'commit'

dsLightRag/Config/Config.py

@@ -3,15 +3,15 @@ ALY_AK = 'LTAI5tE4tgpGcKWhbZg6C4bh'
 ALY_SK = 'oizcTOZ8izbGUouboC00RcmGE8vBQ1'
 
 # 大模型 【DeepSeek深度求索官方】
-# LLM_API_KEY = "sk-44ae895eeb614aa1a9c6460579e322f1"
+LLM_API_KEY = "sk-44ae895eeb614aa1a9c6460579e322f1"
-# LLM_BASE_URL = "https://api.deepseek.com"
+LLM_BASE_URL = "https://api.deepseek.com"
-# LLM_MODEL_NAME = "deepseek-chat"
+LLM_MODEL_NAME = "deepseek-chat"
 
 # 阿里云提供的大模型服务
-LLM_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
+#LLM_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
-LLM_BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+#LLM_BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 # LLM_MODEL_NAME = "qwen-plus" # 不要使用通义千问，会导致化学方程式不正确！
-LLM_MODEL_NAME = "deepseek-v3"
+#LLM_MODEL_NAME = "deepseek-v3"
 
 EMBED_MODEL_NAME = "BAAI/bge-m3"
 EMBED_API_KEY = "sk-pbqibyjwhrgmnlsmdygplahextfaclgnedetybccknxojlyl"

dsLightRag/Doc/8、使用PG数据库.md

@@ -6,6 +6,7 @@ docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/shangor/postgres-
 
 - 启动
 ```
-docker rm if -f postgres-LightRag
+docker ps -a
+docker rm  -f 7a41327deb45
 docker run -p 5432:5432 -d --name postgres-LightRag shangor/postgres-for-rag sh -c "service postgresql start && sleep infinity"
 ```

dsLightRag/Test/T1_WriteToPg.py

@@ -21,7 +21,7 @@ logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO)
 
 async def main():
     try:
-        rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR,namespace_prefix='huanghai')
+        rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR)
         with open(f"../Txt/sushi.txt", "r", encoding="utf-8") as f:
             await rag.ainsert(f.read())
     finally:

dsLightRag/Util/LightRagUtil.py

@@ -152,7 +152,7 @@ os.environ["POSTGRES_PASSWORD"] = POSTGRES_PASSWORD
 os.environ["POSTGRES_DATABASE"] = POSTGRES_DATABASE
 
 
-async def initialize_pg_rag(WORKING_DIR, namespace_prefix):
+async def initialize_pg_rag(WORKING_DIR):
     rag = LightRAG(
         working_dir=WORKING_DIR,
         llm_model_func=llm_model_func,
@@ -169,8 +169,7 @@ async def initialize_pg_rag(WORKING_DIR, namespace_prefix):
         doc_status_storage="PGDocStatusStorage",
         graph_storage="PGGraphStorage",
         vector_storage="PGVectorStorage",
-        auto_manage_storages_states=False,
+        auto_manage_storages_states=False
-        namespace_prefix=namespace_prefix,
     )
 
     await rag.initialize_storages()