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404 lines
14 KiB
404 lines
14 KiB
# FastAPI 应用主入口
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from fastapi import FastAPI, Request
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from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse, FileResponse
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from fastapi.staticfiles import StaticFiles
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from fastapi.templating import Jinja2Templates
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import sys
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import os
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import json
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import subprocess
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import uuid
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import asyncio
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import zipfile
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from datetime import datetime
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# 创建 FastAPI 应用实例
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app = FastAPI(title="Alpha Transformer", version="1.0.0")
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# Chrome DevTools 健康检查端点（可选，阻止 404 日志）
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@app.get("/.well-known/appspecific/com.chrome.devtools.json")
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async def chrome_devtools_check():
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"""Chrome DevTools 健康检查"""
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return {"status": "ok"}
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# 提供模板目录中的 CSS 和 JS 文件
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@app.get("/styles.css")
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async def get_styles():
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"""提供 styles.css 文件"""
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from fastapi.responses import FileResponse
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return FileResponse("templates/styles.css")
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@app.get("/app.js")
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async def get_app_js():
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"""提供 app.js 文件"""
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from fastapi.responses import FileResponse
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return FileResponse("templates/app.js")
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# 配置 Jinja2 模板引擎，用于渲染 HTML 页面
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templates = Jinja2Templates(directory="templates")
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# 存储正在运行的任务信息（task_id -> 任务状态）
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transformer_tasks = {}
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# 全局配置变量
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app_config = {}
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def load_config():
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"""
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加载配置文件
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读取 config.json 文件，如果有则加载，否则返回空字典
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"""
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config_path = os.path.join(os.path.dirname(__file__), 'config.json')
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if os.path.exists(config_path):
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try:
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with open(config_path, 'r', encoding='utf-8') as f:
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config = json.load(f)
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print(f"✓ 已加载配置文件: {config_path}")
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return config
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except Exception as e:
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print(f"⚠ 加载配置文件失败: {e}")
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return {}
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else:
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print(f"⚠ 配置文件不存在: {config_path}")
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return {}
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# 启动时加载配置
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app_config = load_config()
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@app.get("/", response_class=HTMLResponse)
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async def home():
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# 读取并返回前端首页 HTML
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with open("templates/index.html", "r", encoding="utf-8") as f:
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return f.read()
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@app.get("/api/config/defaults")
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async def get_config_defaults():
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"""
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获取默认配置
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返回 config.json 中的配置作为表单默认值
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"""
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return JSONResponse(content={
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"success": True,
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"config": app_config
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})
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@app.post("/api/config/save")
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async def save_config(request: Request):
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"""
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保存配置到 config.json
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用于在页面上修改配置后保存
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"""
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try:
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data = await request.json()
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# 更新全局配置
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global app_config
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app_config = data
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# 写入文件
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config_path = os.path.join(os.path.dirname(__file__), 'config.json')
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with open(config_path, 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=4, ensure_ascii=False)
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return JSONResponse(content={
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"success": True,
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"message": "配置已保存"
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})
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except Exception as e:
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return JSONResponse(
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status_code=500,
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content={"success": False, "error": str(e)}
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)
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@app.post("/api/generate")
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async def generate_alpha(request: Request):
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"""
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生成 Alpha 变种的 API 端点
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接收前端表单数据，启动 Transformer 脚本执行 Alpha 生成任务
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"""
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print("=" * 50)
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print("收到生成变种请求")
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try:
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# 解析请求数据
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data = await request.json()
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print(f"请求数据: alpha_id={data.get('alpha_id')}, llm_model={data.get('llm_model')}")
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# 生成唯一任务 ID
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task_id = str(uuid.uuid4())
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print(f"生成任务 ID: {task_id}")
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# 定义必须提交的字段
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required_fields = [
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"alpha_id",
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"llm_api_key",
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"llm_base_url",
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"llm_model",
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"brain_username",
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"brain_password"
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]
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# 检查必填字段是否完整
