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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "8eccacc7",
"metadata": {},
"outputs": [],
"source": [
"!pip install -q git+https://github.com/srush/MiniChain\n",
"!git clone https://github.com/srush/MiniChain; cp -fr MiniChain/examples/* . "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ebfe63f6",
"metadata": {
"lines_to_next_cell": 2,
"tags": [
"hide_inp"
]
},
"outputs": [],
"source": [
"\n",
"desc = \"\"\"\n",
"### Named Entity Recognition\n",
"\n",
"Chain that does named entity recognition with arbitrary labels. [](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/ner.ipynb)\n",
"\n",
"(Adapted from [promptify](https://github.com/promptslab/Promptify/blob/main/promptify/prompts/nlp/templates/ner.jinja)).\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45dd8a11",
"metadata": {
"lines_to_next_cell": 1
},
"outputs": [],
"source": [
"from minichain import prompt, show, OpenAI"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9ada6ebb",
"metadata": {
"lines_to_next_cell": 1
},
"outputs": [],
"source": [
"@prompt(OpenAI(), template_file = \"ner.pmpt.tpl\", parser=\"json\")\n",
"def ner_extract(model, kwargs):\n",
" return model(kwargs)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f6873c42",
"metadata": {},
"outputs": [],
"source": [
"@prompt(OpenAI())\n",
"def team_describe(model, inp):\n",
" query = \"Can you describe these basketball teams? \" + \\\n",
" \" \".join([i[\"E\"] for i in inp if i[\"T\"] ==\"Team\"])\n",
" return model(query)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a89fa41d",
"metadata": {},
"outputs": [],
"source": [
"def ner(text_input, labels, domain):\n",
" extract = ner_extract(dict(text_input=text_input, labels=labels, domain=domain))\n",
" return team_describe(extract)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3e8a0502",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "634fb50b",
"metadata": {},
"outputs": [],
"source": [
"gradio = show(ner,\n",
" 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\"]],\n",
" description=desc,\n",
" subprompts=[ner_extract, team_describe],\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fa353224",
"metadata": {},
"outputs": [],
"source": [
"if __name__ == \"__main__\":\n",
" gradio.launch()"
]
}
],
"metadata": {
"jupytext": {
"cell_metadata_filter": "tags,-all",
"main_language": "python",
"notebook_metadata_filter": "-all"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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