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Merge pull request #1036 from danielaskdd/neo4j-add-min-degree

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Refactoring Neo4j implementation and fixing storage init problem for Gunicorn
This commit is contained in:
zrguo
2025-03-10 22:24:22 +08:00
committed by GitHub
parent 2b230d403d 2bf40ab636
commit 7ed7cb4ecf
9 changed files with 1081 additions and 545 deletions
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42
lightrag/api/lightrag_server.py
View File

@@ -50,9 +50,6 @@ from .auth import auth_handler
# This update allows the user to put a different.env file for each lightrag folder
load_dotenv(".env", override=True)
# Read entity extraction cache config
enable_llm_cache = os.getenv("ENABLE_LLM_CACHE_FOR_EXTRACT", "false").lower() == "true"
# Initialize config parser
config = configparser.ConfigParser()
config.read("config.ini")
@@ -144,23 +141,25 @@ def create_app(args):
try:
# Initialize database connections
await rag.initialize_storages()
await initialize_pipeline_status()
# Auto scan documents if enabled
if args.auto_scan_at_startup:
# Check if a task is already running (with lock protection)
pipeline_status = await get_namespace_data("pipeline_status")
should_start_task = False
async with get_pipeline_status_lock():
if not pipeline_status.get("busy", False):
should_start_task = True
# Only start the task if no other task is running
if should_start_task:
# Create background task
task = asyncio.create_task(run_scanning_process(rag, doc_manager))
app.state.background_tasks.add(task)
task.add_done_callback(app.state.background_tasks.discard)
logger.info("Auto scan task started at startup.")
await initialize_pipeline_status()
pipeline_status = await get_namespace_data("pipeline_status")
should_start_autoscan = False
async with get_pipeline_status_lock():
# Auto scan documents if enabled
if args.auto_scan_at_startup:
if not pipeline_status.get("autoscanned", False):
pipeline_status["autoscanned"] = True
should_start_autoscan = True
# Only run auto scan when no other process started it first
if should_start_autoscan:
# Create background task
task = asyncio.create_task(run_scanning_process(rag, doc_manager))
app.state.background_tasks.add(task)
task.add_done_callback(app.state.background_tasks.discard)
logger.info(f"Process {os.getpid()} auto scan task started at startup.")
ASCIIColors.green("\nServer is ready to accept connections! 🚀\n")
@@ -326,7 +325,7 @@ def create_app(args):
vector_db_storage_cls_kwargs={
"cosine_better_than_threshold": args.cosine_threshold
},
enable_llm_cache_for_entity_extract=enable_llm_cache, # Read from environment variable
enable_llm_cache_for_entity_extract=args.enable_llm_cache_for_extract,
embedding_cache_config={
"enabled": True,
"similarity_threshold": 0.95,
@@ -355,7 +354,7 @@ def create_app(args):
vector_db_storage_cls_kwargs={
"cosine_better_than_threshold": args.cosine_threshold
},
enable_llm_cache_for_entity_extract=enable_llm_cache, # Read from environment variable
enable_llm_cache_for_entity_extract=args.enable_llm_cache_for_extract,
embedding_cache_config={
"enabled": True,
"similarity_threshold": 0.95,
@@ -419,6 +418,7 @@ def create_app(args):
"doc_status_storage": args.doc_status_storage,
"graph_storage": args.graph_storage,
"vector_storage": args.vector_storage,
"enable_llm_cache_for_extract": args.enable_llm_cache_for_extract,
},
"update_status": update_status,
}

9
lightrag/api/utils_api.py
View File

@@ -362,6 +362,11 @@ def parse_args(is_uvicorn_mode: bool = False) -> argparse.Namespace:
args.chunk_size = get_env_value("CHUNK_SIZE", 1200, int)
args.chunk_overlap_size = get_env_value("CHUNK_OVERLAP_SIZE", 100, int)
# Inject LLM cache configuration
args.enable_llm_cache_for_extract = get_env_value(
"ENABLE_LLM_CACHE_FOR_EXTRACT", False, bool
)
# Select Document loading tool (DOCLING, DEFAULT)
args.document_loading_engine = get_env_value("DOCUMENT_LOADING_ENGINE", "DEFAULT")
@@ -457,8 +462,10 @@ def display_splash_screen(args: argparse.Namespace) -> None:
ASCIIColors.yellow(f"{args.history_turns}")
ASCIIColors.white(" ├─ Cosine Threshold: ", end="")
ASCIIColors.yellow(f"{args.cosine_threshold}")
ASCIIColors.white(" └─ Top-K: ", end="")
ASCIIColors.white(" ├─ Top-K: ", end="")
ASCIIColors.yellow(f"{args.top_k}")
ASCIIColors.white(" └─ LLM Cache for Extraction Enabled: ", end="")
ASCIIColors.yellow(f"{args.enable_llm_cache_for_extract}")
# System Configuration
ASCIIColors.magenta("\n💾 Storage Configuration:")

