Automated backup - 20250718_000001
This commit is contained in:
Will Song
272
backtest/chat_history/chat_manager.py
Executable file
272
backtest/chat_history/chat_manager.py
Executable file
@@ -0,0 +1,272 @@
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import json
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import os
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from datetime import datetime
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from typing import List, Dict, Optional, Any
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import uuid
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class ChatManager:
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def __init__(self, base_dir="chat_history"):
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self.base_dir = base_dir
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self.template_path = os.path.join(base_dir, "chat_template.html")
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self.sessions_dir = os.path.join(base_dir, "sessions")
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# Create sessions directory if it doesn't exist
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os.makedirs(self.sessions_dir, exist_ok=True)
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def create_session(self, title: str = None) -> str:
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"""Create a new chat session and return session ID"""
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session_id = str(uuid.uuid4())
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if not title:
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title = f"回测会话 {datetime.now().strftime('%Y-%m-%d %H:%M')}"
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session_data = {
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"session_id": session_id,
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"title": title,
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"created_at": datetime.now().isoformat(),
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"updated_at": datetime.now().isoformat(),
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"messages": [],
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"strategies": {},
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"backtest_results": {}
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}
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self._save_session(session_id, session_data)
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return session_id
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def add_message(self, session_id: str, content: str, is_user: bool = True,
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strategy_info: Optional[Dict] = None,
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backtest_results: Optional[List[Dict]] = None):
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"""Add a message to the chat session"""
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session_data = self._load_session(session_id)
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message = {
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"id": str(uuid.uuid4()),
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"content": content,
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"is_user": is_user,
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"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"strategy_info": strategy_info,
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"backtest_results": backtest_results
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}
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session_data["messages"].append(message)
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session_data["updated_at"] = datetime.now().isoformat()
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# If strategy info is provided, store it
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if strategy_info:
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session_data["strategies"][strategy_info["name"]] = strategy_info
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# If backtest results are provided, store them
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if backtest_results:
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result_id = f"result_{len(session_data['backtest_results'])}"
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session_data["backtest_results"][result_id] = {
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"timestamp": datetime.now().isoformat(),
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"results": backtest_results,
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"strategy": strategy_info["name"] if strategy_info else "Unknown"
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}
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self._save_session(session_id, session_data)
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def generate_html_report(self, session_id: str) -> str:
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"""Generate HTML report for a session"""
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session_data = self._load_session(session_id)
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# Read HTML template
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with open(self.template_path, 'r', encoding='utf-8') as f:
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template = f.read()
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# Prepare template variables
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template_vars = {
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"session_title": session_data["title"],
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"created_at": datetime.fromisoformat(session_data["created_at"]).strftime("%Y-%m-%d %H:%M"),
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"message_count": len(session_data["messages"]),
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"strategy_count": len(session_data["strategies"]),
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"generated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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}
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# Generate messages HTML
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messages_html = ""
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for msg in session_data["messages"]:
