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The criterion is whether the response is insightful and carefully thought out. The submission provides a clear and concise explanation of the "appeal to nature" fallacy, demonstrating an understanding of the concept. It also provides examples to illustrate why this argument can be faulty, showing t...
结合LangChain的实现逻辑以及PS prompting和PS+ prompting的范式构成,可将PS prompting的实现过程分为计划和求解两个链路节点,而PS+ prompting则在此基础上增加对相关变量及数值的抽取节点。具体实现过程见下文。 环境设置 本文采用的python版本为3.10,langchain版本为0.1.13,langchain-core版本为0.1.33。用于测试的大语...
from skllm.models.gpt import GPTClassifierclf = GPTClassifier(base_model = "gpt-3.5-turbo-0613",n_epochs = None, # int or None. When None, will be determined automatically by OpenAIdefault_label = "Random", # optional)clf.fit(X_train, y_train) # y_train is a list of labelslabels ...
2022 年,在 Google 发布的论文《Chain-of-Thought Prompting Elicits Reasoning in Large Language Models》中首次提出,通过让大模型逐步参与将一个复杂问题分解为一步一步的子问题并依次进行求解的过程可以显著提升大模型的性能。而这一系列推理的中间步骤就被称为思维链(Chain of Thought)。
agent_executor.run("using the teachers table, find the first_name and last name of teachers who earn less the mean salary?")> Entering new AgentExecutor chain...Action: sql_db_list_tablesAction Input: ""Observation: teachersThought:I can query the "teachers" table to find the first_name...
2. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models:https://arxiv.org/pdf/2201.11903.pdf 3. Tree of Thoughts: Deliberate Problem Solving with Large Language Models:https://arxiv.org/pdf/2305.10601.pdf 4. ReAct: Synergizing Reasoning and Acting in Language Models:https://ar...
[2305.04091] Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models (arxiv.org)MapReduce适合大文件场景,可以分块切割然后在reduce阶段聚合归并最终结果。from functools import partial from langchain.schema import Document...
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: ...
LLMs: 少量的 prompting, 思考鏈( Chain of Thought ), ReAct prompting 聊天模型 提示( Prompts ), PromptTemplates 輸出解析器( Output Parsers ) 鏈( Chains ): SequentialChain, LLMChain, RetrievalQA chain 代理( Agents ), 訂製的代理 工具, 工具包( Toolkits ) ...