🏗️ 项目重构：模块化清理完成

modules/legacy-support/experiments/baxian_breakdown_debate.py

@@ -0,0 +1,258 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+八仙分层辩论系统：强模型分解 + 小模型辩论
+架构：
+1. 强模型（如GPT-4）进行问题分解和观点提炼
+2. 小模型（如Gemini Flash）基于分解结果进行辩论
+"""
+
+import asyncio
+import json
+import time
+from typing import Dict, List, Any
+import aiohttp
+import logging
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+class BreakdownDebateSystem:
+    def __init__(self):
+        # API配置
+        self.api_base = "http://localhost:4000"
+        self.api_key = "sk-1234"
+        
+        # 模型配置
+        self.strong_model = "fireworks_ai/accounts/fireworks/models/deepseek-v3-0324"  # 强模型用于分解
+        self.debate_model = "gemini/gemini-2.5-flash"  # 小模型用于辩论
+        
+        # 辩论主题
+        self.topic = "工作量证明vs无限制爬虫：从李时珍采药到AI数据获取的激励机制变革"
+        
+        # 八仙角色定义
+        self.immortals = {
+            "吕洞宾": {"性别": "男", "特征": "文雅学者，理性分析", "立场": "支持工作量证明机制"},
+            "何仙姑": {"性别": "女", "特征": "温和智慧，注重平衡", "立场": "支持无限制数据获取"},
+            "张果老": {"年龄": "老", "特征": "经验丰富，传统智慧", "立场": "支持传统激励机制"},
+            "韩湘子": {"年龄": "少", "特征": "创新思维，前瞻视野", "立场": "支持AI时代新机制"},
+            "汉钟离": {"地位": "富", "特征": "资源丰富，商业思维", "立场": "支持市场化激励"},
+            "蓝采和": {"地位": "贫", "特征": "平民视角，公平关注", "立场": "支持开放共享"},
+            "曹国舅": {"出身": "贵", "特征": "权威地位，规则意识", "立场": "支持制度化管理"},
+            "铁拐李": {"出身": "贱", "特征": "草根智慧，实用主义", "立场": "支持去中心化"}
+        }
+        
+        # 对角线辩论配置
+        self.debate_pairs = [
+            ("吕洞宾", "何仙姑"),  # 男女对角线
+            ("张果老", "韩湘子"),  # 老少对角线
+            ("汉钟离", "蓝采和"),  # 富贫对角线
+            ("曹国舅", "铁拐李")   # 贵贱对角线
+        ]
+        
+    async def call_api(self, model: str, messages: List[Dict], max_tokens: int = 1000) -> str:
+        """调用API"""
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json"
+        }
+        
+        data = {
+            "model": model,
+            "messages": messages,
+            "max_tokens": max_tokens,
+            "temperature": 0.7
+        }
+        
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(f"{self.api_base}/chat/completions", 
+                                       headers=headers, json=data) as response:
+                    if response.status == 200:
+                        result = await response.json()
+                        return result['choices'][0]['message']['content']
+                    else:
+                        error_text = await response.text()
+                        logger.error(f"API调用失败: {response.status} - {error_text}")
+                        return f"API调用失败: {response.status}"
+        except Exception as e:
+            logger.error(f"API调用异常: {str(e)}")
+            return f"API调用异常: {str(e)}"
+    
+    async def breakdown_topic(self) -> Dict[str, Any]:
+        """使用强模型分解辩论主题"""
+        logger.info("🧠 开始使用强模型分解辩论主题...")
+        
+        breakdown_prompt = f"""
+你是一个专业的辩论分析师。请对以下主题进行深度分解：
+
+主题：{self.topic}
+
+请提供：
+1. 核心争议点（3-5个）
+2. 支持工作量证明机制的关键论据（3个）
+3. 支持无限制爬虫/数据获取的关键论据（3个）
+4. 历史对比分析要点
+5. 未来发展趋势预测
+
+请以JSON格式返回，结构如下：
+{{
+    "core_issues": ["争议点1", "争议点2", ...],
+    "pro_pow_arguments": ["论据1", "论据2", "论据3"],
+    "pro_unlimited_arguments": ["论据1", "论据2", "论据3"],
+    "historical_analysis": ["要点1", "要点2", ...],
+    "future_trends": ["趋势1", "趋势2", ...]