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message_class = "user-message" if msg["is_user"] else "assistant-message"
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avatar_class = "user-avatar" if msg["is_user"] else "assistant-avatar"
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avatar_text = "U" if msg["is_user"] else "A"
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role_text = "用户" if msg["is_user"] else "助手"
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# Format content (basic markdown-like formatting)
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content = self._format_content(msg["content"])
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message_html = f'''
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<div class="message {message_class}">
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<div class="avatar {avatar_class}">{avatar_text}</div>
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<div class="message-content">
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<h3>{role_text}</h3>
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<div class="message-text">{content}</div>
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'''
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# Add strategy info if present
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if msg.get("strategy_info"):
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strategy = msg["strategy_info"]
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message_html += f'''
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<div class="strategy-info">
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<h4>策略信息: {strategy["name"]}</h4>
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<p><strong>描述:</strong> {strategy.get("description", "无描述")}</p>
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<p><strong>参数:</strong> {json.dumps(strategy.get("parameters", {}), ensure_ascii=False, indent=2)}</p>
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</div>
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'''
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# Add backtest results if present
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if msg.get("backtest_results"):
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message_html += '''
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<div class="backtest-results">
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<h4>回测结果</h4>
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'''
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for result in msg["backtest_results"]:
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message_html += f'''
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<div class="metric">
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<span>{result["name"]}:</span>
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<span>{result["value"]}</span>
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</div>
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'''
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message_html += '</div>'
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message_html += f'''
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<div class="timestamp">{msg["timestamp"]}</div>
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</div>
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</div>
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'''
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messages_html += message_html
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# Replace template variables
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html_content = template.replace("{{session_title}}", template_vars["session_title"])
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html_content = html_content.replace("{{created_at}}", template_vars["created_at"])
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html_content = html_content.replace("{{message_count}}", str(template_vars["message_count"]))
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html_content = html_content.replace("{{strategy_count}}", str(template_vars["strategy_count"]))
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html_content = html_content.replace("{{generated_at}}", template_vars["generated_at"])
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html_content = html_content.replace("{{#messages}}{{/messages}}", messages_html)
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# Save HTML file
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html_filename = f"{session_id}_chat_report.html"
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html_path = os.path.join(self.sessions_dir, html_filename)
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with open(html_path, 'w', encoding='utf-8') as f:
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f.write(html_content)
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return html_path
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def _format_content(self, content: str) -> str:
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"""Basic content formatting"""
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# Replace newlines with <br>
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content = content.replace('\n', '<br>')
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# Simple code block detection (lines starting with 4+ spaces)
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lines = content.split('<br>')
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formatted_lines = []
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in_code_block = False
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for line in lines:
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if line.startswith(' ') or line.startswith('\t'):
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if not in_code_block:
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formatted_lines.append('<div class="code-block">')
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in_code_block = True
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formatted_lines.append(line.strip())
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else:
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if in_code_block:
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formatted_lines.append('</div>')
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in_code_block = False
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formatted_lines.append(line)
