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Merge branch 'main' into milvus-for-nullable
This commit is contained in:
okxuewei
GitHub
commit
fc60b902e5
@ -882,7 +882,7 @@ rag = LightRAG(
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* **对于Neo4j图数据库，通过label来实现数据的逻辑隔离**：Neo4JStorage
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为了保持对遗留数据的兼容，在未配置工作空间时PostgreSQL的默认工作空间为`default`，Neo4j的默认工作空间为`base`。对于所有的外部存储，系统都提供了专用的工作空间环境变量，用于覆盖公共的 `WORKSPACE`环境变量配置。这些适用于指定存储类型的工作空间环境变量为：`REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`。
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为了保持对遗留数据的兼容，在未配置工作空间时PostgreSQL非图存储的工作空间为`default`，PostgreSQL AGE图存储的工作空间为空，Neo4j图存储的默认工作空间为`base`。对于所有的外部存储，系统都提供了专用的工作空间环境变量，用于覆盖公共的 `WORKSPACE`环境变量配置。这些适用于指定存储类型的工作空间环境变量为：`REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`。
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## 编辑实体和关系
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@ -928,7 +928,7 @@ The `workspace` parameter ensures data isolation between different LightRAG inst
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- **For relational databases, data isolation is achieved by adding a `workspace` field to the tables for logical data separation:** `PGKVStorage`, `PGVectorStorage`, `PGDocStatusStorage`.
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- **For the Neo4j graph database, logical data isolation is achieved through labels:** `Neo4JStorage`
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To maintain compatibility with legacy data, the default workspace for PostgreSQL is `default` and for Neo4j is `base` when no workspace is configured. For all external storages, the system provides dedicated workspace environment variables to override the common `WORKSPACE` environment variable configuration. These storage-specific workspace environment variables are: `REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`.
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To maintain compatibility with legacy data, the default workspace for PostgreSQL non-graph storage is `default` and, for PostgreSQL AGE graph storage is null, for Neo4j graph storage is `base` when no workspace is configured. For all external storages, the system provides dedicated workspace environment variables to override the common `WORKSPACE` environment variable configuration. These storage-specific workspace environment variables are: `REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`.
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## Edit Entities and Relations
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@ -1301,11 +1301,11 @@ def create_document_routes(
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"Starting to delete files in input directory"
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)
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# Delete all files in input_dir
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# Delete only files in the current directory, preserve files in subdirectories
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deleted_files_count = 0
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file_errors_count = 0
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for file_path in doc_manager.input_dir.glob("**/*"):
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for file_path in doc_manager.input_dir.glob("*"):
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if file_path.is_file():
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try:
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file_path.unlink()
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@ -414,7 +414,7 @@ class MemgraphStorage(BaseGraphStorage):
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if records:
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edge_result = dict(records[0]["edge_properties"])
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for key, default_value in {
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"weight": 0.0,
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"weight": 1.0,
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"source_id": None,
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"description": None,
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"keywords": None,
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@ -535,7 +535,7 @@ class Neo4JStorage(BaseGraphStorage):
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# logger.debug(f"Result: {edge_result}")
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# Ensure required keys exist with defaults
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required_keys = {
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"weight": 0.0,
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"weight": 1.0,
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"source_id": None,
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"description": None,
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"keywords": None,
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@ -559,7 +559,7 @@ class Neo4JStorage(BaseGraphStorage):
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)
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# Return default edge properties on error
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return {
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"weight": 0.0,
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"weight": 1.0,
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"source_id": None,
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"description": None,
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"keywords": None,
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@ -610,7 +610,7 @@ class Neo4JStorage(BaseGraphStorage):
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edge_props = edges[0] # choose the first if multiple exist
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# Ensure required keys exist with defaults
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for key, default in {
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"weight": 0.0,
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"weight": 1.0,
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"source_id": None,
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"description": None,
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"keywords": None,
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@ -621,7 +621,7 @@ class Neo4JStorage(BaseGraphStorage):
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else:
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# No edge found – set default edge properties
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edges_dict[(src, tgt)] = {
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"weight": 0.0,
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"weight": 1.0,
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"source_id": None,
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"description": None,
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"keywords": None,
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@ -105,25 +105,32 @@ class PostgreSQLDB:
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):
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pass
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async def _migrate_llm_cache_add_chunk_id(self):
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"""Add chunk_id column to LIGHTRAG_LLM_CACHE table if it doesn't exist"""
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async def _migrate_llm_cache_add_columns(self):
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"""Add chunk_id and cache_type columns to LIGHTRAG_LLM_CACHE table if they don't exist"""
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try:
