fix: 修复 lightrag 序列化与 knowledge router 路径问题 Fixes: #584
- 修正 lightrag.py 中的序列化逻辑 - 修复 knowledge_router.py 路由路径 - 更新 roadmap.md 文档记录
This commit is contained in:
Wenjie Zhang
parent
4f6353d555
commit
d1a02579bc
@ -1,3 +1,4 @@
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import asyncio
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import os
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import os
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import traceback
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import traceback
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from functools import partial
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from functools import partial
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@ -34,6 +35,9 @@ class LightRagKB(KnowledgeBase):
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# 存储 LightRAG 实例映射 {db_id: LightRAG}
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# 存储 LightRAG 实例映射 {db_id: LightRAG}
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self.instances: dict[str, LightRAG] = {}
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self.instances: dict[str, LightRAG] = {}
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self._db_write_locks: dict[str, asyncio.Lock] = {}
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self._db_instance_locks: dict[str, asyncio.Lock] = {}
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self._lock_guard = asyncio.Lock()
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logger.info("LightRagKB initialized")
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logger.info("LightRagKB initialized")
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@ -197,20 +201,34 @@ class LightRagKB(KnowledgeBase):
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if db_id not in self.databases_meta:
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if db_id not in self.databases_meta:
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return None
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return None
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try:
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instance_lock = await self._get_db_instance_lock(db_id)
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# 创建实例
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async with instance_lock:
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rag = await self._create_kb_instance(db_id, {})
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if db_id in self.instances:
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logger.info(f"Using cached LightRAG instance for {db_id}")
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return self.instances[db_id]
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# 异步初始化存储
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try:
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await self._initialize_kb_instance(rag)
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# 创建实例
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rag = await self._create_kb_instance(db_id, {})
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self.instances[db_id] = rag
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# 异步初始化存储
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return rag
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await self._initialize_kb_instance(rag)
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except Exception as e:
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self.instances[db_id] = rag
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logger.error(f"Failed to create LightRAG instance for {db_id}: {e}")
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return rag
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logger.error(f"Traceback: {traceback.format_exc()}")
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return None
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except Exception as e:
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logger.error(f"Failed to create LightRAG instance for {db_id}: {e}")
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logger.error(f"Traceback: {traceback.format_exc()}")
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return None
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async def _get_db_write_lock(self, db_id: str) -> asyncio.Lock:
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async with self._lock_guard:
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return self._db_write_locks.setdefault(db_id, asyncio.Lock())
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async def _get_db_instance_lock(self, db_id: str) -> asyncio.Lock:
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async with self._lock_guard:
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return self._db_instance_locks.setdefault(db_id, asyncio.Lock())
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def _get_llm_func(self, llm_info: dict):
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def _get_llm_func(self, llm_info: dict):
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"""获取 LLM 函数"""
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"""获取 LLM 函数"""
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@ -299,163 +317,73 @@ class LightRagKB(KnowledgeBase):
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if db_id not in self.databases_meta:
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if db_id not in self.databases_meta:
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raise ValueError(f"Database {db_id} not found")
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raise ValueError(f"Database {db_id} not found")
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rag = await self._get_lightrag_instance(db_id)
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db_write_lock = await self._get_db_write_lock(db_id)
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if not rag:
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async with db_write_lock:
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raise ValueError(f"Failed to get LightRAG instance for {db_id}")
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rag = await self._get_lightrag_instance(db_id)
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if not rag:
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raise ValueError(f"Failed to get LightRAG instance for {db_id}")
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# Get file meta
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# Get file meta
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if file_id not in self.files_meta:
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raise ValueError(f"File {file_id} not found")
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file_meta = self.files_meta[file_id]
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# Validate current status - only allow indexing from these states
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current_status = file_meta.get("status")
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allowed_statuses = {
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FileStatus.PARSED,
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FileStatus.ERROR_INDEXING,
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FileStatus.INDEXED, # For re-indexing
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"done", # Legacy status
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}
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if current_status not in allowed_statuses:
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raise ValueError(
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f"Cannot index file with status '{current_status}'. "
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f"File must be parsed first (status should be one of: {', '.join(allowed_statuses)})"
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)
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# Check markdown file exists
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if not file_meta.get("markdown_file"):
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raise ValueError("File has not been parsed yet (no markdown_file)")
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# Clear previous error if any
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if "error" in file_meta:
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self.files_meta[file_id].pop("error", None)
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# Update status and add to processing queue
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self.files_meta[file_id]["status"] = FileStatus.INDEXING
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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# Add to processing queue
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self._add_to_processing_queue(file_id)
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try:
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# Read markdown
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markdown_content = await self._read_markdown_from_minio(file_meta["markdown_file"])
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file_path = file_meta.get("path")
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filename = file_meta.get("filename") or file_id
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processing_params = resolve_chunk_processing_params(