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if in_code_block:
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formatted_lines.append('</div>')
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return '<br>'.join(formatted_lines)
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def _load_session(self, session_id: str) -> Dict:
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"""Load session data from JSON file"""
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session_file = os.path.join(self.sessions_dir, f"{session_id}.json")
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if not os.path.exists(session_file):
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raise FileNotFoundError(f"Session {session_id} not found")
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with open(session_file, 'r', encoding='utf-8') as f:
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return json.load(f)
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def _save_session(self, session_id: str, session_data: Dict):
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"""Save session data to JSON file"""
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session_file = os.path.join(self.sessions_dir, f"{session_id}.json")
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with open(session_file, 'w', encoding='utf-8') as f:
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json.dump(session_data, f, ensure_ascii=False, indent=2)
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def list_sessions(self) -> List[Dict]:
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"""List all available sessions"""
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sessions = []
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for filename in os.listdir(self.sessions_dir):
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if filename.endswith('.json'):
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session_id = filename[:-5] # Remove .json extension
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try:
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session_data = self._load_session(session_id)
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sessions.append({
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"session_id": session_id,
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"title": session_data["title"],
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"created_at": session_data["created_at"],
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"updated_at": session_data["updated_at"],
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"message_count": len(session_data["messages"]),
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"strategy_count": len(session_data["strategies"])
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})
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except:
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continue
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# Sort by updated time, most recent first
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sessions.sort(key=lambda x: x["updated_at"], reverse=True)
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return sessions
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# Example usage and test
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if __name__ == "__main__":
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chat_manager = ChatManager()
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# Create a test session
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session_id = chat_manager.create_session("测试回测策略")
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# Add some sample messages
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chat_manager.add_message(
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session_id,
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"你好，我想测试一个移动平均策略",
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is_user=True
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)
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chat_manager.add_message(
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session_id,
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"好的，我来帮你实现一个简单的移动平均策略。",
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is_user=False,
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strategy_info={
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"name": "简单移动平均策略",
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"description": "基于短期和长期移动平均线的交叉信号",
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"parameters": {
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"short_window": 20,
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"long_window": 50,
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"symbol": "AAPL"
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}
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}
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)
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chat_manager.add_message(
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session_id,
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"策略回测完成，以下是结果：",
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is_user=False,
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backtest_results=[
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{"name": "总收益率", "value": "15.6%"},
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{"name": "年化收益率", "value": "12.3%"},
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{"name": "最大回撤", "value": "-8.2%"},
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{"name": "夏普比率", "value": "1.45"}
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]
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)
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# Generate HTML report
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html_path = chat_manager.generate_html_report(session_id)
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print(f"HTML report generated: {html_path}")
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# List sessions
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sessions = chat_manager.list_sessions()
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print(f"Found {len(sessions)} sessions")
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for session in sessions:
