A collection of prompt templates for language models
- Classic templates formats for different models
- Easily modify and adapt templates on-the-fly
- Few shots and conversation history support
📚 Api doc
npm install modprompt
# or
yarn add modprompt
List the available templates:
import { templates } from "modprompt";
const templateNames = Object.keys(templates);
console.log(templateNames);
To load a template:
import { templates, PromptTemplate } from "modprompt";
const tpl = new PromptTemplate(templates.alpaca)
// or
const tpl = new PromptTemplate("alpaca")
To render a template to string:
const templateText = tpl.render();
Rendering for an Alpaca template:
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
Similar to the render
function above, but replaces {prompt}
by the provided text:
const templateText = tpl.prompt("What is the capital of Kenya?");
The template have system messages support if the original template supports it.
To replace a system message:
tpl.replaceSystem("You are a javascript specialist");
Rendering for an Alpaca template:
You are a javascript specialist
### Instruction:
{prompt}
### Response:
To append to a system message:
tpl.afterSystem("You are a javascript specialist");
Note: some templates does have a system schema but no default system message. Some templates
don't even have a system block. The default render
will show the system schema: exemple for the Vicuna system template:
SYSTEM: {system}
USER: {prompt}
### ASSISTANT:
In case of empty system message it is possible to skip it using the
skip_empty_system
option: outptut of tpl.render(true)
:
USER: {prompt}
### ASSISTANT:
The templates have support for example shots. Add one shot:
tpl.addShot(
"fix this invalid json:\n\n```json\n{'a':1,}\n```",
'\n\n```json\n{"a":1}\n```\n',
)
The first param is the user question, and the second is the assistant response. It is assembled in a prompt template. Example with custom user and assistant messages:
// modify system message
tpl.afterSystem("You are a javascript specialist");
// modify assistant message
tpl.afterAssistant(" (answer in valid json)")
// modify the prompt message
tpl.replacePrompt("fix this invalid json:\n\n```json\n{prompt}\n```")
// add a one shot example
tpl.addShot(
"{'a':1,}",
'\n\n```json\n{"a":1}\n```\n',
)
Rendering for an Alpaca template:
Below is an instruction that describes a task. Write a response that appropriately completes the request. You are a javascript specialist
### Instruction:
fix this invalid json:
'''json
{'a':1,}
'''
### Response: (answer in valid json)
'''json
{"a":1}
'''
### Instruction:
fix this invalid json:
'''json
{prompt}
'''
### Response: (answer in valid json)
The calls can be chained. Example with the code above:
const tpl = new PromptTemplate(templates.llama)
.afterSystem("You are a javascript specialist")
.afterAssistant(" (answer in valid json)")
.replacePrompt("fix this invalid json:\n\n```json\n{prompt}\n```")
.addShot(
"{'a':1,}",
'\n\n```json\n{"a":1}\n```\n',
);
Template types:
interface SpacingSlots {
system?: number;
user?: number;
assistant?: number;
}
interface PromptBlock {
schema: string;
message?: string;
}
interface TurnBlock {
user: string;
assistant: string;
}
interface LmTemplate {
name: string;
user: string;
assistant: string;
system?: PromptBlock;
shots?: Array<TurnBlock>;
stop?: Array<string>;
linebreaks?: SpacingSlots;
}
Example raw template:
import type { LmTemplate } from "modprompt";
const orca: LmTemplate = {
"name": "Orca",
"system": {
"schema": "### System:\n{system}",
"message": "You are an AI assistant that follows instruction extremely well. Help as much as you can.",
},
"user": "### User:\n{prompt}",
"assistant": "### Response:",
"linebreaks": {
"system": 2,
"user": 2
}
}
📚 Api doc