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# Adapted from Prompt-aided Language Models [PAL](https://arxiv.org/pdf/2211.10435.pdf). | |
import minichain | |
# PAL Prompt | |
class PalPrompt(minichain.TemplatePrompt): | |
template_file = "pal.pmpt.tpl" | |
# Prompt to run and print python code. | |
class PyPrompt(minichain.Prompt): | |
def prompt(self, inp): | |
return inp + "\nprint(solution())" | |
def parse(self, response, inp): | |
return int(response) | |
# Chain the prompts. | |
with minichain.start_chain("pal") as backend: | |
question = "Melanie is a door-to-door saleswoman. She sold a third of her ' \ | |
'vacuum cleaners at the green house, 2 more to the red house, and half of ' \ | |
'what was left at the orange house. If Melanie has 5 vacuum cleaners left, ' \ | |
'how many did she start with?'" | |
prompt = PalPrompt(backend.OpenAI()).chain(PyPrompt(backend.Python())) | |
result = prompt({"question": question}) | |
print(result) | |
# View prompt examples. | |
# + tags=["hide_inp"] | |
PalPrompt().show( | |
{"question": "Joe has 10 cars and Bobby has 12. How many do they have together?"}, | |
"def solution():\n\treturn 10 + 12", | |
) | |
# - | |
# + tags=["hide_inp"] | |
PyPrompt().show("def solution():\n\treturn 10 + 12", "22") | |
# - | |
# View the log. | |
minichain.show_log("pal.log") | |