|
||||
})
|
||||
|
||||
response = await client.post(
|
||||
f"{api_url.rstrip('/')}/chat/completions",
|
||||
headers=headers,
|
||||
json=request_data
|
||||
)
|
||||
|
||||
# 处理流式响应
|
||||
if request_data.get('stream', False):
|
||||
return await handle_streaming_response(response, model, attempt + 1, max_retries + 1)
|
||||
|
||||
# 检查响应状态（非流式）
|
||||
if response.status_code == 200:
|
||||
result = response.json()
|
||||
|
||||
# 解析响应 - 根据提供商类型
|
||||
provider = model.get('provider', '').lower()
|
||||
|
||||
if provider == 'anthropic' and "content" in result and len(result["content"]) > 0:
|
||||
# Anthropic格式响应
|
||||
content = result["content"][0]["text"]
|
||||
logger.info(f"API调用成功 (尝试 {attempt + 1})")
|
||||
return {
|
||||
'success': True,
|
||||
'model': model['name'],
|
||||
'content': content,
|
||||
'usage': result.get('usage', {}),
|
||||
'raw_response': result
|
||||
}
|
||||
elif "choices" in result and len(result["choices"]) > 0:
|
||||
# OpenAI和其他兼容API格式响应
|
||||
content = result["choices"][0]["message"]["content"]
|
||||
logger.info(f"API调用成功 (尝试 {attempt + 1})")
|
||||
return {
|
||||
'success': True,
|
||||
'model': model['name'],
|
||||
'content': content,
|
||||
'usage': result.get('usage', {}),
|
||||
'raw_response': result
|
||||
}
|
||||
|
||||
return {
|
||||
'success': False,
|
||||
'error': '无法解析API响应',
|
||||
'raw_response': result
|
||||
}
|
||||
else:
|
||||
error_msg = f"API调用失败 (状态码: {response.status_code})"
|
||||
try:
|
||||
error_detail = response.json()
|
||||
error_msg += f": {error_detail}"
|
||||
except:
|
||||
error_msg += f": {response.text}"
|
||||
|
||||
last_error = {
|
||||
'success': False,
|
||||
'error': error_msg,
|
||||
'status_code': response.status_code
|
||||
}
|
||||
|
||||
# 如果不是最后一次尝试，等待后重试
|
||||
if attempt < max_retries:
|
||||
logger.warning(f"API调用失败，{retry_delay}秒后重试 (尝试 {attempt + 1}/{max_retries + 1}): {error_msg}")
|
||||
await asyncio.sleep(retry_delay)
|
||||
continue
|
||||
else:
|
||||
# 最后一次尝试失败，返回错误
|
||||
return last_error
|
||||
|
||||
except httpx.TimeoutException as e:
|
||||
last_error = {
|
||||
'success': False,
|
||||
'error': 'API调用超时',
|
||||
'timeout': model.get('timeout', 30)
|
||||
}
|
||||
logger.warning(f"API调用超时 (尝试 {attempt + 1}/{max_retries + 1})")
|
||||
# 如果不是最后一次尝试，等待后重试
|
||||
if attempt < max_retries:
|
||||
await asyncio.sleep(retry_delay)
|
||||
continue
|
||||
else:
|
||||
return last_error
|
||||
|
||||
except httpx.RequestError as e:
|
||||
last_error = {
|
||||
'success': False,
|
||||
'error': f'网络请求错误: {str(e)}'
|
||||
}
|
||||
logger.warning(f"网络请求错误 (尝试 {attempt + 1}/{max_retries + 1}): {str(e)}")
|
||||
# 如果不是最后一次尝试，等待后重试
|
||||
if attempt < max_retries:
|
||||
await asyncio.sleep(retry_delay)
|
||||
continue
|
||||
else:
|
||||
return last_error
|
||||
|
||||
except Exception as e:
|
||||
last_error = {
|
||||
'success': False,
|
||||
'error': f'调用失败: {str(e)}',
|
||||
'error_type': type(e).__name__
|
||||
}
|
||||
logger.error(f"未知错误 (尝试 {attempt + 1}/{max_retries + 1}): {str(e)}")
|
||||
# 其他错误不重试，直接返回
|
||||
return last_error
|
||||
|
||||
# 如果所有重试都失败，返回最后一次错误
|
||||
return last_error
|
||||
|
||||
@staticmethod
|
||||
def test_model(model_id: str) -> Dict[str, Any]:
|
||||
"""测试模型连接 - 使用真实的API调用"""
|
||||
import asyncio
|
||||
import threading
|
||||
|
||||
# 使用新线程中的事件循环
|
||||
result_holder = {}
|
||||
|
||||
def run_test():
|
||||
"""在新线程中运行测试"""
|
||||
try:
|
||||
# 直接使用asyncio.run()，不手动设置事件循环
|
||||
test_result = asyncio.run(
|
||||
ModelManager.call_model(
|
||||
model_id=model_id,
|
||||
prompt="你好，请回复'测试成功'"
|
||||
)
|
||||
)
|
||||
|
||||
result_holder['success'] = True
|
||||
result_holder['result'] = test_result
|
||||
|
||||
except Exception as e:
|
||||
result_holder['success'] = False
|
||||
result_holder['error'] = str(e)
|
||||
|
||||
# 在新线程中运行
|
||||
thread = threading.Thread(target=run_test)
|
||||
thread.start()
|
||||
thread.join()
|
||||
|
||||
# 检查结果
|
||||
if not result_holder.get('success'):
|
||||
error = result_holder.get('error', '未知错误')
|
||||
logger.error(f"测试模型连接时发生错误: {error}")
|
||||
|
||||
# 更新模型状态为连接失败
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
if model:
|
||||
ModelManager.update_model(model_id, {'status': '连接失败'})
|
||||
|
||||
return {
|
||||
'model_id': model_id,
|
||||
'success': False,
|
||||
'status': '连接失败',
|
||||
'message': f'测试过程出错: {error}',
|
||||
'error': error
|
||||
}
|
||||
|
||||
test_result = result_holder.get('result', {})
|
||||
|
||||
# 检查测试结果
|
||||
success = test_result.get('success', False)
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
|
||||
# 更新模型状态
|
||||
if model:
|
||||
if success:
|
||||
model['status'] = '已测试'
|
||||
message = '连接测试成功'
|
||||
else:
|
||||
model['status'] = '连接失败'
|
||||
message = f'连接测试失败: {test_result.get("error", "未知错误")}'
|
||||
|
||||
# 保存更新
|
||||
ModelManager.update_model(model_id, {'status': model['status']})
|
||||
|
||||
return {
|
||||
'model_id': model_id,
|
||||
'success': success,
|
||||
'status': model['status'] if model else '未知',
|
||||
'message': message,
|
||||
'test_result': test_result
|
||||
}
|
||||
|
||||
|
||||
