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Arjun Rao 2025-05-14 03:12:03 +10:00
commit 2fbfdb5b17
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11
.github/dependabot.yml vendored Normal file
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@ -0,0 +1,11 @@
# To get started with Dependabot version updates, you'll need to specify which
# package ecosystems to update and where the package manifests are located.
# Please see the documentation for all configuration options:
# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
version: 2
updates:
- package-ecosystem: "pip" # See documentation for possible values
directory: "/" # Location of package manifests
schedule:
interval: "weekly"

2
Dockerfile
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@ -31,7 +31,7 @@ COPY --from=builder /root/.local /root/.local
COPY ./lightrag ./lightrag
COPY setup.py .
RUN pip install .
RUN pip install ".[api]"
# Make sure scripts in .local are usable
ENV PATH=/root/.local/bin:$PATH

2
README-zh.md
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@ -91,7 +91,7 @@ python examples/lightrag_openai_demo.py
如需流式响应示例的实现代码，请参阅 `examples/lightrag_openai_compatible_demo.py`。运行前，请确保根据需求修改示例代码中的LLM及嵌入模型配置。
**注意1**：在运行demo程序的时候需要注意，不同的测试程序可能使用的是不同的embedding模型，更换不同的embeding模型的时候需要把清空数据目录（`./dickens`），否则层序执行会出错。如果你想保留LLM缓存，可以在清除数据目录是保留`kv_store_llm_response_cache.json`文件。
**注意1**：在运行demo程序的时候需要注意，不同的测试程序可能使用的是不同的embedding模型，更换不同的embeding模型的时候需要把清空数据目录（`./dickens`），否则层序执行会出错。如果你想保留LLM缓存，可以在清除数据目录时保留`kv_store_llm_response_cache.json`文件。
**注意2**：官方支持的示例代码仅为 `lightrag_openai_demo.py` 和 `lightrag_openai_compatible_demo.py` 两个文件。其他示例文件均为社区贡献内容，尚未经过完整测试与优化。

18
SECURITY.md Normal file
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@ -0,0 +1,18 @@
# Reporting Security Issues
The LightRAG team and community take security bugs seriously. We appreciate your efforts to responsibly disclose your findings, and will make every effort to acknowledge your contributions.
To report a security issue, please use the GitHub Security Advisory: [Report a Vulnerability](https://github.com/HKUDS/LightRAG/security/advisories/new)
The LightRAG team will send a response indicating the next steps in handling your report. After the initial reply to your report, the security team will keep you informed of the progress towards a fix and full announcement, and may ask for additional information or guidance.
Report security bugs in third-party modules to the person or team maintaining the module.
### Supported Versions
The following versions currently being supported with security updates.
| Version | Supported |
| ------- | ------------------ |
| 1.2.x | :x: |
| 1.3.x | :white_check_mark: |

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31
docker-compose.yml
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@ -1,6 +1,10 @@
services:
lightrag:
build: .
build:
context: .
dockerfile: Dockerfile
tags:
- lightrag:latest
ports:
- "${PORT:-9621}:9621"
volumes:
@ -13,28 +17,3 @@ services:
restart: unless-stopped
extra_hosts:
- "host.docker.internal:host-gateway"
neo4j:
image: neo4j:5.26.4-community
container_name: lightrag-server_neo4j-community
restart: always
ports:
- "7474:7474"
- "7687:7687"
environment:
- NEO4J_AUTH=${NEO4J_USERNAME}/${NEO4J_PASSWORD}
- NEO4J_apoc_export_file_enabled=true
- NEO4J_server_bolt_listen__address=0.0.0.0:7687
- NEO4J_server_bolt_advertised__address=neo4j:7687
volumes:
- ./neo4j/plugins:/var/lib/neo4j/plugins
- lightrag_neo4j_import:/var/lib/neo4j/import
- lightrag_neo4j_data:/data
- lightrag_neo4j_backups:/backups
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
lightrag_neo4j_import:
lightrag_neo4j_data:
lightrag_neo4j_backups:

2
env.example
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@ -96,7 +96,7 @@ EMBEDDING_BINDING=ollama
EMBEDDING_BINDING_HOST=http://localhost:11434
### OpenAI alike example
# EMBEDDING_BINDING=openai
# LLM_BINDING_HOST=https://api.openai.com/v1
# EMBEDDING_BINDING_HOST=https://api.openai.com/v1
### Lollms example
# EMBEDDING_BINDING=lollms
# EMBEDDING_BINDING_HOST=http://localhost:9600

78
examples/lightrag_openai_compatible_demo.py
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@ -7,9 +7,12 @@ from lightrag import LightRAG, QueryParam
from lightrag.llm.openai import openai_complete_if_cache
from lightrag.llm.ollama import ollama_embed
from lightrag.utils import EmbeddingFunc, logger, set_verbose_debug
import numpy as np
from lightrag.kg.shared_storage import initialize_pipeline_status
from dotenv import load_dotenv
load_dotenv(dotenv_path=".env", override=False)
WORKING_DIR = "./dickens"
@ -86,43 +89,16 @@ async def llm_model_func(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
) -> str:
return await openai_complete_if_cache(
"deepseek-chat",
os.getenv("LLM_MODEL", "deepseek-chat"),
prompt,
system_prompt=system_prompt,
history_messages=history_messages,
api_key=os.getenv("OPENAI_API_KEY"),
base_url="https://api.deepseek.com",
api_key=os.getenv("LLM_BINDING_API_KEY") or os.getenv("OPENAI_API_KEY"),
base_url=os.getenv("LLM_BINDING_HOST", "https://api.deepseek.com"),
**kwargs,
)
async def embedding_func(texts: list[str]) -> np.ndarray:
return await ollama_embed(
texts=texts,
embed_model="bge-m3:latest",
host="http://m4.lan.znipower.com:11434",
)
async def get_embedding_dim():
test_text = ["This is a test sentence."]
embedding = await embedding_func(test_text)
embedding_dim = embedding.shape[1]
return embedding_dim
# function test
async def test_funcs():
result = await llm_model_func("How are you?")
print("llm_model_func: ", result)
result = await embedding_func(["How are you?"])
print("embedding_func: ", result)
# asyncio.run(test_funcs())
async def print_stream(stream):
async for chunk in stream:
if chunk:
@ -130,16 +106,17 @@ async def print_stream(stream):
async def initialize_rag():
embedding_dimension = await get_embedding_dim()
print(f"Detected embedding dimension: {embedding_dimension}")
rag = LightRAG(
working_dir=WORKING_DIR,
llm_model_func=llm_model_func,
embedding_func=EmbeddingFunc(
embedding_dim=embedding_dimension,
max_token_size=8192,
func=embedding_func,
embedding_dim=int(os.getenv("EMBEDDING_DIM", "1024")),
max_token_size=int(os.getenv("MAX_EMBED_TOKENS", "8192")),
func=lambda texts: ollama_embed(
texts,
embed_model=os.getenv("EMBEDDING_MODEL", "bge-m3:latest"),
host=os.getenv("EMBEDDING_BINDING_HOST", "http://localhost:11434"),
),
),
)
@ -151,9 +128,36 @@ async def initialize_rag():
async def main():
try:
# Clear old data files
files_to_delete = [
"graph_chunk_entity_relation.graphml",
"kv_store_doc_status.json",
"kv_store_full_docs.json",
"kv_store_text_chunks.json",
"vdb_chunks.json",
"vdb_entities.json",
"vdb_relationships.json",
]
for file in files_to_delete:
file_path = os.path.join(WORKING_DIR, file)
if os.path.exists(file_path):
os.remove(file_path)
print(f"Deleting old file:: {file_path}")
# Initialize RAG instance
rag = await initialize_rag()
# Test embedding function
test_text = ["This is a test string for embedding."]
embedding = await rag.embedding_func(test_text)
embedding_dim = embedding.shape[1]
print("\n=======================")
print("Test embedding function")
print("========================")
print(f"Test dict: {test_text}")
print(f"Detected embedding dimension: {embedding_dim}\n\n")
with open("./book.txt", "r", encoding="utf-8") as f:
await rag.ainsert(f.read())

36
examples/lightrag_openai_demo.py
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@ -91,10 +91,46 @@ async def initialize_rag():
async def main():
# Check if OPENAI_API_KEY environment variable exists
if not os.getenv("OPENAI_API_KEY"):
print(
"Error: OPENAI_API_KEY environment variable is not set. Please set this variable before running the program."
)
print("You can set the environment variable by running:")
print(" export OPENAI_API_KEY='your-openai-api-key'")
return # Exit the async function
try:
# Clear old data files
files_to_delete = [
"graph_chunk_entity_relation.graphml",
"kv_store_doc_status.json",
"kv_store_full_docs.json",
"kv_store_text_chunks.json",
"vdb_chunks.json",
"vdb_entities.json",
"vdb_relationships.json",
]
for file in files_to_delete:
file_path = os.path.join(WORKING_DIR, file)
if os.path.exists(file_path):
os.remove(file_path)
print(f"Deleting old file:: {file_path}")
# Initialize RAG instance
rag = await initialize_rag()
# Test embedding function
test_text = ["This is a test string for embedding."]
embedding = await rag.embedding_func(test_text)
embedding_dim = embedding.shape[1]
print("\n=======================")
print("Test embedding function")
print("========================")
print(f"Test dict: {test_text}")
print(f"Detected embedding dimension: {embedding_dim}\n\n")
with open("./book.txt", "r", encoding="utf-8") as f:
await rag.ainsert(f.read())

