1012 lines
34 KiB
Python
1012 lines
34 KiB
Python
"""
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TradingAgents Web Dashboard Backend
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FastAPI REST API + WebSocket for real-time analysis progress
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"""
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import asyncio
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import fcntl
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import json
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import os
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import subprocess
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import sys
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import tempfile
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import time
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import traceback
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from datetime import datetime
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from pathlib import Path
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from typing import Optional
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from contextlib import asynccontextmanager
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from fastapi import FastAPI, HTTPException, WebSocket, WebSocketDisconnect, Query
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from fastapi.responses import Response
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# Path to TradingAgents repo root
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REPO_ROOT = Path(__file__).parent.parent.parent
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# Use the currently running Python interpreter
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ANALYSIS_PYTHON = Path(sys.executable)
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# Task state persistence directory
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TASK_STATUS_DIR = Path(__file__).parent / "data" / "task_status"
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# ============== Lifespan ==============
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Startup and shutdown events"""
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app.state.active_connections: dict[str, list[WebSocket]] = {}
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app.state.task_results: dict[str, dict] = {}
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app.state.analysis_tasks: dict[str, asyncio.Task] = {}
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# Restore persisted task states from disk
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TASK_STATUS_DIR.mkdir(parents=True, exist_ok=True)
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for f in TASK_STATUS_DIR.glob("*.json"):
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try:
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data = json.loads(f.read_text())
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app.state.task_results[data["task_id"]] = data
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except Exception:
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pass
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yield
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# ============== App ==============
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app = FastAPI(
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title="TradingAgents Web Dashboard API",
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version="0.1.0",
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lifespan=lifespan
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)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# ============== Pydantic Models ==============
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class AnalysisRequest(BaseModel):
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ticker: str
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date: Optional[str] = None
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class ScreenRequest(BaseModel):
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mode: str = "china_strict"
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# ============== Cache Helpers ==============
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CACHE_DIR = Path(__file__).parent.parent / "cache"
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CACHE_TTL_SECONDS = 300 # 5 minutes
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MAX_RETRY_COUNT = 2
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RETRY_BASE_DELAY_SECS = 1
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MAX_CONCURRENT_YFINANCE = 5
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def _get_cache_path(mode: str) -> Path:
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return CACHE_DIR / f"screen_{mode}.json"
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def _load_from_cache(mode: str) -> Optional[dict]:
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cache_path = _get_cache_path(mode)
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if not cache_path.exists():
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return None
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try:
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age = time.time() - cache_path.stat().st_mtime
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if age > CACHE_TTL_SECONDS:
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return None
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with open(cache_path) as f:
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return json.load(f)
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except Exception:
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return None
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def _save_to_cache(mode: str, data: dict):
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"""Save screening result to cache"""
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try:
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CACHE_DIR.mkdir(parents=True, exist_ok=True)
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cache_path = _get_cache_path(mode)
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with open(cache_path, "w") as f:
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json.dump(data, f)
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except Exception:
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pass
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def _save_task_status(task_id: str, data: dict):
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"""Persist task state to disk"""
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try:
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TASK_STATUS_DIR.mkdir(parents=True, exist_ok=True)
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(TASK_STATUS_DIR / f"{task_id}.json").write_text(json.dumps(data, ensure_ascii=False))
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except Exception:
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pass
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def _delete_task_status(task_id: str):
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"""Remove persisted task state from disk"""
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try:
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(TASK_STATUS_DIR / f"{task_id}.json").unlink(missing_ok=True)
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except Exception:
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pass
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# ============== SEPA Screening ==============
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def _run_sepa_screening(mode: str) -> dict:
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"""Run SEPA screening synchronously in thread"""
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sys.path.insert(0, str(REPO_ROOT))
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from sepa_screener import screen_all, china_stocks
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results = screen_all(mode=mode, max_workers=5)
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total = len(china_stocks)
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return {
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"mode": mode,
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"total_stocks": total,
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"passed": len(results),
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"results": results,
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}
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@app.get("/api/stocks/screen")
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async def screen_stocks(mode: str = Query("china_strict"), refresh: bool = Query(False)):
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"""Screen stocks using SEPA criteria with caching"""
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if not refresh:
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cached = _load_from_cache(mode)
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if cached:
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return {**cached, "cached": True}
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# Run in thread pool (blocks thread but not event loop)
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loop = asyncio.get_event_loop()
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result = await loop.run_in_executor(None, lambda: _run_sepa_screening(mode))
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_save_to_cache(mode, result)
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return {**result, "cached": False}
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# ============== Analysis Execution ==============
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# Script template for subprocess-based analysis
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# api_key is passed via environment variable (not CLI) for security
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ANALYSIS_SCRIPT_TEMPLATE = """
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import sys