class ModelsAPI(BaseAPI):
|
||||
"""模型配置管理API"""
|
||||
|
||||
def __init__(self):
|
||||
"""初始化"""
|
||||
super().__init__()
|
||||
self.logger.info("ModelsAPI 初始化完成")
|
||||
|
||||
# API路由定义
|
||||
|
||||
@get("/")
|
||||
async def get_models(self):
|
||||
"""获取所有模型配置"""
|
||||
try:
|
||||
models = ModelManager.load_models()
|
||||
return self.success({
|
||||
'models': models,
|
||||
'total': len(models)
|
||||
}, "获取模型配置成功")
|
||||
except Exception as e:
|
||||
self.logger.error(f"获取模型配置失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@get("/{model_id}")
|
||||
async def get_model(self, model_id: str):
|
||||
"""获取单个模型配置"""
|
||||
try:
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
if not model:
|
||||
raise HTTPException(status_code=404, detail="模型不存在")
|
||||
|
||||
return self.success(model, "获取模型配置成功")
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"获取模型配置失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@post("/")
|
||||
async def create_model(self, model_data: Dict[str, Any] = Body(...)):
|
||||
"""创建新模型配置"""
|
||||
try:
|
||||
# 验证必填字段
|
||||
if not model_data.get('name'):
|
||||
raise HTTPException(status_code=400, detail="模型名称不能为空")
|
||||
|
||||
new_model = ModelManager.create_model(model_data)
|
||||
|
||||
return self.success(new_model, "创建模型配置成功")
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"创建模型配置失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@put("/{model_id}")
|
||||
async def update_model(self, model_id: str, model_data: Dict[str, Any] = Body(...)):
|
||||
"""更新模型配置"""
|
||||
try:
|
||||
# 验证模型是否存在
|
||||
existing_model = ModelManager.get_model_by_id(model_id)
|
||||
if not existing_model:
|
||||
raise HTTPException(status_code=404, detail="模型不存在")
|
||||
|
||||
updated_model = ModelManager.update_model(model_id, model_data)
|
||||
|
||||
return self.success(updated_model, "更新模型配置成功")
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"更新模型配置失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@delete("/{model_id}")
|
||||
async def delete_model(self, model_id: str):
|
||||
"""删除模型配置"""
|
||||
try:
|
||||
# 验证模型是否存在
|
||||
existing_model = ModelManager.get_model_by_id(model_id)
|
||||
if not existing_model:
|
||||
raise HTTPException(status_code=404, detail="模型不存在")
|
||||
|
||||
success = ModelManager.delete_model(model_id)
|
||||
|
||||
if success:
|
||||
return self.success(None, "删除模型配置成功")
|
||||
else:
|
||||
raise HTTPException(status_code=500, detail="删除模型配置失败")
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"删除模型配置失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@post("/{model_id}/test")
|
||||
async def test_model_connection(self, model_id: str):
|
||||
"""测试模型连接"""
|
||||
try:
|
||||
# 直接调用异步的call_model方法
|
||||
result = await ModelManager.call_model(
|
||||
model_id=model_id,
|
||||
prompt="你好，请回复'测试成功'"
|
||||
)
|
||||
|
||||
# 更新模型状态
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
if model:
|
||||
if result.get('success'):
|
||||
model['status'] = '已测试'
|
||||
message = '连接测试成功'
|
||||
else:
|
||||
model['status'] = '连接失败'
|
||||
message = f'连接测试失败: {result.get("error", "未知错误")}'
|
||||
|
||||
# 保存更新
|
||||
ModelManager.update_model(model_id, {'status': model['status']})
|
||||
|
||||
test_result = {
|
||||
'model_id': model_id,
|
||||
'success': result.get('success', False),
|
||||
'status': model['status'] if model else '未知',
|
||||
'message': message,
|
||||
'test_result': result
|
||||
}
|
||||
|
||||
return self.success(test_result, message)
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"测试模型连接失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@post("/{model_id}/call")
|
||||
async def call_model_api(self, model_id: str, request_data: Dict[str, Any] = Body(...)):
|
||||
"""调用模型进行对话（支持流式输出）"""
|
||||
try:
|
||||
# 获取请求参数
|
||||
prompt = request_data.get('prompt', '')
|
||||
system_prompt = request_data.get('systemPrompt', None)
|
||||
stream_enabled = request_data.get('stream', False)
|
||||
|
||||
if not prompt:
|
||||
raise HTTPException(status_code=400, detail="提示词不能为空")
|
||||
|
||||
# 如果启用流式，返回流式响应
|
||||
if stream_enabled:
|
||||
return StreamingResponse(
|
||||
self._stream_data(model_id, prompt, system_prompt),
|
||||
media_type="text/plain",
|
||||
headers={
|
||||
"Cache-Control": "no-cache",
|
||||
"Connection": "keep-alive",
|
||||
"Transfer-Encoding": "chunked"
|
||||
}
|
||||
)
|
||||
else:
|
||||
# 普通非流式调用
|
||||
result = await ModelManager.call_model(
|
||||
model_id=model_id,
|
||||
prompt=prompt,
|
||||
system_prompt=system_prompt
|
||||
)
|
||||
return self.success(result, "模型调用成功" if result.get('success') else "模型调用失败")
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
self.logger.error(f"调用模型失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
async def _stream_data(self, model_id: str, prompt: str, system_prompt: Optional[str] = None):
|
||||
"""真正的流式输出数据"""
|
||||
try:
|
||||
# 重新调用模型，获取流式响应
|
||||
model = ModelManager.get_model_by_id(model_id)
|
||||
if not model:
|
||||
yield "data: " + json.dumps({"error": "模型不存在", "done": True}) + "\n\n"
|
||||
return
|
||||
|
||||
# 设置流式请求
|
||||
api_url = model.get('apiUrl', '').strip()