2
lightrag/api/__init__.py
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@ -1 +1 @@
__api_version__ = "0169"
__api_version__ = "0170"

32
lightrag/api/config.py
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@ -6,6 +6,7 @@ import os
import argparse
import logging
from dotenv import load_dotenv
from lightrag.utils import get_env_value
from lightrag.constants import (
DEFAULT_WOKERS,
@ -50,37 +51,6 @@ def get_default_host(binding_type: str) -> str:
) # fallback to ollama if unknown
def get_env_value(
env_key: str, default: any, value_type: type = str, special_none: bool = False
) -> any:
"""
Get value from environment variable with type conversion
Args:
env_key (str): Environment variable key
default (any): Default value if env variable is not set
value_type (type): Type to convert the value to
special_none (bool): If True, return None when value is "None"
Returns:
any: Converted value from environment or default
"""
value = os.getenv(env_key)
if value is None:
return default
# Handle special case for "None" string
if special_none and value == "None":
return None
if value_type is bool:
return value.lower() in ("true", "1", "yes", "t", "on")
try:
return value_type(value)
except (ValueError, TypeError):
return default
def parse_args() -> argparse.Namespace:
"""
Parse command line arguments with environment variable fallback

3
lightrag/api/gunicorn_config.py
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@ -2,8 +2,7 @@
import os
import logging
from lightrag.kg.shared_storage import finalize_share_data
from lightrag.utils import setup_logger
from lightrag.api.config import get_env_value
from lightrag.utils import setup_logger, get_env_value
from lightrag.constants import (
DEFAULT_LOG_MAX_BYTES,
DEFAULT_LOG_BACKUP_COUNT,

2
lightrag/api/lightrag_server.py
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@ -26,8 +26,8 @@ from .config import (
global_args,
update_uvicorn_mode_config,
get_default_host,
get_env_value,
)
from lightrag.utils import get_env_value
import sys
from lightrag import LightRAG, __version__ as core_version
from lightrag.api import __api_version__

3
lightrag/api/run_with_gunicorn.py
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@ -8,7 +8,8 @@ import sys
import signal
import pipmaster as pm
from lightrag.api.utils_api import display_splash_screen, check_env_file
from lightrag.api.config import global_args, get_env_value
from lightrag.api.config import global_args
from lightrag.utils import get_env_value
from lightrag.kg.shared_storage import initialize_share_data, finalize_share_data
from lightrag.constants import (

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lightrag/api/webui/assets/_basePickBy--_O36kXE.js → lightrag/api/webui/assets/_basePickBy-Lz6agtdo.js generated
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lightrag/api/webui/assets/chunk-4BMEZGHF-M5QBFtoC.js → lightrag/api/webui/assets/chunk-4BMEZGHF-Ct0jZH9M.js generated
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import{_ as l}from"./mermaid-vendor-SwnP6Sr8.js";function m(e,c){var i,t,o;e.accDescr&&((i=c.setAccDescription)==null||i.call(c,e.accDescr)),e.accTitle&&((t=c.setAccTitle)==null||t.call(c,e.accTitle)),e.title&&((o=c.setDiagramTitle)==null||o.call(c,e.title))}l(m,"populateCommonDb");export{m as p};
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lightrag/api/webui/assets/chunk-D6G4REZN-CO4Tk6j6.js → lightrag/api/webui/assets/chunk-D6G4REZN-CQqXYBrW.js generated
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2
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2
lightrag/api/webui/assets/diagram-VNBRO52H-CpzL1-Is.js → lightrag/api/webui/assets/diagram-VNBRO52H-DXx0iDIJ.js generated
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@ -1,4 +1,4 @@
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2
lightrag/api/webui/assets/erDiagram-Q7BY3M3F-CAraTg_G.js → lightrag/api/webui/assets/erDiagram-Q7BY3M3F-DQX4VtAS.js generated
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2
lightrag/api/webui/assets/feature-documents-BKQZIcI6.js → lightrag/api/webui/assets/feature-documents-ClbgnjXg.js generated
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lightrag/api/webui/assets/feature-graph-D6-O-kXP.js → lightrag/api/webui/assets/feature-graph-DbHHHM9y.js generated
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lightrag/api/webui/assets/feature-retrieval-wTZcnY1B.js → lightrag/api/webui/assets/feature-retrieval-zozGWnLh.js generated
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lightrag/api/webui/assets/flowDiagram-4HSFHLVR-DC7cFb2q.js → lightrag/api/webui/assets/flowDiagram-4HSFHLVR-CtTg4KvT.js generated
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import{_ as m,o as O1,l as Z,c as Ge,d as Ce,p as H1,r as q1,u as i1,b as X1,s as Q1,q as J1,a as Z1,g as $1,t as et,k as tt,v as st,J as it,x as rt,y as s1,z as nt,A as at,B as ut,C as lt}from"./mermaid-vendor-SwnP6Sr8.js";import{g as ot,s as ct}from"./chunk-RZ5BOZE2-vCqEaZEa.js";import"./feature-graph-D6-O-kXP.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var ht="flowchart-",Pe,dt=(Pe=class{constructor(){this.vertexCounter=0,this.config=Ge(),this.vertices=new Map,this.edges=[],this.classes=new Map,this.subGraphs=[],this.subGraphLookup=new Map,this.tooltips=new Map,this.subCount=0,this.firstGraphFlag=!0,this.secCount=-1,this.posCrossRef=[],this.funs=[],this.setAccTitle=X1,this.setAccDescription=Q1,this.setDiagramTitle=J1,this.getAccTitle=Z1,this.getAccDescription=$1,this.getDiagramTitle=et,this.funs.push(this.setupToolTips.bind(this)),this.addVertex=this.addVertex.bind(this),this.firstGraph=this.firstGraph.bind(this),this.setDirection=this.setDirection.bind(this),this.addSubGraph=this.addSubGraph.bind(this),this.addLink=this.addLink.bind(this),this.setLink=this.setLink.bind(this),this.updateLink=this.updateLink.bind(this),this.addClass=this.addClass.bind(this),this.setClass=this.setClass.bind(this),this.destructLink=this.destructLink.bind(this),this.setClickEvent=this.setClickEvent.bind(this),this.setTooltip=this.setTooltip.bind(this),this.updateLinkInterpolate=this.updateLinkInterpolate.bind(this),this.setClickFun=this.setClickFun.bind(this),this.bindFunctions=this.bindFunctions.bind(this),this.lex={firstGraph:this.firstGraph.bind(this)},this.clear(),this.setGen("gen-2")}sanitizeText(i){return tt.sanitizeText(i,this.config)}lookUpDomId(i){for(const n of this.vertices.values())if(n.id===i)return n.domId;return i}addVertex(i,n,a,u,l,f,c={},A){var U,T;if(!i||i.trim().length===0)return;let r;if(A!==void 0){let d;A.includes(`
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`:d=`{
`+A+`