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import os
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ticker = sys.argv[1]
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date = sys.argv[2]
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repo_root = sys.argv[3]
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sys.path.insert(0, repo_root)
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os.environ["ANTHROPIC_BASE_URL"] = "https://api.minimaxi.com/anthropic"
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import py_mini_racer
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sys.modules["mini_racer"] = py_mini_racer
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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from pathlib import Path
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print("STAGE:analysts", flush=True)
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config = DEFAULT_CONFIG.copy()
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config["llm_provider"] = "anthropic"
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config["deep_think_llm"] = "MiniMax-M2.7-highspeed"
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config["quick_think_llm"] = "MiniMax-M2.7-highspeed"
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config["backend_url"] = "https://api.minimaxi.com/anthropic"
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config["max_debate_rounds"] = 1
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config["max_risk_discuss_rounds"] = 1
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print("STAGE:research", flush=True)
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ta = TradingAgentsGraph(debug=False, config=config)
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print("STAGE:trading", flush=True)
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final_state, decision = ta.propagate(ticker, date)
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print("STAGE:risk", flush=True)
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results_dir = Path(repo_root) / "results" / ticker / date
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results_dir.mkdir(parents=True, exist_ok=True)
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signal = decision if isinstance(decision, str) else decision.get("signal", "HOLD")
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report_content = (
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"# TradingAgents 分析报告\\n\\n"
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"**股票**: " + ticker + "\\n"
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"**日期**: " + date + "\\n\\n"
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"## 最终决策\\n\\n"
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"**" + signal + "**\\n\\n"
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"## 分析摘要\\n\\n"
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+ final_state.get("market_report", "N/A") + "\\n\\n"
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"## 基本面\\n\\n"
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+ final_state.get("fundamentals_report", "N/A") + "\\n"
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)
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report_path = results_dir / "complete_report.md"
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report_path.write_text(report_content)
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print("STAGE:portfolio", flush=True)
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print("ANALYSIS_COMPLETE:" + signal, flush=True)
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"""
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@app.post("/api/analysis/start")
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async def start_analysis(request: AnalysisRequest):
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"""Start a new analysis task"""
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import uuid
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task_id = f"{request.ticker}_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{uuid.uuid4().hex[:6]}"
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date = request.date or datetime.now().strftime("%Y-%m-%d")
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# Validate API key before storing any task state
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api_key = os.environ.get("ANTHROPIC_API_KEY")
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if not api_key:
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raise HTTPException(status_code=500, detail="ANTHROPIC_API_KEY environment variable not set")
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# Initialize task state
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app.state.task_results[task_id] = {
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"task_id": task_id,
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"ticker": request.ticker,
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"date": date,
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"status": "running",
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"progress": 0,
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"current_stage": "analysts",
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"created_at": datetime.now().isoformat(),
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"elapsed": 0,
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"stages": [
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{"status": "running", "completed_at": None},
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{"status": "pending", "completed_at": None},
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{"status": "pending", "completed_at": None},
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{"status": "pending", "completed_at": None},
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{"status": "pending", "completed_at": None},
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],
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"logs": [],
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"decision": None,
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"error": None,
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}
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await broadcast_progress(task_id, app.state.task_results[task_id])
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# Write analysis script to temp file with restrictive permissions (avoids subprocess -c quoting issues)
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fd, script_path_str = tempfile.mkstemp(suffix=".py", prefix=f"analysis_{task_id}_")
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script_path = Path(script_path_str)
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os.chmod(script_path, 0o600)
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with os.fdopen(fd, "w") as f:
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f.write(ANALYSIS_SCRIPT_TEMPLATE)
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# Store process reference for cancellation
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app.state.processes = getattr(app.state, 'processes', {})
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app.state.processes[task_id] = None
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# Cancellation event for the monitor coroutine
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cancel_event = asyncio.Event()
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# Stage name to index mapping
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STAGE_NAMES = ["analysts", "research", "trading", "risk", "portfolio"]
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def _update_task_stage(stage_name: str):
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"""Update task state for a completed stage and mark next as running."""
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try:
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idx = STAGE_NAMES.index(stage_name)
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except ValueError:
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return
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# Mark all previous stages as completed
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for i in range(idx):
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if app.state.task_results[task_id]["stages"][i]["status"] != "completed":
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app.state.task_results[task_id]["stages"][i]["status"] = "completed"
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app.state.task_results[task_id]["stages"][i]["completed_at"] = datetime.now().strftime("%H:%M:%S")
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# Mark current as completed
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if app.state.task_results[task_id]["stages"][idx]["status"] != "completed":
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app.state.task_results[task_id]["stages"][idx]["status"] = "completed"
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app.state.task_results[task_id]["stages"][idx]["completed_at"] = datetime.now().strftime("%H:%M:%S")
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# Mark next as running
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if idx + 1 < 5:
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if app.state.task_results[task_id]["stages"][idx + 1]["status"] == "pending":
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app.state.task_results[task_id]["stages"][idx + 1]["status"] = "running"
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# Update progress
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app.state.task_results[task_id]["progress"] = int((idx + 1) / 5 * 100)
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app.state.task_results[task_id]["current_stage"] = stage_name
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async def monitor_subprocess(task_id: str, proc: asyncio.subprocess.Process, cancel_evt: asyncio.Event):
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"""Monitor subprocess stdout for stage markers and broadcast progress."""
