import asyncio import mimetypes import os import re import secrets import string from abc import ABC, abstractmethod from typing import Any from yuxi.knowledge.chunking.ragflow_like.presets import ensure_chunk_defaults_in_additional_params from yuxi.knowledge.schemas import FindOutputSchema, FindWindowSchema, SearchOutputSchema, SearchResultSchema from yuxi.knowledge.utils import resolve_processing_params, sanitize_processing_params from yuxi.utils import logger from yuxi.utils.datetime_utils import coerce_any_to_utc_datetime, utc_isoformat class FileStatus: UPLOADED = "uploaded" PARSING = "parsing" PARSED = "parsed" ERROR_PARSING = "error_parsing" INDEXING = "indexing" INDEXED = "indexed" ERROR_INDEXING = "error_indexing" class KnowledgeBaseException(Exception): """知识库统一异常基类""" pass class KBNotFoundError(KnowledgeBaseException): """知识库不存在错误""" pass class KBOperationError(KnowledgeBaseException): """知识库操作错误""" pass class KnowledgeBase(ABC): """知识库抽象基类，定义统一接口""" kb_type = "" name = "" description = "" requires_embedding_model = True supports_documents = True apply_chunk_defaults = True # 类级别的处理队列，跟踪所有正在处理的文件 _processing_files = set() _processing_lock = None def __init__(self, work_dir: str): """ 初始化知识库 Args: work_dir: 工作目录 """ import threading self.work_dir = work_dir self.databases_meta: dict[str, dict] = {} self.files_meta: dict[str, dict] = {} self.benchmarks_meta: dict[str, dict] = {} self._metadata_loaded = False # 标记元数据是否已加载 # 初始化类级别的锁 if KnowledgeBase._processing_lock is None: KnowledgeBase._processing_lock = threading.Lock() os.makedirs(work_dir, exist_ok=True) # 注意：不在 __init__ 中加载元数据，由 KnowledgeBaseManager 统一管理加载 def load_metadata( self, global_databases_meta: dict[str, dict], files_meta: dict[str, dict], benchmarks_meta: dict[str, dict] ): """由 KnowledgeBaseManager 调用，同步加载元数据""" # 过滤出当前 kb_type 的知识库 self.databases_meta = {} for kb_id, meta in global_databases_meta.items(): if meta.get("kb_type") == self.kb_type: normalized_additional_params = self.normalize_additional_params(meta.get("additional_params")) self.databases_meta[kb_id] = { "name": meta.get("name"), "description": meta.get("description"), "kb_type": meta.get("kb_type"), "embedding_model_spec": meta.get("embedding_model_spec"), "llm_model_spec": meta.get("llm_model_spec"), "query_params": meta.get("query_params"), "metadata": normalized_additional_params, "created_at": meta.get("created_at"), } # 过滤文件 self.files_meta = {} for file_id, meta in files_meta.items(): if meta.get("kb_id") in self.databases_meta: kb_id = meta.get("kb_id") kb_additional_params = self.databases_meta.get(kb_id, {}).get("metadata") or {} normalized_meta = dict(meta) normalized_meta["processing_params"] = resolve_processing_params( kb_additional_params=kb_additional_params, file_processing_params=meta.get("processing_params"), ) self.files_meta[file_id] = normalized_meta # 过滤评估基准 self.benchmarks_meta = {} for kb_id, benchmarks in benchmarks_meta.items(): if kb_id in self.databases_meta: self.benchmarks_meta[kb_id] = benchmarks self._normalize_metadata_state() self._metadata_loaded = True logger.info(f"{self.kb_type}: 加载了 {len(self.databases_meta)} 个数据库的元数据") def _ensure_metadata_loaded(self): """确保元数据已加载（延迟加载）""" if not self._metadata_loaded: logger.warning(f"{self.kb_type}: 元数据尚未加载，请确保 KnowledgeBaseManager 已调用 load_metadata()") @staticmethod def _normalize_timestamp(value: Any) -> str | None: """Convert persisted timestamps to a normalized UTC ISO string.""" try: dt_value = coerce_any_to_utc_datetime(value) except (TypeError, ValueError) as exc: # noqa: BLE001 logger.warning(f"Invalid timestamp encountered: {value!r} ({exc})") return None if not dt_value: return None return utc_isoformat(dt_value) def _normalize_metadata_state(self) -> None: """Ensure in-memory metadata uses normalized timestamp formats.""" for meta in self.databases_meta.values(): if "created_at" in meta: normalized = self._normalize_timestamp(meta.get("created_at")) if normalized: meta["created_at"] = normalized for file_info in self.files_meta.values(): if "created_at" in file_info: normalized = self._normalize_timestamp(file_info.get("created_at")) if normalized: file_info["created_at"] = normalized for db_benchmarks in self.benchmarks_meta.values(): for b in db_benchmarks.values(): if "created_at" in b: normalized = self._normalize_timestamp(b.get("created_at")) if normalized: b["created_at"] = normalized if "updated_at" in b: normalized = self._normalize_timestamp(b.get("updated_at")) if normalized: b["updated_at"] = normalized @classmethod def get_create_params_config(cls) -> dict[str, Any]: """获取创建知识库时的类型特定参数配置。""" return {"options": []} @classmethod def validate_additional_params(cls, additional_params: dict | None) -> dict: """校验并规范化类型特定配置。""" return dict(additional_params or {}) @classmethod def normalize_additional_params(cls, additional_params: dict | None) -> dict: """规范化 additional_params，仅文档型知识库补充分块默认值。""" params = cls.validate_additional_params(additional_params) if cls.apply_chunk_defaults: return ensure_chunk_defaults_in_additional_params(params) return params @abstractmethod async def _create_kb_instance(self, kb_id: str, config: dict) -> Any: """ 创建底层知识库实例 Args: kb_id: 数据库ID config: 配置信息 Returns: 底层知识库实例 """ pass @abstractmethod async def _initialize_kb_instance(self, instance: Any) -> None: """ 初始化底层知识库实例 Args: instance: 底层知识库实例 """ pass async def add_file_record( self, kb_id: str, item: str, params: dict | None = None, operator_id: str | None = None ) -> dict: """ Add a file record to metadata (Status: