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https://gitee.com/dify_ai/dify.git
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28b26f67e2
Co-authored-by: jyong <jyong@dify.ai>
136 lines
4.9 KiB
Python
136 lines
4.9 KiB
Python
# Written by YORKI MINAKO🤡
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CONVERSATION_TITLE_PROMPT = """You need to decompose the user's input into "subject" and "intention" in order to accurately figure out what the user's input language actually is.
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Notice: the language type user use could be diverse, which can be English, Chinese, Español, Arabic, Japanese, French, and etc.
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MAKE SURE your output is the SAME language as the user's input!
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Your output is restricted only to: (Input language) Intention + Subject(short as possible)
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Your output MUST be a valid JSON.
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Tip: When the user's question is directed at you (the language model), you can add an emoji to make it more fun.
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example 1:
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User Input: hi, yesterday i had some burgers.
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{
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"Language Type": "The user's input is pure English",
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"Your Reasoning": "The language of my output must be pure English.",
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"Your Output": "sharing yesterday's food"
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}
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example 2:
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User Input: hello
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{
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"Language Type": "The user's input is written in pure English",
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"Your Reasoning": "The language of my output must be pure English.",
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"Your Output": "Greeting myself☺️"
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}
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example 3:
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User Input: why mmap file: oom
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{
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"Language Type": "The user's input is written in pure English",
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"Your Reasoning": "The language of my output must be pure English.",
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"Your Output": "Asking about the reason for mmap file: oom"
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}
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example 4:
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User Input: www.convinceme.yesterday-you-ate-seafood.tv讲了什么?
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{
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"Language Type": "The user's input English-Chinese mixed",
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"Your Reasoning": "The English-part is an URL, the main intention is still written in Chinese, so the language of my output must be using Chinese.",
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"Your Output": "询问网站www.convinceme.yesterday-you-ate-seafood.tv"
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}
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example 5:
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User Input: why小红的年龄is老than小明?
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{
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"Language Type": "The user's input is English-Chinese mixed",
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"Your Reasoning": "The English parts are subjective particles, the main intention is written in Chinese, besides, Chinese occupies a greater \"actual meaning\" than English, so the language of my output must be using Chinese.",
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"Your Output": "询问小红和小明的年龄"
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}
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example 6:
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User Input: yo, 你今天咋样?
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{
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"Language Type": "The user's input is English-Chinese mixed",
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"Your Reasoning": "The English-part is a subjective particle, the main intention is written in Chinese, so the language of my output must be using Chinese.",
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"Your Output": "查询今日我的状态☺️"
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}
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User Input:
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"""
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SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
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"Please help me predict the three most likely questions that human would ask, "
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"and keeping each question under 20 characters.\n"
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"The output must be an array in JSON format following the specified schema:\n"
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"[\"question1\",\"question2\",\"question3\"]\n"
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)
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GENERATOR_QA_PROMPT = (
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'The user will send a long text. Please think step by step.'
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'Step 1: Understand and summarize the main content of this text.\n'
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'Step 2: What key information or concepts are mentioned in this text?\n'
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'Step 3: Decompose or combine multiple pieces of information and concepts.\n'
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'Step 4: Generate 20 questions and answers based on these key information and concepts.'
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'The questions should be clear and detailed, and the answers should be detailed and complete.\n'
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"Answer MUST according to the the language:{language} and in the following format: Q1:\nA1:\nQ2:\nA2:...\n"
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)
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RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \
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the model prompt that best suits the input.
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You will be provided with the prompt, variables, and an opening statement.
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Only the content enclosed in double curly braces, such as {{variable}}, in the prompt can be considered as a variable; \
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otherwise, it cannot exist as a variable in the variables.
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If you believe revising the original input will result in a better response from the language model, you may \
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suggest revisions.
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<< FORMATTING >>
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Return a markdown code snippet with a JSON object formatted to look like, \
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no any other string out of markdown code snippet:
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```json
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{{{{
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"prompt": string \\ generated prompt
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"variables": list of string \\ variables
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"opening_statement": string \\ an opening statement to guide users on how to ask questions with generated prompt \
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and fill in variables, with a welcome sentence, and keep TLDR.
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}}}}
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```
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<< EXAMPLES >>
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[EXAMPLE A]
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```json
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{
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"prompt": "Write a letter about love",
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"variables": [],
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"opening_statement": "Hi! I'm your love letter writer AI."
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}
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```
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[EXAMPLE B]
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```json
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{
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"prompt": "Translate from {{lanA}} to {{lanB}}",
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"variables": ["lanA", "lanB"],
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"opening_statement": "Welcome to use translate app"
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}
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```
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[EXAMPLE C]
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```json
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{
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"prompt": "Write a story about {{topic}}",
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"variables": ["topic"],
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"opening_statement": "I'm your story writer"
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}
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```
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<< MY INTENDED AUDIENCES >>
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{{audiences}}
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<< HOPING TO SOLVE >>
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{{hoping_to_solve}}
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<< OUTPUT >>
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""" |