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# Set stdout to non-blocking
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fd = proc.stdout.fileno()
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fl = fcntl.fcntl(fd, fcntl.GETFL)
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fcntl.fcntl(fd, fcntl.SETFL, fl | os.O_NONBLOCK)
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while not cancel_evt.is_set():
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if proc.returncode is not None:
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break
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await asyncio.sleep(5)
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if cancel_evt.is_set():
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break
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try:
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chunk = os.read(fd, 32768)
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if chunk:
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for line in chunk.decode().splitlines():
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if line.startswith("STAGE:"):
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stage = line.split(":", 1)[1].strip()
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_update_task_stage(stage)
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await broadcast_progress(task_id, app.state.task_results[task_id])
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except (BlockingIOError, OSError):
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# No data available yet
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pass
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async def run_analysis():
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"""Run analysis subprocess and broadcast progress"""
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try:
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# Use clean environment - don't inherit parent env
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clean_env = {k: v for k, v in os.environ.items()
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if not k.startswith(("PYTHON", "CONDA", "VIRTUAL"))}
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clean_env["ANTHROPIC_API_KEY"] = api_key
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clean_env["ANTHROPIC_BASE_URL"] = "https://api.minimaxi.com/anthropic"
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proc = await asyncio.create_subprocess_exec(
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str(ANALYSIS_PYTHON),
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str(script_path),
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request.ticker,
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date,
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str(REPO_ROOT),
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE,
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env=clean_env,
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)
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app.state.processes[task_id] = proc
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# Start monitor coroutine alongside subprocess
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monitor_task = asyncio.create_task(monitor_subprocess(task_id, proc, cancel_event))
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stdout, stderr = await proc.communicate()
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# Signal monitor to stop and wait for it
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cancel_event.set()
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try:
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await asyncio.wait_for(monitor_task, timeout=1.0)
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except asyncio.TimeoutError:
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monitor_task.cancel()
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# Clean up script file
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try:
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script_path.unlink()
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except Exception:
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pass
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if proc.returncode == 0:
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output = stdout.decode()
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decision = "HOLD"
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for line in output.splitlines():
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if line.startswith("ANALYSIS_COMPLETE:"):
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decision = line.split(":", 1)[1].strip()
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app.state.task_results[task_id]["status"] = "completed"
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app.state.task_results[task_id]["progress"] = 100
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app.state.task_results[task_id]["decision"] = decision
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app.state.task_results[task_id]["current_stage"] = "portfolio"
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for i in range(5):
