content: /**
   * Copyright (C) 2024 AIDC-AI
   *
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   *     http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  package com.alibaba.langengine.core.chain.combinedocument;
  
  import com.alibaba.langengine.core.prompt.impl.PromptTemplate;
  
  import java.util.Arrays;
  
  /**
   * 常量类
   *
   * @author xiaoxuan.lp
   */
  public class PromptConstants {
  
      /**
       * qa问答采用的模版
       */
      public static final String QA_PROMPT_TEMPLATE_EN = "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n" +
              "\n" +
  //            "Context:\n" +
              "{context}\n" +
              "\n" +
              "Question: {question}\n" +
              "Helpful Answer:";
  
      public static final String QA_PROMPT_TEMPLATE_CH = "请使用以下的上下文来回答最后的问题。如果你不知道答案，就说你不知道，不要试图编造答案。\n" +
              "\n" +
  //            "Context:\n" +
              "{context}\n" +
              "\n" +
              "问题: {question}\n" +
              "有用的答案:";
  
      public static final String QA_QUESTION_PROMPT_TEMPLATE_EN = "Context information is below. \n" +
              "---------------------\n" +
              "{context_str}" +
              "\n---------------------\n" +
              "Given the context information and not prior knowledge, " +
              "answer the question: {question}\n";
  
      public static final String QA_QUESTION_PROMPT_TEMPLATE_CH = "上下文信息如下。\n" +
              "---------------------\n" +
              "{context_str}" +
              "\n---------------------\n" +
              "给定上下文信息而不是先验知识，" +
              "回答问题：{question}\n";
  
      public static final String QA_REFINE_PROMPT_TEMPLATE_EN = "The original question is as follows: {question}\n" +
          "We have provided an existing answer: {existing_answer}\n" +
              "We have the opportunity to refine the existing answer" +
              "(only if needed) with some more context below.\n" +
              "------------\n" +
              "{context_str}\n" +
              "------------\n" +
              "Given the new context, refine the original answer to better " +
              "answer the question. " +
              "If the context isn't useful, return the original answer.";
  
      public static final String QA_REFINE_PROMPT_TEMPLATE_CH = "原问题如下：{question}\n" +
              "我们已经提供了现有的答案：{existing_answer}\n" +
              "我们有机会完善现有的答案（仅在需要时）下面有更多上下文。\n" +
              "------------\n" +
              "{context_str}\n" +
              "------------\n" +
              "考虑到新的背景，将原来的答案细化为更好的回答问题。" +
              "如果上下文没有用，请返回原始答案。";
  
      public static final String QA_MAPREDUCE_MAP_PROMPT_TEMPLATE_EN = "Summarize this content: {context}";
      public static final String QA_MAPREDUCE_MAP_PROMPT_TEMPLATE_CH = "总结一下本次内容: {context}";
  
      public static final String QA_MAPREDUCE_REDUCE_PROMPT_TEMPLATE_EN = "Combine these summaries: {context}";
      public static final String QA_MAPREDUCE_REDUCE_PROMPT_TEMPLATE_CH = "合并这些总结: {context}";
  
      public static final String QA_MAPREDUCE_QUESTION_PROMPT_TEMPLATE_EN = "Use the following portion of a long document to see if any of the text is relevant to answer the question. \n" +
              "Return any relevant text verbatim.\n" +
              "{context}\n" +
              "Question: {question}\n" +
              "Relevant text, if any:";
  
