llama-index

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from llama_index.legacy.prompts.base import PromptTemplate
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from llama_index.legacy.prompts.prompt_type import PromptType
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"""Single select prompt.
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PromptTemplate to select one out of `num_choices` options provided in `context_list`,
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given a query `query_str`.
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Required template variables: `num_chunks`, `context_list`, `query_str`
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"""
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SingleSelectPrompt = PromptTemplate
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"""Multiple select prompt.
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PromptTemplate to select multiple candidates (up to `max_outputs`) out of `num_choices`
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options provided in `context_list`, given a query `query_str`.
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Required template variables: `num_chunks`, `context_list`, `query_str`,
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    `max_outputs`
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"""
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MultiSelectPrompt = PromptTemplate
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# single select
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DEFAULT_SINGLE_SELECT_PROMPT_TMPL = (
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    "Some choices are given below. It is provided in a numbered list "
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    "(1 to {num_choices}), "
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    "where each item in the list corresponds to a summary.\n"
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    "---------------------\n"
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    "{context_list}"
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    "\n---------------------\n"
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    "Using only the choices above and not prior knowledge, return "
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    "the choice that is most relevant to the question: '{query_str}'\n"
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)
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DEFAULT_SINGLE_SELECT_PROMPT = PromptTemplate(
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    template=DEFAULT_SINGLE_SELECT_PROMPT_TMPL, prompt_type=PromptType.SINGLE_SELECT
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)
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# multiple select
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DEFAULT_MULTI_SELECT_PROMPT_TMPL = (
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    "Some choices are given below. It is provided in a numbered "
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    "list (1 to {num_choices}), "
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    "where each item in the list corresponds to a summary.\n"
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    "---------------------\n"
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    "{context_list}"
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    "\n---------------------\n"
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    "Using only the choices above and not prior knowledge, return the top choices "
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    "(no more than {max_outputs}, but only select what is needed) that "
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    "are most relevant to the question: '{query_str}'\n"
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)
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DEFAULT_MULTIPLE_SELECT_PROMPT = PromptTemplate(
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    template=DEFAULT_MULTI_SELECT_PROMPT_TMPL, prompt_type=PromptType.MULTI_SELECT
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)
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# single pydantic select
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DEFAULT_SINGLE_PYD_SELECT_PROMPT_TMPL = (
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    "Some choices are given below. It is provided in a numbered list "
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    "(1 to {num_choices}), "
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    "where each item in the list corresponds to a summary.\n"
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    "---------------------\n"
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    "{context_list}"
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    "\n---------------------\n"
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    "Using only the choices above and not prior knowledge, generate "
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    "the selection object and reason that is most relevant to the "
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    "question: '{query_str}'\n"
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)
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# multiple pydantic select
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DEFAULT_MULTI_PYD_SELECT_PROMPT_TMPL = (
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    "Some choices are given below. It is provided in a numbered "
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    "list (1 to {num_choices}), "
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    "where each item in the list corresponds to a summary.\n"
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    "---------------------\n"
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    "{context_list}"
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    "\n---------------------\n"
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    "Using only the choices above and not prior knowledge, return the top choice(s) "
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    "(no more than {max_outputs}, but only select what is needed) by generating "
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    "the selection object and reasons that are most relevant to the "
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    "question: '{query_str}'\n"
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)
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