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app.state.task_results[task_id]["stages"][i]["status"] = "completed"
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if not app.state.task_results[task_id]["stages"][i].get("completed_at"):
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app.state.task_results[task_id]["stages"][i]["completed_at"] = datetime.now().strftime("%H:%M:%S")
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else:
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error_msg = stderr.decode()[-1000:] if stderr else "Unknown error"
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app.state.task_results[task_id]["status"] = "failed"
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app.state.task_results[task_id]["error"] = error_msg
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_save_task_status(task_id, app.state.task_results[task_id])
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except Exception as e:
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cancel_event.set()
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app.state.task_results[task_id]["status"] = "failed"
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app.state.task_results[task_id]["error"] = str(e)
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try:
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script_path.unlink()
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except Exception:
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pass
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_save_task_status(task_id, app.state.task_results[task_id])
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await broadcast_progress(task_id, app.state.task_results[task_id])
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task = asyncio.create_task(run_analysis())
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app.state.analysis_tasks[task_id] = task
|
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|
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return {
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"task_id": task_id,
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"ticker": request.ticker,
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"date": date,
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"status": "running",
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}
|
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|
|
|
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@app.get("/api/analysis/status/{task_id}")
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async def get_task_status(task_id: str):
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"""Get task status"""
|
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if task_id not in app.state.task_results:
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raise HTTPException(status_code=404, detail="Task not found")
|
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return app.state.task_results[task_id]
|
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|
|
|
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@app.get("/api/analysis/tasks")
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async def list_tasks():
|
|
"""List all tasks (active and recent)"""
|
|
tasks = []
|
|
for task_id, state in app.state.task_results.items():
|
|
tasks.append({
|
|
"task_id": task_id,
|
|
"ticker": state.get("ticker"),
|
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"date": state.get("date"),
|
|
"status": state.get("status"),
|
|
"progress": state.get("progress", 0),
|
|
"decision": state.get("decision"),
|
|
"error": state.get("error"),
|
|
"created_at": state.get("created_at"),
|
|
})
|
|
# Sort by created_at descending (most recent first)
|
|
tasks.sort(key=lambda x: x.get("created_at") or "", reverse=True)
|
|
return {"tasks": tasks, "total": len(tasks)}
|
|
|
|
|
|
@app.delete("/api/analysis/cancel/{task_id}")
|
|
async def cancel_task(task_id: str):
|
|
"""Cancel a running task"""
|
|
if task_id not in app.state.task_results:
|
|
raise HTTPException(status_code=404, detail="Task not found")
|
|
|
|
# Kill the subprocess if it's still running
|
|
proc = app.state.processes.get(task_id)
|
|
if proc and proc.returncode is None:
|
|
try:
|
|
proc.kill()
|
|
except Exception:
|
|
pass
|
|
|
|
# Cancel the asyncio task
|
|
task = app.state.analysis_tasks.get(task_id)
|
|
if task:
|
|
task.cancel()
|
|
app.state.task_results[task_id]["status"] = "failed"
|
|
app.state.task_results[task_id]["error"] = "用户取消"
|
|
_save_task_status(task_id, app.state.task_results[task_id])
|
|
await broadcast_progress(task_id, app.state.task_results[task_id])
|
|
|
|
# Clean up temp script (may use tempfile.mkstemp with random suffix)
|
|
for p in Path("/tmp").glob(f"analysis_{task_id}_*.py"):
|
|
try:
|
|
p.unlink()
|
|
except Exception:
|
|
pass
|
|
|
|
# Remove persisted task state
|
|
_delete_task_status(task_id)
|
|
|
|
return {"task_id": task_id, "status": "cancelled"}
|
|
|
|
|
|
# ============== WebSocket ==============
|
|
|
|
@app.websocket("/ws/analysis/{task_id}")
|
|
async def websocket_analysis(websocket: WebSocket, task_id: str):
|
|
"""WebSocket for real-time analysis progress"""
|
|
await websocket.accept()
|
|
|
|