      public static final String QA_MAPREDUCE_COMBINE_PROMPT_TEMPLATE_EN = "Given the following extracted parts of a long document and a question, create a final answer with references (\"SOURCES\"). \n" +
              "If you don't know the answer, just say that you don't know. Don't try to make up an answer.\n" +
              "ALWAYS return a \"SOURCES\" part in your answer.\n" +
              "\n" +
              "QUESTION: Which state/country's law governs the interpretation of the contract?\n" +
              "=========\n" +
              "Content: This Agreement is governed by English law and the parties submit to the exclusive jurisdiction of the English courts in  relation to any dispute (contractual or non-contractual) concerning this Agreement save that either party may apply to any court for an  injunction or other relief to protect its Intellectual Property Rights.\n" +
              "Source: 28-pl\n" +
              "Content: No Waiver. Failure or delay in exercising any right or remedy under this Agreement shall not constitute a waiver of such (or any other)  right or remedy.\\n\\n11.7 Severability. The invalidity, illegality or unenforceability of any term (or part of a term) of this Agreement shall not affect the continuation  in force of the remainder of the term (if any) and this Agreement.\\n\\n11.8 No Agency. Except as expressly stated otherwise, nothing in this Agreement shall create an agency, partnership or joint venture of any  kind between the parties.\\n\\n11.9 No Third-Party Beneficiaries.\n" +
              "Source: 30-pl\n" +
              "Content: (b) if Google believes, in good faith, that the Distributor has violated or caused Google to violate any Anti-Bribery Laws (as  defined in Clause 8.5) or that such a violation is reasonably likely to occur,\n" +
              "Source: 4-pl\n" +
              "=========\n" +
              "FINAL ANSWER: This Agreement is governed by English law.\n" +
              "SOURCES: 28-pl\n" +
              "\n" +
              "QUESTION: What did the president say about Michael Jackson?\n" +
              "=========\n" +
              "Content: Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans.  \\n\\nLast year COVID-19 kept us apart. This year we are finally together again. \\n\\nTonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. \\n\\nWith a duty to one another to the American people to the Constitution. \\n\\nAnd with an unwavering resolve that freedom will always triumph over tyranny. \\n\\nSix days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. \\n\\nHe thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined. \\n\\nHe met the Ukrainian people. \\n\\nFrom President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world. \\n\\nGroups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland.\n" +
              "Source: 0-pl\n" +
              "Content: And we won’t stop. \\n\\nWe have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. \\n\\nLet’s use this moment to reset. Let’s stop looking at COVID-19 as a partisan dividing line and see it for what it is: A God-awful disease.  \\n\\nLet’s stop seeing each other as enemies, and start seeing each other for who we really are: Fellow Americans.  \\n\\nWe can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together. \\n\\nI recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. \\n\\nThey were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. \\n\\nOfficer Mora was 27 years old. \\n\\nOfficer Rivera was 22. \\n\\nBoth Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers. \\n\\nI spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves.\n" +
              "Source: 24-pl\n" +
              "Content: And a proud Ukrainian people, who have known 30 years  of independence, have repeatedly shown that they will not tolerate anyone who tries to take their country backwards.  \\n\\nTo all Americans, I will be honest with you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the world. \\n\\nAnd I’m taking robust action to make sure the pain of our sanctions  is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. \\n\\nTonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world.  \\n\\nAmerica will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies.  \\n\\nThese steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming. \\n\\nBut I want you to know that we are going to be okay.\n" +
              "Source: 5-pl\n" +
              "Content: More support for patients and families. \\n\\nTo get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health. \\n\\nIt’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more.  \\n\\nARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s, diabetes, and more. \\n\\nA unity agenda for the nation. \\n\\nWe can do this. \\n\\nMy fellow Americans—tonight , we have gathered in a sacred space—the citadel of our democracy. \\n\\nIn this Capitol, generation after generation, Americans have debated great questions amid great strife, and have done great things. \\n\\nWe have fought for freedom, expanded liberty, defeated totalitarianism and terror. \\n\\nAnd built the strongest, freest, and most prosperous nation the world has ever known. \\n\\nNow is the hour. \\n\\nOur moment of responsibility. \\n\\nOur test of resolve and conscience, of history itself. \\n\\nIt is in this moment that our character is formed. Our purpose is found. Our future is forged. \\n\\nWell I know this nation.\n" +
              "Source: 34-pl\n" +
              "=========\n" +
              "FINAL ANSWER: The president did not mention Michael Jackson.\n" +
              "SOURCES:\n" +
              "\n" +
              "QUESTION: {question}\n" +
              "=========\n" +
              "{summaries}\n" +
              "=========\n" +
              "FINAL ANSWER:";
  
      public static final String QA_MAPRERANK_PROMPT_TEMPLATE_EN = "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n" +
              "\n" +
              "In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\n" +
              "\n" +
              "Question: [question here]\n" +
              "Helpful Answer: [answer here]\n" +
              "Score: [score between 0 and 100]\n" +
              "\n" +
              "How to determine the score:\n" +
              "- Higher is a better answer\n" +
              "- Better responds fully to the asked question, with sufficient level of detail\n" +
              "- If you do not know the answer based on the context, that should be a score of 0\n" +
              "- Don't be overconfident!\n" +
              "\n" +
              "Example #1\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "Apples are red\n" +
              "---------\n" +
              "Question: what color are apples?\n" +
              "Helpful Answer: red\n" +
              "Score: 100\n" +
              "\n" +
              "Example #2\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\n" +
              "---------\n" +
              "Question: what type was the car?\n" +
              "Helpful Answer: a sports car or an suv\n" +
              "Score: 60\n" +
              "\n" +
              "Example #3\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "Pears are either red or orange\n" +
              "---------\n" +
              "Question: what color are apples?\n" +
              "Helpful Answer: This document does not answer the question\n" +
              "Score: 0\n" +
              "\n" +
              "Begin!\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "{context}\n" +
              "---------\n" +
              "Question: {question}\n" +
              "Helpful Answer:";
  