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for field in required_fields:
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if not data.get(field):
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print(f"缺少必填字段: {field}")
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return JSONResponse(
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status_code=400,
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content={"success": False, "error": f"Missing required field: {field}"}
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)
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# 获取脚本所在目录和 Transformer 子目录
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script_dir = os.path.dirname(os.path.abspath(__file__))
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transformer_dir = os.path.join(script_dir, 'Tranformer')
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print(f"Transformer 目录: {transformer_dir}")
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# 构建传递给 Transformer 脚本的配置
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config = {
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"LLM_model_name": data.get('llm_model'),
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"LLM_API_KEY": data.get('llm_api_key'),
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"llm_base_url": data.get('llm_base_url'),
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"username": data.get('brain_username'),
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"password": data.get('brain_password'),
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"alpha_id": data.get('alpha_id'),
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"top_n_datafield": int(data.get('top_n_datafield', 50)),
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"user_region": data.get('user_region'),
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"user_universe": data.get('user_universe'),
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"user_delay": int(data.get('user_delay')) if data.get('user_delay') else None,
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"user_category": data.get('user_category'),
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"user_data_type": data.get('user_data_type', 'MATRIX')
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}
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print(f"配置已构建: LLM_model={config['LLM_model_name']}, alpha_id={config['alpha_id']}")
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# 将配置写入临时 JSON 文件，供 Transformer 脚本读取
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config_path = os.path.join(transformer_dir, f'config_{task_id}.json')
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with open(config_path, 'w', encoding='utf-8') as f:
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json.dump(config, f, indent=4)
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print(f"配置文件已写入: {config_path}")
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try:
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# 启动 Transformer.py 子进程执行 Alpha 生成
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print(f"启动 Transformer 脚本...")
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process = subprocess.run(
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[sys.executable, '-u', os.path.join(transformer_dir, 'Transformer.py'), config_path],
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cwd=transformer_dir,
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capture_output=True,
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text=True,
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timeout=600,
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env={**os.environ, "PYTHONIOENCODING": "utf-8"}
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)
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print(f"Transformer 脚本执行完成，返回码: {process.returncode}")
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# 定义输出文件路径
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output_file = os.path.join(transformer_dir, 'output', 'Alpha_generated_expressions_success.json')
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candidates_file = os.path.join(transformer_dir, 'output', 'Alpha_candidates.json')
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error_file = os.path.join(transformer_dir, 'output', 'Alpha_generated_expressions_error.json')
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# 构建响应数据
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result = {
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"success": True,
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"alpha_id": data.get('alpha_id'),
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"stdout": process.stdout,
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"stderr": process.stderr,
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"return_code": process.returncode
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}
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# 读取成功生成的表达式
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if os.path.exists(output_file):
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print(f"读取成功表达式文件: {output_file}")
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with open(output_file, 'r', encoding='utf-8') as f:
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result['expressions_success'] = json.load(f)
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else:
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print(f"成功表达式文件不存在: {output_file}")
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result['expressions_success'] = []
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# 读取候选表达式
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if os.path.exists(candidates_file):
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print(f"读取候选表达式文件: {candidates_file}")
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with open(candidates_file, 'r', encoding='utf-8') as f:
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result['candidates'] = json.load(f)
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else:
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print(f"候选表达式文件不存在: {candidates_file}")
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result['candidates'] = []
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# 读取生成失败的表达式
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if os.path.exists(error_file):
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print(f"读取错误表达式文件: {error_file}")
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with open(error_file, 'r', encoding='utf-8') as f:
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result['expressions_error'] = json.load(f)
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else:
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print(f"错误表达式文件不存在: {error_file}")
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result['expressions_error'] = []
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print(f"成功: {len(result['expressions_success'])} 个, 候选: {len(result['candidates'])} 个, 错误: {len(result['expressions_error'])} 个")
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print("=" * 50)
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return JSONResponse(content=result)
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finally:
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# 清理临时配置文件
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if os.path.exists(config_path):
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os.remove(config_path)
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print(f"已清理临时配置文件: {config_path}")
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except subprocess.TimeoutExpired:
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print("任务执行超时 (600秒)")
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return JSONResponse(
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status_code=408,
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content={"success": False, "error": "Task timeout (600s)"}
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)
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except Exception as e:
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print(f"执行异常: {str(e)}")
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return JSONResponse(
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status_code=500,
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content={"success": False, "error": str(e)}
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)
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@app.post("/api/transformer/login-and-fetch-options")
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async def login_and_fetch_options(request: Request):
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"""
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登录 BRAIN 并获取地区、Delay、Universe、类别等选项
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用于填充高级选项表单
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"""
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try:
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data = await request.json()
