from src.models.embedding import Reranker from src.utils.logging_config import setup_logger logger = setup_logger("server-common") class Retriever: def __init__(self, config, dbm, model): self.config = config self.dbm = dbm self.model = model if self.config.enable_reranker: self.reranker = Reranker(config) def retrieval(self, query, history, meta): refs = {"query": query, "history": history, "meta": meta} refs["model_name"] = self.config.model_name refs["entities"] = self.reco_entities(query, history, refs) refs["knowledge_base"] = self.query_knowledgebase(query, history, refs) refs["graph_base"] = self.query_graph(query, history, refs) return refs def construct_query(self, query, refs, meta): if not refs or len(refs) == 0: return query external_parts = [] # 解析知识库的结果 kb_res = refs.get("knowledge_base", {}).get("results", []) if kb_res: kb_text = "\n".join(f"{r['id']}: {r['entity']['text']}" for r in kb_res) external_parts.extend(["知识库信息:", kb_text]) # 解析图数据库的结果 db_res = refs.get("graph_base", {}).get("results", {}) if db_res.get("nodes") and len(db_res["nodes"]) > 0: db_text = "\n".join( [f"{edge['source_name']}和{edge['target_name']}的关系是{edge['type']}" for edge in db_res.get("edges", [])] ) external_parts.extend(["图数据库信息:", db_text]) # 构造查询 from src.utils.prompts import knowbase_qa_template if external_parts and len(external_parts) > 0: external = "\n\n".join(external_parts) query = knowbase_qa_template.format(external=external, query=query) return query def query_classification(self, query): """判断是否需要查询 - 对于完全基于用户给定信息的任务，称之为“足够”“sufficient”，不需要检索； - 否则，称之为“不足”“insufficient”，可能需要检索， """ raise NotImplementedError def query_graph(self, query, history, refs): # res = model.predict("qiansdgsa, dasdh ashdsakjdk ak ").content results = [] if refs["meta"].get("use_graph") and self.config.enable_knowledge_base: for entity in refs["entities"]: result = self.dbm.graph_base.query_by_vector(entity) if result != []: results.extend(result) return {"results": self.format_query_results(results)} def query_knowledgebase(self, query, history, refs): """查询知识库""" kb_res = [] final_res = [] db_name = refs["meta"].get("db_name") if not db_name or not self.config.enable_knowledge_base: return { "results": final_res, "all_results": kb_res, "rw_query": query, "message": "Knowledge base is disabled", } rw_query = self.rewrite_query(query, history, refs) kb = self.dbm.metaname2db[db_name] logger.debug(f"{refs['meta']=}") meta = refs["meta"] max_query_count = meta.get("maxQueryCount", 10) rerank_threshold = meta.get("rerankThreshold", 0.1) distance_threshold = meta.get("distanceThreshold", 0) top_k = meta.get("topK", 5) all_kb_res = self.dbm.knowledge_base.search(rw_query, db_name, limit=max_query_count) for r in all_kb_res: r["file"] = kb.id2file(r["entity"]["file_id"]) # use distance threshold to filter results if meta.get("mode") == "search": kb_res = all_kb_res else: kb_res = [r for r in all_kb_res if r["distance"] > distance_threshold] if self.config.enable_reranker: for r in kb_res: r["rerank_score"] = self.reranker.compute_score([rw_query, r["entity"]["text"]], normalize=True)[0] kb_res.sort(key=lambda x: x["rerank_score"], reverse=True) kb_res = [_res for _res in kb_res if _res["rerank_score"] > rerank_threshold] kb_res = kb_res[:top_k] return {"results": kb_res, "all_results": all_kb_res, "rw_query": rw_query} def rewrite_query(self, query, history, refs): """重写查询""" if refs["meta"].get("mode") == "search": # 如果是搜索模式，就使用 meta 的配置，否则就使用全局的配置 rewrite_query_span = refs["meta"].get("use_rewrite_query", "off") else: rewrite_query_span = refs["meta"]["config"].get("use_rewrite_query", "off") if rewrite_query_span == "off": rewritten_query = query else: from src.utils.prompts import rewritten_query_prompt_template history_query = [entry["content"] for entry in history if entry["role"] == "user"] if history else "" rewritten_query_prompt = rewritten_query_prompt_template.format(history=history_query, query=query) rewritten_query = self.model.predict(rewritten_query_prompt).content if rewrite_query_span == "hyde": hy_doc = self.model.predict(rewritten_query).content rewritten_query = f"{rewritten_query} {hy_doc}" return rewritten_query def reco_entities(self, query, history, refs): """识别句子中的实体""" query = refs.get("rewritten_query", query) entities = [] if refs["meta"].get("use_graph"): from src.utils.prompts import entity_extraction_prompt_template as entity_template from src.utils.prompts import keywords_prompt_template as entity_template entity_extraction_prompt = entity_template.format(text=query) entities = self.model.predict(entity_extraction_prompt).content.split("<->") # entities = [entity for entity in entities if all(char.isalnum() or char in "汉字" for char in entity)] return entities def _extract_relationship_info(self, relationship, source_name, target_name): """ 提取关系信息并返回格式化的节点和边信息 """ rel_id = relationship.element_id nodes = relationship.nodes if len(nodes) != 2: return None, None source, target = nodes source_id = source.element_id target_id = target.element_id relationship_type = relationship._properties.get("type", "unknown") if relationship_type == "unknown": relationship_type = relationship.type edge_info = { "id": rel_id, "type": relationship_type, "source_id": source_id, "target_id": target_id, "source_name": source_name, "target_name": target_name, } node_info = [ {"id": source_id, "name": source_name}, {"id": target_id, "name": target_name}, ] return node_info, edge_info def format_general_results(self, results): formatted_results = {"nodes": [], "edges": []} for item in results: relationship = item[1] source_name = item[0]._properties.get("name", "unknown") target_name = item[2]._properties.get("name", "unknown") if len(item) > 2 else "unknown" node_info, edge_info = self._extract_relationship_info(relationship, source_name, target_name) if node_info is None or edge_info is None: continue for node in node_info: if node["id"] not in [n["id"] for n in formatted_results["nodes"]]: formatted_results["nodes"].append(node) formatted_results["edges"].append(edge_info) return formatted_results def format_query_results(self, results): formatted_results = {"nodes": [], "edges": []} node_dict = {} for item in results: if not isinstance(item[1], list) or not item[1]: continue relationship = item[1][0] source_name = item[0] target_name = item[2] if len(item) > 2 else "unknown" node_info, edge_info = self._extract_relationship_info(relationship, source_name, target_name) if node_info is None or edge_info is None: continue node_dict.update({node["id"]: node for node in node_info}) formatted_results["edges"].append(edge_info) formatted_results["nodes"] = list(node_dict.values()) return formatted_results def __call__(self, query, history, meta): refs = self.retrieval(query, history, meta) query = self.construct_query(query, refs, meta) return query, refs