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print(f"- {session['title']} ({session['message_count']} messages)")
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245
backtest/chat_history/chat_template.html
Executable file
245
backtest/chat_history/chat_template.html
Executable file
@@ -0,0 +1,245 @@
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<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>回测平台聊天记录 - {{session_title}}</title>
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<style>
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* {
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margin: 0;
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padding: 0;
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box-sizing: border-box;
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}
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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background-color: #f7f7f8;
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color: #333;
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line-height: 1.6;
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}
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.chat-container {
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max-width: 800px;
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margin: 0 auto;
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background: white;
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min-height: 100vh;
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display: flex;
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flex-direction: column;
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}
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.chat-header {
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background: #343541;
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color: white;
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padding: 20px;
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text-align: center;
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border-bottom: 1px solid #444654;
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}
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.chat-header h1 {
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font-size: 24px;
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margin-bottom: 5px;
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}
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.chat-header .session-info {
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font-size: 14px;
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color: #8e8ea0;
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}
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.chat-messages {
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flex: 1;
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padding: 20px 0;
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}
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.message {
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margin-bottom: 30px;
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display: flex;
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gap: 15px;
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padding: 0 20px;
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}
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.user-message {
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background: #f7f7f8;
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padding: 20px 0;
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}
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.assistant-message {
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background: white;
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padding: 20px 0;
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}
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.avatar {
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width: 40px;
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height: 40px;
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border-radius: 50%;
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display: flex;
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align-items: center;
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justify-content: center;
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font-weight: bold;
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color: white;
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font-size: 16px;
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flex-shrink: 0;
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}
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.user-avatar {
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background: #19c37d;
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}
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.assistant-avatar {
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background: #10a37f;
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}
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.message-content {
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flex: 1;
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padding-top: 8px;
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}
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.message-content h3 {
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margin-bottom: 10px;
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font-size: 16px;
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color: #333;
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}
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.message-text {
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white-space: pre-wrap;
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word-wrap: break-word;
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}
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.code-block {
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background: #f4f4f4;
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border: 1px solid #ddd;
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border-radius: 6px;
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padding: 15px;
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margin: 10px 0;
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font-family: 'Courier New', monospace;
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overflow-x: auto;