2
lightrag/api/webui/assets/ganttDiagram-APWFNJXF-CkKq4NOY.js → lightrag/api/webui/assets/ganttDiagram-APWFNJXF-DPZeRkyR.js generated
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2
lightrag/api/webui/assets/gitGraphDiagram-7IBYFJ6S-C7t9VG9x.js → lightrag/api/webui/assets/gitGraphDiagram-7IBYFJ6S-fIZu_S0j.js generated
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2
lightrag/api/webui/assets/graph-CmqUPRtj.js → lightrag/api/webui/assets/graph-DexVwBa8.js generated
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22
lightrag/api/webui/assets/index-m6I92ZpT.js → lightrag/api/webui/assets/index-Bj1VgJta.js generated
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1
lightrag/api/webui/assets/index-C3vR7z2U.css generated Normal file
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lightrag/api/webui/assets/index-CM0YrL-d.css generated
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2
lightrag/api/webui/assets/infoDiagram-PH2N3AL5-C4VRyMR4.js → lightrag/api/webui/assets/infoDiagram-PH2N3AL5-Bexk_QKW.js generated
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@ -1,2 +1,2 @@
import{_ as e,l as o,K as i,e as n,L as p}from"./mermaid-vendor-SwnP6Sr8.js";import{p as m}from"./radar-MK3ICKWK-CihkADAx.js";import"./feature-graph-D6-O-kXP.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-D81M49Y6.js";import"./_basePickBy--_O36kXE.js";import"./clone-BHIBWXu-.js";var g={parse:e(async r=>{const a=await m("info",r);o.debug(a)},"parse")},v={version:p.version},d=e(()=>v.version,"getVersion"),c={getVersion:d},l=e((r,a,s)=>{o.debug(`rendering info diagram
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2
lightrag/api/webui/assets/journeyDiagram-U35MCT3I-YPalBptu.js → lightrag/api/webui/assets/journeyDiagram-U35MCT3I-Drj8e4jk.js generated
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@ -1,4 +1,4 @@
import{a as pt,g as at,f as gt,d as mt}from"./chunk-D6G4REZN-CO4Tk6j6.js";import{_ as s,g as xt,s as kt,a as _t,b as bt,t as vt,q as wt,c as A,d as W,e as Tt,z as St,N as tt}from"./mermaid-vendor-SwnP6Sr8.js";import"./feature-graph-D6-O-kXP.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var H=function(){var t=s(function(g,r,a,l){for(a=a||{},l=g.length;l--;a[g[l]]=r);return a},"o"),e=[6,8,10,11,12,14,16,17,18],i=[1,9],c=[1,10],n=[1,11],u=[1,12],h=[1,13],f=[1,14],d={trace:s(function(){},"trace"),yy:{},symbols_:{error:2,start:3,journey:4,document:5,EOF:6,line:7,SPACE:8,statement:9,NEWLINE:10,title:11,acc_title:12,acc_title_value:13,acc_descr:14,acc_descr_value:15,acc_descr_multiline_value:16,section:17,taskName:18,taskData:19,$accept:0,$end:1},terminals_:{2:"error",4:"journey",6:"EOF",8:"SPACE",10:"NEWLINE",11:"title",12:"acc_title",13:"acc_title_value",14:"acc_descr",15:"acc_descr_value",16:"acc_descr_multiline_value",17:"section",18:"taskName",19:"taskData"},productions_:[0,[3,3],[5,0],[5,2],[7,2],[7,1],[7,1],[7,1],[9,1],[9,2],[9,2],[9,1],[9,1],[9,2]],performAction:s(function(r,a,l,y,p,o,S){var _=o.length-1;switch(p){case 1:return o[_-1];case 2:this.$=[];break;case 3:o[_-1].push(o[_]),this.$=o[_-1];break;case 4:case 5:this.$=o[_];break;case 6:case 7:this.$=[];break;case 8:y.setDiagramTitle(o[_].substr(6)),this.$=o[_].substr(6);break;case 9:this.$=o[_].trim(),y.setAccTitle(this.$);break;case 10:case 11:this.$=o[_].trim(),y.setAccDescription(this.$);break;case 12:y.addSection(o[_].substr(8)),this.$=o[_].substr(8);break;case 13:y.addTask(o[_-1],o[_]),this.$="task";break}},"anonymous"),table:[{3:1,4:[1,2]},{1:[3]},t(e,[2,2],{5:3}),{6:[1,4],7:5,8:[1,6],9:7,10:[1,8],11:i,12:c,14:n,16:u,17:h,18:f},t(e,[2,7],{1:[2,1]}),t(e,[2,3]),{9:15,11:i,12:c,14:n,16:u,17:h,18:f},t(e,[2,5]),t(e,[2,6]),t(e,[2,8]),{13:[1,16]},{15:[1,17]},t(e,[2,11]),t(e,[2,12]),{19:[1,18]},t(e,[2,4]),t(e,[2,9]),t(e,[2,10]),t(e,[2,13])],defaultActions:{},parseError:s(function(r,a){if(a.recoverable)this.trace(r);else{var l=new Error(r);throw l.hash=a,l}},"parseError"),parse:s(function(r){var a=this,l=[0],y=[],p=[null],o=[],S=this.table,_="",B=0,J=0,ut=2,K=1,yt=o.slice.call(arguments,1),k=Object.create(this.lexer),E={yy:{}};for(var O in this.yy)Object.prototype.hasOwnProperty.call(this.yy,O)&&(E.yy[O]=this.yy[O]);k.setInput(r,E.yy),E.yy.lexer=k,E.yy.parser=this,typeof k.yylloc>"u"&&(k.yylloc={});var Y=k.yylloc;o.push(Y);var dt=k.options&&k.options.ranges;typeof E.yy.parseError=="function"?this.parseError=E.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function ft(v){l.length=l.length-2*v,p.length=p.length-v,o.length=o.length-v}s(ft,"popStack");function Q(){var v;return v=y.pop()||k.lex()||K,typeof v!="number"&&(v instanceof Array&&(y=v,v=y.pop()),v=a.symbols_[v]||v),v}s(Q,"lex");for(var b,P,w,q,C={},N,$,D,j;;){if(P=l[l.length-1],this.defaultActions[P]?w=this.defaultActions[P]:((b===null||typeof b>"u")&&(b=Q()),w=S[P]&&S[P][b]),typeof w>"u"||!w.length||!w[0]){var G="";j=[];for(N in S[P])this.terminals_[N]&&N>ut&&j.push("'"+this.terminals_[N]+"'");k.showPosition?G="Parse error on line "+(B+1)+`:
import{a as pt,g as at,f as gt,d as mt}from"./chunk-D6G4REZN-CQqXYBrW.js";import{_ as s,g as xt,s as kt,a as _t,b as bt,t as vt,q as wt,c as A,d as W,e as Tt,z as St,N as tt}from"./mermaid-vendor-d7rbry5E.js";import"./feature-graph-DbHHHM9y.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var H=function(){var t=s(function(g,r,a,l){for(a=a||{},l=g.length;l--;a[g[l]]=r);return a},"o"),e=[6,8,10,11,12,14,16,17,18],i=[1,9],c=[1,10],n=[1,11],u=[1,12],h=[1,13],f=[1,14],d={trace:s(function(){},"trace"),yy:{},symbols_:{error:2,start:3,journey:4,document:5,EOF:6,line:7,SPACE:8,statement:9,NEWLINE:10,title:11,acc_title:12,acc_title_value:13,acc_descr:14,acc_descr_value:15,acc_descr_multiline_value:16,section:17,taskName:18,taskData:19,$accept:0,$end:1},terminals_:{2:"error",4:"journey",6:"EOF",8:"SPACE",10:"NEWLINE",11:"title",12:"acc_title",13:"acc_title_value",14:"acc_descr",15:"acc_descr_value",16:"acc_descr_multiline_value",17:"section",18:"taskName",19:"taskData"},productions_:[0,[3,3],[5,0],[5,2],[7,2],[7,1],[7,1],[7,1],[9,1],[9,2],[9,2],[9,1],[9,1],[9,2]],performAction:s(function(r,a,l,y,p,o,S){var _=o.length-1;switch(p){case 1:return o[_-1];case 2:this.$=[];break;case 3:o[_-1].push(o[_]),this.$=o[_-1];break;case 4:case 5:this.$=o[_];break;case 6:case 7:this.$=[];break;case 8:y.setDiagramTitle(o[_].substr(6)),this.$=o[_].substr(6);break;case 9:this.$=o[_].trim(),y.setAccTitle(this.$);break;case 10:case 11:this.$=o[_].trim(),y.setAccDescription(this.$);break;case 12:y.addSection(o[_].substr(8)),this.$=o[_].substr(8);break;case 13:y.addTask(o[_-1],o[_]),this.$="task";break}},"anonymous"),table:[{3:1,4:[1,2]},{1:[3]},t(e,[2,2],{5:3}),{6:[1,4],7:5,8:[1,6],9:7,10:[1,8],11:i,12:c,14:n,16:u,17:h,18:f},t(e,[2,7],{1:[2,1]}),t(e,[2,3]),{9:15,11:i,12:c,14:n,16:u,17:h,18:f},t(e,[2,5]),t(e,[2,6]),t(e,[2,8]),{13:[1,16]},{15:[1,17]},t(e,[2,11]),t(e,[2,12]),{19:[1,18]},t(e,[2,4]),t(e,[2,9]),t(e,[2,10]),t(e,[2,13])],defaultActions:{},parseError:s(function(r,a){if(a.recoverable)this.trace(r);else{var l=new Error(r);throw l.hash=a,l}},"parseError"),parse:s(function(r){var a=this,l=[0],y=[],p=[null],o=[],S=this.table,_="",B=0,J=0,ut=2,K=1,yt=o.slice.call(arguments,1),k=Object.create(this.lexer),E={yy:{}};for(var O in this.yy)Object.prototype.hasOwnProperty.call(this.yy,O)&&(E.yy[O]=this.yy[O]);k.setInput(r,E.yy),E.yy.lexer=k,E.yy.parser=this,typeof k.yylloc>"u"&&(k.yylloc={});var Y=k.yylloc;o.push(Y);var dt=k.options&&k.options.ranges;typeof E.yy.parseError=="function"?this.parseError=E.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function ft(v){l.length=l.length-2*v,p.length=p.length-v,o.length=o.length-v}s(ft,"popStack");function Q(){var v;return v=y.pop()||k.lex()||K,typeof v!="number"&&(v instanceof Array&&(y=v,v=y.pop()),v=a.symbols_[v]||v),v}s(Q,"lex");for(var b,P,w,q,C={},N,$,D,j;;){if(P=l[l.length-1],this.defaultActions[P]?w=this.defaultActions[P]:((b===null||typeof b>"u")&&(b=Q()),w=S[P]&&S[P][b]),typeof w>"u"||!w.length||!w[0]){var G="";j=[];for(N in S[P])this.terminals_[N]&&N>ut&&j.push("'"+this.terminals_[N]+"'");k.showPosition?G="Parse error on line "+(B+1)+`:
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2
lightrag/api/webui/assets/kanban-definition-NDS4AKOZ-DDoftzBy.js → lightrag/api/webui/assets/kanban-definition-NDS4AKOZ-ZF435Bcq.js generated
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@ -1,4 +1,4 @@
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2
lightrag/api/webui/assets/mindmap-definition-ALO5MXBD-DGAXVsL1.js → lightrag/api/webui/assets/mindmap-definition-ALO5MXBD-BQ2T_hsy.js generated
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lightrag/api/webui/assets/pieDiagram-IB7DONF6-B0cIkycz.js → lightrag/api/webui/assets/pieDiagram-IB7DONF6-DrMdtRDI.js generated
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@ -1,4 +1,4 @@
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lightrag/api/webui/assets/requirementDiagram-KVF5MWMF-A4JwVpFF.js → lightrag/api/webui/assets/requirementDiagram-KVF5MWMF-CtVTOxeE.js generated
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lightrag/api/webui/assets/sankeyDiagram-QLVOVGJD-DkTUSo82.js → lightrag/api/webui/assets/sankeyDiagram-QLVOVGJD-CSLnqTKw.js generated
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lightrag/api/webui/assets/sequenceDiagram-X6HHIX6F-hDfAwQVw.js → lightrag/api/webui/assets/sequenceDiagram-X6HHIX6F-D6_yAdcj.js generated
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lightrag/api/webui/assets/stateDiagram-DGXRK772-CcL234E-.js → lightrag/api/webui/assets/stateDiagram-DGXRK772-BGTY-Rrs.js generated
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lightrag/api/webui/assets/stateDiagram-v2-YXO3MK2T-BnpIGSVY.js → lightrag/api/webui/assets/stateDiagram-v2-YXO3MK2T-C15fufgb.js generated
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@ -1 +1 @@
import{s as r,b as e,a,S as s}from"./chunk-AEK57VVT-BRJnVklE.js";import{_ as i}from"./mermaid-vendor-SwnP6Sr8.js";import"./chunk-RZ5BOZE2-vCqEaZEa.js";import"./feature-graph-D6-O-kXP.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var b={parser:a,get db(){return new s(2)},renderer:e,styles:r,init:i(t=>{t.state||(t.state={}),t.state.arrowMarkerAbsolute=t.arrowMarkerAbsolute},"init")};export{b as diagram};
import{s as r,b as e,a,S as s}from"./chunk-AEK57VVT-ZyE42AjE.js";import{_ as i}from"./mermaid-vendor-d7rbry5E.js";import"./chunk-RZ5BOZE2-C762jHXr.js";import"./feature-graph-DbHHHM9y.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var b={parser:a,get db(){return new s(2)},renderer:e,styles:r,init:i(t=>{t.state||(t.state={}),t.state.arrowMarkerAbsolute=t.arrowMarkerAbsolute},"init")};export{b as diagram};