51
lightrag/kg/json_doc_status_impl.py
View File

@@ -15,6 +15,10 @@ from lightrag.utils import (
from .shared_storage import (
get_namespace_data,
get_storage_lock,
get_data_init_lock,
get_update_flag,
set_all_update_flags,
clear_all_update_flags,
try_initialize_namespace,
)
@@ -27,21 +31,25 @@ class JsonDocStatusStorage(DocStatusStorage):
def __post_init__(self):
working_dir = self.global_config["working_dir"]
self._file_name = os.path.join(working_dir, f"kv_store_{self.namespace}.json")
self._storage_lock = get_storage_lock()
self._data = None
self._storage_lock = None
self.storage_updated = None
async def initialize(self):
"""Initialize storage data"""
# check need_init must before get_namespace_data
need_init = try_initialize_namespace(self.namespace)
self._data = await get_namespace_data(self.namespace)
if need_init:
loaded_data = load_json(self._file_name) or {}
async with self._storage_lock:
self._data.update(loaded_data)
logger.info(
f"Loaded document status storage with {len(loaded_data)} records"
)
self._storage_lock = get_storage_lock()
self.storage_updated = await get_update_flag(self.namespace)
async with get_data_init_lock():
# check need_init must before get_namespace_data
need_init = await try_initialize_namespace(self.namespace)
self._data = await get_namespace_data(self.namespace)
if need_init:
loaded_data = load_json(self._file_name) or {}
async with self._storage_lock:
self._data.update(loaded_data)
logger.info(
f"Process {os.getpid()} doc status load {self.namespace} with {len(loaded_data)} records"
)
async def filter_keys(self, keys: set[str]) -> set[str]:
"""Return keys that should be processed (not in storage or not successfully processed)"""
@@ -87,18 +95,24 @@ class JsonDocStatusStorage(DocStatusStorage):
async def index_done_callback(self) -> None:
async with self._storage_lock:
data_dict = (
dict(self._data) if hasattr(self._data, "_getvalue") else self._data
)
write_json(data_dict, self._file_name)
if self.storage_updated.value:
data_dict = (
dict(self._data) if hasattr(self._data, "_getvalue") else self._data
)
logger.info(
f"Process {os.getpid()} doc status writting {len(data_dict)} records to {self.namespace}"
)
write_json(data_dict, self._file_name)
await clear_all_update_flags(self.namespace)
async def upsert(self, data: dict[str, dict[str, Any]]) -> None:
logger.info(f"Inserting {len(data)} to {self.namespace}")
if not data:
return
logger.info(f"Inserting {len(data)} records to {self.namespace}")
async with self._storage_lock:
self._data.update(data)
await set_all_update_flags(self.namespace)
await self.index_done_callback()
async def get_by_id(self, id: str) -> Union[dict[str, Any], None]:
@@ -109,9 +123,12 @@ class JsonDocStatusStorage(DocStatusStorage):
async with self._storage_lock:
for doc_id in doc_ids:
self._data.pop(doc_id, None)
await set_all_update_flags(self.namespace)
await self.index_done_callback()
async def drop(self) -> None:
"""Drop the storage"""
async with self._storage_lock:
self._data.clear()
await set_all_update_flags(self.namespace)
await self.index_done_callback()

