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desc = """ |
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### Self-Ask |
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Notebook implementation of the self-ask + Google tool use prompt. [](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/selfask.ipynb) |
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(Adapted from [Self-Ask repo](https://github.com/ofirpress/self-ask)) |
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""" |
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from dataclasses import dataclass, replace |
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from typing import Optional |
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from minichain import prompt, show, OpenAI, Google, transform |
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@dataclass |
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class State: |
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question: str |
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history: str = "" |
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next_query: Optional[str] = None |
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final_answer: Optional[str] = None |
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@prompt(OpenAI(stop="\nIntermediate answer:"), |
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template_file = "selfask.pmpt.tpl") |
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def self_ask(model, state): |
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return model(state) |
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@transform() |
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def next_step(ask): |
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res = ask.split(":", 1)[1] |
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if out.startswith("Follow up:"): |
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return replace(state, next_query=res) |
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elif out.startswith("So the final answer is:"): |
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return replace(state, final_answer=res) |
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@prompt(Google()) |
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def google(model, state): |
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if state.next_query is None: |
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return "" |
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return model(state.next_query) |
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@transform() |
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def update(state, result): |
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if not result: |
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return state |
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return State(state.question, |
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state.history + "\nIntermediate answer: " + result + "\n") |
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def selfask(question): |
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state = State(question) |
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for i in range(3): |
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state = next_step(self_ask(state)) |
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state = update(google(state)) |
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return state |
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gradio = show(selfask, |
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examples=["What is the zip code of the city where George Washington was born?"], |
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subprompts=[self_ask, google] * 3, |
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description=desc, |
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code=open("selfask.py", "r").read().split("$")[1].strip().strip("#").strip(), |
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out_type="json" |
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) |
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if __name__ == "__main__": |
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gradio.queue().launch() |
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