2
lightrag/api/webui/assets/timeline-definition-BDJGKUSR-CFveliQS.js → lightrag/api/webui/assets/timeline-definition-BDJGKUSR-DdDk7fsZ.js generated
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@ -1,4 +1,4 @@
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import{_ as s,c as xt,l as T,d as q,a2 as kt,a3 as _t,a4 as bt,a5 as vt,N as nt,D as wt,a6 as St,z as Et}from"./mermaid-vendor-d7rbry5E.js";import"./feature-graph-DbHHHM9y.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var X=function(){var n=s(function(f,i,a,d){for(a=a||{},d=f.length;d--;a[f[d]]=i);return a},"o"),t=[6,8,10,11,12,14,16,17,20,21],e=[1,9],l=[1,10],r=[1,11],h=[1,12],c=[1,13],g=[1,16],m=[1,17],p={trace:s(function(){},"trace"),yy:{},symbols_:{error:2,start:3,timeline:4,document:5,EOF:6,line:7,SPACE:8,statement:9,NEWLINE:10,title:11,acc_title:12,acc_title_value:13,acc_descr:14,acc_descr_value:15,acc_descr_multiline_value:16,section:17,period_statement:18,event_statement:19,period:20,event:21,$accept:0,$end:1},terminals_:{2:"error",4:"timeline",6:"EOF",8:"SPACE",10:"NEWLINE",11:"title",12:"acc_title",13:"acc_title_value",14:"acc_descr",15:"acc_descr_value",16:"acc_descr_multiline_value",17:"section",20:"period",21:"event"},productions_:[0,[3,3],[5,0],[5,2],[7,2],[7,1],[7,1],[7,1],[9,1],[9,2],[9,2],[9,1],[9,1],[9,1],[9,1],[18,1],[19,1]],performAction:s(function(i,a,d,u,y,o,S){var k=o.length-1;switch(y){case 1:return o[k-1];case 2:this.$=[];break;case 3:o[k-1].push(o[k]),this.$=o[k-1];break;case 4:case 5:this.$=o[k];break;case 6:case 7:this.$=[];break;case 8:u.getCommonDb().setDiagramTitle(o[k].substr(6)),this.$=o[k].substr(6);break;case 9:this.$=o[k].trim(),u.getCommonDb().setAccTitle(this.$);break;case 10:case 11:this.$=o[k].trim(),u.getCommonDb().setAccDescription(this.$);break;case 12:u.addSection(o[k].substr(8)),this.$=o[k].substr(8);break;case 15:u.addTask(o[k],0,""),this.$=o[k];break;case 16:u.addEvent(o[k].substr(2)),this.$=o[k];break}},"anonymous"),table:[{3:1,4:[1,2]},{1:[3]},n(t,[2,2],{5:3}),{6:[1,4],7:5,8:[1,6],9:7,10:[1,8],11:e,12:l,14:r,16:h,17:c,18:14,19:15,20:g,21:m},n(t,[2,7],{1:[2,1]}),n(t,[2,3]),{9:18,11:e,12:l,14:r,16:h,17:c,18:14,19:15,20:g,21:m},n(t,[2,5]),n(t,[2,6]),n(t,[2,8]),{13:[1,19]},{15:[1,20]},n(t,[2,11]),n(t,[2,12]),n(t,[2,13]),n(t,[2,14]),n(t,[2,15]),n(t,[2,16]),n(t,[2,4]),n(t,[2,9]),n(t,[2,10])],defaultActions:{},parseError:s(function(i,a){if(a.recoverable)this.trace(i);else{var d=new Error(i);throw d.hash=a,d}},"parseError"),parse:s(function(i){var a=this,d=[0],u=[],y=[null],o=[],S=this.table,k="",M=0,P=0,B=2,J=1,O=o.slice.call(arguments,1),_=Object.create(this.lexer),E={yy:{}};for(var v in this.yy)Object.prototype.hasOwnProperty.call(this.yy,v)&&(E.yy[v]=this.yy[v]);_.setInput(i,E.yy),E.yy.lexer=_,E.yy.parser=this,typeof _.yylloc>"u"&&(_.yylloc={});var L=_.yylloc;o.push(L);var A=_.options&&_.options.ranges;typeof E.yy.parseError=="function"?this.parseError=E.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function R(I){d.length=d.length-2*I,y.length=y.length-I,o.length=o.length-I}s(R,"popStack");function z(){var I;return I=u.pop()||_.lex()||J,typeof I!="number"&&(I instanceof Array&&(u=I,I=u.pop()),I=a.symbols_[I]||I),I}s(z,"lex");for(var w,C,N,K,F={},j,$,et,G;;){if(C=d[d.length-1],this.defaultActions[C]?N=this.defaultActions[C]:((w===null||typeof w>"u")&&(w=z()),N=S[C]&&S[C][w]),typeof N>"u"||!N.length||!N[0]){var Q="";G=[];for(j in S[C])this.terminals_[j]&&j>B&&G.push("'"+this.terminals_[j]+"'");_.showPosition?Q="Parse error on line "+(M+1)+`:
`+_.showPosition()+`
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2
lightrag/api/webui/assets/xychartDiagram-VJFVF3MP-5OclOI0o.js → lightrag/api/webui/assets/xychartDiagram-VJFVF3MP-B3pR2K46.js generated
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lightrag/api/webui/index.html generated
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@ -5,21 +5,21 @@
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
<meta http-equiv="Pragma" content="no-cache" />
<meta http-equiv="Expires" content="0" />
<link rel="icon" type="image/svg+xml" href="logo.png" />
<link rel="icon" type="image/png" href="favicon.png" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Lightrag</title>
<script type="module" crossorigin src="/webui/assets/index-m6I92ZpT.js"></script>
<script type="module" crossorigin src="/webui/assets/index-Bj1VgJta.js"></script>
<link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
<link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
<link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">
<link rel="modulepreload" crossorigin href="/webui/assets/utils-vendor-BysuhMZA.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-D6-O-kXP.js">
<link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-SwnP6Sr8.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-DbHHHM9y.js">
<link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-d7rbry5E.js">
<link rel="modulepreload" crossorigin href="/webui/assets/markdown-vendor-BBaHfVvE.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-wTZcnY1B.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-BKQZIcI6.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-zozGWnLh.js">
<link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-ClbgnjXg.js">
<link rel="stylesheet" crossorigin href="/webui/assets/feature-graph-BipNuM18.css">
<link rel="stylesheet" crossorigin href="/webui/assets/index-CM0YrL-d.css">
<link rel="stylesheet" crossorigin href="/webui/assets/index-C3vR7z2U.css">
</head>
<body>
<div id="root"></div>