74
lightrag/kg/json_kv_impl.py
View File

@@ -13,6 +13,10 @@ from lightrag.utils import (
from .shared_storage import (
get_namespace_data,
get_storage_lock,
get_data_init_lock,
get_update_flag,
set_all_update_flags,
clear_all_update_flags,
try_initialize_namespace,
)
@@ -23,26 +27,63 @@ class JsonKVStorage(BaseKVStorage):
def __post_init__(self):
working_dir = self.global_config["working_dir"]
self._file_name = os.path.join(working_dir, f"kv_store_{self.namespace}.json")
self._storage_lock = get_storage_lock()
self._data = None
self._storage_lock = None
self.storage_updated = None
async def initialize(self):
"""Initialize storage data"""
# check need_init must before get_namespace_data
need_init = try_initialize_namespace(self.namespace)
self._data = await get_namespace_data(self.namespace)
if need_init:
loaded_data = load_json(self._file_name) or {}
async with self._storage_lock:
self._data.update(loaded_data)
logger.info(f"Load KV {self.namespace} with {len(loaded_data)} data")
self._storage_lock = get_storage_lock()
self.storage_updated = await get_update_flag(self.namespace)
async with get_data_init_lock():
# check need_init must before get_namespace_data
need_init = await try_initialize_namespace(self.namespace)
self._data = await get_namespace_data(self.namespace)
if need_init:
loaded_data = load_json(self._file_name) or {}
async with self._storage_lock:
self._data.update(loaded_data)
# Calculate data count based on namespace
if self.namespace.endswith("cache"):
# For cache namespaces, sum the cache entries across all cache types
data_count = sum(
len(first_level_dict)
for first_level_dict in loaded_data.values()
if isinstance(first_level_dict, dict)
)
else:
# For non-cache namespaces, use the original count method
data_count = len(loaded_data)
logger.info(
f"Process {os.getpid()} KV load {self.namespace} with {data_count} records"
)
async def index_done_callback(self) -> None:
async with self._storage_lock:
data_dict = (
dict(self._data) if hasattr(self._data, "_getvalue") else self._data
)
write_json(data_dict, self._file_name)
if self.storage_updated.value:
data_dict = (
dict(self._data) if hasattr(self._data, "_getvalue") else self._data
)
# Calculate data count based on namespace
if self.namespace.endswith("cache"):
# # For cache namespaces, sum the cache entries across all cache types
data_count = sum(
len(first_level_dict)
for first_level_dict in data_dict.values()
if isinstance(first_level_dict, dict)
)
else:
# For non-cache namespaces, use the original count method
data_count = len(data_dict)
logger.info(
f"Process {os.getpid()} KV writting {data_count} records to {self.namespace}"
)
write_json(data_dict, self._file_name)
await clear_all_update_flags(self.namespace)
async def get_all(self) -> dict[str, Any]:
"""Get all data from storage
@@ -73,15 +114,16 @@ class JsonKVStorage(BaseKVStorage):
return set(keys) - set(self._data.keys())
async def upsert(self, data: dict[str, dict[str, Any]]) -> None:
logger.info(f"Inserting {len(data)} to {self.namespace}")
if not data:
return
logger.info(f"Inserting {len(data)} records to {self.namespace}")
async with self._storage_lock:
left_data = {k: v for k, v in data.items() if k not in self._data}
self._data.update(left_data)
self._data.update(data)
await set_all_update_flags(self.namespace)
async def delete(self, ids: list[str]) -> None:
async with self._storage_lock:
for doc_id in ids:
self._data.pop(doc_id, None)
await set_all_update_flags(self.namespace)
await self.index_done_callback()

976
lightrag/kg/neo4j_impl.py
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File diff suppressed because it is too large Load Diff