|
||||
api_key = model.get('apiKey', '').strip()
|
||||
version = model.get('version', '').strip()
|
||||
provider = model.get('provider', '').strip()
|
||||
|
||||
# 准备请求数据
|
||||
request_data = {
|
||||
"model": version,
|
||||
"messages": [],
|
||||
"temperature": model.get('temperature', 0.7),
|
||||
"top_p": model.get('topP', 1.0),
|
||||
"max_tokens": model.get('maxTokens', 2048),
|
||||
"stream": True # 启用流式
|
||||
}
|
||||
|
||||
# 添加系统提示词
|
||||
if system_prompt:
|
||||
request_data["messages"].append({
|
||||
"role": "system",
|
||||
"content": system_prompt
|
||||
})
|
||||
elif model.get('systemPrompt'):
|
||||
request_data["messages"].append({
|
||||
"role": "system",
|
||||
"content": model.get('systemPrompt')
|
||||
})
|
||||
|
||||
# 添加用户提示词
|
||||
request_data["messages"].append({
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
})
|
||||
|
||||
# 设置请求头
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
if api_key:
|
||||
if provider.lower() == 'anthropic':
|
||||
headers["x-api-key"] = api_key
|
||||
headers["anthropic-version"] = "2023-06-01"
|
||||
else:
|
||||
headers["Authorization"] = f"Bearer {api_key}"
|
||||
|
||||
# 发送流式请求
|
||||
async with httpx.AsyncClient(timeout=60) as client:
|
||||
if provider.lower() == 'anthropic':
|
||||
# Anthropic流式请求
|
||||
anthropic_request = {
|
||||
"model": version,
|
||||
"max_tokens": request_data["max_tokens"],
|
||||
"messages": request_data["messages"][1:],
|
||||
"stream": True
|
||||
}
|
||||
if system_prompt or model.get('systemPrompt'):
|
||||
anthropic_request["system"] = system_prompt or model.get('systemPrompt')
|
||||
|
||||
async with client.stream(
|
||||
"POST",
|
||||
f"{api_url.rstrip('/')}/messages",
|
||||
headers=headers,
|
||||
json=anthropic_request
|
||||
) as response:
|
||||
async for line in response.aiter_lines():
|
||||
if line.startswith('data: '):
|
||||
data_str = line[6:]
|
||||
if data_str.strip() == '[DONE]':
|
||||
yield "data: " + json.dumps({"content": "", "done": True}) + "\n\n"
|
||||
break
|
||||
|
||||
try:
|
||||
chunk_data = json.loads(data_str)
|
||||
if "content" in chunk_data and len(chunk_data["content"]) > 0:
|
||||
content = chunk_data["content"][0]["text"]
|
||||
yield f"data: {json.dumps({'content': content, 'done': False})}\n\n"
|
||||
except:
|
||||
continue
|
||||
else:
|
||||
# OpenAI兼容流式请求
|
||||
async with client.stream(
|
||||
"POST",
|
||||
f"{api_url.rstrip('/')}/chat/completions",
|
||||
headers=headers,
|
||||
json=request_data
|
||||
) as response:
|
||||
async for line in response.aiter_lines():
|
||||
if line.startswith('data: '):
|
||||
data_str = line[6:]
|
||||
if data_str.strip() == '[DONE]':
|
||||
yield "data: " + json.dumps({"content": "", "done": True}) + "\n\n"
|
||||
break
|
||||
|
||||
try:
|
||||
chunk_data = json.loads(data_str)
|
||||
if "choices" in chunk_data and len(chunk_data["choices"]) > 0:
|
||||
delta = chunk_data["choices"][0].get("delta", {})
|
||||
if "content" in delta and delta["content"]:
|
||||
content = delta["content"]
|
||||
yield f"data: {json.dumps({'content': content, 'done': False})}\n\n"
|
||||
except:
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
yield "data: " + json.dumps({"error": str(e), "done": True}) + "\n\n"
|
||||
|
||||
@post("/batch-delete")
|
||||
async def batch_delete_models(self, model_ids: List[str] = Body(...)):
|
||||
"""批量删除模型"""
|
||||
try:
|
||||
deleted_count = 0
|
||||
failed_count = 0
|
||||
|
||||
for model_id in model_ids:
|
||||
if ModelManager.delete_model(model_id):
|
||||
deleted_count += 1
|
||||
else:
|
||||
failed_count += 1
|
||||
|
||||
return self.success({
|
||||
'deleted_count': deleted_count,
|
||||
'failed_count': failed_count
|
||||
}, f'批量删除完成: 成功 {deleted_count} 个, 失败 {failed_count} 个')
|
||||
except Exception as e:
|
||||
self.logger.error(f"批量删除模型失败: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@get("/providers/list")
|
||||
async def get_model_providers(self):
|
||||
"""获取模型提供方列表"""
|
||||
providers = [
|
||||
{'value': 'openai', 'label': 'OpenAI'},
|
||||
{'value': 'anthropic', 'label': 'Anthropic'},
|
||||
{'value': 'azure', 'label': 'Azure OpenAI'},
|
||||
{'value': 'local', 'label': '本地部署'},
|
||||
{'value': 'custom', 'label': '自定义'}
|
||||
]
|
||||
|
||||
return self.success(providers, "获取提供方列表成功")
|
||||
|
||||
@get("/types/list")
|
||||
async def get_model_types(self):
|
||||
"""获取模型类型列表"""
|
||||
types = [
|
||||
{'value': 'gpt', 'label': 'GPT 系列'},
|
||||
{'value': 'bert', 'label': 'BERT 系列'},
|
||||
{'value': 'llama', 'label': 'LLaMA 系列'},
|
||||
{'value': 'claude', 'label': 'Claude 系列'},
|
||||
{'value': 'custom', 'label': '自定义'}
|
||||
]
|
||||
|
||||
return self.success(types, "获取模型类型列表成功")
|
||||
|
||||
@get("/status/list")
|
||||
async def get_model_statuses(self):
|
||||
"""获取模型状态列表"""
|
||||
statuses = [
|
||||
{'value': '已测试', 'label': '已测试', 'color': 'green'},
|
||||
{'value': '连接失败', 'label': '连接失败', 'color': 'red'},
|
||||
{'value': '未测试', 'label': '未测试', 'color': 'gray'}
|
||||
]
|
||||
|
||||
return self.success(statuses, "获取模型状态列表成功")
|
||||
|
||||
|
||||
# 创建API实例
|
||||
