Output: {"filePath": "/root/projects/butler/slack_bot/obsidian/generators.py", "oldString": "1. \u5938\u5f20\u4fee\u9970: \u6781\u5ea6\u8106\u5f31\u3001\u6781\u5176\u8106\u5f31\u3001\u6bc1\u706d\u6027\u7684\u3001\u707e\u96be\u7ea7\u7684\u3001\u538b\u5012\u6027\u7684\u3001\u8fdc\u8d85\u60f3\u8c61\u3001\u4e0d\u6b62\u4e00\u4e2a\u91cf\u7ea7\u3001\u98a0\u8986\u6027\u7684\u3001\u9769\u547d\u6027\u7684\u3001\u6298\u78e8\u4eba\u3001\u5929\u7ffb\u5730\u8986\u3001\u98ce\u9669\u6781\u9ad8\u3001\u77ac\u95f4\u5d29\u65ad\u3001\u7cbe\u75b2\u529b\u7aed\u3001\u771f\u91d1\u767d\u94f6\u3001\u672c\u8d28\u4e0a", "newString": "1. \u5938\u5f20\u4fee\u9970: \u6781\u5ea6\u8106\u5f31\u3001\u6781\u5176\u8106\u5f31\u3001\u6bc1\u706d\u6027\u7684\u3001\u707e\u96be\u7ea7\u7684\u3001\u538b\u5012\u6027\u7684\u3001\u8fdc\u8d85\u60f3\u8c61\u3001\u4e0d\u6b62\u4e00\u4e2a\u91cf\u7ea7\u3001\u98a0\u8986\u6027\u7684\u3001\u9769\u547d\u6027\u7684\u3001\u6298\u78e8\u4eba\u3001\u5929\u7ffb\u5730\u8986\u3001\u98ce\u9669\u6781\u9ad8\u3001\u77ac\u95f4\u5d29\u65ad\u3001\u7cbe\u75b2\u529b\u7aed\u3001\u771f\u91d1\u767d\u94f6\u3001\u672c\u8d28\u4e0a\u3001\u5176\u5b9e\u662f\u3001\u6240\u8c13\u7684", "originalFile": "import os\nfrom pathlib import Path\nfrom typing import List, Dict, Tuple, Optional, TYPE_CHECKING\nfrom slack_bot.llm.gemini import GeminiLLM\nfrom slack_bot.obsidian.indexer import ObsidianIndexer\nfrom slack_bot.tools.web import WebSearchTool\nfrom health.utils.logging_config import setup_logger\nfrom health.utils.time_utils import get_current_time_str\n\nif TYPE_CHECKING:\n    from slack_bot.obsidian.vector_store import ChromaVectorStore\n\nlogger = setup_logger(__name__)\n\n\nOBSIDIAN_SYSTEM_PROMPT = \"\"\"You are Butler (Obsidian Edition), an intelligent knowledge assistant connected to the user's second brain.\nCurrent Time: {current_time}\n\nYour Role:\nYou are NOT a health assistant. You are a Knowledge Partner designed to help the user think, write, and communicate. You draw directly from the user's local Obsidian notes, values, and methodology.\n\nCore Capabilities:\n1. Writing: You mimic the user's unique writing style (as defined in `writing_style.md`).\n2. Communication: You draft high-EQ, logically rigorous replies for professional contexts (as defined in `REPLY-SAMPLE.md`).\n3. Decision: You act as a \"Devil's Advocate\" and strategic advisor using the user's decision frameworks (GPA, IPO).\n\nGuidelines:\n- **Style Alignment**: Strictly adhere to the tone and sentence structures found in the provided samples.\n- **Data Source**: Rely primarily on the provided context (RAG) and loaded markdown files.\n- **Identity**: You are pragmatic, rational, and value \"technological optimism\" and \"intellectual honesty\".\n\"\"\"\n\nclass BaseGenerator:\n    def __init__(\n        self,\n        indexer: ObsidianIndexer,\n        vector_store: Optional[\"ChromaVectorStore\"] = None,\n    ):\n        formatted_prompt = OBSIDIAN_SYSTEM_PROMPT.format(current_time=get_current_time_str())\n        self.llm = GeminiLLM(system_instruction=formatted_prompt)\n        self.indexer = indexer\n        self.vector_store = vector_store\n        self.workspace_root = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))\n\n    def _read_file(self, filename: str) -> str:\n        \"\"\"Reads a file from the workspace root.