225
lightrag/kg/shared_storage.py
View File

@@ -7,12 +7,18 @@ from typing import Any, Dict, Optional, Union, TypeVar, Generic
# Define a direct print function for critical logs that must be visible in all processes
def direct_log(message, level="INFO"):
def direct_log(message, level="INFO", enable_output: bool = True):
"""
Log a message directly to stderr to ensure visibility in all processes,
including the Gunicorn master process.
Args:
message: The message to log
level: Log level (default: "INFO")
enable_output: Whether to actually output the log (default: True)
"""
print(f"{level}: {message}", file=sys.stderr, flush=True)
if enable_output:
print(f"{level}: {message}", file=sys.stderr, flush=True)
T = TypeVar("T")
@@ -32,55 +38,165 @@ _update_flags: Optional[Dict[str, bool]] = None # namespace -> updated
_storage_lock: Optional[LockType] = None
_internal_lock: Optional[LockType] = None
_pipeline_status_lock: Optional[LockType] = None
_graph_db_lock: Optional[LockType] = None
_data_init_lock: Optional[LockType] = None
class UnifiedLock(Generic[T]):
"""Provide a unified lock interface type for asyncio.Lock and multiprocessing.Lock"""
def __init__(self, lock: Union[ProcessLock, asyncio.Lock], is_async: bool):
def __init__(
self,
lock: Union[ProcessLock, asyncio.Lock],
is_async: bool,
name: str = "unnamed",
enable_logging: bool = True,
):
self._lock = lock
self._is_async = is_async
self._pid = os.getpid() # for debug only
self._name = name # for debug only
self._enable_logging = enable_logging # for debug only
async def __aenter__(self) -> "UnifiedLock[T]":
if self._is_async:
await self._lock.acquire()
else:
self._lock.acquire()
return self
try:
direct_log(
f"== Lock == Process {self._pid}: Acquiring lock '{self._name}' (async={self._is_async})",
enable_output=self._enable_logging,
)
if self._is_async:
await self._lock.acquire()
else:
self._lock.acquire()
direct_log(
f"== Lock == Process {self._pid}: Lock '{self._name}' acquired (async={self._is_async})",
enable_output=self._enable_logging,
)
return self
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to acquire lock '{self._name}': {e}",
level="ERROR",
enable_output=self._enable_logging,
)
raise
async def __aexit__(self, exc_type, exc_val, exc_tb):
if self._is_async:
self._lock.release()
else:
self._lock.release()
try:
direct_log(
f"== Lock == Process {self._pid}: Releasing lock '{self._name}' (async={self._is_async})",
enable_output=self._enable_logging,
)
if self._is_async:
self._lock.release()
else:
self._lock.release()
direct_log(
f"== Lock == Process {self._pid}: Lock '{self._name}' released (async={self._is_async})",
enable_output=self._enable_logging,
)
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to release lock '{self._name}': {e}",
level="ERROR",
enable_output=self._enable_logging,
)
raise
def __enter__(self) -> "UnifiedLock[T]":
"""For backward compatibility"""
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
self._lock.acquire()
return self
try:
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
direct_log(
f"== Lock == Process {self._pid}: Acquiring lock '{self._name}' (sync)",
enable_output=self._enable_logging,
)
self._lock.acquire()
direct_log(
f"== Lock == Process {self._pid}: Lock '{self._name}' acquired (sync)",
enable_output=self._enable_logging,
)
return self
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to acquire lock '{self._name}' (sync): {e}",
level="ERROR",
enable_output=self._enable_logging,
)
raise
def __exit__(self, exc_type, exc_val, exc_tb):
"""For backward compatibility"""
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
self._lock.release()
try:
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
direct_log(
f"== Lock == Process {self._pid}: Releasing lock '{self._name}' (sync)",
enable_output=self._enable_logging,
)
self._lock.release()
direct_log(
f"== Lock == Process {self._pid}: Lock '{self._name}' released (sync)",
enable_output=self._enable_logging,
)
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to release lock '{self._name}' (sync): {e}",
level="ERROR",
enable_output=self._enable_logging,
)
raise
def get_internal_lock() -> UnifiedLock:
def get_internal_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified storage lock for data consistency"""
return UnifiedLock(lock=_internal_lock, is_async=not is_multiprocess)
return UnifiedLock(
lock=_internal_lock,
is_async=not is_multiprocess,
name="internal_lock",
enable_logging=enable_logging,
)
def get_storage_lock() -> UnifiedLock:
def get_storage_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified storage lock for data consistency"""
return UnifiedLock(lock=_storage_lock, is_async=not is_multiprocess)
return UnifiedLock(
lock=_storage_lock,
is_async=not is_multiprocess,
name="storage_lock",
enable_logging=enable_logging,
)
def get_pipeline_status_lock() -> UnifiedLock:
def get_pipeline_status_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified storage lock for data consistency"""
return UnifiedLock(lock=_pipeline_status_lock, is_async=not is_multiprocess)