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kb_additional_params=self.databases_meta.get(db_id, {}).get("metadata"),
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file_processing_params=file_meta.get("processing_params"),
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)
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self.files_meta[file_id]["processing_params"] = processing_params
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await self._save_metadata()
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chunks = chunk_markdown(markdown_content, file_id, filename, processing_params)
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chunk_input, split_by_character, split_by_character_only = self._prepare_lightrag_insert_payload(chunks)
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if not chunk_input:
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chunk_input = markdown_content
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# Clean up existing chunks if any (for re-indexing)
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await self.delete_file_chunks_only(db_id, file_id)
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# Insert
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await rag.ainsert(
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input=chunk_input,
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ids=file_id,
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file_paths=file_path,
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split_by_character=split_by_character,
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split_by_character_only=split_by_character_only,
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)
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await self._ensure_doc_processed(rag, file_id)
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logger.info(
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f"Indexed file {file_id} into LightRAG with {len(chunks)} chunks, "
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f"chunk_preset_id={processing_params.get('chunk_preset_id')}"
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)
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# Update status
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self.files_meta[file_id]["status"] = FileStatus.INDEXED
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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return self.files_meta[file_id]
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except Exception as e:
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logger.error(f"Indexing failed for {file_id}: {e}")
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self.files_meta[file_id]["status"] = FileStatus.ERROR_INDEXING
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self.files_meta[file_id]["error"] = str(e)
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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raise
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finally:
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# Remove from processing queue
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self._remove_from_processing_queue(file_id)
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async def update_content(self, db_id: str, file_ids: list[str], params: dict | None = None) -> list[dict]:
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"""更新内容 - 根据file_ids重新解析文件并更新向量库"""
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if db_id not in self.databases_meta:
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raise ValueError(f"Database {db_id} not found")
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rag = await self._get_lightrag_instance(db_id)
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if not rag:
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raise ValueError(f"Failed to get LightRAG instance for {db_id}")
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# 处理默认参数
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if params is None:
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params = {}
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processed_items_info = []
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for file_id in file_ids:
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# 从元数据中获取文件信息
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if file_id not in self.files_meta:
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if file_id not in self.files_meta:
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logger.warning(f"File {file_id} not found in metadata, skipping")
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raise ValueError(f"File {file_id} not found")
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continue
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file_meta = self.files_meta[file_id]
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file_meta = self.files_meta[file_id]
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file_path = file_meta.get("path")
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if not file_path:
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# Validate current status - only allow indexing from these states
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logger.warning(f"File path not found for {file_id}, skipping")
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current_status = file_meta.get("status")
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continue
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allowed_statuses = {
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FileStatus.PARSED,
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FileStatus.ERROR_INDEXING,
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FileStatus.INDEXED, # For re-indexing
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"done", # Legacy status
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}
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# 添加到处理队列
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if current_status not in allowed_statuses:
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raise ValueError(
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f"Cannot index file with status '{current_status}'. "
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f"File must be parsed first (status should be one of: {', '.join(allowed_statuses)})"
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)
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# Check markdown file exists
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if not file_meta.get("markdown_file"):
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raise ValueError("File has not been parsed yet (no markdown_file)")
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# Clear previous error if any
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if "error" in file_meta:
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self.files_meta[file_id].pop("error", None)
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# Update status and add to processing queue
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self.files_meta[file_id]["status"] = FileStatus.INDEXING
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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# Add to processing queue
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self._add_to_processing_queue(file_id)
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self._add_to_processing_queue(file_id)
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try:
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try:
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# 更新状态为处理中
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# Read markdown
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resolved_params = resolve_chunk_processing_params(
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markdown_content = await self._read_markdown_from_minio(file_meta["markdown_file"])
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kb_additional_params=self.databases_meta.get(db_id, {}).get("metadata"),
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file_path = file_meta.get("path")
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file_processing_params=self.files_meta[file_id].get("processing_params"),
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request_params=params,
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)
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self.files_meta[file_id]["processing_params"] = resolved_params
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self.files_meta[file_id]["status"] = "processing"
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await self._persist_file(file_id)
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# 重新解析文件为 markdown
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params["image_bucket"] = "public"
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params["image_prefix"] = f"{db_id}/kb-images"
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markdown_content = await Parser.aparse(source=file_path, params=params)
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markdown_content_lines = markdown_content[:100].replace("\n", " ")
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logger.info(f"Markdown content: {markdown_content_lines}...")
