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- CONVERSATION_TITLE_PROMPT = (
- "Human:{query}\n-----\n"
- "Help me summarize the intent of what the human said and provide a title, the title should not exceed 20 words.\n"
- "If what the human said is conducted in English, you should only return an English title.\n"
- "If what the human said is conducted in Chinese, you should only return a Chinese title.\n"
- "title:"
- )
- CONVERSATION_SUMMARY_PROMPT = (
- "Please generate a short summary of the following conversation.\n"
- "If the following conversation communicating in English, you should only return an English summary.\n"
- "If the following conversation communicating in Chinese, you should only return a Chinese summary.\n"
- "[Conversation Start]\n"
- "{context}\n"
- "[Conversation End]\n\n"
- "summary:"
- )
- INTRODUCTION_GENERATE_PROMPT = (
- "I am designing a product for users to interact with an AI through dialogue. "
- "The Prompt given to the AI before the conversation is:\n\n"
- "```\n{prompt}\n```\n\n"
- "Please generate a brief introduction of no more than 50 words that greets the user, based on this Prompt. "
- "Do not reveal the developer's motivation or deep logic behind the Prompt, "
- "but focus on building a relationship with the user:\n"
- )
- MORE_LIKE_THIS_GENERATE_PROMPT = (
- "-----\n"
- "{original_completion}\n"
- "-----\n\n"
- "Please use the above content as a sample for generating the result, "
- "and include key information points related to the original sample in the result. "
- "Try to rephrase this information in different ways and predict according to the rules below.\n\n"
- "-----\n"
- "{prompt}\n"
- )
- SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
- "Please help me predict the three most likely questions that human would ask, "
- "and keeping each question under 20 characters.\n"
- "The output must be an array in JSON format following the specified schema:\n"
- "[\"question1\",\"question2\",\"question3\"]\n"
- )
- GENERATOR_QA_PROMPT = (
- 'The user will send a long text. Please think step by step.'
- 'Step 1: Understand and summarize the main content of this text.\n'
- 'Step 2: What key information or concepts are mentioned in this text?\n'
- 'Step 3: Decompose or combine multiple pieces of information and concepts.\n'
- 'Step 4: Generate 20 questions and answers based on these key information and concepts.'
- 'The questions should be clear and detailed, and the answers should be detailed and complete.\n'
- "Answer must be the language:{language} and in the following format: Q1:\nA1:\nQ2:\nA2:...\n"
- )
- RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \
- the model prompt that best suits the input.
- You will be provided with the prompt, variables, and an opening statement.
- Only the content enclosed in double curly braces, such as {{variable}}, in the prompt can be considered as a variable; \
- otherwise, it cannot exist as a variable in the variables.
- If you believe revising the original input will result in a better response from the language model, you may \
- suggest revisions.
- << FORMATTING >>
- Return a markdown code snippet with a JSON object formatted to look like, \
- no any other string out of markdown code snippet:
- ```json
- {{{{
- "prompt": string \\ generated prompt
- "variables": list of string \\ variables
- "opening_statement": string \\ an opening statement to guide users on how to ask questions with generated prompt \
- and fill in variables, with a welcome sentence, and keep TLDR.
- }}}}
- ```
- << EXAMPLES >>
- [EXAMPLE A]
- ```json
- {
- "prompt": "Write a letter about love",
- "variables": [],
- "opening_statement": "Hi! I'm your love letter writer AI."
- }
- ```
- [EXAMPLE B]
- ```json
- {
- "prompt": "Translate from {{lanA}} to {{lanB}}",
- "variables": ["lanA", "lanB"],
- "opening_statement": "Welcome to use translate app"
- }
- ```
- [EXAMPLE C]
- ```json
- {
- "prompt": "Write a story about {{topic}}",
- "variables": ["topic"],
- "opening_statement": "I'm your story writer"
- }
- ```
- << MY INTENDED AUDIENCES >>
- {audiences}
- << HOPING TO SOLVE >>
- {hoping_to_solve}
- << OUTPUT >>
- """
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