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# Check if chunk_id column exists
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check_column_sql = """
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# Check if both columns exist
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check_columns_sql = """
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SELECT column_name
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FROM information_schema.columns
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WHERE table_name = 'lightrag_llm_cache'
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AND column_name = 'chunk_id'
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AND column_name IN ('chunk_id', 'cache_type')
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"""
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column_info = await self.query(check_column_sql)
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if not column_info:
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existing_columns = await self.query(check_columns_sql, multirows=True)
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existing_column_names = (
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{col["column_name"] for col in existing_columns}
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if existing_columns
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else set()
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)
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# Add missing chunk_id column
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if "chunk_id" not in existing_column_names:
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logger.info("Adding chunk_id column to LIGHTRAG_LLM_CACHE table")
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add_column_sql = """
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add_chunk_id_sql = """
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ALTER TABLE LIGHTRAG_LLM_CACHE
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ADD COLUMN chunk_id VARCHAR(255) NULL
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"""
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await self.execute(add_column_sql)
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await self.execute(add_chunk_id_sql)
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logger.info(
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"Successfully added chunk_id column to LIGHTRAG_LLM_CACHE table"
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)
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@ -131,54 +138,40 @@ class PostgreSQLDB:
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logger.info(
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"chunk_id column already exists in LIGHTRAG_LLM_CACHE table"
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)
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except Exception as e:
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logger.warning(f"Failed to add chunk_id column to LIGHTRAG_LLM_CACHE: {e}")
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async def _migrate_llm_cache_add_cache_type(self):
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"""Add cache_type column to LIGHTRAG_LLM_CACHE table if it doesn't exist"""
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try:
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# Check if cache_type column exists
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check_column_sql = """
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SELECT column_name
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FROM information_schema.columns
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WHERE table_name = 'lightrag_llm_cache'
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AND column_name = 'cache_type'
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"""
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column_info = await self.query(check_column_sql)
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if not column_info:
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# Add missing cache_type column
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if "cache_type" not in existing_column_names:
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logger.info("Adding cache_type column to LIGHTRAG_LLM_CACHE table")
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add_column_sql = """
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add_cache_type_sql = """
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ALTER TABLE LIGHTRAG_LLM_CACHE
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ADD COLUMN cache_type VARCHAR(32) NULL
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"""
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await self.execute(add_column_sql)
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await self.execute(add_cache_type_sql)
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logger.info(
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"Successfully added cache_type column to LIGHTRAG_LLM_CACHE table"
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)
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# Migrate existing data: extract cache_type from flattened keys
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# Migrate existing data using optimized regex pattern
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logger.info(
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"Migrating existing LLM cache data to populate cache_type field"
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"Migrating existing LLM cache data to populate cache_type field (optimized)"
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)
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update_sql = """
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optimized_update_sql = """
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UPDATE LIGHTRAG_LLM_CACHE
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SET cache_type = CASE
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WHEN id LIKE '%:%:%' THEN split_part(id, ':', 2)
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WHEN id ~ '^[^:]+:[^:]+:' THEN split_part(id, ':', 2)
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ELSE 'extract'
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END
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WHERE cache_type IS NULL
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"""
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await self.execute(update_sql)
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await self.execute(optimized_update_sql)
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logger.info("Successfully migrated existing LLM cache data")
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else:
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logger.info(
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"cache_type column already exists in LIGHTRAG_LLM_CACHE table"
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)
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except Exception as e:
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logger.warning(
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f"Failed to add cache_type column to LIGHTRAG_LLM_CACHE: {e}"
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)
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logger.warning(f"Failed to add columns to LIGHTRAG_LLM_CACHE: {e}")
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async def _migrate_timestamp_columns(self):
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"""Migrate timestamp columns in tables to witimezone-free types, assuming original data is in UTC time"""