return UnifiedLock(
lock=_pipeline_status_lock,
is_async=not is_multiprocess,
name="pipeline_status_lock",
enable_logging=enable_logging,
)
def get_graph_db_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified graph database lock for ensuring atomic operations"""
return UnifiedLock(
lock=_graph_db_lock,
is_async=not is_multiprocess,
name="graph_db_lock",
enable_logging=enable_logging,
)
def get_data_init_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified data initialization lock for ensuring atomic data initialization"""
return UnifiedLock(
lock=_data_init_lock,
is_async=not is_multiprocess,
name="data_init_lock",
enable_logging=enable_logging,
)
def initialize_share_data(workers: int = 1):
@@ -108,6 +224,8 @@ def initialize_share_data(workers: int = 1):
_storage_lock, \
_internal_lock, \
_pipeline_status_lock, \
_graph_db_lock, \
_data_init_lock, \
_shared_dicts, \
_init_flags, \
_initialized, \
@@ -120,14 +238,16 @@ def initialize_share_data(workers: int = 1):
)
return
_manager = Manager()
_workers = workers
if workers > 1:
is_multiprocess = True
_manager = Manager()
_internal_lock = _manager.Lock()
_storage_lock = _manager.Lock()
_pipeline_status_lock = _manager.Lock()
_graph_db_lock = _manager.Lock()
_data_init_lock = _manager.Lock()
_shared_dicts = _manager.dict()
_init_flags = _manager.dict()
_update_flags = _manager.dict()
@@ -139,6 +259,8 @@ def initialize_share_data(workers: int = 1):
_internal_lock = asyncio.Lock()
_storage_lock = asyncio.Lock()
_pipeline_status_lock = asyncio.Lock()
_graph_db_lock = asyncio.Lock()
_data_init_lock = asyncio.Lock()
_shared_dicts = {}
_init_flags = {}
_update_flags = {}
@@ -164,6 +286,7 @@ async def initialize_pipeline_status():
history_messages = _manager.list() if is_multiprocess else []
pipeline_namespace.update(
{
"autoscanned": False, # Auto-scan started
"busy": False, # Control concurrent processes
"job_name": "Default Job", # Current job name (indexing files/indexing texts)
"job_start": None, # Job start time
@@ -200,7 +323,12 @@ async def get_update_flag(namespace: str):
if is_multiprocess and _manager is not None:
new_update_flag = _manager.Value("b", False)
else:
new_update_flag = False
# Create a simple mutable object to store boolean value for compatibility with mutiprocess
class MutableBoolean:
def __init__(self, initial_value=False):
self.value = initial_value
new_update_flag = MutableBoolean(False)
_update_flags[namespace].append(new_update_flag)
return new_update_flag
@@ -220,7 +348,26 @@ async def set_all_update_flags(namespace: str):
if is_multiprocess:
_update_flags[namespace][i].value = True
else:
_update_flags[namespace][i] = True
# Use .value attribute instead of direct assignment
_update_flags[namespace][i].value = True
async def clear_all_update_flags(namespace: str):
"""Clear all update flag of namespace indicating all workers need to reload data from files"""
global _update_flags
if _update_flags is None:
raise ValueError("Try to create namespace before Shared-Data is initialized")
async with get_internal_lock():
if namespace not in _update_flags:
raise ValueError(f"Namespace {namespace} not found in update flags")
# Update flags for both modes
for i in range(len(_update_flags[namespace])):
if is_multiprocess:
_update_flags[namespace][i].value = False
else:
# Use .value attribute instead of direct assignment
_update_flags[namespace][i].value = False
async def get_all_update_flags_status() -> Dict[str, list]:
@@ -247,7 +394,7 @@ async def get_all_update_flags_status() -> Dict[str, list]:
return result
def try_initialize_namespace(namespace: str) -> bool:
async def try_initialize_namespace(namespace: str) -> bool:
"""
Returns True if the current worker(process) gets initialization permission for loading data later.
The worker does not get the permission is prohibited to load data from files.
@@ -257,15 +404,17 @@ def try_initialize_namespace(namespace: str) -> bool:
if _init_flags is None:
raise ValueError("Try to create nanmespace before Shared-Data is initialized")
if namespace not in _init_flags:
_init_flags[namespace] = True
async with get_internal_lock():
if namespace not in _init_flags:
_init_flags[namespace] = True
direct_log(
f"Process {os.getpid()} ready to initialize storage namespace: [{namespace}]"
)
return True
direct_log(
f"Process {os.getpid()} ready to initialize storage namespace: [{namespace}]"
f"Process {os.getpid()} storage namespace already initialized: [{namespace}]"
)
return True
direct_log(
f"Process {os.getpid()} storage namespace already initialized: [{namespace}]"
)
return False
@@ -304,6 +453,8 @@ def finalize_share_data():
_storage_lock, \
_internal_lock, \
_pipeline_status_lock, \
_graph_db_lock, \
_data_init_lock, \
_shared_dicts, \
_init_flags, \
_initialized, \
@@ -369,6 +520,8 @@ def finalize_share_data():
_storage_lock = None
_internal_lock = None
_pipeline_status_lock = None
_graph_db_lock = None
_data_init_lock = None
_update_flags = None
direct_log(f"Process {os.getpid()} storage data finalization complete")