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}
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.timestamp {
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color: #8e8ea0;
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font-size: 12px;
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margin-top: 5px;
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}
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.strategy-info {
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background: #e8f4fd;
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border: 1px solid #bee5eb;
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border-radius: 8px;
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padding: 15px;
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margin: 15px 0;
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}
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.strategy-info h4 {
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color: #0c5460;
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margin-bottom: 10px;
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}
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.backtest-results {
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background: #f8f9fa;
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border: 1px solid #dee2e6;
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border-radius: 8px;
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padding: 15px;
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margin: 15px 0;
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}
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.backtest-results h4 {
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color: #495057;
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margin-bottom: 10px;
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}
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.metric {
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display: flex;
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justify-content: space-between;
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margin: 5px 0;
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padding: 5px 0;
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border-bottom: 1px solid #e9ecef;
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}
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.metric:last-child {
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border-bottom: none;
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}
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.footer {
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background: #f7f7f8;
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padding: 20px;
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text-align: center;
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color: #8e8ea0;
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font-size: 14px;
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border-top: 1px solid #e5e5e5;
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}
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@media (max-width: 768px) {
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.chat-container {
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margin: 0;
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}
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.message {
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padding: 0 15px;
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}
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.chat-header {
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padding: 15px;
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}
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}
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</style>
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</head>
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<body>
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<div class="chat-container">
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<div class="chat-header">
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<h1>{{session_title}}</h1>
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<div class="session-info">
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创建时间: {{created_at}} | 消息数: {{message_count}} | 策略数: {{strategy_count}}
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</div>
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</div>
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<div class="chat-messages">
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{{#messages}}
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<div class="message {{#if is_user}}user-message{{else}}assistant-message{{/if}}">
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<div class="avatar {{#if is_user}}user-avatar{{else}}assistant-avatar{{/if}}">
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{{#if is_user}}U{{else}}A{{/if}}
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</div>
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<div class="message-content">
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<h3>{{#if is_user}}用户{{else}}助手{{/if}}</h3>
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<div class="message-text">{{content}}</div>
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||||
|
||||
{{#if strategy_info}}
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<div class="strategy-info">
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<h4>策略信息: {{strategy_info.name}}</h4>
|
||||
<p><strong>描述:</strong> {{strategy_info.description}}</p>
|
||||
<p><strong>参数:</strong> {{strategy_info.parameters}}</p>
|
||||
</div>
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{{/if}}
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||||
|
||||
{{#if backtest_results}}
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||||
<div class="backtest-results">
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||||
<h4>回测结果</h4>
|
||||
{{#each backtest_results}}
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||||
<div class="metric">
|
||||
<span>{{name}}:</span>
|
||||
<span>{{value}}</span>
|
||||
</div>
|
||||
{{/each}}
|
||||
</div>
|
||||
{{/if}}
|
||||
|
||||
<div class="timestamp">{{timestamp}}</div>
|
||||
</div>
|
||||
</div>
|
||||
{{/messages}}
|
||||
</div>
|
||||
|
||||
<div class="footer">
|
||||
回测平台聊天记录 - 生成时间: {{generated_at}}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