models_api = ModelsAPI()
|
||||
@@ -246,8 +246,19 @@ def setup_routes(app: FastAPI):
|
||||
|
||||
registration_result = auto_register_routes(app)
|
||||
|
||||
# 挂载静态文件目录（放在最后，避免覆盖其他路由）
|
||||
app.mount("/", StaticFiles(directory="static", html=True), name="static")
|
||||
# 挂载静态文件目录
|
||||
from fastapi.responses import FileResponse
|
||||
|
||||
# 为前端页面创建特定路由
|
||||
@app.get("/dashboard")
|
||||
async def dashboard():
|
||||
"""前端监控界面"""
|
||||
return FileResponse("static/index.html")
|
||||
|
||||
# 只挂载静态资源（CSS, JS, 图片等）- 如果目录存在
|
||||
import os
|
||||
if os.path.exists("static"):
|
||||
app.mount("/static", StaticFiles(directory="static"), name="static")
|
||||
|
||||
# 生成离线API文档
|
||||
generate_docs(app)
|
||||
|
||||
@@ -1 +1 @@
|
||||
0dc715b603074fca864c0c5074317e6a
|
||||
0bbf8a1a0807bf0cee9cf3cc5634f318
|
||||
@@ -689,14 +689,14 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/api/datasets/{file_id}": {
|
||||
"/datasets/{file_id}": {
|
||||
"delete": {
|
||||
"tags": [
|
||||
"Datasets"
|
||||
],
|
||||
"summary": "delete_dataset",
|
||||
"description": "删除数据集\n\nArgs:\n file_id: 文件ID\n\nReturns:\n StandardResponse: 包含删除结果的标准响应",
|
||||
"operationId": "delete_dataset_api_datasets__file_id__delete",
|
||||
"operationId": "delete_dataset_datasets__file_id__delete",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "file_id",
|
||||
@@ -737,7 +737,7 @@
|
||||
],
|
||||
"summary": "get_dataset",
|
||||
"description": "获取特定数据集的详细信息\n\nArgs:\n file_id: 文件ID\n\nReturns:\n StandardResponse: 包含数据集详情的标准响应",
|
||||
"operationId": "get_dataset_api_datasets__file_id__get",
|
||||
"operationId": "get_dataset_datasets__file_id__get",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "file_id",
|
||||
@@ -773,14 +773,14 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/api/datasets/{file_id}/content": {
|
||||
"/datasets/{file_id}/content": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Datasets"
|
||||
],
|
||||
"summary": "get_dataset_content",
|
||||
"description": "获取数据集文件内容（前N条记录）\n\nArgs:\n file_id: 文件ID\n limit: 返回的记录数量，默认5条\n\nReturns:\n StandardResponse: 包含数据集内容的标准响应",
|
||||
"operationId": "get_dataset_content_api_datasets__file_id__content_get",
|
||||
"operationId": "get_dataset_content_datasets__file_id__content_get",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "file_id",
|
||||
@@ -826,14 +826,14 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/api/datasets/list-files": {
|
||||
"/datasets/list-files": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Datasets"
|
||||
],
|
||||
"summary": "list_data_files",
|
||||
"description": "查询data目录下的文件列表\n\nReturns:\n StandardResponse: 包含文件列表的标准响应",
|
||||
"operationId": "list_data_files_api_datasets_list_files_get",
|
||||
"operationId": "list_data_files_datasets_list_files_get",
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
@@ -848,14 +848,14 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/api/datasets": {
|
||||
"/datasets": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Datasets"
|
||||
],
|
||||
"summary": "list_datasets",
|
||||
"description": "获取所有数据集列表\n\nArgs:\n list_all: 是否列出data目录下的所有文件（物理文件），默认False（只列出API上传的文件）\n\nReturns:\n StandardResponse: 包含数据集列表的标准响应",
|
||||
"operationId": "list_datasets_api_datasets_get",
|
||||
"operationId": "list_datasets_datasets_get",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "list_all",
|
||||
@@ -892,19 +892,19 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/api/datasets/upload": {
|
||||
"/datasets/upload": {
|
||||
"post": {
|
||||
"tags": [
|
||||
"Datasets"
|
||||
],
|
||||
"summary": "upload_dataset",
|
||||
"description": "上传数据集文件\n\nArgs:\n file: 上传的文件（支持 .json, .jsonl 格式）\n description: 文件描述（可选）\n\nReturns:\n StandardResponse: 包含上传结果的标准响应",
|
||||
"operationId": "upload_dataset_api_datasets_upload_post",
|
||||
"operationId": "upload_dataset_datasets_upload_post",
|
||||
"requestBody": {
|
||||
"content": {
|
||||
"multipart/form-data": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/Body_upload_dataset_api_datasets_upload_post"
|
||||
"$ref": "#/components/schemas/Body_upload_dataset_datasets_upload_post"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -933,6 +933,392 @@
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/batch-delete": {
|
||||
"post": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "batch_delete_models",
|
||||
"description": "批量删除模型",
|
||||
"operationId": "batch_delete_models_models_batch_delete_post",
|
||||
"requestBody": {
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"items": {
|
||||
"type": "string"
|
||||
},
|
||||
"type": "array",
|
||||
"title": "Model Ids"
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": true
|
||||
},
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/{model_id}/call": {
|
||||
"post": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "call_model_api",
|
||||
"description": "调用模型进行对话（支持流式输出）",
|
||||
"operationId": "call_model_api_models__model_id__call_post",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "model_id",
|
||||
"in": "path",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Model Id"