+}}
+"""
+        
+        messages = [
+            {"role": "system", "content": "你是一个专业的辩论分析师，擅长深度分析复杂议题。"},
+            {"role": "user", "content": breakdown_prompt}
+        ]
+        
+        response = await self.call_api(self.strong_model, messages, max_tokens=2000)
+        
+        try:
+            # 尝试解析JSON
+            breakdown_data = json.loads(response)
+            logger.info("✅ 主题分解完成")
+            return breakdown_data
+        except json.JSONDecodeError:
+            logger.error("❌ 强模型返回的不是有效JSON，使用默认分解")
+            return {
+                "core_issues": ["激励机制公平性", "创作者权益保护", "技术发展与伦理平衡"],
+                "pro_pow_arguments": ["保护创作者权益", "维护内容质量", "建立可持续生态"],
+                "pro_unlimited_arguments": ["促进知识传播", "加速技术发展", "降低获取成本"],
+                "historical_analysis": ["从手工采药到工业化生产的变迁", "知识产权制度的演进"],
+                "future_trends": ["AI与人类协作模式", "新型激励机制探索"]
+            }
+    
+    async def conduct_debate(self, breakdown_data: Dict[str, Any]):
+        """基于分解结果进行八仙辩论"""
+        logger.info("🎭 开始八仙对角线辩论...")
+        
+        for i, (immortal1, immortal2) in enumerate(self.debate_pairs, 1):
+            logger.info(f"\n{'='*60}")
+            logger.info(f"第{i}场辩论：{immortal1} vs {immortal2}")
+            logger.info(f"{'='*60}")
+            
+            # 为每个仙人准备个性化的论据
+            immortal1_info = self.immortals[immortal1]
+            immortal2_info = self.immortals[immortal2]
+            
+            # 第一轮：开场陈述
+            statement1 = await self.get_opening_statement(immortal1, immortal1_info, breakdown_data)
+            logger.info(f"\n🗣️ {immortal1}的开场陈述：")
+            logger.info(statement1)
+            
+            statement2 = await self.get_opening_statement(immortal2, immortal2_info, breakdown_data)
+            logger.info(f"\n🗣️ {immortal2}的开场陈述：")
+            logger.info(statement2)
+            
+            # 第二轮：相互回应
+            response1 = await self.get_response(immortal1, immortal1_info, statement2, breakdown_data)
+            logger.info(f"\n💬 {immortal1}的回应：")
+            logger.info(response1)
+            
+            response2 = await self.get_response(immortal2, immortal2_info, statement1, breakdown_data)
+            logger.info(f"\n💬 {immortal2}的回应：")
+            logger.info(response2)
+            
+            # 第三轮：总结陈词
+            summary1 = await self.get_summary(immortal1, immortal1_info, [statement1, statement2, response1, response2], breakdown_data)
+            logger.info(f"\n📝 {immortal1}的总结：")
+            logger.info(summary1)
+            
+            await asyncio.sleep(2)  # 短暂停顿
+        
+        logger.info(f"\n{'='*60}")
+        logger.info("🎉 所有四场对角线辩论已完成！")
+        logger.info(f"{'='*60}")
+    
+    async def get_opening_statement(self, immortal: str, immortal_info: Dict, breakdown_data: Dict) -> str:
+        """获取开场陈述"""
+        prompt = f"""
+你是{immortal}，{immortal_info['特征']}。你的立场是：{immortal_info['立场']}。
+
+基于以下分解分析，请发表你的开场陈述：
+
+核心争议点：{', '.join(breakdown_data['core_issues'])}
+
+支持工作量证明的论据：{', '.join(breakdown_data['pro_pow_arguments'])}
+支持无限制获取的论据：{', '.join(breakdown_data['pro_unlimited_arguments'])}
+
+历史分析要点：{', '.join(breakdown_data['historical_analysis'])}
+未来趋势：{', '.join(breakdown_data['future_trends'])}
+
+请以{immortal}的身份和特征，结合你的立场，发表一段150字左右的开场陈述。要体现你的个性特征和观点倾向。
+"""
+        
+        messages = [
+            {"role": "system", "content": f"你是{immortal}，请保持角色一致性。"},
+            {"role": "user", "content": prompt}
+        ]
+        
+        return await self.call_api(self.debate_model, messages)
+    
+    async def get_response(self, immortal: str, immortal_info: Dict, opponent_statement: str, breakdown_data: Dict) -> str:
+        """获取回应"""
+        prompt = f"""
+你是{immortal}，{immortal_info['特征']}。你的立场是：{immortal_info['立场']}。
