init: RAG 知识库服务初始提交

- 后端 API（Flask + Gunicorn）
- RAG 引擎（混合检索 + 云端 Reranker + 引用溯源）
- 文档解析（MinerU + 多格式支持）
- Docker 生产部署配置
- 排除前端项目、敏感配置、模型文件

core/agentic_context.py

@@ -0,0 +1,111 @@
+"""
+Agentic RAG - 上下文处理 Mixin
+
+包含上下文压缩、去重、Token 控制等方法
+"""
+
+import logging
+
+from .agentic_base import logger, MAX_CONTEXT_TOKENS, RERANK_THRESHOLD
+
+logger = logging.getLogger(__name__)
+
+
+class ContextMixin:
+    """上下文处理方法"""
+
+    def _compress_contexts(self, query: str, contexts: list) -> list:
+        """上下文压缩三步走：Rerank 过滤 → 去重 → Token 控制"""
+        if not contexts:
+            return contexts
+
+        # Step 1: Rerank 过滤
+        filtered = self._rerank_filter(contexts)
+
+        # Step 2: 去重
+        deduped = self._deduplicate_contexts(filtered)
+
+        # Step 3: Token 控制
+        result = self._truncate_to_tokens(deduped, self.MAX_CONTEXT_TOKENS)
+
+        return result
+
+    def _rerank_filter(self, contexts: list) -> list:
+        """Rerank 过滤 - 保留相关性分数 >= 阈值的上下文"""
+        scored_contexts = [c for c in contexts if c.get('score') is not None]
+
+        if scored_contexts:
+            filtered = [c for c in contexts if c.get('score', 0) >= self.RERANK_THRESHOLD]
+            return filtered if filtered else contexts
+
+        return contexts
+
+    def _deduplicate_contexts(self, contexts: list, threshold: float = 0.9) -> list:
+        """去重 - 基于内容相似度去重"""
+        if len(contexts) <= 1:
+            return contexts
+
+        result = []
+        seen_keys = set()
+
+        for c in contexts:
+            doc = c.get('doc', '')
+            key = doc[:100] if doc else ''
+
+            meta = c.get('meta', {})
+            source = meta.get('source', '')
+            page = meta.get('page', '')
+
+            composite_key = f"{source}|{page}|{key}"
+
+            if composite_key not in seen_keys:
+                seen_keys.add(composite_key)
+                result.append(c)
+
+        return result
+
+    def _truncate_to_tokens(self, contexts: list, max_tokens: int) -> list:
+        """Token 控制 - 截断到最大 Token 数"""
+        result = []
+        total_tokens = 0
+
+        for c in contexts:
+            doc = c.get('doc', '')
+            # 简单估算：1 token ≈ 1.5 中文字符
+            tokens = len(doc) // 1.5
+
+            if total_tokens + tokens <= max_tokens:
+                result.append(c)
+                total_tokens += tokens
+            else:
+                break
+
+        return result
+
+    def _merge_and_deduplicate(self, old_contexts: list, new_contexts: list) -> list:
+        """合并并去重两个上下文列表"""
+        result = list(old_contexts)
+        seen_keys = set()
+
+        # 记录已有上下文的 key
+        for c in old_contexts:
+            doc = c.get('doc', '')
+            key = doc[:100] if doc else ''
+            meta = c.get('meta', {})
+            source = meta.get('source', '')
+            composite_key = f"{source}|{key}"
+            seen_keys.add(composite_key)
+
+        # 添加新上下文（去重）
+        for c in new_contexts:
+            doc = c.get('doc', '')
+            key = doc[:100] if doc else ''
+            meta = c.get('meta', {})
+            source = meta.get('source', '')
+            composite_key = f"{source}|{key}"
+
+            if composite_key not in seen_keys:
+                seen_keys.add(composite_key)
+                result.append(c)
+
+        return result