UPLOADED) Args: kb_id: Database ID item: File path or URL params: Parameters operator_id: Operator ID who created the file Returns: File metadata record """ from yuxi.knowledge.utils.kb_utils import prepare_item_metadata params = params or {} content_type = params.get("content_type", "file") # Prepare metadata metadata = await prepare_item_metadata(item, content_type, kb_id, params=params) file_id = metadata["file_id"] kb_additional_params = self.databases_meta.get(kb_id, {}).get("metadata") or {} metadata["processing_params"] = resolve_processing_params( kb_additional_params=kb_additional_params, file_processing_params=metadata.get("processing_params"), ) # Fallback: fetch file size from MinIO if not provided if metadata.get("size") is None and content_type == "file": try: from yuxi.knowledge.utils.kb_utils import is_minio_url, parse_minio_url from yuxi.storage.minio import get_minio_client file_path = metadata.get("path") or item if is_minio_url(file_path): bucket_name, obj_name = parse_minio_url(file_path) minio_client = get_minio_client() file_size = await minio_client.astat_file(bucket_name, obj_name) if file_size is not None: metadata["size"] = file_size except Exception as exc: logger.warning(f"Failed to stat file size from MinIO for {item}: {exc}") # Initial status metadata["status"] = FileStatus.UPLOADED metadata["created_at"] = utc_isoformat() if operator_id: metadata["created_by"] = operator_id # Save to metadata self.files_meta[file_id] = metadata await self._persist_file(file_id) return metadata async def parse_file(self, kb_id: str, file_id: str, operator_id: str | None = None) -> dict: """ Parse file to Markdown and save to MinIO (Status: PARSING -> PARSED/ERROR_PARSING) Args: kb_id: Database ID file_id: File ID operator_id: ID of the user performing the operation Returns: Updated file metadata """ if file_id not in self.files_meta: raise ValueError(f"File {file_id} not found") file_meta = self.files_meta[file_id] current_status = file_meta.get("status") # Validate current status - only allow parsing from these states allowed_statuses = { FileStatus.UPLOADED, FileStatus.ERROR_PARSING, "failed", # Legacy status } if current_status not in allowed_statuses: raise ValueError( f"Cannot parse file with status '{current_status}'. " f"File must be in one of these states: {', '.join(allowed_statuses)}" ) file_path = file_meta.get("path") if not file_path: raise ValueError(f"File {file_id} has no valid path in metadata") # Clear previous error if any if "error" in file_meta: self.files_meta[file_id].pop("error", None) # Update status to PARSING and add to processing queue self.files_meta[file_id]["status"] = FileStatus.PARSING self.files_meta[file_id]["updated_at"] = utc_isoformat() if operator_id: self.files_meta[file_id]["updated_by"] = operator_id await self._persist_file(file_id) # Add to processing queue self._add_to_processing_queue(file_id) try: from yuxi.knowledge.parser.unified import Parser # Prepare params params = file_meta.get("processing_params", {}) or {} params["image_bucket"] = "public" params["image_prefix"] = f"{kb_id}/kb-images" markdown_content = await Parser.aparse( source=file_path, params=params, ) # Save Markdown to MinIO markdown_file_path = await self._save_markdown_to_minio(kb_id, file_id, markdown_content) # Update metadata self.files_meta[file_id]["status"] = FileStatus.PARSED self.files_meta[file_id]["markdown_file"] = markdown_file_path self.files_meta[file_id]["updated_at"] = utc_isoformat() if operator_id: self.files_meta[file_id]["updated_by"] = operator_id await self._persist_file(file_id) return self.files_meta[file_id] except Exception as e: error_msg = str(e) logger.error(f"Failed to parse file {file_id}: {error_msg}") self.files_meta[file_id]["status"] = FileStatus.ERROR_PARSING self.files_meta[file_id]["error"] = error_msg self.files_meta[file_id]["updated_at"] = utc_isoformat() if operator_id: self.files_meta[file_id]["updated_by"] = operator_id await self._persist_file(file_id) raise finally: # Remove from processing queue self._remove_from_processing_queue(file_id) async def update_file_params(self, kb_id: str, file_id: str, params: dict, operator_id: str | None = None) -> None: """Update file processing params""" if file_id not in self.files_meta: raise ValueError(f"File {file_id} not found") # Skip if no params to update if not params: return current_params = self.files_meta[file_id].get("processing_params", {}) or {} kb_additional_params = self.databases_meta.get(kb_id, {}).get("metadata") or {} logger.debug(f"[update_file_params] file_id={file_id}, current_params={current_params}, new_params={params}") current_params = resolve_processing_params( kb_additional_params=kb_additional_params, file_processing_params=current_params, request_params=params, ) self.files_meta[file_id]["processing_params"] = current_params self.files_meta[file_id]["updated_at"] = utc_isoformat() if operator_id: self.files_meta[file_id]["updated_by"] = operator_id logger.debug(f"[update_file_params] file_id={file_id}, updated_params={current_params}") await self._persist_file(file_id) async def _mark_file_unparsed(self, file_id: str, operator_id: str | None = None) -> None: if file_id not in self.files_meta: return self.files_meta[file_id]["status"] = FileStatus.UPLOADED self.files_meta[file_id].pop("markdown_file", None) self.files_meta[file_id].pop("error", None) self.files_meta[file_id]["updated_at"] = utc_isoformat() if operator_id: self.files_meta[file_id]["updated_by"] = operator_id await