120
lightrag/lightrag.py
View File

@@ -354,6 +354,9 @@ class LightRAG:
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(
self
), # Add global_config to ensure cache works properly
embedding_func=self.embedding_func,
)
@@ -404,18 +407,8 @@ class LightRAG:
embedding_func=None,
)
if self.llm_response_cache and hasattr(
self.llm_response_cache, "global_config"
):
hashing_kv = self.llm_response_cache
else:
hashing_kv = self.key_string_value_json_storage_cls( # type: ignore
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
)
# Directly use llm_response_cache, don't create a new object
hashing_kv = self.llm_response_cache
self.llm_model_func = limit_async_func_call(self.llm_model_max_async)(
partial(
@@ -590,6 +583,7 @@ class LightRAG:
split_by_character, split_by_character_only
)
# TODO: deprecated, use insert instead
def insert_custom_chunks(
self,
full_text: str,
@@ -601,6 +595,7 @@ class LightRAG:
self.ainsert_custom_chunks(full_text, text_chunks, doc_id)
)
# TODO: deprecated, use ainsert instead
async def ainsert_custom_chunks(
self, full_text: str, text_chunks: list[str], doc_id: str | None = None
) -> None:
@@ -892,7 +887,9 @@ class LightRAG:
self.chunks_vdb.upsert(chunks)
)
entity_relation_task = asyncio.create_task(
self._process_entity_relation_graph(chunks)
self._process_entity_relation_graph(
chunks, pipeline_status, pipeline_status_lock
)
)
full_docs_task = asyncio.create_task(
self.full_docs.upsert(
@@ -1007,21 +1004,27 @@ class LightRAG:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
async def _process_entity_relation_graph(self, chunk: dict[str, Any]) -> None:
async def _process_entity_relation_graph(
self, chunk: dict[str, Any], pipeline_status=None, pipeline_status_lock=None
) -> None:
try:
await extract_entities(
chunk,
knowledge_graph_inst=self.chunk_entity_relation_graph,
entity_vdb=self.entities_vdb,
relationships_vdb=self.relationships_vdb,
llm_response_cache=self.llm_response_cache,
global_config=asdict(self),
pipeline_status=pipeline_status,
pipeline_status_lock=pipeline_status_lock,
llm_response_cache=self.llm_response_cache,
)
except Exception as e:
logger.error("Failed to extract entities and relationships")
raise e
async def _insert_done(self) -> None:
async def _insert_done(
self, pipeline_status=None, pipeline_status_lock=None
) -> None:
tasks = [
cast(StorageNameSpace, storage_inst).index_done_callback()
for storage_inst in [ # type: ignore
@@ -1040,12 +1043,10 @@ class LightRAG:
log_message = "All Insert done"
logger.info(log_message)
# 获取 pipeline_status 并更新 latest_message 和 history_messages
from lightrag.kg.shared_storage import get_namespace_data
pipeline_status = await get_namespace_data("pipeline_status")
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None and pipeline_status_lock is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
def insert_custom_kg(
self, custom_kg: dict[str, Any], full_doc_id: str = None
@@ -1260,16 +1261,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
system_prompt=system_prompt,
)
elif param.mode == "naive":
@@ -1279,16 +1271,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
system_prompt=system_prompt,
)
elif param.mode == "mix":
@@ -1301,16 +1284,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
system_prompt=system_prompt,
)
else:
@@ -1344,14 +1318,7 @@ class LightRAG:
text=query,
param=param,
global_config=asdict(self),
hashing_kv=self.llm_response_cache
or self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
)
param.hl_keywords = hl_keywords
@@ -1375,16 +1342,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
)
elif param.mode == "naive":
response = await naive_query(
@@ -1393,16 +1351,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
)
elif param.mode == "mix":
response = await mix_kg_vector_query(
@@ -1414,16 +1363,7 @@ class LightRAG:
self.text_chunks,
param,
asdict(self),
hashing_kv=self.llm_response_cache
if self.llm_response_cache
and hasattr(self.llm_response_cache, "global_config")
else self.key_string_value_json_storage_cls(
namespace=make_namespace(
self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
),
global_config=asdict(self),
embedding_func=self.embedding_func,
),
hashing_kv=self.llm_response_cache, # Directly use llm_response_cache
)
else:
raise ValueError(f"Unknown mode {param.mode}")