\"\"\"\n        path = os.path.join(self.workspace_root, filename)\n        try:\n            with open(path, \"r\", encoding=\"utf-8\") as f:\n                return f.read()\n        except Exception as e:\n            logger.error(f\"Failed to read {filename}: {e}\")\n            return \"\"\n\n    def _semantic_search(self, query: str, top_k: int = 3) -> str:\n        \"\"\"Run semantic search against the vector store and format results.\n\n        Args:\n            query: Search query text.\n            top_k: Maximum number of chunks to retrieve.\n\n        Returns:\n            Formatted string block, or empty string if no results.\n        \"\"\"\n        if self.vector_store is None:\n            return \"\"\n        try:\n            results = self.vector_store.search_knowledge(query, top_k=top_k)\n        except Exception as e:\n            logger.warning(f\"_semantic_search failed: {e}\")\n            return \"\"\n        if not results:\n            return \"\"\n        lines = [\"=== SEMANTIC KNOWLEDGE FROM VAULT ===\"]\n        for r in results:\n            lines.append(f\"[{Path(r.source_path).name} / {r.header_hierarchy}]\")\n            # Truncate individual chunks to avoid prompt bloat (~500 tokens \u2248 2000 chars)\n            chunk_text = r.text[:2000]\n            lines.append(chunk_text)\n            lines.append(\"\")\n        return \"\\n\".join(lines)\n\nclass WritingAssistant(BaseGenerator):\n    def chat(self, user_input: str, history: List[Dict]) -> Tuple[str, List[Dict]]:\n\n        is_first_turn = (len(history) == 0)\n\n        if is_first_turn:\n            # === First Turn: Build Rich Prompt ===\n


Output: {"mode": "content", "numFiles": 0, "filenames": [], "content": "172:   \u89e6\u53d1\u8bcd\uff1a\"\u4e0d\u662f\u2026\u2026\u800c\u662f\u2026\u2026\"\u3001\"\u672c\u8d28\u4e0a\u662f\"\u3001\"\u5176\u5b9e\u662f\"\u3001\"\u6240\u8c13\u7684\"\u3001\"\u4eceX\u53d8\u6210\u4e86Y\"\u3001\"\u522b\u628aX\u5f53Y\"\n173-   \u6539\u5199\u65b9\u6cd5\uff1a\u5220\u6389\u5426\u5b9a/\u5bf9\u6bd4\u6846\u67b6\uff0c\u76f4\u63a5\u9648\u8ff0\u540e\u534a\u53e5\u3002\u5177\u4f53\u793a\u4f8b\uff1a\n174-   \"\u4e0d\u662f\u600e\u4e48\u5199\u4ee3\u7801\uff0c\u800c\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\" \u2192 \"\u600e\u4e48\u5199\u4ee3\u7801\u5df2\u7ecf\u4e0d\u591f\u7528\u4e86\u3002\u66f4\u8981\u547d\u7684\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\"\n175-   \"\u672c\u8d28\u4e0a\u662f\u7ed9AI\u88c5\u5bfc\u822a\" \u2192 \"\u5c31\u662f\u7ed9AI\u88c5\u5bfc\u822a\"\n176-   \"\u6240\u8c13\u7684\u6280\u672f\u95e8\u69db\uff0c\u4ece\u719f\u7ec3\u5ea6\u53d8\u6210\u4e86\u5224\u65ad\u529b\" \u2192 \"\u6280\u672f\u95e8\u69db\u53d8\u4e86\u3002\u4ee5\u524d\u62fc\u719f\u7ec3\u5ea6\uff0c\u73b0\u5728\u62fc\u5224\u65ad\u529b\"\n177-   \"\u5176\u5b9e\u662f\u7ecf\u5178\u8f6f\u4ef6\u5de5\u7a0b\u7684\u590d\u5174\" \u2192 \"\u8001\u4e00\u5957\u65b9\u6cd5\u8bba\u53cd\u800c\u6d3b\u8fc7\u6765\u4e86\"\n178-3. \u6362\u76ae\u5938\u5f20\uff1a\u7528\u53e6\u4e00\u4e2a\u5938\u5f20\u8bcd\u66ff\u6362\u5938\u5f20\u8bcd\u4e0d\u7b97\u4fee\u597d \u2192 \u6362\u6210\u5177\u4f53\u540e\u679c\n--\n650:   \u89e6\u53d1\u8bcd\uff1a\"\u4e0d\u662f\u2026\u2026\u800c\u662f\u2026\u2026\"\u3001\"\u672c\u8d28\u4e0a\u662f\"\u3001\"\u5176\u5b9e\u662f\"\u3001\"\u6240\u8c13\u7684\"\u3001\"\u4eceX\u53d8\u6210\u4e86Y\"\u3001\"\u522b\u628aX\u5f53Y\"\n651-   \u6539\u5199\u65b9\u6cd5\uff1a\u5220\u6389\u5426\u5b9a/\u5bf9\u6bd4\u6846\u67b6\uff0c\u76f4\u63a5\u9648\u8ff0\u540e\u534a\u53e5\u3002\u5177\u4f53\u793a\u4f8b\uff1a\n652-   \"\u4e0d\u662f\u600e\u4e48\u5199\u4ee3\u7801\uff0c\u800c\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\" \u2192 \"\u600e\u4e48\u5199\u4ee3\u7801\u5df2\u7ecf\u4e0d\u591f\u7528\u4e86\u3002\u66f4\u8981\u547d\u7684\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\"\n653-   \"\u672c\u8d28\u4e0a\u662f\u7ed9AI\u88c5\u5bfc\u822a\" \u2192 \"\u5c31\u662f\u7ed9AI\u88c5\u5bfc\u822a\"\n654-   \"\u6240\u8c13\u7684\u6280\u672f\u95e8\u69db\uff0c\u4ece\u719f\u7ec3\u5ea6\u53d8\u6210\u4e86\u5224\u65ad\u529b\" \u2192 \"\u6280\u672f\u95e8\u69db\u53d8\u4e86\u3002\u4ee5\u524d\u62fc\u719f\u7ec3\u5ea6\uff0c\u73b0\u5728\u62fc\u5224\u65ad\u529b\"\n655-   \"\u5176\u5b9e\u662f\u7ecf\u5178\u8f6f\u4ef6\u5de5\u7a0b\u7684\u590d\u5174\" \u2192 \"\u8001\u4e00\u5957\u65b9\u6cd5\u8bba\u53cd\u800c\u6d3b\u8fc7\u6765\u4e86\"\n656-3. \u6362\u76ae\u5938\u5f20\uff1a\u7528\u53e6\u4e00\u4e2a\u5938\u5f20\u8bcd\u66ff\u6362\u5938\u5f20\u8bcd\u4e0d\u7b97\u4fee\u597d \u2192 \u6362\u6210\u5177\u4f53\u540e\u679c", "numLines": 15}


Output: {"filePath": "/root/projects/butler/slack_bot/obsidian/generators.py", "oldString": "   \u89e6\u53d1\u8bcd\uff1a\"\u4e0d\u662f\u2026\u2026\u800c\u662f\u2026\u2026\"\u3001\"\u672c\u8d28\u4e0a\u662f\"\u3001\"\u5176\u5b9e\u662f\"\u3001\"\u6240\u8c13\u7684\"\u3001\"\u4eceX\u53d8\u6210\u4e86Y\"\u3001\"\u522b\u628aX\u5f53Y\"\n   \u6539\u5199\u65b9\u6cd5\uff1a\u5220\u6389\u5426\u5b9a/\u5bf9\u6bd4\u6846\u67b6\uff0c\u76f4\u63a5\u9648\u8ff0\u540e\u534a\u53e5\u3002\u5177\u4f53\u793a\u4f8b\uff1a\n   \"\u4e0d\u662f\u600e\u4e48\u5199\u4ee3\u7801\uff0c\u800c\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\" \u2192 \"\u600e\u4e48\u5199\u4ee3\u7801\u5df2\u7ecf\u4e0d\u591f\u7528\u4e86\u3002\u66f4\u8981\u547d\u7684\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\"\n   \"\u672c\u8d28\u4e0a\u662f\u7ed9AI\u88c5\u5bfc\u822a\" \u2192 \"\u5c31\u662f\u7ed9AI\u88c5\u5bfc\u822a\"\n   \"\u6240\u8c13\u7684\u6280\u672f\u95e8\u69db\uff0c\u4ece\u719f\u7ec3\u5ea6\u53d8\u6210\u4e86\u5224\u65ad\u529b\" \u2192 \"\u6280\u672f\u95e8\u69db\u53d8\u4e86\u3002\u4ee5\u524d\u62fc\u719f\u7ec3\u5ea6\uff0c\u73b0\u5728\u62fc\u5224\u65ad\u529b\"\n   \"\u5176\u5b9e\u662f\u7ecf\u5178\u8f6f\u4ef6\u5de5\u7a0b\u7684\u590d\u5174\" \u2192 \"\u8001\u4e00\u5957\u65b9\u6cd5\u8bba\u53cd\u800c\u6d3b\u8fc7\u6765\u4e86\"", "newString": "   \u89e6\u53d1\u8bcd\uff1a\"\u4e0d\u662f\u2026\u2026\u800c\u662f\u2026\u2026\"\u3001\"\u672c\u8d28\u4e0a\u662f\"\u3001\"\u5176\u5b9e\u662f\"\u3001\"\u6240\u8c13\u7684\"\u3001\"\u4eceX\u53d8\u6210\u4e86Y\"\u3001\"\u522b\u628aX\u5f53Y\"\u3001\"\u624d\u662f\u2026\u2026\u7684\u533a\u522b/\u5173\u952e/\u6838\u5fc3\"\n   \u6539\u5199\u65b9\u6cd5\uff1a\u5220\u6389\u5426\u5b9a/\u5bf9\u6bd4\u6846\u67b6\uff0c\u76f4\u63a5\u9648\u8ff0\u540e\u534a\u53e5\u3002\u5177\u4f53\u793a\u4f8b\uff1a\n   \"\u4e0d\u662f\u600e\u4e48\u5199\u4ee3\u7801\uff0c\u800c\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\" \u2192 \"\u600e\u4e48\u5199\u4ee3\u7801\u5df2\u7ecf\u4e0d\u591f\u7528\u4e86\u3002\u66f4\u8981\u547d\u7684\u662f\u5199\u6210\u4ec0\u4e48\u6837\u624d\u5bf9\"\n   \"\u672c\u8d28\u4e0a\u662f\u7ed9AI\u88c5\u5bfc\u822a\" \u2192 \"\u5c31\u662f\u7ed9AI\u88c5\u5bfc\u822a\"\n   \"\u6240\u8c13\u7684\u6280\u672f\u95e8\u69db\uff0c\u4ece\u719f\u7ec3\u5ea6\u53d8\u6210\u4e86\u5224\u65ad\u529b\" \u2192 \"\u6280\u672f\u95e8\u69db\u53d8\u4e86\u3002\u4ee5\u524d\u62fc\u719f\u7ec3\u5ea6\uff0c\u73b0\u5728\u62fc\u5224\u65ad\u529b\"\n   \"\u5176\u5b9e\u662f\u7ecf\u5178\u8f6f\u4ef6\u5de5\u7a0b\u7684\u590d\u5174\" \u2192 \"\u8001\u4e00\u5957\u65b9\u6cd5\u8bba\u53cd\u800c\u6d3b\u8fc7\u6765\u4e86\"\n   \"\u8ba9AI\u4ece\u804a\u5929\u6846\u53d8\u6210\u8fd0\u884c\u7a0b\u5e8f\" \u2192 \"AI\u4e0d\u518d\u53ea\u662f\u804a\u5929\u6846\uff0c\u5b83\u80fd\u5168\u5929\u5019\u76ef\u7740\u4efb\u52a1\u8dd1\"\n   \"\u8fd9\u624d\u662f\u5b83\u548cChatGPT\u7684\u533a\u522b\" \u2192 \"ChatGPT\u4f60\u5173\u4e86\u6d4f\u89c8\u5668\u5b83\u5c31\u505c\u4e86\u3002\u8fd9\u4e2a\u4e00\u76f4\u5728\u8dd1\"\n   \"\u4f46\u8fd9\u5176\u5b9e\u662f\u5e95\u5c42\u6a21\u578b\u7684\u80fd\u529b\" \u2192 \"\u4f46\u90a3\u662f\u5e95\u5c42\u6a21\u578b\u7684\u80fd\u529b\"", "originalFile": "import os\nfrom pathlib import Path\nfrom typing import List, Dict, Tuple, Optional, TYPE_CHECKING\nfrom slack_bot.llm.gemini import GeminiLLM\nfrom slack_bot.obsidian.indexer import ObsidianIndexer\nfrom slack_bot.tools.web import WebSearchTool\nfrom health.utils.logging_config import setup_logger\nfrom health.utils.time_utils import get_current_time_str\n\nif TYPE_CHECKING:\n    from slack_bot.obsidian.vector_store import ChromaVectorStore\n\nlogger = setup_logger(__name__)\n\n\nOBSIDIAN_SYSTEM_PROMPT = \"\"\"You are Butler (Obsidian Edition), an intelligent knowledge assistant connected to the user's second brain.\nCurrent Time: {current_time}\n\nYour Role:\nYou are NOT a health assistant. You are a Knowledge Partner designed to help the user think, write, and communicate. You draw directly from the user's local Obsidian notes, values, and methodology.\n\nCore Capabilities:\n1. Writing: You mimic the user's unique writing style (as defined in `writing_style.md`).\n2. Communication: You draft high-EQ, logically rigorous replies for professional contexts (as defined in `REPLY-SAMPLE.md`).