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filename = file_meta.get("filename") or file_id
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filename = file_meta.get("filename") or file_id
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chunks = chunk_markdown(markdown_content, file_id, filename, resolved_params)
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processing_params = resolve_chunk_processing_params(
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chunk_input, split_by_character, split_by_character_only = self._prepare_lightrag_insert_payload(chunks)
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kb_additional_params=self.databases_meta.get(db_id, {}).get("metadata"),
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file_processing_params=file_meta.get("processing_params"),
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)
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self.files_meta[file_id]["processing_params"] = processing_params
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await self._save_metadata()
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chunks = chunk_markdown(markdown_content, file_id, filename, processing_params)
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chunk_input, split_by_character, split_by_character_only = self._prepare_lightrag_insert_payload(
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chunks
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)
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if not chunk_input:
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if not chunk_input:
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chunk_input = markdown_content
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chunk_input = markdown_content
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# 先删除现有的 LightRAG 数据（仅删除chunks，保留元数据）
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# Clean up existing chunks if any (for re-indexing)
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await self.delete_file_chunks_only(db_id, file_id)
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await self.delete_file_chunks_only(db_id, file_id)
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# 使用 LightRAG 重新插入内容
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# Insert
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await rag.ainsert(
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await rag.ainsert(
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input=chunk_input,
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input=chunk_input,
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ids=file_id,
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ids=file_id,
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@ -465,39 +393,137 @@ class LightRagKB(KnowledgeBase):
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)
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)
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await self._ensure_doc_processed(rag, file_id)
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await self._ensure_doc_processed(rag, file_id)
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logger.info(f"Updated file {file_path} in LightRAG. Done.")
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logger.info(
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f"Indexed file {file_id} into LightRAG with {len(chunks)} chunks, "
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f"chunk_preset_id={processing_params.get('chunk_preset_id')}"
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)
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# 更新元数据状态
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# Update status
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self.files_meta[file_id]["status"] = "done"
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self.files_meta[file_id]["status"] = FileStatus.INDEXED
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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await self._persist_file(file_id)
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# 从处理队列中移除
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return self.files_meta[file_id]
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self._remove_from_processing_queue(file_id)
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# 返回更新后的文件信息
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updated_file_meta = file_meta.copy()
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updated_file_meta["status"] = "done"
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updated_file_meta["file_id"] = file_id
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processed_items_info.append(updated_file_meta)
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except Exception as e:
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except Exception as e:
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error_msg = str(e)
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logger.error(f"Indexing failed for {file_id}: {e}")
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logger.error(f"更新file {file_path} 失败: {error_msg}, {traceback.format_exc()}")
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self.files_meta[file_id]["status"] = FileStatus.ERROR_INDEXING