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@ -187,6 +180,7 @@ class PostgreSQLDB:
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"LIGHTRAG_VDB_ENTITY": ["create_time", "update_time"],
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"LIGHTRAG_VDB_RELATION": ["create_time", "update_time"],
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"LIGHTRAG_DOC_CHUNKS": ["create_time", "update_time"],
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"LIGHTRAG_DOC_STATUS": ["created_at", "updated_at"],
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}
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for table_name, columns in tables_to_migrate.items():
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@ -292,121 +286,105 @@ class PostgreSQLDB:
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# Do not re-raise, to allow the application to start
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async def _check_llm_cache_needs_migration(self):
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"""Check if LLM cache data needs migration by examining the first record"""
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"""Check if LLM cache data needs migration by examining any record with old format"""
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try:
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# Only query the first record to determine format
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# Optimized query: directly check for old format records without sorting
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check_sql = """
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SELECT id FROM LIGHTRAG_LLM_CACHE
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ORDER BY create_time ASC
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SELECT 1 FROM LIGHTRAG_LLM_CACHE
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WHERE id NOT LIKE '%:%'
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LIMIT 1
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"""
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result = await self.query(check_sql)
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if result and result.get("id"):
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# If id doesn't contain colon, it's old format
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return ":" not in result["id"]
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# If any old format record exists, migration is needed
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return result is not None
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return False # No data or already new format
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except Exception as e:
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logger.warning(f"Failed to check LLM cache migration status: {e}")
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return False
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async def _migrate_llm_cache_to_flattened_keys(self):
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"""Migrate LLM cache to flattened key format, recalculating hash values"""
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"""Optimized version: directly execute single UPDATE migration to migrate old format cache keys to flattened format"""
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try:
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# Get all old format data
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old_data_sql = """
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SELECT id, mode, original_prompt, return_value, chunk_id,
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workspace, create_time, update_time
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FROM LIGHTRAG_LLM_CACHE
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# Check if migration is needed
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check_sql = """
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SELECT COUNT(*) as count FROM LIGHTRAG_LLM_CACHE
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WHERE id NOT LIKE '%:%'
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"""
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result = await self.query(check_sql)
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old_records = await self.query(old_data_sql, multirows=True)
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if not old_records:
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if not result or result["count"] == 0:
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logger.info("No old format LLM cache data found, skipping migration")
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return
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logger.info(
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f"Found {len(old_records)} old format cache records, starting migration..."
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old_count = result["count"]
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logger.info(f"Found {old_count} old format cache records")
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# Check potential primary key conflicts (optional but recommended)
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conflict_check_sql = """
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WITH new_ids AS (
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SELECT
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workspace,
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mode,
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id as old_id,
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mode || ':' ||
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CASE WHEN mode = 'default' THEN 'extract' ELSE 'unknown' END || ':' ||
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md5(original_prompt) as new_id
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FROM LIGHTRAG_LLM_CACHE
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WHERE id NOT LIKE '%:%'
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)
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SELECT COUNT(*) as conflicts
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FROM new_ids n1
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JOIN LIGHTRAG_LLM_CACHE existing
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ON existing.workspace = n1.workspace
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AND existing.mode = n1.mode
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AND existing.id = n1.new_id
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WHERE existing.id LIKE '%:%' -- Only check conflicts with existing new format records
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"""
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# Import hash calculation function
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from ..utils import compute_args_hash
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conflict_result = await self.query(conflict_check_sql)
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if conflict_result and conflict_result["conflicts"] > 0:
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logger.warning(
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f"Found {conflict_result['conflicts']} potential ID conflicts with existing records"
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)
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# Can choose to continue or abort, here we choose to continue and log warning
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migrated_count = 0
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# Execute single UPDATE migration
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logger.info("Starting optimized LLM cache migration...")
