2.1垂直领域AI Agent 实现路径 实现AI Agent关键点在于,LLM模型需要具备思维链(Chain of Thought,CoT)与工具调用(Function Call)的能力,需要一个应用框架与环境、数据进行交互。 垂直领域 AI Agent 整体架构示意图: 用户输入的文档或问题,首先经过文本分割模块,将长句子分割为文本块,输入到Embedding模型,实现向量化进行...
其中,“实时数据获取”、“代码模拟执行”这些任务可以通过“tool-call prompt”技术得到解决,而Chain-of-Thought prompt技术被用于解决一些复杂的逻辑和算数问题。 Standard Prompting Chain-of-Thought Prompting “chain-of-thought prompting”的格式如下所示: <hinput,chain of thought,outputi> 关于如何使LLM展现出...
Thought:Retrying langchain.chat_models.openai.ChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 4.0 seconds as it raised RateLimitError: Rate limit reached for default-gpt-3.5-turbo in organization org-FDYSniIsv0FIQBi9p4P9Dinn on requests per min. Limit: 3 / min. Please tr...
根据Langchain官方对 Plan and Execute Agent的介绍,这类Agent主要受到BabyAGI项目和论文[2305.04091] Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models (arxiv.org)的影响,"Plan and Execute" 主要想要解决Action Agent (例如Zero-Shot ReAct Agent) 的三类问题:...
GPT-4 provides a step-by-step solution to a logic puzzle in response to a chain-of-thought prompt. The following are other examples of CoT prompts: "John has one pizza, cut into eight equal slices. John eats three slices, and his friend eats two slices. How many slices are left? Exp...
To improve the reasoning abilities, we propose extbf{ChatCoT}, a tool-augmented chain-of-thought reasoning framework for chat-based LLMs. In ChatCoT, we model the chain-of-thought~(CoT) reasoning as multi-turn conversations, to utilize tools in a more natural way through chatting. At each...
models that can clearly help the development of LLMs. The resutls and scripts from Chain-of-thought Hub is being used and referred by leading industrial and academic organizations in the space of large language models. We devide the tasks into three categories: main, experimental, and long-...
When this comes, chain-of-thought prompt engineering will be the next-generation system calls and shell scripts. The resutls and scripts from Chain-of-thought Hub is being used and referred by leading industrial and academic organizations in the space of large language models. [Call for ...
思考(Thought) 在思考阶段,代理使用预先设定的规则、知识库或者利用机器学习模型来分析观察到的信息。这个阶段的目的是确定如何响应观察到的情况。代理可能会评估不同的行动方案,预测它们的结果,并选择最合适的答案或行为。 在LangChain中,这个过程可能涉及以下几个子步骤: 1.理解用户意图:使用NLP(自然语言处理)技术来...
agent 代理和代理之间是可以相互调用的,不要限制自己的思维,因为一个agent 可以衍生成一个tool 智能代理分类: • 行动代理(Action agents):旨在决定行动序列(工具使用)(例如OpenAI Funciton Call,ReAct)。 • 模拟代理(Simulation agents):通常设计用于角色扮演,在模拟环境中进行(例如生成式智能体,CAMEL)。