|
|
|
desc = """ |
|
### Self-Ask |
|
|
|
Notebook implementation of the self-ask + Google tool use prompt. |
|
|
|
(Adapted from [Self-Ask repo](https://github.com/ofirpress/self-ask)) |
|
""" |
|
|
|
|
|
|
|
from dataclasses import dataclass, replace |
|
from typing import Optional |
|
from minichain import prompt, show, OpenAI, Google |
|
|
|
|
|
@dataclass |
|
class State: |
|
question: str |
|
history: str = "" |
|
next_query: Optional[str] = None |
|
final_answer: Optional[str] = None |
|
|
|
|
|
@prompt(OpenAI(), |
|
template_file = "selfask.pmpt.tpl", |
|
stop_template = "\nIntermediate answer:") |
|
def self_ask(model, state): |
|
out = model(state) |
|
res = out.split(":", 1)[1] |
|
if out.startswith("Follow up:"): |
|
return replace(state, next_query=res) |
|
elif out.startswith("So the final answer is:"): |
|
return replace(state, final_answer=res) |
|
|
|
@prompt(Google()) |
|
def google(model, state): |
|
if state.next_query is None: |
|
return state |
|
|
|
result = model(state.next_query) |
|
return State(state.question, |
|
state.history + "\nIntermediate answer: " + result + "\n") |
|
|
|
def selfask(question): |
|
state = State(question) |
|
for i in range(3): |
|
state = self_ask(state) |
|
state = google(state) |
|
return state |
|
|
|
|
|
|
|
gradio = show(selfask, |
|
examples=["What is the zip code of the city where George Washington was born?"], |
|
subprompts=[self_ask, google] * 3, |
|
description=desc, |
|
code=open("selfask.py", "r").read().split("$")[1].strip().strip("#").strip(), |
|
out_type="json" |
|
) |
|
if __name__ == "__main__": |
|
gradio.launch() |
|
|
|
|
|
|