73
lightrag/operate.py
View File

@@ -3,6 +3,7 @@ from __future__ import annotations
import asyncio
import json
import re
import os
from typing import Any, AsyncIterator
from collections import Counter, defaultdict
@@ -220,6 +221,7 @@ async def _merge_nodes_then_upsert(
entity_name, description, global_config
)
node_data = dict(
entity_id=entity_name,
entity_type=entity_type,
description=description,
source_id=source_id,
@@ -301,6 +303,7 @@ async def _merge_edges_then_upsert(
await knowledge_graph_inst.upsert_node(
need_insert_id,
node_data={
"entity_id": need_insert_id,
"source_id": source_id,
"description": description,
"entity_type": "UNKNOWN",
@@ -337,11 +340,10 @@ async def extract_entities(
entity_vdb: BaseVectorStorage,
relationships_vdb: BaseVectorStorage,
global_config: dict[str, str],
pipeline_status: dict = None,
pipeline_status_lock=None,
llm_response_cache: BaseKVStorage | None = None,
) -> None:
from lightrag.kg.shared_storage import get_namespace_data
pipeline_status = await get_namespace_data("pipeline_status")
use_llm_func: callable = global_config["llm_model_func"]
entity_extract_max_gleaning = global_config["entity_extract_max_gleaning"]
enable_llm_cache_for_entity_extract: bool = global_config[
@@ -400,6 +402,7 @@ async def extract_entities(
else:
_prompt = input_text
# TODO： add cache_type="extract"
arg_hash = compute_args_hash(_prompt)
cached_return, _1, _2, _3 = await handle_cache(
llm_response_cache,
@@ -407,7 +410,6 @@ async def extract_entities(
_prompt,
"default",
cache_type="extract",
force_llm_cache=True,
)
if cached_return:
logger.debug(f"Found cache for {arg_hash}")
@@ -504,8 +506,10 @@ async def extract_entities(
relations_count = len(maybe_edges)
log_message = f" Chunk {processed_chunks}/{total_chunks}: extracted {entities_count} entities and {relations_count} relationships (deduplicated)"
logger.info(log_message)
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
return dict(maybe_nodes), dict(maybe_edges)
tasks = [_process_single_content(c) for c in ordered_chunks]
@@ -519,42 +523,58 @@ async def extract_entities(
for k, v in m_edges.items():
maybe_edges[tuple(sorted(k))].extend(v)
all_entities_data = await asyncio.gather(
*[
_merge_nodes_then_upsert(k, v, knowledge_graph_inst, global_config)
for k, v in maybe_nodes.items()
]
)
from .kg.shared_storage import get_graph_db_lock
all_relationships_data = await asyncio.gather(
*[
_merge_edges_then_upsert(k[0], k[1], v, knowledge_graph_inst, global_config)
for k, v in maybe_edges.items()
]
)
graph_db_lock = get_graph_db_lock(enable_logging=False)
# Ensure that nodes and edges are merged and upserted atomically
async with graph_db_lock:
all_entities_data = await asyncio.gather(
*[
_merge_nodes_then_upsert(k, v, knowledge_graph_inst, global_config)
for k, v in maybe_nodes.items()
]
)
all_relationships_data = await asyncio.gather(
*[
_merge_edges_then_upsert(
k[0], k[1], v, knowledge_graph_inst, global_config
)
for k, v in maybe_edges.items()
]
)
if not (all_entities_data or all_relationships_data):
log_message = "Didn't extract any entities and relationships."
logger.info(log_message)
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
return
if not all_entities_data:
log_message = "Didn't extract any entities"
logger.info(log_message)
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if not all_relationships_data:
log_message = "Didn't extract any relationships"
logger.info(log_message)
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
log_message = f"Extracted {len(all_entities_data)} entities and {len(all_relationships_data)} relationships (deduplicated)"
logger.info(log_message)
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
if pipeline_status is not None:
async with pipeline_status_lock:
pipeline_status["latest_message"] = log_message
pipeline_status["history_messages"].append(log_message)
verbose_debug(
f"New entities:{all_entities_data}, relationships:{all_relationships_data}"
)
@@ -1017,6 +1037,7 @@ async def _build_query_context(
text_chunks_db: BaseKVStorage,
query_param: QueryParam,
):
logger.info(f"Process {os.getpid()} buidling query context...")
if query_param.mode == "local":
entities_context, relations_context, text_units_context = await _get_node_data(
ll_keywords,

