diff --git a/SKILL.md b/SKILL.md index d8fa371..a86b471 100644 --- a/SKILL.md +++ b/SKILL.md @@ -70,6 +70,8 @@ python3 ${CLAUDE_SKILL_DIR}/tools/sutra_collector.py --name "<法师名>" --trad ### Step 3：分析与生成 +**运行时检索规则**：加载 `${CLAUDE_SKILL_DIR}/prompts/rag_instructions.md`，将其中的检索指引嵌入生成的每个法师 SKILL.md 的运行规则中，确保法师回答时调用 FoJin 实时检索而非仅依赖 LLM 自身知识。 + **教义分析**：加载 `${CLAUDE_SKILL_DIR}/prompts/sutra_analyzer.md`，填入采集数据，分析教义结构。 **风格分析**：加载 `${CLAUDE_SKILL_DIR}/prompts/voice_analyzer.md`，填入采集数据，分析说法风格。 @@ -118,6 +120,7 @@ teachers/{slug}/ | 任务 | 工具 | |------|------| | FoJin 数据查询 | `${CLAUDE_SKILL_DIR}/tools/fojin_bridge.py` | +| FoJin 实时检索 | `${CLAUDE_SKILL_DIR}/tools/rag_query.py` | | 经文采集 | `${CLAUDE_SKILL_DIR}/tools/sutra_collector.py` | | 角色生成 | `${CLAUDE_SKILL_DIR}/tools/teacher_builder.py` | | 文件写入 | `${CLAUDE_SKILL_DIR}/tools/skill_writer.py` | diff --git a/prompts/rag_instructions.md b/prompts/rag_instructions.md new file mode 100644 index 0000000..728387d --- /dev/null +++ b/prompts/rag_instructions.md @@ -0,0 +1,38 @@ +# FoJin 实时检索指引 + +在回答用户问题时，你应当调用 FoJin 数据桥检索真实经文，而非仅依赖自身知识。 + +## 检索流程 + +### Step 1：语义检索 +对用户的问题进行语义搜索，获取最相关的经文段落： +```bash +python3 ${CLAUDE_SKILL_DIR}/tools/rag_query.py semantic "<用户问题关键词>" --top_k 5 +``` + +### Step 2：术语查询 +如果问题涉及佛学专业术语，查询 FoJin 词典获取精确定义： +```bash +python3 ${CLAUDE_SKILL_DIR}/tools/rag_query.py dict "<术语>" +``` + +### Step 3：关键词补充检索（可选） +如果语义检索结果不够精确，可用关键词搜索补充： +```bash +python3 ${CLAUDE_SKILL_DIR}/tools/rag_query.py search "<关键词>" --sources cbeta --top_k 5 +``` + +### Step 4：知识图谱（可选） +如果问题涉及人物、传承、宗派关系： +```bash +python3 ${CLAUDE_SKILL_DIR}/tools/rag_query.py kg "<人物名>" --type person +``` + +## 整合规则 + +1. 检索到的经文段落应作为回答的依据，优先于自身知识 +2. 引用格式必须使用检索结果中返回的真实 FoJin 链接 +3. 如果检索结果与该法师的传承不直接相关，可以忽略 +4. 如果检索无结果，坦诚说明并基于 teaching.md 中的已有内容回答 +5. 每次回答至少引用 1-2 段检索到的真实经文 +6. 引用经文时标注出处，格式示例：《大般若经》卷一（[FoJin链接](https://fojin.app/texts/123)） diff --git a/tools/rag_query.py b/tools/rag_query.py new file mode 100644 index 0000000..0ca9507 --- /dev/null +++ b/tools/rag_query.py @@ -0,0 +1,227 @@ +#!/usr/bin/env python3 +""" +RAG Query — runtime FoJin retrieval for teacher skills. + +Usage: + python3 tools/rag_query.py search "如何念佛" --sources cbeta --top_k 5 + python3 tools/rag_query.py semantic "什么是空性" --top_k 5 + python3 tools/rag_query.py dict "般若" + python3 tools/rag_query.py kg "印光" --type person +""" + +import argparse +import sys +import os + +# Ensure tools/ is on the path so we can import fojin_bridge +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) + +from fojin_bridge import create_bridge + + +def format_search_results(data: dict) -> str: + """Format keyword search results for LLM consumption.""" + items = data.get("items") or data.get("results") or [] + if not items: + return "未找到相关结果。" + + lines = [] + for i, item in enumerate(items, 1): + title = item.get("title", "无标题") + source = item.get("source", item.get("collection", "")) + score = item.get("score", item.get("relevance", "")) + snippet = item.get("highlight", item.get("snippet", item.get("content", ""))) + text_id = item.get("text_id", item.get("id", "")) + + lines.append(f"── 结果 {i} ──") + lines.append(f"标题: {title}") + if source: + lines.append(f"来源: {source}") + if score: + lines.append(f"相关度: {score}") + if text_id: + lines.append(f"FoJin链接: https://fojin.app/texts/{text_id}") + if snippet: + # Truncate long snippets + snippet_str = str(snippet) + if len(snippet_str) > 500: + snippet_str = snippet_str[:500] + "..." + lines.append(f"摘要: {snippet_str}") + lines.append("") + + total = data.get("total", len(items)) + lines.insert(0, f"共找到 {total} 条结果，显示前 {len(items)} 条：\n") + return "\n".join(lines) + + +def format_semantic_results(data: dict) -> str: + """Format semantic search results for LLM consumption.""" + items = data.get("items") or data.get("results") or [] + if not items: + return "语义检索未找到相关经文。" + + lines = [f"语义检索返回 {len(items)} 条相关经文：\n"] + for i, item in enumerate(items, 1): + title = item.get("title", "无标题") + source = item.get("source", item.get("collection", "")) + score = item.get("score", item.get("similarity", "")) + content = item.get("content", item.get("snippet", item.get("text", ""))) + text_id = item.get("text_id", item.get("id", "")) + juan = item.get("juan_num", item.get("juan", "")) + + lines.append(f"── 经文 {i} ──") + lines.append(f"标题: {title}") + if source: + lines.append(f"来源: {source}") + if score: + lines.append(f"相似度: {score}") + if text_id: + link = f"https://fojin.app/texts/{text_id}" + if juan: + link += f"/juan/{juan}" + lines.append(f"FoJin链接: {link}") + if content: + content_str = str(content) + if len(content_str) > 500: + content_str = content_str[:500] + "..." + lines.append(f"经文内容: {content_str}") + lines.append("") + + return "\n".join(lines) + + +def format_dict_results(data: dict) -> str: + """Format dictionary search results for LLM consumption.""" + items = data.get("items") or data.get("results") or [] + if not items: + return "词典中未找到该术语。" + + lines = [f"词典检索返回 {len(items)} 条释义：\n"] + for i, item in enumerate(items, 1): + headword = item.get("headword", item.get("term", item.get("word", ""))) + definition = item.get("definition", item.get("content", item.get("meaning", ""))) + source_dict = item.get("source", item.get("dictionary", item.get("dict_name", ""))) + + lines.append(f"── 释义 {i} ──") + if headword: + lines.append(f"词条: {headword}") + if source_dict: + lines.append(f"出处词典: {source_dict}") + if definition: + def_str = str(definition) + if len(def_str) > 800: + def_str = def_str[:800] + "..." + lines.append(f"释义: {def_str}") + lines.append("") + + return "\n".join(lines) + + +def format_kg_results(data: dict) -> str: + """Format knowledge graph entity results for LLM consumption.""" + items = data.get("items") or data.get("results") or data.get("entities") or [] + if not items: + return "知识图谱中未找到相关实体。" + + lines = [f"知识图谱检索返回 {len(items)} 个实体：\n"] + for i, item in enumerate(items, 1): + name = item.get("name", item.get("label", "")) + etype = item.get("entity_type", item.get("type", "")) + desc = item.get("description", item.get("summary", "")) + relations = item.get("relations", item.get("edges", [])) + entity_id = item.get("id", item.get("entity_id", "")) + + lines.append(f"── 实体 {i} ──") + if name: + lines.append(f"名称: {name}") + if etype: + lines.append(f"类型: {etype}") + if entity_id: + lines.append(f"FoJin链接: https://fojin.app/kg/entities/{entity_id}") + if desc: + desc_str = str(desc) + if len(desc_str) > 500: + desc_str = desc_str[:500] + "..." + lines.append(f"描述: {desc_str}") + if relations: + lines.append("关系:") + for rel in relations[:10]: + predicate = rel.get("predicate", rel.get("relation", "")) + target = rel.get("target", rel.get("object", rel.get("name", ""))) + if predicate and target: + lines.append(f" - {predicate} → {target}") + lines.append("") + + return "\n".join(lines) + + +def cmd_search(args): + bridge = create_bridge() + result = bridge.search_texts(args.query, sources=args.sources, size=args.top_k) + print(format_search_results(result)) + + +def cmd_semantic(args): + bridge = create_bridge() + result = bridge.semantic_search(args.query, top_k=args.top_k) + print(format_semantic_results(result)) + + +def cmd_dict(args): + bridge = create_bridge() + result = bridge.search_dictionary(args.query) + print(format_dict_results(result)) + + +def cmd_kg(args): + bridge = create_bridge() + result = bridge.search_kg_entities(args.query, entity_type=args.type) + print(format_kg_results(result)) + + +def main(): + parser = argparse.ArgumentParser( + description="RAG Query — FoJin 佛教文献实时检索工具", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=__doc__, + ) + subparsers = parser.add_subparsers(dest="command", required=True) + + # search + p_search = subparsers.add_parser("search", help="关键词搜索经文") + p_search.add_argument("query", help="搜索关键词") + p_search.add_argument("--sources", default=None, help="限定来源，如 cbeta") + p_search.add_argument("--top_k", type=int, default=5, help="返回条数 (默认 5)") + p_search.set_defaults(func=cmd_search) + + # semantic + p_sem = subparsers.add_parser("semantic", help="语义向量检索") + p_sem.add_argument("query", help="语义查询") + p_sem.add_argument("--top_k", type=int, default=5, help="返回条数 (默认 5)") + p_sem.set_defaults(func=cmd_semantic) + + # dict + p_dict = subparsers.add_parser("dict", help="佛学词典查询") + p_dict.add_argument("query", help="查询术语") + p_dict.set_defaults(func=cmd_dict) + + # kg + p_kg = subparsers.add_parser("kg", help="知识图谱实体搜索") + p_kg.add_argument("query", help="实体名称") + p_kg.add_argument("--type", default=None, help="实体类型，如 person, text, school") + p_kg.set_defaults(func=cmd_kg) + + args = parser.parse_args() + + try: + args.func(args) + except ConnectionError as e: + print(f"[错误] 无法连接 FoJin API: {e}", file=sys.stderr) + sys.exit(1) + except Exception as e: + print(f"[错误] 检索失败: {e}", file=sys.stderr) + sys.exit(1) + + +if __name__ == "__main__": + main()