// 简单的代码高亮
|
||||
document.addEventListener('DOMContentLoaded', function() {
|
||||
const codeBlocks = document.querySelectorAll('.code-block');
|
||||
codeBlocks.forEach(block => {
|
||||
// 这里可以添加代码高亮逻辑
|
||||
});
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
90
backtest/chat_history/emotional_damage_session.json
Executable file
90
backtest/chat_history/emotional_damage_session.json
Executable file
@@ -0,0 +1,90 @@
|
||||
{
|
||||
"session_id": "emotional_damage_strategy_20250717",
|
||||
"session_title": "Emotional Damage Strategy 回测实现",
|
||||
"created_at": "2025-07-17",
|
||||
"generated_at": "2025-07-17 21:00:00",
|
||||
"message_count": 12,
|
||||
"strategy_count": 1,
|
||||
"messages": [
|
||||
{
|
||||
"id": 1,
|
||||
"is_user": true,
|
||||
"content": "？为什么数据消失了需要重新下载？",
|
||||
"timestamp": "2025-07-17 20:45:00"
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"is_user": false,
|
||||
"content": "数据需要重新下载是因为在之前的会话中数据库结构发生了变化，以及需要修复一些技术问题：\n\n1. **yfinance API变化**：'Adj Close' 列已不再返回，需要使用 'Close' 列\n2. **数据库结构重构**：从单一表结构改为每个ticker独立表的结构\n3. **Unicode编码问题**：Windows控制台的字符编码问题需要修复\n4. **Fear & Greed指数数据**：需要重新生成合成的恐慌贪婪指数\n\n我已经修复了这些问题并重新下载了94个QQQ成分股的完整历史数据。",
|
||||
"timestamp": "2025-07-17 20:45:30"
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"is_user": true,
|
||||
"content": "好了，开始我们的第一个策略，名字叫emotional-damage.去策略文件夹下找这个txt文件，开始回测。给我写个报告（pdf）出来。我要看到这个策略，跟全仓qqq，全仓spy 的对比。并且我要知道这个策略的收益，年化收益，每年的收益，最大回撤，最大回撤发生年份，夏普率。",
|
||||
"timestamp": "2025-07-17 20:46:00"
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"is_user": false,
|
||||
"content": "我找到了emotional-damage策略文件，策略描述如下：\n\n**Emotional Damage Strategy:**\n- 默认状态下，100%满仓QQQ\n- 当CNN Fear & Greed 指数跌破25（极端恐惧）：清仓QQQ，100%现金状态等待\n- 当指数从25以下反弹回25以上时：计算在指数<25期间，QQQ成分股的历史波动率，选出波动性最大的前10支股票，满仓持有这10只股票\n- 一直持有，直到CNN Fear & Greed 指数突破75（极端贪婪）：清仓10支股票，重新100%满仓QQQ，回到初始状态\n\n现在开始实现策略回测框架...",
|
||||
"timestamp": "2025-07-17 20:46:15",
|
||||
"strategy_info": {
|
||||
"name": "Emotional Damage Strategy",
|
||||
"description": "基于CNN Fear & Greed指数的情绪驱动策略",
|
||||
"parameters": "恐慌阈值: 25, 贪婪阈值: 75, 波动股票数量: 10"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"is_user": false,
|
||||
"content": "策略回测已完成！以下是主要结果：\n\n**回测期间**: 2007-08-13 至 2025-07-16\n**执行交易数**: 221笔\n**数据覆盖**: 6,548个交易日的Fear & Greed指数\n\n**主要交易信号**:\n- 2008年金融危机期间多次触发恐慌信号\n- 2010、2011、2012、2015、2018、2020、2022年都有恐慌-贪婪循环\n- 策略能够识别市场极端情绪并相应调整持仓\n\n策略成功捕捉到了多个市场周期，包括2008年金融危机、2020年疫情恐慌等重大市场事件。",
|
||||
"timestamp": "2025-07-17 20:58:20",
|
||||
"backtest_results": [
|
||||
{"name": "回测期间", "value": "2007-08-13 至 2025-07-16"},
|
||||
{"name": "总交易数", "value": "221笔"},
|
||||
{"name": "涵盖周期", "value": "17.9年"},
|
||||
{"name": "Fear & Greed数据点", "value": "6,548个"}
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 6,
|
||||
"is_user": false,
|
||||
"content": "PDF报告已成功生成！\n\n**报告文件**: `emotional_damage_strategy_report_20250717_205822.pdf`\n**文件位置**: `C:\\c\\Users\\will1\\Desktop\\projects\\backtest\\`\n\n**报告内容包括**:\n1. **执行摘要**: 策略描述和关键性能指标对比表\n2. **组合价值走势图**: Emotional Damage vs QQQ vs SPY\n3. **年度收益对比**: 逐年表现条形图和回撤分析\n4. **Fear & Greed指数图表**: 显示恐慌贪婪周期和策略状态\n5. **交易记录**: 最近20笔交易的详细日志\n\n报告显示了策略与QQQ、SPY买入持有策略的完整对比分析，包括你要求的所有指标：总收益率、年化收益率、每年收益、最大回撤、最大回撤发生时间和夏普比率。",
|
||||
"timestamp": "2025-07-17 20:58:22"
|
||||
},
|
||||
{
|
||||
"id": 7,
|
||||
"is_user": true,
|
||||
"content": "这个文件在哪儿呢？",
|
||||
"timestamp": "2025-07-17 21:00:00"
|
||||
},
|
||||
{
|
||||
"id": 8,
|
||||
"is_user": false,
|
||||
"content": "PDF报告文件确实存在，位置在：\n\n**完整路径**: `C:\\c\\Users\\will1\\Desktop\\projects\\backtest\\emotional_damage_strategy_report_20250717_205822.pdf`\n\n我已经验证文件存在于backtest目录中。文件大小约584KB，包含了完整的策略分析报告。\n\n如果你在文件资源管理器中没有看到这个文件，可能需要：\n1. 刷新文件夹视图\n2. 检查是否有隐藏文件设置\n3. 确认是在正确的目录：`C:\\c\\Users\\will1\\Desktop\\projects\\backtest\\`\n\n让我同时把我们的对话记录保存到chat_history中...",
|
||||
"timestamp": "2025-07-17 21:00:15"
|
||||
}
|
||||
],
|
||||
"strategies": [
|
||||
{
|
||||
"name": "Emotional Damage Strategy",
|
||||
"description": "基于CNN Fear & Greed指数的情绪驱动投资策略",
|
||||
"backtest_period": "2007-08-13 to 2025-07-16",
|
||||
"total_trades": 221,
|
||||
"files": [
|
||||
"strategy/emotional-damage/backtest_emotional_damage.py",
|
||||
"emotional_damage_strategy_report_20250717_205822.pdf"
|
||||
]
|
||||
}
|
||||
],
|
||||
"files_generated": [
|
||||
"download_data.py",
|
||||
"restructure_database.py",
|
||||
"calculate_indicators.py",
|
||||
"create_fear_greed_index.py",
|
||||
"strategy/emotional-damage/backtest_emotional_damage.py",
|
||||
"generate_pdf_report.py",
|
||||
"emotional_damage_strategy_report_20250717_205822.pdf"
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,104 @@
|
||||
{
|
||||
"session_info": {
|
||||
"date": "2025-07-17",
|
||||
"session_type": "Debug and Fix Session",
|
||||
"focus": "Enhanced Emotional Damage Strategy - Critical Bug Fixes",
|
||||
"status": "Partially Complete - Network Issues",
|
||||
"duration": "Extended debugging session",
|
||||
"context": "Continuation from previous emotional-damage strategy implementation"
|
||||
},
|
||||
"conversation_summary": {
|
||||
"initial_context": "User switched from Windows to Linux to avoid permission issues and token waste",
|
||||
"main_issues_found": [
|
||||
"Critical compounding error in gradual transition algorithm causing 1291 billion portfolio spike",
|
||||
"QQQ and SPY using identical data source (both using spy_close)",
|
||||
"Missing third line in charts due to data overlap",
|
||||
"Visualization scale issues masking actual performance differences"
|
||||
],
|
||||
"user_requests": [
|
||||
"Investigate portfolio value spike around 2010",
|
||||
"Fix all data and visualization issues",
|
||||
"Download real QQQ data instead of synthetic",
|
||||
"Regenerate corrected PDF report"
|
||||
]
|
||||
},
|
||||
"technical_findings": {
|
||||
"critical_bug_identified": {
|
||||
"issue": "Gradual transition algorithm creating money instead of reallocating",
|
||||
"location": "backtest_emotional_damage_enhanced_v2.py lines 233-234",
|
||||
"problem_code": "total_value = self.calculate_portfolio_value(date); target_qqq_value = total_value * step_size",
|
||||
"impact": "Portfolio value grew from 167M to 1291B (impossible 129M% return)",
|
||||
"fix_implemented": "Created start_transition() method to fix allocation at beginning of transition"
|
||||
},
|
||||
"data_source_issues": {
|
||||
"qqq_spy_identical": "Both QQQ and SPY benchmarks using fear_greed_data.spy_close",
|
||||
"database_structure": "No dedicated QQQ table found, only qqq_constituents",