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1
lightrag/api/webui/logo.svg generated Executable file
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39
lightrag/kg/tidb_impl.py
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@ -23,6 +23,23 @@ if not pm.is_installed("sqlalchemy"):
from sqlalchemy import create_engine, text # type: ignore
def sanitize_sensitive_info(data: dict) -> dict:
sanitized_data = data.copy()
sensitive_fields = [
"password",
"user",
"host",
"database",
"port",
"ssl_verify_cert",
"ssl_verify_identity",
]
for field_name in sensitive_fields:
if field_name in sanitized_data:
sanitized_data[field_name] = "***"
return sanitized_data
class TiDB:
def __init__(self, config, **kwargs):
self.host = config.get("host", None)
@ -38,9 +55,9 @@ class TiDB:
try:
self.engine = create_engine(connection_string)
logger.info(f"Connected to TiDB database at {self.database}")
logger.info("Connected to TiDB database")
except Exception as e:
logger.error(f"Failed to connect to TiDB database at {self.database}")
logger.error("Failed to connect to TiDB database")
logger.error(f"TiDB database error: {e}")
raise
@ -55,13 +72,13 @@ class TiDB:
try:
await self.query(f"SELECT 1 FROM {k}".format(k=k))
except Exception as e:
logger.error(f"Failed to check table {k} in TiDB database")
logger.error("Failed to check table in TiDB database")
logger.error(f"TiDB database error: {e}")
try:
await self.execute(v["ddl"])
logger.info(f"Created table {k} in TiDB database")
logger.info("Created table in TiDB database")
except Exception as e:
logger.error(f"Failed to create table {k} in TiDB database")
logger.error("Failed to create table in TiDB database")
logger.error(f"TiDB database error: {e}")
# After all tables are created, try to migrate timestamp fields
@ -82,7 +99,11 @@ class TiDB:
try:
result = conn.execute(text(sql), params)
except Exception as e:
logger.error(f"Tidb database,\nsql:{sql},\nparams:{params},\nerror:{e}")
sanitized_params = sanitize_sensitive_info(params)
sanitized_error = sanitize_sensitive_info({"error": str(e)})
logger.error(
f"Tidb database,\nsql:{sql},\nparams:{sanitized_params},\nerror:{sanitized_error}"
)
raise
if multirows:
rows = result.all()
@ -107,7 +128,11 @@ class TiDB:
else:
conn.execute(text(sql), parameters=data)
except Exception as e:
logger.error(f"Tidb database,\nsql:{sql},\ndata:{data},\nerror:{e}")
sanitized_data = sanitize_sensitive_info(data) if data else None
sanitized_error = sanitize_sensitive_info({"error": str(e)})
logger.error(
f"Tidb database,\nsql:{sql},\ndata:{sanitized_data},\nerror:{sanitized_error}"
)
raise

6
lightrag/lightrag.py
View file

@ -24,7 +24,7 @@ from lightrag.constants import (
DEFAULT_MAX_TOKEN_SUMMARY,
DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE,
)
from lightrag.api.config import get_env_value
from lightrag.utils import get_env_value
from lightrag.kg import (
STORAGES,
@ -1026,7 +1026,7 @@ class LightRAG:
# Persistent llm cache
if self.llm_response_cache:
await self.llm_response_cache.index_done_callback
await self.llm_response_cache.index_done_callback()
# Update document status to failed
await self.doc_status.upsert(
@ -1108,7 +1108,7 @@ class LightRAG:
# Persistent llm cache
if self.llm_response_cache:
await self.llm_response_cache.index_done_callback
await self.llm_response_cache.index_done_callback()
# Update document status to failed
await self.doc_status.upsert(

13
lightrag/llm/openai.py
View file

@ -264,8 +264,17 @@ async def openai_complete_if_cache(
logger.warning(
f"Failed to close stream response in finally block: {close_error}"
)
# Note: We don't close the client here for streaming responses
# The client will be closed by the caller after streaming is complete
# This prevents resource leaks since the caller doesn't handle closing
try:
await openai_async_client.close()
logger.debug(
"Successfully closed OpenAI client for streaming response"
)
except Exception as client_close_error:
logger.warning(
f"Failed to close OpenAI client in streaming finally block: {client_close_error}"
)
return inner()

12
lightrag/operate.py
View file

@ -1615,6 +1615,12 @@ async def _find_most_related_edges_from_entities(
for pair in all_edges:
edge_props = edge_data_dict.get(pair)
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"
)
edge_props["weight"] = 0.0
combined = {
"src_tgt": pair,
"rank": edge_degrees_dict.get(pair, 0),
@ -1676,6 +1682,12 @@ async def _get_edge_data(
pair = (k["src_id"], k["tgt_id"])
edge_props = edge_data_dict.get(pair)
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"
)
edge_props["weight"] = 0.0
# Use edge degree from the batch as rank.
combined = {
"src_id": k["src_id"],

36
lightrag/utils.py
View file

@ -22,7 +22,38 @@ from lightrag.constants import (
DEFAULT_LOG_BACKUP_COUNT,
DEFAULT_LOG_FILENAME,
)
from lightrag.api.config import get_env_value
def get_env_value(
env_key: str, default: any, value_type: type = str, special_none: bool = False
) -> any:
"""
Get value from environment variable with type conversion
Args:
env_key (str): Environment variable key
default (any): Default value if env variable is not set
value_type (type): Type to convert the value to
special_none (bool): If True, return None when value is "None"
Returns:
any: Converted value from environment or default
"""
value = os.getenv(env_key)
if value is None:
return default
# Handle special case for "None" string
if special_none and value == "None":
return None
if value_type is bool:
return value.lower() in ("true", "1", "yes", "t", "on")
try:
return value_type(value)
except (ValueError, TypeError):
return default
# Use TYPE_CHECKING to avoid circular imports
if TYPE_CHECKING:
@ -295,6 +326,9 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
"""
def final_decro(func):
# Ensure func is callable
if not callable(func):
raise TypeError(f"Expected a callable object, got {type(func)}")
queue = asyncio.PriorityQueue(maxsize=max_queue_size)
tasks = set()
initialization_lock = asyncio.Lock()

2
lightrag_webui/index.html
View file

@ -5,7 +5,7 @@
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
<meta http-equiv="Pragma" content="no-cache" />
<meta http-equiv="Expires" content="0" />
<link rel="icon" type="image/svg+xml" href="logo.png" />
<link rel="icon" type="image/png" href="favicon.png" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Lightrag</title>
</head>

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39
lightrag_webui/src/components/graph/PropertyEditDialog.tsx
View file

@ -33,6 +33,8 @@ const PropertyEditDialog = ({
}: PropertyEditDialogProps) => {
const { t } = useTranslation()
const [value, setValue] = useState('')
// Add error state to display save failure messages
const [error, setError] = useState<string | null>(null)
// Initialize value when dialog opens
useEffect(() => {
@ -82,10 +84,20 @@ const PropertyEditDialog = ({
}
};
const handleSave = () => {
const handleSave = async () => {
if (value.trim() !== '') {
onSave(value)
onClose()
// Clear previous error messages
setError(null)
try {
await onSave(value)
onClose()
} catch (error) {
console.error('Save error:', error)
// Set error message to state for UI display
setError(typeof error === 'object' && error !== null
? (error as Error).message || t('common.saveFailed')
: t('common.saveFailed'))
}
}
}
@ -103,6 +115,13 @@ const PropertyEditDialog = ({
</DialogDescription>
</DialogHeader>
{/* Display error message if save fails */}
{error && (
<div className="bg-destructive/15 text-destructive px-4 py-2 rounded-md text-sm mt-2">
{error}
</div>
)}
{/* Multi-line text input using textarea */}
<div className="grid gap-4 py-4">
{(() => {
@ -141,7 +160,19 @@ const PropertyEditDialog = ({
onClick={handleSave}
disabled={isSubmitting}
>
{t('common.save')}
{isSubmitting ? (
<>
<span className="mr-2">
<svg className="animate-spin h-4 w-4" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24">
<circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
<path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
</svg>
</span>
{t('common.saving')}
</>
) : (
t('common.save')
)}
</Button>
</DialogFooter>
</DialogContent>

2
lightrag_webui/src/features/LoginPage.tsx
View file

@ -153,7 +153,7 @@ const LoginPage = () => {
<CardHeader className="flex items-center justify-center space-y-2 pb-8 pt-6">
<div className="flex flex-col items-center space-y-4">
<div className="flex items-center gap-3">
<img src="logo.png" alt="LightRAG Logo" className="h-12 w-12" />
<img src="logo.svg" alt="LightRAG Logo" className="h-12 w-12" />
<ZapIcon className="size-10 text-emerald-400" aria-hidden="true" />
</div>
<div className="text-center space-y-2">

1
lightrag_webui/src/features/SiteHeader.tsx
View file

@ -71,7 +71,6 @@ export default function SiteHeader() {
<div className="min-w-[200px] w-auto flex items-center">
<a href={webuiPrefix} className="flex items-center gap-2">
<ZapIcon className="size-4 text-emerald-400" aria-hidden="true" />
{/* <img src='/logo.png' className="size-4" /> */}
<span className="font-bold md:inline-block">{SiteInfo.name}</span>
</a>
{webuiTitle && (

4
lightrag_webui/src/locales/ar.json
View file

@ -34,7 +34,9 @@
},
"common": {
"cancel": "إلغاء",
"save": "حفظ"
"save": "حفظ",
"saving": "جارٍ الحفظ...",
"saveFailed": "فشل الحفظ"
},
"documentPanel": {
"clearDocuments": {

