但是有可能考虑到使用ConversationChain时会导致输入的内容超过模型输入的上下文,所以适用了ConversationSummaryMemory,就是让模型自己对过去的对话进行总结,但是这种方式可能会丢失一定的关键信息。 from langchain.chains import ConversationChain from langchain.memory import ConversationSummaryMemory from langchain.prompts i...
\"""#定义ConversationSummaryBufferMemory组件memory=ConversationSummaryBufferMemory(llm=llm,max_token_limit=100)memory.save_context({"input":"你好"},{"output":"什么事?"})memory.save_context({"input":"没啥事情, 有个小问题请教"},{"output":"好的,请说"})memory.save_context({"input":"今天的...
Memory之内置模块ConversationSummaryMemory 3.0万 未经授权,禁止转载了解课程 本视频需付费,请购买课程后观看视频。收藏讨论 分享 课程介绍 讨论 适合人群 适合所有对大模型技术感兴趣的同学 你将会学到 精通商业级 RAG 系统设计,学员将具备设计复杂、高效率的商业级 RAG 系统的技能 课程简介 扫码加好友享受答疑服务!
Need support for async memory, especially for ConversationSummaryMemory and ConversationSummaryBufferMemory libs/core/langchain_core/chat_history.py libs/langchain/langchain/chains/conversation/base.py This response is meant to be useful and save you time. It is not meant to be a precise solution...
I will use another memory card. 表示 Tony 的爸爸同意借相机,并建议使用另一张存储卡。 * I will do what you tell me to do. 表示 Tony 答应好好保管相机。 问题答案: 1. 使用另一张存储卡。 2. 当你不知道如何使用相机时。 3. 每天。 4. 100 页。 5. www.google.com。 反馈 收藏 ...
Resource-Constrained Environments:Systems with limited memory availability, where simplification is critical for performance. Algorithmic Flow Message Count Check:Iflen(history) > target_count + threshold_count, proceed; otherwise, do nothing. Location of Safe Cut-Off:Find an index that respects function...
In summary, and trying to tie observations about Coach Wooden with current research in cognitive aging, it was clear that Coach was aware of the memory challenges that come with aging, and he showed intact levels of metacognition in most cases. He maintained his ability to selectively use ...
KernelMemory; 4 5 using Microsoft.SemanticKernel; 5 6 using Microsoft.SemanticKernel.ChatCompletion; 6 7 using Microsoft.SemanticKernel.Connectors.OpenAI; 7 8 using Microsoft.SemanticKernel.Embeddings; 8 9 using Microsoft.SemanticKernel.TextGeneration; 10 + 9 11 using SK_KernelMemory; ...
A. Intelligence. B. Health. C. Skills. D. Calmness. 3. What is the last part of the conversation about? A. The kind of people suitable for the trip. B. Interests and hobbies of the speakers. C. Recruitment of people for the trip. D. Preparation for the trip to Mars. Conversation...
as_retriever(), memory=memory, return_source_documents=True) query = "What did the president say about Ketanji Brown Jackson" result = qa({"question": query}) Expected behavior When return_source_documents is set to False, code runs as intended. When ConversationalRetrievalChain uses the ...