|
||||
}
|
||||
}
|
||||
],
|
||||
"requestBody": {
|
||||
"required": true,
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"title": "Request Data"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "get_models",
|
||||
"description": "获取所有模型配置",
|
||||
"operationId": "get_models_models__get",
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"post": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "create_model",
|
||||
"description": "创建新模型配置",
|
||||
"operationId": "create_model_models__post",
|
||||
"requestBody": {
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"title": "Model Data"
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": true
|
||||
},
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/{model_id}": {
|
||||
"delete": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "delete_model",
|
||||
"description": "删除模型配置",
|
||||
"operationId": "delete_model_models__model_id__delete",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "model_id",
|
||||
"in": "path",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Model Id"
|
||||
}
|
||||
}
|
||||
],
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"get": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "get_model",
|
||||
"description": "获取单个模型配置",
|
||||
"operationId": "get_model_models__model_id__get",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "model_id",
|
||||
"in": "path",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Model Id"
|
||||
}
|
||||
}
|
||||
],
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"put": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "update_model",
|
||||
"description": "更新模型配置",
|
||||
"operationId": "update_model_models__model_id__put",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "model_id",
|
||||
"in": "path",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Model Id"
|
||||
}
|
||||
}
|
||||
],
|
||||
"requestBody": {
|
||||
"required": true,
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"title": "Model Data"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/providers/list": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "get_model_providers",
|
||||
"description": "获取模型提供方列表",
|
||||
"operationId": "get_model_providers_models_providers_list_get",
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/status/list": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "get_model_statuses",
|
||||
"description": "获取模型状态列表",
|
||||
"operationId": "get_model_statuses_models_status_list_get",
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/types/list": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "get_model_types",
|
||||
"description": "获取模型类型列表",
|
||||
"operationId": "get_model_types_models_types_list_get",
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/models/{model_id}/test": {
|
||||
"post": {
|
||||
"tags": [
|
||||
"Models"
|
||||
],
|
||||
"summary": "test_model_connection",
|
||||
"description": "测试模型连接",
|
||||
"operationId": "test_model_connection_models__model_id__test_post",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "model_id",
|
||||
"in": "path",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Model Id"
|
||||
}
|
||||
}
|
||||
],
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successful Response",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/HTTPValidationError"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"components": {
|
||||
@@ -971,7 +1357,7 @@
|
||||
"title": "BatchDownloadRequest",
|
||||
"description": "批量下载请求模型"
|
||||
},
|
||||
"Body_upload_dataset_api_datasets_upload_post": {
|
||||
"Body_upload_dataset_datasets_upload_post": {
|
||||
"properties": {
|
||||
"file": {
|
||||
"type": "string",
|
||||
@@ -994,7 +1380,7 @@
|
||||
"required": [
|
||||
"file"
|
||||
],
|
||||
"title": "Body_upload_dataset_api_datasets_upload_post"
|
||||
"title": "Body_upload_dataset_datasets_upload_post"
|
||||
},
|
||||
"HTTPValidationError": {
|
||||
"properties": {
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
247
request/xrequest/Scripts/Activate.ps1
Normal file
247
request/xrequest/Scripts/Activate.ps1
Normal file
@@ -0,0 +1,247 @@
|
||||
<#
|
||||
.Synopsis
|
||||
Activate a Python virtual environment for the current PowerShell session.
|
||||
|
||||
.Description
|
||||
Pushes the python executable for a virtual environment to the front of the
|
||||
$Env:PATH environment variable and sets the prompt to signify that you are
|
||||
in a Python virtual environment. Makes use of the command line switches as
|
||||
well as the `pyvenv.cfg` file values present in the virtual environment.
|
||||
|
||||
.Parameter VenvDir
|
||||
Path to the directory that contains the virtual environment to activate. The
|
||||
default value for this is the parent of the directory that the Activate.ps1
|
||||
script is located within.
|
||||
|
||||
.Parameter Prompt
|
||||
The prompt prefix to display when this virtual environment is activated. By
|
||||
default, this prompt is the name of the virtual environment folder (VenvDir)
|
||||
surrounded by parentheses and followed by a single space (ie. '(.venv) ').