self._persist_file(file_id) async def _save_markdown_to_minio(self, kb_id: str, file_id: str, content: str) -> str: """Save markdown content to MinIO and return HTTP URL""" from yuxi.storage.minio import get_minio_client minio_client = get_minio_client() bucket_name = minio_client.KB_BUCKETS["parsed"] await asyncio.to_thread(minio_client.ensure_bucket_exists, bucket_name) object_name = f"{kb_id}/parsed/{file_id}.md" data = content.encode("utf-8") # Return standard HTTP URL from UploadResult upload_result = await minio_client.aupload_file( bucket_name=bucket_name, object_name=object_name, data=data, ) return upload_result.url async def _read_minio_bytes(self, file_path: str) -> bytes: from yuxi.knowledge.utils.kb_utils import is_minio_url, parse_minio_url from yuxi.storage.minio import get_minio_client if not file_path or not is_minio_url(file_path): raise ValueError(f"Invalid MinIO path format: {file_path}") bucket_name, object_name = parse_minio_url(file_path) minio_client = get_minio_client() return await minio_client.adownload_file(bucket_name, object_name) async def _read_markdown_from_minio(self, file_path: str) -> str: """Read markdown content from MinIO""" content_bytes = await self._read_minio_bytes(file_path) return content_bytes.decode("utf-8") def _get_file_meta(self, kb_id: str, file_id: str) -> dict: file_meta = self.files_meta.get(file_id) if not file_meta or file_meta.get("kb_id") != kb_id: raise ValueError(f"File {file_id} not found") return file_meta @staticmethod def _original_file_path(file_meta: dict) -> str | None: return file_meta.get("minio_url") or file_meta.get("path") def _knowledge_preview_variants(self, file_meta: dict) -> list[dict]: variants = [] original_path = self._original_file_path(file_meta) if original_path: variants.append({"key": "original", "label": "Source", "supported": True}) if file_meta.get("markdown_file"): variants.append({"key": "parsed", "label": "MD", "supported": True}) return variants def _knowledge_file_entry(self, kb_id: str, file_id: str, file_meta: dict) -> dict: is_dir = bool(file_meta.get("is_folder")) variants = [] if is_dir else self._knowledge_preview_variants(file_meta) preview_modes = [item["key"] for item in variants] default_preview_mode = None if "parsed" in preview_modes: default_preview_mode = "parsed" elif preview_modes: default_preview_mode = preview_modes[0] path = f"/{file_id}" if is_dir: path = f"{path}/" return { "source": "knowledge", "kb_id": kb_id, "file_id": file_id, "parent_id": file_meta.get("parent_id"), "path": path, "virtual_path": f"/knowledge/{kb_id}/{file_id}", "name": file_meta.get("filename") or file_meta.get("original_filename") or file_id, "is_dir": is_dir, "size": 0 if is_dir else file_meta.get("size") or 0, "modified_at": file_meta.get("updated_at") or file_meta.get("created_at") or "", "readonly": True, "status": file_meta.get("status", "done"), "preview_modes": preview_modes, "default_preview_mode": default_preview_mode, } def _sort_file_entries(self, entries: list[dict]) -> list[dict]: return sorted( entries, key=lambda item: (not bool(item.get("is_dir")), str(item.get("name") or "").lower()), ) def _list_knowledge_children( self, kb_id: str, parent_id: str | None, *, recursive: bool, files_only: bool, ) -> list[dict]: children = [ (file_id, meta) for file_id, meta in self.files_meta.items() if meta.get("kb_id") == kb_id and meta.get("parent_id") == parent_id ] entries = [] for file_id, meta in children: if not files_only or not meta.get("is_folder"): entries.append(self._knowledge_file_entry(kb_id, file_id, meta)) if recursive and meta.get("is_folder"): entries.extend( self._list_knowledge_children( kb_id, file_id, recursive=True, files_only=files_only, ) ) return self._sort_file_entries(entries) async def list_file_tree( self, kb_id: str, parent_id: str | None = None, recursive: bool = False, files_only: bool = False, ) -> dict: if kb_id not in self.databases_meta: raise ValueError(f"Database {kb_id} not found") if parent_id: parent_meta = self._get_file_meta(kb_id, parent_id) if not parent_meta.get("is_folder"): raise ValueError("Parent is not a folder") return { "entries": self._list_knowledge_children( kb_id, parent_id, recursive=recursive, files_only=files_only, ), "readonly": True, } async def read_file_preview(self, kb_id: str, file_id: str, variant: str = "parsed") -> dict: from yuxi.services.viewer_filesystem_service import _detect_preview_type file_meta = self._get_file_meta(kb_id, file_id) if file_meta.get("is_folder"): raise ValueError("Cannot preview a folder") variants = self._knowledge_preview_variants(file_meta) variant_keys = {item["key"] for item in variants} if variant not in {"original", "parsed"}: raise ValueError("Unsupported preview variant") filename = file_meta.get("filename") or file_meta.get("original_filename") or file_id response = { "source": "knowledge", "kb_id": kb_id, "file_id": file_id, "filename": filename, "variant": variant, "readonly": True, "available_variants": variants, } if variant == "parsed": markdown_file = file_meta.get("markdown_file") if not markdown_file or "parsed" not in variant_keys: return { **response, "content": None, "preview_type": "unsupported", "supported": False, "message": "文件尚未生成解析结果", } content = await self._read_markdown_from_minio(markdown_file) return { **response, "content": content, "preview_type": "markdown", "supported": True, "message": None, } original_path = self._original_file_path(file_meta) if not original_path or "original" not in variant_keys: return { **response, "content": None, "preview_type": "unsupported", "supported": False, "message": "文件没有可预览的原始内容", } preview_type, supported, message = _detect_preview_type(filename, b"") if preview_type in {"image", "pdf"}: return { **response, "content": None, "preview_type": preview_type, "supported": supported, "message": message, } raw_content = await self._read_minio_bytes(original_path) preview_type, supported, message = _detect_preview_type(filename, raw_content) if preview_type in {"image", "pdf"} or not supported: return { **response, "content": None, "preview_type": preview_type, "supported": supported, "message": message, } try: content = raw_content.decode("utf-8") except UnicodeDecodeError: return { **response, "content": None, "preview_type": "unsupported", "supported": False, "message": "当前文件不是 UTF-8 文本，暂不支持预览", } return { **response, "content": content, "preview_type": preview_type, "supported": True, "message": message, } async def get_file_download(self, kb_id: str, file_id: str, variant: str = "original") -> dict: file_meta = self._get_file_meta(kb_id, file_id) if file_meta.get("is_folder"): raise ValueError("Cannot download a folder") if variant not in {"original", "parsed"}: raise ValueError("Unsupported download variant") filename = file_meta.get("filename") or file_meta.get("original_filename") or file_id if variant == "parsed": markdown_file = file_meta.get("markdown_file") if not markdown_file: raise ValueError("文件尚未生成解析结果") return { "filename": f"{filename}.parsed.md", "content": await self._read_minio_bytes(markdown_file), "media_type": "text/markdown; charset=utf-8", } original_path = self._original_file_path(file_meta) if not original_path: raise ValueError("文件没有可下载的原始内容") media_type = file_meta.get("content_type") or mimetypes.guess_type(filename)[0] or "application/octet-stream" return { "filename": filename, "content": await self._read_minio_bytes(original_path), "media_type": media_type, } def _build_open_file_window(self, content: str, *, offset: int = 0, limit: int = 800) -> dict[str, Any]: lines = content.splitlines() total_lines = len(lines) start = min(max(int(offset), 0), total_lines) window_size = min(max(int(limit), 1), 2000) selected = lines[start : start + window_size] end = start + len(selected) return { "start_line": start + 1 if selected else 0, "end_line": end, "total_lines": total_lines, "offset": start, "window_size": window_size, "has_more_before": start > 0, "has_more_after": end < total_lines, "next_offset": end if end < total_lines else None, "content": "\n".join(f"{start + idx + 1:6d}\t{line}" for idx, line in enumerate(selected)), } @staticmethod def build_search_output(kb_id: str, retrieval_results: Any) -> dict[str, Any] | Any: if not isinstance(retrieval_results, list): return retrieval_results results = [] for index, chunk in enumerate(retrieval_results): if not isinstance(chunk, dict): continue metadata = chunk.get("metadata") if isinstance(chunk.get("metadata"), dict) else {} metadata = { key: value for key, value in metadata.items() if key not in {"filepath", "parsed_path", "path", "markdown_file"} } file_id = metadata.get("file_id") or chunk.get("file_id") or chunk.get("full_doc_id") or "" chunk_id = metadata.get("chunk_id") or chunk.get("chunk_id") or chunk.get("id") chunk_index = metadata.get("chunk_index") if chunk_index is None: chunk_index = chunk.get("chunk_index") if chunk_index is not None: metadata.setdefault("chunk_index", chunk_index) if chunk.get("score") is not None: metadata.setdefault("score", chunk.get("score")) if chunk.get("distance") is not None: metadata.setdefault("distance", chunk.get("distance")) results.append( SearchResultSchema( id=str(chunk_id or f"{file_id}:{index + 1}"), kb_id=str(kb_id), file_id=str(file_id or ""), content=str(chunk.get("content") or ""), metadata=metadata, ) ) return SearchOutputSchema(kb_id=str(kb_id), results=results).model_dump() @staticmethod def _build_find_file_windows( content: str, *, patterns: list[str], use_regex: bool = False, case_sensitive: bool = False, max_windows: int = 5, window_size: int = 80, ) -> dict[str, Any]: patterns = [pattern for pattern in patterns if pattern] if not patterns: raise ValueError("请提供至少一个 pattern") lines = content.splitlines() flags = 0 if case_sensitive else re.IGNORECASE if use_regex: matchers = [re.compile(pattern, flags) for pattern in patterns] def line_matches(line: str) -> bool: return any(matcher.search(line) for matcher in matchers) else: normalized_patterns = patterns if case_sensitive else [pattern.lower() for pattern in patterns] def line_matches(line: str) -> bool: haystack = line if case_sensitive else line.lower() return any(pattern in haystack for pattern in normalized_patterns) matched_indexes = [index for index, line in enumerate(lines) if line_matches(line)] windows: list[FindWindowSchema] = [] covered_until = -1 normalized_window_size = min(max(int(window_size), 1), 200) half_window = normalized_window_size // 2 for matched_index in matched_indexes: if matched_index < covered_until: continue start = max(matched_index - half_window, 0) end = min(start + normalized_window_size, len(lines)) start = max(end - normalized_window_size, 0) matched_lines = [index + 1 for index in matched_indexes if start <= index < end] selected = lines[start:end] windows.append( FindWindowSchema( start_line=start + 1 if selected else 0, end_line=end, matched_lines=matched_lines, content="\n".join(f"{start + idx + 1:6d}\t{line}" for idx, line in enumerate(selected)), ) ) covered_until = end if len(windows) >= max_windows: break return FindOutputSchema( kb_id="", file_id="", semantic=False, match_mode="regex" if use_regex else "keyword", total_matches=len(matched_indexes), windows=windows, ).model_dump(exclude={"kb_id", "file_id"}) async def open_file_content(self, kb_id: str, file_id: str, offset: int = 0, limit: int = 800) -> dict: """按行窗口打开文件解析后的 Markdown 内容""" file_meta = self.files_meta.get(file_id) if file_meta is None: raise Exception(f"文件不存在: {file_id}") if file_meta.get("kb_id") != kb_id: raise Exception(f"文件 {file_id} 不属于知识库 {kb_id}") if file_meta.get("is_folder"): raise Exception(f"文件 {file_id} 是文件夹") markdown_file = file_meta.get("markdown_file") if not markdown_file: raise Exception(f"文件 {file_id} 没有解析后的 Markdown 内容") content = await self._read_markdown_from_minio(markdown_file) return self._build_open_file_window(content, offset=offset, limit=limit) async def find_file_content( self, kb_id: str, file_id: str, patterns: list[str], *, use_regex: bool = False, case_sensitive: bool = False, max_windows: int = 5, window_size: int = 80, ) -> dict: file_meta = self.files_meta.get(file_id) if file_meta is None: raise Exception(f"文件不存在: {file_id}") if file_meta.get("kb_id") != kb_id: raise Exception(f"文件 {file_id} 不属于知识库 {kb_id}") if file_meta.get("is_folder"): raise Exception(f"文件 {file_id} 是文件夹") markdown_file = file_meta.get("markdown_file") if not markdown_file: raise Exception(f"文件 {file_id} 没有解析后的 Markdown 内容") content = await self._read_markdown_from_minio(markdown_file) return self._build_find_file_windows( content, patterns=patterns, use_regex=use_regex, case_sensitive=case_sensitive, max_windows=max_windows, window_size=window_size, ) @abstractmethod async def index_file(self, kb_id: str, file_id: str, operator_id: str | None = None) -> dict: """ Index parsed file (Status: INDEXING -> INDEXED/ERROR_INDEXING) Args: kb_id: Database ID file_id: File ID operator_id: ID of the user performing the operation Returns: Updated file metadata """ pass async def create_database( self, database_name: str, description: str, embedding_model_spec: str | None = None, llm_model_spec: str | None = None, **kwargs, ) -> dict: """ 创建数据库 Args: database_name: 数据库名称 description: 数据库描述 embedding_model_spec: 嵌入模型 spec llm_model_spec: LLM 模型 spec **kwargs: 其他配置参数 Returns: 数据库信息字典 """ kwargs = self.normalize_additional_params(kwargs) alphabet = string.ascii_lowercase + string.digits while True: kb_id = "kb_" + "".join(secrets.choice(alphabet) for _ in range(10)) if kb_id not in self.databases_meta: break self.databases_meta[kb_id] = { "name": database_name, "description": description, "kb_type": self.kb_type, "embedding_model_spec": embedding_model_spec, "llm_model_spec": llm_model_spec, "metadata": kwargs, "created_at": utc_isoformat(), "query_params": self._get_default_query_params(kb_id), } await self._persist_kb(kb_id) # 创建工作目录 working_dir = os.path.join(self.work_dir, kb_id) os.makedirs(working_dir, exist_ok=True) # 返回数据库信息 db_dict = self.databases_meta[kb_id].copy() db_dict["kb_id"] = kb_id db_dict["files"] = {} return db_dict async def delete_database(self, kb_id: str) -> dict: """ 删除数据库 Args: kb_id: 数据库ID Returns: 操作结果 """ if kb_id in self.databases_meta: from yuxi.knowledge.utils.kb_utils import is_minio_url, parse_minio_url from yuxi.repositories.knowledge_base_repository import KnowledgeBaseRepository from yuxi.storage.minio import get_minio_client minio_client = get_minio_client() # 1. 删除文件元数据中记录的 MinIO 文件 files_to_delete = [fid for fid, finfo in self.files_meta.items() if finfo.get("kb_id") == kb_id] for file_id in files_to_delete: file_path = self.files_meta[file_id].get("path") if file_path and is_minio_url(file_path): try: bucket_name, object_name = parse_minio_url(file_path) await minio_client.adelete_file(bucket_name, object_name) except Exception as e: logger.warning(f"Failed to delete MinIO file {file_path}: {e}") # 删除解析后的 markdown 文件 parsed_object = f"{kb_id}/parsed/{file_id}.md" await minio_client.adelete_file(minio_client.KB_BUCKETS["parsed"], parsed_object) del self.files_meta[file_id] # 2. 并行删除所有知识库 bucket 中该 kb_id 下的文件 prefix = f"{kb_id}/" cleanup_buckets = { minio_client.KB_BUCKETS["parsed"], minio_client.KB_BUCKETS["documents"], minio_client.KB_BUCKETS["images"], } cleanup_tasks = [ minio_client.adelete_objects_by_prefix(bucket_name, prefix) for bucket_name in cleanup_buckets ] await asyncio.gather(*cleanup_tasks) # 3. 删除数据库记录 del self.databases_meta[kb_id] kb_repo = KnowledgeBaseRepository() await kb_repo.delete(kb_id) await self._save_metadata() # 删除工作目录 working_dir = os.path.join(self.work_dir, kb_id) if os.path.exists(working_dir): import shutil try: shutil.rmtree(working_dir) except Exception as e: logger.error(f"Error deleting working directory {working_dir}: {e}") return {"message": "删除成功"} async def create_folder(self, kb_id: str, folder_name: str, parent_id: str | None = None) -> dict: """Create a folder in the database.""" import uuid folder_id = f"folder-{uuid.uuid4()}" self.files_meta[folder_id] = { "file_id": folder_id, "filename": folder_name, "is_folder": True, "parent_id": parent_id, "kb_id": kb_id, "created_at": utc_isoformat(), "status": "done", "path": folder_name, "file_type": "folder", } await self._persist_file(folder_id) return self.files_meta[folder_id] @abstractmethod async def update_content(self, kb_id: str, file_ids: list[str], params: dict | None = None) -> list[dict]: """ 更新内容 - 根据file_ids重新解析文件并更新向量库 Args: kb_id: 数据库ID file_ids: 文件ID列表 params: 处理参数 Returns: 更新结果列表 """ pass @abstractmethod async def aquery(self, query_text: str, kb_id: str, **kwargs) -> list[dict]: """ 异步查询知识库 Args: query_text: 查询文本 kb_id: 数据库ID **kwargs: 查询参数 Returns: 一个包含字典的列表，每个字典代表一个检索到的文档块。 """ pass @abstractmethod def get_query_params_config(self, kb_id: str, **kwargs) -> dict: """ 获取知识库类型的查询参数配置 Args: kb_id: 数据库ID **kwargs: 额外参数 Returns: dict: { "type": "kb_type", "options": [ { "key": "param_name", "label": "参数名称", "type": "select|number|boolean", "default": default_value, "options": [...], # 对于 select 类型 "description": "参数描述", "min": 1, # 对于 number 类型 "max": 100, "step": 0.1 }, ... ] } """ pass async def export_data(self, kb_id: str, format: str = "zip", **kwargs) -> str: pass def _get_query_params(self, kb_id: str) -> dict: """从实例元数据中加载查询参数""" if kb_id in self.databases_meta: query_params_meta = self.databases_meta[kb_id].get("query_params") or {} return query_params_meta.get("options", {}) return {} def _get_default_query_params(self, kb_id: str) -> dict[str, Any]: """从 get_query_params_config 中提取所有参数的默认值，返回 {"options": {...}}""" config = self.get_query_params_config(kb_id) defaults = {} for opt in config.get("options", []): if "default" in opt: defaults[opt["key"]] = opt["default"] return {"options": defaults} def get_database_info(self, kb_id: str, include_files: bool = True) -> dict | None: """ 获取数据库详细信息 Args: kb_id: 数据库ID include_files: 是否包含文件信息，默认为True Returns: 数据库信息或None """ if kb_id not in self.databases_meta: return None meta = self.databases_meta[kb_id].copy() meta["kb_id"] = kb_id # 检查并修复异常的processing状态 self._check_and_fix_processing_status(kb_id) # 统计文件数量（始终计算，即使不加载文件详情） db_file_count = sum(1 for file_info in self.files_meta.values() if file_info.get("kb_id") == kb_id) meta["row_count"] = db_file_count # 仅在需要时加载文件详情 if include_files: db_files = {} for file_id, file_info in self.files_meta.items(): if file_info.get("kb_id") == kb_id: created_at = self._normalize_timestamp(file_info.get("created_at")) db_files[file_id] = { "file_id": file_id, "filename": file_info.get("filename", ""), "path": file_info.get("path", ""), "markdown_file": file_info.get("markdown_file", ""), "type": file_info.get("file_type", ""), "status": file_info.get("status", "done"), "created_at": created_at, "is_folder": file_info.get("is_folder", False), "parent_id": file_info.get("parent_id", None), } # 按创建时间倒序排序文件列表 sorted_files = dict( sorted( db_files.items(), key=lambda item: item[1].get("created_at") or "", reverse=True, ) ) meta["files"] = sorted_files meta["status"] = "已连接" return meta def get_databases(self, include_files: bool = False) -> dict: """ 获取所有数据库信息 Args: include_files: 是否包含文件信息，默认False以减少响应大小 Returns: 数据库列表 """ # 确保元数据已加载（延迟加载机制） self._ensure_metadata_loaded() databases = [] for kb_id, meta in self.databases_meta.items(): # 检查并修复异常的processing状态 self._check_and_fix_processing_status(kb_id) db_dict = meta.copy() db_dict["kb_id"] = kb_id # 统计文件数量（始终计算，即使不加载文件详情） db_file_count = sum(1 for file_info in self.files_meta.values() if file_info.get("kb_id") == kb_id) db_dict["row_count"] = db_file_count # 仅在需要时加载文件详情 if include_files: db_files = {} for file_id, file_info in self.files_meta.items(): if file_info.get("kb_id") == kb_id: created_at = self._normalize_timestamp(file_info.get("created_at")) db_files[file_id] = { "file_id": file_id, "filename": file_info.get("filename", ""), "path": file_info.get("path", ""), "markdown_file": file_info.get("markdown_file", ""), "type": file_info.get("file_type", ""), "status": file_info.get("status", "done"), "created_at": created_at, "is_folder": file_info.get("is_folder", False), "parent_id": file_info.get("parent_id", None), } # 按创建时间倒序排序文件列表 sorted_files = dict( sorted( db_files.items(), key=lambda item: item[1].get("created_at") or "", reverse=True, ) ) db_dict["files"] = sorted_files db_dict["status"] = "已连接" databases.append(db_dict) return {"databases": databases} @classmethod def _add_to_processing_queue(cls, file_id: str) -> None: """ 将文件添加到处理队列 Args: file_id: 文件ID """ with cls._processing_lock: cls._processing_files.add(file_id) logger.debug(f"Added file {file_id} to processing queue") @classmethod def _remove_from_processing_queue(cls, file_id: str) -> None: """ 从处理队列中移除文件 Args: file_id: 文件ID """ with cls._processing_lock: cls._processing_files.discard(file_id) logger.debug(f"Removed file {file_id} from processing queue") @classmethod def _is_file_in_processing_queue(cls, file_id: str) -> bool: """ 检查文件是否在处理队列中 Args: file_id: 文件ID Returns: bool: 文件是否在处理队列中 """ with cls._processing_lock: return file_id in cls._processing_files def _check_and_fix_processing_status(self, kb_id: str) -> None: """ 检查并修复异常的处理中状态 如果文件状态为处理中但实际不在处理队列中，则修改为相应的错误状态 Args: kb_id: 数据库ID """ try: status_changed = False # 定义需要检查的中间状态及其对应的错误状态 intermediate_states = { FileStatus.PARSING: FileStatus.ERROR_PARSING, FileStatus.INDEXING: FileStatus.ERROR_INDEXING, } # 检查该数据库下所有中间状态的文件 for file_id, file_info in self.files_meta.items(): if file_info.get("kb_id") == kb_id: current_status = file_info.get("status") if current_status in intermediate_states: # 检查文件是否真的在处理队列中 if not self._is_file_in_processing_queue(file_id): error_status = intermediate_states[current_status] logger.warning( f"File {file_id} has {current_status} status but is not in processing queue, " f"marking as {error_status}" ) self.files_meta[file_id]["status"] = error_status self.files_meta[file_id]["error"] = ( f"{current_status.capitalize()} interrupted - process not found in queue" ) self.files_meta[file_id]["updated_at"] = utc_isoformat() status_changed = True # 如果有状态变更，保存元数据 if