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migration_sql = """
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UPDATE LIGHTRAG_LLM_CACHE
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SET
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id = mode || ':' ||
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CASE WHEN mode = 'default' THEN 'extract' ELSE 'unknown' END || ':' ||
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md5(original_prompt),
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cache_type = CASE WHEN mode = 'default' THEN 'extract' ELSE 'unknown' END,
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update_time = CURRENT_TIMESTAMP
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WHERE id NOT LIKE '%:%'
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"""
|
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|
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# Migrate data in batches
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for record in old_records:
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||||
try:
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# Recalculate hash using correct method
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new_hash = compute_args_hash(
|
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record["mode"], record["original_prompt"]
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)
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# Execute migration
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await self.execute(migration_sql)
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# Determine cache_type based on mode
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cache_type = "extract" if record["mode"] == "default" else "unknown"
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# Verify migration results
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verify_sql = """
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SELECT COUNT(*) as remaining_old FROM LIGHTRAG_LLM_CACHE
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WHERE id NOT LIKE '%:%'
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"""
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verify_result = await self.query(verify_sql)
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remaining = verify_result["remaining_old"] if verify_result else -1
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# Generate new flattened key
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new_key = f"{record['mode']}:{cache_type}:{new_hash}"
|
||||
|
||||
# Insert new format data with cache_type field
|
||||
insert_sql = """
|
||||
INSERT INTO LIGHTRAG_LLM_CACHE
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(workspace, id, mode, original_prompt, return_value, chunk_id, cache_type, create_time, update_time)
|
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VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
|
||||
ON CONFLICT (workspace, mode, id) DO NOTHING
|
||||
"""
|
||||
|
||||
await self.execute(
|
||||
insert_sql,
|
||||
{
|
||||
"workspace": record[
|
||||
"workspace"
|
||||
], # Use original record's workspace
|
||||
"id": new_key,
|
||||
"mode": record["mode"],
|
||||
"original_prompt": record["original_prompt"],
|
||||
"return_value": record["return_value"],
|
||||
"chunk_id": record["chunk_id"],
|
||||
"cache_type": cache_type, # Add cache_type field
|
||||
"create_time": record["create_time"],
|
||||
"update_time": record["update_time"],
|
||||
},
|
||||
)
|
||||
|
||||
# Delete old data
|
||||
delete_sql = """
|
||||
DELETE FROM LIGHTRAG_LLM_CACHE
|
||||
WHERE workspace=$1 AND mode=$2 AND id=$3
|
||||
"""
|
||||
await self.execute(
|
||||
delete_sql,
|
||||
{
|
||||
"workspace": record[
|
||||
"workspace"
|
||||
], # Use original record's workspace
|
||||
"mode": record["mode"],
|
||||
"id": record["id"], # Old id
|
||||
},
|
||||
)
|
||||
|
||||
migrated_count += 1
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
f"Failed to migrate cache record {record['id']}: {e}"
|
||||
)
|
||||
continue
|
||||
|
||||
logger.info(
|
||||
f"Successfully migrated {migrated_count} cache records to flattened format"
|
||||
)
|
||||
if remaining == 0:
|
||||
logger.info(
|
||||
f"✅ Successfully migrated {old_count} LLM cache records to flattened format"
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
f"⚠️ Migration completed but {remaining} old format records remain"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"LLM cache migration failed: {e}")
|
||||
# Don't raise exception, allow system to continue startup
|
||||
logger.error(f"Optimized LLM cache migration failed: {e}")
|
||||
raise
|
||||
|
||||
async def _migrate_doc_status_add_chunks_list(self):
|
||||
"""Add chunks_list column to LIGHTRAG_DOC_STATUS table if it doesn't exist"""
|
||||
@ -646,20 +624,11 @@ class PostgreSQLDB:
|
||||
logger.error(f"PostgreSQL, Failed to migrate timestamp columns: {e}")
|
||||
# Don't throw an exception, allow the initialization process to continue
|
||||
|
||||
# Migrate LLM cache table to add chunk_id field if needed
|
||||
# Migrate LLM cache table to add chunk_id and cache_type columns if needed
|
||||
try:
|
||||
await self._migrate_llm_cache_add_chunk_id()
|
||||
await self._migrate_llm_cache_add_columns()
|
||||
except Exception as e:
|
||||
logger.error(f"PostgreSQL, Failed to migrate LLM cache chunk_id field: {e}")
|
||||
# Don't throw an exception, allow the initialization process to continue
|
||||
|
||||
# Migrate LLM cache table to add cache_type field if needed
|
||||
try:
|
||||
await self._migrate_llm_cache_add_cache_type()
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"PostgreSQL, Failed to migrate LLM cache cache_type field: {e}"
|
||||
)
|
||||
logger.error(f"PostgreSQL, Failed to migrate LLM cache columns: {e}")
|
||||
# Don't throw an exception, allow the initialization process to continue
|
||||
|
||||
# Finally, attempt to migrate old doc chunks data if needed
|
||||
@ -1494,9 +1463,10 @@ class PGDocStatusStorage(DocStatusStorage):
|
||||
"""Convert datetime to ISO format string with timezone info"""
|
||||
if dt is None:
|
||||
return None
|
||||
# If no timezone info, assume it's UTC time
|
||||
# If no timezone info, assume it's UTC time (as stored in database)
|
||||
if dt.tzinfo is None:
|
||||
dt = dt.replace(tzinfo=timezone.utc)
|
||||
# If datetime already has timezone info, keep it as is
|
||||
return dt.isoformat()
|
||||
|
||||
async def initialize(self):
|
||||
@ -1818,8 +1788,8 @@ class PGGraphStorage(BaseGraphStorage):
|
||||
"""
|
||||
Generate graph name based on workspace and namespace for data isolation.