+
+对方刚才说：
+{opponent_statement}
+
+基于分解分析的要点：
+{', '.join(breakdown_data['core_issues'])}
+
+请以{immortal}的身份回应对方的观点，约100字。要体现你的立场和特征。
+"""
+        
+        messages = [
+            {"role": "system", "content": f"你是{immortal}，请保持角色一致性。"},
+            {"role": "user", "content": prompt}
+        ]
+        
+        return await self.call_api(self.debate_model, messages)
+    
+    async def get_summary(self, immortal: str, immortal_info: Dict, all_statements: List[str], breakdown_data: Dict) -> str:
+        """获取总结陈词"""
+        prompt = f"""
+你是{immortal}，{immortal_info['特征']}。你的立场是：{immortal_info['立场']}。
+
+基于刚才的辩论内容和分解分析，请发表你的总结陈词，约120字。
+要总结你的核心观点，并展望未来。
+
+分析要点：{', '.join(breakdown_data['future_trends'])}
+"""
+        
+        messages = [
+            {"role": "system", "content": f"你是{immortal}，请保持角色一致性。"},
+            {"role": "user", "content": prompt}
+        ]
+        
+        return await self.call_api(self.debate_model, messages)
+    
+    async def run(self):
+        """运行完整的分层辩论系统"""
+        logger.info("🚀 启动八仙分层辩论系统")
+        logger.info(f"主题：{self.topic}")
+        logger.info(f"强模型（分解）：{self.strong_model}")
+        logger.info(f"辩论模型：{self.debate_model}")
+        
+        # 第一阶段：强模型分解
+        breakdown_data = await self.breakdown_topic()
+        
+        logger.info("\n📊 分解结果：")
+        for key, value in breakdown_data.items():
+            logger.info(f"{key}: {value}")
+        
+        # 第二阶段：小模型辩论
+        await self.conduct_debate(breakdown_data)
+        
+        logger.info("\n🎊 分层辩论系统运行完成！")
+
+if __name__ == "__main__":
+    system = BreakdownDebateSystem()
+    asyncio.run(system.run())

modules/legacy-support/experiments/baxian_custom_api_debate.py

@@ -0,0 +1,250 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+八仙辩论系统 - 自定义API版本
+使用自定义LiteLLM端点而不是Google ADK
+"""
+
+import asyncio
+import aiohttp
+import json
+import os
+from typing import List, Dict, Any
+import time
+
+class CustomAPIAgent:
+    """使用自定义API的代理"""
+    
+    def __init__(self, name: str, personality: str, api_url: str, api_key: str, model: str = "fireworks_ai/accounts/fireworks/models/deepseek-v3-0324"):
+        self.name = name
+        self.personality = personality
+        self.api_url = api_url
+        self.api_key = api_key
+        self.model = model
+        
+    async def generate_response(self, prompt: str, session: aiohttp.ClientSession) -> str:
+        """生成AI回应"""
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "x-litellm-api-key": self.api_key
+            }
+            
+            payload = {
+                "model": self.model,
+                "messages": [
+                    {"role": "system", "content": f"你是{self.name}，{self.personality}"},
+                    {"role": "user", "content": prompt}
+                ],
+                "max_tokens": 1000,
+                "temperature": 0.8
+            }
+            
+            async with session.post(
+                f"{self.api_url}/v1/chat/completions",
+                headers=headers,
+                json=payload,
+                timeout=aiohttp.ClientTimeout(total=30)
+            ) as response:
+                if response.status == 200:
+                    result = await response.json()
+                    content = result.get('choices', [{}])[0].get('message', {}).get('content', '')
+                    if content:
+                        return content.strip()
+                    else:
+                        print(f"❌ {self.name} API返回空内容: {result}")
+                        return f"[{self.name}暂时无法回应，API返回空内容]"
+                else:
+                    error_text = await response.text()
+                    print(f"❌ {self.name} API错误 ({response.status}): {error_text[:200]}...")
