Decoder

Making Decisions

Making choices and decisions is a core part of any intelligence system, and we wanted to make that as easy as possible. The decoder service (accessible via Bot().llm.decoder) can be used to make decisions or navigate choices with minimal configuration or code.

Basic Decoder

Here is a simple example of how to use the decoder to return the family of an animal. The decoder uses a prompt, keys description, and keys/values mapping to make decisions.

from dandy import Bot

bot = Bot()

keys_description = 'Animal Sounds'
keys_values = {
    'barking': 'dog',
    'meowing': 'cat',
    'quacking': 'duck'
}

animal_family = bot.llm.decoder.prompt_to_value(
    prompt='I was out on a walk and heard some barking',
    keys_description=keys_description,
    keys_values=keys_values
)

print(animal_family)

dog

Multiple Values

You can also request multiple values to be returned using prompt_to_values with max_return_values:

from dandy import Bot

bot = Bot()

keys_description = 'Activities'
keys_values = {
    'running': 'Sports',
    'reading': 'Learning',
    'coding': 'Technology',
    'painting': 'Art'
}

activities = bot.llm.decoder.prompt_to_values(
    prompt='I like running, reading books, and coding on my computer',
    keys_description=keys_description,
    keys_values=keys_values,
    max_return_values=3
)

for activity in activities:
    print(activity)

Sports Learning Technology

Note

The decoder's keys_values dictionary can contain any type of object as values, allowing you to map to complex objects, not just strings.