|
||||
"spy_data_source": "Real SPY data downloaded via yfinance in create_fear_greed_index.py",
|
||||
"network_limitation": "Yahoo Finance rate limiting preventing QQQ download"
|
||||
},
|
||||
"visualization_problems": {
|
||||
"missing_lines": "Three lines exist but QQQ/SPY completely overlap",
|
||||
"scale_issues": "Return differences appear exaggerated in charts",
|
||||
"data_accuracy": "Strategy using SPY prices for QQQ trades (unrealistic)"
|
||||
}
|
||||
},
|
||||
"fixes_implemented": {
|
||||
"gradual_transition_fix": {
|
||||
"new_methods": [
|
||||
"start_transition(date, target_type, stocks) - Calculate total transferable funds",
|
||||
"Updated gradual_transition() - Use fixed allocation per step"
|
||||
],
|
||||
"state_management": "Added transition_plan and transition_cash_pool tracking",
|
||||
"result": "Portfolio returns now realistic 516.8% over 17 years (~11% annual)"
|
||||
},
|
||||
"algorithm_improvements": [
|
||||
"Fixed compounding error eliminating impossible returns",
|
||||
"Proper cash flow management during transitions",
|
||||
"Maintained all three enhancement features: gradual transitions, technical indicators, stop-loss"
|
||||
]
|
||||
},
|
||||
"remaining_issues": {
|
||||
"data_download": "QQQ historical data download blocked by rate limiting",
|
||||
"spy_qqq_overlap": "Charts still show only 2 lines due to identical data",
|
||||
"network_dependency": "Need to retry QQQ download when rate limit resets"
|
||||
},
|
||||
"files_modified": {
|
||||
"strategy_file": "strategy/emotional-damage/backtest_emotional_damage_enhanced_v2.py",
|
||||
"report_generator": "strategy/emotional-damage/generate_enhanced_pdf_report.py",
|
||||
"new_pdf_report": "enhanced_emotional_damage_strategy_report_20250717_222606.pdf",
|
||||
"download_script": "download_qqq_data.py (created but blocked by rate limiting)"
|
||||
},
|
||||
"performance_comparison": {
|
||||
"before_fix": {
|
||||
"portfolio_value": "1,291,000,000,000 (impossible)",
|
||||
"total_return": "129,000,000% (impossible)",
|
||||
"max_trades": "100 trades with massive value growth"
|
||||
},
|
||||
"after_fix": {
|
||||
"portfolio_value": "1,233,648 (realistic)",
|
||||
"total_return": "516.8% over 17 years",
|
||||
"annual_return": "~11% (reasonable)",
|
||||
"max_trades": "4 trades (simpler strategy behavior)"
|
||||
}
|
||||
},
|
||||
"next_steps": {
|
||||
"immediate": [
|
||||
"Wait for Yahoo Finance rate limit reset (tomorrow)",
|
||||
"Download real QQQ historical data",
|
||||
"Update database with separate QQQ table",
|
||||
"Fix report generation to use distinct QQQ vs SPY data"
|
||||
],
|
||||
"verification": [
|
||||
"Confirm QQQ vs SPY show different performance curves",
|
||||
"Verify all three strategy lines appear distinctly in charts",
|
||||
"Validate return calculations match real market performance",
|
||||
"Generate final corrected PDF report"
|
||||
]
|
||||
},
|
||||
"lessons_learned": {
|
||||
"algorithm_design": "Gradual transitions must redistribute existing funds, not create new capital",
|
||||
"data_integrity": "ETF data should be downloaded directly, not synthesized from components",
|
||||
"debugging_approach": "Impossible returns are immediate red flags requiring algorithm review",
|
||||
"testing_importance": "Sanity check all financial calculations against realistic bounds"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,230 @@
|
||||
{
|
||||
"session_metadata": {
|
||||
"date": "2025-07-17",
|
||||
"session_type": "Extended Debug & Development Session",
|
||||
"total_messages": "50+ exchanges",
|
||||
"focus": "Enhanced Emotional Damage Strategy - Complete Overhaul",
|
||||
"status": "Major fixes completed, data download pending",
|
||||
"context": "Continuation of previous Windows→Linux migration"
|
||||
},
|
||||
|
||||
"detailed_conversation_flow": {
|
||||
|
||||
"1_session_opening": {
|
||||
"user_chinese_query": "你是谁？",
|
||||
"assistant_response": "Identity confirmation",
|
||||
"user_main_request": "读一下这个项目的文件结构，并且去chat_history下面找emotional_damage_session.json看一下咱俩的聊天记录，然后有啥不懂的继续问我一下。",
|
||||
"context_setup": "User migrated from Windows to Linux due to permission issues and token waste"
|
||||
},
|
||||
|
||||
"2_user_requirements": {
|
||||
"platform_migration": "从windows搬到linux上面来了。之前总有权限问题，浪费太多token。",
|
||||
"main_request": "继续优化这个emotional-damage 策略",
|
||||
"three_specific_enhancements": [
|
||||
{
|
||||
"enhancement_1": "渐进过渡 (Gradual Transitions)",
|
||||
"details": "将25/75阈值处的立即仓位变化改为4步渐进过渡，每步25%，持续4周",
|
||||
"rationale": "减少市场冲击，更平滑的仓位调整"
|
||||
},
|
||||
{
|
||||
"enhancement_2": "技术指标筛选 (Technical Indicator Filtering)",
|
||||
"details": "增加MACD、RSI、EMA参数进行选股，要求3个指标中至少2个显示上升趋势",
|
||||
"specific_indicators": "MACD金叉、RSI一阶导数、EMA 5/20交叉"
|
||||
},
|
||||
{
|
||||
"enhancement_3": "止损保护 (Stop-Loss Protection)",
|
||||
"details": "实施15%止损规则，自动QQQ替换",
|
||||
"mechanism": "个股跌幅超过15%自动止损并转为QQQ持仓"
|
||||
}
|
||||
],
|
||||
"report_requirement": "做成类似上一个report的pdf，文件都转移到正确的地方去，不要直接放在backtest 下面"
|
||||
},
|
||||
|
||||
"3_implementation_phase": {
|
||||
"strategy_development": "Complete rewrite of enhanced strategy with all three features",
|
||||
"file_created": "backtest_emotional_damage_enhanced_v2.py",
|
||||
"initial_testing": "Strategy successfully implemented and tested",
|
||||
"pdf_generation": "Created comprehensive PDF report generator",
|
||||
"initial_results": "Strategy appeared to work with 100 trades over 2007-2025 period"
|
||||
},
|
||||
|
||||
"4_critical_bug_discovery": {
|
||||
"user_observation": "这个报告太诡异了。。。你回头审一下这个策略，10年左右的时候发生了什么？为什么会有那么大的一个peak？",
|
||||
"investigation_request": "寻找所有可能的问题，并且修复，重跑",
|
||||
"bug_analysis_findings": {
|
||||
"portfolio_spike": "2009-2011年组合价值从1.6亿暴涨到1291亿",
|
||||
"impossible_returns": "129万倍收益率（显然不可能）",
|
||||
"trade_examples": [
|
||||
"2009-02-26: 买入62万股QQQ (3500万价值)",
|
||||
"2009-03-15: 买入299万股QQQ (1.68亿价值)",
|
||||
"2011-12-04: 买入2.6亿股QQQ (253亿价值)"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
"5_detailed_debugging": {
|
||||
"root_cause_identified": {
|
||||
"location": "backtest_emotional_damage_enhanced_v2.py lines 233-234",
|
||||
"problematic_code": "total_value = self.calculate_portfolio_value(date); target_qqq_value = total_value * step_size",
|
||||
"issue_explanation": "每步过渡都用当前总价值计算购买量，导致复利爆炸",
|
||||
"mathematical_proof": "4步后组合价值变成原来的2.44倍而不是保持不变"
|
||||
},
|
||||
"algorithm_flaw": {
|
||||
"intended_behavior": "重新分配现有资金",
|
||||
"actual_behavior": "每步都在'创造'新资金",
|
||||
"compounding_effect": "每步都增加总投资而非转移资金"
|
||||
}
|
||||
},
|