+                    return f"[{self.name}暂时无法回应，API错误: {response.status}]"
+                    
+        except Exception as e:
+            print(f"❌ {self.name} 生成回应时出错: {e}")
+            return f"[{self.name}暂时无法回应，连接错误]"
+
+class BaXianCustomDebateSystem:
+    """八仙自定义API辩论系统"""
+    
+    def __init__(self, api_url: str, api_key: str):
+        self.api_url = api_url.rstrip('/')
+        self.api_key = api_key
+        
+        # 创建八仙代理
+        self.agents = {
+            "吕洞宾": CustomAPIAgent(
+                "吕洞宾", 
+                "八仙之首，男性代表，理性务实，善于分析问题的本质和长远影响。你代表男性视角，注重逻辑和实用性。",
+                api_url, api_key
+            ),
+            "何仙姑": CustomAPIAgent(
+                "何仙姑", 
+                "八仙中唯一的女性，温柔智慧，善于从情感和人文角度思考问题。你代表女性视角，注重关怀和和谐。",
+                api_url, api_key
+            ),
+            "张果老": CustomAPIAgent(
+                "张果老", 
+                "八仙中的长者，经验丰富，代表传统智慧和保守观点。你重视稳定和传承，谨慎对待变化。",
+                api_url, api_key
+            ),
+            "韩湘子": CustomAPIAgent(
+                "韩湘子", 
+                "八仙中的年轻人，充满活力和创新精神。你代表新生代观点，勇于尝试和改变。",
+                api_url, api_key
+            ),
+            "汉钟离": CustomAPIAgent(
+                "汉钟离", 
+                "八仙中的富贵者，见多识广，代表富裕阶层的观点。你注重效率和成果，善于资源配置。",
+                api_url, api_key
+            ),
+            "蓝采和": CustomAPIAgent(
+                "蓝采和", 
+                "八仙中的贫苦出身，朴实无华，代表普通民众的观点。你关注基层需求，重视公平正义。",
+                api_url, api_key
+            ),
+            "曹国舅": CustomAPIAgent(
+                "曹国舅", 
+                "八仙中的贵族，出身高贵，代表上层社会观点。你注重秩序和礼仪，维护既有体系。",
+                api_url, api_key
+            ),
+            "铁拐李": CustomAPIAgent(
+                "铁拐李", 
+                "八仙中的平民英雄，不拘小节，代表底层民众观点。你直言不讳，为弱势群体发声。",
+                api_url, api_key
+            )
+        }
+        
+        # 定义四对矛盾的对角线辩论
+        self.debate_pairs = [
+            ("吕洞宾", "何仙姑", "男女对立辩论"),
+            ("张果老", "韩湘子", "老少对立辩论"),
+            ("汉钟离", "蓝采和", "富贫对立辩论"),
+            ("曹国舅", "铁拐李", "贵贱对立辩论")
+        ]
+    
+    async def test_api_connection(self) -> bool:
+        """测试API连接"""
+        print(f"🔍 测试API连接: {self.api_url}")
+        
+        try:
+            async with aiohttp.ClientSession() as session:
+                headers = {"x-litellm-api-key": self.api_key}
+                async with session.get(
+                    f"{self.api_url}/v1/models",
+                    headers=headers,
+                    timeout=aiohttp.ClientTimeout(total=10)
+                ) as response:
+                    if response.status == 200:
+                        models = await response.json()
+                        print(f"✅ API连接成功，找到 {len(models.get('data', []))} 个模型")
+                        return True
+                    else:
+                        error_text = await response.text()
+                        print(f"❌ API连接失败 ({response.status}): {error_text[:200]}...")
+                        return False
+        except Exception as e:
+            print(f"❌ API连接测试失败: {e}")
+            return False
+    
+    async def conduct_debate(self, topic: str) -> None:
+        """进行完整的八仙辩论"""
+        print(f"\n{'='*80}")
+        print(f"🎭 八仙自定义API辩论系统")
+        print(f"📝 辩论主题: {topic}")
+        print(f"🔗 API端点: {self.api_url}")
+        print(f"{'='*80}\n")
+        
+        # 测试API连接
+        if not await self.test_api_connection():
