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# + tags=["hide_inp"]
desc = """
### Named Entity Recognition
Chain that does named entity recognition with arbitrary labels. [](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/ner.ipynb)
(Adapted from [promptify](https://github.com/promptslab/Promptify/blob/main/promptify/prompts/nlp/templates/ner.jinja)).
"""
# -
# $
from minichain import prompt, transform, show, OpenAI
import json
@prompt(OpenAI(), template_file = "ner.pmpt.tpl")
def ner_extract(model, kwargs):
return model(kwargs)
@transform()
def to_json(chat_output):
return json.loads(chat_output)
@prompt(OpenAI())
def team_describe(model, inp):
query = "Can you describe these basketball teams? " + \
" ".join([i["E"] for i in inp if i["T"] =="Team"])
return model(query)
def ner(text_input, labels, domain):
extract = to_json(ner_extract(dict(text_input=text_input, labels=labels, domain=domain)))
return team_describe(extract)
# $
gradio = show(ner,
examples=[["An NBA playoff pairing a year ago, the 76ers (39-20) meet the Miami Heat (32-29) for the first time this season on Monday night at home.", "Team, Date", "Sports"]],
description=desc,
subprompts=[ner_extract, team_describe],
code=open("ner.py", "r").read().split("$")[1].strip().strip("#").strip(),
)
if __name__ == "__main__":
gradio.queue().launch()
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