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self.files_meta[file_id]["status"] = "failed"
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self.files_meta[file_id]["error"] = str(e)
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self.files_meta[file_id]["error"] = error_msg
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self.files_meta[file_id]["updated_at"] = utc_isoformat()
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if operator_id:
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self.files_meta[file_id]["updated_by"] = operator_id
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await self._persist_file(file_id)
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await self._persist_file(file_id)
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raise
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# 从处理队列中移除
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finally:
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# Remove from processing queue
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self._remove_from_processing_queue(file_id)
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self._remove_from_processing_queue(file_id)
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# 返回失败的文件信息
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async def update_content(self, db_id: str, file_ids: list[str], params: dict | None = None) -> list[dict]:
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failed_file_meta = file_meta.copy()
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"""更新内容 - 根据file_ids重新解析文件并更新向量库"""
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failed_file_meta["status"] = "failed"
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if db_id not in self.databases_meta:
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failed_file_meta["file_id"] = file_id
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raise ValueError(f"Database {db_id} not found")
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failed_file_meta["error"] = error_msg
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processed_items_info.append(failed_file_meta)
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return processed_items_info
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db_write_lock = await self._get_db_write_lock(db_id)
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async with db_write_lock:
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rag = await self._get_lightrag_instance(db_id)
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if not rag:
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raise ValueError(f"Failed to get LightRAG instance for {db_id}")
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# 处理默认参数
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if params is None:
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params = {}
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processed_items_info = []
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for file_id in file_ids:
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# 从元数据中获取文件信息
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||||||
|
if file_id not in self.files_meta:
|
||||||
|
logger.warning(f"File {file_id} not found in metadata, skipping")
|
||||||
|
continue
|
||||||
|
|
||||||
|
file_meta = self.files_meta[file_id]
|
||||||
|
file_path = file_meta.get("path")
|
||||||
|
|
||||||
|
if not file_path:
|
||||||
|
logger.warning(f"File path not found for {file_id}, skipping")
|
||||||
|
continue
|
||||||
|
|
||||||
|
# 添加到处理队列
|
||||||
|
self._add_to_processing_queue(file_id)
|
||||||
|
|
||||||
|
try:
|
||||||
|
# 更新状态为处理中
|
||||||
|
resolved_params = resolve_chunk_processing_params(
|
||||||
|
kb_additional_params=self.databases_meta.get(db_id, {}).get("metadata"),
|
||||||
|
file_processing_params=self.files_meta[file_id].get("processing_params"),
|
||||||
|
request_params=params,
|
||||||
|
)
|
||||||
|
self.files_meta[file_id]["processing_params"] = resolved_params
|
||||||
|
self.files_meta[file_id]["status"] = "processing"
|
||||||
|
await self._persist_file(file_id)
|
||||||
|
|
||||||
|
# 重新解析文件为 markdown
|
||||||
|
params["image_bucket"] = "public"
|
||||||
|
params["image_prefix"] = f"{db_id}/kb-images"
|
||||||
|
markdown_content = await Parser.aparse(source=file_path, params=params)
|
||||||
|
markdown_content_lines = markdown_content[:100].replace("\n", " ")
|
||||||
|
logger.info(f"Markdown content: {markdown_content_lines}...")
|
||||||
|
filename = file_meta.get("filename") or file_id
|
||||||
|
chunks = chunk_markdown(markdown_content, file_id, filename, resolved_params)
|
||||||
|
chunk_input, split_by_character, split_by_character_only = self._prepare_lightrag_insert_payload(
|
||||||
|
chunks
|
||||||
|
)
|
||||||
|
if not chunk_input:
|
||||||
|
chunk_input = markdown_content
|
||||||
|
|
||||||
|
# 先删除现有的 LightRAG 数据（仅删除chunks，保留元数据）
|
||||||
|
await self.delete_file_chunks_only(db_id, file_id)
|
||||||
|
|
||||||
|
# 使用 LightRAG 重新插入内容
|
||||||
|
await rag.ainsert(
|
||||||
|
input=chunk_input,
|
||||||
|
ids=file_id,
|
||||||
|
file_paths=file_path,
|
||||||
|
split_by_character=split_by_character,
|
||||||
|
split_by_character_only=split_by_character_only,
|
||||||
|
)
|
||||||
|
await self._ensure_doc_processed(rag, file_id)
|
||||||
|
|
||||||
|
logger.info(f"Updated file {file_path} in LightRAG. Done.")
