From a1fb20998b1beb8892f093d42606d38cc0ddae18 Mon Sep 17 00:00:00 2001 From: "jinli.yl" Date: Tue, 9 Sep 2025 12:30:40 +0800 Subject: [PATCH] docs(service): update service description layout and content - Adjust column widths for better readability - Capitalize table header text - Replace 'Desc' with 'Description' for clarity - Make 'Note' column more concise and include GitHub link - Update environment variable information formatting --- reme_ai/service/service_description.md | 52 ++++++++++++++------------ 1 file changed, 29 insertions(+), 23 deletions(-) diff --git a/reme_ai/service/service_description.md b/reme_ai/service/service_description.md index 81a45184..59c0beb1 100644 --- a/reme_ai/service/service_description.md +++ b/reme_ai/service/service_description.md @@ -1,24 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - +
memory typeimportDescNote
ReMe.PersonalMemoryServicefrom reme_ai.service.personal_memory_service import PersonalMemoryServiceReMe's personalized memory service (formerly MemoryScope) empowers you to generate, retrieve, and share customized memories. Leveraging advanced LLM, embedding, and vector store technologies, it builds a comprehensive memory system with intelligent, context- and time-aware memory management—seamlessly enabling you to configure and deploy powerful AI agents.https://github.com/modelscope/ReMe Need to configure environment variables: FLOW_EMBEDDING_API_KEY, FLOW_EMBEDDING_BASE_URL, FLOW_LLM_API_KEY and FLOW_LLM_BASE_URL
ReMe.TaskMemoryServicefrom reme_ai.service.task_memory_service import TaskMemoryServiceReMe's task-oriented memory service helps you efficiently manage and schedule task-related memories, enhancing both the accuracy and efficiency of task execution. Powered by LLM capabilities, it supports flexible creation, retrieval, update, and deletion of memories across diverse task scenarios—enabling you to effortlessly build and scale robust agent-based task systems.the same as ReMe.PersonalMemoryService
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Memory TypeImportNoteDescription
ReMe.PersonalMemoryServicefrom reme_ai.service.personal_memory_service import PersonalMemoryServiceGitHub
Env: FLOW_EMBEDDING_API_KEY, FLOW_EMBEDDING_BASE_URL, FLOW_LLM_API_KEY, FLOW_LLM_BASE_URL		ReMe's personalized memory service (formerly MemoryScope) empowers you to generate, retrieve, and share customized memories. Leveraging advanced LLM, embedding, and vector store technologies, it builds a comprehensive memory system with intelligent, context- and time-aware memory management—seamlessly enabling you to configure and deploy powerful AI agents.
ReMe.TaskMemoryServicefrom reme_ai.service.task_memory_service import TaskMemoryServiceSame as aboveReMe's task-oriented memory service helps you efficiently manage and schedule task-related memories, enhancing both the accuracy and efficiency of task execution. Powered by LLM capabilities, it supports flexible creation, retrieval, update, and deletion of memories across diverse task scenarios—enabling you to effortlessly build and scale robust agent-based task systems.