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62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
# The following prompts are used for verifying the LLM answer after it is already produced.
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# Reflexion flow essentially. This feature can be toggled on/off
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from onyx.configs.app_configs import CUSTOM_ANSWER_VALIDITY_CONDITIONS
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from onyx.prompts.constants import ANSWER_PAT
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from onyx.prompts.constants import QUESTION_PAT
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ANSWER_VALIDITY_CONDITIONS = (
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"""
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1. Query is asking for information that varies by person or is subjective. If there is not a \
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globally true answer, the language model should not respond, therefore any answer is invalid.
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2. Answer addresses a related but different query. To be helpful, the model may provide \
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related information about a query but it won't match what the user is asking, this is invalid.
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3. Answer is just some form of "I don\'t know" or "not enough information" without significant \
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additional useful information. Explaining why it does not know or cannot answer is invalid.
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"""
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if not CUSTOM_ANSWER_VALIDITY_CONDITIONS
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else "\n".join(
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[
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f"{indice+1}. {condition}"
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for indice, condition in enumerate(CUSTOM_ANSWER_VALIDITY_CONDITIONS)
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]
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)
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)
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ANSWER_FORMAT = (
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"""
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1. True or False
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2. True or False
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3. True or False
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"""
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if not CUSTOM_ANSWER_VALIDITY_CONDITIONS
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else "\n".join(
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[
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f"{indice+1}. True or False"
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for indice, _ in enumerate(CUSTOM_ANSWER_VALIDITY_CONDITIONS)
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]
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)
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)
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ANSWER_VALIDITY_PROMPT = f"""
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You are an assistant to identify invalid query/answer pairs coming from a large language model.
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The query/answer pair is invalid if any of the following are True:
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{ANSWER_VALIDITY_CONDITIONS}
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{QUESTION_PAT} {{user_query}}
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{ANSWER_PAT} {{llm_answer}}
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------------------------
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You MUST answer in EXACTLY the following format:
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```
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{ANSWER_FORMAT}
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Final Answer: Valid or Invalid
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```
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Hint: Remember, if ANY of the conditions are True, it is Invalid.
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""".strip()
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# Use the following for easy viewing of prompts
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if __name__ == "__main__":
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print(ANSWER_VALIDITY_PROMPT)
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