if task_id not in app.state.active_connections:
|
|
app.state.active_connections[task_id] = []
|
|
app.state.active_connections[task_id].append(websocket)
|
|
|
|
# Send current state immediately if available
|
|
if task_id in app.state.task_results:
|
|
await websocket.send_text(json.dumps({
|
|
"type": "progress",
|
|
**app.state.task_results[task_id]
|
|
}))
|
|
|
|
try:
|
|
while True:
|
|
data = await websocket.receive_text()
|
|
message = json.loads(data)
|
|
if message.get("type") == "ping":
|
|
await websocket.send_text(json.dumps({"type": "pong"}))
|
|
except WebSocketDisconnect:
|
|
if task_id in app.state.active_connections:
|
|
app.state.active_connections[task_id].remove(websocket)
|
|
|
|
|
|
async def broadcast_progress(task_id: str, progress: dict):
|
|
"""Broadcast progress to all connections for a task"""
|
|
if task_id not in app.state.active_connections:
|
|
return
|
|
|
|
message = json.dumps({"type": "progress", **progress})
|
|
dead = []
|
|
|
|
for connection in app.state.active_connections[task_id]:
|
|
try:
|
|
await connection.send_text(message)
|
|
except Exception:
|
|
dead.append(connection)
|
|
|
|
for conn in dead:
|
|
app.state.active_connections[task_id].remove(conn)
|
|
|
|
|
|
# ============== Reports ==============
|
|
|
|
def get_results_dir() -> Path:
|
|
return Path(__file__).parent.parent.parent / "results"
|
|
|
|
|
|
def get_reports_list():
|
|
"""Get all historical reports"""
|
|
results_dir = get_results_dir()
|
|
reports = []
|
|
if not results_dir.exists():
|
|
return reports
|
|
for ticker_dir in results_dir.iterdir():
|
|
if ticker_dir.is_dir() and ticker_dir.name != "TradingAgentsStrategy_logs":
|
|
ticker = ticker_dir.name
|
|
for date_dir in ticker_dir.iterdir():
|
|
# Skip non-date directories like TradingAgentsStrategy_logs
|
|
if date_dir.is_dir() and date_dir.name.startswith("20"):
|
|
reports.append({
|
|
"ticker": ticker,
|
|
"date": date_dir.name,
|
|
"path": str(date_dir)
|
|
})
|
|
return sorted(reports, key=lambda x: x["date"], reverse=True)
|
|
|
|
|
|
def get_report_content(ticker: str, date: str) -> Optional[dict]:
|
|
"""Get report content for a specific ticker and date"""
|
|
# Validate inputs to prevent path traversal
|
|
if ".." in ticker or "/" in ticker or "\\" in ticker:
|
|
return None
|
|
if ".." in date or "/" in date or "\\" in date:
|
|
return None
|
|
report_dir = get_results_dir() / ticker / date
|
|
# Strict traversal check: resolved path must be within get_results_dir()
|
|
try:
|
|
report_dir.resolve().relative_to(get_results_dir().resolve())
|
|
except ValueError:
|
|
return None
|
|
if not report_dir.exists():
|
|
return None
|
|
content = {}
|
|
complete_report = report_dir / "complete_report.md"
|
|
if complete_report.exists():
|
|
content["report"] = complete_report.read_text()
|
|
for stage in ["1_analysts", "2_research", "3_trading", "4_risk", "5_portfolio"]:
|
|
stage_dir = report_dir / "reports" / stage
|
|
if stage_dir.exists():
|
|
for f in stage_dir.glob("*.md"):
|
|
content[f.name] = f.read_text()
|
|
return content
|
|
|
|
|
|
@app.get("/api/reports/list")
|
|
async def list_reports():
|
|
return get_reports_list()
|
|
|
|
|
|
@app.get("/api/reports/{ticker}/{date}")
|
|
async def get_report(ticker: str, date: str):
|
|
content = get_report_content(ticker, date)
|
|
if not content:
|
|
raise HTTPException(status_code=404, detail="Report not found")
|
|
return content
|
|
|
|
|
|
# ============== Report Export ==============
|
|
|
|
import csv
|
|
import io
|
|
import re
|
|
from fpdf import FPDF
|
|
|
|
|
|
def _extract_decision(markdown_text: str) -> str:
|
|
"""Extract BUY/SELL/HOLD from markdown bold text."""
|
|
match = re.search(r'\*\*(BUY|SELL|HOLD)\*\*', markdown_text)
|
|
return match.group(1) if match else 'UNKNOWN'
|
|
|
|
|
|
def _extract_summary(markdown_text: str) -> str:
|
|
"""Extract first ~200 chars after '## 分析摘要'."""
|
|
match = re.search(r'## 分析摘要\s*\n+(.{0,300}?)(?=\n##|\Z)', markdown_text, re.DOTALL)
|
|
if match:
|
|
text = match.group(1).strip()
|
|
# Strip markdown formatting
|
|
text = re.sub(r'\*\*(.*?)\*\*', r'\1', text)
|
|
text = re.sub(r'\*(.*?)\*', r'\1', text)
|
|
text = re.sub(r'[#\n]+', ' ', text)
|
|
return text[:200].strip()
|
|
return ''
|
|
|
|
|
|
@app.get("/api/reports/export")
|
|
async def export_reports_csv():
|
|
"""Export all reports as CSV: ticker,date,decision,summary."""
|
|
reports = get_reports_list()
|
|
output = io.StringIO()
|
|
writer = csv.DictWriter(output, fieldnames=["ticker", "date", "decision", "summary"])
|
|
writer.writeheader()
|
|
for r in reports:
|
|
content = get_report_content(r["ticker"], r["date"])
|
|
if content and content.get("report"):
|
|
writer.writerow({
|
|
"ticker": r["ticker"],
|
|
"date": r["date"],
|
|
"decision": _extract_decision(content["report"]),
|
|
"summary": _extract_summary(content["report"]),
|
|
})
|
|
else:
|
|
writer.writerow({
|
|
"ticker": r["ticker"],
|
|
"date": r["date"],
|
|
"decision": "UNKNOWN",
|
|
"summary": "",
|
|
})
|
|
return Response(
|
|
content=output.getvalue(),
|
|
media_type="text/csv",
|
|
headers={"Content-Disposition": "attachment; filename=tradingagents_reports.csv"},
|
|
)
|
|
|
|
|
|
@app.get("/api/reports/{ticker}/{date}/pdf")
|
|
async def export_report_pdf(ticker: str, date: str):
|
|
"""Export a single report as PDF."""