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username = data.get('username')
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password = data.get('password')
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if not username or not password:
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return JSONResponse(
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status_code=400,
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content={'success': False, 'error': 'Username and password are required'}
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)
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# 添加 Transformer 目录到 sys.path
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script_dir = os.path.dirname(os.path.abspath(__file__))
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transformer_dir = os.path.join(script_dir, 'Tranformer')
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if transformer_dir not in sys.path:
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sys.path.append(transformer_dir)
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# 导入必要的模块
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from Tranformer.ace_lib import SingleSession, get_instrument_type_region_delay
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import pandas as pd
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# 创建新的会话实例
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session = SingleSession()
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session.auth = (username, password)
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brain_api_url = "https://api.worldquantbrain.com"
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response = session.post(brain_api_url + "/authentication")
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if response.status_code == 201:
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# 认证成功
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pass
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elif response.status_code == 401:
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return JSONResponse(
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status_code=401,
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content={'success': False, 'error': 'Authentication failed: Invalid credentials'}
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)
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else:
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return JSONResponse(
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status_code=400,
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content={'success': False, 'error': f'Authentication failed: {response.status_code}'}
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)
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# 获取 region/delay/universe 选项
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df = get_instrument_type_region_delay(session)
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# 获取数据类别
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categories_resp = session.get(brain_api_url + "/data-categories")
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categories = []
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if categories_resp.status_code == 200:
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categories_data = categories_resp.json()
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if isinstance(categories_data, list):
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categories = categories_data
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elif isinstance(categories_data, dict):
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categories = categories_data.get('results', [])
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# 转换 DataFrame 为前端需要的嵌套字典结构
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# 结构: Region -> Delay -> Universe
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df_equity = df[df['InstrumentType'] == 'EQUITY']
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options = {}
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for _, row in df_equity.iterrows():
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region = row['Region']
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delay = row['Delay']
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universes = row['Universe'] # 这是一个列表
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if region not in options:
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options[region] = {}
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# 将 delay 转换为字符串作为字典的键
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delay_str = str(delay)
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if delay_str not in options[region]:
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options[region][delay_str] = universes
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return JSONResponse(content={
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'success': True,
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'options': options,
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'categories': categories
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})
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except Exception as e:
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print(f"登录获取选项失败: {str(e)}")
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return JSONResponse(
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status_code=500,
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content={'success': False, 'error': str(e)}
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)
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@app.get("/api/health")
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async def health_check():
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"""健康检查端点，用于验证服务是否正常运行"""
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return {"status": "healthy", "service": "alpha-transformer"}
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@app.get("/api/download/{alpha_id}")
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async def download_results(alpha_id: str):
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"""
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下载生成结果的 zip 压缩包
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包含三个 JSON 文件：success, candidates, error
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"""
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try:
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transformer_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'Tranformer')
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output_dir = os.path.join(transformer_dir, 'output')
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# 检查文件是否存在
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files_to_zip = {
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'Alpha_generated_expressions_success.json': os.path.join(output_dir, 'Alpha_generated_expressions_success.json'),
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'Alpha_candidates.json': os.path.join(output_dir, 'Alpha_candidates.json'),
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'Alpha_generated_expressions_error.json': os.path.join(output_dir, 'Alpha_generated_expressions_error.json')
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}
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# 生成时间戳
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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zip_filename = f"{alpha_id}_{timestamp}.zip"
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zip_path = os.path.join(output_dir, zip_filename)
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# 创建 zip 文件
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with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
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for arcname, filepath in files_to_zip.items():
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if os.path.exists(filepath):
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zipf.write(filepath, arcname)
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# 返回文件
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return FileResponse(
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zip_path,
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media_type='application/zip',
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filename=zip_filename
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)
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except Exception as e:
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return JSONResponse(
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status_code=500,
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content={"success": False, "error": str(e)}
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)
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if __name__ == "__main__":
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# 启动 FastAPI 应用，使用 uvicorn 作为 ASGI 服务器
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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