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backend/app/rag/local_retriever.py

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+import json
+import re
+from pathlib import Path
+
+
+class LocalKnowledgeRetriever:
+    def __init__(self, kb_path: str):
+        self.kb_path = Path(kb_path)
+        self.documents = []
+        self._load()
+
+    @staticmethod
+    def _tokenize(text: str) -> set:
+        text = text or ""
+        words = set(re.findall(r"[A-Za-z0-9_]+", text.lower()))
+        cjk_chunks = re.findall(r"[\u4e00-\u9fff]+", text)
+        for chunk in cjk_chunks:
+            if len(chunk) <= 2:
+                words.add(chunk)
+            else:
+                for idx in range(len(chunk) - 1):
+                    words.add(chunk[idx : idx + 2])
+        return words
+
+    def _load(self):
+        if not self.kb_path.exists():
+            self.documents = []
+            return
+        with self.kb_path.open("r", encoding="utf-8-sig") as file:
+            rows = json.load(file)
+        self.documents = rows if isinstance(rows, list) else []
+
+    def reload(self):
+        self._load()
+
+    def search(self, query: str, top_k: int = 3) -> list:
+        query_tokens = self._tokenize(query)
+        if not query_tokens:
+            return []
+
+        scored = []
+        for item in self.documents:
+            content = f"{item.get('question', '')} {item.get('answer', '')} {' '.join(item.get('tags', []))}"
+            doc_tokens = self._tokenize(content)
+            if not doc_tokens:
+                continue
+            overlap = len(query_tokens & doc_tokens)
+            if overlap == 0:
+                continue
+            score = overlap / max(len(query_tokens), 1)
+            scored.append(
+                {
+                    "score": round(score, 4),
+                    "question": item.get("question", ""),
+                    "answer": item.get("answer", ""),
+                    "tags": item.get("tags", []),
+                    "source": item.get("source", "本地知识库"),
+                }
+            )
+
+        scored.sort(key=lambda x: x["score"], reverse=True)
+        return scored[:top_k]