|
||||
|
||||
.Example
|
||||
Activate.ps1
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -Verbose
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script,
|
||||
and shows extra information about the activation as it executes.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv
|
||||
Activates the Python virtual environment located in the specified location.
|
||||
|
||||
.Example
|
||||
Activate.ps1 -Prompt "MyPython"
|
||||
Activates the Python virtual environment that contains the Activate.ps1 script,
|
||||
and prefixes the current prompt with the specified string (surrounded in
|
||||
parentheses) while the virtual environment is active.
|
||||
|
||||
.Notes
|
||||
On Windows, it may be required to enable this Activate.ps1 script by setting the
|
||||
execution policy for the user. You can do this by issuing the following PowerShell
|
||||
command:
|
||||
|
||||
PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
|
||||
|
||||
For more information on Execution Policies:
|
||||
https://go.microsoft.com/fwlink/?LinkID=135170
|
||||
|
||||
#>
|
||||
Param(
|
||||
[Parameter(Mandatory = $false)]
|
||||
[String]
|
||||
$VenvDir,
|
||||
[Parameter(Mandatory = $false)]
|
||||
[String]
|
||||
$Prompt
|
||||
)
|
||||
|
||||
<# Function declarations --------------------------------------------------- #>
|
||||
|
||||
<#
|
||||
.Synopsis
|
||||
Remove all shell session elements added by the Activate script, including the
|
||||
addition of the virtual environment's Python executable from the beginning of
|
||||
the PATH variable.
|
||||
|
||||
.Parameter NonDestructive
|
||||
If present, do not remove this function from the global namespace for the
|
||||
session.
|
||||
|
||||
#>
|
||||
function global:deactivate ([switch]$NonDestructive) {
|
||||
# Revert to original values
|
||||
|
||||
# The prior prompt:
|
||||
if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) {
|
||||
Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt
|
||||
Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT
|
||||
}
|
||||
|
||||
# The prior PYTHONHOME:
|
||||
if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) {
|
||||
Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME
|
||||
Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME
|
||||
}
|
||||
|
||||
# The prior PATH:
|
||||
if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) {
|
||||
Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH
|
||||
Remove-Item -Path Env:_OLD_VIRTUAL_PATH
|
||||
}
|
||||
|
||||
# Just remove the VIRTUAL_ENV altogether:
|
||||
if (Test-Path -Path Env:VIRTUAL_ENV) {
|
||||
Remove-Item -Path env:VIRTUAL_ENV
|
||||
}
|
||||
|
||||
# Just remove VIRTUAL_ENV_PROMPT altogether.
|
||||
if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) {
|
||||
Remove-Item -Path env:VIRTUAL_ENV_PROMPT
|
||||
}
|
||||
|
||||
# Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether:
|
||||
if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) {
|
||||
Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force
|
||||
}
|
||||
|
||||
# Leave deactivate function in the global namespace if requested:
|
||||
if (-not $NonDestructive) {
|
||||
Remove-Item -Path function:deactivate
|
||||
}
|
||||
}
|
||||
|
||||
<#
|
||||
.Description
|
||||
Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the
|
||||
given folder, and returns them in a map.
|
||||
|
||||
For each line in the pyvenv.cfg file, if that line can be parsed into exactly
|
||||
two strings separated by `=` (with any amount of whitespace surrounding the =)
|
||||
then it is considered a `key = value` line. The left hand string is the key,
|
||||
the right hand is the value.
|
||||
|
||||
If the value starts with a `'` or a `"` then the first and last character is
|
||||
stripped from the value before being captured.
|
||||
|
||||
.Parameter ConfigDir
|
||||
Path to the directory that contains the `pyvenv.cfg` file.
|
||||
#>
|
||||
function Get-PyVenvConfig(
|
||||
[String]
|
||||
$ConfigDir
|
||||
) {
|
||||
Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg"
|
||||
|
||||
# Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue).
|
||||
$pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue
|
||||
|
||||
# An empty map will be returned if no config file is found.
|
||||
$pyvenvConfig = @{ }
|
||||
|
||||
if ($pyvenvConfigPath) {
|
||||
|
||||
Write-Verbose "File exists, parse `key = value` lines"
|
||||
$pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath
|
||||
|
||||
$pyvenvConfigContent | ForEach-Object {
|
||||
$keyval = $PSItem -split "\s*=\s*", 2
|
||||
if ($keyval[0] -and $keyval[1]) {
|
||||
$val = $keyval[1]
|
||||
|
||||
# Remove extraneous quotations around a string value.
|
||||
if ("'""".Contains($val.Substring(0, 1))) {
|
||||
$val = $val.Substring(1, $val.Length - 2)
|
||||
}
|
||||
|
||||
$pyvenvConfig[$keyval[0]] = $val
|
||||
Write-Verbose "Adding Key: '$($keyval[0])'='$val'"
|
||||
}
|
||||
}
|
||||
}
|
||||
return $pyvenvConfig
|
||||
}
|
||||
|
||||
|
||||
<# Begin Activate script --------------------------------------------------- #>
|
||||
|
||||
# Determine the containing directory of this script
|
||||
$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition
|
||||
$VenvExecDir = Get-Item -Path $VenvExecPath
|
||||
|
||||
Write-Verbose "Activation script is located in path: '$VenvExecPath'"
|
||||
Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)"
|
||||
Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)"
|
||||
|
||||
# Set values required in priority: CmdLine, ConfigFile, Default
|
||||
# First, get the location of the virtual environment, it might not be
|
||||
# VenvExecDir if specified on the command line.
|
||||
if ($VenvDir) {
|
||||
Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values"
|
||||
}
|
||||
else {
|
||||
Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir."