4
lightrag_webui/src/locales/en.json
View file

@ -34,7 +34,9 @@
},
"common": {
"cancel": "Cancel",
"save": "Save"
"save": "Save",
"saving": "Saving...",
"saveFailed": "Save failed"
},
"documentPanel": {
"clearDocuments": {

4
lightrag_webui/src/locales/fr.json
View file

@ -34,7 +34,9 @@
},
"common": {
"cancel": "Annuler",
"save": "Sauvegarder"
"save": "Sauvegarder",
"saving": "Sauvegarde en cours...",
"saveFailed": "Échec de la sauvegarde"
},
"documentPanel": {
"clearDocuments": {

4
lightrag_webui/src/locales/zh.json
View file

@ -34,7 +34,9 @@
},
"common": {
"cancel": "取消",
"save": "保存"
"save": "保存",
"saving": "保存中...",
"saveFailed": "保存失败"
},
"documentPanel": {
"clearDocuments": {

724
lightrag_webui/src/locales/zh_TW.json
View file

@ -1,365 +1,365 @@
{
"settings": {
"language": "語言",
"theme": "主題",
"light": "淺色",
"dark": "深色",
"system": "系統"
},
"header": {
"documents": "文件",
"knowledgeGraph": "知識圖譜",
"retrieval": "檢索",
"api": "API",
"projectRepository": "專案庫",
"logout": "登出",
"themeToggle": {
"switchToLight": "切換至淺色主題",
"switchToDark": "切換至深色主題"
}
},
"login": {
"description": "請輸入您的帳號和密碼登入系統",
"username": "帳號",
"usernamePlaceholder": "請輸入帳號",
"password": "密碼",
"passwordPlaceholder": "請輸入密碼",
"loginButton": "登入",
"loggingIn": "登入中...",
"successMessage": "登入成功",
"errorEmptyFields": "請輸入您的帳號和密碼",
"errorInvalidCredentials": "登入失敗，請檢查帳號和密碼",
"authDisabled": "認證已停用，使用免登入模式",
"guestMode": "免登入"
},
"common": {
"cancel": "取消",
"save": "儲存"
},
"documentPanel": {
"clearDocuments": {
"button": "清空",
"tooltip": "清空文件",
"title": "清空文件",
"description": "此操作將從系統中移除所有文件",
"warning": "警告：此操作將永久刪除所有文件，無法復原！",
"confirm": "確定要清空所有文件嗎？",
"confirmPrompt": "請輸入 yes 確認操作",
"confirmPlaceholder": "輸入 yes 以確認",
"clearCache": "清空 LLM 快取",
"confirmButton": "確定",
"success": "文件清空成功",
"cacheCleared": "快取清空成功",
"cacheClearFailed": "清空快取失敗：\n{{error}}",
"failed": "清空文件失敗：\n{{message}}",
"error": "清空文件失敗：\n{{error}}"
},
"uploadDocuments": {
"button": "上傳",
"tooltip": "上傳文件",
"title": "上傳文件",
"description": "拖曳檔案至此處或點擊瀏覽",
"single": {
"uploading": "正在上傳 {{name}}：{{percent}}%",
"success": "上傳成功：\n{{name}} 上傳完成",
"failed": "上傳失敗：\n{{name}}\n{{message}}",
"error": "上傳失敗：\n{{name}}\n{{error}}"
},
"batch": {
"uploading": "正在上傳檔案...",
"success": "檔案上傳完成",
"error": "部分檔案上傳失敗"
},
"generalError": "上傳失敗\n{{error}}",
"fileTypes": "支援的檔案類型：TXT, MD, DOCX, PDF, PPTX, RTF, ODT, EPUB, HTML, HTM, TEX, JSON, XML, YAML, YML, CSV, LOG, CONF, INI, PROPERTIES, SQL, BAT, SH, C, CPP, PY, JAVA, JS, TS, SWIFT, GO, RB, PHP, CSS, SCSS, LESS",
"fileUploader": {
"singleFileLimit": "一次只能上傳一個檔案",
"maxFilesLimit": "最多只能上傳 {{count}} 個檔案",
"fileRejected": "檔案 {{name}} 被拒絕",
"unsupportedType": "不支援的檔案類型",
"fileTooLarge": "檔案過大，最大允許 {{maxSize}}",
"dropHere": "將檔案拖放至此處",
"dragAndDrop": "拖放檔案至此處，或點擊選擇檔案",
"removeFile": "移除檔案",
"uploadDescription": "您可以上傳{{isMultiple ? '多個' : count}}個檔案（每個檔案最大{{maxSize}}）",
"duplicateFile": "檔案名稱與伺服器上的快取重複"
}
},
"documentManager": {
"title": "文件管理",
"scanButton": "掃描",
"scanTooltip": "掃描輸入目錄中的文件",
"pipelineStatusButton": "pipeline 狀態",
"pipelineStatusTooltip": "查看pipeline 狀態",
"uploadedTitle": "已上傳文件",
"uploadedDescription": "已上傳文件清單及其狀態",
"emptyTitle": "無文件",
"emptyDescription": "尚未上傳任何文件",
"columns": {
"id": "ID",
"summary": "摘要",
"status": "狀態",
"length": "長度",
"chunks": "分塊",
"created": "建立時間",
"updated": "更新時間",
"metadata": "元資料"
},
"status": {
"all": "全部",
"completed": "已完成",
"processing": "處理中",
"pending": "等待中",
"failed": "失敗"
},
"errors": {
"loadFailed": "載入文件失敗\n{{error}}",
"scanFailed": "掃描文件失敗\n{{error}}",
"scanProgressFailed": "取得掃描進度失敗\n{{error}}"
},
"fileNameLabel": "檔案名稱",
"showButton": "顯示",
"hideButton": "隱藏",
"showFileNameTooltip": "顯示檔案名稱",
"hideFileNameTooltip": "隱藏檔案名稱"
},
"pipelineStatus": {
"title": "pipeline 狀態",
"busy": "pipeline 忙碌中",
"requestPending": "待處理請求",
"jobName": "工作名稱",
"startTime": "開始時間",
"progress": "進度",
"unit": "梯次",
"latestMessage": "最新訊息",
"historyMessages": "歷史訊息",
"errors": {
"fetchFailed": "取得pipeline 狀態失敗\n{{error}}"
}
}
},
"graphPanel": {
"dataIsTruncated": "圖資料已截斷至最大回傳節點數",
"statusDialog": {
"title": "LightRAG 伺服器設定",
"description": "查看目前系統狀態和連線資訊"
},
"legend": "圖例",
"nodeTypes": {
"person": "人物角色",
"category": "分類",
"geo": "地理名稱",
"location": "位置",
"organization": "組織機構",
"event": "事件",
"equipment": "設備",
"weapon": "武器",
"animal": "動物",
"unknown": "未知",
"object": "物品",
"group": "群組",
"technology": "技術"
},
"sideBar": {
"settings": {
"settings": "設定",
"healthCheck": "健康檢查",
"showPropertyPanel": "顯示屬性面板",
"showSearchBar": "顯示搜尋列",
"showNodeLabel": "顯示節點標籤",
"nodeDraggable": "節點可拖曳",
"showEdgeLabel": "顯示 Edge 標籤",
"hideUnselectedEdges": "隱藏未選取的 Edge",
"edgeEvents": "Edge 事件",
"maxQueryDepth": "最大查詢深度",
"maxNodes": "最大回傳節點數",
"maxLayoutIterations": "最大版面配置迭代次數",
"resetToDefault": "重設為預設值",
"edgeSizeRange": "Edge 粗細範圍",
"depth": "深度",
"max": "最大值",
"degree": "鄰邊",
"apiKey": "API key",
"enterYourAPIkey": "輸入您的 API key",
"save": "儲存",
"refreshLayout": "重新整理版面配置"
},
"zoomControl": {
"zoomIn": "放大",
"zoomOut": "縮小",
"resetZoom": "重設縮放",
"rotateCamera": "順時針旋轉圖形",
"rotateCameraCounterClockwise": "逆時針旋轉圖形"
},
"layoutsControl": {
"startAnimation": "繼續版面配置動畫",
"stopAnimation": "停止版面配置動畫",
"layoutGraph": "圖形版面配置",
"layouts": {
"Circular": "環形",
"Circlepack": "圓形打包",
"Random": "隨機",
"Noverlaps": "無重疊",
"Force Directed": "力導向",
"Force Atlas": "力圖"
}
},
"fullScreenControl": {
"fullScreen": "全螢幕",
"windowed": "視窗"
},
"legendControl": {
"toggleLegend": "切換圖例顯示"
}
},
"statusIndicator": {
"connected": "已連線",
"disconnected": "未連線"
},
"statusCard": {
"unavailable": "狀態資訊不可用",
"storageInfo": "儲存資訊",
"workingDirectory": "工作目錄",
"inputDirectory": "輸入目錄",
"llmConfig": "LLM 設定",
"llmBinding": "LLM 綁定",
"llmBindingHost": "LLM 綁定主機",
"llmModel": "LLM 模型",
"maxTokens": "最大權杖數",
"embeddingConfig": "嵌入設定",
