上传文件至 kg_lab_6.13

6.18 更新数据配置路径统一，和前端demo

kg_lab_6.13/vector_lab.py

@@ -7,6 +7,8 @@ import requests
 import httpx
 import logging
 
+from extraction_info import info_data_txt, info_faiss_archived
+
 class SiliconFlowEmbeddings(Embeddings):
     """SiliconFlow嵌入模型封装"""
     def __init__(self, api_key: str, model: str = "bge-m3"):
@@ -39,15 +41,15 @@ class SiliconFlowEmbeddings(Embeddings):
 # embeddings = Embedding(url="http://10.1.16.39:9995/v1", api_key="xxx", model_name="bge-m3")
 embeddings  = SiliconFlowEmbeddings(api_key="xxx")
 
-with open("./data/data.txt", 'r', encoding='utf-8') as file:
+with open(info_data_txt, 'r', encoding='utf-8') as file:
     txt_list = [line.strip() for line in file]
 
 # embedding_path = "/data/Z_LLM_data/Embed_data/bge-m3"
 # embeddings = HuggingFaceEmbeddings(model_name=embedding_path)
 
-faiss_archived = "./data/faiss_data/data"
+# faiss_archived = "./data/faiss_data/data"
 vectorstore_txt_faiss = FAISS.from_texts(txt_list, embeddings)
-vectorstore_txt_faiss.save_local(faiss_archived)
+vectorstore_txt_faiss.save_local(info_faiss_archived)
 
 retriever_txt_faiss1 = vectorstore_txt_faiss.as_retriever(search_kwargs={"k":3})
 retriever_txt_faiss2 = vectorstore_txt_faiss.as_retriever(