status_changed: logger.info(f"Fixed interrupted processing status for database {kb_id}") except Exception as e: logger.error(f"Error checking processing status for database {kb_id}: {e}") async def delete_folder(self, kb_id: str, folder_id: str) -> None: """ Recursively delete a folder and its content. Args: kb_id: Database ID folder_id: Folder ID to delete """ # Find all children children = [ fid for fid, meta in self.files_meta.items() if meta.get("kb_id") == kb_id and meta.get("parent_id") == folder_id ] for child_id in children: child_meta = self.files_meta.get(child_id) if child_meta and child_meta.get("is_folder"): await self.delete_folder(kb_id, child_id) else: await self.delete_file(kb_id, child_id) # Delete the folder itself # We call delete_file which should handle the actual removal. # Implementations should ensure they handle folder deletion gracefully (e.g. skip vector deletion) await self.delete_file(kb_id, folder_id) async def move_file(self, kb_id: str, file_id: str, new_parent_id: str | None) -> dict: """ Move a file or folder to a new parent folder. Args: kb_id: Database ID file_id: File/Folder ID to move new_parent_id: New parent folder ID (None for root) Returns: dict: Updated metadata """ if file_id not in self.files_meta: raise ValueError(f"File {file_id} not found") meta = self.files_meta[file_id] if meta.get("kb_id") != kb_id: raise ValueError(f"File {file_id} does not belong to database {kb_id}") # Basic cycle detection for folders if meta.get("is_folder") and new_parent_id: # Check if new_parent_id is a child of file_id (or is file_id itself) if new_parent_id == file_id: raise ValueError("Cannot move a folder into itself") # Walk up the tree from new_parent_id current = new_parent_id while current: parent_meta = self.files_meta.get(current) if not parent_meta: break # Should not happen if integrity is maintained if current == file_id: raise ValueError("Cannot move a folder into its own subfolder") current = parent_meta.get("parent_id") meta["parent_id"] = new_parent_id await self._persist_file(file_id) return meta @abstractmethod async def delete_file(self, kb_id: str, file_id: str) -> None: """ 删除文件 Args: kb_id: 数据库ID file_id: 文件ID """ pass @abstractmethod async def get_file_basic_info(self, kb_id: str, file_id: str) -> dict: """ 获取文件基本信息（仅元数据） Args: kb_id: 数据库ID file_id: 文件ID Returns: dict: 包含文件基本信息的字典 """ pass @abstractmethod async def get_file_content(self, kb_id: str, file_id: str) -> dict: """ 获取文件内容信息（chunks和lines） Args: kb_id: 数据库ID file_id: 文件ID Returns: dict: 包含文件内容信息的字典 """ pass @abstractmethod async def get_file_info(self, kb_id: str, file_id: str) -> dict: """ 获取文件完整信息（基本信息+内容信息） Args: kb_id: 数据库ID file_id: 文件ID Returns: dict: 包含文件信息和chunks的字典 """ pass def update_database( self, kb_id: str, name: str, description: str, llm_model_spec: str | None = None, update_llm_model_spec: bool = False, ) -> dict: """ 更新数据库 Args: kb_id: 数据库ID name: 新名称 description: 新描述 llm_model_spec: LLM 模型 spec（可选） Returns: 更新后的数据库信息 """ if kb_id not in self.databases_meta: raise ValueError(f"数据库 {kb_id} 不存在") self.databases_meta[kb_id]["name"] = name self.databases_meta[kb_id]["description"] = description if update_llm_model_spec: self.databases_meta[kb_id]["llm_model_spec"] = llm_model_spec return self.get_database_info(kb_id) def get_retrievers(self) -> dict[str, dict]: """ 获取所有检索器 Returns: 检索器字典 """ retrievers = {} for kb_id, meta in self.databases_meta.items(): def make_retriever(kb_id): async def retriever(query_text, **kwargs): results = await self.aquery(query_text, kb_id, agent_call=True, **kwargs) return self.build_search_output(kb_id, results) return retriever retrievers[kb_id] = { "name": meta["name"], "description": meta["description"], "retriever": make_retriever(kb_id), "metadata": meta, } return retrievers async def _load_metadata(self) -> None: from yuxi.repositories.knowledge_base_repository import KnowledgeBaseRepository from yuxi.repositories.knowledge_file_repository import KnowledgeFileRepository kb_repo = KnowledgeBaseRepository() file_repo = KnowledgeFileRepository() databases = [kb for kb in await kb_repo.get_all() if kb.kb_type == self.kb_type] self.databases_meta = { kb.kb_id: { "name": kb.name, "description": kb.description, "kb_type": kb.kb_type, "embedding_model_spec": kb.embedding_model_spec, "llm_model_spec": kb.llm_model_spec, "query_params": kb.query_params or self._get_default_query_params(kb.kb_id), "metadata": self.normalize_additional_params(kb.additional_params), "created_at": utc_isoformat(kb.created_at) if kb.created_at else utc_isoformat(), } for kb in databases } self.files_meta = {} for kb in databases: kb_additional_params = self.databases_meta.get(kb.kb_id, {}).get("metadata") or {} for record in await file_repo.list_by_kb_id(kb.kb_id): self.files_meta[record.file_id] = { "file_id": record.file_id, "kb_id": record.kb_id, "parent_id": record.parent_id, "filename": record.filename, "file_type": record.file_type, "path": record.path, "markdown_file": record.markdown_file, "status": record.status, "content_hash": record.content_hash, "size": record.file_size, "content_type": record.content_type, "processing_params": sanitize_processing_params( resolve_processing_params( kb_additional_params=kb_additional_params, file_processing_params=record.processing_params, ) ), "is_folder": record.is_folder, "error": record.error_message, "created_by": record.created_by, "updated_by": record.updated_by, "created_at": utc_isoformat(record.created_at) if record.created_at else