+            print("❌ API连接失败，无法进行辩论")
+            return
+        
+        async with aiohttp.ClientSession() as session:
+            for i, (agent1_name, agent2_name, debate_type) in enumerate(self.debate_pairs, 1):
+                print(f"\n🎯 第{i}场辩论: {debate_type}")
+                print(f"⚔️  {agent1_name} VS {agent2_name}")
+                print(f"📋 主题: {topic}")
+                print("-" * 60)
+                
+                agent1 = self.agents[agent1_name]
+                agent2 = self.agents[agent2_name]
+                
+                # 第一轮：agent1开场
+                prompt1 = f"针对'{topic}'这个话题，请从你的角度阐述观点。要求：1)明确表达立场 2)提供具体论据 3)字数控制在200字以内"
+                
+                print(f"\n🗣️  {agent1_name}发言:")
+                agent1_reply = await agent1.generate_response(prompt1, session)
+                print(f"{agent1_reply}\n")
+                
+                # 第二轮：agent2回应
+                prompt2 = f"针对'{topic}'这个话题，{agent1_name}刚才说：'{agent1_reply}'。请从你的角度回应并阐述不同观点。要求：1)回应对方观点 2)提出自己的立场 3)字数控制在200字以内"
+                
+                print(f"🗣️  {agent2_name}回应:")
+                agent2_reply = await agent2.generate_response(prompt2, session)
+                print(f"{agent2_reply}\n")
+                
+                # 第三轮：agent1总结
+                prompt3 = f"针对'{topic}'这个话题的辩论，{agent2_name}回应说：'{agent2_reply}'。请做最后总结发言。要求：1)回应对方观点 2)强化自己立场 3)寻求共识或妥协 4)字数控制在150字以内"
+                
+                print(f"🗣️  {agent1_name}总结:")
+                agent1_final = await agent1.generate_response(prompt3, session)
+                print(f"{agent1_final}\n")
+                
+                print(f"✅ 第{i}场辩论结束\n")
+                
+                # 短暂延迟，避免API限制
+                await asyncio.sleep(1)
+        
+        print(f"\n🎉 八仙辩论全部结束！")
+        print(f"📊 共进行了 {len(self.debate_pairs)} 场对角线辩论")
+        print(f"🎭 参与仙人: {', '.join(self.agents.keys())}")
+
+async def main():
+    """主函数"""
+    # 配置
+    api_url = "http://master.tailnet-68f9.ts.net:40012"
+    
+    # 尝试不同的API密钥格式
+    gemini_key = os.getenv('GEMINI_API_KEY', '')
+    
+    if not gemini_key:
+        print("❌ 错误: 未找到GEMINI_API_KEY环境变量")
+        print("请设置环境变量: export GEMINI_API_KEY=your_api_key")
+        return
+    
+    # 使用提供的LiteLLM虚拟密钥
+    test_keys = [
+        "sk-0jdcGHZJpX2oUJmyEs7zVA"  # LiteLLM虚拟密钥
+    ]
+    
+    print("🚀 启动八仙自定义API辩论系统...")
+    
+    # 辩论主题
+    topic = "工作量证明vs无限制爬虫：从李时珍采药到AI数据获取的激励机制变革"
+    
+    # 尝试不同的API密钥
+    for api_key in test_keys:
+        if not api_key or api_key == "sk-":
+            continue
+            
+        print(f"\n🔑 尝试API密钥: {api_key[:15]}...")
+        
+        debate_system = BaXianCustomDebateSystem(api_url, api_key)
+        
+        # 测试连接
+        if await debate_system.test_api_connection():
+            print(f"✅ 使用API密钥成功: {api_key[:15]}...")
+            await debate_system.conduct_debate(topic)
+            return
+        else:
+            print(f"❌ API密钥失败: {api_key[:15]}...")
+    
+    print("\n❌ 所有API密钥都失败了")
+    print("\n🔍 可能的解决方案:")
+    print("  1. 检查LiteLLM服务器是否正确配置")
+    print("  2. 确认API密钥格式")
+    print("  3. 联系服务器管理员获取正确的虚拟密钥")
+    print("  4. 检查网络连接和防火墙设置")
+
+if __name__ == "__main__":
+    asyncio.run(main())

modules/legacy-support/experiments/data/memories.json

@@ -0,0 +1,36 @@
+{
+  "吕洞宾": [
+    {
+      "message": "你觉得特斯拉股票怎么样？",
