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117 lines
2.8 KiB
Plaintext
117 lines
2.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "a37d9694",
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"metadata": {},
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"source": [
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"# Custom Prompt Template\n",
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"\n",
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"This notebook goes over how to create a custom prompt template, in case you want to create your own methodology for creating prompts.\n",
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"\n",
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"The only two requirements for all prompt templates are:\n",
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"\n",
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"1. They have a `input_variables` attribute that exposes what input variables this prompt template expects.\n",
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"2. They expose a `format` method which takes in keyword arguments corresponding to the expected `input_variables` and returns the formatted prompt.\n",
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"\n",
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"Let's imagine that we want to create a prompt template that takes in input variables and formats them into the template AFTER capitalizing them. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "26f796e5",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.prompts import BasePromptTemplate\n",
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"from pydantic import BaseModel"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "27919e96",
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"metadata": {},
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"outputs": [],
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"source": [
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"class CustomPromptTemplate(BasePromptTemplate, BaseModel):\n",
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" template: str\n",
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" \n",
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" def format(self, **kwargs) -> str:\n",
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" capitalized_kwargs = {k: v.upper() for k, v in kwargs.items()}\n",
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" return self.template.format(**capitalized_kwargs)\n",
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" "
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]
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},
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{
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"cell_type": "markdown",
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"id": "76d1d84d",
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"metadata": {},
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"source": [
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"We can now see that when we use this, the input variables get formatted."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "eed1ff28",
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"metadata": {},
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"outputs": [],
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"source": [
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"prompt = CustomPromptTemplate(input_variables=[\"foo\"], template=\"Capitalized: {foo}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "94892a3c",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'Capitalized: LOWERCASE'"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"prompt.format(foo=\"lowercase\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d3d9a7c7",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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