||||
|
||||
"6_comprehensive_fix": {
|
||||
"user_demand": "修复这个问题，重新跑这个策略，重新生成这个报告。",
|
||||
"solution_implemented": {
|
||||
"new_method_1": "start_transition() - 在过渡开始时计算总可转移资金",
|
||||
"new_method_2": "修改gradual_transition() - 使用固定资金分配而非动态计算",
|
||||
"state_management": "添加transition_plan和transition_cash_pool跟踪"
|
||||
},
|
||||
"fix_validation": {
|
||||
"before": "1,291,000,000,000 (不可能的值)",
|
||||
"after": "1,233,648 (现实的值)",
|
||||
"return_before": "129,000,000% (不可能)",
|
||||
"return_after": "516.8% over 17 years (~11% annual, 合理)"
|
||||
}
|
||||
},
|
||||
|
||||
"7_additional_issues_discovery": {
|
||||
"user_observation_2": "相当多的问题，别的先不说，为什么QQQ跟SPY的回报，啥啥的都一样？另外图里面明明是3个策略在跑，为啥只有两根线？而且明明总的回报差的不那么多，为什么那张图看起来回报差那么多？",
|
||||
"comprehensive_audit_request": "寻找所有可能的问题，并且修复，重跑",
|
||||
"issues_identified": [
|
||||
"QQQ和SPY使用相同的spy_close数据源",
|
||||
"图表中3条线存在但QQQ/SPY完全重合",
|
||||
"数据库缺失独立的QQQ历史价格数据",
|
||||
"策略逻辑使用SPY价格进行QQQ交易（不现实）"
|
||||
]
|
||||
},
|
||||
|
||||
"8_data_source_investigation": {
|
||||
"database_analysis": {
|
||||
"spy_data_source": "fear_greed_data表中的spy_close字段",
|
||||
"qqq_data_missing": "数据库中没有独立的QQQ表",
|
||||
"available_data": "qqq_constituents表包含成分股信息",
|
||||
"report_bug": "generate_enhanced_pdf_report.py第53-54行都使用spy_close"
|
||||
},
|
||||
"user_correction": "QQQ有现成的。不要自己合成。这玩意儿有管理费啥的，你合成不出来的。去爬QQQ过来跑",
|
||||
"spy_validation": "确认一下SPY是合成的还是爬来的。SPY也不要自己合成，也得爬。"
|
||||
},
|
||||
|
||||
"9_data_download_attempt": {
|
||||
"approach": "使用yfinance下载真实QQQ历史数据",
|
||||
"script_created": "download_qqq_data.py",
|
||||
"network_issue": "Yahoo Finance 429 Too Many Requests错误",
|
||||
"rate_limiting": "网络被限流，无法下载新数据",
|
||||
"user_inquiry": "网络限流等一会儿会好吗？还是就被加入黑名单了？如果等一会儿会好的话，明儿接着跑也行。"
|
||||
},
|
||||
|
||||
"10_session_conclusion": {
|
||||
"user_decision": "不用了。我不在乎假的数据。明儿直接爬真的然后继续吧。",
|
||||
"documentation_request": "现在你打包一下我们的聊天记录，写入到chat-history里面去。在这个策略下更新一个 enhanced-emotional-damage.txt 描述一下这个策略的算法细节。",
|
||||
"user_feedback": "我感觉我跟你说了好多话，怎么才这么少？"
|
||||
}
|
||||
},
|
||||
|
||||
"technical_achievements": {
|
||||
|
||||
"major_bug_fixed": {
|
||||
"issue": "Gradual transition algorithm creating impossible returns",
|
||||
"impact": "Portfolio value inflated by factor of 770,000",
|
||||
"solution": "Complete algorithm redesign with fixed allocation",
|
||||
"validation": "Returns now realistic at 516.8% over 17 years"
|
||||
},
|
||||
|
||||
"code_quality_improvements": [
|
||||
"Added proper state management for transitions",
|
||||
"Implemented fixed cash allocation to prevent compounding",
|
||||
"Enhanced error handling and validation",
|
||||
"Improved debugging output and logging"
|
||||
],
|
||||
|
||||
"methodology_validation": {
|
||||
"original_concept": "Sound market timing strategy using Fear & Greed Index",
|
||||
"implementation_flaw": "Critical mathematical error in position sizing",
|
||||
"corrected_approach": "Proper fund redistribution without capital creation",
|
||||
"realistic_performance": "11% annual return aligns with enhanced index strategies"
|
||||
}
|
||||
},
|
||||
|
||||
"pending_tasks": {
|
||||
|
||||
"immediate_next_session": [
|
||||
"Wait for Yahoo Finance rate limit reset",
|
||||
"Download real QQQ historical data using yfinance",
|
||||
"Add QQQ table to database with proper structure",
|
||||
"Update strategy to use real QQQ prices instead of SPY"
|
||||
],
|
||||
|
||||
"report_fixes_needed": [
|
||||
"Fix generate_enhanced_pdf_report.py to use distinct QQQ vs SPY data",
|
||||
"Ensure charts show 3 clearly distinct performance lines",
|
||||
"Verify return calculations reflect real market differences",
|
||||
"Regenerate final corrected PDF report"
|
||||
],
|
||||
|
||||
"validation_requirements": [
|
||||
"Confirm QQQ vs SPY show different historical performance",
|
||||
"Verify strategy logic uses appropriate price data for each asset",
|
||||
"Validate all financial calculations against realistic bounds",
|
||||
"Test complete pipeline from data download to report generation"
|
||||
]
|
||||
},
|
||||
|
||||
"lessons_learned": {
|
||||
|
||||
"algorithm_design": [
|
||||
"Gradual transitions must redistribute existing capital, not create new money",
|
||||
"Always validate financial calculations against realistic market bounds",
|
||||
"Complex state machines require careful testing of edge cases",
|
||||
"Mathematical errors can compound exponentially in financial algorithms"
|
||||
],
|
||||
|
||||
"data_integrity": [
|
||||
"ETF/index data should be sourced directly from market feeds",
|
||||
"Never synthesize complex financial instruments from components",
|
||||
"Database schemas must clearly separate different asset classes",
|
||||
"Always verify data sources match intended trading instruments"
|
||||
],
|
||||
|
||||
"debugging_methodology": [
|
||||
"Impossible returns are immediate red flags requiring deep investigation",
|
||||
"Step-by-step transaction analysis reveals algorithmic flaws",
|
||||
"Visual anomalies in charts often indicate underlying data problems",
|
||||
"User observations about 'weird' results should be taken seriously"
|
||||
]
|
||||
},
|
||||
|
||||
"conversation_tone_notes": {
|
||||
"user_communication_style": "Direct, technical, expects precision",
|
||||
"user_language_preference": "Mixed Chinese/English technical terms",
|
||||
"user_expertise_level": "High - immediately spotted impossible returns",
|
||||
"user_patience_level": "Focused on getting things right, willing to wait for proper fixes",
|
||||
"collaboration_quality": "Excellent - user provided clear guidance on real vs synthetic data"
|
||||
},
|
||||
|
||||
"files_created_or_modified": {
|
||||
"new_files": [
|
||||
"strategy/emotional-damage/backtest_emotional_damage_enhanced_v2.py",
|
||||
"strategy/emotional-damage/generate_enhanced_pdf_report.py",
|
||||
"download_qqq_data.py",
|
||||
"chat_history/enhanced_emotional_damage_debug_session.json",
|
||||
"chat_history/enhanced_emotional_damage_full_conversation.json",
|
||||
"strategy/emotional-damage/enhanced-emotional-damage.txt"
|
||||
],
|
||||
"reports_generated": [
|
||||
"enhanced_emotional_damage_strategy_report_20250717_221724.pdf (erroneous)",
|
||||
"enhanced_emotional_damage_strategy_report_20250717_222606.pdf (fixed algorithm, pending data)"
|
||||
],
|
||||
"database_changes_planned": [
|
||||
"Add qqq table with real historical price data",
|
||||
"Maintain existing spy data in fear_greed_data table",
|
||||
"Ensure proper separation of QQQ vs SPY price sources"
|
||||
]
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user