"embeddingBinding": "嵌入綁定",
"embeddingBindingHost": "嵌入綁定主機",
"embeddingModel": "嵌入模型",
"storageConfig": "儲存設定",
"kvStorage": "KV 儲存",
"docStatusStorage": "文件狀態儲存",
"graphStorage": "圖形儲存",
"vectorStorage": "向量儲存"
},
"propertiesView": {
"editProperty": "編輯{{property}}",
"editPropertyDescription": "在下方文字區域編輯屬性值。",
"errors": {
"duplicateName": "節點名稱已存在",
"updateFailed": "更新節點失敗",
"tryAgainLater": "請稍後重試"
},
"success": {
"entityUpdated": "節點更新成功",
"relationUpdated": "關係更新成功"
},
"node": {
"title": "節點",
"id": "ID",
"labels": "標籤",
"degree": "度數",
"properties": "屬性",
"relationships": "關係(子圖內)",
"expandNode": "展開節點",
"pruneNode": "修剪節點",
"deleteAllNodesError": "拒絕刪除圖中的所有節點",
"nodesRemoved": "已刪除 {{count}} 個節點，包括孤立節點",
"noNewNodes": "沒有發現可以展開的節點",
"propertyNames": {
"description": "描述",
"entity_id": "名稱",
"entity_type": "類型",
"source_id": "來源ID",
"Neighbour": "鄰接",
"file_path": "來源",
"keywords": "Keys",
"weight": "權重"
}
},
"edge": {
"title": "關係",
"id": "ID",
"type": "類型",
"source": "來源節點",
"target": "目標節點",
"properties": "屬性"
}
},
"search": {
"placeholder": "搜尋節點...",
"message": "還有 {count} 個"
},
"graphLabels": {
"selectTooltip": "選擇查詢標籤",
"noLabels": "未找到標籤",
"label": "標籤",
"placeholder": "搜尋標籤...",
"andOthers": "還有 {count} 個",
"refreshTooltip": "重載圖形數據(新增檔案後需重載)"
},
"emptyGraph": "無數據(請重載圖形數據)"
},
"retrievePanel": {
"chatMessage": {
"copyTooltip": "複製到剪貼簿",
"copyError": "複製文字到剪貼簿失敗"
},
"retrieval": {
"startPrompt": "輸入查詢開始檢索",
"clear": "清空",
"send": "送出",
"placeholder": "輸入查詢內容 (支援模式前綴：/<Query Mode>)",
"error": "錯誤：取得回應失敗",
"queryModeError": "僅支援以下查詢模式：{{modes}}",
"queryModePrefixInvalid": "無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"
},
"querySettings": {
"parametersTitle": "參數",
"parametersDescription": "設定查詢參數",
"queryMode": "查詢模式",
"queryModeTooltip": "選擇檢索策略：\n• Naive：基礎搜尋，無進階技術\n• Local：上下文相關資訊檢索\n• Global：利用全域知識庫\n• Hybrid：結合本地和全域檢索\n• Mix：整合知識圖譜和向量檢索\n• Bypass：直接傳遞查詢到LLM，不進行檢索",
"queryModeOptions": {
"naive": "Naive",
"local": "Local",
"global": "Global",
"hybrid": "Hybrid",
"mix": "Mix",
"bypass": "Bypass"
},
"responseFormat": "回應格式",
"responseFormatTooltip": "定義回應格式。例如：\n• 多段落\n• 單段落\n• 重點",
"responseFormatOptions": {
"multipleParagraphs": "多段落",
"singleParagraph": "單段落",
"bulletPoints": "重點"
},
"topK": "Top K結果",
"topKTooltip": "檢索的前幾項結果數。在'local'模式下表示實體，在'global'模式下表示關係",
"topKPlaceholder": "結果數量",
"maxTokensTextUnit": "文字單元最大權杖數",
"maxTokensTextUnitTooltip": "每個檢索文字區塊允許的最大權杖數",
"maxTokensGlobalContext": "全域上下文最大權杖數",
"maxTokensGlobalContextTooltip": "全域檢索中關係描述的最大權杖數",
"maxTokensLocalContext": "本地上下文最大權杖數",
"maxTokensLocalContextTooltip": "本地檢索中實體描述的最大權杖數",
"historyTurns": "歷史輪次",
"historyTurnsTooltip": "回應上下文中考慮的完整對話輪次（使用者-助手對）數量",
"historyTurnsPlaceholder": "歷史輪次數",
"hlKeywords": "進階關鍵字",
"hlKeywordsTooltip": "檢索中優先考慮的進階關鍵字清單。用逗號分隔",
"hlkeywordsPlaceHolder": "輸入關鍵字",
"llKeywords": "基礎關鍵字",
"llKeywordsTooltip": "用於細化檢索重點的基礎關鍵字清單。用逗號分隔",
"onlyNeedContext": "僅需上下文",
"onlyNeedContextTooltip": "如果為True，僅回傳檢索到的上下文而不產生回應",
"onlyNeedPrompt": "僅需提示",
"onlyNeedPromptTooltip": "如果為True，僅回傳產生的提示而不產生回應",
"streamResponse": "串流回應",
"streamResponseTooltip": "如果為True，啟用即時串流輸出回應"
}
},
"apiSite": {
"loading": "正在載入 API 文件..."
},
"apiKeyAlert": {
"title": "需要 API key",
"description": "請輸入您的 API key 以存取服務",
"placeholder": "請輸入 API key",
"save": "儲存"
"settings": {
"language": "語言",
"theme": "主題",
"light": "淺色",
"dark": "深色",
"system": "系統"
},
"header": {
"documents": "文件",
"knowledgeGraph": "知識圖譜",
"retrieval": "檢索",
"api": "API",
"projectRepository": "專案庫",
"logout": "登出",
"themeToggle": {
"switchToLight": "切換至淺色主題",
"switchToDark": "切換至深色主題"
}
},
"login": {
"description": "請輸入您的帳號和密碼登入系統",
"username": "帳號",
"usernamePlaceholder": "請輸入帳號",
"password": "密碼",
"passwordPlaceholder": "請輸入密碼",
"loginButton": "登入",
"loggingIn": "登入中...",
"successMessage": "登入成功",
"errorEmptyFields": "請輸入您的帳號和密碼",
"errorInvalidCredentials": "登入失敗，請檢查帳號和密碼",
"authDisabled": "認證已停用，使用免登入模式",
"guestMode": "免登入"
},
"common": {
"cancel": "取消",
"save": "儲存",
"saving": "儲存中...",
"saveFailed": "儲存失敗"
},
"documentPanel": {
"clearDocuments": {
"button": "清空",
"tooltip": "清空文件",
"title": "清空文件",
"description": "此操作將從系統中移除所有文件",
"warning": "警告：此操作將永久刪除所有文件，無法復原！",
"confirm": "確定要清空所有文件嗎？",
"confirmPrompt": "請輸入 yes 確認操作",
"confirmPlaceholder": "輸入 yes 以確認",
"clearCache": "清空 LLM 快取",
"confirmButton": "確定",
"success": "文件清空成功",
"cacheCleared": "快取清空成功",
"cacheClearFailed": "清空快取失敗：\n{{error}}",
"failed": "清空文件失敗：\n{{message}}",
"error": "清空文件失敗：\n{{error}}"
},
"uploadDocuments": {
"button": "上傳",
"tooltip": "上傳文件",
"title": "上傳文件",
"description": "拖曳檔案至此處或點擊瀏覽",
"single": {
"uploading": "正在上傳 {{name}}：{{percent}}%",
"success": "上傳成功：\n{{name}} 上傳完成",
"failed": "上傳失敗：\n{{name}}\n{{message}}",
"error": "上傳失敗：\n{{name}}\n{{error}}"
},
"batch": {
"uploading": "正在上傳檔案...",
"success": "檔案上傳完成",
"error": "部分檔案上傳失敗"
},
"generalError": "上傳失敗\n{{error}}",
"fileTypes": "支援的檔案類型：TXT, MD, DOCX, PDF, PPTX, RTF, ODT, EPUB, HTML, HTM, TEX, JSON, XML, YAML, YML, CSV, LOG, CONF, INI, PROPERTIES, SQL, BAT, SH, C, CPP, PY, JAVA, JS, TS, SWIFT, GO, RB, PHP, CSS, SCSS, LESS",
"fileUploader": {
"singleFileLimit": "一次只能上傳一個檔案",
"maxFilesLimit": "最多只能上傳 {{count}} 個檔案",
"fileRejected": "檔案 {{name}} 被拒絕",
"unsupportedType": "不支援的檔案類型",
"fileTooLarge": "檔案過大，最大允許 {{maxSize}}",
"dropHere": "將檔案拖放至此處",
"dragAndDrop": "拖放檔案至此處，或點擊選擇檔案",
"removeFile": "移除檔案",
"uploadDescription": "您可以上傳{{isMultiple ? '多個' : count}}個檔案（每個檔案最大{{maxSize}}）",
"duplicateFile": "檔案名稱與伺服器上的快取重複"
}
},
"documentManager": {
"title": "文件管理",
"scanButton": "掃描",
"scanTooltip": "掃描輸入目錄中的文件",
"pipelineStatusButton": "pipeline 狀態",
"pipelineStatusTooltip": "查看pipeline 狀態",
"uploadedTitle": "已上傳文件",
"uploadedDescription": "已上傳文件清單及其狀態",
"emptyTitle": "無文件",
"emptyDescription": "尚未上傳任何文件",
"columns": {
"id": "ID",
