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Fix Document & Expose StringPromptTemplate as a custom-prompt-template. (#1753)

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Regarding [this
issue](https://github.com/hwchase17/langchain/issues/1754), the code in
the document [Creating a custom prompt
template](https://langchain.readthedocs.io/en/latest/modules/prompts/examples/custom_prompt_template.html)
is no longer functional and outdated.

To address this, I have made the following changes:

1. Updated the guide in the document to use `StringPromptTemplate`
instead of `BasePromptTemplate`.
2. Exposed `StringPromptTemplate` in `prompts/__init__.py` for easier
importing.
This commit is contained in:
hitoshi44 2023-03-20 01:47:56 +09:00 committed by GitHub
parent e635c86145
commit 3cf493b089
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2 changed files with 11 additions and 9 deletions
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17
docs/modules/prompts/examples/custom_prompt_template.ipynb
View File

@ -21,16 +21,17 @@
"id": "5d56ce86",
"metadata": {},
"source": [
"## Create a custom prompt template\n",
"## Creating a Custom Prompt Template\n",
"\n",
"The only two requirements for all prompt templates are:\n",
"There are essentially two distinct prompt templates available - string prompt templates and chat prompt templates. String prompt templates provides a simple prompt in string format, while chat prompt templates produces a more structured prompt to be used with a chat API.\n",
"\n",
"1. They have a input_variables attribute that exposes what input variables this prompt template expects.\n",
"2. They expose a format method which takes in keyword arguments corresponding to the expected input_variables and returns the formatted prompt.\n",
"In this guide, we will create a custom prompt using a string prompt template. \n",
"\n",
"Let's create a custom prompt template that takes in the function name as input, and formats the prompt template to provide the source code of the function.\n",
"To create a custom string prompt template, there are two requirements:\n",
"1. It has an input_variables attribute that exposes what input variables the prompt template expects.\n",
"2. It exposes a format method that takes in keyword arguments corresponding to the expected input_variables and returns the formatted prompt.\n",
"\n",
"First, let's create a function that will return the source code of a function given its name."
"We will create a custom prompt template that takes in the function name as input and formats the prompt to provide the source code of the function. To achieve this, let's first create a function that will return the source code of a function given its name."
]
},
{
@ -62,11 +63,11 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import BasePromptTemplate\n",
"from langchain.prompts import StringPromptTemplate\n",
"from pydantic import BaseModel, validator\n",
"\n",
"\n",
"class FunctionExplainerPromptTemplate(BasePromptTemplate, BaseModel):\n",
"class FunctionExplainerPromptTemplate(StringPromptTemplate, BaseModel):\n",
" \"\"\" A custom prompt template that takes in the function name as input, and formats the prompt template to provide the source code of the function. \"\"\"\n",
"\n",
" @validator(\"input_variables\")\n",

3
langchain/prompts/__init__.py
View File

@ -1,5 +1,5 @@
"""Prompt template classes."""
from langchain.prompts.base import BasePromptTemplate
from langchain.prompts.base import BasePromptTemplate, StringPromptTemplate
from langchain.prompts.chat import (
AIMessagePromptTemplate,
ChatMessagePromptTemplate,
@ -15,6 +15,7 @@ from langchain.prompts.prompt import Prompt, PromptTemplate
__all__ = [
"BasePromptTemplate",
"StringPromptTemplate",
"load_prompt",
"PromptTemplate",
"FewShotPromptTemplate",