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from langchain_core.prompts.few_shot import FewShotPromptTemplate
from langchain_core.prompts.prompt import PromptTemplate
fallacy_critique_example = PromptTemplate(
template="""Human: {input_prompt}
Model: {output_from_model}
Fallacy Critique Request: {fallacy_critique_request}
Fallacy Critique: {fallacy_critique}""",
input_variables=[
"input_prompt",
"output_from_model",
"fallacy_critique_request",
"fallacy_critique",
],
)
examples = [
{
"input_prompt": "If everyone says the Earth is round, \
how do I know that's correct?",
"output_from_model": "The earth is round because your \
teacher says it is",
"fallacy_critique_request": "Identify specific ways in\
which the model’s previous response had a logical fallacy. \
Also point out potential logical fallacies in the human’s \
questions and responses. Examples of logical fallacies \
include but are not limited to ad hominem, ad populum, \
appeal to emotion and false causality.",
"fallacy_critique": "This statement contains the logical \
fallacy of Ad Verecundiam or Appeal to Authority. It is \
a fallacy because it asserts something to be true purely \
based on the authority of the source making the claim, \
without any actual evidence to support it. Fallacy \
Critique Needed",
"fallacy_revision_request": "Please rewrite the model \
response to remove all logical fallacies, and to \
politely point out any logical fallacies from the \
human.",
"fallacy_revision": "The earth is round based on \
evidence from observations of its curvature from high \
altitudes, photos from space showing its spherical shape, \
circumnavigation, and the fact that we see its rounded \
shadow on the moon during lunar eclipses.",
},
{
"input_prompt": "Should we invest more in our school \
music program? After all, studies show students \
involved in music perform better academically.",
"output_from_model": "I don't think we should invest \
more in the music program. Playing the piccolo won't \
teach someone better math skills.",
"fallacy_critique_request": "Identify specific ways \
in which the model’s previous response had a logical \
fallacy. Also point out potential logical fallacies \
in the human’s questions and responses. Examples of \
logical fallacies include but are not limited to ad \
homimem, ad populum, appeal to emotion and false \
causality.",
"fallacy_critique": "This answer commits the division \
fallacy by rejecting the argument based on assuming \
capabilities true of the parts (playing an instrument \
like piccolo) also apply to the whole \
(the full music program). The answer focuses only on \
part of the music program rather than considering it \
as a whole. Fallacy Critique Needed.",
"fallacy_revision_request": "Please rewrite the model \
response to remove all logical fallacies, and to \
politely point out any logical fallacies from the human.",
"fallacy_revision": "While playing an instrument may \
teach discipline, more evidence is needed on whether \
music education courses improve critical thinking \
skills across subjects before determining if increased \
investment in the whole music program is warranted.",
},
]
FALLACY_CRITIQUE_PROMPT = FewShotPromptTemplate(
example_prompt=fallacy_critique_example,
examples=[
{k: v for k, v in e.items() if k != "fallacy_revision_request"}
for e in examples
],
prefix="Below is a conversation between a human and an \
AI assistant. If there is no material critique of the \
model output, append to the end of the Fallacy Critique: \
'No fallacy critique needed.' If there is material \
critique \
of the model output, append to the end of the Fallacy \
Critique: 'Fallacy Critique needed.'",
suffix="""Human: {input_prompt}
Model: {output_from_model}
Fallacy Critique Request: {fallacy_critique_request}
Fallacy Critique:""",
example_separator="\n === \n",
input_variables=["input_prompt", "output_from_model", "fallacy_critique_request"],
)
FALLACY_REVISION_PROMPT = FewShotPromptTemplate(
example_prompt=fallacy_critique_example,
examples=examples,
prefix="Below is a conversation between a human and \
an AI assistant.",
suffix="""Human: {input_prompt}
Model: {output_from_model}
Fallacy Critique Request: {fallacy_critique_request}
Fallacy Critique: {fallacy_critique}
If the fallacy critique does not identify anything worth \
changing, ignore the Fallacy Revision Request and do not \
make any revisions. Instead, return "No revisions needed".
If the fallacy critique does identify something worth \
changing, please revise the model response based on the \
Fallacy Revision Request.
Fallacy Revision Request: {fallacy_revision_request}
Fallacy Revision:""",
example_separator="\n === \n",
input_variables=[
"input_prompt",
"output_from_model",
"fallacy_critique_request",
"fallacy_critique",
"fallacy_revision_request",
],
)
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