|
||||||
|
|
||||||
|
# 更新元数据状态
|
||||||
|
self.files_meta[file_id]["status"] = "done"
|
||||||
|
await self._persist_file(file_id)
|
||||||
|
|
||||||
|
# 从处理队列中移除
|
||||||
|
self._remove_from_processing_queue(file_id)
|
||||||
|
|
||||||
|
# 返回更新后的文件信息
|
||||||
|
updated_file_meta = file_meta.copy()
|
||||||
|
updated_file_meta["status"] = "done"
|
||||||
|
updated_file_meta["file_id"] = file_id
|
||||||
|
processed_items_info.append(updated_file_meta)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
error_msg = str(e)
|
||||||
|
logger.error(f"更新file {file_path} 失败: {error_msg}, {traceback.format_exc()}")
|
||||||
|
self.files_meta[file_id]["status"] = "failed"
|
||||||
|
self.files_meta[file_id]["error"] = error_msg
|
||||||
|
await self._persist_file(file_id)
|
||||||
|
|
||||||
|
# 从处理队列中移除
|
||||||
|
self._remove_from_processing_queue(file_id)
|
||||||
|
|
||||||
|
# 返回失败的文件信息
|
||||||
|
failed_file_meta = file_meta.copy()
|
||||||
|
failed_file_meta["status"] = "failed"
|
||||||
|
failed_file_meta["file_id"] = file_id
|
||||||
|
failed_file_meta["error"] = error_msg
|
||||||
|
processed_items_info.append(failed_file_meta)
|
||||||
|
|
||||||
|
return processed_items_info
|
||||||
|
|
||||||
async def aquery(self, query_text: str, db_id: str, agent_call: bool = False, **kwargs) -> str:
|
async def aquery(self, query_text: str, db_id: str, agent_call: bool = False, **kwargs) -> str:
|
||||||
"""异步查询知识库"""
|
"""异步查询知识库"""
|
||||||
|
|||||||
@ -392,6 +392,7 @@ async def add_documents(
|
|||||||
try:
|
try:
|
||||||
# 2. Parse file (PARSING -> PARSED)
|
# 2. Parse file (PARSING -> PARSED)
|
||||||
file_meta = await knowledge_base.parse_file(db_id, file_id, operator_id=current_user.user_id)
|
file_meta = await knowledge_base.parse_file(db_id, file_id, operator_id=current_user.user_id)
|
||||||
|
added_files[item] = (file_id, file_meta)
|
||||||
processed_items.append(file_meta)
|
processed_items.append(file_meta)
|
||||||
parse_success_count += 1
|
parse_success_count += 1
|
||||||
except Exception as parse_error:
|
except Exception as parse_error:
|
||||||
|
|||||||
@ -65,6 +65,7 @@
|
|||||||
- 修复前端工具图标与渲染匹配不准确的问题：工具管理列表与工具调用结果统一改为基于工具 `id` 的精确映射，避免模糊匹配导致的误渲染，未命中的工具不再显示默认扳手图标
|
- 修复前端工具图标与渲染匹配不准确的问题：工具管理列表与工具调用结果统一改为基于工具 `id` 的精确映射，避免模糊匹配导致的误渲染，未命中的工具不再显示默认扳手图标
|
||||||
- 修复 GitHub Pages 文档部署工作流失败：移除 `actions/setup-node@v4` 对不存在 `docs/package-lock.json` 的缓存依赖，并将 `docs` 目录安装命令从 `npm ci` 调整为 `npm install`，避免因未提交锁文件导致 CI 在依赖缓存和安装阶段直接失败
|
- 修复 GitHub Pages 文档部署工作流失败：移除 `actions/setup-node@v4` 对不存在 `docs/package-lock.json` 的缓存依赖，并将 `docs` 目录安装命令从 `npm ci` 调整为 `npm install`，避免因未提交锁文件导致 CI 在依赖缓存和安装阶段直接失败
|
||||||
- 修正沙盒 provisioner backend 命名与配置说明：统一对外使用 `docker` / `kubernetes`，保留 `local` 作为兼容别名；同步清理 compose 中未生效的 provisioner 环境变量、补齐 K8s 相关变量注释，并更新沙盒架构文档中的默认模式与 backend 描述
|
- 修正沙盒 provisioner backend 命名与配置说明：统一对外使用 `docker` / `kubernetes`，保留 `local` 作为兼容别名；同步清理 compose 中未生效的 provisioner 环境变量、补齐 K8s 相关变量注释，并更新沙盒架构文档中的默认模式与 backend 描述
|
||||||
|
- 修复 LightRAG 同库写入并发导致的入库失败：为 `index_file` / `update_content` 增加按知识库维度的串行锁，并补齐 `documents` 接口 `auto_index` 阶段对最新解析状态的回写与回归测试，避免长时间入库任务进行中再次选择同库文件时直接并发写入报错
|
||||||
|
|
||||||
<!-- 添加到这里 -->
|
<!-- 添加到这里 -->
|
||||||
|
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user