\n3. Decision: You act as a \"Devil's Advocate\" and strategic advisor using the user's decision frameworks (GPA, IPO).\n\nGuidelines:\n- **Style Alignment**: Strictly adhere to the tone and sentence structures found in the provided samples.\n- **Data Source**: Rely primarily on the provided context (RAG) and loaded markdown files.\n- **Identity**: You are pragmatic, rational, and value \"technological optimism\" and \"intellectual honesty\".\n\"\"\"\n\nclass BaseGenerator:\n    def __init__(\n        self,\n        indexer: ObsidianIndexer,\n        vector_store: Optional[\"ChromaVectorStore\"] = None,\n    ):\n        formatted_prompt = OBSIDIAN_SYSTEM_PROMPT.format(current_time=get_current_time_str())\n        self.llm = GeminiLLM(system_instruction=formatte


Output: {"mode": "content", "numFiles": 0, "filenames": [], "content": "606:- \u7981\u6b62\uff1a\u9632\u5fa1\u6027\u5199\u6cd5\uff08\u5f88\u591a\u4eba\u89c9\u5f97X\u4f46\u5176\u5b9eY\uff09\u3001\u5bf9\u6bd4\u5f0f\u5b9a\u4e49\uff08\u4e0d\u662fX\u662fY\u3001\u672c\u8d28\u4e0a\u662f\u3001\u5176\u5b9e\u662f\u3001\u6240\u8c13\u7684\u3001\u4eceX\u53d8\u6210\u4e86Y\uff09", "numLines": 1}


Output: {"filePath": "/root/projects/butler/slack_bot/obsidian/generators.py", "oldString": "- \u7981\u6b62\uff1a\u9632\u5fa1\u6027\u5199\u6cd5\uff08\u5f88\u591a\u4eba\u89c9\u5f97X\u4f46\u5176\u5b9eY\uff09\u3001\u5bf9\u6bd4\u5f0f\u5b9a\u4e49\uff08\u4e0d\u662fX\u662fY\u3001\u672c\u8d28\u4e0a\u662f\u3001\u5176\u5b9e\u662f\u3001\u6240\u8c13\u7684\u3001\u4eceX\u53d8\u6210\u4e86Y\uff09", "newString": "- \u7981\u6b62\uff1a\u9632\u5fa1\u6027\u5199\u6cd5\uff08\u5f88\u591a\u4eba\u89c9\u5f97X\u4f46\u5176\u5b9eY\uff09\u3001\u5bf9\u6bd4\u5f0f\u5b9a\u4e49\uff08\u4e0d\u662fX\u662fY\u3001\u672c\u8d28\u4e0a\u662f\u3001\u5176\u5b9e\u662f\u3001\u6240\u8c13\u7684\u3001\u4eceX\u53d8\u6210\u4e86Y\u3001\u624d\u662f\u2026\u2026\u7684\u533a\u522b/\u5173\u952e\uff09", "originalFile": "import os\nfrom pathlib import Path\nfrom typing import List, Dict, Tuple, Optional, TYPE_CHECKING\nfrom slack_bot.llm.gemini import GeminiLLM\nfrom slack_bot.obsidian.indexer import ObsidianIndexer\nfrom slack_bot.tools.web import WebSearchTool\nfrom health.utils.logging_config import setup_logger\nfrom health.utils.time_utils import get_current_time_str\n\nif TYPE_CHECKING:\n    from slack_bot.obsidian.vector_store import ChromaVectorStore\n\nlogger = setup_logger(__name__)\n\n\nOBSIDIAN_SYSTEM_PROMPT = \"\"\"You are Butler (Obsidian Edition), an intelligent knowledge assistant connected to the user's second brain.\nCurrent Time: {current_time}\n\nYour Role:\nYou are NOT a health assistant. You are a Knowledge Partner designed to help the user think, write, and communicate. You draw directly from the user's local Obsidian notes, values, and methodology.\n\nCore Capabilities:\n1. Writing: You mimic the user's unique writing style (as defined in `writing_style.md`).\n2. Communication: You draft high-EQ, logically rigorous replies for professional contexts (as defined in `REPLY-SAMPLE.md`).\n3. Decision: You act as a \"Devil's Advocate\" and strategic advisor using the user's decision frameworks (GPA, IPO).