56
lightrag/utils.py
View File

@@ -633,15 +633,15 @@ async def handle_cache(
prompt,
mode="default",
cache_type=None,
force_llm_cache=False,
):
"""Generic cache handling function"""
if hashing_kv is None or not (
force_llm_cache or hashing_kv.global_config.get("enable_llm_cache")
):
if hashing_kv is None:
return None, None, None, None
if mode != "default":
if mode != "default": # handle cache for all type of query
if not hashing_kv.global_config.get("enable_llm_cache"):
return None, None, None, None
# Get embedding cache configuration
embedding_cache_config = hashing_kv.global_config.get(
"embedding_cache_config",
@@ -651,8 +651,7 @@ async def handle_cache(
use_llm_check = embedding_cache_config.get("use_llm_check", False)
quantized = min_val = max_val = None
if is_embedding_cache_enabled:
# Use embedding cache
if is_embedding_cache_enabled: # Use embedding simularity to match cache
current_embedding = await hashing_kv.embedding_func([prompt])
llm_model_func = hashing_kv.global_config.get("llm_model_func")
quantized, min_val, max_val = quantize_embedding(current_embedding[0])
@@ -667,24 +666,29 @@ async def handle_cache(
cache_type=cache_type,
)
if best_cached_response is not None:
logger.info(f"Embedding cached hit(mode:{mode} type:{cache_type})")
logger.debug(f"Embedding cached hit(mode:{mode} type:{cache_type})")
return best_cached_response, None, None, None
else:
# if caching keyword embedding is enabled, return the quantized embedding for saving it latter
logger.info(f"Embedding cached missed(mode:{mode} type:{cache_type})")
logger.debug(f"Embedding cached missed(mode:{mode} type:{cache_type})")
return None, quantized, min_val, max_val
# For default mode or is_embedding_cache_enabled is False, use regular cache
# default mode is for extract_entities or naive query
else: # handle cache for entity extraction
if not hashing_kv.global_config.get("enable_llm_cache_for_entity_extract"):
return None, None, None, None
# Here is the conditions of code reaching this point:
# 1. All query mode: enable_llm_cache is True and embedding simularity is not enabled
# 2. Entity extract: enable_llm_cache_for_entity_extract is True
if exists_func(hashing_kv, "get_by_mode_and_id"):
mode_cache = await hashing_kv.get_by_mode_and_id(mode, args_hash) or {}
else:
mode_cache = await hashing_kv.get_by_id(mode) or {}
if args_hash in mode_cache:
logger.info(f"Non-embedding cached hit(mode:{mode} type:{cache_type})")
logger.debug(f"Non-embedding cached hit(mode:{mode} type:{cache_type})")
return mode_cache[args_hash]["return"], None, None, None
logger.info(f"Non-embedding cached missed(mode:{mode} type:{cache_type})")
logger.debug(f"Non-embedding cached missed(mode:{mode} type:{cache_type})")
return None, None, None, None
@@ -701,9 +705,22 @@ class CacheData:
async def save_to_cache(hashing_kv, cache_data: CacheData):
if hashing_kv is None or hasattr(cache_data.content, "__aiter__"):
"""Save data to cache, with improved handling for streaming responses and duplicate content.
Args:
hashing_kv: The key-value storage for caching
cache_data: The cache data to save
"""
# Skip if storage is None or content is a streaming response
if hashing_kv is None or not cache_data.content:
return
# If content is a streaming response, don't cache it
if hasattr(cache_data.content, "__aiter__"):
logger.debug("Streaming response detected, skipping cache")
return
# Get existing cache data
if exists_func(hashing_kv, "get_by_mode_and_id"):
mode_cache = (
await hashing_kv.get_by_mode_and_id(cache_data.mode, cache_data.args_hash)
@@ -712,6 +729,16 @@ async def save_to_cache(hashing_kv, cache_data: CacheData):
else:
mode_cache = await hashing_kv.get_by_id(cache_data.mode) or {}
# Check if we already have identical content cached
if cache_data.args_hash in mode_cache:
existing_content = mode_cache[cache_data.args_hash].get("return")
if existing_content == cache_data.content:
logger.info(
f"Cache content unchanged for {cache_data.args_hash}, skipping update"
)
return
# Update cache with new content
mode_cache[cache_data.args_hash] = {
"return": cache_data.content,
"cache_type": cache_data.cache_type,
@@ -726,6 +753,7 @@ async def save_to_cache(hashing_kv, cache_data: CacheData):
"original_prompt": cache_data.prompt,
}
# Only upsert if there's actual new content
await hashing_kv.upsert({cache_data.mode: mode_cache})