      public static final String QA_MAPRERANK_PROMPT_TEMPLATE_CH = "使用以下上下文来回答最后的问题。 如果你不知道答案，就说你不知道，不要试图编造答案。\n" +
              "\n" +
              "除了给出答案之外，还返回其回答用户问题的程度的分数。 这应该采用以下格式：\n" +
              "\n" +
              "Question: [question here]\n" +
              "Helpful Answer: [answer here]\n" +
              "Score: [score between 0 and 100]\n" +
              "\n" +
              "如何确定分数：\n" +
              "- 答案越高越好\n" +
              "- 更好地全面回答所提出的问题，并提供足够的细节\n" +
              "- 如果您根据上下文不知道答案，则应为 0 分\n" +
              "- 不要过于自信！\n" +
              "\n" +
              "例子 #1\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "Apples are red\n" +
              "---------\n" +
              "Question: what color are apples?\n" +
              "Helpful Answer: red\n" +
              "Score: 100\n" +
              "\n" +
              "例子 #2\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\n" +
              "---------\n" +
              "Question: what type was the car?\n" +
              "Helpful Answer: a sports car or an suv\n" +
              "Score: 60\n" +
              "\n" +
              "例子 #3\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "Pears are either red or orange\n" +
              "---------\n" +
              "Question: what color are apples?\n" +
              "Helpful Answer: This document does not answer the question\n" +
              "Score: 0\n" +
              "\n" +
              "开始！\n" +
              "\n" +
              "Context:\n" +
              "---------\n" +
              "{context}\n" +
              "---------\n" +
              "Question: {question}\n" +
              "Helpful Answer:";
  //            "使用以下 已知问题 输出你的答案和相关性程度的分数(分数在0.00-1.00之间，分数越高越相关，如果您根据已知问题不知道答案，则应为0分），使用以下json格式作为返回：\n" +
  //            "'''\n" +
  //            "{ \"answer\": \"答案\", \"score\": 分数 } \n" +
  //            "'''\n" +
  //            "已知问题: {context}\n" +
  //            "我的问题: {question}\n";
  
      public static final PromptTemplate QA_PROMPT_EN = new PromptTemplate(QA_PROMPT_TEMPLATE_EN);
      public static final PromptTemplate QA_PROMPT_CH = new PromptTemplate(QA_PROMPT_TEMPLATE_CH);
  
      public static final PromptTemplate QA_QUESTION_PROMPT_EN = new PromptTemplate(QA_QUESTION_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "context_str", "question" }));
      public static final PromptTemplate QA_QUESTION_PROMPT_CH = new PromptTemplate(QA_QUESTION_PROMPT_TEMPLATE_CH, Arrays.asList(new String[]{ "context_str", "question" }));
      public static final PromptTemplate QA_REFINE_PROMPT_EN = new PromptTemplate(QA_REFINE_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "question", "existing_answer", "context_str" }));
      public static final PromptTemplate QA_REFINE_PROMPT_CH = new PromptTemplate(QA_REFINE_PROMPT_TEMPLATE_CH, Arrays.asList(new String[]{ "question", "existing_answer", "context_str" }));
  
      public static final PromptTemplate QA_MAPREDUCE_MAP_PROMPT_EN = new PromptTemplate(QA_MAPREDUCE_MAP_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "context" }));
      public static final PromptTemplate QA_MAPREDUCE_MAP_PROMPT_CH = new PromptTemplate(QA_MAPREDUCE_MAP_PROMPT_TEMPLATE_CH, Arrays.asList(new String[]{ "context" }));
  
      public static final PromptTemplate QA_MAPREDUCE_REDUCE_PROMPT_EN = new PromptTemplate(QA_MAPREDUCE_REDUCE_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "context" }));
      public static final PromptTemplate QA_MAPREDUCE_REDUCE_PROMPT_CH = new PromptTemplate(QA_MAPREDUCE_REDUCE_PROMPT_TEMPLATE_CH, Arrays.asList(new String[]{ "context" }));
  
      public static final PromptTemplate QA_MAPRERANK_PROMPT_EN = new PromptTemplate(QA_MAPRERANK_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "context" }));
      public static final PromptTemplate QA_MAPRERANK_PROMPT_CH = new PromptTemplate(QA_MAPRERANK_PROMPT_TEMPLATE_CH, Arrays.asList(new String[]{ "context" }));
  
      public static final PromptTemplate QA_MAPREDUCE_QUESTION_PROMPT_EN = new PromptTemplate(QA_MAPREDUCE_QUESTION_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "context", "question" }));
      public static final PromptTemplate QA_MAPREDUCE_COMBINE_PROMPT_EN = new PromptTemplate(QA_MAPREDUCE_COMBINE_PROMPT_TEMPLATE_EN, Arrays.asList(new String[]{ "summaries", "question" }));
  
  }
  