None, "updated_at": utc_isoformat(record.updated_at) if record.updated_at else None, "original_filename": record.original_filename, "minio_url": record.minio_url, } self.benchmarks_meta = {} logger.info(f"Loaded {self.kb_type} metadata from database for {len(self.databases_meta)} databases") await self._fill_missing_file_sizes() async def _fill_missing_file_sizes(self) -> None: """为缺少 size 的已有文件从 MinIO 补全大小信息""" from yuxi.knowledge.utils.kb_utils import is_minio_url, parse_minio_url from yuxi.storage.minio import get_minio_client files_to_update: list[str] = [] for file_id, meta in self.files_meta.items(): if meta.get("is_folder"): continue if meta.get("size") is not None: continue file_path = meta.get("minio_url") or meta.get("path") if not file_path or not is_minio_url(file_path): continue files_to_update.append(file_id) if not files_to_update: return minio_client = get_minio_client() async def _stat_file(file_id: str, file_path: str) -> tuple[str, int | None]: bucket_name, obj_name = parse_minio_url(file_path) try: return file_id, await minio_client.astat_file(bucket_name, obj_name) except Exception as exc: logger.warning(f"Failed to fill size for {file_id}: {exc}") return file_id, None results = await asyncio.gather( *( _stat_file(fid, self.files_meta[fid].get("minio_url") or self.files_meta[fid].get("path")) for fid in files_to_update ) ) updated = 0 for file_id, file_size in results: if file_size is not None: self.files_meta[file_id]["size"] = file_size updated += 1 if updated: logger.info(f"Filled {updated}/{len(files_to_update)} missing file sizes from MinIO for {self.kb_type}") for file_id, file_size in results: if file_size is not None: await self._persist_file(file_id) async def _save_metadata(self) -> None: from yuxi.repositories.knowledge_base_repository import KnowledgeBaseRepository from yuxi.repositories.knowledge_file_repository import KnowledgeFileRepository kb_repo = KnowledgeBaseRepository() file_repo = KnowledgeFileRepository() self._normalize_metadata_state() for kb_id, meta in self.databases_meta.items(): existing = await kb_repo.get_by_kb_id(kb_id) payload = { "kb_id": kb_id, "name": meta.get("name") or kb_id, "description": meta.get("description"), "kb_type": meta.get("kb_type") or self.kb_type, "embedding_model_spec": meta.get("embedding_model_spec"), "llm_model_spec": meta.get("llm_model_spec"), "query_params": meta.get("query_params"), "additional_params": meta.get("metadata") or {}, } if existing is None: await kb_repo.create(payload) for file_id, meta in self.files_meta.items(): kb_id = meta.get("kb_id") if not kb_id: continue await file_repo.upsert( file_id=file_id, data={ "kb_id": kb_id, "parent_id": meta.get("parent_id"), "filename": meta.get("filename") or "", "original_filename": meta.get("original_filename"), "file_type": meta.get("file_type"), "path": meta.get("path"), "minio_url": meta.get("minio_url"), "markdown_file": meta.get("markdown_file"), "status": meta.get("status"), "content_hash": meta.get("content_hash"), "file_size": meta.get("size"), "content_type": meta.get("content_type"), "processing_params": sanitize_processing_params(meta.get("processing_params")), "is_folder": meta.get("is_folder", False), "error_message": meta.get("error"), "created_by": str(meta.get("created_by")) if meta.get("created_by") else None, "updated_by": str(meta.get("updated_by")) if meta.get("updated_by") else None, }, ) async def _persist_file(self, file_id: str) -> None: """只保存单个文件到数据库，避免全量遍历""" from yuxi.repositories.knowledge_file_repository import KnowledgeFileRepository file_repo = KnowledgeFileRepository() if file_id not in self.files_meta: return meta = self.files_meta[file_id] kb_id = meta.get("kb_id") if not kb_id: return await file_repo.upsert( file_id=file_id, data={ "kb_id": kb_id, "parent_id": meta.get("parent_id"), "filename": meta.get("filename") or "", "original_filename": meta.get("original_filename"), "file_type": meta.get("file_type"), "path": meta.get("path"), "minio_url": meta.get("minio_url"), "markdown_file": meta.get("markdown_file"), "status": meta.get("status"), "content_hash": meta.get("content_hash"), "file_size": meta.get("size"), "content_type": meta.get("content_type"), "processing_params": sanitize_processing_params(meta.get("processing_params")), "is_folder": meta.get("is_folder", False), "error_message": meta.get("error"), "created_by": str(meta.get("created_by")) if meta.get("created_by") else None, "updated_by": str(meta.get("updated_by")) if meta.get("updated_by") else None, }, ) async def _persist_kb(self, kb_id: str) -> None: """只保存单个知识库到数据库，避免全量遍历""" from yuxi.repositories.knowledge_base_repository import KnowledgeBaseRepository kb_repo = KnowledgeBaseRepository() if kb_id not in self.databases_meta: return meta = self.databases_meta[kb_id] existing = await kb_repo.get_by_kb_id(kb_id) payload = { "kb_id": kb_id, "name": meta.get("name") or kb_id, "description": meta.get("description"), "kb_type": meta.get("kb_type") or self.kb_type, "embedding_model_spec": meta.get("embedding_model_spec"), "llm_model_spec": meta.get("llm_model_spec"), "query_params": meta.get("query_params"), "additional_params": meta.get("metadata") or {}, } if existing is None: await kb_repo.create(payload) else: await kb_repo.update( kb_id, { "name": payload["name"], "description": payload["description"], "kb_type": payload["kb_type"], "embedding_model_spec": payload["embedding_model_spec"], "llm_model_spec": payload["llm_model_spec"], "query_params": payload["query_params"], "additional_params": payload["additional_params"], }, )