Prompts
Prompt vs String
We recommend using our Prompt class to create prompts as it provides a lot of extra features and capabilities over a simple string.
The main advantage to this is that as feature and formatting improves over time for AI models, you can ensure that your project is using consistent formatting.
Creating a Prompt
Creating a new prompt is simple and can be done multiple ways each have their own pros and cons.
Structured Style Prompt
this method is the best for creating prompts that are complex and can be statically typed.
from dandy import Prompt
prompt = (
Prompt()
.title('Car Generator')
.line_break()
.heading('Instructions')
.text('I would like you to create me a new type of car.')
.line_break()
.heading('Rules')
.list([
'The car should be fast',
'The car should be safe',
'The car should be fun to drive',
])
)
print(prompt.to_str())
Dynamic Style Prompt
This method is the best for creating prompts that are complex or need to have things injected into them.
from dandy import Prompt
CAR_RULES = [
'The car should be fast',
'The car should be safe',
'The car should be fun to drive',
]
prompt = Prompt()
prompt.title('Car Generator')
prompt.line_break()
prompt.heading('Instructions')
prompt.text('I would like you to create me a new type of car.')
prompt.line_break()
prompt.heading('Rules')
prompt.list(CAR_RULES)
print(prompt.to_str())
String Style Prompt
This method is the best for creating prompts that are simple and do not need structured formatting.
from dandy import Prompt
prompt = Prompt("""
# Car Generator
## Instructions
I would like you to create me a new type of car.
## Rules
- The car should be fast
- The car should be safe
- The car should be fun to drive
""")
print(prompt.to_str())
Prompt Formatting
There is lots of different types of formatting that can be used to create prompts.
from dandy import Prompt, BaseIntel
class PersonIntel(BaseIntel):
name: str
age: int
person_intel = PersonIntel(name='John', age=30)
another_prompt = (
Prompt()
.text('Hello from another prompt')
)
new_prompt = (
Prompt()
.dict(dictionary={'key': 'value'})
.divider()
.array(items=['item1', 'item2'])
.array_random_order(items=['item1', 'item2'])
.file(file_path='docs/tutorials/prompt_test_document.md')
.heading(heading='Heading Followed by a line break')
.line_break()
.list(items=['item1 after a line break', 'item2'])
.intel(intel=person_intel)
.intel_schema(intel_class=PersonIntel)
.module_source(module_name='dandy.processor.bot.bot')
.object_source(object_module_name='dandy.processor.bot.bot.Bot')
.ordered_list(items=['item1', 'item2'])
.prompt(prompt=another_prompt)
.random_choice(choices=['choice1', 'choice2'])
.sub_heading(sub_heading='Sub Heading')
.text('Hello World')
.title(title='Title')
.unordered_list(items=['item1', 'item2'])
.unordered_random_list(items=['item1', 'item2'])
)
print(new_prompt.to_str())
{
"key": "value"
}
----------
[
"item1",
"item2"
]
[
"item1",
"item2"
]
# Hello From the Prompt Information Test File
Hello World in the test file
## Heading Followed by a line break
- item1 after a line break
- item2
{
"name": "John",
"age": 30
}
{
"properties": {
"name": {
"title": "Name",
"type": "string"
},
"age": {
"title": "Age",
"type": "integer"
}
},
"required": [
"name",
"age"
],
"title": "PersonIntel",
"type": "object"
}
""" dandy.processor.bot.bot
from dataclasses import dataclass
from typing import ClassVar
from dandy import BaseIntel
from dandy.http.mixin import HttpProcessorMixin
from dandy.intel.typing import IntelType
from dandy.llm.mixin import LlmProcessorMixin
from dandy.llm.prompt.typing import PromptOrStr
from dandy.processor.bot.service import BotService
from dandy.processor.processor import BaseProcessor
from dandy.vision.mixin import VisionProcessorMixin
@dataclass(kw_only=True)
class Bot(
BaseProcessor,
LlmProcessorMixin,
HttpProcessorMixin,
VisionProcessorMixin,
):
services: ClassVar[BotService] = BotService()
description = 'Base Dandy Bot Class That Can Do Anything'
def process(
self,
prompt: PromptOrStr,
intel_class: type[IntelType] | None = None,
) -> IntelType:
return self.llm.prompt_to_intel(
prompt=prompt,
intel_class=intel_class,
)
"""
""" dandy.processor.bot.bot.Bot
@dataclass(kw_only=True)
class Bot(
BaseProcessor,
LlmProcessorMixin,
HttpProcessorMixin,
VisionProcessorMixin,
):
services: ClassVar[BotService] = BotService()
description = 'Base Dandy Bot Class That Can Do Anything'
def process(
self,
prompt: PromptOrStr,
intel_class: type[IntelType] | None = None,
) -> IntelType:
return self.llm.prompt_to_intel(
prompt=prompt,
intel_class=intel_class,
)
"""
1. item1
2. item2
Hello from another prompt
choice1
### Sub Heading
Hello World
# Title
- item1
- item2
- item1
- item2
Tip
Check out the API Reference API documentation for more information on all the possibilities.
Advanced Prompts
Let's make a function that returns a dynamically constructed prompt based on the function arguments.