In [ ]:

In [1]:

desc = """
### Typed Extraction

Information extraction that is automatically generated from a typed specification. [[Code](https://github.com/srush/MiniChain/blob/main/examples/stats.py)]

(Novel to MiniChain)
"""

desc = """ ### Typed Extraction Information extraction that is automatically generated from a typed specification. [[Code](https://github.com/srush/MiniChain/blob/main/examples/stats.py)] (Novel to MiniChain) """

$

In [2]:

from minichain import prompt, show, type_to_prompt, OpenAI
from dataclasses import dataclass
from typing import List
from enum import Enum

from minichain import prompt, show, type_to_prompt, OpenAI from dataclasses import dataclass from typing import List from enum import Enum

Data specification

In [3]:

class StatType(Enum):
    POINTS = 1
    REBOUNDS = 2
    ASSISTS = 3

@dataclass
class Stat:
    value: int
    stat: StatType

@dataclass
class Player:
    player: str
    stats: List[Stat]

class StatType(Enum): POINTS = 1 REBOUNDS = 2 ASSISTS = 3 @dataclass class Stat: value: int stat: StatType @dataclass class Player: player: str stats: List[Stat]

In [4]:

@prompt(OpenAI(), template_file="stats.pmpt.tpl", parser="json")
def stats(model, passage):
    out = model(dict(passage=passage, typ=type_to_prompt(Player)))
    return [Player(**j) for j in out]

@prompt(OpenAI(), template_file="stats.pmpt.tpl", parser="json") def stats(model, passage): out = model(dict(passage=passage, typ=type_to_prompt(Player))) return [Player(**j) for j in out]

$

In [5]:

article = open("sixers.txt").read()
gradio = show(lambda passage: stats(passage),
              examples=[article],
              subprompts=[stats],
              out_type="json",
              description=desc,
              code=open("stats.py", "r").read().split("$")[1].strip().strip("#").strip(),
)
if __name__ == "__main__":
    gradio.launch()

article = open("sixers.txt").read() gradio = show(lambda passage: stats(passage), examples=[article], subprompts=[stats], out_type="json", description=desc, code=open("stats.py", "r").read().split("$")[1].strip().strip("#").strip(), ) if __name__ == "__main__": gradio.launch()

Running on local URL:  http://127.0.0.1:7861

To create a public link, set `share=True` in `launch()`.

ExtractionPrompt().show({"passage": "Harden had 10 rebounds."}, '[{"player": "Harden", "stats": {"value": 10, "stat": 2}}]')

View the run log.¶

minichain.show_log("bash.log")