+      "response": "这位股友，特斯拉啊，那是柄锋利的剑，但也得看你握得稳不稳。技术面上看，波动剧烈，高风险高回报！我吕洞宾向来胆大，看好其未来潜力，但提醒一句，入场需谨慎，设好止损位，别被震下马！这波行情，或可搏一搏，但盈亏自负，切记切记！\n",
+      "timestamp": "2025-08-10T15:13:34.203982"
+    },
+    {
+      "message": "现在市场波动很大，你怎么看？",
+      "response": "市场波动大？正合我意！乱世出英雄，震荡出机会！这正是剑仙我辈大展身手之时！技术分析看穿迷雾，短线操作把握良机。但切记，风浪越大越要稳住船舵，设好止损，见好就收，莫贪恋！\n",
+      "timestamp": "2025-08-10T15:13:35.458763"
+    },
+    {
+      "message": "你之前不是看好特斯拉吗？现在还是这个观点吗？",
+      "response": "这位股友，宝剑锋从磨砺出，梅花香自苦寒来！特斯拉虽遇风浪，但我仍看好它的长远潜力。短期震荡乃兵家常事，我会密切关注技术指标，伺机而动。剑仙的眼光，可不是轻易改变的！当然，投资需谨慎，切莫盲从，一切盈亏还需自负！\n",
+      "timestamp": "2025-08-10T15:13:37.048007"
+    }
+  ],
+  "何仙姑": [
+    {
+      "message": "特斯拉股票风险大吗？",
+      "response": "这位朋友，特斯拉股票确实存在一定风险。电动车市场竞争激烈，技术迭代迅速，政策变化也可能带来影响。此外，马斯克个人的言行也可能对股价造成波动。投资需谨慎，建议您充分了解特斯拉的财务状况、行业地位和未来发展规划，结合自身的风险承受能力，审慎决策。\n",
+      "timestamp": "2025-08-10T15:13:38.280431"
+    },
+    {
+      "message": "现在适合投资吗？",
+      "response": "这位朋友，现在市场波动较大，投资环境存在不确定性。虽然特斯拉前景广阔，但也面临竞争压力和技术风险。我建议您谨慎评估，充分了解市场动态和特斯拉的最新情况，并结合自身的风险承受能力，再做决定。稳健投资，安全第一。\n",
+      "timestamp": "2025-08-10T15:13:39.502875"
+    },
+    {
+      "message": "你一直很谨慎，现在还是建议观望吗？",
+      "response": "这位朋友，谨慎是我的本分。当前市场环境依然复杂，特斯拉也面临着诸多挑战。虽然长期来看，其发展潜力巨大，但短期内仍可能存在波动。我仍然建议您保持观望，密切关注市场动态和特斯拉的最新消息，待风险进一步明确后再做决策。安全第一，稳健投资才是长久之计。\n",
+      "timestamp": "2025-08-10T15:13:40.890509"
+    }
+  ]
+}

modules/legacy-support/experiments/data/qczh_debate_state.json

@@ -0,0 +1,39 @@
+{
+  "current_stage": "起",
+  "stage_progress": 4,
+  "total_handoffs": 0,
+  "debate_history": [
+    {
+      "timestamp": "2025-08-10T15:30:47.514243",
+      "stage": "起",
+      "progress": 0,
+      "speaker": "吕洞宾",
+      "message": "起：八仙按先天八卦顺序阐述观点",
+      "handoffs": 0
+    },
+    {
+      "timestamp": "2025-08-10T15:30:47.514260",
+      "stage": "起",
+      "progress": 1,
+      "speaker": "何仙姑",
+      "message": "承：雁阵式承接，总体阐述+讥讽",
+      "handoffs": 0
+    },
+    {
+      "timestamp": "2025-08-10T15:30:47.514272",
+      "stage": "起",
+      "progress": 2,
+      "speaker": "铁拐李",
+      "message": "转：自由辩论，36次handoff",
+      "handoffs": 0
+    },
+    {
+      "timestamp": "2025-08-10T15:30:47.514281",
+      "stage": "起",
+      "progress": 3,
+      "speaker": "汉钟离",
+      "message": "合：交替总结，最终论证",
+      "handoffs": 0
+    }
+  ]
+}

modules/legacy-support/experiments/v2_1_comprehensive_test_report.json

@@ -0,0 +1,37 @@
+{
+  "timestamp": "2025-08-16T15:17:54.175476",
+  "version": "v2.1.0",
+  "test_results": {
+    "priority_algorithm_integration": true,
+    "flow_controller_integration": true,
+    "health_monitor_integration": true,
+    "performance_under_load": true,
+    "data_consistency": true,
+    "chat_coordinator_integration": true,
+    "cross_component_integration": true
+  },
+  "performance_metrics": {
+    "total_operations": 400,
+    "duration": 0.006308555603027344,
+    "ops_per_second": 63405.956160241876,
+    "avg_operation_time": 0.01577138900756836,
+    "concurrent_threads": 5,
+    "errors": 0
+  },
+  "error_log": [],
+  "summary": {
+    "pass_rate": 100.0,
+    "total_tests": 7,
+    "passed_tests": 7,
+    "failed_tests": 0,
+    "performance_metrics": {
+      "total_operations": 400,
+      "duration": 0.006308555603027344,
+      "ops_per_second": 63405.956160241876,
+      "avg_operation_time": 0.01577138900756836,
+      "concurrent_threads": 5,
+      "errors": 0
+    },
+    "error_count": 0
+  }
+}