"summary": "摘要",
"status": "狀態",
"length": "長度",
"chunks": "分塊",
"created": "建立時間",
"updated": "更新時間",
"metadata": "元資料"
},
"status": {
"all": "全部",
"completed": "已完成",
"processing": "處理中",
"pending": "等待中",
"failed": "失敗"
},
"errors": {
"loadFailed": "載入文件失敗\n{{error}}",
"scanFailed": "掃描文件失敗\n{{error}}",
"scanProgressFailed": "取得掃描進度失敗\n{{error}}"
},
"fileNameLabel": "檔案名稱",
"showButton": "顯示",
"hideButton": "隱藏",
"showFileNameTooltip": "顯示檔案名稱",
"hideFileNameTooltip": "隱藏檔案名稱"
},
"pipelineStatus": {
"title": "pipeline 狀態",
"busy": "pipeline 忙碌中",
"requestPending": "待處理請求",
"jobName": "工作名稱",
"startTime": "開始時間",
"progress": "進度",
"unit": "梯次",
"latestMessage": "最新訊息",
"historyMessages": "歷史訊息",
"errors": {
"fetchFailed": "取得pipeline 狀態失敗\n{{error}}"
}
}
},
"graphPanel": {
"dataIsTruncated": "圖資料已截斷至最大回傳節點數",
"statusDialog": {
"title": "LightRAG 伺服器設定",
"description": "查看目前系統狀態和連線資訊"
},
"legend": "圖例",
"nodeTypes": {
"person": "人物角色",
"category": "分類",
"geo": "地理名稱",
"location": "位置",
"organization": "組織機構",
"event": "事件",
"equipment": "設備",
"weapon": "武器",
"animal": "動物",
"unknown": "未知",
"object": "物品",
"group": "群組",
"technology": "技術"
},
"sideBar": {
"settings": {
"settings": "設定",
"healthCheck": "健康檢查",
"showPropertyPanel": "顯示屬性面板",
"showSearchBar": "顯示搜尋列",
"showNodeLabel": "顯示節點標籤",
"nodeDraggable": "節點可拖曳",
"showEdgeLabel": "顯示 Edge 標籤",
"hideUnselectedEdges": "隱藏未選取的 Edge",
"edgeEvents": "Edge 事件",
"maxQueryDepth": "最大查詢深度",
"maxNodes": "最大回傳節點數",
"maxLayoutIterations": "最大版面配置迭代次數",
"resetToDefault": "重設為預設值",
"edgeSizeRange": "Edge 粗細範圍",
"depth": "深度",
"max": "最大值",
"degree": "鄰邊",
"apiKey": "API key",
"enterYourAPIkey": "輸入您的 API key",
"save": "儲存",
"refreshLayout": "重新整理版面配置"
},
"zoomControl": {
"zoomIn": "放大",
"zoomOut": "縮小",
"resetZoom": "重設縮放",
"rotateCamera": "順時針旋轉圖形",
"rotateCameraCounterClockwise": "逆時針旋轉圖形"
},
"layoutsControl": {
"startAnimation": "繼續版面配置動畫",
"stopAnimation": "停止版面配置動畫",
"layoutGraph": "圖形版面配置",
"layouts": {
"Circular": "環形",
"Circlepack": "圓形打包",
"Random": "隨機",
"Noverlaps": "無重疊",
"Force Directed": "力導向",
"Force Atlas": "力圖"
}
},
"fullScreenControl": {
"fullScreen": "全螢幕",
"windowed": "視窗"
},
"legendControl": {
"toggleLegend": "切換圖例顯示"
}
},
"statusIndicator": {
"connected": "已連線",
"disconnected": "未連線"
},
"statusCard": {
"unavailable": "狀態資訊不可用",
"storageInfo": "儲存資訊",
"workingDirectory": "工作目錄",
"inputDirectory": "輸入目錄",
"llmConfig": "LLM 設定",
"llmBinding": "LLM 綁定",
"llmBindingHost": "LLM 綁定主機",
"llmModel": "LLM 模型",
"maxTokens": "最大權杖數",
"embeddingConfig": "嵌入設定",
"embeddingBinding": "嵌入綁定",
"embeddingBindingHost": "嵌入綁定主機",
"embeddingModel": "嵌入模型",
"storageConfig": "儲存設定",
"kvStorage": "KV 儲存",
"docStatusStorage": "文件狀態儲存",
"graphStorage": "圖形儲存",
"vectorStorage": "向量儲存"
},
"propertiesView": {
"editProperty": "編輯{{property}}",
"editPropertyDescription": "在下方文字區域編輯屬性值。",
"errors": {
"duplicateName": "節點名稱已存在",
"updateFailed": "更新節點失敗",
"tryAgainLater": "請稍後重試"
},
"success": {
"entityUpdated": "節點更新成功",
"relationUpdated": "關係更新成功"
},
"node": {
"title": "節點",
"id": "ID",
"labels": "標籤",
"degree": "度數",
"properties": "屬性",
"relationships": "關係(子圖內)",
"expandNode": "展開節點",
"pruneNode": "修剪節點",
"deleteAllNodesError": "拒絕刪除圖中的所有節點",
"nodesRemoved": "已刪除 {{count}} 個節點，包括孤立節點",
"noNewNodes": "沒有發現可以展開的節點",
"propertyNames": {
"description": "描述",
"entity_id": "名稱",
"entity_type": "類型",
"source_id": "來源ID",
"Neighbour": "鄰接",
"file_path": "來源",
"keywords": "Keys",
"weight": "權重"
}
},
"edge": {
"title": "關係",
"id": "ID",
"type": "類型",
"source": "來源節點",
"target": "目標節點",
"properties": "屬性"
}
},
"search": {
"placeholder": "搜尋節點...",
"message": "還有 {count} 個"
},
"graphLabels": {
"selectTooltip": "選擇查詢標籤",
"noLabels": "未找到標籤",
"label": "標籤",
"placeholder": "搜尋標籤...",
"andOthers": "還有 {count} 個",
"refreshTooltip": "重載圖形數據(新增檔案後需重載)"
},
"emptyGraph": "無數據(請重載圖形數據)"
},
"retrievePanel": {
"chatMessage": {
"copyTooltip": "複製到剪貼簿",
"copyError": "複製文字到剪貼簿失敗"
},
"retrieval": {
"startPrompt": "輸入查詢開始檢索",
"clear": "清空",
"send": "送出",
"placeholder": "輸入查詢內容 (支援模式前綴：/<Query Mode>)",
"error": "錯誤：取得回應失敗",
"queryModeError": "僅支援以下查詢模式：{{modes}}",
"queryModePrefixInvalid": "無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"
},
"querySettings": {
"parametersTitle": "參數",
"parametersDescription": "設定查詢參數",
"queryMode": "查詢模式",
"queryModeTooltip": "選擇檢索策略：\n• Naive：基礎搜尋，無進階技術\n• Local：上下文相關資訊檢索\n• Global：利用全域知識庫\n• Hybrid：結合本地和全域檢索\n• Mix：整合知識圖譜和向量檢索\n• Bypass：直接傳遞查詢到LLM，不進行檢索",
"queryModeOptions": {
"naive": "Naive",
"local": "Local",
"global": "Global",
"hybrid": "Hybrid",
"mix": "Mix",
"bypass": "Bypass"
},
"responseFormat": "回應格式",
"responseFormatTooltip": "定義回應格式。例如：\n• 多段落\n• 單段落\n• 重點",
"responseFormatOptions": {
"multipleParagraphs": "多段落",
"singleParagraph": "單段落",
"bulletPoints": "重點"
},
"topK": "Top K結果",
"topKTooltip": "檢索的前幾項結果數。在'local'模式下表示實體，在'global'模式下表示關係",
"topKPlaceholder": "結果數量",
"maxTokensTextUnit": "文字單元最大權杖數",
"maxTokensTextUnitTooltip": "每個檢索文字區塊允許的最大權杖數",
"maxTokensGlobalContext": "全域上下文最大權杖數",
"maxTokensGlobalContextTooltip": "全域檢索中關係描述的最大權杖數",
"maxTokensLocalContext": "本地上下文最大權杖數",
"maxTokensLocalContextTooltip": "本地檢索中實體描述的最大權杖數",
"historyTurns": "歷史輪次",
"historyTurnsTooltip": "回應上下文中考慮的完整對話輪次（使用者-助手對）數量",
"historyTurnsPlaceholder": "歷史輪次數",
"onlyNeedContext": "僅需上下文",
"onlyNeedContextTooltip": "如果為True，僅回傳檢索到的上下文而不產生回應",
"onlyNeedPrompt": "僅需提示",
"onlyNeedPromptTooltip": "如果為True，僅回傳產生的提示而不產生回應",
"streamResponse": "串流回應",
"streamResponseTooltip": "如果為True，啟用即時串流輸出回應",
"userPrompt": "用戶提示詞",
"userPromptTooltip": "向LLM提供額外的響應要求（與查詢內容無關，僅用於處理輸出）。",
"userPromptPlaceholder": "輸入自定義提示詞（可選）"
}
},
"apiSite": {
"loading": "正在載入 API 文件..."
},
"apiKeyAlert": {
"title": "需要 API key",
"description": "請輸入您的 API key 以存取服務",
"placeholder": "請輸入 API key",
"save": "儲存"
}
}