|
||||
$VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/")
|
||||
Write-Verbose "VenvDir=$VenvDir"
|
||||
}
|
||||
|
||||
# Next, read the `pyvenv.cfg` file to determine any required value such
|
||||
# as `prompt`.
|
||||
$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir
|
||||
|
||||
# Next, set the prompt from the command line, or the config file, or
|
||||
# just use the name of the virtual environment folder.
|
||||
if ($Prompt) {
|
||||
Write-Verbose "Prompt specified as argument, using '$Prompt'"
|
||||
}
|
||||
else {
|
||||
Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value"
|
||||
if ($pyvenvCfg -and $pyvenvCfg['prompt']) {
|
||||
Write-Verbose " Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'"
|
||||
$Prompt = $pyvenvCfg['prompt'];
|
||||
}
|
||||
else {
|
||||
Write-Verbose " Setting prompt based on parent's directory's name. (Is the directory name passed to venv module when creating the virtual environment)"
|
||||
Write-Verbose " Got leaf-name of $VenvDir='$(Split-Path -Path $venvDir -Leaf)'"
|
||||
$Prompt = Split-Path -Path $venvDir -Leaf
|
||||
}
|
||||
}
|
||||
|
||||
Write-Verbose "Prompt = '$Prompt'"
|
||||
Write-Verbose "VenvDir='$VenvDir'"
|
||||
|
||||
# Deactivate any currently active virtual environment, but leave the
|
||||
# deactivate function in place.
|
||||
deactivate -nondestructive
|
||||
|
||||
# Now set the environment variable VIRTUAL_ENV, used by many tools to determine
|
||||
# that there is an activated venv.
|
||||
$env:VIRTUAL_ENV = $VenvDir
|
||||
|
||||
if (-not $Env:VIRTUAL_ENV_DISABLE_PROMPT) {
|
||||
|
||||
Write-Verbose "Setting prompt to '$Prompt'"
|
||||
|
||||
# Set the prompt to include the env name
|
||||
# Make sure _OLD_VIRTUAL_PROMPT is global
|
||||
function global:_OLD_VIRTUAL_PROMPT { "" }
|
||||
Copy-Item -Path function:prompt -Destination function:_OLD_VIRTUAL_PROMPT
|
||||
New-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Description "Python virtual environment prompt prefix" -Scope Global -Option ReadOnly -Visibility Public -Value $Prompt
|
||||
|
||||
function global:prompt {
|
||||
Write-Host -NoNewline -ForegroundColor Green "($_PYTHON_VENV_PROMPT_PREFIX) "
|
||||
_OLD_VIRTUAL_PROMPT
|
||||
}
|
||||
$env:VIRTUAL_ENV_PROMPT = $Prompt
|
||||
}
|
||||
|
||||
# Clear PYTHONHOME
|
||||
if (Test-Path -Path Env:PYTHONHOME) {
|
||||
Copy-Item -Path Env:PYTHONHOME -Destination Env:_OLD_VIRTUAL_PYTHONHOME
|
||||
Remove-Item -Path Env:PYTHONHOME
|
||||
}
|
||||
|
||||
# Add the venv to the PATH
|
||||
Copy-Item -Path Env:PATH -Destination Env:_OLD_VIRTUAL_PATH
|
||||
$Env:PATH = "$VenvExecDir$([System.IO.Path]::PathSeparator)$Env:PATH"
|
||||
63
request/xrequest/Scripts/activate
Normal file
63
request/xrequest/Scripts/activate
Normal file
@@ -0,0 +1,63 @@
|
||||
# This file must be used with "source bin/activate" *from bash*
|
||||
# you cannot run it directly
|
||||
|
||||
deactivate () {
|
||||
# reset old environment variables
|
||||
if [ -n "${_OLD_VIRTUAL_PATH:-}" ] ; then
|
||||
PATH="${_OLD_VIRTUAL_PATH:-}"
|
||||
export PATH
|
||||
unset _OLD_VIRTUAL_PATH
|
||||
fi
|
||||
if [ -n "${_OLD_VIRTUAL_PYTHONHOME:-}" ] ; then
|
||||
PYTHONHOME="${_OLD_VIRTUAL_PYTHONHOME:-}"
|
||||
export PYTHONHOME
|
||||
unset _OLD_VIRTUAL_PYTHONHOME
|
||||
fi
|
||||
|
||||
# Call hash to forget past commands. Without forgetting
|
||||
# past commands the $PATH changes we made may not be respected
|
||||
hash -r 2> /dev/null
|
||||
|
||||
if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then
|
||||
PS1="${_OLD_VIRTUAL_PS1:-}"