|
|
content = get_report_content(ticker, date)
|
|
if not content or not content.get("report"):
|
|
raise HTTPException(status_code=404, detail="Report not found")
|
|
|
|
markdown_text = content["report"]
|
|
decision = _extract_decision(markdown_text)
|
|
summary = _extract_summary(markdown_text)
|
|
|
|
pdf = FPDF()
|
|
pdf.set_auto_page_break(auto=True, margin=20)
|
|
|
|
# Try multiple font paths for cross-platform support
|
|
font_paths = [
|
|
"/System/Library/Fonts/Supplemental/DejaVuSans.ttf",
|
|
"/System/Library/Fonts/Supplemental/DejaVuSans-Bold.ttf",
|
|
"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
|
|
"/usr/share/fonts/dejavu/DejaVuSans.ttf",
|
|
"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
|
|
"/usr/share/fonts/dejavu/DejaVuSans-Bold.ttf",
|
|
str(Path.home() / ".local/share/fonts/DejaVuSans.ttf"),
|
|
str(Path.home() / ".fonts/DejaVuSans.ttf"),
|
|
]
|
|
regular_font = None
|
|
bold_font = None
|
|
for p in font_paths:
|
|
if Path(p).exists():
|
|
if "Bold" in p and bold_font is None:
|
|
bold_font = p
|
|
elif regular_font is None and "Bold" not in p:
|
|
regular_font = p
|
|
|
|
use_dejavu = bool(regular_font and bold_font)
|
|
if use_dejavu:
|
|
pdf.add_font("DejaVu", "", regular_font, unicode=True)
|
|
pdf.add_font("DejaVu", "B", bold_font, unicode=True)
|
|
font_regular = "DejaVu"
|
|
font_bold = "DejaVu"
|
|
else:
|
|
font_regular = "Helvetica"
|
|
font_bold = "Helvetica"
|
|
|
|
pdf.add_page()
|
|
pdf.set_font(font_bold, "B", 18)
|
|
pdf.cell(0, 12, f"TradingAgents 分析报告", ln=True, align="C")
|
|
pdf.ln(5)
|
|
|
|
pdf.set_font(font_regular, "", 11)
|
|
pdf.cell(0, 8, f"股票: {ticker} 日期: {date}", ln=True)
|
|
pdf.ln(3)
|
|
|
|
# Decision badge
|
|
pdf.set_font(font_bold, "B", 14)
|
|
if decision == "BUY":
|
|
pdf.set_text_color(34, 197, 94)
|
|
elif decision == "SELL":
|
|
pdf.set_text_color(220, 38, 38)
|
|
else:
|
|
pdf.set_text_color(245, 158, 11)
|
|
pdf.cell(0, 10, f"决策: {decision}", ln=True)
|
|
pdf.set_text_color(0, 0, 0)
|
|
pdf.ln(5)
|
|
|
|
# Summary
|
|
pdf.set_font(font_bold, "B", 12)
|
|
pdf.cell(0, 8, "分析摘要", ln=True)
|
|
pdf.set_font(font_regular, "", 10)
|
|
pdf.multi_cell(0, 6, summary or "无")
|
|
pdf.ln(5)
|
|
|
|
# Full report text (stripped of heavy markdown)
|
|
pdf.set_font(font_bold, "B", 12)
|
|
pdf.cell(0, 8, "完整报告", ln=True)
|
|
pdf.set_font(font_regular, "", 9)
|
|
# Split into lines, filter out very long lines
|
|
for line in markdown_text.splitlines():
|
|
line = re.sub(r'\*\*(.*?)\*\*', r'\1', line)
|
|
line = re.sub(r'\*(.*?)\*', r'\1', line)
|
|
line = re.sub(r'#{1,6} ', '', line)
|
|
line = line.strip()
|
|
if not line:
|
|
pdf.ln(2)
|
|
continue
|
|
if len(line) > 120:
|
|
line = line[:120] + "..."
|
|
try:
|
|
pdf.multi_cell(0, 5, line)
|
|
except Exception:
|
|
pass
|
|
|
|
return Response(
|
|
content=pdf.output(),
|
|
media_type="application/pdf",
|
|
headers={"Content-Disposition": f"attachment; filename={ticker}_{date}_report.pdf"},
|
|
)
|
|
|
|
|
|
# ============== Portfolio ==============
|
|
|
|
import sys
|
|
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
|
|
from api.portfolio import (
|
|
get_watchlist, add_to_watchlist, remove_from_watchlist,
|
|
get_positions, add_position, remove_position,
|
|
get_accounts, create_account, delete_account,
|
|
get_recommendations, get_recommendation, save_recommendation,
|
|
RECOMMENDATIONS_DIR,
|
|
)
|
|
|
|
|
|
# --- Watchlist ---
|
|
|
|
@app.get("/api/portfolio/watchlist")
|
|
async def list_watchlist():
|
|
return {"watchlist": get_watchlist()}
|
|
|
|
|
|
@app.post("/api/portfolio/watchlist")
|
|
async def create_watchlist_entry(body: dict):
|
|
try:
|
|
entry = add_to_watchlist(body["ticker"], body.get("name", body["ticker"]))
|
|
return entry
|
|
except ValueError as e:
|
|
raise HTTPException(status_code=400, detail=str(e))
|
|
|
|
|
|
@app.delete("/api/portfolio/watchlist/{ticker}")
|
|
async def delete_watchlist_entry(ticker: str):
|
|
if remove_from_watchlist(ticker):
|
|
return {"ok": True}
|
|
raise HTTPException(status_code=404, detail="Ticker not found in watchlist")
|
|
|
|
|
|
# --- Accounts ---
|