|
||||
Rules:
|
||||
- If workspace is empty: graph_name = namespace
|
||||
- If workspace has value: graph_name = workspace_namespace
|
||||
- If workspace is empty or "default": graph_name = namespace
|
||||
- If workspace has other value: graph_name = workspace_namespace
|
||||
|
||||
Args:
|
||||
None
|
||||
@ -1828,15 +1798,15 @@ class PGGraphStorage(BaseGraphStorage):
|
||||
str: The graph name for the current workspace
|
||||
"""
|
||||
workspace = getattr(self, "workspace", None)
|
||||
namespace = self.namespace or os.environ.get("AGE_GRAPH_NAME", "lightrag")
|
||||
namespace = self.namespace
|
||||
|
||||
if workspace and workspace.strip():
|
||||
if workspace and workspace.strip() and workspace.strip().lower() != "default":
|
||||
# Ensure names comply with PostgreSQL identifier specifications
|
||||
safe_workspace = re.sub(r"[^a-zA-Z0-9_]", "_", workspace.strip())
|
||||
safe_namespace = re.sub(r"[^a-zA-Z0-9_]", "_", namespace)
|
||||
return f"{safe_workspace}_{safe_namespace}"
|
||||
else:
|
||||
# When workspace is empty, use namespace directly
|
||||
# When workspace is empty or "default", use namespace directly
|
||||
return re.sub(r"[^a-zA-Z0-9_]", "_", namespace)
|
||||
|
||||
@staticmethod
|
||||
|
||||
@ -1016,8 +1016,8 @@ async def _merge_edges_then_upsert(
|
||||
already_edge = await knowledge_graph_inst.get_edge(src_id, tgt_id)
|
||||
# Handle the case where get_edge returns None or missing fields
|
||||
if already_edge:
|
||||
# Get weight with default 0.0 if missing
|
||||
already_weights.append(already_edge.get("weight", 0.0))
|
||||
# Get weight with default 1.0 if missing
|
||||
already_weights.append(already_edge.get("weight", 1.0))
|
||||
|
||||
# Get source_id with empty string default if missing or None
|
||||
if already_edge.get("source_id") is not None:
|
||||
@ -1284,7 +1284,7 @@ async def merge_nodes_and_edges(
|
||||
"content": f"{edge_data['src_id']}\t{edge_data['tgt_id']}\n{edge_data['keywords']}\n{edge_data['description']}",
|
||||
"source_id": edge_data["source_id"],
|
||||
"file_path": edge_data.get("file_path", "unknown_source"),
|
||||
"weight": 0,
|
||||
"weight": edge_data.get("weight", 1.0),
|
||||
}
|
||||
}
|
||||
await relationships_vdb.upsert(data_for_vdb)
|
||||
@ -2494,9 +2494,9 @@ async def _find_most_related_edges_from_entities(
|
||||
if edge_props is not None:
|
||||
if "weight" not in edge_props:
|
||||
logger.warning(
|
||||
f"Edge {pair} missing 'weight' attribute, using default value 0.0"
|
||||
f"Edge {pair} missing 'weight' attribute, using default value 1.0"
|
||||
)
|
||||
edge_props["weight"] = 0.0
|
||||
edge_props["weight"] = 1.0
|
||||
|
||||
combined = {
|
||||
"src_tgt": pair,
|
||||
@ -2549,9 +2549,9 @@ async def _get_edge_data(
|
||||
if edge_props is not None:
|
||||
if "weight" not in edge_props:
|
||||
logger.warning(
|
||||
f"Edge {pair} missing 'weight' attribute, using default value 0.0"
|
||||
f"Edge {pair} missing 'weight' attribute, using default value 1.0"
|
||||
)
|
||||
edge_props["weight"] = 0.0
|
||||
edge_props["weight"] = 1.0
|
||||
|
||||
# Use edge degree from the batch as rank.
|
||||
combined = {
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user