|
||||
export PS1
|
||||
unset _OLD_VIRTUAL_PS1
|
||||
fi
|
||||
|
||||
unset VIRTUAL_ENV
|
||||
unset VIRTUAL_ENV_PROMPT
|
||||
if [ ! "${1:-}" = "nondestructive" ] ; then
|
||||
# Self destruct!
|
||||
unset -f deactivate
|
||||
fi
|
||||
}
|
||||
|
||||
# unset irrelevant variables
|
||||
deactivate nondestructive
|
||||
|
||||
VIRTUAL_ENV='D:\Code\Project\FT-Platform\request\xrequest'
|
||||
export VIRTUAL_ENV
|
||||
|
||||
_OLD_VIRTUAL_PATH="$PATH"
|
||||
PATH="$VIRTUAL_ENV/"Scripts":$PATH"
|
||||
export PATH
|
||||
|
||||
# unset PYTHONHOME if set
|
||||
# this will fail if PYTHONHOME is set to the empty string (which is bad anyway)
|
||||
# could use `if (set -u; : $PYTHONHOME) ;` in bash
|
||||
if [ -n "${PYTHONHOME:-}" ] ; then
|
||||
_OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}"
|
||||
unset PYTHONHOME
|
||||
fi
|
||||
|
||||
if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then
|
||||
_OLD_VIRTUAL_PS1="${PS1:-}"
|
||||
PS1='(xrequest) '"${PS1:-}"
|
||||
export PS1
|
||||
VIRTUAL_ENV_PROMPT='(xrequest) '
|
||||
export VIRTUAL_ENV_PROMPT
|
||||
fi
|
||||
|
||||
# Call hash to forget past commands. Without forgetting
|
||||
# past commands the $PATH changes we made may not be respected
|
||||
hash -r 2> /dev/null
|
||||
34
request/xrequest/Scripts/activate.bat
Normal file
34
request/xrequest/Scripts/activate.bat
Normal file
@@ -0,0 +1,34 @@
|
||||
@echo off
|
||||
|
||||
rem This file is UTF-8 encoded, so we need to update the current code page while executing it
|
||||
for /f "tokens=2 delims=:." %%a in ('"%SystemRoot%\System32\chcp.com"') do (
|
||||
set _OLD_CODEPAGE=%%a
|
||||
)
|
||||
if defined _OLD_CODEPAGE (
|
||||
"%SystemRoot%\System32\chcp.com" 65001 > nul
|
||||
)
|
||||
|
||||
set "VIRTUAL_ENV=D:\Code\Project\FT-Platform\request\xrequest"
|
||||
|
||||
if not defined PROMPT set PROMPT=$P$G
|
||||
|
||||
if defined _OLD_VIRTUAL_PROMPT set PROMPT=%_OLD_VIRTUAL_PROMPT%
|
||||
if defined _OLD_VIRTUAL_PYTHONHOME set PYTHONHOME=%_OLD_VIRTUAL_PYTHONHOME%
|
||||
|
||||
set _OLD_VIRTUAL_PROMPT=%PROMPT%
|
||||
set PROMPT=(xrequest) %PROMPT%
|
||||
|
||||
if defined PYTHONHOME set _OLD_VIRTUAL_PYTHONHOME=%PYTHONHOME%
|
||||
set PYTHONHOME=
|
||||
|
||||
if defined _OLD_VIRTUAL_PATH set PATH=%_OLD_VIRTUAL_PATH%
|
||||
if not defined _OLD_VIRTUAL_PATH set _OLD_VIRTUAL_PATH=%PATH%
|
||||
|
||||
set "PATH=%VIRTUAL_ENV%\Scripts;%PATH%"
|
||||
set "VIRTUAL_ENV_PROMPT=(xrequest) "
|
||||
|
||||
:END
|
||||
if defined _OLD_CODEPAGE (
|
||||
"%SystemRoot%\System32\chcp.com" %_OLD_CODEPAGE% > nul
|
||||
set _OLD_CODEPAGE=
|
||||
)
|
||||
22
request/xrequest/Scripts/deactivate.bat
Normal file
22
request/xrequest/Scripts/deactivate.bat
Normal file
@@ -0,0 +1,22 @@
|
||||
@echo off
|
||||
|
||||
if defined _OLD_VIRTUAL_PROMPT (
|
||||
set "PROMPT=%_OLD_VIRTUAL_PROMPT%"
|
||||
)
|
||||
set _OLD_VIRTUAL_PROMPT=
|
||||
|
||||
if defined _OLD_VIRTUAL_PYTHONHOME (
|
||||
set "PYTHONHOME=%_OLD_VIRTUAL_PYTHONHOME%"
|
||||
set _OLD_VIRTUAL_PYTHONHOME=
|
||||
)
|
||||
|
||||
if defined _OLD_VIRTUAL_PATH (
|
||||
set "PATH=%_OLD_VIRTUAL_PATH%"
|
||||
)
|
||||
|
||||
set _OLD_VIRTUAL_PATH=
|
||||
|
||||
set VIRTUAL_ENV=
|
||||
set VIRTUAL_ENV_PROMPT=
|
||||
|
||||
:END
|
||||
BIN
request/xrequest/Scripts/dotenv.exe
Normal file
BIN
request/xrequest/Scripts/dotenv.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/httpx.exe
Normal file
BIN
request/xrequest/Scripts/httpx.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/pip.exe
Normal file
BIN
request/xrequest/Scripts/pip.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/pip3.11.exe
Normal file
BIN
request/xrequest/Scripts/pip3.11.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/pip3.exe
Normal file
BIN
request/xrequest/Scripts/pip3.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/python.exe
Normal file
BIN
request/xrequest/Scripts/python.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/pythonw.exe
Normal file
BIN
request/xrequest/Scripts/pythonw.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/uvicorn.exe
Normal file
BIN
request/xrequest/Scripts/uvicorn.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/watchfiles.exe
Normal file
BIN
request/xrequest/Scripts/watchfiles.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/websockets.exe
Normal file
BIN
request/xrequest/Scripts/websockets.exe
Normal file
Binary file not shown.
BIN
request/xrequest/Scripts/wheel.exe
Normal file
BIN
request/xrequest/Scripts/wheel.exe
Normal file
Binary file not shown.
5
request/xrequest/pyvenv.cfg
Normal file
5
request/xrequest/pyvenv.cfg
Normal file
@@ -0,0 +1,5 @@
|
||||
home = D:\Softwares\Anaconda\envs\ft
|
||||
include-system-site-packages = false
|
||||
version = 3.11.14
|
||||
executable = D:\Softwares\Anaconda\envs\ft\python.exe
|
||||
command = D:\Softwares\Anaconda\envs\ft\python.exe -m venv D:\Code\Project\FT-Platform\request\xrequest
|
||||
1704
web/pages/main.html
1704
web/pages/main.html
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user