Kimi's official cue word: public content summary
Distill the following for this article: 1. metadata: title, author, links, tags 2. author claims, highlights 3. layer-by-layer for deeper understanding 4. key terms/concepts 5. useless information within the article 6. summarize the core information 7. golden nuggets of information 8. summarize 9. based on the content of the article give...
Kimi's official cue word: Summarize
You are an assistant who is good at summarizing long texts, able to summarize the text given by the user and generate a summary. ## Workflow Let's think step by step, read the content I provided and make the following actions: ## Tagging Read the content of the article and then tag the article, the tags are usually field, sch...
Kimi's official tip word: Organize thorough notes!
Please return to your exhaustive notes carefully organized after reading the text repeatedly Main article below:
LLM application: reflections on Agent dialog (with tool calls)
Q&A products such as ChatGPT and Kimi are using Agent conversations (the ability to invoke different tools to interact with the user), for example Kimi's tools have LLM conversations, link conversations, file conversations, and networking conversations. For example, ChatGPT, Wenxin Yiyin and Xunfei Starfire also extend...
Hands-on ReAct Implementation Logic
Using the Reflection technique to validate the React full process rationalization. https://arxiv.org/abs/2303.11366 Step 1: Constructing ReAct's base prompt instruction The first step is centered on printing out the...
Dify relies on ChatGPT-on-WeChat to access the WeChat ecosystem
Author: Han Fangyuan, author of "Dify on WeChat" open source project 1. Overview WeChat, as the most popular instant messaging software, has a huge amount of traffic. WeChat's friendly chat window is a natural AI application LUI (Language User Int...
Multibook (example) jailbreak attack
Researchers have investigated a "jailbreak attack" technique - a method that can be used to bypass security fences set up by developers of large language models (LLMs). The technique, known as a "multisample jailbreak attack," uses Anthropic's own models, as well as those produced by other AI companies, to...
ReAct: Reasoning and Action Working Together in Large Language Models
Original: https://arxiv.org/pdf/2210.03629.pdf Can't understand how ReAct works and applies even after reading it? See "ReAct Implementation Logic in Action" for an explanation with real-world examples. Abstract Although large languages ...
RAG: Retrieval Augmentation
RAG (Retrieve Augmented Generation) is a technique for optimizing the output of large language models (LLMs) based on authoritative knowledge base information. This technique generates responses by extending the functionality of LLMs to...
ChatOllama Notes | Implementing Advanced RAG for Productivity and Redis-based Document Databases
ChatOllama is an open source chatbot based on LLMs. For a detailed description of ChatOllama click on the link below. ChatOllama | Ollama based 100% local RAG application ChatOl...