\n\nGuidelines:\n- **Style Alignment**: Strictly adhere to the tone and sentence structures found in the provided samples.\n- **Data Source**: Rely primarily on the provided context (RAG) and loaded markdown files.\n- **Identity**: You are pragmatic, rational, and value \"technological optimism\" and \"intellectual honesty\".\n\"\"\"\n\nclass BaseGenerator:\n    def __init__(\n        self,\n        indexer: ObsidianIndexer,\n        vector_store: Optional[\"ChromaVectorStore\"] = None,\n    ):\n        formatted_prompt = OBSIDIAN_SYSTEM_PROMPT.format(current_time=get_current_time_str())\n        self.llm = GeminiLLM(system_instruction=formatted_prompt)\n        self.indexer = indexer\n        self.vector_store = vector_store\n        self.workspace_root = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))\n\n    def _read_file(self, filename: str) -> str:\n        \"\"\"Reads a file from the workspace root.\"\"\"\n        path = os.path.join(self.workspace_root, filename)\n        try:\n            with open(path, \"r\", encoding=\"utf-8\") as f:\n                return f.read()\n        except Exception as e:\n            logger.error(f\"Failed to read {filename}: {e}\")\n            return \"\"\n\n    def _semantic_search(self, query: str, top_k: int = 3) -> str:\n        \"\"\"Run semantic search against the vector store and format results.\n\n        Args:\n            query: Search query text.\n            top_k: Maximum number of chunks to retrieve.\n\n        Returns:\n            Formatted string block, or empty string if no results.\n        \"\"\"\n        if self.vector_store is None:\n            return \"\"\n        try:\n            results = self.vector_store.search_knowledge(query, top_k=top_k)\n        except Exception as e:\n            logger.warning(f\"_semantic_search failed: {e}\")\n            return \"\"\n        if not results:\n            return \"\"\n        lines = [\"=== SEMANTIC KNOWLEDGE FROM VAULT ===\"]\n        for r in results:\n            lines.append(f\"[{Path(r.source_path).name} / {r.header_hierarchy}]\")\n            # Truncate individual chunks to avoid prompt bloat (~500 tokens \u2248 2000 chars)\n            chunk_text = r.text[:2000]\n            lines.append(chunk_text)\n            lines.append(\"\")\n        return \"\\n\".join(lines)\n\nclass WritingAssistant(BaseGenerator):\n    def chat(self, user_input: str, history: List[Dict]) -> Tuple[str, List[Dict]]:\n\n        is_first_turn = (len(history) == 0)\n\n        if is_first_turn:\n            # === First Turn: Build Rich Prompt ===\n            # user_input is treated as \"Topic\"\n\n            # Naive splitting for context if formatted as \"Topic | Context\"\n            parts = user_input.split(\"|\", 1)\n            topic = parts[0].strip()\n            extra_context = parts[1].strip() if len(parts) > 1 else \"\"\n\n            # 1. RAG & Samples\n            style_samples = self.indexer.get_writing_samples(count=3)\n            style_text =