|
|
|
@app.get("/api/portfolio/accounts")
|
|
async def list_accounts():
|
|
accounts = get_accounts()
|
|
return {"accounts": list(accounts.get("accounts", {}).keys())}
|
|
|
|
|
|
@app.post("/api/portfolio/accounts")
|
|
async def create_account_endpoint(body: dict):
|
|
try:
|
|
return create_account(body["account_name"])
|
|
except ValueError as e:
|
|
raise HTTPException(status_code=400, detail=str(e))
|
|
|
|
|
|
@app.delete("/api/portfolio/accounts/{account_name}")
|
|
async def delete_account_endpoint(account_name: str):
|
|
if delete_account(account_name):
|
|
return {"ok": True}
|
|
raise HTTPException(status_code=404, detail="Account not found")
|
|
|
|
|
|
# --- Positions ---
|
|
|
|
@app.get("/api/portfolio/positions")
|
|
async def list_positions(account: Optional[str] = Query(None)):
|
|
return {"positions": get_positions(account)}
|
|
|
|
|
|
@app.post("/api/portfolio/positions")
|
|
async def create_position(body: dict):
|
|
try:
|
|
pos = add_position(
|
|
ticker=body["ticker"],
|
|
shares=body["shares"],
|
|
cost_price=body["cost_price"],
|
|
purchase_date=body.get("purchase_date"),
|
|
notes=body.get("notes", ""),
|
|
account=body.get("account", "默认账户"),
|
|
)
|
|
return pos
|
|
except Exception as e:
|
|
raise HTTPException(status_code=400, detail=str(e))
|
|
|
|
|
|
@app.delete("/api/portfolio/positions/{ticker}")
|
|
async def delete_position(ticker: str, position_id: Optional[str] = Query(None), account: Optional[str] = Query(None)):
|
|
removed = remove_position(ticker, position_id or "", account)
|
|
if removed:
|
|
return {"ok": True}
|
|
raise HTTPException(status_code=404, detail="Position not found")
|
|
|
|
|
|
@app.get("/api/portfolio/positions/export")
|
|
async def export_positions_csv(account: Optional[str] = Query(None)):
|
|
positions = get_positions(account)
|
|
import csv
|
|
import io
|
|
output = io.StringIO()
|
|
writer = csv.DictWriter(output, fieldnames=["ticker", "shares", "cost_price", "purchase_date", "notes", "account"])
|
|
writer.writeheader()
|
|
for p in positions:
|
|
writer.writerow({k: p[k] for k in ["ticker", "shares", "cost_price", "purchase_date", "notes", "account"]})
|
|
return Response(content=output.getvalue(), media_type="text/csv", headers={"Content-Disposition": "attachment; filename=positions.csv"})
|
|
|
|
|
|
# --- Recommendations ---
|
|
|
|
@app.get("/api/portfolio/recommendations")
|
|
async def list_recommendations(date: Optional[str] = Query(None)):
|
|
return {"recommendations": get_recommendations(date)}
|
|
|
|
|
|
@app.get("/api/portfolio/recommendations/{date}/{ticker}")
|
|
async def get_recommendation_endpoint(date: str, ticker: str):
|
|
rec = get_recommendation(date, ticker)
|
|
if not rec:
|
|
raise HTTPException(status_code=404, detail="Recommendation not found")
|
|
return rec
|
|
|
|
|
|
# --- Batch Analysis ---
|
|
|
|
@app.post("/api/portfolio/analyze")
|
|
async def start_portfolio_analysis():
|
|
"""
|
|
Trigger batch analysis for all watchlist tickers.
|
|
Runs serially, streaming progress via WebSocket (task_id prefixed with 'port_').
|
|
"""
|
|
import uuid
|
|
date = datetime.now().strftime("%Y-%m-%d")
|
|
task_id = f"port_{date}_{uuid.uuid4().hex[:6]}"
|
|
|
|
watchlist = get_watchlist()
|
|
if not watchlist:
|
|
raise HTTPException(status_code=400, detail="自选股为空，请先添加股票")
|
|
|
|
total = len(watchlist)
|
|
app.state.task_results[task_id] = {
|
|
"task_id": task_id,
|
|
"type": "portfolio",
|
|
"status": "running",
|
|
"total": total,
|
|
"completed": 0,
|
|
"failed": 0,
|
|
"current_ticker": None,
|
|
"results": [],
|
|
"error": None,
|
|
}
|
|
|
|
api_key = os.environ.get("ANTHROPIC_API_KEY")
|
|
if not api_key:
|
|
raise HTTPException(status_code=500, detail="ANTHROPIC_API_KEY environment variable not set")
|
|
|
|
await broadcast_progress(task_id, app.state.task_results[task_id])
|
|
|
|
async def run_portfolio_analysis():
|
|
max_retries = MAX_RETRY_COUNT
|
|
|
|
async def run_single_analysis(ticker: str, stock: dict) -> tuple[bool, str, dict | None]:
|
|
"""Run analysis for one ticker. Returns (success, decision, rec_or_error)."""
|
|
last_error = None
|
|
for attempt in range(max_retries + 1):
|
|
script_path = None
|
|
try:
|
|
fd, script_path_str = tempfile.mkstemp(suffix=".py", prefix=f"analysis_{task_id}_{stock['_idx']}_")
|
|
script_path = Path(script_path_str)
|
|
os.chmod(script_path, 0o600)
|
|
with os.fdopen(fd, "w") as f:
|
|
f.write(ANALYSIS_SCRIPT_TEMPLATE)
|
|
|
|
clean_env = {k: v for k, v in os.environ.items()
|
|
if not k.startswith(("PYTHON", "CONDA", "VIRTUAL"))}
|
|
clean_env["ANTHROPIC_API_KEY"] = api_key
|
|
clean_env["ANTHROPIC_BASE_URL"] = "https://api.minimaxi.com/anthropic"
|
|
|
|
proc = await asyncio.create_subprocess_exec(
|
|
str(ANALYSIS_PYTHON), str(script_path), ticker, date, str(REPO_ROOT),
|
|
stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE,
|
|
env=clean_env,
|
|
)
|
|
app.state.processes[task_id] = proc
|
|
|
|
stdout, stderr = await proc.communicate()
|
|
|
|
try:
|
|
script_path.unlink()
|
|
except Exception:
|
|
pass
|
|
|
|
if proc.returncode == 0:
|
|
output = stdout.decode()
|
|
decision = "HOLD"
|
|
for line in output.splitlines():
|
|
if line.startswith("ANALYSIS_COMPLETE:"):
|
|
decision = line.split(":", 1)[1].strip()
|
|
rec = {
|
|
"ticker": ticker,
|
|
"name": stock.get("name", ticker),
|
|
"analysis_date": date,
|
|
"decision": decision,
|
|
"created_at": datetime.now().isoformat(),
|
|
}
|
|
save_recommendation(date, ticker, rec)
|
|
return True, decision, rec
|
|
else:
|
|
last_error = stderr.decode()[-500:] if stderr else f"exit {proc.returncode}"
|
|
except Exception as e:
|
|
last_error = str(e)
|
|
finally:
|
|
if script_path:
|
|
try:
|
|
script_path.unlink()
|
|
except Exception:
|
|
pass
|
|
if attempt < max_retries:
|
|
await asyncio.sleep(RETRY_BASE_DELAY_SECS ** attempt) # exponential backoff: 1s, 2s
|
|
|
|
return False, "HOLD", None
|
|
|
|
try:
|
|
for i, stock in enumerate(watchlist):
|
|
stock["_idx"] = i # used in temp file name
|
|
ticker = stock["ticker"]
|
|
app.state.task_results[task_id]["current_ticker"] = ticker
|
|
app.state.task_results[task_id]["status"] = "running"
|
|
app.state.task_results[task_id]["completed"] = i
|
|
await broadcast_progress(task_id, app.state.task_results[task_id])
|
|
|
|
success, decision, rec = await run_single_analysis(ticker, stock)
|
|
if success:
|
|
app.state.task_results[task_id]["completed"] = i + 1
|
|
app.state.task_results[task_id]["results"].append(rec)
|
|
else:
|
|
app.state.task_results[task_id]["failed"] += 1
|
|
|
|
await broadcast_progress(task_id, app.state.task_results[task_id])
|
|
|
|
app.state.task_results[task_id]["status"] = "completed"
|
|
app.state.task_results[task_id]["current_ticker"] = None
|
|
_save_task_status(task_id, app.state.task_results[task_id])
|
|
|
|
except Exception as e:
|
|
app.state.task_results[task_id]["status"] = "failed"
|
|
app.state.task_results[task_id]["error"] = str(e)
|
|
_save_task_status(task_id, app.state.task_results[task_id])
|
|
|
|
await broadcast_progress(task_id, app.state.task_results[task_id])
|
|
|
|
task = asyncio.create_task(run_portfolio_analysis())
|
|
app.state.analysis_tasks[task_id] = task
|
|
|
|
return {
|
|
"task_id": task_id,
|
|
"total": total,
|
|
"status": "running",
|
|
}
|
|
|
|
|
|
|
|
@app.get("/")
|
|
async def root():
|
|
return {"message": "TradingAgents Web Dashboard API", "version": "0.1.0"}
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import uvicorn
|
|
# Run with: cd web_dashboard && ../env312/bin/python -m uvicorn main:app --reload
|
|
# Or: cd web_dashboard/backend && python3 main.py (requires env312 in PATH)
|
|
uvicorn.run(app, host="0.0.0.0", port=8000)
|